Medicine, Faculty of
DSpace
UBCV
Levesque, Dominique Louise
Master of Science - MSc
University of British Columbia
Lithium is an effective treatment for bipolar disorder (BD) as it reduces the occurrence of mania, which is associated with deficits in impulse control, pathological gambling, drug-seeking, and suicidality. Whether lithium regulates impulsivity directly is unclear. We determined the effects of chronic lithium administration on performance of the five-choice serial reaction time task (5-CSRTT)—a rodent analogue of the continuous performance test used clinically—and the delay discounting task (DDT), as well as its influence on drug-induced behaviours. In the 5-CSRTT, animals respond to a brief visual stimulus to earn a reward. Accuracy of target detection measures attentional ability whilst responses made prior to stimulus presentation provide an index of motor impulsivity. The DDT measures impulsive choice by assessing animals' tendency to choose smaller, immediate food rewards over larger, delayed rewards. Lithium treatment improved target detection and attenuated stress-induced impulsive responding. There were no differences between the groups on the initial delay discounting task—animals abruptly shifted their preference towards the smaller reward as the larger reward became increasingly delayed. We re-trained these animals using shorter delays to obtain a more meaningful discounting pattern. Lithium treatment facilitated behavioural flexibility as rats adapted this change more rapidly, and animals displayed a consistent pattern of choice between both delay sets. We trained another cohort of animals using the shorter delays only. Again, lithium treatment accelerated task acquisition, but did not affect choice behaviour. Lithium treatment blocked stimulant-induced changes in choice behaviour. Real-time PCR analyses revealed that lithium treatment decreased gene expression in the prefrontal cortex and nucleus accumbens. Notable changes were detected in intracellular components and neuronal processes associated with a behavioural and cognitive profile relevant to BD and other impulse control disorders, including monoaminergic receptors, neurotrophins, synaptic proteins, signalling kinases, and transcription and apoptotic factors, to name a few. Results generated herein suggest that chronic lithium treatment may enhance attention, attenuate stress-induced motor impulsivity, accelerate task acquisition, enhance behavioural flexibility, and block stimulant-induced changes in choice behaviour. These findings contribute to our understanding of lithium’s clinical efficacy and may lead to better treatments for BD and other impulse-control disorders.
CHRONIC LITHIUM TREATMENT INFLUENCES IMPULSE CONTROL AND COGNITION AND REGULATES GENE EXPRESSION by Dominique Louise Levesque B.Sc., University of Ottawa, 2009 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in The Faculty of Graduate and Postdoctoral Studies (Neuroscience) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) November 2013 ? Dominique Louise Levesque, 2013 ii Abstract Lithium is an effective treatment for bipolar disorder (BD) as it reduces the occurrence of mania, which is associated with deficits in impulse control, pathological gambling, drug-seeking, and suicidality. Whether lithium regulates impulsivity directly is unclear. We determined the effects of chronic lithium administration on performance of the five-choice serial reaction time task (5-CSRTT)?a rodent analogue of the continuous performance test used clinically?and the delay discounting task (DDT), as well as its influence on drug-induced behaviours. In the 5-CSRTT, animals respond to a brief visual stimulus to earn a reward. Accuracy of target detection measures attentional ability whilst responses made prior to stimulus presentation provide an index of motor impulsivity. The DDT measures impulsive choice by assessing animals' tendency to choose smaller, immediate food rewards over larger, delayed rewards. Lithium treatment improved target detection and attenuated stress-induced impulsive responding. There were no differences between the groups on the initial delay discounting task?animals abruptly shifted their preference towards the smaller reward as the larger reward became increasingly delayed. We re-trained these animals using shorter delays to obtain a more meaningful discounting pattern. Lithium treatment facilitated behavioural flexibility as rats adapted this change more rapidly, and animals displayed a consistent pattern of choice between both delay sets. We trained another cohort of animals using the shorter delays only. Again, lithium treatment accelerated task acquisition, but did not affect choice behaviour. Lithium treatment blocked stimulant-induced changes in choice behaviour. Real-time PCR analyses revealed that lithium treatment decreased gene expression in the prefrontal cortex and nucleus accumbens. Notable changes were detected in intracellular components and neuronal processes associated with a behavioural and cognitive profile relevant to BD and other impulse control disorders, including monoaminergic receptors, neurotrophins, synaptic proteins, signalling kinases, and transcription and apoptotic factors, to name a few. Results generated herein suggest that chronic lithium treatment may enhance attention, attenuate stress-induced motor impulsivity, accelerate task acquisition, enhance behavioural flexibility, and block stimulant-induced changes in choice behaviour. These findings contribute to our understanding of lithium?s clinical efficacy and may lead to better treatments for BD and other impulse-control disorders. iii Preface Animal testing and housing conditions were in accordance with the Canadian Council of Animal Care, experimental protocols were approved by the Animal Care Committee of the University of British Columbia and analyses of biological specimen were approved by the Vancouver General Hospital (certificate numbers A10-0101 and A10-0283; research number R1058, respectively). iv Table of Contents Abstract ........................................................................................................................................... ii Preface ........................................................................................................................................... iii Table of Contents ............................................................................................................................ iv List of Tables .................................................................................................................................. vii List of Figures ................................................................................................................................ viii Glossary .......................................................................................................................................... ix Acknowledgements .......................................................................................................................... x Dedication ...................................................................................................................................... xi 1 Introduction ................................................................................................................................ 1 1.1 Bipolar Disorder ............................................................................................................................. 1 1.1.1 Characterisation of bipolar disorder ................................................................................. 1 1.1.2 Neuropathophysiology of bipolar disorder ....................................................................... 1 1.1.3 Bipolar disorder and pharmacology .................................................................................. 4 1.2 Impulsivity ...................................................................................................................................... 5 1.2.1 Characterisation and clinical relevance of impulsivity ...................................................... 5 1.2.2 Animal models of impulsivity ............................................................................................ 6 1.2.3 Neurobiology of impulsivity .............................................................................................. 8 1.2.4 Pharmacology and impulsivity ........................................................................................ 11 1.3 Lithium ......................................................................................................................................... 17 1.3.1 Clinical efficacy of lithium treatment .............................................................................. 17 1.3.2 Lithium's mechanisms of action ...................................................................................... 18 2 Methods .................................................................................................................................... 23 2.1 Subjects ........................................................................................................................................ 23 2.2 Lithium Treatment and Feeding Procedure ................................................................................. 23 2.3 Measurement of Serum Lithium Levels ....................................................................................... 24 2.4 Behavioural Apparatus ................................................................................................................. 25 2.5 Behavioural Testing ...................................................................................................................... 27 2.5.1 The five-choice serial reaction time task (5-CSRTT) ........................................................ 27 2.5.2 The delay discounting task (DDT): Experiments 1 and 2 ................................................ 28 2.6 Pharmacological Challenges: D-amphetamine (AMPH) and yohimbine (YHB) ............................ 31 2.7 Tissue Collection .......................................................................................................................... 31 2.7.1 Real-time polymerase chain reaction (qPCR) ................................................................. 32 v 2.8 Data Analyses ............................................................................................................................... 34 2.8.1 General health and baseline behavioural data ............................................................... 34 2.8.2 Pharmacological challenges ............................................................................................ 35 2.8.3 qPCR ................................................................................................................................ 35 3 Results ...................................................................................................................................... 36 3.1 General Health and Serum-Lithium Quantification ..................................................................... 36 3.2 The Five-Choice Serial Reaction Time Task (5-CSRTT) ................................................................. 36 3.2.1 5-CSRTT baseline performance ....................................................................................... 36 3.2.3 Effects of AMPH on 5-CSRTT performance ..................................................................... 38 3.2.3 Effects of YHB on 5-CSRTT performance ......................................................................... 40 3.3 The Delay Discounting Task (DDT) ............................................................................................... 43 3.3.1 Delay discounting Experiment 1: Large vs. short delay sets ........................................... 43 3.3.2 Delay discounting Experiment 2: New cohort with short delay set only ........................ 48 3.3.3 Effects of AMPH on delay discounting performance ...................................................... 52 3.3.4 Effects of YHB on delay discounting performance ......................................................... 55 3.4 Effects of Chronic Lithium Treatment on Gene Expression ......................................................... 58 4 Discussion ................................................................................................................................. 61 4.1 Effects of Chronic Lithium Treatment on the Five-Choice Serial Reaction Time Task (5-CSRTT) 61 4.1.1 Chronic lithium treatment improves attention and performance but does not influence impulsive action .............................................................................................. 61 4.1.2 Chronic lithium treatment does not block AMPH-induced impairments in attention or behavioural control but might influence decisional processing ................................ 65 4.1.3 Chronic lithium treatment blocks YHB-induced impairments in attention and impulsive action and may increase decisional processing .............................................. 66 4.2 Effects of Chronic Lithium Treatment on the Delay Discounting Task (DDT) .............................. 69 4.2.1 Chronic lithium treatment enhances reversal learning and facilitates behavioural flexibility and adaptation ............................................................................ 69 4.2.2 Chronic lithium treatment enhances learning and accelerates task acquisition ............ 70 4.2.3 Chronic lithium treatment may affect the response to AMPH and YHB on the DDT ..... 71 4.3 Effects of Chronic Lithium Treatment on Gene Expression ......................................................... 73 4.4 General Summary ........................................................................................................................ 79 References ..................................................................................................................................... 80 Appendices .................................................................................................................................. 117 Appendix A. 5-CSRTT training parameters ...................................................................................... 117 Appendix B. Schemata showing one trial of the 5-CSRTT ............................................................... 118 vi Appendix C. Flow diagrams of the three training phases of the DDT ............................................. 119 Appendix D. 5-CSRTT baseline behavioural measures .................................................................... 121 Appendix E. 5-CSRTT behavioural measures during AMPH challenge ............................................ 122 Appendix F. 5-CSRTT behavioural measures during YHB challenge ................................................ 123 Appendix G. DDT Experiment 1b (short delay set) baseline behavioural measures ....................... 124 Appendix H. DDT Experiment 2 baseline behavioural measures .................................................... 125 Appendix I. DDT choice of large reward during AMPH challenge .................................................. 126 Appendix J. DDT behavioural measures during AMPH challenge .................................................. 127 Appendix K. DDT choice of large reward during YHB challenge ..................................................... 128 Appendix L. DDT behavioural measures during YHB challenge ...................................................... 129 Appendix M. qPCR analyses: Effects of chronic lithium treatment on mRNA levels within the mPFC, OFC, and the NAc ............................................................................................. 130 vii List of Tables Table 1. Sequence of primers used for qPCR analyses ............................................................ 33 Table 2. Effects of chronic lithium treatment on gene expression in the mPFC, OFC, and the NAc ................................................................................................................ 59 viii List of Figures Figure 1. Diagrams of the five-hole operant chamber .............................................................. 26 Figure 2. Flow diagram showing the trial structure of the 5-CSRTT ......................................... 28 Figure 3. Flow diagram showing a "free choice" trial in the DDT ............................................. 30 Figure 4. Effects of chronic lithium treatment on attention and accuracy of target detection ("correct responses") and motor impulsivity ("prematures") on the 5-CSRTT .......... 37 Figure 5. Effects of chronic lithium treatment on AMPH during the 5-CSRTT .......................... 39 Figure 6. Lithium treatment blocks the effects of YHB on 5-CSRTT performance .................... 42 Figure 7. Delay Discounting Experiment 1a?Large delay set .................................................. 43 Figure 8. Change in choice of large reward when retraining on shorter delay set: Lithium treatment enhances behavioural flexibility .................................................. 45 Figure 9. Delay Discounting Experiment 1: Lithium treatment promotes consistency of choice between long and short delay sets ................................................................. 47 Figure 10. Delay Discounting Experiment 2 (short delay set only)?Training new cohort: Lithium treatment accelerates task acquisition of choice behaviour ........................ 50 Figure 11. Delay Discounting Experiment 2 (short delay set only)?Baseline: Lithium treatment does not influence impulsive choice ........................................... 51 Figure 12. Lithium attenuates the effects of AMPH on delay discounting performance ........... 54 Figure 13. Effects of YHB on delay discounting performance ..................................................... 57 Figure 14. Effects of chronic lithium treatment on mRNA levels within the mPFC, OFC, and the NAc ................................................................................................................ 60 ix Glossary 5-HT1a serotonin receptor subtype 1a 5-HT2a serotonin receptor subtype 2a 5-HT2c serotonin receptor subtype 2c 5-CSRTT five-choice serial reaction time task ?1a-AR AR receptor subtype ?1a ?2a-AR AR receptor subtype ?2a ?1-AR AR receptor subtype ?1 ?2-AR AR receptor subtype ?2 AMPH D-amphetamine AR adrenergic receptor Bcl-2 B-cell lymphoma/leukemia-2 protein BDNF brain-derived neurotrophic factor cdk5 cyclin-dependent kinase 5 c-fos FBR osteogenic sarcoma cell protein CREB cyclic AMP response element-binding protein CSP cysteine string protein D1 dopamine receptor subtype D1 D2 dopamine receptor subtype D2 DDT delay discounting task DSM-IV TR Diagnostic and Statistics Manual IV Text Revised ERK1 extracellular signal-regulated kinase-1 ERK2 extracellular signal-regulated kinase-2 Gsk-3? glycogen synthase kinase-3? M1 muscarinic cholinergic receptor subtype 1 M2 muscarinic cholinergic receptor subtype 2 mPFC medial prefrontal cortex NAc nucleus accumbens NGF nerve growth factor OFC orbitofrontal cortex qPCR real-time polymerase chain reaction PSD-95 postsynaptic density-95 TrkB tropomyosin-related kinase B YHB yohimbine x Acknowledgements Dr. Catharine Winstanley: I am forever thankful to you for welcoming me into your lab as a Graduate Student, for all the wonderful opportunities you gave me, and for the patience and acceptance you have shown me. I admire you greatly, both professionally and personally? I have learned more from you than you will ever know. I extend my full gratitude to the members of my Supervisory Committee, Dr. Alasdair Barr and Dr. Joanne Weinberg. Thank you for your time, feedback, and encouragement; you have been instrumental in shaping this learning experience. Thank you, Dr. Allan Young, for your involvement with this project. Dr. Christian Sch?tz: my work with you has immensely enriched and complemented my graduate experience; thank you for your guidance and for believing in me. I would also like to acknowledge the CIHR and NSERC granting agencies for funding this research, as well as the UBC Faculty of Graduate Studies and College for Interdisciplinary Studies for their travel awards. I could not have asked for better lab-mates. Thank you for your support, camaraderie, and the many laughs we shared. To my family and friends: thank you? not for believing I could accomplish this, but for knowing I would. IV, AC, MWP: the greatest parts of me I owe to you. xi Dedication To Mom, Dad, Agga: You invested as much time and effort as I have, and worked just as hard as I did? if not harder. ?and you still had enough energy to cheer me on. Ceci est pour vous. 1 1 Introduction 1.1 Bipolar Disorder 1.1.1 Characterisation of bipolar disorder Bipolar disorder (BD) is a debilitating psychiatric condition characterised by alternating episodes of mania and depression (American Psychiatric Association [APA], 2000). This mood disorder affects about 3% of the worldwide population and, due to the recurring and severe nature of the illness, BD is among the top ten global burden of disease and leading causes of disability worldwide (Lopez & Murray, 1998; World Health Organization [WHO], 2001). The prevalence of BD is equal for men and women; however, women are more prone to depressive episodes while men are more likely to experience manic episodes (APA, 2000). Typical features of mania include excess mental and physical activity, euphoric and irritable mood, poor judgment, impulsive behaviour, and deficits in several executive functions including sustained attention, working memory, and inhibitory control (Altshuler, Bookheimer, Proenza et al., 2005a; Altshuler, Bookheimer, Townsend et al., 2005b; APA, 2000; Clark & Goodwin, 2004; Clark, Iversen & Goodwin, 2002; Frangou, Donaldson, Adjulis et al., 2005; Grant & Kim, 2003; Mann, Brent & Arango, 2001; McElroy, Pope, Keck et al., 1996; Moeller, Barrat, Dougherty et al., 2001a; Swann, 2009; Swann, Dougherty, Pazzaglia et al., 2004; Swann, Lijffit, Lane et al., 2009a,b), all of which may worsen after repeated manic episodes (Clark & Goodwin, 2004; Rubinsztein, Fletcher, Rogers et al., 2001; Swann, 2009; Swann, Anderson, Dougherty & Moeller, 2001; Swann, Dougherty, Pazzaglia et al., 2005b ; Swann, Pazzaglia, Nicholls et al., 2003; Swann et al., 2009a). Although the diagnostic and clinical features of BD are well established, the illness's precise neurobiological correlates have yet to be fully identified. Decades of investigating potential vulnerability markers of BD have provided indispensable clues on the role of neurochemicals, cellular signalling, and neural networks that might underlie the pathophysiology of BD. Interestingly, much of what we know of BD comes from studies investigating the efficacy of medical treatments, which provide invaluable information regarding the neuropathology of BD. 1.1.2 Neuropathophysiology of bipolar disorder Neuronal Health and Survival Bipolar disorder is generally classified as a neurochemical disorder, characterised in part by compromised cellular integrity, disrupted neural circuitry, and by suboptimal neurotransmission (Ferrier, Ferrie & Macritchie, 2006; Kato & Kato, 2000; Gray, Zhou, Jing et al., 2003; Young, 2009). Neurotrophins 2 and signalling molecules may play a role in the underlying aetiology of BD due to their vast effects on the adult nervous system, including mediating gene expression; cell differentiation and cell proliferation; neurotransmission; synaptic plasticity; and cell death and survival (Benmansour, Deltheil, Piotrowski et al., 2008; Denton & Tavare, 1995; Hempstead, Rabin, Kaplan et al., 1992; Lien, Flaisher-Grinberg, Cleary et al., 2008; McAllister, Katz & Lo, 1999; Pullarkat, Mysels, Tan & Cowen, 1998; Russell, 1995; Russell & Duman, 2002; Shaltiel, Chen & Manji, 2007). In turn, these processes determine the efficacy of the neural connections and circuits in which they are involved. Thus, neurotrophic factors and signalling molecules set up the foundation for and maintain the efficiency of higher-order functions such as learning, memory, executive functioning, and behaviour (Russell, 1995; Russell & Duman, 2002). For example, BD is associated with altered levels of neurotrophins BDNF (brain-derived neurotrophic factor) and for Bcl-2 (B-cell lymphoma line 2). In both humans and animals, these abnormalities lead to aggressive behaviour, hyperactivity, hyperphagia, increased reward seeking, amphetamine sensitization, and deficits in memory tasks and other higher-order behaviours that have clinical correlates to psychiatric disorders (Cunha, Frey, Andreazza et al., 2006; Lien et al., 2008; Machado-Vieira, Dietrich, Leke et al., 2007). Neurotoxicity in BD is also linked to the pro-apoptotic factor GSK-3? (glycogen synthase kinase-3?) (Chiu & Chuang, 2011; Jope, 2011; Jord?, Verdaguer, Canudas et al., 2005; Tyagarajana, Ghosha, Y?venesa et al., 2010). This enzyme prevents neurotrophic expression, neurotrophin-mediated signalling, and neuroplasticity, and plays a role in glutamate-induced excitotoxicity (Grimes & Jope, 2001) as well as neuronal membrane fragmentation (Tyagarajana et al., 2010). Thus, further characterising these factors and their interaction may shed light on the pathophysiology underlying psychiatric disorders such as BD. Neuroanatomy and Neurocircuitry Abnormalities with neurotrophins and other intracellular factors may compromise neuronal health, which in turn can lead to deficiencies within neural circuits that control higher-order functions (Cunha et al., 2006; Kato & Kato, 2000; Lien et al., 2008; Machado-Vieira et al., 2007; Russell, 1995; Russell & Duman, 2002). To this end, several neurofunctional irregularities are associated with BD, including atypical brain activity during resting state and during tasks involving response inhibition, decision-making, and cognitive control. For example, structures in frontosubcortical brain pathways underlie attentional performance (Posner & Peterson, 1990) and are normally active when performing tasks that involve vigilance and response inhibition (Carter, Braver, Barch et al., 1998). Indeed, impaired attentional functioning in manic patients is correlated with abnormal activation of these circuits (Sax, Strakowski, McElroy et al., 1999). Interestingly, successful motor response inhibition is associated with 3 blunted activity in the nucleus accumbens (NAc) and orbitofrontal cortex (OFC), whereas failed motor inhibition is associated with increased activity in the anterior cingulate cortex (ACC) (Weathers, Stringaris, Deveney et al., 2012). In general though, bipolar euthymic and manic patients performing tasks of sustained attention and response inhibition such as the Go/No go task or the Continuous Performance Task (CPT) (Clark & Goodwin, 2004; Halperin, Wolf, Pascualvaca et al., 1988; Sax et al., 1999; Young, Light, Marston et al., 2009) usually show greater activation in the amygdala, ACC, striatal limbic structures, and the NAc (Altshuler et al., 2005a; Rubinsztein et al., 2001; Strakowski, Adler, Holland et al., 2004; Weathers et al., 2012; Wessa, Houenou, Paillere-Martinot et al., 2007). These patients also show blunted activation in the hippocampus (Hpc), OFC, and other prefrontal areas while performing these types of tasks (Altshuler et al., 2005b; Blumberg, Leung, Skudlarski et al., 2003a; Blumberg, Martin, Kaufman et al., 2003b; Blumberg, Stern, Ricketts et al., 1999; Elliott, Ogilvie, Rubinsztein et al., 2004; Mazzola-Pomietto, Kaladjian, Azorin et al., 2009; Rubinsztein et al., 2001; Sax, Strakowski & Zimmerman, 1999). Disrupted activation or functional connectivity throughout these regions is appropriate considering their role in producing the behaviours that are affected in BD, namely mood regulation, decision-making, reward and goal-directed behaviour, various cognitive and attentional abilities, and impulse-control (Altshuler et al., 2005a,b; Clark & Goodwin, 2004; Clark et al., 2002; Frangou et al., 2005; McElroy et al., 1996; Moeller et al., 2001a; Swann, 2009; Swann et al., 2004, 2005, 2009a,b). Neurotransmission Altered neurotransmitter systems involving noradrenaline (NA), dopamine (DA), and serotonin (5-HT) might also contribute to the pathophysiology of BD. For example, the severity of mania appears to correlate with increased NA activity (Swann, Koslow, Katz et al., 1987; Swann, Secunda, Davis et al., 1983). In the same way, Clark and Goodwin (2004) linked abnormal ascending noradrenergic as well as dopaminergic projections in BD patients with poor sustained attention. Furthermore, blunting DA transporter (DAT) activity in animals produces behavioural features relevant to bipolar mania (Young, Goey, Minassian et al., 2010; Young, van Enkhuizen, Winstanley & Geyer, 2011b), supporting the role of catecholamine neurotransmission in the pathophysiology of BD. In addition, cortical serotonergic neurotransmission appears to be decreased in patients with BD (Nikolaus, Antke & M?ller, 2009), and impaired in BD patients whose death results from suicide (Mann, 2002; Mann, Arango, Marzuk et al., 1989; Mann et al., 2001). Finally, a greater incidence of past mood and substance use disorders is associated with a serotonergic receptor polymorphism (Bjork, Moeller, Dougherty et al., 2002). Taken 4 together, these findings suggest that deficient monoaminergic systems may be implicated in the aetiology of BD. 1.1.3 Bipolar disorder and pharmacology Further insight into the neurochemical abnormalities underlying BD can be gained by pharmacologically manipulating neurotransmitter systems involved in the pathophysiology of BD, and observing whether changes in biology or behaviour resemble the BD phenotype. Amphetamine (AMPH) is a psychomotor stimulant often used to model mania in humans and animals. Amongst several mechanisms of actions, AMPH inhibits monoamine uptake and increases monoamine and cholinergic release from nerve terminals (Azzaro & Rutledge, 1973; Biederman & Faraone, 2002; Boileau, Dagher, Leyton et al., 2006; Consolo, Girotti, Russi et al., 1992; Flemenbaum, 1974; Frey, Martins, Petronilho et al., 2006a; Frey, Valvassori, R?us et al., 2006b; Holmes & Rutledge, 1976; Mandell & Knapp, 1976; Mandel, Leanza, Nilsson & Rosengren, 1994; Sulzer, Sonders, Poulsen & Galli, 2005). The drug exerts its effects primarily by inducing DA efflux through DAT (Sulzer et al., 2005), inhibiting monoamine oxidase activity (Holmes & Rutledge, 1976), reducing presynaptic tryptophan hydroxylase activity (Mandell & Knapp, 1976), and by acting on monoamine synaptic vesicles (Sulzer et al., 2005). The physiological and psychological effects of AMPH parallel the major symptoms of bipolar mania such as increased energy, psychomotor activity, alertness, impulsivity, clear-headedness, feelings of euphoria, increased heart rate and blood pressure, novelty-seeking, and hyperactivity, to name a few (Boileau et al., 2006; Cappeliez & Moore, 1990; Frey et al., 2006b; Jacobs & Silverstone, 1986; Lien et al., 2008; Mamelak, 1978; Vale & Ratcliffe, 1987; van Kammen, Docherty, Marder et al., 1985; van Kammen & Murphy, 1975). Chronically administering high doses of AMPH increases DNA, protein, and lipid oxidative damage (Andreazza, Kauer-Sant?Anna, Frey et al., 2008; Frey et al., 2006b; Tan, Young, Shao et al., 2011; Valvassori, Rezin, Ferreira et al., 2010) that results from mitochondrial dysfunction and oxidative stress (Cochrane, 1991; Valvassori et al., 2010). This damage leads to impairments in signal transduction, structural plasticity, and cellular resilience (Cochrane, 1991) which, as mentioned previously, are disrupted in BD (Benmansour et al., 2008; Denton & Tavare, 1995; Hempstead et al., 1992; Lien et al., 2008; McAllister et al., 1999; Pullarkat et al., 1998; Russell, 1995; Russell & Duman, 2002; Shaltiel et al., 2007). Together, these findings suggest that oxidative stress and cell death might play a role in the illness' pathophysiology (Gould & Einat, 2007; Kasahara, Kubota, Miyauchi et al., 2006; Kato & Kato, 2000; Kato, Kubota & Kasahara, 2007; Kuloglu, Ustundag, Atrnaca et al., 2002; Steckert, Valvassori, Moretti et al., 2010). To this end, the pathophysiology of BD may share common features 5 with AMPH-induced neurotoxicity (Frey et al., 2006a,b; Kuloglu et al., 2002), supporting the use of AMPH to model the neuropathophysiology of mania in humans and animals (Andreazza et al., 2008; Frey et al., 2006a,b; Tan et al., 2011). As previously mentioned, BD is associated with abnormal noradrenergic neurotransmission (Clark & Goodwin, 2004; Mendlewicz, Hirsch, Sevy et al., 1989; Swann et al., 1983, 1987). Yohimbine (YHB), a potent ?2-adrenoceptor (?2-AR) antagonist, increases central NA release, and induces arousal and stress-responses in humans and animals (Cedarbaum & Aghajanian, 1976, 1977; Charney, Heninger & Redmond, 1983; Charney, Heninger & Sternberg, 1982; Sirvi?, J?k?l?, Mazurkiewicz et al., 1993; Swann et al., 1983, 1987, 2005a). Yohimbine increases impulsivity in manic and mixed states of BD (Swann et al., 2001, 2003), and in healthy control subjects (Swann, Birnbaum, Jagar et al., 2005a) when assessed on the CPT and paradigms of delay discounting. YHB increases impulsive responding in an animal model of the CPT (Sun, Green, Theobald et al., 2010) and reinstates drug-seeking?a highly impulsive behaviour (APA, 2000; Moeller et al., 2001a; Moeller, Dougherty, Barratt et al., 2001b; Monterosso, Ehrman, Napier et al., 2001; Swann et al., 2004)? in humans (Krishnan-Sarin, Reynolds, Duhig et al., 2007) and rodents (Dalley, Fryer, Brichard et al., 2007; Shepard, Bossert, Liu & Shaham, 2004). Most importantly, YHB induces mania or hypomania in patients with BD (Price, Charney & Heninger, 1984), which is appropriate considering the positive correlation between NA function and severity of mania (Mendlewicz et al., 1989; Swann et al., 1983, 1987). Together, these findings support the idea that abnormal noradrenergic transmission and impulsivity may underlie certain psychiatric disorders, including BD. 1.2 Impulsivity 1.2.1 Characterisation and clinical relevance of impulsivity Impulsivity can be broadly defined as actions which are poorly conceived, prematurely expressed, and considered risky or inappropriate to the situation. Taking risks and seeking novelty are prime indications of impulsive behaviours and, although impulsivity is a normal human characteristic (Aristotle, 1925, as cited by Cardinal, Winstanley, Robbins & Everitt, 2004; Swann, Bjork, Moeller & Dougherty, 2002), abnormally high levels of impulsivity are expressed as behavioural disinhibition, risky decision-making, poor attentional ability, intolerance to delay of gratification, and as a lack of foresight when making decisions or of consideration for future consequences (Cole & Robbins, 1989; Logan, Schachar & Tannock, 1997; Winstanley, Zeeb, Bedard et al., 2010; Zeeb, Floresco & Winstanley, 2010). If 6 left unmanaged, these impulsive tendencies could further develop into such maladaptive behaviours as pathological gambling, aggression, violence, drug seeking and abuse, and criminality? all of which are especially pronounced in psychiatric disorders, namely attention-deficit hyperactivity disorder, bipolar mania, psychosis, substance use disorders, personality disorders, obsessive-compulsive and impulse-control disorders (ICDs), self-injurious behaviours, and suicidality, to name a few (APA, 2000; Coccaro, Siever, Klar, et al., 1989; Dougherty, Mathias, Marsh et al., 2004; King, Tenney, Rossi et al., 2003; Lock, Garrett, Beenhakker & Reiss, 2010; Moeller et al., 2001a,b; Monterosso et al., 2001; Paloyelis, Asherson & Kuntsi, 2009; Stein, Zohan & Simeon, 2002; Swann et al., 2004, 2005b, 2009b; Wu, Liao, Lin et al., 2008). The following sub-section describes two well-known and well-validated rodent paradigms used to investigate the behavioural, pharmacological, and physiological bases of impulsivity. 1.2.2 Animal models of impulsivity Two major forms of impulsivity are deficits in behavioural inhibition (impulsive action) and intolerance for delayed gratification or reward (impulsive choice) (Carli, Robbins, Evenden & Everitt, 1983; Evenden & Ryan, 1996; Talpos, Wilkinson & Robbins, 2006). Measures of impulsivity are behaviourally and neurochemically dissociable from each other (Evenden, 1999a,b; Talpos et al., 2006), and are differentially influenced by monoaminergic neurotransmitter systems (Robbins & Everitt, 1995). Accordingly, impulsive behaviour can be manipulated by drug treatments, lesions to brain areas expressing these neurotransmitter systems, and/or by lesions to areas or circuits relevant to impulsivity (Carli et al., 1983; Dougherty et al., 2004; Mathias, Marsh & Dougherty, 2002; Navarra, Graf, Huang et al., 2008; Robbins, 2002; Swann et al., 2005a; Talpos et al., 2006). In this way, animal models are indispensible for investigating the neurobiological bases of impulsive behaviour and identifying its role in generating behaviours or symptoms relevant to psychiatric disorders such as bipolar mania. The 5-CSRTT and Impulsive Action Impulsive action, also referred to as motor impulsivity or behavioural disinhibition, is broadly defined as the inability to withhold from making a prepotent motor response (Carli et al., 1983; Mar & Robbins, 2007; Robbins, 2002). This type of impulsivity is successfully assessed in humans using the Continuous Performance Task (CPT), which also measures attention and working memory (Clark & Goodwin, 2004; Halperin et al., 1988; Sax et al., 1999; Young et al., 2009). Subjects performing the CPT attend to a series of 5-digit numbers on a computer screen and must respond (mouse click) when a sequence matches a target sequence. Correct detections provide a measure of attention and motivation, while responding to a sequence that differs from the target by a single digit is scored as a 7 commission error. Commission errors are responses made before fully assessing the stimulus, and provide a measure of rapid-response impulsivity (Dougherty et al., 2004; Swann et al., 2002). A very well-established animal model of the CPT is the five-choice serial reaction time task (5-CSRTT), which is the most widely used paradigm to measure this type of impulsivity (Carli et al., 1983; Higgins & Breysse, 2008; Pattij & Vanderschuren, 2008; Robbins, 2002; Talpos et al., 2006; Winstanley, 2011). The 5-CSRTT also provides relatively independent measures of visuospatial attention, motivation, and speed of responding, thus can functionally dissociate attentional processes and impulsive motor activity (Carli & Samanin, 1992). The 5-CSRTT is performed in a five-hole operant chamber, where animals attend to the apertures and wait for a stimulus light briefly illuminates one of five holes. Animals learn to make a nose-poke response (head entry) into the illuminated hole to receive a food reward. Responses made before the stimulus light is presented are scored as premature response (Carli et al., 1983). Premature responses provide a measure of motor impulsivity and are analogous to commission errors on the CPT (Dougherty et al., 2004; Mathias et al., 2002; Swann et al., 2005a; Winstanley, 2011; Young et al., 2009). Elevated commission error rates on the CPT are associated with an increased risk for impulsive behaviour and psychopathology (Dougherty et al., 2000, 2004; Moeller et al., 2004; Swann et al., 2002, 2003, 2004), and are exacerbated following pharmacological manipulations known to increase impulsive behaviour (Dougherty et al., 2000; 2004; Mathias et al., 2002; Swann et al., 2002, 2003, 2005a). Interestingly, drugs that increase commission errors on the CPT, including drugs that affect the noradrenergic system (Dougherty et al., 2004; Mathias et al., 2002; Swann et al., 2002, 2003, 2005a), also induce premature responses on the 5-CSRTT (Winstanley, 2011). This type of impulsivity is a defining feature of ICDs and many psychiatric conditions including mania (Strakowski, Fleck, DelBello et al., 2009; Swann et al., 2002, 2005a,b). In fact, two fundamental markers of BD are impaired target detection and increased impulsive responding on the CPT (Swann et al., 2003). Considering this relationship, the 5-CSRTT is an appropriate animal model to explore the behavioural, neurological, and pharmacological aspects of impulsivity that may be implicated in the pathophysiology of BD mania and other ICDs. Delay Discounting Task (DDT) and Impulsive Choice Another major form of impulsivity is impulsive choice, or delay discounting. Human and animal delay discounting tasks (DDTs) assess tolerance to a delayed reward by measuring subjects' tendency to favour and choose smaller, immediate rewards instead of larger, delayed rewards over a certain period of time, and this tendency is considered impulsive (Ainslie, 1975; Evenden & Ryan, 1996; Monterosso & 8 Ainslie, 1999). As such, elevated discounting rates are characteristic of several psychiatric conditions associated with highly impulsive behaviours, such as BD (Strakowski et al., 2009; Swann et al., 2009a), disruptive behavioural problems (Swann et al., 2002), personality disorders, and ICDs (APA, 2000; Bickel, Yi, Landes et al., 2011; Moeller et al., 2001a; Monterosso et al., 2001). Thus, by modelling this key psychiatric feature, animal DDTs are instruments for investigating and broadening our knowledge of the neurobiological and pharmacological bases of tolerance to delayed gratification inherent in psychiatric disorders prominent in impulsive choice (Evenden & Ryan, 1996; King et al., 2003). Significance to Present Study Impulsive behaviour is a major characteristic of many psychiatric illnesses, especially BD, and treating these illnesses using medication effectively reduces the occurrence and/or severity of these impulsive behaviours. The study presented herein shows that rodents treated with lithium, a well-known mood stabilizer used for treating BD (see section 1.3 "Lithium" for details), affects performance on the 5-CSRTT and DDT by influencing attention and impulsivity. 1.2.3 Neurobiology of impulsivity In bipolar mania, a more severe course of illness is associated with higher levels of impulsivity, greater deficits in attention, response inhibition, the ability to wait before receiving a large reward, and with medically severe suicide attempts (Swann, 2009; Swann et al., 2001, 2003, 2005a,b, 2009a,b). As a result, BD is often comorbid with other psychiatric disorders, ICDs, personality disorders, pathological gambling, substance abuse, aggression, antisocial behaviour, and suicidality (APA, 2000; Cassidy, Ahearn & Carroll, 2001; Kim, Grant, Eckert et al., 2006; McElroy et al., 1996; Moeller et al., 2001a,b; Swann et al., 2002, 2004, 2005b). Thus, as one might expect, the neurobiology associated with mania is comparable to that which underscores impulsivity. Frontostriatal brain structures play a fundamental role in regulating many aspects of cognition, attention, executive function and behaviour. In particular, response inhibition? withholding a response to certain stimuli?depends on the integrity of limbic and frontostriatal regions (Carter et al., 1998; Simmonds, Pekar & Mostofsky, 2008). In sum, the neuroanatomical correlates of major forms of impulsive behaviour are governed mainly, albeit somewhat differently, by areas of the prefrontal cortex, nucleus accumbens, and amygdala. The Orbitofrontal Cortex (OFC) The OFC is implicated in the rapid learning and unlearning of stimulus-incentive associations, anticipating reinforcer value, and in using this information to guide behaviour (Bechara, Damasio & 9 Damasio, 2000; Bechara, Damasio, Tranel & Damasio, 1997; Miller, 2000; Rolls, 1999, as cited by Davidson, 2002; Winstanley, Theobald, Dalley et al., 2006). The OFC is also responsible for reversal learning (Kehagia, Murray & Robbins, 2010; Rolls, 1999, as cited by Davidson, 2002), behavioural flexibility (Ragozzino, 2007), and for monitoring motor inhibitory processing, hyperactivity, attention, and impulsivity (Barkley, 1994, 1997; Duncan & Owen, 1998; Eagle, Bari & Robbins, 2008; McAlonan & Brown, 2003; Posner & Peterson, 1990; Schneider, Retz, Coogan et al., 2006). Lesions to the OFC decrease impulsive choice in a rodent delay discounting task as animals increase their choice of larger, delayed rewards (Winstanley, Theobald, Cardinal & Robbins, 2004b). On the other hand, OFC lesions increase premature responses in rodent versions of the CPT (Dalley et al., 2007; Winstanley et al., 2010). Lesions to the OFC also impair reversal learning in rats and monkeys (Dias, Robbins & Roberts, 1996; Schoenbaum, Setlow, Nugent et al., 2003), perhaps by reducing interference from salient stimuli (Kehagia, Murray & Robbins, 2010), or by disrupting communication between the OFC and the amygdala (Schoenbaum et al., 2003). In fact, as the OFC provides inhibitory signals to the amygdala, lesions to the OFC might impair performance by disrupting an important inhibitory prefrontal-amygdala circuit (Altshuler et al., 2005b; Cocchi, Bramati, Zalesky et al., 2012; Schoenbaum et al., 2003). Furthermore, these two structures may provide information on the reward's value as they connect to other areas in the limbic corticostriatal loop involved in motivation and reward learning such as the nucleus accumbens (NAc) (Cardinal, Parkinson, Hall & Everitt, 2002). Interactions between the BLA and NAc are also involved in reinforcement and decision-making (King et al., 2003), but also enable stimuli to guide behavior (Cardinal et al., 2002). Thus, the BLA and NAc?independently or within the limbic corticostriatal circuit? are critical for the expression of impulsivity (King et al., 2003), as discussed below. The Nucleus Accumbens (NAc) The NAc divides into the core and shell. These parts are anatomically and functionally distinct and, as such, mediate different aspects of impulsivity and respond differently to pharmacological treatments and surgical procedures known to affect impulsive behaviour. The NAc core in particular is involved in the ability to tolerate delays by assigning and maintaining the subjective value of a reward over the delay period (Cardinal, Pennicott, Sugathapala et al., 2001; Christakou, Robbins & Everitt, 2004). The NAc also modulates attentional performance (Christakou, Robbins & Everitt, 2001, 2004), reward expectation (Schultz, Apicella, Scarnati & Ljungberg, 1992), and motivated responses (Boileau et al., 2006; Cardinal et al., 2002, 2004; Christakou et al., 2004) by adjusting response inhibition according to reinforcement outcome (Christakou et al., 2004). While NAc lesions to both the core and shell 10 decrease premature responding (Cole & Robbins, 1989) and impulsive choice (Acheson, Farrar, Patak et al., 2006; Cardinal et al., 2001; Pothuizen, Jongen-Relo, Feldon & Yee, 2005), selective lesions to the core increase impulsive choice on rodent delay discounting paradigms (Cardinal et al., 2001; Cardinal & Cheung, 2005; Cardinal & Howes, 2005) without affecting premature responding or accuracy of target detection on a continuous performance task (Christakou et al., 2001, 2004). Following AMPH administration, selective lesions to the NAc core potentiate?while lesions to the shell antagonise? AMPH-induced increases in premature responses (Murphy, Robinson, Theobald et al., 2008). Disconnecting the NAc core from the medial prefrontal cortex (mPFC) also increases premature responding (Cardinal et al., 2001; Cardinal & Cheung, 2005; Cardinal & Howes, 2005; Christakou et al., 2001, 2004), which is appropriate considering the mPFC's role in regulating impulsive behaviour. The Medial Prefrontal Cortex (mPFC) In addition to the OFC, the mPFC is another major prefrontal brain structure that regulates impulsivity as well as working memory, attention (Fletcher, Tenn, Sinyard et al., 2007; Jones, 2002; Passetti, Dalley, O?Connell et al., 2000), attentional set-shifting, (Birrell & Brown, 2000; McAlonan & Brown, 2003), and behavioural flexibility (Ragozzino, 2007). To this end, connections between regions of the PFC and striatum are essential for learning and adapting to changing reinforcement contingencies (Kehagia et al., 2010). The mPFC also controls anticipation for future positive or negative consequences (Bechara, Damasio, Damasio & Lee, 1999). Bilateral lesions to the mPFC increase impulsive action and impair accuracy of target detection in rodent continuous performance tasks (Muir, Robbins & Everitt, 1996), while unilateral lesions to the mPFC do not (Christakou et al., 2004). Further, lesions to the mPFC do not affect impulsive choice in a rodent task of delay discounting (Cardinal et al., 2001; Muir et al., 1996). Thus, it might not be damage to the mPFC itself that impacts impulsive choice per se, but rather the communication between the mPFC and other brain regions, such as the NAc, that might be important for governing this aspect of impulsivity (Christakou et al., 2004). Overlapping Neurobiology between Impulsivity and Mania Altogether, prefrontal areas such as the OFC and mPFC and their functional connections to areas like the NAc are necessary to optimise attention and suppress behavioural responses to distracting stimuli. These circuits are also important in regulating choice behaviour influenced by the subjective value of delayed rewards (H?ger, Volz, Gaser et al., 1998; Mazzola-Pomietto et al., 2009). Investigating these relationships provides insight into the underlying neurocircuitry of behavioural disinhibition and intolerance to delayed gratification manifested during PFC-dependent tasks. These findings also maintain that distinct neural circuitries within limbic corticostriatal networks govern attention and two 11 major behavioural expressions of inhibitory regulation?impulsive action and impulsive choice. More importantly, the regions involved in regulating impulsivity parallel the regions associated with the pathophysiology of BD. As discussed in sub-section 1.1.2 "Neuropathophysiology of Bipolar Disorder," poor communication between or disrupted activation in these regions may underlie many symptoms and behaviours that are affected in BD, namely mood regulation, various cognitive and attentional abilities, decision-making, reward and goal-directed behaviour, and impulse-control (Altshuler et al., 2005a,b; Blumberg et al., 1999, 2003a, 2005; Elliott et al., 2004; Mazzola-Pomietto et al., 2009; Rubinsztein et al., 2001; Sax et al., 1999; Strakowski et al., 2004; Weathers et al., 2012; Wessa et al., 2007). Therefore, as impulsivity is such a prominent feature of mania, modeling this endophenotype for research purposes may further characterise this condition's pathology and/or might help determine the efficacy of certain medications (Gould & Einat, 2007). Significance to Present Study The study presented herein investigates the neurobiological actions of chronic lithium treatment and relates these actions to the behavioural performance observed on the 5-CSRTT and DDT. We show that chronic lithium treatment alters gene expression within the mPFC, OFC, and NAc, which are key brain regions implicated in the pathology of BD and in the neuroanatomy of impulse-control and cognitive function. In turn, the biomolecular regulation resulting from lithium treatment might underlie lithium's therapeutic effects on mood, impulsive behaviour, and cognitive dysfunction manifested during bipolar mania, ICDs, and other psychiatric illnesses successfully treated with this mood stabilizer. 1.2.4 Pharmacology and impulsivity The neurobiological properties underlying impulsivity are intricate as several neurochemical mechanisms influence this behaviour (Evenden, 1999b; King et al., 2003). Malfunctioning cortico-striatal monoaminergic systems disrupts communication between regions crucial for executive and motor functions that control attention and response inhibition (King et al., 2003). Given the influence that these neurotransmitter systems have on key symptoms or behaviours relevant to BD, drugs which target these systems should affect these behaviours in a fairly predictable manner. Indeed, manipulating these monoaminergic systems anatomically or pharmacologically affects attention and impulsive behaviour during rodent and human response inhibition tasks (Evenden, 1999a). Serotonin (5-HT) The role of 5-HT in impulsivity is complex as the serotonergic system consists of at least fourteen different receptor subtypes divided into seven receptor families? 5-HT1A, 5-HT1B, 5-HT1C, 5-HT1D, 5-HT2, 12 5-HT3, and 5-HT4 (Glennon, 1990). These receptors are differentially distributed throughout the brain and can either excite or inhibit neural activity (Barnes & Sharp, 1999; Glennon, 1990). As a result, applying selective agonists or antagonists to a particular receptor subtype can produce various effects on overall neural activity and behaviour (Winstanley, 2011). High levels of serotonergic activity are generally associated with behavioural inhibition and choice behaviour on delay discounting paradigms (Evenden, 1998; Winstanley, Dalley, Theobald et al., 2004a,b,c; Puumala & Sirvi?, 1998; Winstanley et al., 2006), such that suboptimal serotonergic transmission in humans may increase the risk or incidence of past mood disorders, substance abuse, and other impulsive behaviors including violence, aggression, and suicide (Bjork et al., 2002; Brown, Ebert, Goyer, et al., 1982; Coccaro et al., 1989; Linnoila, Virkkunen, Scheinin et al., 1983; Mann et al., 2001). In rodents, suboptimal serotonergic transmission impairs response control (Evenden, 1998, 1999a,b; Ruotsalainen, Miettinen, MacDonald et al., 2000; Winstanley, Chudasama, Dalley et al., 2003a), diminishes tolerance to delayed gratification (Evenden & Ryan, 1996), induces anxiety (Schreiber & De Vry, 1992; Soubrie, 1986; Winstanley, 2011), and increases self-injurious actions (King et al., 2003; Stein et al., 2002), alcohol consumption (Crabbe Phillips, Feller et al., 1996), aggression, and substance abuse (Lucas, Segu & Hen, 1997; Saudou, Amara, Dierich et al., 1994). Normalizing serotonergic function has beneficial effects on impulsive behaviours, which are promoted either directly by activating both pre- and post-synaptic 5-HT1A receptors, or indirectly by attenuating the inhibitory effects of 5-HT2 receptors (Schreiber & De Vry, 1992). Thus, the 5-HT1A and 5-HT2 receptors have functionally opposing effects and their interaction is mutually inhibitory (Schreiber & De Vry, 1992). The 5-HT2A and 5-HT2C receptor subtypes also have opposing effects on behaviour. In animal models of sustained attention and response inhibition, 5-HT2A receptor activation and 5-HT2C receptor antagonism both increase premature responses without affecting accuracy of target detection (Carli & Samanin, 1992; Koskinen, Haapalinna & Sirvi?, 2003; Koskinen, Ruotsalainen, Puumala et al., 2000a; Koskinen, Ruotsalainen & Sirvio, 2000b; Robinson, Dalley, Theobald et al., 2008a; Talpos et al., 2006; Young, Powell, Scott et al., 2011a), or impulsive choice (Talpos et al., 2006). Conversely, 5-HT2A and 5-HT2A/C receptor antagonism not only decrease premature responses on the 5-CSRTT (Koskinen et al., 2000a,b; Passetti, Dalley & Robbins, 2003; Robinson et al., 2008a; Talpos et al., 2006; Winstanley et al., 2003a), but the latter also blocks 5-HT2A receptor-induced premature responding (Koskinen et al., 2000a), suggesting the 5-HT2C receptor has a predominant role in modulating motor impulsivity. The role of 5-HT in regulating impulsive choice in delay discounting paradigms is inconclusive (Pattij & Vanderschuren, 2008); although global 5-HT depletion does not appear to alter choice during a 13 delay discounting paradigm (Winstanley et al., 2003a, 2006), 5-HT depletion attenuates the ability of AMPH-induced changes in choice behaviour (Winstanley, Dalley, Theobald & Robbins, 2003b). Together, these findings suggest that the 5-HT2A and 5-HT2C receptors both modulate?albeit in opposite ways?inhibitory processes, perhaps by regulating DA transmission in the NAc (Higgins, Enderlin, Haman & Fletcher, 2003; King et al., 2003; Robinson et al., 2008a; Talpos et al., 2006). Dopamine (DA) Optimal cortico-striatal dopaminergic neurotransmission is critical for regulating attention (Barnes, Young & Neil, 2012; Granon, Passetti, Thomas et al., 2000; Passetti et al., 2003), impulsive behaviour (Higgins et al., 2003; King et al., 2003; Robinson et al., 2008a; Talpos et al., 2006), as well as for learning reinforcement contingencies, and integrating negative feedback during reversal learning (Kehagia et al., 2010). In general, depleting cortical levels of DA impairs response suppression in rats (Sokolowski & Salamone, 1994). The DA receptor subtypes D1 and D2 are the primary recognition sites for DA (Carli, Anand-Srivastava, Molina-Holgado et al., 1994), and their affect on behaviour and impulsivity vary according to brain area and the type of pharmacological manipulation. Dopaminergic activity within the OFC might be correlated with decision-making during delay discounting paradigms, whereas DA efflux within the mPFC might occur during reward delivery (Winstanley et al., 2006). Increasing the levels of DA and selectively antagonising D2 receptors within the OFC decrease the value of delayed rewards on delay discounting paradigms (van Gaalen, Brueggeman, Bronius et al., 2006; Wade, de Wit & Richards, 2000), impair cognitive flexibility (Ragozzino, 2007), but do not affect motor impulsivity (van Gaalen et al., 2006; Winstanley et al., 2010). Intra-OFC infusions of D1 antagonists and D2 agonists improve motor response inhibition on the 5-CSRTT, but, for D1 antagonists, this effect is only observed in rats characterised as highly impulsive at baseline (Winstanley et al., 2010). On the other hand, while activating D2 receptors decreased accuracy scores on the 5-CSRTT, stimulating D1 receptors improves sustained attention and accuracy on rodent versions of the CPT (Barnes et al., 2012; Granon et al., 2000; Passetti et al., 2003; Winstanley et al., 2010). However, this D1 agonist-mediated effect might depend on baseline levels of performance (Granon et al., 2000) and method of drug administration (Winstanley et al., 2010). Antagonising D1 and D1/2 receptors within the mPFC (Fletcher et al., 2007) and NAc (Cole & Robbins, 1989; van Gaalen et al., 2009) attenuates premature responding. The ability of AMPH to increase alertness and premature responding on the 5-CSRTT (Boileau et al., 2006; Cole & Robbins, 1987; van Gaalen et al., 2009) are most likely mediated via D1 and D2 receptor inhibition and stimulation, respectively (Cole & Robbins, 1989; van Gaalen et al., 2009), as both are associated with enhanced DA 14 release in the NAc and PFC and an overall increase in mesolimbic DA activity (Baptista, Tene?d, Contreras et al., 1993; Boileau et al., 2006; Pattij & Vanderschuren, 2008). To this end, infusing D1 and/or D2 receptor antagonists in the NAc blocks AMPH-induced behavioural disinhibition (Cole & Robbins, 1987, 1989; van Gaalen et al., 2006, 2009). Noradrenaline (NA) Cortical noradrenergic activity is responsible for several cognitive functions, including arousal, attention, motivation, working memory, response inhibition, and regulates higher order behavioral flexibility, attentional set-shifting, and task switching (Kehagia et al., 2010; Lapiz & Morilak, 2006). The noradrenergic system is engaged during particularly novel or arousing tasks in a way that optimizes performance in paradigms of attentional function and impulse-control (Carli et al., 1983; Cole & Robbins, 1987; Lapiz & Morilak, 2006; Liu, Lin, Chuang et al., 2009; Robbins, 2002; Sirvi? et al., 1993). The level of noradrenergic activity determines which receptors become active and this in turn impacts PFC function. Noradrenaline binds to the adrenergic receptors ?1, ?2, ?1, ?2, and ?3-ARs, each of which has several subtypes (Ji, Ji, Zhang & Li, 2008; Ramos & Arnsten, 2007). While moderate levels of noradrenergic activity engage the ?2A-adrenergic autoreceptors, higher levels of noradrenergic activity (i.e. during high arousal or stressful state) engage ?1-and ?-ARs (Arnsten, 2000; Birnbaum, Gobeske, Auerbach et al., 1999). Depleting overall levels of cortical NA attenuates impulsivity and speed of responding, yet impairs working memory (Arnsten & Goldman-Rakic, 1985; Li & Mei, 1994). However, this manipulation does not affect accuracy of target detection on the 5-CSRTT (Cole & Robbins, 1989), suggesting that, relative to attentional and/ or memory processes, impulsive responding and motor response inhibition might be more sensitive to overall cortical NA efflux. Reports from studies examining the influence of ?1- or ?2-AR activation on cognitive function and behavioural inhibition often conflict (Robbins & Roberts, 2007). Generally, stimulating the ?2-AR decreases central NA release and enhances PFC function, decreases premature responses, increases omissions, and increases speed of responding in attention and working memory tasks in rodents (Ruotsalainen, Haapalinna, Riekkinen & Sirvi?, 1997; Sirvi? et al., 1993; Sirvi?, Mazurkiewicz, Haapalinna et al., 1994). On the other hand, increasing central NA release by blocking ?2-ARs (Cedarbaum & Aghajanian, 1977; Charney et al., 1982, 1983; Robinson et al., 2007; Sirvi? et al., 1993; Swann et al., 1983, 1987) reverses some of these ?2-AR agonist-induced effects and increases premature responding in rodent models of impulsivity (Koskinen et al., 2003; Liu et al., 2009; Ruotsalainen et al., 1997; Sirvi? et al., 1993, 1994). Together, these findings imply that intact PFC function is generally associated with 15 ?2-AR activity (Cedarbaum & Aghajanian, 1976, 1977; Charney et al., 1992; Ramos & Arnsten, 2007; Robbins, 2002). Conversely, evidence also shows that acute, low doses of ?2-AR antagonists have a mild stimulant effect on behavior (Sirvi? et al., 1994), such that these agents facilitate attention (Sirvi? et al., 1993) and improve performance on attentional and stimulus reversal tasks (Lapiz & Morilak, 2006; Sirvi? et al., 1993), and may even improve attentional focus and accuracy on the 5-CSRTT (Liu et al., 2009; Robbins, 2002; Robinson et al., 2007; Sirvi? et al., 1993). These ?2-mediated cognitive effects are impeded by ?1-AR antagonism (Lapiz & Morilak, 2006) which, on its own, impairs accuracy of target detection (Arnsten, 2000; Arnsten, Mathew, Ubriani et al., 1999; Carli et al., 1983; Cole & Robbins, 1987; Liu et al., 2009), while stimulating ?1-ARs enhances attention. Together, research on the ?-ARs clearly shows that these receptor subtypes are largely responsible for cognitive function and attentional accuracy by modulating central noradrenergic function (Arnsten et al., 1999; Carli et al., 1983; Cole & Robbins, 1987; Dalley et al., 2004; Dias et al., 1996; Lapiz & Morilak; Liu et al., 2009; Puumala, Riekkinen & Sirvi?, 1997). In the same way as the ?1- and ?2-ARs, the ?1- and ?2-ARs also have opposing functional effects (Ramos et al., 2005). For instance, activating ?1-ARs impairs working memory in rats and monkeys (Arnsten, 2000; Ramos et al., 2005), while blocking ?1-ARs prevents stress-induced impairments in cognitive flexibility (Alexander, Hillier, Smith et al., 2007). Meanwhile, activating cortical ?2-ARs improves working memory (Ramos et al., 2005), enhances retention (Introini-Collison, Miyazaki & McGaugh, 1991) and amplifies memory consolidation (Roozendaal, Quirarte & McGaugh, 2002). These ?2-AR agonists might also enhance long-term potentiation (LTP) in the hippocampus (McIntyre et al., 2005), suggesting that agonistic agents at this receptor subtype hold potential as global cognitive enhancers (Ramos et al., 2005). Altogether, these findings support the notion that optimizing noradrenergic transmission induces arousal mechanisms that facilitate attentional focus, processing of reward-related stimuli, and behavioural inhibition, thereby improving cognitive function (Arnsten, 2000; MacDonald, Kobilka & Scheinin, 1997) and performance on paradigms of attention, impulsivity, and behavioural flexibility (Birrell & Brown, 2000; Dias et al., 1996; Liu et al., 2009; Puumala et al., 1997; Robbins, 2002; Ruotsalainen et al., 1997; Sirvi? et al., 1993, 1994). Acetylcholine (ACh) The cholinergic system also plays a role in modulating cognitive function such as memory, reversal learning, sustained visuospatial attention, psychomotor speed, and impulsive behaviour (Ellis, Ellis, Bartholomeusz et al., 2006; Robbins & Robers, 2007; Tzavos, Jih & Ragozzino, 2004). In humans, 16 muscarinic receptor antagonism impairs all of these functions (Ellis et al., 2006). Basal forebrain cholinergic projections to the cortex are important for visuospatial attention; as such, the central cholinergic system largely regulates attentional function. For instance, performance on the 5-CSRTT is associated with increased ACh efflux in the mPFC. Although cholinergic output is not necessarily directly correlated with high performance or level of cognitive demand (Passetti et al., 2000), administering muscarinic receptor antagonists nevertheless impairs attention, choice accuracy, and response inhibition on the 5-CSRTT (Ruotsalainen et al., 2000). As the cholinergic system largely regulates attentional function, particularly with accurate timing of stimulus presentation and target detection on the 5-CSRTT (Risbrough, Bontempi & Menzaghi, 2002), lesioning cholinergic neurons increases omissions and reduces premature responses when a target stimulus is less predictable (Risbrough et al., 2002). Furthermore, blocking the M1 muscarinic cholinergic receptor subtype impairs reversal learning? a process during which subjects learn to stop performing a previously reinforced behaviour and instead learn to switch their response to the opposite choice not previously reinforced (Tzavos et al., 2004). Reversal learning relies on ACh activity in the OFC and dorsomedial striatum (Robbins & Roberts, 2007; Tzavos et al., 2004). Within the striatum, DA, AMPH, and DA agonists all activate D1 receptors and stimulate DA efflux, which, in turn, enhances and regulates striatal ACh release (Consolo et al., 1992; Mandel et al., 1994). Interestingly, AMPH abuse dysregulates the levels of striatal ACh, such that excessive DA and ACh transmission may result in increased cholinergic activity in humans (Flemenbaum, 1974). Since D1 antagonists decrease striatal ACh release (Consolo et al., 1992), and given that D1 receptors regulate striatal ACh release via DA efflux, agents acting at the D1 receptor might indirectly adjust and normalize ACh activity. In turn, restoring this cholinergic balance might attenuate AMPH abuse and other impulsive behaviours. Significance to Present Study The pharmacological correlates of cognitive function and impulse control described herein are also those implicated in the pathophysiology of BD (see sub-section 1.1.2 "Neuropathophysiology of bipolar disorder" for details). In light of these connections, the present study not only examines lithium's effects on impulsivity and attention but also investigates whether chronic lithium treatment influences pharmacology-induced behavioural changes by challenging rodents with acute doses of AMPH and YHB. In healthy humans and animals, these drugs induce impulsive behaviours akin to those manifested during bipolar mania and other ICDs. Moreover, these drugs are used to model certain psychiatric conditions or to precipitate manic episodes within psychiatric populations, such as manic episodes in patients with BD (see sub-section 1.1.3 "Bipolar disorder and pharmacology" for details). 17 Given these associations, the project herein investigates whether chronic lithium treatment affects stimulant- and arousal-induced changes in attention, impulsive behaviour, and overall performance on the 5-CSRTT and DDT. 1.3 Lithium 1.3.1 Clinical efficacy of lithium treatment Lithium is a naturally occurring element commonly used as a drug treatment in psychiatry (Young, 2009). Since Cade (1949) first reported the anti-manic effects of lithium in patients with chronic or recurrent mania, lithium has become the most widely used mood-stabilizer (Abou-Saleh, 1992; Baldessarini, Tondo, Hennen & Viguera, 2002; Ferrier et al., 2006; Smith et al., 2007). It is superior to other medications because it is the most effective in decreasing the occurrence of manic relapses, suicidal behaviour, and suicide (Schou, 1997; Swann et al., 2005b). Lithium is the most cost and clinically effective, and the best the tolerated treatment option for patients with BD (Chrisholm, van Ommeren, Ayuso-Mateos & Saxena, 2005; Potter & Ozcan, 1999; Schou, 1997; Smith et al., 2007; WHO, 2001; Young, 2009); as a result, current clinical guidelines recommend using lithium as first-line treatment for BD (Canadian Network for Mood and Anxiety Treatments [CANMAT], 2006; National Institute for Health and Clinical Excellence [NICE], 2006). Lithium's prophylactic efficacy can be largely attributed to its ability to dampen behaviours characterised as impulsive. Lithium treatment in patients with BD and even in patients with other psychiatric and/or personality disorders reduces the risk of substance abuse and addiction (Cassidy et al., 2001; Flemenbaum, 1974; Geller, Cooper, Sun et al., 1998; Swann, 2009; Swann et al., 2004; van Kammen & Murphy, 1975), pathological gambling (Hollander, Pallanti, Allen et al., 2005; Kim, Grant, Eckert et al., 2006), aggression (Dostal & Zvolsky, 1970; Luchins & Dojka, 1989; Sheard, 1971; Sheard, Marini , Bridges & Wagner, 1976; Tupin, Smith, Clanon et al., 1973), violent behaviour (Sheard et al., 1976), deliberate self-harm or suicidal behaviour (Osman & Loschen, 1992; Swann, 2009; Swann et al., 2005b; Winchel & Stanley, 1991), child abuse behaviour (Prado-Lima, Knijnik, Juruena & Padilla, 2001), and conduct disorder, hostility, and hyperactivity in children and adolescents (Campbell, Adams, Small et al., 1995; Malone, Delaney, Luebbert et al., 2000). Furthermore, sustained attention and behavioural performance is generally impaired in non-medicated patients with BD. However, when treated with lithium, these patients perform within a normal range on memory and cognitive tasks (Lund, Nissen & 18 Rafaelsen, 1982; Marusarz, Wolpert & Koh, 1981), indicating that lithium might also restore cognitive functioning. Interestingly, lithium might also produce beneficial effects to the general population, as it is found in various foods and drinking water (Schrauzer, 2002). Geographical regions with higher levels of lithium in the drinking water tend to have lower rates of suicide, drug use, and violent criminal behaviour (Ohgami, Terao, Shiotsuki et al., 2009; Schrauzer, 1990; Schrauzer & Shrestha, 1990). In animals, lithium decreases alcohol consumption (Alexander & Alexander, 1978), morphine self-administration (Tomkiewicz & Steinberg, 1974), aggression (Brain & Al-Maliki, 1979; Kovacsis & Gould, 2010; Mukherjee & Pradhan, 1976; O?Donnel, & Gould, 2007; Oehler, Jahkel & Schmidt, 1985; Prasad & Sheard, 1982), and overall impulsive-like behaviours (Ohmura Y, Tsutsui-Kimura, Kumamoto et al., 2011). To this end, lithium treatment in animals is also shown to boost attentional focus and performance (Cappeliez & Moore, 1988; Cappeliez, Moore & Souliere, 1989; Cappeliez & White, 1981), improve memory (Nocjar, Hammonds & Shim, 2007), and enhance task acquisition (Gallo, Poletti & Cazorla, 1990; Nocjar et al., 2007). Although lithium has clear therapeutic effects, its precise actions remain unknown despite decades of research (Ferrier et al., 2006). Given that lithium reduces the occurrence of highly impulsive behaviours and may benefit cognitive functioning, investigating whether chronic lithium treatment directly affects laboratory measures of impulsivity and cognition is worthwhile. Also of interest is determining lithium's neurochemical mechanisms of action and relating them to any behavioural changes resulting from lithium treatment. Findings here might provide information on the manner in which lithium exerts its prophylactic effect on symptoms of mania, which might also apply to the underlying pathophysiology of BD. In turn, these findings could provide a framework for identifying specific behavioural and neurochemical targets relevant to BD, which are instrumental in understanding lithium's clinical efficacy. 1.3.2 Lithium's mechanisms of action Lithium's prophylactic effects might be attributed to its ability to alter cellular components and neuronal processes that underlie psychiatric symptoms and cognitive dysfunction (Baptista et al., 1993; Gould & Einat, 2007; Ferrier et al., 2006; Lenox & Frazer, 2002). The following sub-section provides a brief overview of lithium's neurochemical targets including monoamines, neurotrophic factors, signalling kinases, transcription factors, synaptic proteins, and apoptotic factors (Cordeiro, Umbach & Gundersen, 2000; Ferrier et al., 2006; Gray et al., 2003; Lenox & Frazer, 2002; Young, 2009). 19 Neurotransmitter Systems Although lithium's therapeutic benefits are largely attributed to stabilizing monoaminergic neurotransmission, it is unclear whether lithium increases or dampens neurotransmission, and some studies even question whether lithium even affects neurotransmission at all. Despite this ambiguity, a wealth of studies provide compelling evidence that lithium influences many mechanisms involved in neurotransmission including receptor expression, receptor binding, and/ or receptor turnover, as well as neurotransmitter synthesis, release, and/or metabolism. However, lithium's effects are region-specific (Devaki, Rao & Nadgir, 2006; Lam & Christensen, 1992; Maggi & Enna, 2006; Treiser, Cascio, O'Donohue et al., 1981) and depend on the duration of treatment (Maggi & Enna, 2006; Schubert, 1973; Treiser et al., 1981) which might account for some of the discrepancy regarding its effects on neurotransmission. Lithium's clinical efficacy may be related to its ability to reduce noradrenergic (Devaki et al., 2006; Katz, Chase, & Kopin, 1968), serotonergic (Wang & Friedman, 1989), dopaminergic (Ferrie, Young & McQuade, 2005; Pert, Rosenblatt, Sivit et al., 1978), and cholinergic (Bymaster & Felder, 2002; Ellis & Lenox, 1990; Sourial-Bassillious, Rydelius, Aperia & Aizman, 2009) activity. For instance, lithium might dampen dopaminergic activity in the PFC (Baptista et al., 1993; Katz et al., 1968), striatum, and NAc (Carli et al., 1994; Dziedzicka-Wasylewska & W?dzony, 1996; Ichikawa, Dai & Meltzer, 2005). On the other hand, others postulate that lithium might instead enhance prefrontal DA release (Ichikawa et al., 2005; Ohmura et al., 2011; Tsaltas, Kontis, Boulougouris et al., 2007a), since depleting DA concentration in the PFC impairs response inhibition in rats (Sokolowski & Salamone, 1994) and lithium is reported to suppress this behaviour (Ohmura et al., 2011). Some researchers posit that lithium might indirectly exert its therapeutic effects on the dopaminergic system by stabilizing the serotonergic system (Carli et al., 1994; Ichikawa et al., 2005; Treiser et al., 1981; Wang & Friedman, 1989). To this end, lithium might enhance serotonergic neurotransmission by increasing 5-HT synthesis rate (Knapp & Mandell, 1973, 1975, 1976; Maggi & Enna, 2006; Mandell & Knapp, 1976; Perez-Cruet, Tagliamonte, Tagliamonte & Gessa, 1971) and 5-HT release (Treiser et al., 1981) in the hippocampus. At the same time, lithium might decrease 5-HT content and receptor binding in the hippocampus (Treiser et al., 1981). Lithium might also induce ?2-AR changes, decreasing its density but increase its turnover in this region as well as the cortex (Carbonell, Cuffy & Forn, 2004). Despite these observations, others have shown that lithium does not affect cortical receptor activity for noradrenergic (Carbonell et al., 2004; Maggi & Enna, 2006), serotonergic (Goodwin, De Souza, Wood & Green, 1986; Maggi & Enna, 2006; Treiser et al., 1981), dopaminergic (Baptista et al., 1993; Carli et al., 1994; Maggi & Enna, 2006), or muscarinic cholinergic (Maggi & Enna, 2006) 20 neurotransmission, nor does lithium affect DA levels or receptor activity in the NAc (Ferrie et al., 2005). In light of these diverse findings, the present study was undertaken in part to clarify lithium's influence on monoaminergic neurotransmission. We approached this inquiry by examining mRNA expression for several of the monoaminergic neurotransmitters' GPCRs (G-protein coupled receptors), the receptors' downstream intracellular targets, and other factors that contribute to efficient neurotransmission. Neuroprotection The cytoprotective protein Bcl-2 (B-cell lymphoma/leukemia-2 protein) is one of lithium's major biochemical targets (Chen et al., 1999; Chen & Chuang, 1999; Hammonds & Shim, 2009; Manji et al., 2000). This anti-apoptotic protein maintains calcium balance in organelles and regulates the permeability of the mitochondria's outer membrane, ultimately protecting the cell against the damages of oxidative stress (Adams & Cory, 1998; Youle & Strasser, 2008). As such, Bcl-2 is implicated in the aetiology of psychiatric disorders such as BD (Lien et al., 2008; Manji et al., 2000). Lithium regulates other neuroprotective factors such as NGF (nerve growth factor) and BDNF (brain-derived neurotrophic factor). These neurotrophins maintain normal synaptic transmission and plasticity (McAllister, Katz & Lo, 1999), and promote optimal neuronal function, growth, and survival (Hempstead, Rabin, Kaplan et al., 1992; Pullarkat, Mysels, Tan & Cowen, 1998). These neurotrophins bind to Trk (tropomyosin-related kinase) receptors (Hashimoto, Takei, Shimazo et al., 2002; Klein, Nanduri, Jing et al., 1991); activating these receptors initiates intracellular signalling cascades such as the ERK (extracellular signal-regulated kinase) pathway which ultimately activates gene transcription for factors involved in regulating cell survival (Hashimoto et al., 2002; Hempstead et al., 1992; Klein et al., 1991; Pullarkat et al., 1998; Russell, 1995; Yan, Hou, Wu et al., 2007). Other factors that promote cell survival by activating the ERK pathway include NMDARs (N-methyl-D-aspartate receptors) (Kim, Dunah, Wang & Sheng, 2005) and the GPCRs that bind monoamines (Flordellis, Berguerand, Gouache et al., 1995; Hempstead et al., 1992; Mendez, Kadia, Somayazula et al., 1999; Pullarkat et al., 1998), both of which are also targets of lithium. The ERK pathway activates transcription factors that regulate mRNA translation, protein synthesis, and cell proliferation (Denton & Tavare, 1995; Pullarkat et al., 1998). For instance, activating the transcription factor CREB (cyclic AMP [adenosine-mono-phosphate] response element-binding protein) increases BDNF, NGF, and Bcl-2 content in various brain regions (Benmansour et al., 2008; Denton & Tavare, 1995; Finkbeiner, 2000; Hammonds & Shim, 2009; Hellweg, Lang, Nagel & Baumgartner, 2002). By activating the ERK pathway, lithium activates transcription factors and immediate-early genes such as CREB and c-fos, respectively (Leslie, Moorman & Grahame-Smith, 1993; 21 Moorman & Leslie, 1998). In turn, ERK, CREB, and c-fos all play crucial roles in maintaining normal synaptic transmission and plasticity (Bliss & Collingridge, 1993; Silva, Kogon & Frankland, 1998), which points to their key role in the neuroprotective effects of lithium treatment. Vesicular and Synaptic Factors Optimal neurotransmission and synaptic plasticity relies on proteins involved with the vesicular and synaptic machinery. Many neuropsychiatric disorders are associated with abnormal proteins in the synaptic complex (Camp, Feyder, Ihne et al., 2011; Fernandez, Collins, Uren et al., 2009; Grant, Marshall, Page et al., 2005; Halstead, Jalink & Divecha, 2005; Yao, Gainetdinov, Arbuckle et al. 2004) and evidence suggests that lithium might interact with these proteins to normalize neurotransmission. For example, lithium increases the expression of CSP (cysteine string proteins) (Cordeiro et al., 2000), a family of vesicle proteins involved in the regulated secretory pathway that fine-tunes neurotransmission (Buchner & Gundersen, 1997; Umbach & Gundersen, 1997; Magga, Jarvis, Arnot et al., 2000). Lithium also influences the scaffolding protein PSD-95 (post-synaptic density-95) (Ma & Zhang, 2003; Tyagarajana et al., 2010), one of the major proteins required for synaptic plasticity (Elias & Nicoll, 2007; Kim & Sheng 2004; Steiner et al., 2008). Thus, lithium might stabilize neurotransmission by influencing vesicular mechanisms (Chamberlain & Burgoyne, 1998; Cordeiro et al., 2000; Umbach & Gundersen, 1997) or by inducing/modifying synapse formation (Hall, Lucas & Salinas, 2002; Kim & Thayer, 2009). Apoptotic Factors By stabilizing neurotransmission, lithium enhances neuronal health and survival while preventing glutamate-induced excitotoxicity, toxicity, and cell death. For example, lithium reduces calcium influx and regulates PSD-95 and cdk5 (cyclin-dependent kinase 5) activity, all of which mediate NMDAR activation and thus NMDAR?mediated apoptosis (Hashimoto et al., 2002; Ma & Zhang, 2003; Morabito, Sheng & Tsai, 2004; Nonaka, Hough & Chuang, 1998; Sourial-Bassillious et al., 2009). The kinase cdk5 plays an important role in cell differentiation, neural outgrowth and elaboration, and in axonal pathfinding, thus involved in synaptic plasticity as well as apoptosis (Nikolic, Dudek & Kwon, 1996; Tsai, Delalle, Caviness et al., 1994). Neurotoxins can dysregulate cdk5 activity and transform the kinase into a pro-apoptotic protein (Jord? et al., 2005; Lee, Kwon, Li et al., 2000; Lee & Tsai, 2003; Nguyen, Mushynski & Julien, 2002; Patrick, Zukerberg, Nikolic et al., 1999; Sengupta et al., 1997; Tsai et al., 1994). This altered kinase can localize to the nucleus and modulate gene transcription (Gong et al., 2003) and cause neurodegeneration (Jord? et al., 2005). Lithium treatment stabilizes cdk5 activity (Mao, Hoang & DiCorleto, 2001) and prevents this neurotoxin-induced conversion (Jord? et al., 2005), suggesting that lithium interacts with cdk5 to prevent neurotoxin-induced apoptosis. 22 Lithium also prevents apoptosis by inhibiting GSK-3? (glycogen-synthase kinase-3?) activity (Beaulieu, Sotnikova, Yao et al., 2004; Hooper, Markevich, Plattner et al., 2007; Jope, 2011; Mai, Jope & Li, 2002; Mendes, Mury, De Sa et al., 2009; Pardo, Andreolotti, Ramos et al., 2003; Tyagarajana et al., 2010), an enzyme with pro-apoptotic properties that might be implicated in the pathology of BD (Chiu & Chuang, 2011; Jope, 2011; Jord? et al., 2005; Tyagarajana et al., 2010). Blocking GSK-3? disinhibits CREB activity and BDNF-mediated signal transduction (Chiu & Chuang, 2011; Mai et al., 2002), regulates PSD-95 clustering to induce synaptogenesis (Tyagarajana et al., 2010), prevents glutamate-induced excitotoxicity (Grimes & Jope, 2001), and prevents neuronal membrane fragmentation (Tyagarajana et al., 2010). Thus, lithium's influence over GSK-3? activity may account for some of lithium's neuroprotective effects. Significance to Present Study One of the experiments herein demonstrates that chronic lithium treatment alters mRNA levels for several of the neurochemical targets described above. Changes in gene expression are quantified in several brain regions including the mPFC, OFC, and the NAc? regions which are closely associated with the pathophysiology of BD, impulsive behaviour, and with performance on the 5-CSRTT and DDT. In this context, the study discusses the changes in gene expression following chronic lithium treatment in terms of the behavioural changes observed on the 5-CSRTT and DDT, as well as their relevance to psychiatric disorders. Together, these findings might shed light on the manner in which lithium exerts its prophylactic effect on symptoms of mania in BD, which might also apply to the underlying pathophysiology of BD. In turn, these findings could provide a framework for identifying specific behavioural and neurochemical targets relevant to BD, which are instrumental in understanding lithium's clinical efficacy and for developing novel medications relevant for bipolar mania or other ICDs. 23 2 Methods 2.1 Subjects Subjects consisted of 32 male Long-Evans rats (Charles River Laboratories, St. Constant, QC, Canada). Rats were pair-housed in a climate-controlled environment, with constant temperature and humidity (21?C and 70%, respectively). Upon their arrival at the laboratory and thereafter, animals were exposed to a 12 h light/dark cycle (lights off at 08:00 h) so that behavioural testing took place during the active phase of their circadian rhythm. Rodents were given one week to adjust to the reverse light cycle, during which they remained pair-housed and were free fed with regular rodent chow (PMI rat LabDiet? # 5012, www.labdiet.com). At week two, animals were restricted to and maintained on 14 g of chow?85% of their free-feeding weight?throughout the experiment. This calculation was made in comparison to standard growth curves available from Charles River (for example, see Charles River 2013 Research Models & Services US Catalog, p. 7; http://www.criver.com/files/pdfs/rms/us-model-pricing/rm_mm_c_ 2013_us.aspx). At week three, animals were introduced to their respective custom-made diets, on which they were maintained throughout the experiment (see sub-section 2.2 "Lithium treatment and feeding procedure" for details). Behavioural training began two weeks after rats were placed on either the lithium or control diet (i.e. five weeks after arriving to the laboratory). Housing cages were made from clear polycarbonate (length x width x height: 48.3 cm x 26.7 cm x 20.3 cm); the lids were made of a metal grid and snapped shut. The bottoms of the cages were covered with 2-5 cm of woodchip bedding to provide the animals with comfort and enrichment. Each cage was also supplied with a cylindrical PVC tube and a few paper towels. Cages and enrichment materials were changed every 1-3 days. Water and 0.9% saline were available ad libitum to both control and lithium-treated animals. 2.2 Lithium Treatment and Feeding Procedure Three weeks after arrival, animals were randomly assigned and maintained on either a lithium chloride- (LiCl-) supplemented diet or a rodent control diet (Teklad Custom Research Diet TD.09574 with 0.3% w/v, 2.91 g/kg LiCl, or Teklad Custom Research Diet TD.02027, respectively; Harlan Laboratories Inc., Madison, WI, USA, www.harlan.com). Lithium treatment continued during behavioural training, testing, and pharmacological manipulations, and was maintained until the end of experimentation. Animals were separated during feeding to ensure that each consumed the correct amount of food and thus the proper dosage of lithium. Control animals were also separated to ensure 24 consistency between groups. Once every animal had finished eating, they were re-housed in pairs. In accordance with laboratory protocols, animals were fed immediately after behavioural assessments (11:30 h - 12:30 h). The pharmacokinetics of lithium vary between human and rodent populations. The half life of lithium is shorter in rodents than it is during sustained therapy in humans; thus, lithium was administered to rodents twice daily in order for plasma concentrations to remain within the relevant therapeutic range of 0.6 mM - 1.2 mM used in humans to treat BD (Ferrie, Young & McQuade, 2005; Lenox & Frazer, 2002; Wood, Goodwin, De Souza & Green, 1986). Animals were given 10 g of the 14 g of chow immediately after testing, while the remaining 4 g of chow was given at 09:00 h the next morning, two hours before testing, overall resulting in 14 g of chow within a 24-hour period. Animals had free access to 0.9% saline to minimize any ionic imbalances that may have occurred due to the diuretic properties of lithium (Maletzky & Shore, 1978), and to reduce renal toxicity associated with chronic lithium administration (Smith & Amdisen, 1983). As animals were rewarded with sugar pellets, and salt can affect sweet palatability (Smith & Amdisen, 1983), controls were also given free access to 0.9% saline to ensure that any salt-induced changes in taste would be at least partly controlled for (Nocjar, Hammonds & Shim, 2007). Body weight was monitored frequently to ensure equal weight gain between the groups. 2.3 Measurement of Serum Lithium Levels One week prior to sacrificing the animals, blood samples were taken at two distinct time points to measure plasma lithium levels. Samples (2 ml) were first taken between 11:30 h -12:30 h to coincide with the timing of behavioural testing (i.e. two hours after ingesting 4 g of rat chow). Samples were also taken at 14:30 h, the time when animals had eaten the remaining 10 g of chow and when serum lithium levels were at their highest. The order in which samples were collected alternated between lithium-treated and control rats to minimise any time of day effects. Prior to blood collection, animals were anaesthetised with a 2:1 mixture of ketamine (Ketaset?, 100 mL/kg, i.m.; V?toquinol, Lavaltrie, QC, Canada) and xylazine (Rompun? 20 ml/kg, i.m.; UBC Animal Care Centre, Vancouver, BC, Canada). Blood was collected from the jugular vein and analysed within the hour; plasma lithium concentrations were determined using flame atomic absorption spectrophotometry (Hospadaruk, Frankenberg & Neufeld, 1951; Velapoldi, Paule, Schaffer et al., 1980) at the UBC Hospital (Radiology and Laboratory Medicine, Vancouver, BC, Canada). 25 2.4 Behavioural Apparatus Behavioural testing took place in five-hole operant chambers (25 cm x 25 cm x 25 cm) (PVC Sound Attenuating Cubicles, Med Associates Inc., Georgia, VT, USA; www.med-associates.com; Figure 1A and B). Operant chambers were enclosed within a ventilated sound-attenuating cubicle (inner dimensions 55.9 cm x 40.6 cm x 38.1 cm). Both side walls are made of aluminum and have three modular columns to store input and/or output devices. The roof, front and back walls of the chamber are made of clear polycarbonate; the front wall is hinged to serve as the entry door. One side wall is curved and contains five square holes (2.5 cm sides, 4 cm deep) positioned 2 cm above a metallic grid floor made of parallel, 4.5-mm stainless steel rods spaced 1.6 cm apart (centre to centre). A stimulus light (28 V, 100 mA, 1 W, 2.5 cm diameter) is positioned at the back of each hole and a horizontal infrared photo beam is mounted across the entrance of each hole to detect head entries (nose-poke responses). The other side wall is flat and contains a house light (28 V DC, 100 mA, 3 W) located 1 cm from the top of the central column. The central column also contains a food receptacle (5 cm x 5 cm) mounted 2 cm above the grid floor and 25 cm away from each of the five holes. The food tray also contains a stimulus light and photo beam. The animal is trained to poke its nose inside the food tray in order to receive a sucrose pellet (45 mg; Bio-Serv Inc., Frenchtown, NJ, USA, www.bioserv.com), which is delivered to the tray from an automatic dispenser positioned outside of the chamber. A micro-camera is mounted on the ceiling of the cubicle to record the rats' behaviour. An aerial diagram and a front-view photograph of the chamber are provided in Figure 1A and B, respectively. Chamber features were controlled by MED-PC? IV Software (product# SOF-735; Med Associates Inc.; www.med-associates.com), which ran on an IBM-compatible computer. 26 A B Figure 1. Diagrams of the five-hole operant chamber. During the 5-CSRTT, animals respond to a brief stimulus light located in one of the five response apertures to receive a sugar pellet reward. (A) Aerial view showing the chamber's dimensions, the location of five response holes (H1-H5), a stimulus light (in H3), and the food tray. (B) Side view of chamber, indicating: 1) side wall with five holes, each equipped with infrared photo-beam detectors; 2) food tray with infrared photo beam detector; 3) house light (illuminates during time-outs); 4) metallic grid floor; 5) removable tray; 6) hinged door; 7) automatic pellet dispenser; 8) plastic tube that delivers pellets from dispenser to food tray; 9) sound attenuating cubicle; and 10) ventilation fan. 27 2.5 Behavioural Testing Rodents were randomly assigned to either the five-choice serial reaction time task (5-CSRTT; lithium-treated n = 8, control n = 8) or to the delay discounting task (DDT) (Experiment 1: lithium-treated n = 8, control n = 7; Experiment 2: lithium-treated n = 8, control n = 8). Each animal was assigned to a specific five-hole operant chamber and it was tested in that chamber for the remainder of the experiment. Animals were habituated to the five-hole chambers over two daily sessions; sucrose pellets were placed in the five response holes and the food tray, and rats were given 30 min per session to consume them. Subjects were then trained for several weeks on their behavioural paradigm (5-CSRTT or DDT) (see sub-sections 2.5.1 "The five-choice serial reaction time task (5-CSRTT)" and 2.5.2 "The delay discounting task (DDT)," respectively, for details). Once a stable baseline level of performance was established, animals were challenged with acute doses of D-amphetamine sulphate and yohimbine hydrochloride (see sub-section 2.6 "Pharmacological challenge: D-amphetamine (AMPH) and yohimbine (YHB)"). 2.5.1 The five-choice serial reaction time task (5-CSRTT) A flow diagram for the 5-CSRTT is shown in Figure 2. Animals were trained to perform the 5-CSRTT as described previously (Winstanley et al., 2003, 2007). Animals were assessed on the 5-CSRTT at least five times per week between 11:00 h - 11:30 h. A trial was initiated once the rat poked its nose into the illuminated food tray. This nose-poke extinguished the tray light and started the 5-sec inter-trial interval (ITI). During the ITI, animals scanned the five holes in order to detect a stimulus light that briefly illuminated (0.5 sec) one of the holes. Animals responded to this stimulus by poking their nose in that hole; this "correct" response was immediately rewarded with one sugar pellet. The pellet was dispensed in the food tray, which was illuminated during reward collection. A response made in any other hole, or a failure to respond in one of the five holes was scored as an "incorrect" response and an "omission," respectively. These two responses were punished with a 5-sec time-out, during which the house light was illuminated, no reward pellets were dispensed, and no new trial could be initiated. A response made before the stimulus light was presented, during the ITI, was classified as a "premature" response and provided an index of motor impulsivity. Premature responses were also punished with a 5-sec time-out. Once the time-out was served, the house light turned off and rats were permitted to initiate a new trial by poking their nose into the food well. The program continued until the rat completed all 100 trials in the session, or until the session lasted 30 min, whichever came first. Animals proceeded through twelve training stages before reaching criterion testing parameters (see Appendix A for details). The duration of stimulus light, ITI, and limited hold period (time during 28 which animals responded) depended on training stage. The initial parameters were stimulus duration of 30 sec, inter-trial interval of 2 sec, limited hold of 30 sec, and time-out of 5 sec. Each rat was exposed to one session daily until it reached a criterion of at least 30 rewarded trials per session. Once this criterion was reached, the stimulus duration and limited hold were decreased, and the ITI was increased until the following target testing parameters were attained in the final stage: stimulus duration of 0.5 sec, ITI of 5 sec, limited hold period of 5 sec, and time-out of 5 sec. Figure 2. Flow diagram showing the trial structure of the 5-CSRTT. The 5-CSRTT measures visuospatial attention, motivation and behavioural disinhibition (motor impulsivity). Animals initiate trials by poking their nose in the food tray, afterwhich a brief stimulus light illuminates one of the five holes. Animals respond by poking their nose into this hole; this "correct" response is rewarded with one sugar pellet, which is dispensed in the food tray. Animals that respond in the wrong hole ("incorrect" response), do not repond at all ("omission"), or respond before presentation of the stimulus light ("premature" response) are punished by a 5-sec time-out, during which the house light is illuminated. A new trial cannot be initiated until the time-out period is complete. Premature responses and accuracy of target detection ("correct" responses) provide a measure of motor impulsivity and attention, respectively. (See Appendix B for a more detailed schema). 2.5.2 The delay discounting task (DDT): Experiments 1 and 2 The DDT was performed between 11:30 h - 12:30 h at least five times per week. Animals underwent two training phases before being assessed on the actual DDT (see Appendix C for details). One session of the actual DDT lasted 56 min and consisted of four blocks of twelve trials, each trial lasting 70 sec. Every 70 sec, the central stimulus light (hole 3) would illuminate, indicating that a new trial could be initiated. Rats were given 10 sec to poke their nose in the food tray, which triggered the presentation of two stimulus lights?one in the far left response aperture and the other in the far right 29 (holes 1 and 5, respectively); these two holes were designated as either the "immediate" or the "delay" hole. Once the two stimulus lights were presented, animals had 10 sec to make a nose-poke response in either hole. Animals learned that a nose-poke response in the "immediate" hole was always associated with the instant delivery of one single food pellet (delay of 0 sec). In contrast, responding in the "delay" hole resulted in the delivery of four sugar pellets (dispensed 500 ms apart), where the delay period between the nose-poke response and reward delivery increased within the session in a step-wise manner between blocks: from 0 sec in block 1, to 15 sec in block 2, 30 sec in block 3, and to 45 sec in block 4. Once animals responded to one of the two holes, the stimulus lights turned off and, either immediately or after a delay, the tray light turned on, signaling that a sugar pellet had been dispensed. An ITI followed pellet delivery; duration of the ITI was contingent on the choice made, such that each trial always lasted 70 sec (i.e. choosing the "immediate" hole was followed by a longer ITI, while choosing the "delay" hole was follow by a shorter ITI, which decreased as the delays increased throughout the session). Failure to initiate a trial or to respond in one of the illuminated holes within 10 sec was recorded as an "omission" and punished with a time-out, during which the house light was illuminated, reward pellets were withheld, and animals were forced to wait until the ITI ended before initiating the next trial. Throughout the session, rate of pellet delivery associated with either behavioural response (nose-poking in "immediate" versus "delay" hole) was identical, preventing any differences in the timing of reinforcement from influencing choice. Holes were designated as either the "immediate" or "delay" hole on the first day of training and remained the same throughout testing. These designations were kept constant for each rat and were counterbalanced between experimental groups to offset any potential confound of side bias. Each block of 12 trials lasted 14 min and began with two "forced choice" trials, which signalled the duration of the delay assigned to that particular block. During the two "forced choice" trials, a stimulus light illuminated either the "immediate" or the "delay" hole in a random order. The remaining ten "free choice" trials proceeded in a manner described in the previous paragraph, where a stimulus light appeared in both the "immediate" and "delay" holes and subjects were free to choose between the immediate delivery of one sugar pellet or the delivery of four pellets after a particular delay (Figure 3). Once animals had learned the task, groups were compared on their choice of the larger reward across the delay periods. In the initial experiment (Experiment 1a), the discounting curves were relatively steep in both groups?animals' choice of the larger, delayed reward dropped abruptly across progressive delays, such that there were minimal differences in choice of the "delay" hole between 30 blocks with longer delays. To assess sensitivity to a shorter delay regimen, these animals were retrained on the task using shorter delays (0, 5, 10, and 20 sec; Experiment 1b) with the aim of obtaining a more meaningful discounting curve (Mar & Robbins, 2007). Holes associated with the short and long delays were reversed for each rat to avoid side biases. Once their performance was stable across three to five sessions, animals were subject to pharmacological challenges with amphetamine sulphate and yohimbine (see sub-section 2.6 "Pharmacological Challenges: D-amphetamine (AMPH) and yohimbine (YHB)" for details). A second cohort of animals was subsequently trained and assessed on the DDT using only the compressed delay scale (see sub-section 3.3.2 "Delay discounting Experiment 2: New cohort with short delay set only" for details). Animals from this cohort were not exposed to the larger delay set, nor were they subject to pharmacological challenges. All other procedures relating to feeding, training, and testing were identical to those of the first cohort. Figure 3. Flow diagram showing a "free choice" trial in the DDT. The DDT measures impulsive choice by quantifying the tendency to choose smaller, immediate food rewards over larger, delayed rewards. Animals initiate a trial by nose-poking in the food tray, which triggers the illumination of two stimulus lights in holes one and five (H1 and H5). Animals that respond in the "immediate" hole instantly receive a single sugar pellet (small reward), while animals that respond in the "delay" hole receive four sugar pellets (large reward), which are only delivered after the delay assigned to that block. An inter-trial interval ("ITI") follows pellet delivery, the duration of which depends on the choice made, so that each trial lasts 70 sec for every animal. Nose-poke in food traySmall reward chosen1 pelletNo delay4 pelletsLarge reward chosen (0, 5, 10, 20 sec)Stimulus lights onDelay(0 sec)Food trayH2 H4H3ITIITIH5H11 Trial (70 sec) 31 2.6 Pharmacological Challenges: D-amphetamine (AMPH) and yohimbine (YHB) Pharmacological challenges were performed once statistically stable baseline measures on the behavioural tasks had been confirmed across at least three sessions (see sub-section 2.8.1 "General health and baseline behavioural data" for details). D-amphetamine sulphate (AMPH) was purchased under an exemption from Health Canada from Sigma-Aldrich (UK, Dorset, England) and yohimbine hydrochloride (YHB) was purchased from Sigma-Aldrich (Oakville, ON, Canada). Drug doses used were assigned according to a digram-balanced Latin-square design (i.e. for doses A-D: ABCD, BDAC, CABD, and DCBA). For the 5-CSRTT and DDT, AMPH (0.0, 0.3, 0.6, and 1.0 mg/kg, i.p.; 0.0, 0.3, 1.0, and 1.5 mg/kg, i.p, respectively) was dissolved in 0.9% sterile saline and YHB (0.0, 1.0, 2.0, and 5.0 mg/kg, i.p.) was dissolved in water. Doses were selected based on previous studies investigating the effects of these drugs on similar behaviour (Sun et al., 2010; van Gaalen et al., 2009; Winstanley et al., 2003b, 2005, 2006). In human control subjects, doses of YHB that increase impulsive responding do not necessarily increase subjective feelings of arousal (Swann et al., 2005a). Similarly, in rodents, lower doses of YHB (1-2 mg/kg) increase impulsivity (Sun et al., 2010) without producing the anxiogenic effect obtained from a higher dose of YHB (5 mg/kg) (Cole, Hillmann, Seidelmann et al., 1995). Drugs were prepared fresh on each day of injection and were administered in a volume of 1 ml/kg, 10 min before testing. The schedule for drug administration began with a day of regular baseline testing, followed by one day of injection; the next day was test-free and animals remained in their home cage during the regular testing time (time of feeding remained the same). This three-day cycle was repeated until each dose had been administered to every rat. Animals were tested drug-free during a one-week wash-out period between the two drug regimes to prevent carryover effects. 2.7 Tissue Collection Once behavioural experiments were complete, animals tested on the 5-CSRTT were euthanised by live decapitation. This single-day procedure took place in a designated room, separate from live animal colonies. Decapitations were performed in the same timeframe behavioural testing had occurred. Animals were placed in a decapicone and the head was severed using a guillotine, which was wiped clean with 70% ethanol between subjects. The order of sacrificing between subjects was alternated between pairs of lithium-treated and control rats. Brains were extracted immediately after decapitation, sliced 1-mm thick using a metal rat brain matrix, and bilateral tissue punches were sampled from the medial prefrontal cortex (mPFC), orbitofrontal cortex (OFC), and the nucleus 32 accumbens (NAc). As these samples would later be analysed for mRNA expression, the work area and all tools used during decapitation sessions were treated with a surface decontamination solution that destroyed RNases on contact, thereby preventing the breakdown of RNA in the samples (RNaseZap? RNase Decontamination Solution, Applied Biosystems, part# AM9780; www.products.applied-biosystems.com). Samples were stored at -80?C and subsequently processed via real-time polymerase chain reaction to determine the expression of several genes of interest. 2.7.1 Real-time polymerase chain reaction (qPCR) Brain samples were removed from animals tested on the 5-CSRTT and were processed using qPCR. First, frozen samples were homogenized and RNA was removed using a TRIzol reagent (Invitrogen?, Carlsbad, CA, USA, http://products.invitrogen.com). The quality, purity, and RNA concentration of each sample were verified using the NanoDrop? 2000 Single-beam UV/Vis spectrophotometer (Thermo Fisher Scientific?, www.nanodrop.com). The purity of each sample was verified by calculating the ratio of its absorbance (A) measured at 260 nm to its absorbance at 280 nm. Samples were considered relatively pure and sufficiently free from contamination if their A 260/280 ratio was greater than 2.0, and these samples underwent DNA contamination to minimize the detection of DNA during qPCR analyses. The amount of sample required for DNA removal was calculated using the RNA concentration, such that the amount treated would consist of 1-5 ?g/?l of sample. Contaminating DNA was removed from the RNA preparation using the Ambion? DNA-free kit (Invitrogen?, part# AM1906). The resulting DNA-free RNA was further processed to obtain a cDNA library using a SuperScript? VILO? cDNA Synthesis Kit (Invitrogen?, catalog# 11754050). Primers were designed using Primer Express? Software v 3.0 (Applied Biosystems?, part# 4363993, Foster City, CA, USA, www.appliedbiosystems.com), were custom-synthesised using Eurofins MWG Operon (Huntsville, AL, USA, http://www.operon.com), and were validated for linearity and specificity (see Table 1 for gene of interest?GOI?primer sequences). Transcripts for each GOI were prepared for qPCR using the ExpressSYBR? GreenER? qPCR Supermix (Invitrogen?, catalog# 11784200) and quantified using a 96-well StepOnePlus? Real-Time PCR System (Applied Biosystems?, catalog# 4376600). Real-time PCR data were given as the threshold cycle- (CT -) value for each sample. To obtain the change (?) in CT -value, mean CT -values were normalised to glyceraldgyde-3-phosphate dehydrogenase (GAPDH). Normalisation was calculated as follows: ?CT = CT (GOI) ? CT (GAPDH). Target gene expression levels for the lithium-treated group were adjusted relative to controls according to the 33 following formula: ??CT = ?CT (lithium-treated group) ? ?CT (control group), and the fold-change in expression levels relative to controls were then calculated using the equation: 2???CT. Gene of Interest Primer Sequences Forward (Sequence 5? ? 3?) Reverse (Sequence 5? ? 3?) ?FosB AGGCAGAGCTGGAGTCGGAGAT GCCGAGGACTTGAACTTCACTCG 5-HT1A TACTCCACTTTCGGCGCTTT AAGCGTGCGGCTCTGAAG 5-HT2A CCTCAGCACTCGAGCCAAAC TGGACCGTTGGGAGCTTT 5-HT2C TGACCCCAACTTCGTTCTCAT CGCAGGACGTAGATCGTTAAGA ?1a-AR CATGGGCCTCTGCATCATCT CCTCCTCTGGGTGACAATGG ?2a-AR AGCTCGCTGAACCCTGTTATCT GTCCCCACGGCAGAGGAT ?1-AR CATCGTAGTGGGCAACGTGTT CCAGGGACATGATGAAGAGGTT ?2-AR TGGATTGTGTCGGGCCTTAC CAGTCGATGGCTTGCTTGTG Bcl-2 AGCATGCGACCTCTGTTTGA CAGGTATGCACCCAGAGTGATG BDNF AAGGCACTGGAACTCGCAAT TTATGAACCGCCAGCCAATT cdk5 ATCCCAGTCCGCTGCTACTCT CGATGGACGTGGAGTACAGCTT c-fos GGAATTAACCTGGTGCTGGA TGAACATGGACGCTGAAGAG CREB CAAGCTGCCTCTGGTGATGTAC GGGAGGACGCCATAACAACTC CSP GAAGCTGGCCCTGAAATATCAC GCGTGGGCGTTGTTAATCTC D1 GGCCTTTGGGTCCCTTTTGT ATCACGCAGAGGTTCAGAATGG D2 TAAGACGATGAGCCGCAGAA TGAACACACCGAGAACAATGG ERK1 TCCCAAATCTGACTCCAAAGCT GGTGAGCCAGTGCTTCCTCTA ERK2 AACCTCCTGCTGAACACCACTT CGCGTGGCTACATACTCTGTCA GAPDH GGTGGACCTCATGGCCTACA GGCCTCTCTCTTGCTCTCAGTATC Gsk-3? CCTGCCCTCTTCAACTTTACCA CGAGCGTGAGGAGGGATAAG M1 GCTCTGATGATTGGCCTAGCA CCCCAACTAGGTATTGCCAGAA M2 TGCAGACGTGGCTTCCTTT GTGGTGGGTTGGGCTTCA NGF GGCGAGGTGAACATTAACAACA CCCGGCATCCACTCTCTACA PSD-95 GGTTCCATCGTTCGCCTCTA AGGCCCTTTGATGAGTTTGATC TrkB TGGACCACGCCAACTGACAT GAGATGCTCCCGATTGGTTTG Table 1. Sequence of primers used for qPCR analyses. Target genes were chosen based on their involvement in impulsive behaviour, BD, and/or the effects of lithium treatment. For each gene, mRNA levels in lithium-treated rats were compared to those of controls in order to identify any changes induced by chronic lithium treatment. (See Glossary for full name of target genes). 34 2.8 Data Analyses Analyses were conducted using the Statistical Package for the Social Sciences (SPSS/PC) for Windows (version 16.0, SPSS Inc., 2006). Variables expressed as percentages were subject to an arcsine square root transformation to limit the effect of an artificially-imposed ceiling (i.e. 100%). All data are expressed using the group mean ? the standard error of the mean (? SEM). Findings were reported as significant if p < 0.05, and as a trend if 0.05 < p < 0.10. 2.8.1 General health and baseline behavioural data The effects of lithium treatment on weight gain were determined using independent-samples Student's t-tests, with average weight as the test variable, and treatment condition (lithium vs. control) as the grouping variable. The following variables were analysed for the 5-CSRTT: the total number of trials completed; the percent of trials on which correct, incorrect, and premature responses were made; the percent of trials omitted; the latency to respond correctly and incorrectly; the latency to collect reward; the number of perseverative nose-poke responses made; and the number of nose-pokes made in the food tray. Baseline behavioural data between groups were analysed using a repeated-measures analysis of variance (ANOVA), with session as the within-subjects factor, and treatment condition (lithium vs. control) as the between-subjects factor. The following variables were analysed for the DDT: the percent choice of large reward per delay; the average number of perseverative responses (across- and per-delay); the number of and latency to make anticipatory nose-poke responses (across- and per-delay); the latency to respond/ choose between the "immediate" and "delay" holes (across- and per-delay); the latency to initiate a trial (across- and per-delay); the latency to collect reward (across- and per-delay); and the percentage of trials omitted (across delays). Baseline behavioural data were analysed using repeated-measures ANOVA, with session and delay (0, 15, 30, 45 sec in Experiment 1a; 0, 5, 10, 20 sec in Experiment 1b) as within-subjects factors, and treatment condition (lithium vs. control) as the between-subjects factor. For each behavioural paradigm, subjects were considered to have reached a stable baseline of performance when behavioural measures no longer varied significantly across three to five consecutive sessions. Stable performance was confirmed using a repeated-measures ANOVA, where p > 0.05 for effect of Session, and for Group by Session and Delay by Session interactions, as appropriate. 35 2.8.2 Pharmacological challenges The behavioural variables measured during pharmacological manipulations were identical to those measured during baseline behaviour. Data obtained following drug challenges were analysed by repeated-measures ANOVA with dose (four levels: vehicle plus three doses of either AMPH or YHB) and/or delay (four levels: 0, 5, 10, and 20 sec1) as within-subjects factors, and group (lithium vs. control) as the between-subjects factor. Significant effects of dose were further analysed using paired-samples Student's t-tests, where each dose was compared to vehicle. Significant interactions were followed-up by further repeated-measures ANOVA examining responses to single drug doses over delay, or by paired-samples Student's t-tests comparing group or vehicle and dose at different delays. 2.8.3 qPCR For each sample, data obtained from qPCR were normalized to the housekeeping gene GAPDH; data obtained from samples of lithium-treated animals were then adjusted relative to controls. Gene expression for the lithium-treated group was expressed as the fold-change from controls'. Significant effects of lithium treatment on gene expression were determined using independent-samples Student's t-tests, with each gene of interest (total 25 genes) as the test variable and treatment condition (lithium vs. control) as the grouping variable. Corrections to account for these multiple comparisons were not included in the statistical analyses. We recognise that excluding such a statistical control increases the probability of at least one false positive, where a result appears significant when there is in fact no effect. One way to control for this error rate is to use the Bonferroni correction, which reduces the number of false positives when making multiple, independent comparisons (McDonald, 2008, p. 233). However, due to the limited number of samples collected, we excluded this correction in order to limit the number of false negatives, where a true effect is not detected as statistically significant. 1 Pharmacological manipulations were done on subjects from Experiment 1, once they were retrained on the shorter delay set. 36 3 Results 3.1 General Health and Serum Lithium Quantification Animals on the lithium-supplemented diet were initially slower to gain weight, however this difference was negligible by the time training began two weeks later. By the end of experimentation, lithium-treated and control animals weighed 346.75 ? 7.09 g and 367.13 ? 7.88 g, respectively, and this difference was not significant (t(29) = -1.93, ns; data not shown). Lithium-treated animals also exhibited polyuria and polydipsia. These biological effects, along with slower weight gain, are not permanent and have been reported by several other groups investigating lithium treatment (Baptista et al., 1995; Cox, Harrison-Read, Steinberg & Tomkiewicz, 1971; Nocjar et al., 2007; Smith, 2009; Treiser et al., 1981; Tsaltas et al., 2007a). A few weeks after arriving at the laboratory (before any behavioural manipulations began), one of the control rats died, which was most likely due to a failure to thrive as opposed to housing or experimental conditions. Lithium-treated animals appeared healthy and normally active throughout each study and did not present any of the distress symptoms associated with paradigms of lithium taste aversion (Nachman & Ashe, 1973). The mean (? SEM) serum lithium levels after feeding and during behavioural testing were 0.89 ? 0.044 mmol/L and 0.65 ? 0.042 mmol/L, respectively, levels which fall within the well-established therapeutic range of 0.5 - 1.5 mmol/L (CANMAT, 2006; Chen et al., 2000; Gelenberg et al., 1989; Kovacsis & Gould, 2010; Maletzky & Shore, 1978; NICE, 2006; Nocjar et al., 2007; O'Donnell & Gould, 2007; Treiser et al., 1981). 3.2 The Five-Choice Serial Reaction Time Task (5-CSRTT) The majority of animals began to respond within five sessions of the 5-CSRTT. By session 35 (seven weeks of training; nine weeks of lithium treatment), every rat had passed all twelve training stages. Once training was complete, animals were tested on the 5-CSRTT until performance was stable and did not significantly vary between five consecutive sessions. Animals reached a stable baseline of behaviour after 25 sessions (five weeks of testing; 14 weeks of lithium treatment). 3.2.1 5-CSRTT baseline performance Once stability was reached, lithium-treated rats were consistently and significantly more accurate at target detection than control animals, indicating that chronic lithium treatment may enhance attentional processes (ACCURACY?Group: F(1, 14) = 7.44, p = 0.016; Figure 4A). Thus, 37 Accuracy: BaselineSession0 5 10 15 20 25% Correct Responses057580859095100Lithium Control Motor Impulsivity: BaselineSession0 5 10 15 20 25% Premature Responses051015202530 A Baseline Accuracy B Baseline Motor Impulsivity Figure 1. Effects of chronic lithium treatment on attention and accuracy of target detection ns * behavioural changes became apparent after nine weeks of chronic lithium treatment, and remained significantly different once a stable baseline was reached. There were no significant differences between the groups on the number of premature responses made, indicating similar levels of motor impulsivity (PREMATURES?Group: F(1, 14) = 0.10, ns; Figure 4B). Compared to controls, lithium-treated animals tended to make more nose-poke responses in the food tray (NOSE-POKES?Group: F(1, 14) = 4.42, p = 0.054, Appendix D). However, these data were likely driven by one rat in particular which scored particularly high on this measure over the five sessions used for analyses (much greater than the interquartile range and above two standard deviations from the group mean). Finally, there were no group differences on the number of perseverative responses made, the latencies to respond correctly or incorrectly, the latency to collect reward, or on the number of trials completed or omitted (Appendix D), demonstrating that lithium treatment did not influence motivation to perform the task, affect speed of responding or locomotor activity, alter the incentive value of reward, or change sugar pellet palatability. Figure 4. Effects of chronic lithium treatment on attention and accuracy of target detection ("correct responses") and motor impulsivity ("premature responses") on the 5-CSRTT. (A) Lithium-treated rats (gray diamonds, n = 8) were significantly more accurate at target detection than were controls (dark squares, n = 8), responding correctly over 90% of the time compared to 82% for controls. (B) Lithium-treated and control animals did not differ with respect to motor impulsivity, as both groups responded prematurely approximately 10% of the time. Data used for analyses were averaged over the last five testing sessions, after 14 weeks of lithium treatment. Where indicated, repeated-measures ANOVA reported a significant effect of Group: * = p < 0.05; ns = non-significant. 38 3.2.2 Effects of AMPH on 5-CSRTT performance Accuracy and Premature Responses Each dose of AMPH (0.3, 0.6, 1.0 mg/kg) significantly decreased the accuracy of target detection and significantly increased the number of premature responses made (ACCURACY?Dose: F(3, 42) = 4.52, p = 0.008; saline vs. 0.3 mg/kg: t(15) = 2.46, p = 0.026; saline vs. 0.6 mg/kg: t(15) = 3.01, p = 0.009; saline vs. 1.0 mg/kg: t(15) = 3.08, p = 0.008; Figure 5A; PREMATURES?Dose: F(3, 42) = 22.39, p < 0.001; saline vs. 0.3 mg/kg: t(15) = -6.78, p < 0.001; saline vs. 0.6 mg/kg: t(15) = -5.89, p < 0.001; saline vs. 1.0 mg/kg: t(15) = -6.01, p < 0.001; Figure 5B; Appendix E). Lithium treatment did not alter the effect of AMPH on these measures, suggesting that lithium might not influence stimulant-induced changes in target detection and impulsive action (ACCURACY?Group: F(1, 14) = 1.41, ns; PREMATURES?Group: F(1, 14) = 0.004, ns; Figure 5A and B, respectively; Appendix E). Nose-pokes and Perseverative Responses Amphetamine had contrasting effects on nose-poke responses and perseverative responses?two other measures of impulsive-like behaviours?significantly increasing the former while significantly decreasing the latter at the two highest doses for both groups; lithium treatment did not block these effects (NOSE-POKES?Dose: F(3, 39) = 280.78, p < 0.001; saline vs. 0.6 mg/kg: t(14) = -19.37, p < 0.001; saline vs. 1.0 mg/kg: t(15) = -17.47, p < 0.001; Group: F(1, 13) = 1.65, ns; PERSEVERATIVE RESPONSES?Dose: F(3, 39) = 6.70, p < 0.001; saline vs. 0.6 mg/kg: t(15) = 3.66, p = 0.002; saline vs. 1.0 mg/kg: t(15) = 3.61, p = 0.003; Group: F(1, 13) = 0.21, ns; Appendix E). These results suggest that lithium treatment might not alter stimulant-induced changes in impulsive-like behaviours, which is in line with our results on premature responses presented above. Responses Latencies Amphetamine did not significantly affect the latencies to respond correctly or incorrectly (Appendix E), but there was a main effect of group on incorrect response latency across doses of AMPH, as lithium-treated rats took significantly longer to respond when responding incorrectly (INCORRECT RESPONSE LATENCY?Group: F(1, 14) = 17.50, p < 0.001; Appendix E). The two highest doses of AMPH decreased the latency to collect reward; lithium-treatment did not block this effect (COLLECTION LATENCY?Dose: F(3, 42) = 4.10, p = 0.012; saline vs. 0.6 mg/kg: t(15) = 2.86, p = 0.012; saline vs. 1.0 mg/kg: t(15) = 3.23, p = 0.006; Group: F(1, 14) = 1.00, ns; Appendix E). These results suggest that under circumstances where the outcome of a response is uncertain, lithium treatment might increase cognitive or decisional processing before choosing the way in which to respond. 39 Motor Impulsivity: AmphetamineAMPH Dose (mg/kg)Saline 0.3 0.6 1.0 % Premature Responses0102030405060Accuracy: Amphetam neAMPH Dose (mg/kg)Saline 0.3 .6 1.0 % Correct Responses0565707580859095100LithiumControl A Accuracy: AMPH B Motor Impulsivity: AMPH Figure 1. Effects of chronic lithium treatment on D-amphetamine (AMPH) during the 5-CSRTT. Each nsa nsa *b ?b ?b *b ?b ?b Number of Trials and Omissions The two highest doses of AMPH significantly decreased the number of trials initiated; there was no effect of lithium treatment (TRIALS?Dose: F(3, 42) = 6.81, p < 0.001; saline vs. 0.6 mg/kg: t(15) = 2.22, p = 0.042; saline vs. 1.0 mg/kg: t(15) = 3.05, p = 0.008; Group: F(1, 14) = 0.19, ns; Appendix E). Finally, both groups omitted significantly more trials at the highest dose of AMPH; while this effect was slightly more pronounced in lithium-treated animals, the difference was not significant (OMISSIONS?Dose: F(3, 42) = 2.87, p = 0.048; saline vs. 1.0 mg/kg: t(15) = -2.50, p = 0.024; Group: F(1, 14) = 4.25, p = 0.058, trend; Appendix E). Altogether, these results suggest that acute treatment with AMPH may impair attentional focus and increase motor impulsivity, and that these effects are not largely modulated by chronic lithium treatment. These results also indicate that lithium treatment might modulate decisional processing during a state of heightened psychomotor stimulation by increasing response times when the outcome of a choice response might be uncertain. Figure 5. Effects of chronic lithium treatment on AMPH during the 5-CSRTT. Each dose of AMPH significantly impaired accuracy of target detection ("correct responses") (A), and worsened motor impulsivity ("premature responses") (B). Lithium treatment did not block either stimulant-induced effect. Lithium-treated group: gray diamonds, n = 8; control group: dark squares, n = 8. Where indicated, repeated-measures ANOVA reported an effect of Group (a) and paired-samples Student's t-tests identified Dose (b) as significantly different from saline. Significance levels are reported as follows: ? = p < 0.001; ? = p < 0.01; * = p < 0.05; ns = non-significant. 40 3.2.3 Effects of YHB on 5-CSRTT performance Accuracy Acute treatment with medium and high doses of YHB disrupted accuracy of target detection across groups; however, lithium-treated rats maintained significantly higher accuracy scores than controls (ACCURACY?Dose: F(3, 39) = 4.25, p = 0.011; vehicle vs. 2.0 mg/kg: t(15) = 3.31, p = 0.005; vehicle vs. 5.0 mg/kg: t(14) = 2.56, p = 0.023; Group: F(1, 13) = 7.80, p = 0.015; Figure 6A; Appendix F). Investigating the main effect of group by analysing the groups separately indicated that there was no effect of dose for the lithium-treated group, while a only trend of dose emerged for controls, where the medium dose of YHB reduced accuracy scores (ACCURACY?Control: Dose: F(3, 21) = 2.77, p = 0.67, trend; vehicle vs. 2.0 mg/kg: t(7) = 2.52, p = 0.040; Lithium: Dose: F(3, 18) = 1.63, ns; Figure 6A; Appendix F). These data suggest that acute treatment with the pharmacological stressor YHB may impair attentional focus and task performance and that chronic lithium treatment might counteract this effect via arousal-mediated mechanisms. Premature Responses, Nose-pokes, and Perseverative Responses The two lowest doses of YHB significantly increased premature responding, however lithium treatment buffered this effect, as indicated by a significant main effect of group (PREMATURES?Dose: F(3, 36) = 14.92, p < 0.001; vehicle vs. 1.0 mg/kg: t(14) = -4.93, p < 0.001; vehicle vs. 2.0 mg/kg: t(14) = -7.87, p < 0.001; Group: F(1, 12) = 5.47, p = 0.037). A main effect of dose by group also emerged, and the highest dose of YHB did not affect controls whereas this dose tended to decrease premature responses below baseline levels for lithium-treated animals (PREMATURES?Dose x Group: F(3, 36) = 3.17, p = 0.036; Control: Dose: F(3, 18) = 6.23, p = 0.004; vehicle vs. 1.0 mg/kg: t(6) = -4.70, p = 0.003; vehicle vs. 2.0 mg/kg: t(6) = -7.63, p < 0.001; vehicle vs. 5.0 mg/kg: t(6) = -1.59, ns; Lithium: Dose: F(3, 18) = 15.63, p < 0.000; vehicle vs. 1.0 mg/kg: t(7) = -2.89, p = 0.023; vehicle vs. 2.0 mg/kg: t(7) = -5.08, p = 0.001; vehicle vs. 5.0 mg/kg: t(6) = 2.20, p = 0.071, trend; Figure 6B; Appendix F). These data suggest that lithium treatment might buffer arousal-induced increases in impulsive action, especially during highly stressful conditions. All three doses of YHB significantly increased the number of nose-poke responses made in the food tray for both groups (NOSE-POKES?Dose: F(3, 42) = 4.04, p = 0.013; vehicle vs. 1.0 mg/kg: t(15) = -2.39, p = 0.030; vehicle vs. 2.0 mg/kg: t(15) = -3.09, p = 0.007; vehicle vs. 5.0 mg/kg: t(15) = -3.84, p = 0.002; Group: F(1, 14) = 0.83, ns; Appendix F). YHB tended to decrease perseverative responding on 41 correct trials; the groups did not differ in this respect (PERSEVERATIVE RESPONSES?Dose: F(3, 39) = 2.67, p = 0.061, trend; Group: F(1, 13) = 1.38, ns; Appendix F). Latencies, Omissions, and Number of Trials At the lowest dose of YHB, both groups tended to be faster when responding correctly while at the highest dose, animals were significantly slower to respond correctly and incorrectly, the latter effect being significantly more pronounced in lithium-treated animals while only trend-like in controls (CORRECT RESPONSE LATENCY?Dose: F(3, 42) = 5.71, p = 0.002; vehicle vs. 1.0 mg/kg: t(15) = 2.08, p = 0.055, trend; vehicle vs. 5.0 mg/kg: t(15) = -2.35, p = 0.033; INCORRECT RESPONSE LATENCY?Dose: F(3, 42) = 9.77, p < 0.001; vehicle vs. 5.0 mg/kg: t(15) = -3.52, p = 0.003; Group: F(1, 14) = 5.63, p = 0.033; Lithium: Dose: F(3, 21) = 6.45, p = 0.003; vehicle vs. 5.0 mg/kg: t(7) = -2.71, p = 0.030; Control: Dose: F(3, 21) = 3.62, p = 0.030; vehicle vs. 5.0 mg/kg: t(7) = -2.13, p = 0.071, trend; Appendix F). The low and medium doses of YHB significantly decreased the latency to collect reward, while the highest dose significantly increased the latency to collect reward in both groups (COLLECTION LATENCY?Dose: F(3, 42) = 51.90, p < 0.001; vehicle vs. 1.0 mg/kg: t(15) = 4.58, p < 0.001; vehicle vs. 2.0 mg/kg: t(15) = 4.74, p < 0.001; vehicle vs. 5.0 mg/kg: t(15) = -6.16, p < 0.001; Group: F(1, 14) = 1.02, ns; Appendix F). In addition, both groups omitted significantly more trials at the highest dose; in general, lithium-treated animals tended to omit slightly more than controls at the lower dose of YHB (OMISSIONS?Dose: F(3, 42) = 30.55, p < 0.001; vehicle vs. 5.0 mg/kg: t(15) = -5.81, p < 0.001; Group: F(1, 14) = 4.55, p = 0.051, trend; Appendix F). Finally, there were no dose or group effects on the number of trials completed (Appendix F). 42 Accuracy: YohimbineYHB Dose (mg/kg)Vehicle 1.0 2.0 5.0 % Correct Responses0565707580859095100Lithium Control Motor Impulsivity: YohimbineYHB Dose (mg/kg)Vehicle 1.0 2.0 5.0 % Premature Responses051015202530 A Accuracy: YHB B Motor Impulsivity: YHB Figure 1. Lithium treatment blocks the effects of yohimbine (YHB) on 5-CSRTT performance. ?a *b ?a ?b ?a nsb ?b *c ?c *d Figure 6. Lithium treatment blocks the effects of YHB on 5-CSRTT performance. (A) YHB impaired accuracy of target detection in both groups; however, lithium-treated animals (gray diamonds, n = 8) maintained significantly higher scores than controls (dark squares, n = 8), suggesting that lithium treatment may have buffered the negative effects of YHB on attention. A main effect of group was followed-up by separating the groups for further analyses, which indicated that the medium dose of YHB significantly worsened accuracy scores for the control group, while only tending to do so for the lithium group. (B) Low and medium doses of YHB significantly increased premature responding in both groups; however, this effect was significantly less pronounced in lithium-treated animals, indicating that lithium treatment may have attenuated stress-induced increases in motor impulsivity. Significant group effects were further analysed with separate ANOVAs for each group. Where indicated, paired-samples Student's t-tests identified YHB dose as different from vehicle for the control (a) and lithium-treated (b) groups. Where indicated, repeated-measures ANOVA reported an effect of Group (c) and a Dose by Group interaction (d). Significance levels are represented as follows: ? = p < 0.001; ? = p < 0.01; * = p < 0.05; ? = 0.05 < p < 0.10, trend. 43 Impulsive Choice:Experiment 1a- Large Delay SetDelay to Large Reward (sec)0 15 30 45% Choice of Large Reward0102030405060708090100LithiumControl Impulsive Choice Experiment 1a- Large Delay Set Figure 1. Delay discounting Experiment 1a?Large delay set. Choice of the large reward significantly nsb ?a Lithium Control 3.3 The Delay Discounting Task (DDT) All rats began to respond within the first session; it took ten sessions before each rat had passed both training phases (see Appendix C for details). Animals were then trained on the full DDT; training considered complete once performance did not significantly vary between three consecutive sessions. 3.3.1 Delay discounting Experiment 1: Large vs. short delay sets Experiment 1a?Large delay set With the initial delays of 0, 15, 30, and 45 sec, every subject completed training within two weeks and reached stability after an additional 25 sessions of testing (nine weeks of lithium treatment). Both groups generated steep discounting curves by choosing the small, immediate reward as soon as the first delay (15 sec) was presented (CHOICE OF LARGE REWARD?Delay: F(3, 39) = 96.67, p < 0.001; Group: F(1, 12) = 0.06, ns; Figure 7). Impulsive Choice Experiment 1a- Large Delay Set Figure 7. Delay Discounting Experiment 1a?Large delay set. Choice of the large reward significantly decreased as the delay in each block increased. At the 0-sec delay, animals chose the large reward approximately 90% of the time whereas, during the 15-, 30-, and 45-sec delays, animals chose the large reward approximately 30%, 15%, and 10% of the time, respectively (lithium-treated group: gray diamonds, n = 8; control group: dark squares, n = 7). Data shown are averaged over four consecutive baseline sessions, following seven weeks of testing and nine weeks of lithium treatment. Where indicated, repeated-measures ANOVA determined an effect of Delay (a) and Group (b). Significance levels are reported as follows: ? = p < 0.001; ns = non-significant. Lithium Control 44 Experiment 1b?Short delay set In order to obtain a broader discounting curve where choice of the larger reward would decrease across delays more gradually, the delays for blocks 1, 2, 3, and 4 were reduced to 0, 5, 10, and 20 sec, respectively, and animals were retrained on the task using these shorter delays. The location of the "delay" and "immediate" holes were reversed for each rat to avoid side biases. Training. Compared to controls, lithium-treated rats were significantly faster to adjust their behaviour in response to these new delays. Within the first week of retraining, they switched their nose-poke responses according to the new locations for the "delay" and "immediate" holes, whereas controls had not yet shifted their responses according to these new contingencies (CHOICE, TRAINING?Delay x Group: F(3, 39) = 3.94, p = 0.015; Session x Delay: F(9, 117) = 2.00, p = 0.046; Session x Delay x Group: F(9, 117) = 2.17, p = 0.029; Lithium: Session: F(5, 21) = 52.75, p < 0.001; Delay: F(3, 21) = 4.71, p = 0.011; Session x Delay: F(9, 63) = 3.07, p = 0.004; Control: Session: F(3, 18) = 26.55, p < 0.001; Delay: F(3, 18) = 2.60, p = 0.084, trend; Session x Delay: F(15, 90) = 1.36, ns; Figure 8). These results suggest that lithium treatment might facilitate reversal learning and enhance the capacity for behavioural flexibility. Choice Behaviour. Both groups had fully re-learned the task and reached a stable baseline of performance after two weeks of retraining (eleven weeks of lithium treatment) (CHOICE, SHORT DELAY SET?Session: F(4, 48) = 0.89, ns; Session x Delay: F(12, 144) = 0.79, ns; data not shown). Unlike the steep discounting pattern generated from the larger delay set in Experiment 1a (Figure 9A), the shorter delays in Experiment 1b produced shallower and more gradual discounting curves (Figure 9B). These short delays generated meaningful discounting patterns as they differed between the two groups: as the delay increased, lithium-treated animals discounted the large reward in favour of the small reward sooner than controls, suggesting that chronic lithium treatment influences choice behaviour (CHOICE, SHORT DELAY SET?Delay: F(3, 36) = 60.43, p < 0.001; Group: F(1, 12) = 10.24, p = 0.008; Delay x Group: F(3, 36) = 10.96, p < 0.001; Figure 9B; Appendix G). Other Behavioural Measures. In addition to lithium's effects on choice behaviour, the groups tended to differ on the number of anticipatory nose-poke responses made at different delays. Specifically, controls made the most anticipatory nose-pokes during the 10-sec delay whereas lithium-treated animals made the fewest nose-poke responses during this delay (NOSE-POKES?Delay: F(2, 24) = 0.60, ns; Group: F(1, 12) = 1.95, ns; Delay x Group: F(2, 24) = 2.78, p = 0.082, trend; Appendix G). The delays significantly increased reaction times to initiate a trial and to choose between the immediate and delayed reward (INITIATION LATENCY?Delay: F(3, 39) = 11.12, p < 0.001; CHOICE LATENCY?Delay: F(3, 39) = 7.16, p < 0.001; Appendix G). By contrast, delay magnitude had no effect on the latencies to make anticipatory nose-poke 45 Control:Retraining on Short Delay SetTraining Session1 2 3 4 5 6 7 8% Choice of Large Reward01020304050607080901000-sec delay5-sec delay10-sec delay20-sec delayLithium: Retraining on Short Delay Set Trai ing Session1 2 3 4 5 6 7 8% Choice of Large Reward0102030405060708090100 Figure 1. Change in choice of large reward when retraining on shorter delay set: Lithium treatment ?a nsa ?b,c nsb ?c 0-sec delay 5-sec delay 10-sec delay 20-sec delay Control:Retraining on Short Delay SetTraining Session1 2 3 4 5 6 7 8% Choice of Large Reward01020304050607080901000-sec delay5-sec delay10-sec delay20-sec delayresponses or to collect reward, nor did it affect the number of omissions and perseverative responses made (Appendix G). Together, these results indicate that the different discounting patterns generated from the two delay sets are most likely attributable to lithium's influence on choice behaviour rather than on motivation to perform the task, locomotor activity, or on appraisal or palatability of the sugar reward. Figure 8. Change in choice of large reward when retraining on shorter delay set: Lithium treatment enhances behavioural flexibility. Delays for blocks 1, 2, 3, and 4 were reduced from 0, 15, 30, and 45 sec to 0, 5, 10, and 20 sec, respectively, and animals were retrained on the task using these shorter delays. Within the first week of retraining (by session five), lithium-treated animals (n = 8) had already begun to discount the large reward, adjusting their behaviour according to the new task parameters, whereas controls (n = 7) required more sessions to adjust their choice behaviour. Where indicated, repeated-measures ANOVA reported an effect of Session (a) and Delay (b) and a Session by Delay interaction (c). Significance levels are represented as follows: ? = p < 0.001; ? = 0.05 < p < 0.10, trend; ns = non-significant. Experiment 1a vs. 1b?Comparing large and short delay sets Another way to evaluate the different discounting patterns that emerged from shortening the delays is to examine consistency of choice behaviour between the two sets of delays by comparing choice of the large reward during a specific delay. For example, the large delay set (Experiment 1a) did not generate any significant group differences on choice behaviour during the 15-sec delay (first delay 46 presented in the session); both groups chose the large, delayed reward about 30% of the time (CHOICE AT 15 sec, LARGE DELAY SET?Control: 30.4% ? 11.8%; Lithium: 27.5% ? 10.9%; Group: F(1, 13) = 0.01, ns; Figure 9A). Although the shorter delay set (Experiment 1b) did not include the 15-sec delay, one can interpolate data for this time point by averaging data for the 10- and 20-sec delays then compare these data with those for the 15-sec delay from Experiment 1a. This comparison shows that lithium-treated animals did not change their choice behaviour between the two delay sets, as they continued to choose the large reward approximately 30% of the time. On the other hand, upon shortening the delays, controls doubled their choice of the large reward from 30% to about 60% of the time. This change produced a main effect of delay set on choice of the large reward for this 15-sec delay (CHOICE AT 15 sec, LARGE VS. SHORT DELAY SET?Control: 30.4% ? 11.8% vs.61.6% ? 9.7%; Lithium: 27.5% ? 10.9% vs. 28.9% ? 8.2%; Delay Set: F(1, 7) = 0.16, ns; Delay Set: F(1, 6) = 10.65, p = 0.017; Figure 9A and B; dashed lines). These results show that lithium-treated animals were significantly more consistent in their choice of the large reward at 15 sec between both delay sets, demonstrating the group's internal consistency with respect to choice behaviour. Evidently, shortening the delays produced a significant main effect of group on choice behaviour since only controls changed their behaviour in response to these new delays. Specifically, at the 15 sec time-point during the new delay set, controls chose the large reward twice as often as lithium-treated animals (CHOICE AT 15 sec, SHORT DELAY SET?Control: 61.6% ? 9.7% vs. Lithium: 28.9% ? 8.2%; Group: F(1, 12) = 10.24, p = 0.008; Delay Set x Group: F(1, 13) = 4.78, p = 0.048; Figure 9B). Lithium-treated animals also maintained this consistency of choice at 20 sec, choosing the large reward one in five times in both delay sets, whereas controls more than doubled their choice of the large reward (CHOICE AT 20 sec, LARGE VS. SHORT DELAY SET?Control: 22.3% ? 10.0% vs. 52.6% ? 10.4%; Lithium: 20.5% ? 9.5% vs. 21.8% ? 6.7%; Figure 9A and B, dashed-dot-dot lines). Altogether, these data tentatively suggest that chronic lithium treatment may enhance reversal learning and behavioural flexibility, thus promoting consistency of behavioural preferences following changes in task contingencies. It is also possible that control animals were more sensitive to the difference in delay sets. Since the animals had been accustomed to lengthy 30- and 45-sec delays, perhaps lithium treatment blunted any sensitivity to contrasts in time between the delay sets; alternatively, lithium treatment might impair tolerance to delays of gratification and exacerbate choice impulsivity. These interpretations are addressed and examined in a follow-up experiment where a new cohort of animals is trained on the DDT using only the short delays (see sub-section 3.3.2 "Delay discounting: Experiment 2: New cohort with short delay set only"). 47 B Impulsive Choice:Experiment 1a- Large Delay SetDelay to Large Reward (sec)0 15 30 45% Choice of Large Reward0102030405060708090100LithiumControlImpulsive Choice:Experiment 1b- Short Delay SetDelay to Large Reward (sec)0 5 10 20% Choice of Large Reward0102030405060708090100nsa ?b ?b ?a ?c B Impulsive Choice:Experim nt 1a- Large Delay S tDelay to Large Reward (sec)0 15 30 45% Choice of Large Reward0102030405060708090100LithiumControlImpulsive Choice:Experiment 1b- Short Delay SetDelay to Large Reward (sec)0 5 10 20% Choice of Large Reward0102030405060708090100nsa ?b ?b ?a ?c Impulsive Choice:Experiment 1a- Large Delay SetDelay to Large Re r ( )0 15 30 45% Choice of Large Reward0102030405060708090100LithiumControlnsa ?b ?b ?a ?c Impulsive Choice:Experiment 1b- Short Delay SetDelay to Large Reward (sec)0 5 10 20% Choice of Large Reward01203405607809100Impulsive Choice:Experiment 1a- Large Delay SetDelay to Larg Reward (sec)0 15 30 45% Choice of Large Reward01203405607809100LithiumControl A B Figure 1. Delay discounting Experiment 1: Lithium treatment promotes consistency of choice nsa ?a ?c ?b ?b Lithium Control B Impulsive Choic :Experiment 1a- Large Delay SetDelay to Large Reward (sec)0 15 30 45% Choice of Large Reward0102030405060708090100LithiumControlImpulsive Choice:Expe iment 1b- Short Delay SetDelay to Large Re0 5 0% Choice of Large Reward0102030405060708090100nsa ?b ?b ?a ?c Impulsive C i :Experiment 1a- Larg l tDelay to Lar 0 15 5% Choice of Large Reward0102030405060708090100Lithiuntrolnsa ?b ?b ?a ?c Impulsive Choice:Experiment 1b- Short Delay SetDelay to Large Reward (sec)0 5 10 20% Choice of Large Reward203405607809100Impulsiv Choice:Experiment 1a- Large Delay SetDelay to L rg Reward (sec)0 15 30 45% Choice of Large Reward01203405607809100LithiumControl A B Figure 1. Delay discounting Experiment 1: Lithium treatment promotes consistency of choice nsa ?a ?c ?b ?b Lithium Control B Impulsive Choice:Experiment 1a- Large Delay SetDel L rge Reward (s c)0 15 30 45% Choice of Large Reward0102030405060708090100LithiumControlnsa ?b ?b ?a ?c Impulsive Choice:Experiment 1a- Large Delay SetDelay to Large R ward (sec)15 30 45% Choice of Large Reward102304050607809100LithiumControlnsa ?b ?b ?a ?c Impul e Ch ice:Experi nt - Short Delay S tDelay to Large Reward (sec)0 5 10 20% Choice of Large Reward01203405607809100Impulsive ChoicExperiment 1a- Large y SetD lay to Larg Rewar (s c)0 15 30 45% Choice of Large Reward0007809100LithiumControl A B Figure 1. Delay dis ting Experiment 1: Lithium treatm n promotes consistency of choi e nsa ?a ?c ?b ?b Lithium Control A B Figure 9. Delay Discounting Experiment 1: Lithium treatment promotes consistency of choice between long and short delay sets. (A) Experiment 1a?Large delay set. Choice of the large reward significantly decreased as the delay increased, producing steep discounting curves for each group. (B) Experiment 1b?Short delay set. Shortening the delays to 0, 5, 10, and 20 sec generated a more gradual discounting pattern (data taken from four consecutive sessions, after two weeks of retraining, after 11 weeks of lithium treatment). Delay discounting was significantly more pronounced in the lithium-treated animals (gray diamonds, n = 8; control animals: dark squares, n = 7). Comparing the two sets of delays, lithium-treated animals were more consistent in their choice of the large reward. Interpolating data for a 15-sec delay in the short delay set (B) indicates that controls (dashed dark gray lines) chose the large reward twice as often than they did during the original set (A) of longer delays (62% vs. 30%, respectively), while lithium-treated rats did not change the distribution of their responses at 15 sec between the larger (A) and shorter (B) delay sets (28% vs. 29%, respectively; dashed light gray lines). The lithium group's internal consistency is also evident for the 20-sec delay; interpolating data for the 20-sec delay from the large delay set (A) and comparing them with the 20-sec data from the shorter delay set (B) indicates that lithium treatment promoted a stable preference of choice as lithium-treated animals responded uniformly during these delays, choosing the large reward 21% and 22% of the time, respectively (light gray dashed-dot-dot lines, both sets). On the other hand, controls more than doubled their choice preference between the two delay sets, choosing the large reward 22% and 53% of the time, respectively (dark gray dashed-dot-dot lines, both sets). Where indicated, repeated-measures ANOVA determined an effect of Group (a) and Delay (b) and a Delay by Group interaction (c). Significance levels are reported as follows: ? = p < 0.001; ? = p < 0.01; ns = non-significant. 48 3.3.2 Delay discounting Experiment 2: New cohort with short delay set only Recapitulation of Experiment 1 In the first delay discounting experiment (sub-section 3.3.1, "Experiment 1a?Large delay set"), the four delays for blocks one to four were set at 0, 15, 30, and 45 sec, respectively, which produced a relatively steep discounting pattern in both groups. Shortening the delays to 0, 5, 10, and 20 sec in Experiment 1b shifted choice from the large, delayed reward toward the smaller, immediate reward later in the session (i.e. at longer delays), which generated a more gradual and shallow discounting pattern. In general, lithium treatment significantly increased choice of the smaller, immediate reward, thereby producing a significant group effect. As there were several ways to interpret these results, a follow-up experiment (Experiment 2) was conducted to address these results. Experiment 2?Short delay set only A new cohort of animals was trained on the DDT using delays of 0, 5, 10, and 20 sec (thus, this cohort was never exposed to the larger set of delays used in Experiment 1a). It took eleven sessions before each rat had passed both training phases (see Appendix C for details on training phases), after which animals were tested on the full DDT. Choice Behaviour during Training. Lithium-treated rats were significantly quicker to learn the task. Within the first week of training, they adapted their choice behaviour in response to the delay duration, whereas controls required additional sessions before stabilising their discounting pattern (CHOICE OF LARGE REWARD, TRAINING?Group: F(1, 14) = 13.48, p = 0.003; Delay: F(5, 42) = 84.62, p < 0.001; Session x Group: F(4, 56) = 3.06, p = 0.024; Delay x Group: F(3, 42) = 4.49, p = 0.008; Session x Delay x Group: F(12, 168) = 2.15, p < 0.017; Control: Delay: F(3, 21) = 60.83, p < 0.001; Session x Delay: F(12, 84) = 1.11, ns; Lithium: Delay: F(3, 21) = 39.70, p < 0.001; Session x Delay: F(12, 84) = 2.37, p = 0.011; Figure 10). Choice Behaviour at Baseline. Performance reached stability after seven weeks of testing (nine weeks of lithium treatment). Both groups favoured the small, immediate reward as the delays increased, eliminating the effect of group noted during training (CHOICE OF LARGE REWARD, BASELINE?Delay: F(3, 42) = 89.71, p < 0.001; Group: F(1, 14) = 1.02, ns; Figure 11; Appendix H). These data suggest that chronic lithium treatment may accelerate learning and task acquisition. Other Behavioural Measures. In general, as the delay to the large reward increased, both groups took significantly more time to initiate trials and to choose between the small or large reward (INITIATION LATENCY?Delay: F(3, 39) = 10.03, p < 0.001; CHOICE LATENCY?Delay: F(3, 42) = 6.96, p < 0.001; Appendix H). However, lithium-treated animals took longer to choose between the reward options compared to 49 controls. This main effect of group enabled separate group analyses, which revealed that the effect of delay on choice latency was only significant for the control group and just a trend for the lithium-treated group (CHOICE LATENCY?Delay: F(3, 42) = 6.96, p < 0.001; Group: F(1, 14) = 11.94, p = 0.004; Control: Delay: F(3, 21) = 7.17, p = 0.002; Lithium: Delay: F(3, 21) = 2.79, p = 0.065, trend; Appendix H). The delays also significantly increased the latency to collect reward at the 5-and 20-sec delays, while tending to do so at the 10-sec delay (COLLECTION LATENCY?Delay: F(3, 42) = 5.28, p = 0.004; Appendix H). The only latency not affected by the size of the delay was the latency to make anticipatory nose-poke responses in the food tray. The number of anticipatory nose-pokes and omissions were not dependent on delay, either; by contrast, larger delays significantly decreased perseverative responses (PERSEVERATIVE RESPONSES?Delay: F(3, 42) = 9.37, p < 0.001; Appendix H). There were no group differences on any of these measures, suggesting that lithium treatment does not affect motivation or task engagement, locomotor activity, or appraisal or palatability of the sugar reward. Thus, results from this second experiment support our findings from Experiment 1 and demonstrate that both groups displayed similar levels of delay tolerance and delay discounting patterns that were unlikely attributed to other confounding factors. Accordingly, it is unlikely that the group difference that emerged after shortening the delays in Experiment 1 reflected an increase in impulsive choice or a decrease in tolerability to delays, suggesting that lithium treatment must influence choice behaviour by other means. 50 Figure 10. Delay Discounting Experiment 2 (short delay set only)?Training new cohort: Lithium treatment accelerates acquisition of choice behaviour. Delays for blocks 1, 2, 3, and 4 were set to 0, 5, 10, and 20 sec, respectively, and animals were trained on the task using these short delays (thus, this cohort of animals was never exposed to the longer delay set from Experiment 1a). Within the first week of training, lithium-treated animals (n = 8) had already begun to discount the large reward as delays increased, whereas controls (n = 8) required more sessions to distinguish between the different delays and develop of choice preference. Where indicated, repeated-measures ANOVA reported an effect of Delay (a) and a Session by Delay interaction (b). Significance levels are represented as follows: ? = p < 0.001; ns = non-significant. Control: Lithium: New Cohort Training on Short Delay Set Only New Cohort Training on Short Delay Set Only Lithium: New Cohort Training on Short Delay Set OnlyTraining Session1 2 3 4 5 6 7 8% Choice of Large Reward0102030405060708090100Control:New Cohort Training on Short Delay Set OnlTraining Sess on1 2 3 4 5 6 7 8% Choice of Large Reward01020304050607080901000-sec delay5-sec delay 10-sec delay 20-sec delay?a,b ?a nsb Lithiu : New Cohort Training on Shor Delay Set lTraining Session1 2 3 4 5 6 7 8% Choice of Large Reward01020304050607080901 0Control:New Cohort Training on Short Delay Set nlTraining Se s o1 2 3 4 5 6 7 8% Choice of Large Reward01020304050607080901 00-sec delay5-sec delay 10-sec delay 20-sec delay?a,b ?a nsb 51 Figure 11. Delay Discounting Experiment 2 (short delay set only)?Baseline: Lithium treatment does not influence impulsive choice. Once baseline stability was reached, there were no longer group differences on choice of the large reward during larger delays. Controls shifted their choice behaviour from training such that both groups chose the large, delayed reward about 30% of the time during the longest delay (20 sec) (data from seventh week of testing, after nine weeks of lithium treatment). Where indicated, repeated-measures ANOVA reported an effect of Delay (a) and Group (b). Significance levels are represented as follows: ? = p < 0.001; ns = non-significant. Impulsive Choice:Experiment 2- Short Delay SetDelay to Large Reward (sec)0 5 10 20% Choice of Large Reward0102030405060708090100LithiumControlnsb Impulsive Choice:Experiment 1a- Large Delay SetDelay to Large Reward (sec)0 15 30 45% Choice of Large Reward010203040506078090100LithiumControl Impulsive Choice Experiment 1a- Large Delay Set Figure 1. Delay discounting Experiment 1a?Large delay set. Choice of the large reward significantly nsb ?a Lithium Control ?a 52 3.3.3 Effects of AMPH on delay discounting performance Animals from Experiment 1 were subject to an acute AMPH challenge once a stable baseline was reached for the shorter delay set (i.e. AMPH challenge took place after Experiment 1b). Choice of Large Reward Both groups discounted the large reward as the delay increased, however the groups discounted differently at different delays, producing a significant main effect of group and a delay by group interaction. Specifically, controls chose the larger reward more often than lithium-treated animals as the delay increased, maintaining the group difference noted during baseline. Both groups showed a significant effect of delay on choice (CHOICE OF LARGE REWARD?Delay: F(3, 39) = 42.88, p < 0.001; Group: F(1, 13) = 20.61, p = 0.001; Delay x Group: F(3, 39) = 5.14, p = 0.004; Control: Delay: F(3, 18) = 12.06, p < 0.001; Figure 12A; Lithium: Delay: F(3, 21) = 33.55, p < 0.001; Figure 12B; Appendix I). When analysed together, there were no differences between the groups on choice of the large reward when given AMPH (CHOICE OF LARGE REWARD?Dose x Group: F(3, 39) = 1.41, ns; Dose x Group x Delay: F(9, 117) = 0.87, ns). However, investigating the significant main effect of group showed that each dose of AMPH significantly increased choice of the large reward in control animals. In fact, the largest dose completely eliminated the effect of delay on choice, indicating a decrease in impulsive decision-making. Chronic lithium treatment completely blocked the effects of AMPH on choice behaviour as lithium-treated animals' discounting pattern remained unaffected across all doses of AMPH (CHOICE OF LARGE REWARD?Control: Dose: F(3, 18) = 6.73, p = 0.003; Figure 12A; Lithium: Dose: F(3, 21) = 0.39, ns; Figure 12B). For the control group, AMPH significantly increased choice of the large reward at all three doses, each of which produced a shallower discounting curve compared to saline. Conversely, AMPH did not alter the lithium-treated group's discounting pattern from baseline (EFFECT OF DOSE ON CHOICE?Control: saline vs. 0.3 mg/kg: t(6) = -3.50, p = 0.013; saline vs. 1.0 mg/kg: t(6) = -2.87, p = 0.029; saline vs. 1.5 mg/kg: t(6) = -2.98, p = 0.025; Figure 12A). These results indicate that chronic lithium treatment countered the effects of AMPH on choice behaviour, suggesting that the mood stabiliser might be involved in regulating stimulant-induced changes in impulsive choice or decision-making. Perseverative Responses, Nose-poke Responses, and Omissions All three doses of AMPH significantly increased perseverative responding in both groups (PERSEVERATIVE RESPONSES?Dose: F(3, 39) = 11.07, p < 0.001; saline vs. 0.3 mg/kg: t(14) = -2.30, p = 0.037; saline vs. 1.0 mg/kg: t(14) = -6.44, p < 0.000; saline vs. 1.5 mg/kg: t(14) = -3.94, p = 0.001; Delay: 53 F(3, 39) = 4.34, p = 0.010; Appendix J). Conversely, the delays significantly decreased perseverative responses overall. However, lithium-treated animals perseverated less with each increasing delay while controls perseverated more at 5-sec and less thereafter Although there was no main effect of lithium treatment on this measure, there was a trend toward a delay by group interaction where (PERSEVERATIVE RESPONSES? Delay: F(3, 39) = 4.34, p = 0.010; Group: F(1, 13) = 0.27, ns; Delay x Group: F(3, 39) = 2.53, p = 0.071, trend; Appendix J). Finally, there were no significant effects of AMPH, delay, or of lithium treatment on the number of anticipatory nose-pokes or omissions (Appendix J). Latencies The latency to initiate a trial and to choose between the large and small reward both significantly increased for all delays, while the latency to collect reward tended to increase at the longest delay (INITIATION LATENCY?Delay: F(3, 39) = 9.76, p < 0.001; CHOICE LATENCY?Delay: F(3, 39) = 6.92, p < 0.001; COLLECT LATENCY?Delay: F(3, 39) = 2.57, p = 0.068, trend; Appendix J). AMPH had the opposite effect on the latency to initiate a trial, decreasing response time and making animals quicker as the dose increased (INITIATION LATENCY?Dose: F(3, 39) = 4.23, p = 0.011; saline vs. 0.3 mg/kg: t(14) = 2.42, p = 0.030; saline vs. 1.0 mg/kg: t(14) = 2.87, p = 0.012; saline vs. 1.5 mg/kg: t(14) = 2.95, p = 0.010; Appendix J). Neither AMPH nor lithium treatment affected the latency to choose between the small and large reward or the latency to collect reward (Appendix J). Animals were generally slower to make nose-poke responses across all delays, but this effect was especially pronounced for the control group, which was significantly slower at the 10- and 20-sec delays. Conversely, lithium-treated animals had comparable latencies across delays (NOSE-POKE LATENCY?Delay: F(2, 26) = 4.29, p = 0.024; Group: F(1, 13) = 5.38, p = 0.037; Delay x Group: F(2, 26) = 4.40, p = 0.023; Control: Delay: F(2, 12) = 4.16, p = 0.043; Lithium: Delay: F(2, 14) = 0.41, ns; Appendix J). Only controls displayed a significant effect of AMPH on anticipatory nose-poke latency where the two highest doses made them slower, particularly at the 20-sec delay. Just as it blocked the effect of delay, lithium treatment blocked this AMPH-induced effect and animals maintained the same speed they showed during baseline. As a result of these differences, analyses reported several significant interactions between group, dose, and delay (NOSE-POKE LATENCY?Dose x Group: F(3, 39) = 6.53, p = 0.001; Dose x Delay: F(6, 78) = 4.74, p < 0.001; Dose x Delay x Group: F(6, 78) = 5.21, p < 0.001; Control: Dose: F(3, 18) = 5.84, p = 0.006; saline vs. 1.0 mg/kg: t(6) = -3.78, p = 0.009; saline vs. 1.5 mg/kg: t(6) = -3.32, p = 0.016; Dose x Delay: F(6, 36) = 6.18, p < 0.001; ?AT 20-sec DELAY: saline vs. 1.0 mg/kg: t(6) = -4.28, p = 0.005; saline vs. 1.5 mg/kg: t(6) = -4.12, p = 0.006; Lithium: Dose: F(3, 21) = 1.04, ns; Appendix J). 54 Control:Amphetamine and Impulsive ChoiceDelay to Large Reward (sec)0 5 10 20% Choice of Large Reward 0102030405060708090100SalineAMPH 0.3 mg/kgAMPH 1.0 mg/kgAMPH 1.5 mg/kgLithium: Amphetamine and Impulsive ChoiceDelay to L ge R ward (sec)0 5 10 20% Choice of Large Reward0102030405060708090100Control: AMPH and Impulsive Choice Lithium: AMPH and Impulsive Choice A B Figure 1. Lithium attenuates the effects of D-amphetamine (AMPH) on delay discounting ?b ?a nsb ?a Control:Retraining on Short Delay SetTraining Session1 2 3 4 5 6 7 8% Choice of Large Reward01020304050607080901000-sec delay5-sec delay10-sec delay20-sec delaySaline AMPH 0.3 mg/kg AMPH 1.0 mg/kg AMPH 1.5 mg/kg Figure 12. Lithium attenuates the effects of AMPH on delay discounting performance. (A) Control animals significantly increased their choice of the large reward across AMPH doses, while (B) there was no effect of dose for the lithium-treated group, suggesting that chronic lithium treatment may block stimulant-induced changes in choice behaviour. Where indicated, repeated-measures ANOVA identified a significant effect of Delay (a) and Dose (b); significance levels are reported as follows: ? = p < 0.001; ? = p < 0.01; ns = non-significant. 55 3.3.4 Effects of YHB on delay discounting performance Choice of Large Reward During this YHB challenge, animals continued to discount the large reward as the delays became longer. When analysed together, there were no differences between the groups on choice of the large reward when given YHB (CHOICE OF LARGE REWARD?Dose x Group: F(3, 39) = 0.66, ns; Dose x Group x Delay: F(9, 117) = 0.84, ns). However, lithium-treated animals tended to increase choice of the large reward at the lowest dose of YHB, indicating that lithium treatment might decrease impulsive decision-making under heightened arousal. On the contrary, YHB did not affect choice of the large reward in control animals, suggesting that states of heightened arousal or stress do not affect impulsive choice. (CHOICE OF LARGE REWARD?Delay: F(3, 39) = 82.10, p < 0.001; Dose: F(3, 39) = 3.13, p = 0.036; vehicle vs. 1.0 mg/kg: t(14) = -3.33, p = 0.005; Group: F(1, 13) = 3.78, p = 0.074, trend; Control: Dose: F(3, 18) = 1.18, ns; Lithium: Dose: F(3, 21) = 2.67, p = 0.074, trend; vehicle vs. 1.0 mg/kg: t(7) = -3.36, p = 0.012; Figure 13A and B, respectively; Appendix K). This group difference, though nearly significant, was relatively maintained from baseline, which suggests that lithium treatment may alter arousal-induced changes in choice behaviour. Hence, these data indicate that during a mild stressor, chronic lithium treatment might affect decision-making and impulsive choice through arousal-mediated effects. Nose-pokes Responses, Perseverative Responses, and Omissions The lowest dose of YHB significantly increased anticipatory nose-poke responses; there were no effects of delay or lithium treatment (NOSE-POKES?Dose: F(3, 39) = 3.26, p = 0.032; vehicle vs. 1.0 mg/kg: t(14) = -2.85, p = 0.013; Delay: F(2, 26) = 2.42, ns; Group: F(1, 13) = 0.00, ns; Appendix L). There were no effects of YHB, delay, or lithium treatment on perseverative responding (PERSEVERATIVE RESPONSES?Dose: F(3, 39) = 1.67, ns; Delay: F(3, 39) = 2.10, ns; Group: F(1, 13) = 0.00, ns; Appendix L). The groups tended to omit differently at different doses of YHB, such that controls omitted slightly more trials at the low and medium doses whereas lithium-treated animals omitted fewer trials at these doses. As a result of these differences, analyses revealed a nearly significant dose by group interaction where lithium treatment tended to reduce omissions at the lowest dose of YHB (OMISSIONS?Dose: F(3, 39) = 0.13, ns; Group: F(1, 13) = 0.11, ns; Dose x Group: F(3, 39) = 2.80, p = 0.053, trend; Control: Dose: F(3, 18) = 0.86, ns; Lithium: Dose: F(3, 18) = 2.30, ns; vehicle vs. 1.0 mg/kg: t(7) = 5.02, p = 0.002; Appendix L). 56 Latencies Yohimbine did not generally affect latency measures, except when the highest dose significantly increased the latency to choose between the "delay" and "immediate" holes; lithium treatment did not alter this effect (CHOICE LATENCY?Dose: F(3, 33) = 10.17, p < 0.001; vehicle vs. 5.0 mg/kg: t(12) = -5.41, p < 0.001; Group: F(1, 11) = 0.01, ns; Appendix L). YHB did not affect reaction time to collect reward, while neither YHB nor lithium treatment affected the latencies to initiate a trial or to make an anticipatory nose-poke response (COLLECTION LATENCY?Dose: F(3, 39) = 0.72, ns; INITIATION LATENCY?Dose: F(3, 39) = 0.70, ns; Group: F(1, 13) = 0.44, ns; NOSE-POKE LATENCY?Dose: F(3, 39) = 0.79, ns; Group: F(1, 13) = 0.17, ns; Appendix L). The duration of the delay to the large reward, on the other hand, had an overall significant effect on latency measures, increasing the time taken for subjects to initiate a trial and to respond (INITIATION LATENCY?Delay: F(3, 39) = 26.32, p < 0.001; RESPONSE LATENCY?Delay: F(3, 33) = 5.76, p = 0.003; Appendix L). The delays altered the latency to collect reward differently for each group, producing a significant delay by group interaction. Further analyses specified that controls tended to be slower to collect reward at the 5-sec delay, whereas the lithium-treated group was unaffected by the delays (COLLECTION LATENCY?Delay: F(3, 39) = 3.23, p = 0.032; Group: F(1, 13) = 0.58, ns; Delay x Group: F(3, 39) = 3.87, p = 0.016; DELAY: 0- vs. 5-sec delay: t(14) = -1.77, p = 0.098, trend; Control: Delay: F(3, 18) = 4.57, p = 0.015; Lithium: Delay: F(3, 21) = 1.61, ns; Appendix L). Finally, the magnitude of the delay did not affect the latency to make an anticipatory nose-poke response in the food tray (NOSE-POKE LATENCY?Delay: F(2, 26) = 1.00, ns; Appendix L). 57 Control:Yohimbine and Impulsive ChoiceDelay to Large Reward (sec)0 5 10 20% Choice of Large Reward 0102030405060708090100Vehicle YHB 1.0 mg/kg YHB 2.0 mg/kg YHB 5.0 mg/kg Lithium:Yohimbine and Impulsive ChoiceDelay to Large Reward (sec)0 5 10 20% Choice of Large Reward0102030405060708090100 A B Figure 1. Effects of yohimbine (YHB) on delay discounting performance. (A) In response to Control: YHB and Impulsive Choice Lithium: YHB and Impulsive Choice ?a ?b nsb ?a Control:Retraining on Short Delay SetTraining Session1 2 3 4 5 6 7 8% Choice of Large Reward01020304050607080901000-sec delay5-sec delay10-sec delay20-sec delayVehicle YHB 1.0 mg/kg YHB 2.0 mg/kg YHB 5.0 mg/kg Figure 13. Effects of YHB on delay discounting performance. (A) In response to increasing doses of YHB, controls significantly increased their choice of the large reward as the delays became longer. (B) Lithium-treated rats increased their choice of the larger delayed reward as the delay increased, although lithium treatment tended to attenuate this YHB-induced change in choice behaviour. These results suggest that during a mild stressor, chronic lithium treatment might affect impulsive choice and decision-making through arousal-mediated effects. Where indicated, repeated-measures ANOVA identified significant effects of Delay (a) and Dose (b). Significance levels are reported as follows: ? = p < 0.001; ? = 0.05 < p < 0.10, trend; ns = non-significant. 58 3.4 Effects of Chronic Lithium Treatment on Gene Expression The present study investigated the effects of chronic lithium treatment on gene expression by quantifying the fold-change in levels of mRNA in lithium-treated animals compared to controls. Quantitative PCR analyses revealed that chronic lithium treatment significantly downregulated gene expression in the frontal cortex yet upregulated gene expression in the NAc (Table 2, Figure 14; see Glossary for full name of target genes; see Appendix M for data and analyses). Gene Expression in the mPFC Lithium treatment significantly decreased mRNA levels for the neurotrophic factor BDNF (t(11) = -2.30, p = 0.041), the signalling molecules ERK1 and ERK2 (t(11) = -2.37, p = 0.037; t(11) = -2.22, p = 0.049, respectively), and for the pro-apoptotic protein GSK-3? (t(11) = -2.88, p = 0.015). Lithium treatment also decreased mRNA levels for the serotonergic 5-HT2C receptor subtype (t(11) = -1.94, p = 0.079, trend) and the ?2A- and ?1-ARs (t(11) = -1.89, p = 0.085, trend; t(11) = -1.80, p = 0.100, trend, respectively), although these changes fell short of significance. Gene Expression in the OFC Lithium significantly decreased mRNA levels for the serotonergic 5-HT2A receptor subtype (t(11) = -2.43, p = 0.033), the ?1-AR (t(11) = -2.80, p = 0.017), the M1 muscarinic cholinergic receptor subtype (t(11) = -2.24, p = 0.047), the neurotrophic factor BDNF (t(11) = -2.62, p = 0.024), the transcription factor CREB (t(11) = -2.63, p = 0.023), the signaling kinase ERK2 (t(11) = -2.24, p = 0.047), the apoptotic factor cdk5 (t(11) = -2.92, p = 0.014), the scaffolding protein PSD-95 (t(11) = -2.36, p = 0.038), and for the vesicular-associated protein CSP (t(11) = -2.50, p = 0.029). Gene Expression in the NAc In contrast to its effects in the OFC, lithium treatment increased mRNA levels for the M1 muscarinic cholinergic receptor (t(8) = 3.16, p = 0.013). There were no other differences in gene expression within the NAc. Finally, lithium treatment did not alter gene expression for the serotonergic 5-HT1A receptor subtype, the DA D1 and D2 receptor subtypes, the M2 muscarinic cholinergic receptor subtype, the TrkB receptor, nor for the immediate early gene c-fos in any brain region (Appendix M). 59 Brain Region Brain Region Gene of Interest mPFC OFC NAc Gene of Interest mPFC OFC NAc ?FosB ? ? ? CREB ? ?? ? 5-HT1a ? ? ? CSP ? ?? ? 5-HT2a ? ?? ? D1 ? ? ? 5-HT2c ? ? ? D2 ? ? ? ?1a-AR ? ? ? ERK1 ?? ? ? ?2a-AR ? ? ? ERK2 ?? ?? ? ?1-AR ? ?? ? Gsk-3? ?? ? ? ?2-AR ? ? ? M1 ? ?? ?? Bcl-2 ? ? ? M2 ? ? ? BDNF ?? ?? ? NGF ? ? ? cdk5 ? ?? ? PSD-95 ? ?? ? c-fos ? ? ? TrkB ? ? ? Table 2. Effects of chronic lithium treatment on gene expression in the mPFC, OFC, and the NAc. Samples were extracted from animals tested on the 5-CSRTT and were processed via qPCR to assess the effects of chronic lithium treatment on gene expression. Mean threshold cycle (CT)-values were normalized to the housekeeping gene GAPDH. Brain regions are abbreviated as follows: mPFC = medial prefrontal cortex; OFC = orbitofrontal cortex; NAc = nucleus accumbens. Upright, downward, and two-headed arrows indicate increased, decreased, and no change in gene expression relative to controls, respectively. Where indicated, independent-samples Student?s t-test identified a significant difference between controls (n = 8) and lithium-treated rats (n = 8). Significance levels are represented as follows: ??/?? = p < 0.05; ?/? = 0.05 < p < 0.10, trend; ? = no change. (See Glossary for full name of target genes). 60 mPFC OFC NAc Figure 14. Effects of chronic lithium treatment on mRNA levels within the mPFC, OFC, and the NAc. Samples were extracted from animals tested on the 5-CSRTT and were processed via qPCR to assess the effects of chronic lithium treatment on gene expression. Mean threshold cycle (CT)-values were normalized to the housekeeping gene GAPDH; data for lithium-treated animals were calculated relative to control values. Brain regions are abbreviated as follows: mPFC = medial prefrontal cortex; OFC = orbitofrontal cortex; NAc = nucleus accumbens. Where indicated, independent samples Student?s t-test identified lithium-treated rats as significantly different from controls. Significance levels are represented as follows: * = p < 0.05; ? = 0.05 < p < 0.10, trend. (See Glossary for full name of target genes). NAcRelative (normalized) expression0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5Gene of interestmPFCRelative (normalized) expression0.0 0.4 0.8 1.2 1.6 2.0Gene of interestHpcRelative (normalized) res ion0.0 0.5 1.0 1.5 0 2.5Gene of InterestOFCRelative (normalized) expr ssion0.0 0.4 0.8 1.2 1.6 2.0Gene of interest?FosB 5-HT1A 5-HT2A 5-HT2C ?1A-AR ?2A-AR ?1-AR ?2-AR Bcl-2 BDNF cdk-5 c-fos CREB CSP D1 D2 ERK1 ERK2 Gsk-3? M1 M2 NGF PSD-95 TrkB Lithium Control ?FosB 5-HT1A 5-HT2A 5-HT2C ?1A-AR ?2A-AR ?1-AR ?2-AR Bcl-2 BDNF cdk-5 c-fos CREB CSP D1 D2 ERK1 ERK2 Gsk-3? M1 M2 NGF PSD-95 TrkB ?FosB 5-HT1A 5-HT2A 5-HT2C ?1A-AR ?2A-AR ?1-AR ?2-AR Bcl-2 BDNF cdk-5 c-fos CREB CSP D1 D2 ERK1 ERK2 Gsk-3? M1 M2 NGF PSD-95 TrkB ?FosB 5-HT1A 5-HT2A 5-HT2C ?1A-AR ?2A-AR ?1-AR ?2-AR Bcl-2 BDNF cdk-5 c-fos CREB CSP D1 D2 ERK1 ERK2 Gsk-3? M1 M2 NGF PSD-95 TrkB ? * * * * * ? * * * * * * * * * 61 4 Discussion The experiments described herein extend our current understanding of lithium's therapeutic effects and molecular actions. We demonstrate that chronic exposure to therapeutic doses of lithium in rodents affects behaviour in models of impulsivity and attention, influences pharmacologically-induced changes in behaviour, and alters gene expression. Results obtained from the five-choice serial reaction time task (5-CSRTT), a rodent model of attention and impulsive action, suggest that chronic lithium treatment may enhance attentional focus and decisional processing, and might block stress-induced impulsive action. Results gathered from the delay discounting task (DDT), a rodent model of impulsive choice, indicate that chronic lithium treatment might accelerate task acquisition, enhance behavioural flexibility and reversal learning, and might attenuate stimulant-induced changes in choice behaviour. Furthermore, real-time PCR data reveal that lithium treatment may modulate gene expression in brain regions and molecular pathways relevant to impulse control and/or in areas associated with psychiatric disorders. Lithium's effects on behaviour, pharmacological interactions, and on gene expression are discussed in turn below. 4.1 Effects of Chronic Lithium Treatment on the Five-Choice Serial Reaction Time Task (5-CSRTT) 4.1.1 Chronic lithium treatment improves attention and performance but does not influence impulsive action Attention This study shows that chronic lithium treatment enhances accuracy of target detection on the 5-CSRTT. Lithium-treated and control animals both reached typical 5-CSRTT baseline levels of performance (> 80% accuracy; < 15% omissions; Robbins, 2002) after five weeks of testing (14 weeks of lithium-supplemented diet). Lithium-treated animals outperformed controls, indicating that chronic lithium treatment may enhance attentional processes and/or cognitive function. This proposition is supported by other reports claiming that lithium improves performance and memory, and may have potential as a cognitive enhancer in rodents (Gallo et al., 1990; Nocjar et al., 2007; Tsaltas & Kontis, 2009; Tsaltas et al., 2007a, 2009; Son, Yu, Hwang et al., 2003). For example, lithium enhances overall performance in a rodent spatial working memory task by increasing reward retrieval accuracy and efficiency (Nocjar et al., 2007). Lithium treatment also promotes long-term 62 retention of weak aversive contingencies in conditioned place preference tests that involve passive avoidance to a foot shock paradigm (Nocjar et al., 2007; Tsaltas et al., 2007a). In a model of appetitive discrimination, lithium promotes attentional focus and discrimination between cues that signal reinforcement and improves the ability to ignore distracting cues (Cappeliez et al., 1989; Cappeliez & Moore, 1988; Cappeliez & White, 1981). In this case, lithium treatment might enhance the ability to remain vigilant, to retain information obtained 'on-task,' and to use this information to proceed accordingly, implying that lithium might improve working memory, or memory for trial-unique stimuli or events (Prior, Schwegler & Ducker, 1997). A recent study by Ohmura and colleagues (2011) investigated the effects of lithium using a paradigm of attention and impulsivity similar to the one used herein, yet did not report cognitive enhancing effects of lithium (Ohmura et al., 2011). However, several methodological differences between our studies may have contributed to this discrepancy. Rodents in our experiment started their lithium-supplemented diet two weeks before training on the 5-CSRTT, and treatment continued during behavioural testing. In contrast to this chronic lithium feeding regime, rodents in Ohmura's group had already completed training before receiving any lithium, and were injected with acute doses of lithium prior to behavioural testing. Levels of lithium spike following injection and serum levels are clinically relevant by 12 h post injection (Chen, Rajkowska, Du et al., 2000; Tsaltas et al., 2007a). Although Ohmura's study did not report serum lithium levels at the time of testing, a study by Tsaltas and colleagues (2007a) used the same dose and method of administration and reported that lithium blood concentrations were above the recommended therapeutic range at the time of behavioral assessment (2 mmol/kg i.p. produced serum levels of 1.7 mmol/L within the first hour). Since Ohmura's study tested their rodents 40 min post injection, serum lithium levels during the task were likely similar and above the suggested therapeutic range. In contrast to these studies, the lithium diet and feeding procedure used in the present study ensured a more stable and clinically relevant drug serum and brain levels (CANMAT, 2006; Chen et al., 2000; Gelenberg et al., 1989; Kovacsis & Gould, 2010; Maletzky & Shore, 1978; NICE, 2006; Nocjar et al., 2007; O'Donnell & Gould, 2007; Treiser et al., 1981) than injection (Chen et al., 2000) at the time of testing (0.89 ? 0.044 mmol/L), without approaching the range of toxicity (Brumm, van Gorp & Wirshing, 1998; Chen et al., 2000; Smith, 2009; Finley, Warner & Peabody, 1995; Wood et al., 1986; Young & Macritchie, 2004). Alternatively, Ohmura's group (2011) may have observed a lithium-induced decrease in premature responding because rodents were assessed using the three-choice serial reaction time task (3-CSRTT), a simplified version of the 5-CSRTT (Carli et al., 1983). Although very similar to the 5-CSRTT, 63 the 3-CSRTT is conducted in a three-hole operant chamber and rodents respond in one of three, instead of five, holes for a reward. In addition, the light stimulus in Ohmura's study was presented for 1 sec, which is double the duration of our light stimulus (0.5 sec). Accordingly, in our experiment, reducing the stimulus duration and having two extra apertures available for stimulus presentation increased task difficulty; these features placed additional load on attentional resources and processing such that rats performing the 5-CSRTT were subject to increased cognitive demand. Interestingly, although increasing cognitive demand typically weakens attentional ability and overall performance (Fletcher et al., 2007; Sirvi? et al., 1993), evidence suggests that lithium might in fact be most beneficial under these conditions (Nocjar et al., 2007; Tsaltas et al., 2007a; de Vasconcellos, Tabajara, Ferrari et al., 2003). Hence, the different drug regimen and less demanding task parameters used in Ohmura's group (2011) may have resulted in the absence of such an enhancing effect. Impulsive Action The study herein shows that lithium treatment does not alter premature responding, which contrasts the mood stabilizer's enhancing effect on attentional performance, suggesting that lithium treatment might boost cognitive performance without affecting behavioural inhibition or motor impulsivity. These results counter those from Ohmura's group (2011), which claims that an acute dose of lithium decreases premature responses on the 3-CSRTT (Ohmura et al., 2011). As discussed previously, the different treatment regime employed in Ohmura's study likely contributes to our incongruous findings regarding lithium's effects on attention as well as impulsive action. Furthermore, although our studies' behavioural paradigms are similar, the baseline number of premature responses on the 3-CSRTT is generally higher than on the 5-CSRTT (Tsutsui-Kimura, Ohmura, Izumi et al., 2009). In fact, the number of premature responses reported in Ohmura's study (2011) is more than double the number of premature responses observed in our study. Consequently, a relatively high number of prematures at baseline will make any decrease in prematures following a drug challenge more noticeable. However, as noted previously, since animals typically make fewer prematures on the 5-CSRTT than the 3-CSRTT (Tsutsui-Kimura et al., 2009), the nature of our paradigm may have masked lithium's influence on impulsive responding. This explanation is unlikely however, as decreases in premature responding have been observed using the 5-CSRT by our group and others (e.g. Winstanley et al., 2010). Also noteworthy is the notion that Wistar/ST rodents, the strain used in Ohmura's study, typically display a higher number of premature responses on the 3-CSRTT than other strains (Ohmura et al., 2009; Tsutsui-Kimura et al., 2009). Since we used Long Evans rodents, the difference in our rodent strains could have contributed to our discrepant findings regarding lithium treatment on motor 64 impulsivity (Ohmura, Yamaguchi, Futam et al., 2009; Robinson Eagle, Mar et al., 2008b; Smith, 2009; Tsutsui-Kimura et al., 2009). As mentioned in sub-section 1.2.2 "Animal models of impulsivity," the 5-CSRTT is the rodent analogue of the human Continuous Performance Task (CPT) used clinically to assess impulse control. Clinical studies with bipolar patients show that the severity of mania correlates with the degree of commission errors on the CPT (analogous to premature responses/ impulsive responding on the 5-CSRTT) (Sax et al., 1998; Swann et al., 2001, 2002, 2003, 2005b, 2009b). However, there does not seem to be a relationship between CPT performance and treatment (Shaw, Stokes, Mann & Manevitz, 1987; Swann et al., 2001, 2009b), which is comparable to lithium's null-effect on premature responses in our rodent version of the CPT. On the other hand, since the attention score on the CPT is more strongly related to psychiatric illness (Swann et al., 2002), our findings imply that lithium treatment can especially benefit the cognitive decline associated with BD and other disorders. In the present study, lithium treatment did not affect speed of responding or other markers of motor activity. Interestingly, individuals in some impulsive populations as well as medicated manic patients respond faster than normal controls (Daugherty et al., 2000). Along with findings presented herein, Dougherty's report (2000) oppose those from previous studies that show that lithium increases reaction times and suppresses locomotor activity in a dose-dependent manner in bipolar patients and animals (Ohmura et al., 2011; Shaw et al., 1987; Smith, 2009). However, since a chronic regime of lithium does not influence general motor activity or motivation to perform behavioural tasks (Tsaltas et al., 2007a), the effects on reaction times and locomotor activity might only appear following subchronic lithium treatment or when testing occurs shortly after treatment onset, (Cappeliez & Moore, 1990; Ohmura et al., 2011; Tsaltas et al., 2007a; Tsaltas & Kontis, 2009), or under different paradigm conditions (Fletcher et al., 2007; Ohmura et al., 2011; Tsutsui-Kimura et al., 2009). These propositions fit well with the present study as the major indices of motivation and general motor activity (latencies to respond or to collect reward, trials initiated, omissions, etc) did not differ between the lithium-treated and control groups. Nevertheless, the wide range of findings indicates that more research is needed to address the effects of lithium treatment on speed of responding and locomotor activity. Altogether, our results indicate that lithium treatment magnifies attention and enhances overall performance, all of which occur when tested using a paradigm that is inherently more challenging and cognitively demanding. Some clinical data seem to contradict these findings; for example, psychiatric patients and normal volunteers who receive lithium report mental slowing and blurring (Judd, 1979; Judd, Hubbard, Janowsky et al., 1977a, 1977b; Kropf & M?ller- Oerlinghausen 1979; Lenzer, Eastwood & 65 Street, 1989). However, these effects do not necessarily imply cognitive dysfunction (O'Donnell & Gould 2007; Pachet & Wisniewski 2003; Stip, Dufresne, Lussier & Yatham, 2000), as lithium-treated bipolar patients perform within a normal range on memory and cognitive tasks (Lund et al., 1982; Marusarz et al., 1981). In fact, lithium's cognitive enhancing effects are not only demonstrated in normal animals (as described above), but lithium is also thought to facilitate cognitive recovery in rodents that suffered transient global cerebral ischemia (Yan, Hou, Wu et al., 2007), traumatic brain injury (Zhu, Wang, Han & William, 2010), and in human patients with dementia (Terao, Nakano, Inoue et al., 2006) and Alzheimer's disease (Forlenza, Diniz, Radanovic et al., 2011; Nunes, Forlenza & Gattaz, 2007). As sustained attention and behavioural performance are generally impaired in non-medicated patients with BD, these findings may be important in understanding lithium's clinical efficacy. 4.1.2 Chronic lithium treatment does not block AMPH-induced impairments in attention or behavioural control but might influence decisional processing Attention and Impulsive Action This study shows that acute AMPH administration decreases accuracy of target detection and exacerbates premature responding on the 5-CSRTT, and that chronic lithium treatment does not block these effects. Results from this acute AMPH challenge are in line with other animal studies which also demonstrate that AMPH impairs performance during tasks of sustained attention (Cole & Robbins, 1987, 1989; Fletcher et al., 2007; Kondrad & Burk, 2004) and that AMPH increases premature responding on serial reaction time tasks (Cole & Robbins, 1987; Evenden & Ryan, 1996; Fletcher et al., 2007; Navarra et al., 2007; Pattij, Janssen, Vanderschuren et al., 2007; van Gaalen et al., 2009). Furthermore, our results indicate that the detrimental effects of AMPH on 5-CSRTT performance are dose-dependent, such that higher doses of AMPH result in a greater decrease in performance and a greater increase in premature responding. In keeping with the notion that AMPH administration serves as a model of mania, these results parallel clinical data that indicate an association between the severity of mania (analogous to the higher dose of AMPH used in this experiment) and increased commission errors, and incorrect responses on the CPT (measure of rapid-response impulsivity/ premature responses and lower accuracy scores on the 5-CSRTT, respectively) (Sax et al., 1998; Swann et al., 2001, 2002, 2003). Interestingly, this relationship emerges regardless of whether patients receive medical treatment such as lithium (Swann et al., 2001, 2003), which is in line with our finding that lithium treatment did not influence the AMPH-induced decline in accuracy scores or the increase in premature responding. 66 Further supporting our results, Silverstone's group (1998) reported that lithium treatment does not block AMPH's physiological or psychological effects in healthy volunteers (Silverstone, Pukhovsky & Rotzinger, 1998). However, an important factor to consider about Silverstone's study? which also applies to our study? is that subjects received only a single dose of AMPH whereas AMPH regimes that truly parallel mania tend to last longer (Frey et al., 2006a). Thus, future studies investigating the effects of chronic lithium treatment on AMPH-induced impulsivity and attentional performance should consider a more chronic or long-term AMPH regimen as lithium might only influence AMPH upon repeated exposure to the stimulant. On a similar note, lithium's effects on AMPH might differ according to the duration of lithium treatment itself, and might be dose- (van Gaalen et al., 2009) and task- (Fletcher et al., 2007) dependent. In this respect, many studies contend that only acute, and not chronic, lithium treatment counteracts AMPH-induced motor activity (Cappeliez & Moore, 1990; Cox et al., 1971; Fessler et al., 1982, 2007; Mandell & Knapp, 1976; Matussek & Linsmayer, 1968; Smith, 2009; Steinberg & Tomkiewicz, 1971). Results from our study are in line with this argument, as our chronic lithium regime did not block the effects of AMPH on motor impulsivity. Future studies might address this point by challenging subjects with AMPH earlier during lithium treatment. Other Behavioural Measures In keeping with previous reports, AMPH increased the latency to collect reward but also increased omissions and decreased the number of trials completed. Given the former observation, it is unlikely that the latter findings are indiciative of reduced task engagement or motivation. Instead, the changes in these measures are consistent with disruptions in attentional focus (Robbins 2002). Altogether, the present study shows that acute treatment with AMPH disrupts performance on the 5-CSRTT, suggesting that central nervous stimulation might impair attentional focus and increase motor impulsivity, and that chronic lithium treatment might not attenuate these effects. 4.1.3 Chronic lithium treatment blocks YHB-induced impairments in attention and impulsive action and may increase decisional processing In summary, this study shows that acute administration of YHB, a potent ?2-AR antagonist used as a pharmacological stressor, dose-dependently affected 5-CSRTT performance. In general, lower doses of YHB increased premature responding and decreased the latencies to respond correctly and to collect reward, while higher doses impaired accuracy of target detection and increased all response latencies as well as omissions. All three doses increased anticipatory nose-poking at the food tray yet neither dose affected perseverative responding at the response apertures. Interestingly, animals under 67 chronic lithium treatment were more accurate and made fewer premature responses than controls, the latter being especially prominent at the highest dose of YHB. The highest dose of YHB also significantly increased the latency to make an incorrect response and tended to increase omissions for the lithium-treated group as well. These results suggest that chronic lithium treatment might counteract arousal-induced impairments in attentional focus and behavioural inhibition, and might increase decisional processing when response outcome is uncertain. Attention YBH tended to decrease accuracy scores in controls, especially at the medium dose. This finding contradictrs many lines of evidence which show that increasing NA activity via ?2-AR antagonism or blocking the NA transporter mildly stimulates and enhances behavior, thereby improving overall attention, performance, and cognitive function (Bymaster et al., 2002; Cedarbaum & Aghajanian, 1976, 1977; Charney et al., 1982, 1983; Liu et al., 2009; Navarra et al., 2007; Robinson et al., 2007, 2008b; Sirvi? et al., 1993; Swann et al., 1983, 1987, 2005a). On the other hand, other studies report no change in attentional performance following an acute YHB challenge (Sun et al., 2010; Swann et al., 2005b). These latter studies might be more in line with our results considering that only the moderate dose of YHB decreased accuracy scores, and this effect was at the trend level. Nevertheless, in the present study, the slight performance impairment observed in the control group at the moderate dose of YHB suggests that increasing the level of arousal negatively impacts attentional focus and cognitive functioning. By comparison, lithium- treated animals maintained significantly higher accuracy scores than controls suggesting that chronic lithium treatment might buffer arousal- or stress-mediated effects on attention and performance. This finding is consistent with the notion that lithium antagonizes ?2-AR-mediated behaviours in animals (De Souza et al., 1986; Goodwin et al., 1986) and attenuates the adverse effect of chronic stress on cognitive functioning (de Vasconcellos et al., 2003). However, further studies are required in order to clarify the role of NA on performance and the way in which the noradrenergic system interacts with lithium in order to block its detrimental effects on task performance and impulsive behaviour. This idea is further explored in sub-section 4.3 "Effects of Chronic Lithium Treatment on Gene Expression," which considers the genes altered by lithium treatment and how these biochemical changes translate into the behavioural pattern we observed. Impulsive Action This experiment demonstrates that low and moderate doses of YHB significantly increased premature responding and that lithium treatment significantly attenuated this effect. We also show that lithium-treated rats tended to make fewer premature responses at the highest dose of YHB than 68 they did during baseline. These results indicate that stimulating noradrenergic activity by blocking ?2-ARs increases impulsive action and that lithium treatment attenuates this effect, thereby mitigating arousal- or stress-induced increases in behavioural disinhibition. YHB had a similar effect on other measures, where moderate doses significantly decreased the latency to collect reward. In line with these results, modest doses of YHB reduce the latency to respond in rodents (Sun et al., 2010) and in humans (Swann et al., 2005a). This relationship aligns with the notion of impulsivity as a tendency toward unplanned and rapid responses (Swann et al., 2005b) and supports our results regarding the YHB-induced increase in premature responding. Other reports show that YHB, as well as other ?2-AR blockers, exacerbate impulsive action in rodents (Koskinen et al., 2003; Liu et al., 2009; Ruotsalainen et al., 1997; Sirvi? et al., 1993, 1994; Sun et al., 2010) and increase impulsivity in healthy control subjects assessed on the CPT and delay discounting paradigms (Swann et al., 2005a). As mentioned previously, individuals with bipolar mania and substance abuse generally show increased impulsive responding on the CPT (Dougherty et al., 2004; Moeller et al., 2004; Swann et al., 2003, 2004), and this impulsive responding worsens according to the severity of manic episodes (Swann et al., 2001). In the same way, administering YHB to BD patients increases this response impulsivity on the CPT and can even induce mania (Price et al., 1984; Swann et al., 2001, 2003), consistent with the association between increased NA function and severity of mania (Clark & Goodwin, 2004; Mendlewicz et al., 1989; Swann et al., 1983, 1987, 2003). Interestingly, YHB affects other behavioural expressions of impulsivity. For example, YHB reinstates drug-seeking in rodents (Dalley et al., 2007; Shepard et al., 2004) and in humans (Krishnan-Sarin et al., 2007), which is a behaviour relieved with lithium treatment (Cassidy et al., 2001; Flemenbaum, 1974; Geller et al., 1998; Swann et al., 2004, 2009a; van Kammen & Murphy, 1975). The association between NA activity and psychiatric disorders and/or with other ICDs is well documented, as are lithium's therapeutic effects on cognition and impulsive behaviours. Our results suggest that lithium treatment might attenuate impulsive responding during stressful or arousing conditions by regulating noradrenergic function, which might, at last in part, account for lithium's therapeutic efficacy in mania, substance abuse, and other ICDs (Arnsten et al., 1999; Campbell et al., 1995; Cassidy et al., 2001; Cole & Robbins, 1989; Dostal & Zvolsky, 1970; Flemenbaum, 1974; Geller et al., 1998; Hollander et al., 2005; Kim et al., 2006; Luchins & Dojka, 1989; Malone et al., 2000; Osman & Loschen, 1992; Sheard, 1971; Sheard et al., 1976; Swann, 2009; Swann et al., 2004, 2005b; Tupin et al., 1973; van Kammen & Murphy, 1975; Winchel & Stanley, 1991). Hence, the relationship between arousal and lithium treatment in models of impulsivity warrant further investigation. 69 4.2 Effects of Chronic Lithium Treatment on the Delay Discounting Task (DDT) 4.2.1 Chronic lithium treatment enhances reversal learning and facilitates behavioural flexibility The DDT assesses impulsive choice by measuring the rats' tendency to choose smaller, immediate food rewards instead of larger, delayed rewards over the course of four ten-trial blocks. This task successfully measures the tendency to discount a large reward in situations where a delay precedes its delivery, such that the delay reduces the reward's value?i.e. the negative valuation associated with the delay outweighs the reward's positive valuation. In this way, the DDT measures an aspect of impulsivity or lack of self-control as an exaggeration in the normal decrease in value over time (Evenden & Ryan, 1996; Monterosso & Aimslie, 1999). Individuals are considered more impulsive when they decrease their choice of the large reward when delays are longer, thus generating a hyperbolic discounting curve (Monterosso & Aimslie, 1999). Such is the case for patients with BD who, compared to controls, are unable to wait for a delayed reward or gratification (Swann et al., 2002). This characteristic increases impulsive choice on the DDT and, similar to our study, medication such as lithium does not attenuate impulsive decision-making (Swann et al., 2009a). Experiment 1a?Large delay set There were no differences between lithium-treated and control rats on discounting patterns with the original longer delays (0, 15, 30, and 45 sec); both groups chose the smaller, immediate reward as soon as the delays were presented. In order to obtain a more meaningful discounting curve, where choice of the larger reward would gradually decrease across delays, the delays were reduced (Mar & Robbins, 2007) to 0, 5, 10, and 20 sec and animals were retrained on the task using these shorter delays. Experiment 1b?Short delay set Lithium-treated rats were much quicker to adapt to the new delays and adjusted their choice behaviour within the first week of re-training while controls required extra training sessions to adjust their choice response pattern. Once both groups reached baseline performance levels, lithium-treated rats chose the smaller, immediate reward more often than controls. Furthermore, lithium-treated animals produced similar discounting pattern between the two sets of delays and did not alter the distribution of their choice response at 15 and 20 sec between the two sets of delays. Meanwhile, during the shorter delay set, controls chose the large, delayed reward twice as much as the lithium-treated group and twice as much as they did during the original, longer delay set. 70 As controls chose the large reward more often than the lithium-treated animals, one might reason that lithium-treated rats displayed more impulsive decision-making. However, this explanation is unlikely to be the case since lithium treatment did not increase impulsive choice in animals trained only using the short delay set (Experiment 2). In contrast to controls, lithium-treated animals were quicker to adapt their behaviour in response to the new contingencies at play and even maintained the same discounting pattern despite the change in stimulus-response-reward associations. In this way, our results further illustrate that lithium might enhance attention, and also suggest that lithium might enhance the capacity for reversal learning and facilitate cognitive and behavioural flexibility. Studies investigating the effects of lithium treatment on behavioral flexibility or response inhibition are extremely rare (Tsaltas & Kontis, 2009). The need to investigate the effects of lithium on higher order tasks is warranted as lithium's enhancing effects on cognition might be more pronounced under increased task difficulty, as enhancement appears to emerge under conditions of increased challenge to cognitive possessing or conditions of stress (Nocjar et al., 2007; Tsaltas et al., 2007a; de Vasconcellos et al., 2003). Possibly then, in the current study, reducing the delays and reversing reward contingencies associated with the "large, delayed" and "small, immediate" rewards increased cognitive demand thereby drawing out the beneficial effects of lithium treatment. Interestingly, reversal learning and cognitive flexibility is mediated by the same frontostriatal circuit implicated in the pathophysiology of mood disorders, including BD (Blumberg, Charney & Krystal, 2002; Blumberg et al., 2003; Pfeifer, Welge, Strakowski et al., 2008). Not surprisingly, impaired reversal learning and poor cognitive flexibility is common amongst non-medicated patients with BD (Dickstein, Finger, Brotman et al., 2010; Dickstein, Nelson, McClure et al., 2007; Dickstein, Treland, Snow et al., 2004; Gorrindo, Blair, Budhani et al., 2005; McKirdy, Sussmann, Hall et al., 2009). However when treated with lithium, these patients perform within a normal range on memory and cognitive tasks (Lund, Nissen & Rafaelsen, 1982; Marusarz, Wolpert & Koh, 1981), indicating that lithium might restore cognitive functioning. In this context, data from the current study suggest that chronic lithium treatment may enhance attention and behavioural flexibility and accelerate reversal learning, thereby facilitating behavioural adaptation in response to changes in task contingencies. 4.2.2 Chronic lithium treatment accelerates task acquisition A new cohort of animals was trained on the DDT using the shorter delay set. Lithium-treated rats learned the task faster than controls, suggesting that chronic lithium treatment may accelerate learning and task acquisition. Once fully trained, there were no longer group differences in choice behaviour, 71 indicating that lithium treatment does not affect baseline levels of choice behaviour or the tolerability to delayed reward. Therefore, as noted above, it is unlikely that the group difference that emerged from shortening the delays in Experiment 1 reflected an increase in impulsive choice or a decrease in tolerability to delays. In turn, our results suggest that lithium treatment influences choice behaviour by other means, perhaps by enhancing decisional processing. Objective data from studies examining the effect of lithium treatment on learning deficits in either clinical or normal populations are scarce (Nocjar et al., 2007; Tsaltasur & Kontis, 2009); rather, evidence points towards prolonged lithium treatment and lithium's potential as a cognitive enhancer (Gallo et al., 1990). Although lithium in healthy volunteers may compromise learning during initial, subchronic administration, the effects are no longer apparent with prolonged lithium treatment (Calil, Zwicker & Klepacz, 1990; Stip et al., 2000). In fact, similar to our results, longer treatment periods are shown to boost learning ability (Gallo et al., 1990). For instance, long-term lithium treatment in normal animals improves instrumental, spatial, and associative learning (Gallo et al., 1990; Nocjar et al., 2007). Lithium also accelerates training on delayed-alternation and conditioned place preference tasks as animals reach stable baselines of behaviour earlier than controls (Nocjar et al., 2007). Moreover, lithium treatment in animals improves long-term memory (Nocjar et al., 2007) and memory deficits resulting from environmental stressors (de Vasconcellos et al., 2003) or neurological insults (Yan et al., 2007; Zhu et al., 2010), supporting the drug's use as a potential treatment option for cognitive dysfunction (Nocjar et al., 2007). To this end, lithium treatment reduces the learning deficits associated with ADHD (Dorrego, Canevaro, Kuzis et al., 2002), dementia (Terao et al., 2006), Alzheimer's disease (Forlenza et al., 2011; Nunes et al., 2007) and other psychiatric disorders such as BD (Lund et al., 1982; Marusarz et al., 1981). As attention and cognitive performance are generally impaired in non-medicated patients with BD, our findings might be useful in understanding lithium's clinical efficacy. 4.2.3 Chronic lithium treatment may affect the response to AMPH and YHB on the DDT The present study demonstrates that AMPH increased choice of the large reward in control animals; in fact, animals no longer discounted the large reward at the highest dose, eliminating the effect of delay on impulsive choice. These results suggest that high levels of psychomotor stimulation decreases impulsive decision-making in normal animals. Our results are in line with other studies showing that AMPH decreases impulsive choice and reduces discounting of large rewards in humans and animals (de Wit et al., 2002; van Gaalen et al., 2006; Wade et al., 2000; Winstanley et al., 2003b, 2005, 2006). 72 Amphetamine did not affect lithium-treated animals; when challenged with AMPH, their distribution of choice of the large reward across delays was comparable to the distribution pattern they generated at baseline. As this behaviour was opposite to that of controls', our results suggest that chronic lithium treatment may block stimulant-induced changes in impulsive decision-making and choice behaviour. However, lithium did not block the ability of AMPH to increase impulsive action on the 5-CSRTT. The fact that behaviour on the two tasks is dissociable is not surprising; measures of response inhibition do not generally correlate with measures of reward-delay impulsivity (McDonald, Schleifer, Richards & de Wit, 2003; Swann et al., 2002; Winstanley et al., 2004a). While this evidence supports the notion that impulsivity is a multi-faceted construct (Winstanley et al., 2004a), it is unclear as to why lithium would block the effects of the drug on one task and not the other, particularly a the changes in choice behaviour on both tasks is thought to involve both the serotonin and dopamine systems. Acute AMPH administration is often used as a model of mania (Cappeliez & Moore, 1990; Frey et al., 2006a,b; Jacobs & Silverstone, 1986; Mamelak, 1978; Vale & Ratcliffe, 1987; van Kammen et al., 1985; van Kammen & Murphy, 1975), but it is hard to argue that an AMPH-induced decrease in impulsive choice would reflect a manic state. However, it is worth emphasising that there was no significant Dose by Group effect when rats from both the control and lithium-treated groups were analysed together. Although visual inspection of the data encouraged us to analyse the groups separately, such statistical tests are actually not warranted. Before concluding that lithium treatment genuinely reduces the effect of AMPH on impulsive choice, further experiments would be required. Similarly, when the lithium-treated and control rats were analysed separately, a significant effect of YHB was observed in the lithium-treated group but not in controls. It is tempting to speculate that the decrease in impulsive choice observed in the lithium-treated group reflects improved choice behavior under conditions of high arousal. However, again, the absence of a Dose by Group effect in the main ANOVA reduces our confidence that this effect is robust. An important consideration when using food as a reward during a long-term lithium regime is that lithium is frequently used in taste aversion studies to reduce the appetitive nature of food rewards. In this case, lithium would dampen the animals' responsiveness to food rewards, thereby affecting behaviour. However, because the dose of lithium used in taste aversion studies is well above the dose used for other types of behavioural experiments (Masaki & Nakajima, 2006; Tsaltas et al., 2007a), it is unlikely that the lithium regime in our study influenced behaviour by altering the sugar pellet's palatability (Nocjar et al., 2007; Tsaltas et al., 2007a). Indeed, Nocjar and colleagues (2007) investigated 73 the difference between using food and non-food rewards to reinforce behaviour in lithium-treated animals and discovered that learning and behaviour was independent of reward type. In contrast, saline decreases sweet palatability (Nocjar et al., 2007; Smith & Amdisen, 1983), such that higher sodium consumption might diminish overall performance (Nocjar et al., 2007). Thus, giving the lithium-treated group free access to saline introduces a potential confound which our study controlled for, at least in part, by providing control animals with salt water as well. Similar to Nocjar and colleagues' findings (2007), our lithium-treated and control groups drank comparable amounts of saline, which ensured that the animals' serum-sodium levels were the same during testing (Nocjar et al., 2007), thereby sparing performance. The behavioural tasks we used in our experiments are well-validated animal models of the human tasks. Although human participants typically receive money or points as their reward rather than food, these impulsivity models draw upon reward processes in general, rather than processes specific to a particular type of reward. However, using food reward may pose a limitation as animals could potentially become satiated by the end of a session, and individual differences in how animals judge the taste or the size of the reward might affect behaviour. Restricting the amount of food animals consume prevents satiation; however, quantifying subjective appraisal of the food reward's size or taste is difficult. For example, we cannot measure whether the animals consider the large reward of four sugar pellets as four times the amount of the small reward of one pellet, or whether the animals view the larger reward as merely "greater than" the smaller reward. To circumvent this issue, one may consider using intra-cranial self-stimulation (ICSS) as a behavioural task. ICSS enables the experimenter to adjust the magnitude of the electric current for each animal such that the animal responds four times as much for the large reward as it does for the smaller one. This method ensures that animals subjectively value the reward sizes in a way pre-determined by the experimenter. Thus, ICSS is an appropriate alternative to delivering food reinforcement and should be considered for future experiments. 4.3 Effects of Chronic Lithium Treatment on Gene Expression Results from qPCR analyses suggest that chronic lithium treatment might alter the expression of several intracellular components and neuronal processes associated with the behavioural and cognitive profile relevant to many psychiatric and impulse-control disorders (ICDs) (Baptista et al., 1993; Gould & Einat, 2007; Ferrier et al., 2006; Lenox & Frazer, 2002). In turn, changes in levels of mRNA for 74 monoaminergic receptors, neurotrophic factors, signalling kinases, transcription factors, synaptic proteins, and apoptotic factors described below might underlie lithium's therapeutic effects in patients treated for such disorders. Obviously, observing changes in expression of a gene via qPCR after lithium treatment does not prove that this change contributes to the change in behaviour caused by lithium. Nevertheless, the following discussion outlines how such changes fit with previous observations in the literature and what they may mean for cognitive function. Neurotransmission Noradrenaline. Our results show that lithium treatment relatively downregulates prefrontal ?2A- and ?1-AR gene expression. These findings align with the notion that long-term lithium treatment reduces NA transmission (Katz et al., 1968) by downregulating gene expression for cortical ARs (Carbonell et al., 2004; Devaki et al., 2006). While antagonising ?1-ARs impairs performance accuracy (Arnsten, 2000; Arnsten et al., 1999; Carli et al., 1983; Cole & Robbins, 1987; Liu et al., 2009), stimulating this receptor increases noradrenergic neurotransmission thereby enhancing attention and facilitating cognitive function. Accordingly, this enhanced central noradrenergic transmission might be responsible for improving attentional focus and performance accuracy in lithium-treated animals tested on the 5-CSRTT (Arnsten, 2000; Arnsten et al., 1999; Carli et al., 1983; Cole & Robbins, 1987; Dalley et al., 2004; Dias et al., 1996; Lapiz & Morilak; Liu et al., 2009; Puumala et al., 1997). In this way, these cognitive and behavioural improvements might contribute to the beneficial effects of psychotherapeutic drugs that target NA neurotransmission (Lapiz & Morilak, 2006) such as lithium. Lithium's influence on ?2-AR gene expression is expected considering the association between ?2-ARs and affective disorders (Mendlewicz et al., 1989). As presynaptic ?2-noradrenergic autoreceptors regulate NA efflux (Langer, 1981), lithium treatment might attenuate ?2-AR-mediated behavioral effects (Goodwin et al., 1986) by relieving the inhibitory effect of these presynaptic ?2-ARs on NA release (Spengler, Hollingsworth & Smith, 1986) or by decreasing ?2-AR sensitivity (Manji, Hsiao, Ribsy et al., 1991), thereby increasing noradrenergic transmission (Katz et al., 1968). The present study shows that lithium downregulates ?1-AR expression in the PFC. Over-stimulating ?1-AR via stress may result in PFC-dependent cognitive dysfunction while blocking these receptors prevents stress-induced impairments in cognitive flexibility (Alexander et al., 2007). For instance, high levels of ?1-ARs increase cAMP signalling (Cuffi, Carbonell, M?rmol et al., 2003) which weakens PFC network connections (Wang et al., 2007). Interestingly, elevated levels of cAMP are associated with cognitive dysfunction (Ramos et al., 2005) and are also linked to BD (Chang, Li & Warsh, 2003; Karege, Schwald, Papadimitriou et al., 2004; Friedman & Wang, 1996; Young, Li, Kish et al., 1993). 75 Given this association, decreasing ?1-AR expression might produce therapeutic effects by strengthening PFC function (Ramos & Arnsten, 2007). Possibly, lithium treatment enhanced cognitive functioning by attenuating a downstream effect of noradrenergic transmission such as cAMP signalling (Ramos et al., 2005). Serotonin. Our results demonstrate that chronic lithium treatment downregulates mRNA levels for the 5-HT2A and 5-HT2C receptor subtypes in the PFC. Contrary to our results, Goodwin and colleagues report that lithium does not alter prefrontal 5-HT2 receptor expression (Goodwin et al., 1986), while others attest that lithium administration may instead facilitate serotonergic transmission (Sandgee & Franz, 1978) by decreasing 5-HT receptor sensitivity (Maggi & Enna, 2006). Alternatively, Moorman & Leslie (1998) argue that changes in receptor numbers might not account for the physiological effect of chronic lithium. Despite these conflicting reports, our results fit with the notion that the serotonergic system is dysregulated in impulsive individuals (Dalley et al. 2002). For example, a polymorphism in the gene coding for the 5-HT2A receptor is associated with a greater incidence of past mood disorders and substance use disorders (Bjork et al., 2002), and that 5-HT2 receptors might be upregulated/ supersensitive in psychiatric conditions such as ICDs (Mann et al., 1989; Schreiber & De Vry, 1992). In addition, modeling this mutation in rodents results in impulsive responding on a rodent version of the CPT (Bjork et al., 2002), suggesting the 5-HT2A receptor may be a marker for impaired behavioural control and/or psychiatric disturbances. Furthermore, decreasing serotonergic neurotransmission increases GSK-3? activity (Kovacsis & Gould, 2009), and this apoptotic factor is strongly linked to the neurotoxicity in BD is also linked to the pro-apoptotic factor GSK-3? (Chiu & Chuang, 2011; Jope, 2011; Jord? et al., 2005; Tyagarajana et al., 2010). Together, these findings suggest that 5-HT activation and downregulating the 5-HT2 receptor subtype can contribute to lithium's therapeutic effects (Schreiber & De Vry, 1992). Acetylcholine. The present study shows that chronic lithium treatment downregulates levels of mRNA coding for the M1 (muscarinic cholinergic) receptor subtype in the OFC, and upregulates this gene in the NAc. The cholinergic system largely regulates attentional function and impulsive behaviour (Ellis et al., 2006; Risbrough et al., 2002; Robbins & Robers, 2007; Tzavos et al., 2004). For example, performance on the 5-CSRTT is associated with increased prefrontal ACh efflux, and mAChR (muscarinic cholinergic receptor) antagonists impair attention, accuracy, and response inhibition on the 5-CSRTT (Ruotsalainen et al., 2000) and other paradigms of vigilance and behavioural control (Ellis et al., 2006). Furthermore, learning a new choice pattern is associated with increased ACh output (Ragozzino & Choi, 2004), suggesting that this neurotransmitter is involved in behavioural flexibility and in adapting response 76 patterns following changes in task contingencies. Interestingly, the NAc plays an essential part in this type of learning, where response patterns must be adaptable (Ragozzino & Choi, 2004). In accordance with this view, we found that lithium treatment increased levels of M1 mRNA levels in the NAc; as such, these modifications might have contributed to the behavioural and cognitive enhancing effects observed in our lithium-treated rats. The cholinergic system, particularly its activity within the OFC (McAlonan & Brown, 2003; Robbins & Roberts, 2007; Tzavos et al., 2004), also plays a role in modulating cognitive functioning such reversal learning (Ellis et al., 2006; Robbins & Robers, 2007; Tzavos et al., 2004). In particular, regional M1 activity is critical for reversal learning (Tzavos et al., 2004) and blocking this receptor subtype (Tzavos et al., 2004) or depleting ACh within the PFC (Roberts, Robbins, Everitt & Muir, 1992) impairs reversal learning. Although the current study found decreased levels of M1 mRNA in the OFC, levels of mRNA do not necessarily parallel receptor protein functionality (Ferrie et al., 2005). As such, our findings suggest that our lithium-treated animals' enhanced attentional performance as well as cognitive flexibility and reversal learning observed on the 5-CSRTT and DDT, respectively, is unlikely attributed to the change in M1 receptor protein synthesis within the OFC. As mentioned earlier, receptor binding characteristics may factor into its activity and influence on neurotransmitter flux. However, although lithium has been shown to dampen mAChR supersensitivity (Ellis & Lenox, 1990) it does not alter mAChR binding (Maggi & Enna, 2006). Instead, lithium's efficacy in affective disorders may be related to reduced cholinergic activity (Bymaster & Felder, 2002), as lithium treatment attenuates the detrimental effects of cholinergic excitatory neurotoxicity and protects neurons from the neurochemical and behavioral consequences of neurotoxicity (Silva et al., 2008). In this context, our finding that lithium downregulated M1 gene expression in the OFC could be explained as an adaptive compensatory mechanism (Dziedzicka-Wasylewska et al., 1996) in response to weakened ACh output, however further research is necessary to clarify this relationship. Neuroprotection The present study shows that chronic lithium treatment downregulates levels of mRNA for BDNF in the mPFC and OFC. These findings might appear to counter the neurotrophic factor's well-established role in cytoprotection, neuronal survival, and synaptic plasticity, as well as reports claiming that lithium increases BDNF's expression in the PFC (Fukumoto, Morinobu, Okamoto et al., 2001). However, lithium's effects on BDNF gene expression appear to rely on duration of treatment and on the neural circuit in which the neurotrophic factor is involved (Chen & Manji, 2006). For example, while chronic dietary lithium treatment increases BDNF expression in the PFC after just two weeks, this effect is no 77 longer evident after a more prolonged treatment regime lasting 28 days (Fukumoto et al., 2001). In fact, similar to our findings on BDNF, another group also reports a decrease in BDNF expression in the PFC after 42 days of lithium treatment. These findings suggest that lithium might produce different, or even opposite, effects on gene expression depending on the duration of treatment, which include BDNF gene expression. Alternatively, the decrease in prefrontal levels of BDNF mRNA observed in our study might have resulted from decreased CREB expression, as CREB induces BDNF gene expression (Benmansour et al., 2008; Finkbeiner, 2000) and we detected decreased levels of CREB mRNA in the OFC. This idea fits the notion that lithium decreases CREB phosphorylation (activation) in prefrontal regions (Chen et al., 1990). Neurotrophic factors and signalling molecules establish and maintain the efficiency of higher-order functions such as learning, memory, executive functioning, and behaviour (Russell, 1995; Russell & Duman, 2002). Considering CREB has diverse neuroplastic actions, stabilizing its activity by regulating its genetic expression may underlie lithium's neurotrophic actions. In turn, increasing cellular resiliency might contribute to the mood stabilizer's therapeutic efficacy in psychiatric disorders such as BD (Chen et al., 1990; Fukumoto et al., 2001; Hammonds & Shim, 2009; Leslie et al., 1993; Moorman & Leslie, 1998). Vesicular and Synaptic Factors Lithium might interact with proteins in the synaptic complex to normalize neurotransmission. For example, CSPs (cysteine string proteins) are important components of the regulated secretory pathway at nerve terminals as they fine-tune neurotransmission (Buchner & Gundersen, 1997; Magga et al., 2000; Umbach & Gundersen, 1997). In this study we demonstrate that lithium treatment decreases levels of CSP mRNA in the OFC. As levels of CSP expression correlate with the magnitude of evoked neurotransmitter release (Chamberlain & Burgoyne, 1998; Umbach & Gundersen, 1997), lithium treatment in our study might have produced its behavioural effects and influenced changes in behaviour in response to AMPH and YHB challenges by decreasing neuronal secretory behaviour (Cordeiro et al., 2000). This view fits well with the notion that lithium's therapeutic efficacy is mainly ascribed to its ability to decrease monoaminergic transmission (Baptista et al., 1993; Bymaster & Felder, 2002; Devaki et al., 2006; Ellis & Lenox, 1990; Ferrie et al., 2005; Katz et al., 1968; Sourial-Bassillious et al., 2009; Wang & Friedman, 1989), particularly considering the correlation between BD and abnormal monoamine activity (Bymaster & Felder, 2002; Swann et al., 1983). In this way, our findings suggest that altering the genetic expression of proteins involved in monoaminergic neurons' secretory behavior 78 (Cordeiro et al., 2000) thereby regulating vesicular mechanisms (Chamberlain & Burgoyne, 1998; Cordeiro et al., 2000; Umbach & Gundersen, 1997) may be part of lithium's pharmacological action. Lithium treatment might also stabilize neurotransmission by inducing and/or modifying synapse formation (Hall et al., 2002; Kim & Thayer, 2009). For instance, PSD-95 (post-synaptic density-95) is a scaffolding protein that anchors receptors and downstream signalling molecules to the post-synaptic density. In this respect, PSD-95 is required for synaptic plasticity (Elias & Nicoll, 2007; Kim & Sheng 2004; Steiner et al., 2008). New presynaptic terminals form following lithium treatment (Chen et al., 2000; Hall et al., 2002; Kim & Thayer, 2009; Ma & Zhang, 2003; Tyagarajana et al., 2010), alluding to the role of PSD-95's in the treatment of BD. Many neuropsychiatric disorders are associated with abnormal PSD-95 -associated proteins (Camp, Feyder, Ihne et al., 2011; Grant, Marshall, Page et al., 2005; Fernandez, Collins, Uren et al., 2009; Yao, Gainetdinov, Arbuckle et al. 2004) and PSD-95 -mediated actions might contribute to the actions of various abused substances (Camp et al., 2011; Yao et al. 2004). The present study shows that lithium treatment downregulates levels of mRNA for PSD-95 in the OFC. Further characterising these synaptic factors and their interaction may shed light on the pathophysiology underlying psychiatric disorders such as BD and substance abuse, and could have important implications for the development of novel treatments. Apoptotic Factors The present study shows that chronic lithium treatment downregulates the expression of GSK-3? (glycogen synthase kinase-3?) in the mPFC. This finding is appropriate considering the role of neurotoxicity in the pathophysiology of BD, which is strongly linked to GSK-3? over-activity and/or over-expression (Chiu & Chuang, 2011; Jope, 2011; Jord? et al., 2005; Tyagarajana et al., 2010). Not surprisingly, over-expressing this apoptotic factor in mice has been proposed as a model of hyperactivity and mania (Prickaerts, Moechars, Cryns et al., 2006). To this end, lithium also prevents neurotoxicity and apoptosis by regulating the levels of cdk5. Cdk5 is a kinase involved in neurogenesis, neurite outgrowth and axonal pathfinding (Nikolic, Dudek & Kwon, 1996) and is elevated in areas characterized by high neuronal plasticity. Cdk5 activity is regulated by a co-factor that can also convert cdk5 into a pro-apoptotic factor if exposed to neurotoxins (Gong, Tang, Wiedmann et al., 2003; Jord? et al., 2005). This conversion also occurs following oxidative stress, both of which are associated with BD (Gould & Einat, 2007; Kasahara et al., 2006; Kato & Kato, 2000; Kato et al., 2007; Kuloglu et al., 2002; Steckert et al., 2010) and several other neurodegenerative diseases (Lee & Tsai, 2003; Patrick et al., 1999; Sengupta et al., 1997). This damage leads to impairments in signal transduction, structural plasticity, and cellular resilience (Cochrane, 1991) which 79 are also disrupted in BD (Benmansour et al., 2008; Denton & Tavare, 1995; Hempstead et al., 1992; Lien et al., 2008; McAllister et al., 1999; Pullarkat et al., 1998; Russell, 1995; Russell & Duman, 2002; Shaltiel et al., 2007). Thus, as the neuroprotective mechanisms of lithium might involve regulating cdk5 expression, lithium might have enhanced attentional performance, behavioural flexibility, and task acquisition in the present study by preventing the conversion of cdk5 into a pro-apoptotic protein (Jord? et al., 2005) and promoting cell survival, synaptic plasticity, and neurotransmission. As a result, lithium's anti-apoptotic effects might also underlie lithium's potential as a cognitive enhancer (de Vasconcellos et al., 2003; Tsaltas & Kontis, 2009). Examining lithium's effects on intracellular actions may provide clues to the mechanisms underlying the neuropathology of bipolar mania and may help identify targets for novel pharmacotherapies for treating BD and other ICDs. 4.4 General Summary Impulsivity and disrupted cognitive functioning during mania is pervasive, producing deficits in attention and behavioral inhibition, to name a few (Swann, 2009). 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During the limited hold period, animals must withhold from responding until a stimulus light briefly illuminates one of the five holes. When the stimulus light flashes, subjects must make a nose-poke response in this hole to earn a reward. Animals may then start a new trial once the inter-trial interval has passed. As rats progress through training stages, the limited hold period increases (i.e. rats must withhold their response for a longer period of time), the stimulus duration decreases (requiring greater attentional focus), and the inter-trial interval increases (more time between trials). Subjects progress to the next training stage upon meeting the current stages' performance criterion. Task Parameters Criteria to advance to next training stage Training Stage Limited Hold (sec) Stimulus Duration (sec) Inter-trial Interval (sec) # Correct Trials Accuracy Omissions 1 30 30 2 ? 30 -- -- 2 20 20 2 ? 30 -- -- 3 10 10 5 ? 50 -- -- 4 5 5 5 ? 50 > 80% -- 5 5 2.5 5 ? 50 > 80% < 20% 6 5 1.25 5 ? 50 > 80% < 20% 7 5 1 5 ? 50 > 80% < 20% 8 5 0.9 5 ? 50 > 80% < 20% 9 5 0.8 5 ? 50 > 80% < 20% 10 5 0.7 5 ? 50 > 80% < 20% 11 5 0.6 5 ? 50 > 80% < 20% 12 5 0.5 5 ? 50 > 80% < 20% 118 Appendix B. Schemata showing one trial of the 5-CSRTT. Animals initiate a trial by nose-poking into the illuminated food tray, which extinguishes the tray light. Animals then scan the five holes to detect a brief stimulus light in one of the holes. Animals respond by poking their nose in that hole?this nose-poke is recorded as a "correct" response is rewarded with one sugar pellet. A response made in any other hole or a failure to respond is scored as an "incorrect" response and an "omission," respectively. These outcomes are punished by a "time-out" period, during which the house light is turned on, sugar pellets are withheld, and animals must wait to begin a new trial. Responses made before the stimulus light is presented in one of the five holes are classified as "premature" responses and are also punished by a time-out. At the end of the time-out period, the house light turns off, the tray light turns on, and the rat can initiate a new trial. Nose-poke in one of 5 response apertures "Premature" response Tray light off. Tray light on. 1 pellet dispensed. "Incorrect" response House light off. Tray light on. "Correct" response "Omission" House light on. 30 sec time-out Inter-trial interval Nose-poke in lit hole No response within 5 sec Nose-poke in food tray Nose-poke in unlit hole Brief stimulus light in one of 5 response apertures. 119 Appendix C. Flow diagrams of the three training phases of the DDT. (A) Phase 1?Operant training. A trial begins when the tray light turns on and a pellet is dispensed. The rat collects the pellet, which turns off the tray light and turns on a stimulus light in either hole 1 (H1), hole 3 (H3), or hole 5 (H5; random illumination order for each pair of trials). The rat has 30 sec to respond in the illuminated hole; doing so also turns off the stimulus light and turns on the tray light, which signals delivery of a sugar pellet reward. After collecting the reward, the rat may initiate a new trial. After 30 sec without a response, the stimulus light turns off and the house light turns on for 5 sec, indicating a period of punishment during which reward pellets are withheld. The session continues until the rat completes 100 trials or until 30 min have elapsed, whichever comes first. Each rat is exposed to one session daily until it reaches a criterion of at least 60 rewarded trials (30 responses in each hole) within a session. This criterion is usually met within one to four sessions. (B) Phase 2?Nose-poke initiation training. A trial begins when the tray light turns on; trials begin every 40 sec thereafter, irrespective of the animals' behaviour. The rat has 10 sec to poke its nose into the food tray; doing so extinguishes the tray light and illuminates one of the two stimulus lights (H1 or H5; random illumination order for each pair of trials). Failure to nose-poke in the food tray is counted as an omission and the house light turns on as punishment. If the rat responds in the illuminated hole within 10 sec, the tray light is turned on and a sugar pellet is dispensed. The tray light stays on for 10 sec or until the pellet is collected, after which the rat may start a new trial on condition that the 40 sec for that trial are over. However, if the rat does not respond in the illuminated hole within 10 sec, the house light turns on and the reward pellet is withheld, thereby punishing the omitted response. The session continues until the rat completes 90 trials (60 min). Each rat is exposed to one session daily until it reaches a criterion of at least 60 rewarded trials (30 responses in each hole) within a session. This criterion is usually met within one to three sessions. (Continued on the next page). A B Nose-poke in food tray Stimulus light off. Tray light on. 1 pellet dispensed. No response within 10 sec Tray light off. Stimulus light on in H1 or H5. Nose-poke in illuminated hole Nose-poke in food tray Inter-trial interval. Trial every 40 sec Tray light on. House light off. No response within 10 sec Tray light off. No response within 10 sec House light on. Nose-poke in food tray Stimulus light off. Tray light on. 1 pellet dispensed. Stimulus light on in H1, H3, or H5. No response within 30 sec Nose-poke in illuminated hole House light on. 5 sec time-out Tray light off. House light off. 120 (Appendix C, continued from previous page). (C) Complete delay discounting procedure. See sub-section 2.5.2 "The delay discounting task (DDT): Experiments 1 and 2" for detailed description. (Schemata adapted from Mar & Robbins, 2007). C "Delay" hole chosen Nose-poke in food tray "Immediate" hole chosen Nose-poke in food tray Nose-poke In food tray DELAY: Block 1: 0 sec Block 2: 5 sec Block 3: 10 sec Block 4: 20 sec 6 sec without nose-poke No response within 10 sec No response within 10 sec 6 sec without nose-poke Tray light off. Stimulus lights off. Tray light on. 1 pellet dispensed. Tray light off. Stimulus lights on in H1 AND H5. Trial every 100 sec. Tray light on. House light off. Tray light off. Tray light on. 4 pellets dispensed. Stimulus lights off. Inter-trial interval. House light on. 121 Appendix D. 5-CSRTT baseline behavioural measures. A stable baseline of performance was reached after five weeks of testing, at which time animals had been on their respective diets for twelve weeks. Data are presented as the group mean plus/minus the standard error of the mean (? SEM), averaged over five consecutive baseline test sessions. Significant group differences were determined by repeated-measures ANOVA, with session as the within-subjects factor and group (lithium, n = 8 vs. control, n = 8) as the between-subjects factor. Latencies are given in sec; ns = non-significant. Behavioural Measure Group Group Mean ? SEM Repeated-measures ANOVA Main Effect of Group Accuracy (% correct responses) Lithium Control 90.73 81.87 ? 2.37 ? 2.39 F(1, 14) = 7.44 p = 0.016 Premature responses (%) Lithium Control 8.75 10.79 ? 1.94 ? 2.76 F(1, 14) = 0.10 ns Anticipatory nose-poke responses Lithium Control 164.35 134.10 ? 14.53 ? 6.34 F(1, 14) = 4.42 p = 0.054 Perseverative responses Lithium Control 4.83 5.86 ? 1.56 ? 2.05 F(1, 14) = 0.21 ns Latency to respond correctly Lithium Control 0.48 0.50 ? 0.03 ? 0.03 F(1, 14) = 0.39 ns Latency to respond incorrectly Lithium Control 1.17 0.95 ? 0.23 ? 0.11 F(1, 14) = 1.89 ns Latency to collect reward Lithium Control 1.56 1.70 ? 0.10 ? 0.10 F(1, 14) = 1.26 ns Number of trials completed Lithium Control 99.58 100.00 ? 0.43 ? 0.00 F(1, 14) = 1.01 ns Omissions (%) Lithium Control 5.80 3.83 ? 1.67 ? 1.08 F(1, 14) = 1.62 ns 122 Appendix E. 5-CSRTT behavioural measures during AMPH challenge. Each subject was exposed to saline and to each dose of AMPH once, in an order determined using a Latin-square drug design. Drugs were prepared fresh daily and were administered 10 min before testing in a volume of 1 ml/mg, i.p. Data are presented as the mean plus/minus the standard error of the mean (? SEM). Significant dose and group effects were determined by repeated-measures ANOVA, using Dose (saline, 0.3, 0.6, and 1.0 mg/kg) as the within-subjects factor, and Group (lithium, n = 8 vs. control, n = 8) as the between-subjects factor. Significant dose effects were further analysed by paired-samples Student's t-tests with each dose paired with saline; for main effects of group, group data were analysed separately, where a = effect of Dose. Significance levels are reported as follows: ? = p < 0.001; ? = p < 0.01; * = p < 0.05. Latencies are given in sec; ns = non-significant. Behavioural Measure Dose of AMPH (mg/kg) Repeated-measures ANOVA Group Saline 0.3 0.6 1.0 Dose Group Dose x Group Accuracy (% correct responses) Lithium 91.69 ? 2.10 84.72 ? 3.73* 79.25 ? 4.37? 81.03 ? 5.49? F(3, 42) = 4.52 p = 0.008 F(1, 14) = 1.41 ns F(3, 42) = 1.46 ns Control 83.18 ? 1.86 79.26 ? 3.74* 80.94 ? 3.56? 76.94 ? 4.10? Premature responses (%) Lithium 8.87 ? 2.36 19.13 ? 4.45? 32.88 ? 8.01? 41.29 ? 10.24? F(3, 42) = 22.39 p < 0.001 F(1, 14) = 0.004 ns F(3, 42) = 0.58 ns Control 9.33 ? 2.62 19.37 ? 2.76? 34.58 ? 7.71? 33.71 ? 6.93? Anticipatory nose-poke responses Lithium 145.50 ? 8.94 137.38 ? 17.66 666.50 ? 62.05? 567.00 ? 41.43? F(3, 39) = 280.78 p < 0.001 F(1, 13) = 1.65 ns F(3, 39) = 0.83 ns Control 127.25 ? 11.06 121.75 ? 9.26 548.00 ? 29.15? 522.50 ? 22.15? Perseverative responses Lithium 4.88 ? 2.04 4.38 ? 0.98 2.38 ? 1.03? 2.00 ? 0.60? F(3, 39) = 6.70 p < 0.001 F(1, 13) = 0.21 ns F(3, 39) = 0.46 ns Control 0.26 ? 0.02 0.20 ? 0.04 0.14 ? 0.03? 0.10 ? 0.02? Latency to respond correctly Lithium 0.45 ? 0.03 0.43 ? 0.03 0.51 ? 0.05 0.49 ? 0.06 F(3, 42) = 1.98 ns F(1, 14) = 0.22 ns F(3, 42) = 0.37 ns Control 0.45 ? 0.02 0.45 ? 0.03 0.44 ? 0.04 0.41 ? 0.01 Latency to respond incorrectly Lithium 1.37 ? 0.19 1.02 ? 0.08 1.19 ? 0.16 1.51 ? 0.23 F(3, 42) =2.22 ns F(1, 14) = 17.50 p < 0.001 F(3, 42) = 0.66 ns Control 0.79 ? 0.05 0.68 ? 0.08 0.73 ? 0.08 0.82 ? 0.16 Latency to collect reward Lithium 1.43 ? 0.08 1.41 ? 0.07 1.31 ? 0.08* 1.31 ? 0.08? F(3, 42) = 4.10 p = 0.012 F(1, 14) = 1.00 ns F(3, 42) = 0.26 ns Control 1.59 ? 0.10 1.51 ? 0.13 1.45 ? 0.09* 1.40 ? 0.12? Number of trials completed Lithium 1.57 ? 0.00 1.57 ? 0.00 1.40 ? 0.11* 1.19 ? 0.15? F(3, 42) = 6.81 p < 0.001 F(1, 14) = 0.19 ns F(3, 42) = 0.68 ns Control 1.57 ? 0.00 1.57 ? 0.00 1.38 ? 0.13* 1.37 ? 0.12? Omissions (%) Lithium 3.63 ? 1.31 3.38 ? 0.73 5.06 ? 1.35 10.68 ? 3.81* F(3, 42) = 2.87 p = 0.048 F(1, 14) = 4.25 p = 0.058 F(3, 42) = 1.08 ns Control 1.88 ? 0.48 5.13 ? 2.62 1.75 ? 1.06 4.42 ? 0.90* nsa nsa 123 Appendix F. 5-CSRTT behavioural measures during YHB challenge. Each subject was exposed to saline and each dose of YHB once in an order determined using a Latin-square design. Drugs were prepared fresh daily and were administered 10 min before testing in a volume of 1 ml/mg, i.p. Data are presented as the mean plus/minus the standard error of the mean (? SEM). Significant dose and group effects were determined using repeated-measures ANOVA, using Dose (vehicle, 1.0, 2.0, and 5.0 mg/kg) as the within-subjects factor and Group (lithium, n = 8 vs. control, n = 8) as the between-subjects factor. Significant dose effects were further analysed by paired-samples Student's t-tests with each dose paired with vehicle; for group effects, data were analysed separately, where a = effect of Dose. Significance levels are reported as follows: ? = p < 0.001; ? = p < 0.01; * = p < 0.05; ? = 0.05 < p < 0.10, trend. Latencies are given in sec; ns = non-significant. Behavioural Measure Dose of YHB (mg/kg) Repeated-measures ANOVA Group Vehicle 1.0 2.0 5.0 Dose Group Dose x Group Accuracy (% correct responses) Lithium 90.50 ? 2.53 88.37 ? 3.00 87.02 ? 2.40 85.24 ? 3.80 F(3, 39) = 4.25 p = 0.011 F(1, 13) = 7.80 p = 0.015 F(3, 39) = 0.17 ns Control ?a 84.62 ? 3.53 81.16 ? 3.12 77.05 ? 3.32* 72.28 ? 6.24 Premature responses (%) Lithium ?a 7.87 ? 1.94 13.18 ? 3.08* 17.29 ? 3.70? 2.33 ? 0.77? F(3, 36) = 14.92 p < 0.001 F(1, 12) = 5.47 p = 0.037 F(3, 36) = 3.17 p = 0.036 Control ?a 5.47 ? 0.99 21.79 ? 4.13? 22.59 ? 2.60? 15.56 ? 3.80ns Anticipatory nose-poke responses Lithium 140.75 ? 9.22 166.63 ? 14.26* 155.38 ? 7.79? 165.88 ? 12.17? F(3, 42) = 4.04 p = 0.013 F(1, 14) = 0.83 ns F(3, 42) = 0.46 ns Control 124.63 ? 11.07 150.00 ? 13.06* 157.50 ? 9.19? 162.25 ? 7.02? Perseverative responses Lithium 5.00 ? 2.15 4.63 ? 1.21 2.50 ? 0.71 2.50 ? 0.98 F(3, 42) = 2.67 p = 0.061 F(1, 13) = 1.38 ns F(3, 39) = 0.12 ns Control 8.88 ? 3.38 6.63 ? 3.17 6.25 ? 2.43 6.43 ? 2.10 Latency to respond correctly Lithium 0.46 ? 0.03 0.45 ? 0.03? 0.43 ? 0.02 0.63 ? 0.04* F(3, 42) = 5.71 p = 0.002 F(1, 14) = 0.08 ns F(3, 42) = 0.62 ns Control 0.44 ? 0.02 0.42 ? 0.03? 0.43 ? 0.02 0.57 ? 0.03* Latency to respond incorrectly Lithium ?a 1.13 ? 0.09 1.04 ? 0.22 0.97 ? 0.14 1.85 ? 0.20* F(3, 42) = 9.77 p < 0.001 F(1, 14) = 5.63 p = 0.033 F(3, 42) = 0.13 ns Control *a 0.84 ? 0.07 0.79 ? 0.18 0.70 ? 0.11 1.42 ? 0.26? Latency to collect reward Lithium 1.51 ? 0.07 1.30 ? 0.05? 1.35 ? 0.07? 1.98 ? 0.09? F(3, 42) = 51.90 p < 0.001 F(1, 14) = 1.02 ns F(3, 42) = 2.08 ns Control 1.66 ? 0.12 1.56 ? 0.13? 1.51 ? 0.13? 1.98 ? 0.17? Number of trials completed Lithium 100.00 ? 0.00 100.00 ? 0.00 100.00 ? 0.00 100.00 ? 0.00 F(3, 42) = 1.81 ns F(1, 14) = 1.81 ns F(3, 42) = 1.81 ns Control 100.00 ? 0.00 100.00 ? 0.00 100.00 ? 0.00 96.71 ? 3.29 Omissions (%) Lithium ?a 5.13 ? 1.37 4.88 ? 1.16 3.88 ? 0.79 24.75 ? 5.74? F(3, 42) = 30.55 p < 0.001 F(1, 14) = 4.55 p = 0.051 F(3, 42) = 0.35 ns Control ?a 1.63 ? 0.50 1.00 ? 0.27 2.50 ? 0.53 19.29 ? 6.26? nsa 124 Appendix G. DDT Experiment 1b (short delay set) baseline behavioural measures. Data from this shorter delay set indicate that across delay, lithium-treated animals chose the smaller, immediate reward significantly more than controls. Data are averaged over four consecutive sessions and are presented as the mean plus/minus the standard error of the mean (? SEM). Significant effects of delay and of lithium treatment were determined using repeated-measures ANOVA, with Delay (0, 5, 10, and 20 sec) as the within-subjects factor and Group (lithium, n = 8 vs. control, n = 7) as the between-subjects factor. Significant delay effects were further analysed by paired-samples Student's t-tests with Delay (5, 10, and 20 sec) paired with the 0-sec delay. Significance levels are reported as follows: ? = p < 0.001; ? = p < 0.01; * = p < 0.05. #: 0-sec delay data were generated as default values of 0.00, thus repeated-measures ANOVA were conducted using Delay (5, 10, and 20 sec) as the within-subjects factor, and Group (lithium vs. control) as the between-subjects factor. Latencies are given in sec; ns = non-significant. Behavioural Measure Delay to Large Reward (sec) Repeated-measures ANOVA Group 0 5 10 20 Delay Group Delay x Group % Choice of large reward Lithium 94.75 ? 2.85 60.25 ? 9.51 36.00 ? 9.72 21.75 ? 6.71 F(3, 36) = 60.43 p < 0.001 F(1, 12) = 10.24 p = 0.008 F(3, 36) = 10.96 p < 0.001 Control 90.33 ? 5.56 84.57 ? 7.72 70.67 ? 8.95 52.62 ? 10.40 Perseverative responses Lithium 0.35 ? 0.18 0.28 ? 0.15 0.35 ? 0.19 0.32 ? 0.15 F(3, 36) = 1.10 ns F(1, 12) = 0.95 ns F(3, 36) = 0.53 ns Control 0.75 ? 0.33 0.53 ? 0.17 0.45 ? 0.21 0.46 ? 0.18 Anticipatory nose-poke responses # Lithium 0.00 ? 0.00 1.00 ? 0.52 0.50 ? 0.24 0.71 ? 0.42 F(2, 24) = 0.60 ns F(1, 12) = 1.95 ns F(2, 24) = 2.78 p = 0.082 Control 0.00 ? 0.00 1.89 ? 0.98 2.69 ? 1.40 2.06 ? 0.94 Anticipatory nose-poke latency # Lithium 0.00 ? 0.00 0.65 ? 0.24 0.63 ? 0.34 0.68 ? 0.33 F(2, 26) = 0.05 ns F(1, 13) = 0.46 ns F(2, 26) = 0.16 ns Control 0.00 ? 0.00 0.86 ? 0.38 1.00 ? 0.47 0.84 ? 0.39 Initiation latency Lithium 1.51 ? 0.32 2.50 ? 0.53? 3.21 ? 0.62? 3.16 ? 0.54? F(3, 39) = 11.12 p < 0.001 F(1, 13) = 0.22 ns F(3, 39) = 0.24 ns Control 1.60 ? 0.33 2.11 ? 0.32? 2.95 ? 0.52? 2.85 ? 0.53? Response latency Lithium 0.49 ? 0.04 1.00 ? 0.24? 1.01 ? 0.25* 0.79 ? 0.19* F(3, 39) = 7.16 p < 0.001 F(1, 13) = 0.00 ns F(3, 39) = 0.36 ns Control 0.47 ? 0.06 0.87 ? 0.28? 1.04 ? 0.39* 0.91 ? 0.31* Latency to collect reward Lithium 0.90 ? 0.04 0.70 ? 0.10 0.81 ? 0.13 1.04 ? 0.14 F(3, 21) = 2.21 ns F(1, 7) = 0.18 ns F(3, 21) = 1.22 ns Control 0.76 ? 0.03 0.85 ? 0.24 0.83 ? 0.18 0.86 ? 0.16 125 Appendix H. DDT Experiment 2 baseline behavioural measures. A second cohort of animals was trained on the DDT using only the short delay set; animals reached stable baseline criteria after seven weeks of training (nine weeks of lithium treatment). Training the animals using only these short delays eliminated the group effect observed with the longer delays?both groups discounted the large reward in a similar fashion across delays. Data are averaged over four consecutive sessions and are presented as the mean plus/minus the standard error of the mean (? SEM). Effects of delay and of lithium treatment were determined using repeated-measures ANOVA, with Delay (0, 5, 10, and 20 sec) as the within-subjects factor and Group (lithium, n = 8 vs. control, n = 8) as the between-subjects factor. Significant delay effects were further analysed by paired-samples Student's t-tests with Delay (5, 10, and 20 sec) paired with the 0-sec delay. Significant group effects were followed up with separate ANOVAs for each group, where, for each group, repeated-measures ANOVA reported effects of Delay (a). Significance levels are reported as follows: ? = p < 0.001; ? = p < 0.01; * = p < 0.05; ? = 0.05 < p < 0.10, trend. #: 0-sec delay data were generated as default values of 0.00, thus repeated-measures ANOVA were conducted using Delay (5, 10, and 20 sec) as the within-subjects factor, and Group (lithium vs. control) as the between-subjects factor. Latencies are given in sec; ns = non-significant. Behavioural Measure Delay to Large Reward (sec) Repeated-measures ANOVA Group 0 5 10 20 Delay Group Delay x Group % Choice of large reward Lithium 98.33 ? 1.03 75.83 ? 5.97 45.42 ? 9.29 22.50 ? 7.73 F(3, 42) = 89.71 p < 0.001 F(1, 14) = 1.02 ns F(3, 42) = 0.40 ns Control 98.75 ? 0.96 82.92 ? 6.94 56.67 ? 9.72 32.50 ? 10.53 Perseverative responses Lithium 0.98 ? 0.41 0.50 ? 0.19? 0.53 ? 0.26? 0.47 ? 0.21? F(3, 42) = 9.37 p < 0.001 F(1, 14) = 0.08 ns F(3, 42) = 0.46 ns Control 1.08 ? 0.43 0.55 ? 0.25? 0.26 ? 0.09? 0.26 ? 0.09? Anticipatory nose-poke responses # Lithium 0.00 ? 0.00 2.37 ? 0.58 2.83 ? 0.70 2.69 ? 0.84 F(2, 20) = 1.73 ns F(1, 10) = 0.20 ns F(2, 20) = 0.03 ns Control 0.00 ? 0.00 3.20 ? 0.86 4.82 ? 1.58 3.88 ? 1.54 Anticipatory nose-poke latency # Lithium 0.00 ? 0.00 0.99 ? 0.19 0.92 ? 0.35 0.87 ? 0.45 F(2, 26) = 0.09 ns F(1, 13) = 0.32 ns F(2, 26) = 0.28 ns Control 0.00 ? 0.00 1.00 ? 0.24 0.98 ? 0.24 0.91 ? 0.36 Initiation latency Lithium 1.84 ? 0.25 3.05 ? 0.44? 2.78 ? 0.47? 2.79 ? 0.53? F(3, 39) = 10.03 p < 0.001 F(1, 13) = 0.02 ns F(3, 39) = 0.08 ns Control 1.86 ? 0.31 2.69 ? 0.46? 3.03 ? 0.56? 3.45 ? 0.64? Response latency Lithium 0.53 ? 0.03 0.88 ? 0.18 0.96 ? 0.28 1.00 ? 0.28 F(3, 42) = 6.96 p < 0.001 F(1, 14) = 11.94 p = 0.004 F(3, 42) = 1.20 ns Control 0.40 ? 0.02 0.48 ? 0.04* 0.63 ? 0.09? 0.58 ? 0.06? Latency to collect reward Lithium 0.96 ? 0.08 1.64 ? 0.36* 1.14 ? 0.21? 1.42 ? 0.18? F(3, 42) = 5.28 p = 0.004 F(1, 14) = 1.35 ns F(3, 42) = 0.40 ns Control 0.83 ? 0.04 1.44 ? 0.47* 1.01 ? 0.31? 0.97 ? 0.17? ?a ?a 126 Appendix I. DDT choice of large reward during AMPH challenge. Each subject was exposed to saline and to each dose of AMPH once, in an order determined using a Latin-square drug design. Drugs were prepared fresh daily and were administered in a volume of 1 ml/mg, i.p., 10 min before testing. Data are presented as the mean plus/minus the standard error of the mean (? SEM). Significant main effects of dose, delay, and of group were determined by repeated-measures ANOVA, with Dose (saline, 0.3, 1.0, and 1.5 mg/kg) and Delay (0, 5, 10, and 20 sec) as within-subjects factors and Group (lithium, n = 8 vs. control, n = 7) as the between-subjects factor. The significant group effect was followed-up with separate ANOVAs for each group, which determined significant effects of Dose (a) and Delay (b). Significance levels are indicated as follows: ? = p < 0.001; ? = p < 0.01; ns = non-significant. Delay (sec) Dose of AMPH (mg/kg) Repeated-measures ANOVA Group Saline 0.3 1.0 1.5 Dose Delay Group Lithium 0 83.75 ? 8.65 97.14 ? 1.80 82.50 ? 8.61 92.50 ? 4.12 F(3, 39) = 1.26, ns F(3, 39) = 42.88 p < 0.001 F(1, 13) = 20.61 p = 0.001 5 62.50 ? 12.50 63.75 ? 9.81 42.50 ? 11.30 56.25 ? 9.44 10 46.25 ? 12.38 38.75 ? 10.25 36.25 ? 10.51 45.00 ? 12.25 20 18.75 ? 6.66 20.00 ? 8.66 25.00 ? 3.70 15.70 ? 9.82 Control 0 95.71 ? 2.97 100.00 ? 0.00 98.57 ? 1.43 97.14 ? 2.86 Delay x Group 5 84.29 ? 7.19 91.43 ? 4.04 92.86 ? 4.21 88.57 ? 3.40 F(1, 13) = 5.14 p = 0.004 10 65.71 ? 9.48 90.00 ? 4.36 84.29 ? 8.41 91.43 ? 3.40 20 55.71 ? 13.25 67.14 ? 8.92 75.71 ? 7.51 84.29 ? 5.71 ?b ?a ?b 127 Appendix J. DDT behavioural measures during AMPH challenge. Each subject was exposed to saline and to each dose of AMPH once, in an order determined using a Latin-square drug design. Drugs were prepared fresh daily and were administered in a volume of 1 ml/mg, i.p., 10 min before testing. Data are presented as the mean plus/minus the standard error of the mean (? SEM). Significant main effects of dose, delay, and of lithium treatment were determined using repeated-measures ANOVA, with Dose (0.3, 1.0, and 1.5 mg/kg) and Delay (0, 5, 10, and 20 sec) as within-subjects factors and Group (lithium, n = 8 vs. control, n = 7) as the between-subjects factor. Main effects of group were followed-up with separate ANOVAs for each group, where, for each group, repeated-measures ANOVA reported effects of Dose (a) and Delay (b). Where indicated, repeated-measures ANOVA showed interactions between: Dose x Delay (c), Dose x Group (d), Delay x Group (e), and Dose x Delay x Group (f). Dose effects were followed-up with paired-samples Student's t-test with each dose of AMPH paired with saline. Significance levels are reported as follows: ? = p < 0.001; ? = p < 0.01; * = p < 0.05; ? = 0.05 < p < 0.10, trend. Latencies are given in sec; ns = non-significant; N/A = not available. Behavioural Measure Dose of AMPH (mg/kg) Repeated-measures ANOVA Group Saline 0.3 1.0 1.5 Dose Delay Group Perseverative responses ?e Lithium 0.83 ? 0.50 1.53 ? 0.79* 2.53 ? 0.66? 2.88 ? 0.89? F(3, 39) = 11.07 p < 0.001 F(3, 39) = 4.34 p = 0.010 F(1, 13) = 0.27 ns Control 0.70 ? 0.28 0.95 ? 0.29* 2.09 ? 0.63? 2.40 ? 0.70? Anticipatory nose-poke responses Lithium 1.23 ? 0.43 0.96 ? 0.35 0.64 ? 0.24 1.25 ? 0.80 F(3, 39) = 1.35 ns F(2, 26) = 1.78 ns F(1, 13) = 0.60 ns Control 1.75 ? 0.76 2.39 ? 1.14 0.98 ? 0.55 1.22 ? 0.61 Anticipatory nose-poke latency Lithium 0.53 ? 0.20 0.45 ? 0.22 0.31 ? 0.15 0.29 ? 0.13 F(3, 39) = 1.70 ns F(2, 26) = 4.29 p < 0.024 F(1, 13) = 5.38 p = 0.037 Control 0.53 ? 0.16 0.69 ? 0.26 1.11 ? 0.19? 1.27 ? 0.18* Initiation latency Lithium 2.41 ? 0.32 2.13 ? 0.40* 1.90 ? 0.45* 1.72 ? 0.42* F(3, 39) = 4.23 p = 0.011 F(3, 39) = 9.76 p < 0.001 F(1, 13) = 1.95 ns Control 2.26 ? 0.32 1.47 ? 0.20* 1.24 ? 0.19* 1.21 ? 0.17* Response latency Lithium 0.84 ? 0.16 0.62 ? 0.09 0.82 ? 0.12 0.81 ? 0.16 F(3, 39) = 0.55 ns F(3, 39) = 6.92 p = 0.001 F(1, 13) = 1.21 ns Control 0.72 ? 0.16 0.61 ? 0.20 0.56 ? 0.11 0.62 ? 0.12 Latency to collect reward Lithium 0.85 ? 0.09 0.87 ? 0.08 0.80 ? 0.10 0.78 ? 0.07 F(3, 39) = 0.23 ns F(3, 39) = 2.57 p = 0.068 F(1, 13) = 0.48 ns Control 0.82 ? 0.11 0.74 ? 0.07 0.77 ? 0.10 0.75 ? 0.10 Omissions (%) Lithium 2.25 ? 0.94 2.00 ? 0.89 2.75 ? 1.03 1.50 ? 0.45 F(3, 39) = 1.60 ns N/A F(1, 13) = 3.08 ns Control 1.86 ? 0.51 0.29 ? 0.29 0.29 ? 0.18 0.86 ? 0.46 ?d,e ?c,f nsa,b ?a,b ?c 128 Appendix K. DDT choice of large reward during YHB challenge. Each subject was exposed to vehicle and to each dose of YHB once, in an order determined using a Latin-square drug design. Drugs were prepared fresh daily and were administered in a volume of 1 ml/mg, i.p., 10 min before testing. Data are presented as the mean plus/minus the standard error of the mean (? SEM). Significant main effects of dose, delay, and of group were determined by repeated-measures ANOVA, with Dose (vehicle, 1.0, 2.0, and 5.0 mg/kg) and Delay (0, 5, 10, and 20 sec) as within-subjects factors and Group (lithium, n = 8 vs. control, n = 7) as the between-subjects factor. Delay (sec) Dose of YHB (mg/kg) Repeated-measures ANOVA Group Vehicle 1.0 2.0 5.0 Dose Delay Group Lithium 0 97.50 ? 1.64 96.25 ? 2.63 93.75 ? 2.63 96.25 ? 2.63 F(3, 39) = 3.13 p = 0.036 F(3, 39) = 82.10 p < 0.001 F(1, 13) = 3.78 p = 0.074 5 68.75 ? 13.68 86.25 ? 8.44 77.50 ? 8.61 86.25 ? 5.32 10 35.00 ? 10.18 56.25 ? 12.24 46.25 ? 9.81 58.75 ? 11.09 20 20.00 ? 8.45 53.75 ? 10.68 35.00 ? 9.45 30.00 ? 8.66 Control 0 100.00 ? 0.00 100.00 ? 0.00 98.57 ? 1.43 92.86 ? 5.65 5 92.86 ? 1.84 95.71 ? 2.02 81.43 ? 5.53 91.43 ? 4.04 10 62.86 ? 9.93 84.29 ? 4.81 65.71 ? 9.48 62.86 ? 10.40 20 41.43 ? 12.23 57.14 ? 7.78 50.00 ? 13.45 47.14 ? 13.04 129 Appendix L. DDT behavioural measures during YHB challenge. Each subject was exposed to saline and to each dose of YHB once, in an order determined using a Latin-square drug design. Drugs were prepared fresh daily and were administered in a volume of 1 m/mg, i.p., 10 min before testing. Data are presented as the mean plus/minus the standard error of the mean (? SEM). Significant main effects of dose, delay, and group were determined using repeated-measures ANOVA, with Dose (vehicle, 1.0, 2.0, and 5.0 mg/kg) and Delay (0, 5, 10, and 20 sec) as within-subjects factors and Group (lithium, n = 8 vs. control, n = 7) as the between-subjects factor. Group differences were further analysed by separate ANOVAs for each group, where effects of Dose (a) and Delay (b) are indicated. Where indicated, repeated-measures ANOVA determined interactions between: Dose x Delay (c), Delay x Group (d), and Dose x Group (e). Dose effects were followed-up with paired-samples Student's t-test with each dose of YHB paired with vehicle. Significance levels are reported as follows: ? = p < 0.001; ? = p < 0.01; * = p < 0.05; ? = 0.05 < p < 0.10, trend. Latencies are given in sec; ns = non-significant; N/A = not available. Behavioural Measure Dose of YHB (mg/kg) Repeated-measures ANOVA Group Vehicle 1.0 2.0 5.0 Dose Delay Group Perseverative responses Lithium 0.80 ? 0.41 1.28 ? 0.65 1.29 ? 0.45 0.58 ? 0.25 F(3, 39) = 1.67 ns F(3, 39) = 2.10 ns F(1, 13) = 0.00 ns Control 0.88 ? 0.46 0.86 ? 0.41 1.18 ? 0.49 1.05 ? 0.48 Anticipatory nose-poke responses Lithium 1.56 ? 0.61 3.04 ? 0.88* 2.14 ? 0.77 1.38 ? 0.41 F(3, 39) = 3.26 p = 0.032 F(2, 26) = 2.42 ns F(1, 13) = 0.00 ns Control 1.58 ? 0.70 2.73 ? 1.39* 2.25 ? 1.56 1.68 ? 1.33 Anticipatory nose-poke latency Lithium 0.57 ? 0.20 0.80 ? 0.17 0.67 ? 0.23 0.63 ? 0.16 F(3, 39) = 0.79 ns F(2, 26) = 1.00 ns F(1, 13) = 0.17 ns Control 0.45 ? 0.19 0.75 ? 0.22 0.58 ? 0.23 0.50 ? 0.18 Initiation Latency Lithium 2.31 ? 0.28 2.15 ? 0.33 2.29 ? 0.31 2.94 ? 0.50 F(3, 39) = 0.70 ns F(3, 39) = 26.32 p < 0.001 F(1, 13) = 0.44 ns Control 2.07 ? 0.36 2.32 ? 0.29 2.23 ? 0.21 2.08 ? 0.26 Response latency Lithium 0.71 ? 0.17 0.60 ? 0.07 0.77 ? 0.15 0.91 ? 0.06? F(3, 33) = 10.17 p < 0.001 F(3, 33) = 5.76 p = 0.003 F(1, 11) = 0.01 ns Control 0.69 ? 0.17 1.00 ? 0.35 0.79 ? 0.23 1.27 ? 0.43? Latency to collect reward *d Lithium 0.89 ? 0.07 0.81 ? 0.10 0.97 ? 0.10 1.17 ? 0.16 F(3, 39) = 0.72 ns F(3, 39) = 3.23 p = 0.032 F(1, 13) = 0.58 ns Control *b 0.93 ? 0.20 0.86 ? 0.11? 0.91 ? 0.11 0.83 ? 0.07 Omissions (%) ? e Lithium 2.75 ? 1.01 1.00 ? 0.46 1.50 ? 0.63 4.38 ? 1.80 F(3, 39) = 0.13 ns N/A F(1, 13) = 0.01 ns Control 2.00 ? 0.95 3.14 ? 1.03 2.86 ? 0.77 2.29 ? 1.66 nsb 130 Appendix M. qPCR analyses: Effects of chronic lithium treatment on mRNA levels within the mPFC, OFC, and the NAc. Samples were extracted from animals tested on the 5-CSRTT and were processed via qPCR to assess the effects of chronic lithium treatment on gene expression. Mean threshold cycle (CT)-values were normalized to the housekeeping gene GAPDH. Data are presented as the mean plus/minus the standard error of the mean (? SEM). Abbreviations: mPFC = medial prefrontal cortex; OFC = orbitofrontal cortex; NAc = nucleus accumbens; ns = non-significant. (See Glossary for full name of target genes). Brain Region Gene of Interest mPFC OFC NAc Group Mean ? SEM Mean ? SEM Mean ? SEM ?FosB Lithium 1.011 ? 0.083 1.009 ? 0.150 1.610 ? 0.290 Control 1.098 ? 0.180 1.160 ? 0.250 1.257 ? 0.553 Student's t-test t(11) = -0.36, ns t(11) = -0.44, ns t(6) = -0.33, ns 5-HT1A Lithium 0.912 ? 0.075 0.839 ? 0.101 0.738 ? 0.291 Control 1.005 ? 0.038 1.014 ? 0.063 1.180 ? 0.326 Student's t-test t(11) = -1.23, ns t(11) = -1.56, ns t(8) = -1.01, ns 5-HT2A Lithium 0.920 ? 0.105 0.797 ? 0.046 1.066 ? 0.170 Control 1.042 ? 0.127 1.012 ? 0.063 1.067 ? 0.197 Student's t-test t(11) = -0.65, ns t(11) = -2.43, p = 0.033 t(8) = -0.01, ns 5-HT2C Lithium 0.787 ? 0.105 1.102 ? 0.191 1.209 ? 0.177 Control 1.015 ? 0.067 1.116 ? 0.231 1.016 ? 0.090 Student's t-test t(11) = -1.94, p = 0.079 t(10) = -0.05, ns t(8) = 0.97, ns ?1A-AR Lithium 0.855 ? 0.076 0.994 ? 0.050 1.024 ? 0.096 Control 1.025 ? 0.085 1.004 ? 0.035 1.010 ? 0.071 Student's t-test t(11) = -1.37, ns t(11) = -0.17, ns t(8) = 0.12, ns ?2A-AR Lithium 0.870 ? 0.044 0.986 ? 0.101 0.926 ? 0.245 Control 1.013 ? 0.061 1.042 ? 0.110 1.050 ? 0.162 Student's t-test t(11) = -1.89, p = 0.085 t(11) = -0.35, ns t(8) = -0.42, ns ?1-AR Lithium 0.861 ? 0.051 0.795 ? 0.053 1.176 ? 0.187 Control 1.016 ? 0.069 1.008 ? 0.050 1.073 ? 0.217 Student's t-test t(11) = -1.80, p = 0.100 t(11) = -2.80, p = 0.017 t(7) = 0.36, ns ?2-AR Lithium 1.013 ? 0.067 1.041 ? 0.073 0.976 ? 0.089 Control 1.012 ? 0.059 1.004 ? 0.033 1.030 ? 0.135 Student's t-test t(11) = 0.01, ns t(11) = 0.53, ns t(8) = -0.33, ns Bcl-2 Lithium 0.924 ? 0.020 0.951 ? 0.049 0.787 ? 0.317 Control 1.013 ? 0.063 1.009 ? 0.053 1.032 ? 0.119 Student's t-test t(11) = -1.08, ns t(11) = -0.75, ns t(6) = -0.88, ns BDNF Lithium 0.811 ? 0.078 0.788 ? 0.051 1.006 ? 0.136 Control 1.008 ? 0.047 1.012 ? 0.059 1.019 ? 0.131 Student's t-test t(11) = -2.30, p = 0.041 t(11) = -2.62, p = 0.024 t(4) = -0.68, ns cdk5 Lithium 0.921 ? 0.057 0.851 ? 0.025 1.172 ? 0.117 Control 1.004 ? 0.034 1.005 ? 0.038 1.033 ? 0.133 Student's t-test t(11) = -1.34, ns t(11) = -2.92, p = 0.014 t(8) = 0.78, ns 131 Brain Region Gene of Interest mPFC OFC NAc Group Mean ? SEM Mean ? SEM Mean ? SEM c-fos Lithium 0.770 ? 0.169 0.814 ? 0.165 1.004 ? 0.152 Control 1.127 ? 0.202 1.076 ? 0.150 1.736 ? 1.001 Student's t-test t(11) = -1.23, ns t(11) = -1.13, ns t(8) = -0.72, ns CREB Lithium 0.959 ? 0.034 0.851 ? 0.027 1.093 ? 0.108 Control 1.005 ? 0.039 1.007 ? 0.043 1.013 ? 0.081 Student's t-test t(11) = -0.82, ns t(11) = -2.63, p = 0.023 t(8) = -0.55, ns CSP Lithium 0.985 ? 0.056 0.892 ? 0.010 1.136 ? 0.146 Control 1.004 ? 0.035 1.004 ? 0.034 1.015 ? 0.089 Student's t-test t(11) = -0.30, ns t(11) = -2.50, p = 0.029 t(8) = 0.70, ns D1 Lithium 0.878 ? 0.070 1.371 ? 0.521 1.350 ? 0.268 Control 1.028 ? 0.094 1.155 ? 0.302 1.066 ? 0.195 Student's t-test t(11) = -1.14, ns t(8) = 0.56, ns t(8) = 0.86, ns D2 Lithium 1.208 ? 0.123 1.553 ? 0.334 1.548 ? 0.230 Control 1.010 ? 0.052 1.062 ? 0.160 1.070 ? 0.184 Student's t-test t(11) = 1.72, ns t(8) = 1.40, ns t(8) = 1.62, ns ERK1 Lithium 0.886 ? 0.021 0.865 ? 0.076 0.938 ? 0.054 Control 1.005 ? 0.037 1.015 ? 0.067 1.021 ? 0.113 Student's t-test t(11) = -2.37, p = 0.037 t(11) = -1.45, ns t(7) = -0.71, ns ERK2 Lithium 0.847 ? 0.071 0.876 ? 0.029 1.468 ? 0.312 Control 1.004 ? 0.035 1.009 ? 0.051 1.021 ? 0.119 Student's t-test t(11) = -2.22, p = 0.049 t(11) = -2.24, p = 0.047 t(7) = 1.21, ns Gsk-3? Lithium 0.872 ? 0.043 0.945 ? 0.034 1.284 ? 0.171 Control 1.002 ? 0.024 1.003 ? 0.028 1.005 ? 0.050 Student's t-test t(11) = -2.88, p = 0.015 t(11) = -1.29, ns t(8) = 1.57, ns M1 Lithium 1.012 ? 0.067 0.919 ? 0.023 3.150 ? 0.540 Control 1.003 ? 0.032 1.003 ? 0.030 1.197 ? 0.302 Student's t-test t(11) = 0.13, ns t(11) = -2.24, p = 0.047 t(8) = 3.16, p = 0.013 M2 Lithium 0.965 ? 0.041 0.886 ? 0.073 1.097 ? 0.243 Control 1.003 ? 0.031 1.006 ? 0.042 1.115 ? 0.263 Student's t-test t(11) = -0.76, ns t(11) = -1.54, ns t(8) = -0.05, ns NGF Lithium 0.956 ? 0.079 1.004 ? 0.087 1.150 ? 0.144 Control 1.007 ? 0.045 1.012 ? 0.059 1.025 ? 0.130 Student's t-test t(11) = -0.60, ns t(11) = -0.08, ns t(7) = 0.63, ns PSD-95 Lithium 0.999 ? 0.029 0.868 ? 0.036 1.338 ? 0.204 Control 1.006 ? 0.040 1.006 ? 0.040 1.044 ? 0.180 Student's t-test t(11) = -0.12, ns t(11) = -2.36, p = 0.038 t(7) = 1.05, ns TrkB Lithium 0.924 ? 0.028 0.961 ? 0.085 1.008 ? 0.124 Control 1.013 ? 0.061 1.005 ? 0.038 1.004 ? 0.043 Student's t-test t(11) = -1.09, ns t(11) = -0.54, ns t(8) = -0.31, ns
Thesis/Dissertation
eng
Neuroscience
Vancouver : University of British Columbia Library
Attribution-NoDerivs 2.5 Canada
Graduate
Chronic lithium treatment influences impulse control and cognition and regulates gene expression
Text