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The maturation of the acoustic change complex in response to iterated ripple noise in normal-hearing… Strahm, Stephanie 2019

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THE MATURATION OF THE ACOUSTIC CHANGE COMPLEX IN RESPONSE TO ITERATED RIPPLE NOISE IN NORMAL-HEARING TODDLERS   by   STEPHANIE STRAHM  B.A., The University of Ottawa, 2013 M.A., The University of Ottawa, 2014        A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF  THE REQUIREMENTS FOR THE DEGREE OF   MASTER OF SCIENCE    in    THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES    (Audiology and Speech Sciences)      THE UNIVERSITY OF BRITISH COLUMBIA  (Vancouver)    November 2019     © Stephanie Strahm, 2019   ii  The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: The maturation of the acoustic change complex in response to iterated ripple noise in normal-hearing toddlers  submitted by Stephanie Strahm in partial fulfillment of the requirements for the degree of Master of Science in Audiology and Speech Sciences  Examining Committee: Susan Small, Associate Professor, UBC Supervisor  Valter Ciocca, Professor, UBC Supervisory Committee Member  Rae Riddler, Clinical Pediatric Audiologist Supervisory Committee Member iii  Abstract With the introduction of newborn hearing screening and early intervention programs, there has been an increase in the number of early-identified hearing loss. However, clinical audiological test batteries do not currently include an objective (i.e., not requiring responses from the patient) measure of speech discrimination in very young infants and difficult-to-test populations. The ability to process temporal speech cues to discriminate between speech sounds is disrupted in all degrees of sensorineural hearing loss and in populations with auditory neuropathy spectrum disorder. The purpose of this study was to investigate the maturational time course of a cortical auditory evoked potential, the acoustic change complex (ACC) elicited to iterated ripple noise (IRN), as a possible clinical measure of speech perception capacity. Previously, Small et al. (in prep) determined that ACC responses to IRN stimuli are not mature in infants up to 16 months old. Participants were 27 children divided into two groups:  13 younger children (22 to 32 months; 6 males) and 14 older children (38 to 59 months; 5 males). IRN stimuli were created with varying degrees of pitch saliency by adjusting the number of iterations (4, 8, 16 & 32); each 500-ms IRN stimulus was concatenated to a 500-ms noise stimulus to generate noise-IRN (experimental) and noise-noise (control) conditions. Onset and ACC responses were recorded to all conditions presented binaurally under insert earphones while children were awake. All children had responses present to every IRN condition for at least one electrode site. Latencies decreased significantly as the number of iterations increased and the older children had significantly shorter ACC latencies than the younger group. Amplitudes were significantly smaller for the younger children compared to the older children; however, the effect of condition on ACC amplitudes between age groups did not reach significance. iv  Children as young as 22 months old have ACC responses elicited to low-saliency pitch stimuli, indicating that IRN discrimination abilities are emerging in this age group. Future research will determine how these processing abilities correlate with functional speech abilities in children with normal hearing and hearing loss.   v  Lay Summary  Part of a hearing test for older children and adults includes some form of speech testing that helps determine how a hearing loss affects everyday communication abilities. This also helps to determine whether the patient will benefit from interventions such as hearing aids or cochlear implants. Currently, there is no such test available for infants or difficult-to-test populations that have limited language skills. Previous research has looked into using brain responses to help clinicians determine speech abilities. This could lead to earlier intervention in these populations and possibly improve overall communication abilities and later language, reading, and academic skills. This study investigates how one of these brain responses matures (i.e., changes with age) to determine whether it could be used clinically. vi  Preface  The research described in this thesis was carried out in collaboration with my supervisor, Dr. Susan Small, at the University of British Columbia. The study was originally conceived by Dr. Small and Dr. Mridula Sharma, Macquarie University, Australia. The experiment set-up was developed by Dr. Susan Small and research assistant April Tian for an infant population and I modified it for the current study. I carried out participant recruitment, execution, data analysis, and writing. Dr. Small assisted on all aspects of the study’s development, including participant recruitment, study design, experiment set-up, statistical analysis, and writing.   This study was approved by the UBC Clinical Research Ethics Board (CREB), titled as “Speech perception and early auditory experience”; UBC CREB number: H07-01218  vii  Table of Contents  Abstract ......................................................................................................................................... iii!Lay Summary .................................................................................................................................v!Preface ........................................................................................................................................... vi!Table of Contents ........................................................................................................................ vii!List of Tables ................................................................................................................................ ix!List of Figures ............................................................................................................................... xi!List of Abbreviations ................................................................................................................. xiii!Acknowledgements .................................................................................................................... xiv!Dedication .....................................................................................................................................xv!Chapter 1: Introduction ................................................................................................................1!1.1! Current Audiological Testing ......................................................................................... 2!1.2! Considerations for a Clinical Assessment Tool .............................................................. 5!1.3! Cortical Auditory Evoked Potentials .............................................................................. 7!1.3.1! N1-P2 Onset Response ........................................................................................... 7!1.3.2! Mismatch Negativity ............................................................................................. 13!1.3.3! Acoustic Change Complex in Adults .................................................................... 14!1.3.4! Acoustic Change Complex in Children ................................................................ 17!1.4! Auditory Temporal Processing ..................................................................................... 21!1.4.1! Pitch Perception .................................................................................................... 23!1.4.2! Maturation of Auditory Temporal Processing ...................................................... 26!1.4.3! Auditory Temporal Processing and Hearing Loss ................................................ 29!viii  1.5! Iterated Ripple Noise .................................................................................................... 31!1.6! Rationale for Thesis ...................................................................................................... 34!Chapter 2: The Maturation of the Acoustic Change Complex in Response to Iterated Ripple Noise in Normal-Hearing Toddlers ................................................................................36!2.1! Participants .................................................................................................................... 36!2.2! Stimuli ........................................................................................................................... 38!2.3! EEG Recording ............................................................................................................. 39!2.4! Procedure ...................................................................................................................... 40!2.5! Data Analysis ................................................................................................................ 41!2.6! Adult Pilot data ............................................................................................................. 43!2.7! Predictions ..................................................................................................................... 46!2.8! Results ........................................................................................................................... 46!Chapter 3: Discussion and Conclusion ......................................................................................55!3.1! Discussion ..................................................................................................................... 55!3.2! Conclusion .................................................................................................................... 59!References .....................................................................................................................................61!Appendices ....................................................................................................................................87!A.1 Individual Toddler Amplitudes and Latencies ................................................................... 88!A.2 Individual Adult Pilot Amplitudes and Latencies ............................................................ 100! ix  List of Tables Table 1 Participant number, gender, and age for individual younger (22-35 months) and older (36-59 months) toddlers. ............................................................................................................... 37!Table 2 Number of participants tested per condition in the younger (22-35 months) and older (36-59 months) age groups. .......................................................................................................... 37!Table 3 Adult mean and 1 SD amplitudes (µV) and latencies (ms) for the N1 component of the ACC response for all IRN conditions and electrode sites. (2a) previously collected means (n = 8) from Small et al. (in prep) and (2b) means collected as pilot data for the current study (n = 5). . 44!Table 4 Summary of components present for the onset and ACC response for all IRN conditions and electrode sites in younger (22-35 months) and older (36-59 months) age groups. Total refers to the number of participants tested in each condition. ................................................................ 50!Table 5 Mean and 1SD amplitudes (Amp: µV) and latencies (Lat: ms) of the onset response (5a) and ACC response (5b) for each IRN condition and electrode in the (22-35 months) and older (36-59 months) age groups. .......................................................................................................... 52!Table A.1 Individual onest toddler amplitude (µV) for each condition measured at Cz ............. 88!Table A.2 Individual toddler onset amplitude (µV) for each condition measured at C3 ............. 89!Table A.3 Individual toddler onset amplitude (µV) for each condition measured at C4 ............. 90!Table A.4 Individual toddler onset latency (ms) for each condition measured at Cz .................. 91!Table A.5 Individual toddler onset latency (ms) for each condition measured at C3 .................. 92!Table A.6 Individual toddler onset latency (ms) for each condition measured at C4 .................. 93!Table A.7 Individual toddler ACC amplitude (µV) for each condition measured at Cz ............. 94!Table A.8 Individual toddler ACC amplitude (µV) for each condition measured at C3 ............. 95!Table A.9 Individual toddler ACC amplitude (µV) for each condition measured at C4 ............. 96!x  Table A.10 Individual toddler ACC latency (ms) for each condition measured at Cz ................ 97!Table A.11 Individual toddler ACC latency (ms) for each condition measured at C3 ................ 98!Table A.12 Individual toddler ACC latency (ms) for each condition measured at C4 ................ 99!Table A.13 Individual onest adult pilot amplitude (µV) for each condition measured at Cz .... 100!Table A.15 Individual adult pilot onset amplitude (µV) for each condition measured at C4 .... 102!Table A.16 Individual adult pilot onset latency (ms) for each condition measured at Cz ......... 103!Table A.17 Individual adult pilot onset latency (ms) for each condition measured at C3 ......... 103!Table A.19 Individual adult pilot ACC amplitude (µV) for each condition measured at Cz .... 104!Table A.20 Individual adult pilot ACC amplitude (µV) for each condition measured at C3 .... 105!Table A.21 Individual adult pilot ACC amplitude (µV) for each condition measured at C4 .... 105!Table A.22 Individual adult pilot ACC latency (ms) for each condition measured at Cz ......... 106!Table A.23 Individual adult pilot ACC latency (ms) for each condition measured at C3 ......... 106!Table A.24 Individual adult pilot ACC latency (ms) for each condition measured at C4 ......... 107! xi  List of Figures Figure 1 (A) Waveforms (IRN and noise), (B) spectra (IRN and noise), (C) IRN fast Fourier transform (FFT) spectra, and (D) IRN autocorrelation function for each stimuli condition: IRN4, IRN8, IRN16 and IRN32. ............................................................................................................. 39!Figure 2 Examples “good” (T15), “fair” (T29), and “poor” (T14) replicability ratings for pairs of waveforms elicited to the IRN4 condition. Waveforms are displayed as changes in amplitude (µV) and latency (ms). Replicability needed to be at least fair or good for the ACC portion of the waveform for the data to be included. .......................................................................................... 42!Figure 3 Grand mean waveforms for adults comparing the current pilot adults (solid lines) with data collected by Small et al. (in prep) (dashed lines). The waveforms displayed are the control condition (black), and IRN4 (red), IRN8 (blue), IRN16 (green), and IRN32 (purple) experimental conditions. Vertical lines represent the onset of the noise and IRN stimuli. The components of the onset and ACC response are labelled. The dotted horizontal line indicates zero amplitude. Horizontal coloured bars indicate significant difference in amplitude from the baseline (p < 0.05). ....................................................................................................................... 45!Figure 4 Variability of responses to IRN4 stimuli for the 22-35 month olds (red) and 36-59 month olds (blue). The averages are shown as bolded solid lines, the individual results are shown as light dashed lines. Vertical lines represent to onset of the noise and IRN stimuli. The components of the onset and ACC response are labelled. The dotted horizontal line indicates zero amplitude. .............................................................................................................................. 47!Figure 5 Grand mean waveforms of the 22-35 month olds (top) and the 36-59 month olds (bottom). The waveforms displayed are the control condition (black), and IRN4 (red), IRN8 (blue), IRN16 (green), and IRN32 (purple) experimental conditions. Vertical lines represent to xii  onset of the noise and IRN stimuli. The components of the onset and ACC response are labelled. The dotted horizontal line indicates zero amplitude. Horizontal coloured bars indicate significant difference in amplitude from the baseline (p < 0.05). .................................................................. 48!Figure 6 Grand mean waveforms for each IRN condition and control displaying the 22-35 month olds (solid) and the 36-59 month olds (dashed) for each electrode, Cz (red), C3 (green), and C4 (blue). Vertical lines represent to onset of the noise and IRN stimuli. The components of the onset and ACC response are labelled. The dotted horizontal line indicates zero amplitude. ....... 49!Figure 7 The ACC P to N amplitude displayed for the 3 to 16 month olds (Small et al., in prep), the 22-35 month olds, the 36-59 month olds and adults for IRN4 (red), IRN8 (blue), IRN16 (green), and IRN32 (purple) experimental conditions. Error bars represent 1SD. ....................... 53!   xiii  List of Abbreviations ABR: Auditory brainstem response ACC: Acoustic change complex AEP: Auditory evoked potential ANF: Auditory nerve fibre ANSD: Auditory neuropathy spectrum disorder CAEP: Cortical auditory evoked potential EEG: Electroencephalogram EHDI: Early hearing detection and intervention fMRI: Functional magnetic resonance imaging IRN: Iterated ripple noise ISI: Inter-stimulus interval MMN: Mismatch negativity N: Negative (e.g., N1, N2) P: Positive (e.g., P1, P2) SNHL: Sensorineural hearing loss TEOAE: Transient evoked otoacoustic emissions TFS: Temporal fine structure  xiv  Acknowledgements Thank you to Dr. Susan Small for her valuable feedback, guidance, and time invested to help me through this project. Thank you also to the members of my supervisory committee, Dr. Valter Ciocca and Rae Riddler who brought their expertise and perspectives to the project.  I am grateful to the members of the Pediatric Audiology Lab who assisted in testing, Ronald Adjekum, Sylvia Chan, Ricky Lau, and Candace Yip. Thank you especially to Serene Chang and Monique Tian for giving up your weekends to assist with data collection.  I also want to thank my classmates for their encouragement and motivation and for lending their time and ears whenever it was needed.  Finally to my partner Derek for his support and patience throughout my time in the program.  This research was funded through a Canadian Graduate Scholarship -Master’s (NSERC) awarded to Stephanie Strahm and an NSERC-Discovery Grant awarded to Susan Small.    xv  Dedication To everyone who got me through the master’s program including instructors, clinical educators, classmates, family, and friends.                1  Chapter 1:!Introduction As newborn hearing screening and early intervention (EHDI) programs become more popular world-wide, it is important to develop tools that assess functional hearing abilities at much younger ages. According to guidelines set out in EHDI programs, all infants should be screened for hearing loss by 1 month of age, identified by 3 months, and have appropriate intervention implemented by 6 months of age (Canadian Infant Hearing Task Force, 2016; Joint Committee on Infant Hearing, 2007). This early intervention for infants identified with a hearing loss leads to significantly better outcomes in speech and language development as well as later academic performance (Kennedy et al., 2006; Moeller, 2000; Yoshinaga-Itano, Sedey, Coulter, & Mehl, 1998). For a child learning an oral language, rich and varied auditory input from birth is important to reach language milestones later in development (reviewed in Saffran & Kirkham, 2018). Even a mild sensorineural hearing loss may lead to poorer speech and language outcomes in childhood (Bess, Dodd-Murphy, & Parker, 1998). This may be due, in part, to temporal processing deficits that often accompany sensorineural loss (reviewed in Moore, 2008). Another population with significant temporal processing deficits are those with auditory neuropathy spectrum disorder (ANSD). Due to disruptions in temporal processing, individuals with ANSD have some abnormal or absent electrophysiological responses typically tested for very young infants. Therefore, auditory threshold testing in this population is often delayed until behavioural results can be obtained at about 6-7 months of age (He, Teagle, Roush, Grose, & Buchman, 2013; Parfett, 2018; Pham, 2017). Even with normal audiometric pure-tone thresholds, individuals with ANSD may have difficulties understanding speech due to disruptions higher in the auditory system (He, 2016; Norrix & Velenovsky, 2014; Rance & Starr, 2015). This creates challenges for the provision of amplification within the prescribed EHDI timelines.  2  It is important to develop an objective clinical tool to assess speech perception abilities in infants and difficult to test populations in order to optimize outcome benefits for cases of temporal processing disruptions. In this context, “objective” refers to the response from the patient; a “subjective” test requires the patient to choose when to answer, whereas, an “objective” test does not require an active response from the patient, only interpretation of the findings by the examiner. To develop this tool, researchers have recommended electrophysiological measures. The current study will investigate the maturation of one cortical auditory evoked potential (CAEP), the acoustic change complex (ACC), as a possible electrophysiological clinical measure to predict speech processing abilities in toddlers (1 to 4 years old). The stimuli used to evoke the ACC response will be iterated ripple noise (IRN) which may be related to auditory temporal processing cues that are often disrupted across all degrees of sensorineural hearing loss, including ANSD.   This review of the literature will first describe current audiological testing methods and gaps in the audiological test battery. Some considerations for what constitutes a well-developed clinical testing tool will follow. Three CAEP measures will be discussed in terms of the advantages and disadvantages of their use, maturation of the responses, and the effects of hearing loss on these responses. Next, there will be a description of auditory temporal processing, encompassing the physiology, perception, maturation, and disruption in processing due to hearing loss. Finally, there will be a detailed description of the stimuli used in the current study, iterated ripple noise (IRN), and previous studies using this stimulus. 1.1! Current Audiological Testing Behavioural testing for frequency-specific audiological threshold estimation can be conducted beginning around 6 months of age in an otherwise typically developing infant (Hicks, 3  Tharpe, & Ashmead, 2000). For very young infants, thresholds are routinely estimated using auditory evoked potential measures. The auditory brainstem response (ABR) is one of the most commonly used electrophysiological threshold measure in infants. ABR testing is also used as a measure of hearing thresholds into adulthood (e.g., compensation cases, unreliable results, or suspected pseudohyperacusis) and for populations that are difficult to test behaviourally (e.g., developmental delays). An ABR is elicited in response to a brief-tone stimulus and is used to determine frequency-specific hearing thresholds. Other advantages of ABR assessments are that results can be obtained without the overt attention of the patient, they can be measured while asleep or sedated, and it is a non-invasive procedure. There are two important limitations to ABR testing in pediatric populations. First, the presence of ABR waves (typically identified as peaks I to V) depends on the neural synchrony of the auditory nerve and connections between structures in the brainstem. In disorders such as ANSD, this neural synchrony is disrupted (Rance & Starr, 2015; Starr et al., 1996). Behavioural hearing thresholds in ANSD populations can range from normal hearing to a profound hearing loss. However, even with behavioural hearing thresholds within normal limits, the ABR components are absent or abnormal. Because it is not possible to obtain reliable ABR thresholds in infants with ANSD, an intervention option such as fitting hearing aids, is often delayed until threshold data can be obtained behaviourally. Furthermore, patients with ANSD often have additional co-morbities, which further delays the onset of reliable behavioural results.  The second limitation with ABR testing is that it measures the ability to detect that a signal has occurred but does not tell audiologists what infants perceive or how they integrate complicated auditory signals like speech. For example, ABR thresholds cannot tell audiologists how infants process auditory temporal cues such as differences in pitch to aid in discrimination 4  between speech sounds. A typical audiological test battery for an adult or older child includes some form of behavioural testing using a speech signal to assess functional auditory skills of the individual. Certain populations, such as infants and individuals with low verbal skills, are unable to be tested using these behavioural methods. Currently, objective tests of functional auditory skill, which are important for very young infants or difficult-to-test populations who cannot provide subjective behavioural responses, are not available. This gap in the audiological test battery has implications for determining the benefits of amplification. The benefits of amplification for young infants with a hearing loss or with ANSD are currently measured using subjective caregiver questionnaires. The earliest age that an audiometric speech discrimination test can be administered reliably is between 18 and 24 months, in an otherwise typically developing child (McCreery & Walker, 2017). In older children and adults, performance in speech tests as well as subjective impressions help to verify and validate amplification benefits. Speech tests can also be used to help determine hearing levels in cases of ANSD.  As the global number of EHDI programs increases to meet the 1-3-6 month guidelines, there remains a shortage of clinical tools to test speech perception or functional hearing in very young infants, difficult-to-test populations, and populations where current clinical testing is unreliable such as those with ANSD. To remedy this, researchers have been turning towards electrophysiological measures to develop a clinically viable tool. The current study is a first step towards the use of a CAEP, the acoustic change complex (ACC), as a possibility for a clinical speech perception test. The purpose of this research is to determine the maturation of the ACC response elicited by IRN stimuli in normal-hearing children. 5  1.2! Considerations for a Clinical Assessment Tool A well-designed clinical testing tool must be able to balance costs and benefits (Turner, Robinette, & Bauch, 1999). Costs include the number of false positives or missed diagnoses, the monetary cost of equipment and training, and the time efficiency of the test in a busy clinic. Benefits include the ability of a tool to correctly identify a specific condition while minimizing false positives. Time efficiency is especially important when diagnosing infants and young children as there is only a short period in which to obtain reliable results before cooperation or tolerance towards the procedure decreases. The effectiveness of a test tool can be defined in terms of psychometric measures. A good tool must be specific (correctly identifies those who do not have the condition), sensitive (correctly identifies those who have the condition), valid (accurately measures the intended measure), and reliable (measures are consistent over multiple sessions or examiners). The tool should also be norm-referenced to the population of its intended use, which may include age, gender, or language (American Psychological Association, 2014; Lucks Mendel & Danhauer, 1997; McCauley & Swisher, 1984). In developing an audiological tool, it is important to keep in mind the different levels of auditory processing. Erber (1982) described four auditory processing levels: awareness, discrimination, identification, and comprehension. The ability to process higher levels depends upon the ability to process lower levels. For example, it is not possible to comprehend an utterance without being aware someone is speaking, discriminating between the sounds they are making, and identifying individual words. In the current audiological test battery, the lowest auditory processing level, awareness, is tested by threshold measures. Discrimination requires the ability to detect a change in an acoustic stimulus. There are currently no widely used clinical 6  tests that only measure discrimination, although tests targeting higher processing levels must take discrimination abilities into account. Identification requires a label to be attached to an auditory stimulus. Speech testing with young children is one example of identification; children are given a set of images and are asked to identify (often by pointing) a target in response to words presented auditorily while presentation level is varied. Finally, comprehension requires integrating the identified auditory stimuli and combining them in a meaningful way. For example, listening to a short story and answering questions. Comprehension is not typically tested in a standard audiometric exam which typically only assesses recognition of single words. Currently, young infant and difficult-to-test populations are assessed only at the level of awareness. For an otherwise typically developing child, behavioural tests of discrimination are performed beginning at 18- to 24-months old (McCreery & Walker, 2017). Before this age, there are no clinical tests to determine how the detection of those sounds corresponds to the perception of speech until a child’s receptive language matures. Note that behavioural experimental methods do exist to measure speech perception in infants but are often time consuming and not feasible clinically. The development of clinical tools to measure higher levels of auditory processing is important for tracking outcome measures for hearing aids and cochlear implants. For example, amplifying the incoming sound information does not necessarily make it more intelligible (especially in individuals with auditory processing disorders, problems with temporal processing, or who experience distortion at higher intensities). Development of an objective speech perception tool is particularly important for infants with disorders such as ANSD, who may have normal auditory threshold levels but have difficulties understanding speech due to lesions higher in the auditory system (He, 2016; Norrix & Velenovsky, 2014; Rance & Starr, 2015). There are challenges in providing interventions, such as amplification, for infants with 7  ANSD as it is necessary to wait for behavioural thresholds, causing significant delays. There are also currently no clinical tests to identify the degree of speech processing deficits in this population.  Although the current study will not be analyzing the psychometric measures needed to create a clinically relevant assessment tool, the results of this study may contribute to future development of clinical tests. The next section will review auditory evoked cortical responses that are related to higher-level auditory processing. It has been proposed that these responses may be the key to developing a speech perception test for very young infants, individuals with ANSD or auditory processing disorders, and other difficult to test populations. 1.3! Cortical Auditory Evoked Potentials 1.3.1! N1-P2 Onset Response Auditory evoked potentials (AEPs) refer to changes in electrical energy measured at the scalp in response to an auditory stimulus. These responses are time-locked to the onset of the stimulus and are displayed as averaged waveforms. Each change in voltage (displayed as a measured wave) corresponds to the activation of different neural areas as processing of acoustic information moves up the auditory pathway over time. This section will focus on late AEPs originating from the auditory cortex. The series of positive and negative peaks is labelled the N1-P2 onset response. In adults, the latency of the N1 peak ranges from 100 to 150 ms after the stimulus onset and the P2 peak around 175 ms (Näätänen & Picton, 1987; Picton, 2011).  These late potentials are evoked by the onset of an auditory stimulus. For very long sustained stimuli they also occur at the offset (Davis, 1939; Onishi & Davis, 1968). In adults, the dominant N1 wave is generated by a combination of activated areas in the primary auditory cortex and auditory association areas (reviewed in Lightfoot, 2016; Näätänen & Picton, 1987). 8  Each of these cortical areas generates its own N1-P2 response and the electrical signals are summed together to create a measurable waveform. The presence of the N1-P2 complex indicates detection of the auditory signal by the listener (Davis, 1939). The N1-P2 has been proposed as a way to measure audiometric thresholds in adults (reviewed in Hyde, 1993; Lightfoot, 2016). It is currently used clinically with adolescents and adults with unreliable behavioural thresholds as well as in cases of medicolegal or occupational hearing loss (Dejonckere & Coryn, 2000; Hyde, 1997). It is also used for verification of amplification in infants and children in Australia (Punch, Van Dun, King, Carter, & Pearce, 2016).  The latency, amplitude, and morphology of CAEPs are sensitive to stimulus and subject parameters. In adults, as the intensity of pure-tone and click stimuli decreases (i.e., approaches audiometric thresholds), the amplitude of N1 decreases and the latency increases (Beagley & Knight, 1967; Onishi & Davis, 1968; Spoor, Timmer, & Odenthal, 1969). As the frequency of a pure-tone stimulus increases, the N1 amplitude decreases (Antinoro, Skinner, & Jones, 1969; Spoor, Timmer, & Odenthal, 1969). Amplitudes and latencies of the waves are also affected by the rate of presentation or inter-stimulus interval (Nelson & Lassman, 1968; Nordby, Roth, & Pfefferbaum, 1988), rise- and fall-times (Kodera et al., 1979; Onishi & Davis, 1968), and spectral complexity of the signal (Bardy, Van Dun, & Dillon, 2015). The amplitude and latency of the N1-P2 onset response are also sensitive to subject parameters. One significant subject parameter is attention. As attention to the incoming stimuli increases, the amplitudes of N1 and P2 increase (Hillyard, Hink, Schwent, & Picton, 1973; Picton & Hillyard, 1974). For example, Picton and Hillyard (1974) compared N1-P2 waveforms when participants counted the number of stimuli and while participants read a book during stimuli presentation. The amplitudes of N1 and P2 were significantly higher in the overt attention 9  condition. Sleep state also affects the N1-P2 response. Recording during sleep causes a decrease in N1 amplitude as well as more variable waveforms (Osterhammel, Davis, Wier, & Hirsh, 1973). Attention and sleep-state are especially important when considering testing with very young infants. One reason the ABR is used clinically for infant testing is because the components of this response are present during sleep or even sedation. This prevents contamination of the response due to myogenic artifacts caused by movement of the child. Age is another important subject variable in CAEP testing. There are changes to the morphology, amplitude, and latency of the response from infancy to adulthood to the elder years (Goodin, Squires, Henderson, & Starr, 1978; Shucard, Shucard, & Tomas, 1987; Wunderlich, Cone-Wesson, & Shepherd, 2006). Wunderlich, Cone-Wesson, and Shepherd (2006) investigated the changes in latency and amplitude of the CAEP response in typically developing infants, toddlers, children, and adults. The results indicate consistent changes in scalp distribution, morphology, latency and amplitude of the response from age 3- to 13-months and adulthood. The infant results were more variable and amplitudes depended on the stimulus that was presented. These changes indicate a developmental difference in the source and/or positioning of the neural generators of these waves and in overall auditory processing abilities between infants and adults.  CAEPs are ontogenetically one of the earliest measurable auditory responses and can be recorded in preterm infants at 24 weeks gestation (Weitzman & Graziani, 1968). The morphology of the N1-P2 response in preterm infants is predominantly negative and diffused across the scalp. Between 26- to 40-weeks gestational age, the predominant wave becomes positive, indicating a change in the sources of the response as the cortex develops (Lengel, Chen, & Wakai, 2001; Rotteveel, Colon, Stegeman, & Visco, 1987). 10  In full term newborns up to 6 months of age, the CAEP response is monophasic with a large positive component occurring between 200 to 250 ms (reviewed in Picton & Taylor, 2007; Wunderlich & Cone-Wesson, 2006). This positive response is generated in the temporal lobe near the auditory association areas. Over the first few months of life, the amplitude of the response decreases and becomes more reliable and less variable. These early changes are likely due to shifts in the synaptic organization and myelination of the auditory cortex. In toddlers, the responses have variable morphologies with the large positive response gradually decreasing and the negative response emerging as the dominant wave. The latency of the responses also decreases as there is continued myelination and synchronization of responding areas. (Barnet, 1971; Barnet, Ohlrich, Weiss, & Shanks, 1975; Ceponiene et al., 2003; Choudhury & Benasich, 2011; Haapala et al., 2013; Mills, Coffrey-Corina, & Neville, 1997; Molfese & Molfese, 1978; Molfese & Molfese, 1988; Niemitalo-Haapola, Haapala, Jansson-Verkasalo, & Kujala, 2015; Shafer, Yu, & Wagner, 2015).  In older children and into adolescence, the response morphology continues to increase in complexity, with well-defined and reliable peaks. The morphology is adult-like by twelve years of age (Ponton et al., 2000). Latencies continue to decrease and amplitudes to increase throughout adolescence and into adulthood. The source and orientation of the dipoles (the electric field generated at the source of the response) are mature by 5 years old, however synchrony of the responses and amplitude of the waves, continues to increase (Albrecht, Suchodoletz, & Uwer, 2000). Another subject variable affecting late CAEP thresholds is the individual’s degree of hearing loss. Audiometric CAEP thresholds fall within 7 to 10 dB above the behavioural threshold in adults (Ross, Lütkenhöner, Pantev, & Hoke, 1999; Van Dun, Dillon, & Seeto, 2015, 11  Van Maanen & Stapells, 2005). However, in all infants identified with a permanent hearing loss in Australia over the course of one year, 20% had absent CAEP responses at a sound level which should have been audible (Punch et al., 2016). Therefore, a present CAEP threshold can be informative in patients with a hearing loss but an absent response at audible levels may not be significant. Similarly, it was found that normal-hearing subjects receiving 20 dB of gain from a hearing aid show no significant differences in N1-P2 responses compared to an unaided condition (Billings, Tremblay, Souza, & Binns, 2007; Jenstad, Marynewich, & Stapells, 2012). In other words, with a decrease in the behavioural threshold of these participants there was no corresponding decrease in CAEP thresholds. This may be due to a reduced signal-to-noise ratio that occurs when providing amplification to a normal-hearing ear. The internal noise of the hearing aid causes the incoming signal to be less audible over the extraneous noise. When CAEPs are recorded from listeners with a hearing loss, aided responses increase in amplitude compared to unaided conditions as expected (Chang et al., 2012; Van Dun, Kania, & Dillon, 2016). This is useful in verifying hearing aid settings in infants as it is expected that the amplitude of the N1-P2 response will increase if the hearing aid output is sufficient compared to no amplification (Punch et al., 2012).  CAEPs are also useful in determining hearing thresholds or audibility in patients with ANSD (Pearce, Golding, & Dillon, 2007; Rance, Cone-Wesson, Wunderlich, & Dowell, 2002). Due to the lack of synchrony in the auditory system of ANSD patients, the ABR components are absent or abnormal. CAEP responses require less synchrony to be recorded and it is hypothesized that the presence of CAEPs may be related to the degree of speech perception abilities in these populations (Rance et al., 2002). 12  To summarize, CAEPs are measurable even in preterm babies. The response changes across early development as myelination and synaptic pruning increases the efficiency of the processing of an auditory signal in the cortex. This causes changes in the morphology, latency, and amplitude of the response as the cortex matures. Generally, the CAEP goes from a monophasic positive response in newborns to a triphasic predominantly negative response in adults. With maturation, latency of the response decreases with an increase in myelination and amplitudes increase due to improvements in the synchrony of responses (reviewed in Wunderlich & Cone-Wesson, 2006). As a clinical tool, CAEPs can be useful in determining auditory thresholds for infants and difficult to test populations (Purdy et al., 2005; Chang et al., 2012). However, because the responses of the CAEP are more reliable in an alert but very still subject, ABR measures (which can be determined in a sleeping or sedated infant) are still used more often for these populations. The CAEP onset responses are more often used audiologically in adult populations for determining audiometric thresholds, although they are also used clinically in Australia for verification of amplification in infants and in cases where ABRs are not reliable. Additionally, like ABR, the CAEP thresholds only measure the awareness or detection stage of speech processing.  The review above focusses on responses to the onset of an auditory stimulus. Late CAEP responses can also be recorded to an unexpected auditory change between two stimuli or within an ongoing stimulus. Two of these discrimination measures will be discussed in the next section. The mismatch negativity (MMN) response is a difference measure between two stimuli and has been extensively studied. The acoustic change complex (ACC) is a response to a change in an ongoing stimulus and has more recently been proposed as a discrimination measure that may be clinically feasible. 13  1.3.2! Mismatch Negativity  The N1-P2 onset response described above is an automatic response to the onset of an auditory stimulus. Näätänen, Gaillard, and Mäntysalo (1978) discovered that changes in an otherwise constant stimuli produce a second component which resembles the N1-P2 waveform. The response to the deviant auditory stimuli is called the mismatch negativity (MMN) response. An oddball paradigm is used to evoke this response, where a standard stimulus is presented repeatedly and randomly interspersed with a deviant stimulus. If the participant detects the acoustic change between the standard and the deviant (i.e., discriminates the change), the MMN is present. The bigger the perceived changes between the standard and deviant stimuli, the larger the MMN response (Näätänen et al., 1978; Squires, Squires, & Hillyard, 1975). The MMN occurs whether or not the participant is overtly attending to the stimuli (Näätänen, Paavilainen, Rinne, & Alho, 2007; Picton, 1995). The response can be elicited by changes in frequency (Hari et al., 1984; Näätänen et al, 1978; Sams, Paavilainen, Alho, & Näätänen, 1985) or intensity (Näätänen et al., 1978; 1988). The MMN response has been extensively investigated and it has been elicited by temporal changes such as duration, gaps, and rise time as well as changes in spatial location, stimulus order, complex stimuli, and segment order (reviewed in Näätänen et al., 2007). The MMN has been used to investigate the speech perception abilities in a variety of populations including those with developmental disorders (such as dyslexia, Down syndrome, autism spectrum disorder, and specific language impairment), psychiatric disorders (such as schizophrenia, bipolar disorder, depression), neurologic disorders (such as Alzheimer’s disease, coma patients, and the elderly) (reviewed in Näätänen, 2003).  The MMN response has been consistently shown to be present in young infants, including newborns (reviewed in Alho & Cheour, 1997). The response has even been found in 14  premature newborns born between 25 and 34 weeks gestation (Cheour-Luhtanen et al., 1996). While there are some developmental changes in terms of latency, the MMN in newborns is morphologically similar to that of adults (Alho & Cheour, 1997) and has matured to an adult-like pattern by four months old (He, Hotson, & Trainor, 2009).   Since the MMN is present in very young infants and requires no overt attention, it has been proposed as a possible electrophysiological tool for measuring speech perception across development (Alho & Cheour, 1997; Näätänen, 2003; Sussman, Chen, Sussman-Fort, & Dinces, 2014). The MMN findings reveal high sensitivity for many acoustic aspects of speech discrimination; however, there are some limitations of this measure. The MMN is calculated by taking the difference between the averaged responses to standard and deviant stimuli. Using the oddball paradigm, only the deviant stimuli are considered test trials. In typical studies, the probability of a deviant trial is around 20% (Näätänen et al., 2007). Therefore, 80% of the presented stimuli do not contribute to the MMN response. This results in a decreased signal-to-noise ratio leading to long test times (Picton, 1995). Although the MMN has been recorded at the individual level for infants (Uhler, Hunter, Tierney, & Gilley, 2018), it is more reliable at the group level (Picton, 1995). The low efficiency may make it difficult to develop a viable clinical tool, as testing time is often limited with infants and young children. The next section will discuss another late CAEP, the acoustic change complex, which has many of the advantages of the MMN and may overcome some of the challenges. 1.3.3! Acoustic Change Complex in Adults The acoustic change complex (ACC) has been extensively investigated in adults and can be elicited to changes in a wide variety of speech cues. The ACC is a late CAEP response to an acoustic change in an ongoing auditory stimulus (Ostroff, Martin, & Boothroyd, 1999). If a 15  response occurs, it can be inferred that the listener perceives the difference or change in the stimulus (Kaukoranta, Hari, & Lounasmaa, 1987; Martin & Boothroyd, 1999). In adults, the ACC is characterized by a P1-N1-P2 waveform that is time-locked to the change in the stimulus. The ACC shares many of the same advantages as the MMN. The ACC does not require the overt attention of the listener and has been elicited to many different acoustic stimuli. The ACC also has advantages over the MMN as it has a larger amplitude (i.e., is not a difference score) and requires fewer presentations to determine presence or absence of a response (Martin & Boothroyd, 1999; Picton, 1995). The larger signal-to-noise ratio of the ACC makes it a more time-efficient measure, which is important in a pediatric test. The larger amplitude of the individual ACC waveforms also means it is potentially more reliably present at an individual level. Ostroff, Martin and Boothroyd (1998) performed one of the early studies investigating the ACC response. The N1-P2 onset response had been well documented to the beginning of a stimulus, but these authors used natural speech (the word “say”) to investigate changes in cortical potentials at the phonemic level. Eight normal hearing adults were presented with the sounds /sei/, /s/, and /ei/. As expected, these participants had a N1-P2 response to the onset of each of these stimuli. A second response was also observed at the transition between the consonant and vowel of /sei/. This transitional response resembled the N1-P2 components of the onset response but were smaller in amplitude. The authors concluded that the presence of the second wave complex indicates the detection of a change in acoustic information between the consonant and the vowel. From this first study, it was unclear whether the ACC response at the consonant-vowel transition was due to a change in amplitude, periodicity, spectral envelope or a combination of 16  the complicated changes in acoustic cues found in natural speech. A series of follow-up studies aimed to narrow the possible acoustic parameters causing the ACC response. Results of these studies suggested that the ACC can be elicited by changes in periodicity (Martin & Boothroyd, 1999), as well as amplitude and formant frequency (Martin & Boothroyd, 2000). Subsequent studies have elicited the ACC in response to changes between speech sounds (Chen & Small, 2015; Martinez, Eisenberg, & Boothroyd, 2013; Small & Werker, 2012; Tremblay, Friesen, Martin & Wright, 2003; Uhler, Hunter, Tierney, & Gilley, 2018), frequency (Harris, Mills, He, & Dubno, 2008; Mathew et al., 2016), intensity (Harris, Mills, & Dubno, 2007), temporal cues such as gaps (Atcherson, Gould, Mendel, & Ethington, 2009; Jordan, 2016; Lister, Maxfield, & Pitt, 2007; Michalewski, Starr, Nguyen, Kong, & Zeng, 2005; Pratt, Starr, Michalewski, Bleich & Mittleman, 2007) and voice onset time (Tremblay, Billings, & Rohila, 2004; Tremblay, Piskosz, & Sousa, 2002). The ACC has been shown to be strongly correlated with behavioural measures in adults (He, Grose, & Buckman, 2012; Martin & Boothroyd, 1999; Mathew et al., 2016; Won et al., 2011). The ACC has also been found to have high test-retest reliability (Friesen & Tremblay, 2006; Tremblay, Friesen, Martin, & Wright, 2003). It is present in adults and children with hearing loss as well as in adults with cochlear implants (Brown et al., 2008; Friesen & Tremblay, 2006; Kim, Brown, Abbas, Etler, & O’Brien, 2009; Martinez, Eisenberg & Boothroyd, 2013; Mathew et al., 2016). The ACC can also be recorded in adults with ANSD (Michalewski, Starr, Nguyen, Kong, & Zeng, 2005). The ACC has been shown to be robust enough to provide individual-level data in adults (Small & Werker, 2012). Only a few studies have investigated the ACC in infants and children and these will be described in detail in the next section. 17  Overall, the ACC response shares the advantages of the MMN in the lack of overt attention and correlation with behavioural data but it also is a larger response which requires fewer trials to determine its presence. The ACC may be a more sensitive measure of discrimination, and may be more useful for clinical use. 1.3.4! Acoustic Change Complex in Children  The ACC has been increasingly suggested as a clinical testing tool to assess speech perception abilities in infants and difficult to test populations (Kim, 2015; Martin, Tremblay, & Korczak, 2008; Small, 2015). However, only a few studies have investigated the ACC response in these populations. This section will focus on the details of studies investigating the ACC in infants and children. In one of the first studies examining the presence of the ACC in young infants, Small and Werker (2012) investigated the ACC in 4-month-old infants to native and non-native speech contrasts. Participants in this study were English-learning and had normal hearing. The stimuli chosen for this study were the English contrast /daba/ as well as the Hindi dental retroflex /daɖa/. Previous behavioural data have shown that within the first year of life infants lose their abilities to discriminate between non-native speech contrasts while experience with their native language strengthens discrimination abilities for native language contrasts (Eimas, Siqueland, Jusczyk, & Vigorito, 1971; Werker, Gilbert, Humphrey, & Tees, 1981; Werker & Tees, 1985). Therefore, it was predicted that young infants who behaviourally show discrimination of this contrast would also have an ACC response compared to an adult group that would only show a response elicited to the English contrast. These predictions are also consistent with previous studies investigating MMN responses to native and non-native speech contrasts. Cheour et al. (1998) and Rivera-Gaxiola et al. (2005) reported MMN responses to non-native consonant contrasts for infants 18  younger than 8 months old. These responses were reduced in older infants as they gained experience with contrasts in their target language. The results from this first study by Small and Werker found that an ACC response was present in infants to the native /daba/ stimulus. Unexpectedly, all components of the ACC response were not present with the non-native /daɖa/ stimulus and the ACC was present in adults for both native and non-native contrasts. The unexpected results may be explained by the stimulus parameters chosen in this study. The authors stated that the stimuli durations chosen for this study may not have provided a long enough refractory period in the immature cortex, especially for the less familiar non-native sound contrast.  The study by Small and Werker was a preliminary step towards determining whether changing acoustic stimulus parameters can elicit an ACC response in infants. Chen and Small (2015) used the same sets of stimuli and methodology but with changes to the stimulus parameters to elicit the ACC in 4-month-old infants and adults. The differences in this study were an increased stimulus length (564 ms in the first study increased to 816 ms) to accommodate the immature refractory periods in infants. The results showed a significantly larger ACC response to both the native and non-native contrasts when compared to a no-change control condition (/dada/). These results are consistent with previous behavioural and MMN studies and suggest that the 4-month-olds are able to perceive a difference between both /da-ba/ and /da-ɖa/. However, when these stimuli were optimized for infants, there were no longer differences in responses elicited in the adult group between conditions. The authors suggested that the stimuli were now too long for adults and they no longer perceived the two tokens as belonging together (e.g., instead of perceiving /daba/, adults perceived /da/ /ba/ and an onset N1-P2 response was elicited to both syllables). This is consistent with the physiological differences 19  in the brains of infants and adults leading to changes in auditory processing. Therefore, it is important not to assume that speech perception abilities are the same in these populations and to investigate how to optimize speech perception tests for infants and children. A study by Martinez, Eisenberg, and Boothroyd (2013) has extended the elicitation of the ACC response to include children ages 2 to 6 years old with normal hearing as well as with sensorineural hearing loss (SNHL) using binaural amplification. The stimuli used in this study were changes in vowel height (/ua/) and vowel place (/ui/) which correspond to a change in formant frequency. The ACC was reliably elicited in all but the youngest participant which may have been due to high electrode impedances for this child rather than an absence of the response. The children with SNHL were tested with their hearing aids on. Two children were also tested unaided and had significantly reduced responses. These results are promising in the use of the ACC response as a tool to measure the benefits of amplification in young children, although the sample size for both groups was low (5 normal hearing, 5 hearing loss). Recently Uhler, Hunter, Tierney, and Gilley (2018) investigated whether the ACC can be elicited in sleeping infants. If the response is present during sleep, it would increase its usefulness as a clinical tool as sleeping infants have fewer rejected trials due to myogenic noise, resulting in more efficient recording times. These authors explored whether either the ACC or MMN responses can provide reliable measures in sleeping infants for detection and discrimination of vowels (/a/ and /i/). Participants in this study were 1- to 4-month-olds with normal hearing. Results indicate that the MMN provides a reliable measure at the individual level for both detection and discrimination of the two vowel stimuli. However, the ACC was only reliable at the detection level. When presented with the stimuli /i-a-i/, there was no significant ACC response to the change in vowel. This suggests that the measure was not 20  sensitive to discrimination at the individual level for the vowel contrasts, at least while infants are asleep. The presence of an onset N1-P2 response during sleep is promising and further research is needed to determine if different stimulus or recording parameters could result in an ACC response in sleeping infants. He et al., (2015) investigated whether the ACC response can be elicited in children with ANSD and if ACC responses to different gap durations can predict performance on a typical audiological measure of speech discrimination. These authors tested children ages 1 to 14 years who were diagnosed with ANSD. Both the onset CAEP and ACC response were present in children with ANSD as young as 1 year of age. The results indicated a significant correlation between gap detection thresholds and scores on an open-set speech recognition task. This study indicated that the ACC can be measured in young children with ANSD and accurately predict scores on speech tests commonly used in audiological assessments. Several studies have successfully elicited the ACC in infants as young as 4-months-old. However, previous infant and child studies have used speech stimuli which have complex frequency, amplitude, and temporal changes between phonemes and syllables. It is unclear which aspects of speech elicit the ACC response in infants and children. Small, Chan, Tian, and Sharma (article in prep) investigated the ACC response in infants ages 3 to 16 months of age using iterated ripple noise (IRN), which may be related to temporal pitch perception (IRN stimuli will be discussed in more detail in section 1.5. Using these stimuli, Small and colleagues attempted to elicit the ACC response in infants and adults. Adults had ACC responses present to all IRN pitch saliency conditions, from low to high saliency changes in pitch. Results from the infants were more variable with approximately 50% of infants showing an ACC response to the lower pitch saliency IRN condition and most infants showing a response to the greater pitch saliency 21  condition. These findings suggest that temporal processing of the IRN stimuli in infants is not yet mature. The current study will continue this investigation to determine a maturational time course of the development of the ACC response to the IRN stimuli in young children ages 1 to 4 years. In summary, the ACC response has several potential advantages as a clinical tool to evaluate speech perception in young infants (reviewed in Kim, 2015; Small, 2015). The ACC has the potential to be a time efficient measure due to its large responses. It would also be inexpensive to set up as many clinics performing ABR testing may have the materials and software needed to test the ACC. Further studies are needed to determine if the ACC response is a sensitive, valid, and reliable speech discrimination measure in infants and young children. 1.4! Auditory Temporal Processing A change in the auditory stimulus is necessary in order to elicit both the MMN and ACC responses. Many studies used fine acoustic differences between stimuli to elicit a response such as those in natural speech signals, synthetic speech, changes in frequency, intensity, periodicity, duration, rise time, spatial location, order, voice onset time, interstimulus interval, and temporal gaps (reviewed in section 2.3). However, if the goal is to create a clinical tool to diagnose and measure outcomes of intervention for hearing loss, it is important to use a change in acoustic parameters that is known to be processed differently in listeners with normal hearing and those with hearing loss. One well documented difference between these populations is the ability to process auditory temporal information. Auditory temporal processing refers to the ability to integrate a signal over time. It relies on synchrony of processing throughout the auditory system; disruptions in this synchrony due to hearing loss can cause distortions in the system leading to poorer speech understanding abilities. 22  Speech is a complex and broad signal with many acoustic changes over time. When a complex sound reaches the cochlea in a normal-hearing listener, the motion of the travelling wave of the basilar membrane activates place-specific auditory nerve fibres (ANFs). The place activated along the cochlea relates to the mass and elasticity properties of the basilar membrane, where different incoming frequencies resonate at specific places. The resonant frequencies are organized tonotopically along the cochlea with low frequencies at the apical end and high frequencies at the basal end. The movement of the basilar membrane and subsequent activation of place-specific ANFs act similarly to a Fourier transform (used in signal processing). The basilar membrane can be imagined as a series of auditory filters which function as a bandpass filter, only analyzing the place-specific resonant frequency, although in reality these filters do not have discrete cut-off points (Fletcher, 1940; Moore, 1986). The tonotopic organization continues through the auditory processing areas in the brainstem and cortex (reviewed in Moore 2008; Plack, 2014; Robles & Ruggero, 2001).  Complex auditory signals are made up of many rapid fluctuations of amplitude over time. This is the temporal fine structure (TFS) of the signal. Overlain on the TFS are the slower modulations in amplitude called the envelope. The firing of the ANFs phase-locks to these two temporal cues. Each ANF fires at regular integers of the period of the incoming frequency. A combination of all the surrounding ANF spikes corresponds to the sound pressure variations in the signal. For example, if an input has a frequency of 100 Hz, three activated ANFs may have inter-spike intervals of 10, 20, or 30 ms. When averaged, all activated ANFs are firing at a rate of 10 ms, which is the reciprocal of the signal’s frequency. ANFs are able to follow the TFS up to about 5000 Hz after which the frequency becomes too rapid and exceeds the refractory period. Envelope cues are much slower changes in the overall amplitude over time (between 2 to 50 Hz). 23  ANFs are able to phase lock to the envelope cues even when the changes in TFS are too rapid for the refractory period of the ANFs (Heinz, Colburn, & Carney, 2001; Moore, 2008; Plack, 2014; Young & Sachs, 1979). Envelope and TFS cues correspond to different features of speech. Envelope cues correspond to the linguistic information indicating manner of articulation. For example, large variations such as those between consonants and vowels and small differences such as those between affricates and fricatives. Envelope cues are also important for discriminating voicing, vowel quality, and prosody. TFS cues correspond to acoustic information regarding place of articulation, vowel quality, formant transitions, intonation, and pitch (Rosen, 1992). The current study will use a stimulus which may be related to temporal pitch processing. The next sections will describe two models of pitch perception (temporal and spectral), maturation of auditory temporal processing abilities, and how hearing loss affects an individual’s ability to process auditory temporal information. 1.4.1! Pitch Perception One well-documented difference in the auditory temporal perception between listeners with normal hearing and with hearing loss is a poorer ability to process variations in pitch. Pitch perception involves processing of spectral and temporal cues and can be defined as the “attribute of auditory sensation in terms of which sounds may be ordered on a scale extending from low to high. Pitch depends primarily on the frequency content of the sound stimulus, but it also depends on the sound pressure and the waveform of the stimulus” (American National Standards Institute, 1994). The ability to differentiate pitch is important for speech understanding, separating speech from background noise, music appreciation, and auditory scene analysis (reviewed in Darwin, 2005; Plack, 2014). There are two main models of pitch perception, spectral (Goldstein, 1973; 24  Moore, 1997; Terhardt, 1974; Wightman, 1973) and temporal (Licklider, 1951; Meddis & O’Mard, 1997; Yost et al., 1996).  Spectral models of pitch perception rely on the place-specific frequency resolution of the cochlea as the psychophysiological basis (Moore, 1997; Yost, 2009). The perception of pitch is directly related to the fundamental frequency and resolved harmonics of a complex signal. Harmonics below the 10th are able to be resolved by the filtering characteristics of the basilar membrane. Resolvable harmonics are compared to known patterns and the fundamental frequency can be predicted even when it is masked or removed (Goldstein, 1973; Schouten, 1940). These models are also able to explain the phenomena of a “mistuned” harmonic where a single harmonic is moved out of place but the listener does not perceive a change in the overall pitch (Lin & Hartmann, 1998; Moore, Glasberg, & Peters, 1986). Spectral models of pitch perception are not able to account for the weak perception that listeners report in a stimulus containing only unresolved harmonics (Bernstein & Oxenham, 2003) or the perception of pitch that occurs with amplitude modulated noise containing no spectral information (Burns & Viemeister, 1981).  Temporal models of pitch perception are able to explain some of the gaps in spectral models. Temporal models rely on the ability of the ANFs to follow signal fluctuations over time (Yost, 2009). The interspike intervals of the ANFs are phase locked to integer multiples of the period of the signal. Temporal models use an autocorrelation function which compares the original signal to several delayed versions of itself (Licklider, 1951). There is a high correlation when the delay is equal to a multiple of the fundamental frequency. For example, the original signal has an interspike interval equal to 2 ms (i.e., spikes occur at 0, 2, 4, 6 ms). When the signal is delayed by 2 ms, the interspike intervals are highly correlated to the original (i.e., spikes 25  occur at 2, 4, 6, 8 ms). However, when the signal is delayed by 1 ms, the interspike intervals of the delayed wave are not correlated to the original (i.e., spikes occur at 1, 3, 5, 7 ms). The summary of the autocorrelation function contains a large peak at the reciprocal of the fundamental frequency, which is perceived as the pitch. Spectral and temporal pitch cues are highly related; the temporal waveform is an inverse function of the spectral information (Yost, 2009). Since the two measures are so closely related, it is difficult to tease apart the two models of pitch perception. It is likely that pitch processing requires information from both spectral and temporal models (Benstein & Oxenham, 2003; Meddis & Hewitt, 1991; Meddis & O’Mard, 1997). It has been proposed that spectral pitch is important for high frequencies, for example a pure tone with a frequency above 5000 Hz cannot be followed synchronously by the ANFs and has a flat temporal envelope, therefore must be discriminated by the place-specific spectral information (Yost, 2009). Humans are able to perceive differences between low frequencies that are smaller than expected based on frequency-specific tuning curves. These small difference limens (for example, the difference between 250 and 249 Hz) are likely due to the ability of the system to follow the fine temporal information at lower frequencies (Sek & Moore, 1995; Wier et al., 1977; Yost, 2009). This indicates that both cues are important for auditory processing of everyday listening. The neural correlate for pitch perception is still being investigated. Several studies have attempted to discover a “pitch area” within the auditory cortex using fMRI. These studies have primarily proposed an area in Heschl’s gyrus and the planum temporale (Allen, Burton, Olman, & Oxenham, 2017; Barker, Plack, & Hall, 2013; Norman-Haignere, Kanwisher, & McDermott, 2013), however some studies have found multiple cues activate these areas and that activation patterns are not consistent across listeners (Allen et al., 2017; Barker, Plack, & Hall, 2013; 26  Norman-Haignere, Kanwisher, & McDermott, 2013). McPherson & McDermott (2018), investigated many pitch processing tasks behaviourally and determined that pitch may be used differently in tasks requiring discrimination of voice and melody compared to discrimination between isolated complex tones. This may explain some of the variability in the brain imaging studies, however research in this area is still in progress. 1.4.2! Maturation of Auditory Temporal Processing Researchers in psychoacoustics have developed methods to manipulate an acoustic stimulus to isolate either the envelope or TFS cues. It has been found that normal-hearing adult listeners are able to use either cue alone to identify speech. When envelope cues are extracted from speech stimuli, listeners are able to correctly identify phonemes (Lorenzi, Gilbert, Carn, Garnier, & Moore, 2006; Shannon, Zeng, Kamath, Wygonski, & Ekelid, 1995) and melodies (Smith, Delgutte, & Oxenham, 2002). Normal-hearing listeners can also identify phonemes and words in quiet using TFS cues alone; however, they require extra training to do this accurately (Gilbert & Lorenzi, 2006; Lorenzi et al., 2006).   Comparatively little research has been done to investigate the processing of temporal envelope and TFS cues in children and infants. Bertoncini, Sernicles, and Lorenzi (2009) found that children ages 5 to 7 years old showed similar behavioural responses to that of adults using both envelope and TFS cues. Newman and Chatterjee (2013) found that 2-year-olds were able to reliably identify a target image when the auditory stimulus comprised only envelope cues. Temporal processing abilities were investigated behaviourally in children ages 4 to 6 years old and adult-like performance measures of temporal processing were found using the temporal modulation transfer function (Hall & Grose, 1994) and gap detection (Wightman, Allen, Dolan, Kistler, & Jamieson, 1989). 27  In a series of behavioural studies with 6-month-olds, Cabrera and colleagues found that infants showed good temporal processing abilities for envelope-only speech cues in a visual habituation task. They were able to discriminate between vocoded stimuli for contrasts corresponding to voicing and place of articulation with both 32 and 8 filter channels (Bertoncini, Nazzi, Cabrera, & Lorenzi, 2011; Cabrera, Bertoncini, & Lorenzi, 2013; Cabrera, Lorenzi, & Bertoncini, 2015). However, infants were slower to habituate to stimuli which were filtered to contain only information below 16 Hz, eliminating the high-frequency fine structure. This indicates a difference in processing of auditory information with and without fine structure cues in this age (Cabrera, Lorenzi, & Bertoncini, 2015). Cabrera and Werner (2017) used similar stimuli to compare the discrimination abilities of 3 month old infants and adults with and without background noise. Like the older infants, 3-month-olds were less successful when the fine structure was removed from the stimuli. There were no differences in the adult group. Surprisingly, the 3-month-olds outperformed the adults in discrimination of amplitude modulated stimuli with background noise. Together, these studies indicate that infants and adults rely on different temporal cues for speech processing, with adults able to take advantage of more specific temporal cues. By 6 months of age, infants are functionally able to use some temporal processing cues though this is not yet mature. Young infants have been shown to use temporal envelope cues, however, there are fewer studies investigating processing of TFS cues. Butler and Trainor (2013) found that 4-month-olds had MMN responses to TFS stimuli but only with additional training sessions. Similarly, 8-month-olds did not show consistent behavioural responses to TFS stimuli without additional training (Butler, Folland, & Trainor, 2013). Dawes and Bishop (2008) and Varghese et al. (2010) found that children 6 to 12 years of age can discriminate TFS stimuli using behavioural methods. 28  Together, these results suggest that children under 1 year of age do not have adult-like processing abilities to TFS cues using either electrophysiological or behavioural methods but these abilities are likely mature by 6 years of age. There is a large gap in the literature with few studies investigating auditory temporal processing in the toddler years. The current study aims to fill part of this gap by investigating the ACC response to stimuli requiring the resolution of temporal pitch cues in children ages 1 to 4 years old. The maturation of pitch processing has been sporadically researched and results are varied. This is complicated by the difficulty of separating temporal and spectral cues from complex pitch. Behaviourally, researchers have found that spectral pitch processing matures around 6 months of age. Spetner and Olsho (1990), found adult-like psychophysical tuning curves to frequency-specific stimuli at 6 months old, however frequency resolution was not adult-like in 3 month olds at 4000 Hz. Similarly, Olsho, Koch, and Halpin (1987) found difference limens for pure tones to be adult-like at 6 and 12 months old but not 3 month-olds. In older children, there were no differences in the processing of spectral and temporal cues in 5- to 13-year-olds, but discrimination of difference thresholds for both stimuli continued to improve with age (Buss, Taylor, & Leibold, 2015). Research in temporal pitch perception indicates that perception abilities continue to develop into childhood. Behaviourally, infants showed immature discrimination of low-frequency pure tones at 12 months old (Olsho et al., 1987) and infants were not able to perceive the pitch of stimuli with missing fundamental frequencies at 7 and 8 months old (Clarkson & Clifton, 1995). Perception of the temporal modulation transfer function were immature in 4- to 7-year-olds, and continued to develop past 10 years of age (Hall & Grose, 1994). Similarly, difference limen thresholds continue to decrease in high frequencies (4000 Hz) between 4 and 12 29  years of age (Maxon & Hochberg, 1982). However, using the MMN procedure, He and Trainor (2009) found that 4-month-olds were able to detect stimuli with missing fundamental frequencies but 3-month-olds could not. These mixed results indicate continued changes of temporal pitch processing into childhood, likely due to changes in cortical structures. For example, using ABR, Werner, Folsom, Manci and Syapin (2001) found mature gap detection thresholds in 3 month olds but immature thresholds using behavioural measures. This indicates that temporal information may be reaching the auditory processing areas in the brainstem and cortex but infants are not able to take advantage of these cues to use functionally, as shown in behavioural studies. 1.4.3! Auditory Temporal Processing and Hearing Loss Auditory temporal processing and pitch perception has also been studied in populations with sensorineural hearing loss and ANSD. The cause of sensorineural hearing loss is damage to the outer hair cells, which affects both the precision of basilar membrane movement and the synchronicity of the firing of the ANFs. Moore (2008) proposed several possible explanations for the reduced ability to use temporal cues, especially temporal fine structure, in sensorineural hearing loss. These include reduced synchrony of the phase locking abilities of the ANFs, changes in basilar membrane function resulting in shifting of the phase of the response, broader auditory filters, mismatches between TFS information and place coding, and disruptions in the cortical processing of auditory information. Both spectral and temporal pitch perception are disrupted with sensorineural hearing loss. Studies have compared listeners with normal hearing and hearing loss in their ability to identify speech sounds using only envelope or TFS cues (Hopkins, Moore, & Stone, 2008; Lorenzi et al., 2006; Moore & Moore, 2003). Lorenzi et al. (2006) compared consonant 30  identification in adults with normal-hearing and with hearing loss. Both groups performed very well in the identification task when all speech cues were intact and with envelope-only cues. However, listeners with hearing loss performed significantly poorer than normal-hearing listeners when presented with TFS-only stimuli. The poor performance in the TFS cue condition can aid in explaining why individuals with SNHL often complain of difficulty listening to speech in the presence of background noise. The TFS can be used by normal-hearing individuals to separate the speech from the noise by listening for the signal in the dips of the noise. A hearing loss originating from cochlear dysfunction disrupts the ability to separate the signal from noise and leads to reduced comprehension (Moore, 2008; Moore & Glasberg, 1987; Schoonveldt & Moore, 1987). Another population in which temporal processing is impaired are individuals with ANSD. ANSD can be caused by a number of etiologies which all result in a deficit in auditory temporal processing due to a reduced precision of ANF phase-locking, leading to reduced synchrony of the signal in higher processing areas (He, 2016; Norrix & Velenovsky, 2014; Rance & Starr, 2015). Narne and colleagues (2015) investigated temporal processing in adults with ANSD. They found that individuals with ANSD have higher thresholds for differentiating amplitude modulated stimuli (envelope cues). They also showed poorer performance in speech tasks in quiet and in noise compared to normal-hearing adults, indicating deficits in temporal processing abilities. Other neural hearing losses resulting in loss of myelination of the ANFs, such as cochlear synaptopathy (also referred to as hidden hearing loss) and the effects of normal aging result in similar reduction of the precision of ANF phase locking (Hopkins & Moore, 2011; Peters, 2002; Wu et al., 2019).  31   Auditory temporal processing abilities are affected in individuals with both cochlear (SNHL) and neural (ANSD) hearing loss. Thus, an ideal stimulus to determine benefits of amplification in these groups would be one related to the temporal processing of speech sounds. The next section will describe the stimulus used in the current study, iterated ripple noise, which may be related to temporal pitch perception. 1.5! Iterated Ripple Noise Iterated ripple noise (IRN) is a broadband stimulus that creates a perception of pitch without the periodicity present in a pure-tone or speech stimulus (Yost, 1996). Discrimination of IRN stimuli has been found to be poorer in listeners with hearing loss and throughout maturation (discussed below). Therefore, it is hypothesized that the ACC should be elicited to IRN stimuli in normal-hearing participants but absent or abnormal in listeners with sensorineural hearing loss or ANSD. IRN stimuli are created by taking a broadband noise, delaying it, and adding it back to the original stimuli (Yost, 1996; Yost, Hill, & Perez-Falcon, 1978; Yost, Patterson, & Sheft, 1996). Yost, Patterson, and Sheft (1996) describe a real-world example similar to this process. In everyday listening, sounds are continuously reflected back to us from the environment. When a sound is reflected back (e.g., echoing off a wall), the reflected portion is delayed and attenuated compared to the original sound. The original sound and the reflection are then added together in the air before reaching our ears. IRN stimuli are similar to listening to water flowing from a fountain while standing beside risers or a large staircase. Many echoes (iterations) are reflected at regularly spaced intervals (delays). The parameters that can be manipulated in IRN are the amount of delay, the gain, and the number of iterations (Denham, 2005; Yost et al., 1978). The perceived pitch of the IRN stimuli corresponds to the reciprocal of the delay, as the delay 32  increases the frequency of the perceived pitch decreases. IRN stimuli sound like the combination of a tonal component with a hissing component related to the original noise (Patterson, Handel, Yost, & Datta, 1996). As gain or number of iterations increases, the saliency of the perception of pitch increases (e.g., less hissing and more tonal) (Yost, 1996; Yost et al., 1978).  Processing IRN stimuli may involve the resolution of temporal pitch (Yost, Patterson, & Sheft, 1996, 1998). The ability to discriminate between IRN stimuli has been claimed to be largely determined by the resolution of TFS cues (Yost, Patterson, & Sheft, 1998). When the stimuli are filtered to remove TFS cues, participants are unable to discriminate between two different IRN stimuli, but are able to discriminate between IRN stimuli and broadband noise (Yost, Patterson, & Sheft, 1998). Recently, it has been proposed that IRN stimuli do not purely evoke temporal pitch cues and discrimination of these stimuli may be related to the changes in slow modulation (Barker, Plack, & Hall, 2013; Hall & Plack, 2009). Investigations into determining a cortical “pitch centre” using fMRI in adults have found differences in the localization of stimuli containing pitch and modulation cues; IRN has more recently been proposed to contain both cues (Barker, Plack, & Hall, 2012, 2013). However, pitch and slow modulation cues overlapped in activation areas and the results were not consistent across all participants. The authors state that it is still unclear whether the same neurons respond to both types of cues or the cues are processed in the same area. These neuroimaging studies have not yet been attempted in pediatric populations.  IRN stimuli have also been investigated in adult cochlear implant users (Penninger et al., 2013). Cochlear implant processing strategies preserve the temporal envelope cues (spectral pitch) while omitting the fine structure (temporal pitch). As a result, individuals with cochlear implants also have difficulties discriminating fine differences in spectral pitch as there are fewer 33  electrodes than outer hair cells in normal-hearing listeners. This leads to reduced spectral resolvability. Penninger et al. found that normal-hearing listeners were able to perform a pitch-ranking and melody-identification task with both pure-tone and IRN stimuli. However, the listeners with cochlear implants were only able to perform the tasks with pure-tones but not with IRN stimuli. The authors concluded that disruptions in both temporal and spectral pitch resolution lead to the inability of cochlear implant users to discriminate between IRN stimuli.  Although recent studies suggest IRN stimuli may not contain purely temporal pitch cues, studies using IRN stimuli have found poorer results in populations with hearing loss. Shearer, Molis, Bennett, and Leek (2018) investigated auditory stream segregation using IRN stimuli in adults with normal-hearing and with mild to moderate SNHL. Listeners were asked to identify whether they heard one or two streams in sets of alternating stimuli. Listeners with hearing loss were less likely to segregate the two streams, indicating the two sounds were more often perceived as similar than in the normal-hearing group.  Discrimination of IRN stimuli has also been shown to be immature across maturation. It was found that infants were able to discriminate these stimuli only if they were first trained with a pure-tone prime, suggesting that discrimination of IRN stimuli are not yet mature physiologically (MMN) at 4 months and behaviourally at 8 months of age (Butler, Folland, & Trainor, 2013; Butler & Trainor, 2013). Dawes and Bishop (2008) found that 6-year-old children had adult-like IRN thresholds using a behavioural discrimination task.  Small et al., (in prep) investigated the ACC response to IRN stimuli in infants and adults. Four IRN conditions were created by varying the number of iterations (4, 8, 16, and 32). Adult participants had an ACC response to all IRN conditions, indicating that adults are able to discriminate between stimuli even for a weak perceptual change in pitch. However, only half of 34  the infants from 3 to 16 months old had a response to the 16-iteration condition and most, but not all, infants had responses to the 32-iteration condition. The lower saliency conditions (4 and 8 iterations) were not tested with the infant group. The results indicated that the processing of IRN stimuli is not yet mature by 16 months old. Electrophysiological discrimination of IRN stimuli are not yet mature by 16 months of age but are mature using behavioural testing by 6 years old. These results may be due to immaturities elsewhere in the temporal processing abilities of young infants (for example in abilities to use temporal fine structure). However, there is little research investigating the processing of auditory temporal cues, including discrimination of IRN stimuli in children between 1 and 4 years of age. The current study will expand on the previous results of Small et al. (in prep) and will add to our knowledge of temporal processing maturation in normal-hearing children.  Although the exact correlates of IRN stimuli are still undergoing investigation, previous studies have found differences in the ability to process or discriminate these stimuli in sensorineural hearing loss and throughout maturation. If IRN stimuli contained purely spectral pitch cues, we would expect adult-like discrimination abilities to emerge around 6 months of age. However, studies investigating IRN in infants found immature responses up to 16 months. This may suggest that IRN stimuli require resolution of both spectral and temporal pitch cues and that infants are unable to use spectral cues alone to process these stimuli. 1.6! Rationale for Thesis  The purpose of this study is to investigate the maturational time course of the acoustic change complex to iterated ripple noise in normal-hearing toddlers. Previous research has investigated this response in infants up to 16 months old and found that the response is not yet adult-like in this population. The ACC was chosen as an electrophysiological measure of 35  discrimination abilities. IRN stimuli were selected due to the disruption of the ability to process auditory temporal cues in populations with a hearing loss. The results of this study may contribute to the future development of a clinically viable testing tool correlated to speech outcomes in young children and difficult-to-test populations.  36  Chapter 2:!The Maturation of the Acoustic Change Complex in Response to Iterated Ripple Noise in Normal-Hearing Toddlers 2.1! Participants Participants were 27 children age 22 to 49 months old. The participants were split into two groups, younger toddlers (22 to 32 months, mean = 27 months, [SD 3.65]; n = 13, 6 males) and older toddlers (38 to 49 months, mean= 48 months, [SD 6.02]; n = 14, 5 males). One additional child (20 months old) was tested but would not tolerate the electrodes and no data were collected. Table 1 shows the individual participants’ ages and group means. All participants were considered low risk for hearing loss. All children were born in an area with newborn hearing screening and passed at birth (26 in British Columbia, 1 in Ontario, 1 in Japan, and 1 in Israel). All participants received a hearing screening using TEOAEs (transient evoked otoacoustic emissions) before testing to determine normal inner-ear function using a Madsen AccuScreen Pro (GN Otometrics). Participants were recruited from the community through social media and community groups. Table 2 displays the number of participants tested for each age group and experimental and control condition.         37   22-35 month olds 36-49 month olds N Sex Age (months) N Sex Age (months) 1 M 22 1 F 38 2 M 23 2 F 40 3 F 23 3 M 42 4 M 24 4 F 44 5 M 25 5 F 45 6 F 25 6 F 46 7 M 26 7 F 47 8 F 28 8 M 49 9 F 30 9 M 49 10 F 30 10 F 50 11 F 31 11 F 53 12 F 32 12 M 53 13 M 32 13 M 56    14 F 59 Mean 27 Mean 48  SD 3.65  SD 6.02 Table 1 Participant number, gender, and age for individual younger (22-35 months) and older (36-59 months) toddlers.    IRN4 IRN8 IRN16 IRN32 Control 22-35 month olds 10 11 10 5 4 36-59 month olds 10 9 10 6 7 Total 20 20 20 11 11 Table 2 Number of participants tested per condition in the younger (22-35 months) and older (36-59 months) age groups.  38  2.2! Stimuli   The stimuli for the current study were identical to Small et al. (in prep) and consisted of four IRN conditions. The IRN stimuli were created following the procedure outlined by Yost et al. (1996) using a delay-and-add procedure. A broadband noise was delayed and added onto itself. The number of iterations varied with the condition. A total of four IRN conditions with 4, 8, 16, and 32 iterations were created. All stimuli had a constant delay of 10 ms and gain of 0.7. The total duration of the IRN stimuli was 500 ms. The 10 ms delay results in a perception of a 100 Hz pitch. Each IRN stimulus was combined with a 500 ms band-pass filtered noise (1 to 4 kHz). Total stimulus durations were 1000 ms (500 ms noise + 500 ms IRN). Figure 1 displays the waveforms and spectra of each IRN condition. A control condition with no change in stimulus (500 ms noise + 500 ms noise) was also created. The stimuli were presented binaurally with a jittered ISI of 1000 to 1200 ms at 65 dB SPL through ER3-A (50 Ohm) insert earphones, calibrated using a Type I sound level meter and a 2cc coupler. The stimulus conditions were generated with Sigview 3.2 software (SignalLab e.K.) and presented with Presentation 18.1 software (Neurobehavioral Systems Inc.) via a Cedrus StimTracker. The stimuli were attenuated through Tucker Davis Technologies PA5 modules.  39   Figure 1 (A) Waveforms (IRN and noise), (B) spectra (IRN and noise), (C) IRN fast Fourier transform (FFT) spectra, and (D) IRN autocorrelation function for each stimuli condition: IRN4, IRN8, IRN16 and IRN32.  2.3! EEG Recording EEG recording setup and parameters were identical to Small et al. (in prep). Cortical responses for all participants are recorded via a three-channel electrode montage (Cz, C3, and C4) with six gold-plated cup electrodes placed at Cz, C3, C4, M1, M2 (International 10-20 System) and ground (forehead) with M2 selected as the reference electrode. The impedance of the connections was kept below 3 kOhms at 10 Hz and values were confirmed before and after data collection.  All EEG readings were amplified with a gain of 500 and converted using an analog-to-digital rate of 1000 Hz using Scan 4.5 (Compumedics Neuroscan). Recorded data were filtered online with a low-pass filter with a cut-off at 100 Hz and a high-pass filter at 10 Hz and offline with a cutoff at 30 Hz low-pass and 1 Hz high-pass filter. The total recording period is 1500 ms including a 100 ms pre-stimulus onset period followed by a 1400 ms post-stimulus onset period. 40  Five conditions were tested (4, 8, 16, and 32 iterations plus a control condition), and two runs of 150 epochs (300 in total) were recorded when possible. If a child was beginning to tire of the experiment and vocalized or moved excessively, the recording time was cut short. A minimum of two replications were recorded for each condition for each participant to be included in the analysis.  2.4! Procedure  The data were collected in the Pediatric Audiology Laboratory at the University of British Columbia, Vancouver, Canada and approved by the University of British Columbia Behavioural Research Ethics Board. Consent forms were signed by the legal guardian prior to testing and families received an honorarium and t-shirt at the end of each session. The experiment took place over one to two sessions which lasted 1.5 to 2 hours each. Before the EEG recording, toddlers were screened for normal hearing using TEOAEs. EEG recordings were conducted in a sound-attenuated booth. The caregiver sat in a comfortable chair with the child on their lap to minimize movement and prevent any accidental removal of the insert earphones or electrodes. Children were awake and quiet during recording and either watching a muted movie or engaged by a research assistant playing with quiet toys or books to prevent sleeping or excessive movement. Recording sessions lasted as long as the child was quiet and ranged from 10 to 50 minutes (average 30 minutes). Breaks were taken whenever necessary to keep the child quiet but alert.  IRN stimuli conditions were presented to the participants via insert earphones. Presentation of conditions was pseudorandomized to ensure equal numbers of participants in each age group per condition. Two runs of 150 epochs each were presented consecutively with each run lasting five minutes. Participants completed as many test conditions as possible and 41  testing was terminated when the child became disinterested in the task resulting in excessive movement, vocalizations or drowsiness. Children completed between one to five conditions (mean = 3). Due to limited testing times in this population, a higher priority was given to collecting responses to IRN4, IRN8, and IRN16. Small et al. (in prep) found that responses to IRN32 were present in most 3 to 16 month old infants. Because the purpose of this study was to determine the time course of maturation of ACC responses to lower-saliency IRN stimuli, IRN32 was often omitted from testing to save time.  2.5! Data Analysis  Grand mean averages were calculated for each age group and condition at Cz, C3, and C4. The morphology and mean amplitudes and latencies of the onset and ACC responses were compared across age groups and conditions. The change in amplitude of the grand mean waveforms from the zero-amplitude baseline were compared to confirm the presence of onset and ACC responses using two-tailed t-tests (p < 0.05) (e.g. Kraus et al., 1993; McGee, Kraus, & Nicol, 1997; Stapells, 2009; Small et al., 2016; Small et al., in prep). Individual EEG recordings were analyzed offline using Scan 4.5 software (Compumedics Neuroscan). Each replication was first epoched into individual trials. Each epoch then underwent a baseline correction to the prestimulus interval. Epochs were then filtered with a low-pass filter with a cut-off of 0.1 Hz and a high-pass filter with a cut-off of 30 Hz. Artifacts from myogenic noise were rejected exceeding ±75 µV between -100 to 900 ms. All accepted epochs were then averaged. The number of accepted epochs per participant per epoch ranged from 51 to 254 (mean = 126.5). Averaged waveforms for each replication were visually compared to determine replicability. Waveforms were judged to have good, fair, or poor replicability. Figure 2 displays examples of each replicability category. Replicable (judged as “good” or “fair”) peaks and 42  troughs for the onset and ACC responses of IRN4, IRN8, and IRN16 conditions were identified manually in the mid-point of the peak or trough. Amplitudes and latencies of each onset and ACC component were measured. The components identified for both the onset and ACC responses were the first major positivity (P) and the following negativity (N). The waveforms were examined by a second experienced judger with high inter-rater agreement of response present (96%). For the control and IRN32 conditions, responses were described qualitatively due to fewer data points collected for these conditions.  Figure 2 Examples “good” (T15), “fair” (T29), and “poor” (T14) replicability ratings for pairs of waveforms elicited to the IRN4 condition. Waveforms are displayed as changes in amplitude (µV) and latency (ms). Replicability needed to be at least fair or good for the ACC portion of the waveform for the data to be included.  43  When a response or component was absent, the amplitude was assigned the value of 0 µV. If a response could not be evaluated (CNE) the amplitude and latency values were replaced with the mean value for the age group. Total CNE responses across electrodes and conditions were 11 in the younger group (3 onset, 8 ACC) and 10 in the older group (1 onset, 9 ACC). Three-way repeated-measures analyses of variance (ANOVAs) were used to compare the ACC latency and amplitude between age groups (younger and older toddlers) and electrodes (Cz, C3, and C4), and within conditions (IRN4, IRN8, and IRN16). A three-way repeated-measures ANOVA was also used to compare the amplitude of the onset responses between age groups (younger and older) and electrodes (Cz, C3, and C4), and within conditions (IRN4, IRN8, and IRN16). Hunyh-Feldt epsilon-adjustments (ε) were made to control for Type I error in repeated measures. Results were considered to be statistically significant if p < 0.05. 2.6! Adult Pilot data   Five adult participants completed this study as a training exercise before performing the procedure with the toddler group and to ensure that recording parameters and calibration were unchanged from the previous study. The stimuli, conditions, and procedures were identical to the toddler group. Adults were presented with all four IRN conditions plus the control condition while they watched a silent movie. Recording duration was 50 minutes. Results were expected to replicate the previously collected adult data from Small et al. (in prep). Most adult participants showed all components of the onset response. All participants had P1, N1, and P2 components of the ACC response for all IRN iterations. Due to experimental error, IRN16 was unable to be analyzed for one adult participant. Figure 3 shows grand mean CAEP waveforms for the five adult pilots (four in IRN16) compared to the eight adult participants previously collected by Small et al. In both adult groups, the amplitudes of the ACC 44  response increase and the latencies decrease with increasing iterations. Table 3 summarizes the mean N1 amplitude and latency across conditions at each electrode site. These results are consistent with the previous adult results.  a. Small et al. (in prep) IRN4 IRN8 IRN16 IRN32  Amplitude Latency Amplitude Latency Amplitude Latency Amplitude Latency Cz Mean -3.34 193.22 -4.05 191.38 -4.88 182.76 -5.70 177.65   SD 1.69 9.26 1.52 11.35 2.11 8.64 2.12 6.51 C3 Mean -3.01 191.72 -3.54 191.38 -4.38 180.89 -4.85 184. 51   SD 1.61 8.75 0.94 11.23 1.78 8.53 1.72 21.03 C4 Mean -2.71 190.93 -3.62 191.03 -4.25 182.76 -5.11 178.54   SD 1.41 12.17 1.79 11.30 2.25 12.09 2.41 8.35             b. Current Data IRN4 IRN8 IRN16 IRN32  Amplitude Latency Amplitude Latency Amplitude Latency Amplitude Latency Cz Mean -3.54 199.10 -4.04 199.90 -5.85 186.84 -6.18 179.11   SD 1.81 15.33 1.62 10.18 1.98 10.72 1.82 7.47 C3 Mean -2.61 204.00 -3.35 198.40 -4.50 178.26 -5.23 169.52   SD 1.03 14.95 1.30 9.43 0.71 7.85 2.24 7.77 C4 Mean -1.83 201.70 -3.69 196.10 -4.48 186.51 -5.04 182.31   SD 1.95 17.81 1.63 9.12 0.94 7.87 1.55 6.05 Table 3 Adult mean and 1 SD amplitudes (µV) and latencies (ms) for the N1 component of the ACC response for all IRN conditions and electrode sites. (2a) previously collected means (n = 8) from Small et al. (in prep) and (2b) means collected as pilot data for the current study (n = 5). 45   Figure 3 Grand mean waveforms for adults comparing the current pilot adults (solid lines) with data collected by Small et al. (in prep) (dashed lines). The waveforms displayed are the control condition (black), and IRN4 (red), IRN8 (blue), IRN16 (green), and IRN32 (purple) experimental conditions. Vertical lines represent the onset of the noise and IRN stimuli. The components of the onset and ACC response are labelled. The dotted horizontal line indicates zero amplitude. Horizontal coloured bars indicate significant difference in amplitude from the baseline (p < 0.05). 46   2.7! Predictions In the previous study by Small et al. (in prep), younger infants were only tested with the higher numbers of IRN iterations (IRN16 and IRN32). Adults were tested for all four conditions. Most of the younger infants showed responses at 32 iterations and about half had responses to 16 iterations. It is expected that the current study will continue to show the same trends with more responses across all conditions as age increases. It is also expected that as age increases, there will be more responses present to lower-iteration IRN stimuli. It is expected that amplitudes of the ACC responses will increase and latencies will decrease with increasing age reflecting the maturation of cortical pathways in normal-hearing children. 2.8! Results Figure 4 illustrates the variability of the morphology of responses across participants (for the IRN4 condition) and is representative of all conditions tested. Across all conditions, participants showed a large monophasic positive onset response. The ACC response comprised a positive peak followed by a large negative trough. Figure 5 shows the changes in morphology with increasing IRN iterations. Generally, as the number of iterations increased, the latencies of the ACC response decreased and the amplitudes increased across both age groups. Figure 6 displays the grand mean waveform averages for each age group across conditions for every electrode site. The morphologies of the waveforms were similar across age groups, though the older group had a larger peak onset and the ACC response was shifted negatively.        47      Figure 4 Variability of responses to IRN4 stimuli for the 22-35 month olds (red) and 36-59 month olds (blue). The averages are shown as bolded solid lines, the individual results are shown as light dashed lines. Vertical lines represent to onset of the noise and IRN stimuli. The components of the onset and ACC response are labelled. The dotted horizontal line indicates zero amplitude.    48    Figure 5 Grand mean waveforms of the 22-35 month olds (top) and the 36-59 month olds (bottom). The waveforms displayed are the control condition (black), and IRN4 (red), IRN8 (blue), IRN16 (green), and IRN32 (purple) experimental conditions. Vertical lines represent to onset of the noise and IRN stimuli. The components of the onset and ACC response are labelled. The dotted horizontal line indicates zero amplitude. Horizontal coloured bars indicate significant difference in amplitude from the baseline (p < 0.05). 49    Figure 6 Grand mean waveforms for each IRN condition and control displaying the 22-35 month olds (solid) and the 36-59 month olds (dashed) for each electrode, Cz (red), C3 (green), and C4 (blue). Vertical lines represent to onset of the noise and IRN stimuli. The components of the onset and ACC response are labelled. The dotted horizontal line indicates zero amplitude.  50  Table 4 displays the number of onset and ACC components identified for each condition and electrode between the age groups. The components chosen for analysis were the first major positivity (P) and following negativity (N) for both the onset the ACC. One hundred percent of the younger toddlers had onset and ACC responses for at least one electrode in the IRN4, IRN8, and IRN16 conditions. In the older toddler group, 100% of participants had onset responses in all three conditions and ACC responses for IRN8 and IRN16. Ninety percent of the older group had ACC responses for IRN4 (1 participant could not be evaluated due to high levels of extraneous noise).      22-35 month olds 36-59 month olds    Onset ACC   Onset ACC Condition Electrode Total P N P N Total P N P N Control Cz 5 5 3 0 0 7 7 7 0 0 C3 5 5 4 0 0 7 7 7 0 0 C4 5 5 3 0 0 7 7 7 0 0 IRN4 Cz 10 10 10 9 10 10 10 10 8 9 C3 10 10 10 9 9 10 9 9 5 6 C4 10 10 10 9 9 10 10 10 7 8 IRN8 Cz 11 10 10 7 10 9 8 8 7 8 C3 11 10 10 8 10 9 9 8 6 8 C4 11 10 10 8 10 9 9 8 5 8 IRN16 Cz 10 9 9 8 9 10 10 10 10 10 C3 10 10 10 9 10 10 10 10 8 10 C4 10 10 10 7 9 10 10 10 8 9 IRN32  Cz 4 4 4 3 4 6 6 6 5 6 C3 4 4 4 4 4 6 6 6 5 5 C4 4 4 4 4 4 6 6 6 6 5  Table 4 Summary of components present for the onset and ACC response for all IRN conditions and electrode sites in younger (22-35 months) and older (36-59 months) age groups. Total refers to the number of participants tested in each condition.  51  Table 5b summarizes the mean latencies and amplitudes of the ACC response for each age group, IRN stimulus condition, and electrode. Results from a three-way repeated-measures ANOVA comparing ACC latencies showed significant main effects for age group [F (1, 33) = 16.94, p = 0.002] and IRN condition [F (2, 66) = 5.58, ε = 0.92, p = 0.006]. The older group had shorter latencies than the younger group and the ACC latency decreased as the number of iterations increased. There was no significant effect of electrode [F (2, 33) = 0.26, p = 0.733] or significant interactions between either age and electrode [F (2, 33) = 0.45, p = 0.614], IRN condition and age group [F (2, 66) = 1.40, ε = 0.92, p = 0.276] or IRN condition and electrode [F (4, 66) = 0.36, ε = 0.92, p = 0.802], or among IRN condition, age group, and electrode [F (4, 66) = 0.25, ε = 0.92, p = 0.924]. However, the mean latencies of the older children were generally shorter across IRN conditions and electrodes.  52   5a.Onset           5b. ACC       22-35 months 22-35 months   Control IRN4 IRN8 IRN16 IRN32 IRN4 IRN8 IRN16 IRN32             Amp Lat Amp Lat Amp Lat Amp Lat Amp Lat Amp Lat Amp Lat Amp Lat Amp Lat Cz Mean 9.65 168.6 11.93 173.5 12.38 183.6 11.28 179.7 10.35 159.0 10.10 372.1 7.73 321.9 9.82 372.1 9.23 232.3   SD 4.71 28.8 6.01 20.2 6.02 18.8 5.36 25.0 4.20 14.5 4.04 201.4 4.41 142.9 4.16 67.8 5.96 74.12 C3 Mean 11.75 167.3 13.09 170.8 13.29 178.6 11.91 166.8 11.90 167.3 9.85 389.6 8.88 334.9 8.86 370.45 13.02 280.5   SD 2.62 27.1 5.21 20.89 6.16 15.3 5.49 21.0 2.04 20.8 3.98 164.0 5.09 123.9 4.91 70.2 2.90 19.0 C4 Mean 8.14 199.01 10.11 167.38 12.56 177.2 9.24 164.4 10.66 157.6 9.92 343.2 9.15 321.4 8.80 312.7 12.94 268.8   SD 5.15 61.7 4.57 14.25 5.63 17.0 5.58 21.1 0.80 12.9 3.37 197.4 4.91 123.2 5.08 170.2 6.82 15.0 36-59 months 36-59 months   Control IRN4 IRN8 IRN16 IRN32 IRN4 IRN8 IRN16 IRN32   Amp Lat Amp Lat Amp Lat Amp Lat Amp Lat Amp Lat Amp Lat Amp Lat Amp Lat Cz Mean 15.28 169.3 15.99 168.4 14.16 173.7 13.65 170.2 17.32 173.8 7.02 347.0 7.75 265.3 8.52 268.1 7.40 234.0   SD 8.34 9.2 5.47 20.5 4.01 9.6 3.78 11.2 5.06 13.5 2.45 129.01 4.54 179.9 3.07 190.2 3.85 72.9 C3 Mean 18.28 163.8 16.36 162. 1 11.51 164.5 12.82 168.5 17.68 170.8 5.21 347.3 7.00 226.0 7.17 247.4 7.60 149.1   SD 9.77 8.7 9.13 18.9 3.91 20.4 4.52 12.1 7.40 13.6 4.29 176.3 3.55 157.1 3.31 191.2 4.73 318.1 C4 Mean 15.44 159. 6 15.92 161.1 13.16 170.7 13.28 171.1 17.97 166.3 5.97 347.7 7.00 251.7 7.41 268.9 8.53 265.0   SD 10.61 7.7 6.68 17.1 4.63 14.0 4.64 17.5 5.21 8.6 3.69 134.4 5.15 128.0 4.08 169.0 2.91 64.9  Table 5 Mean and 1SD amplitudes (Amp: µV) and latencies (Lat: ms) of the onset response (5a) and ACC response (5b) for each IRN condition and electrode in the (22-35 months) and older (36-59 months) age groups.   53  ACC amplitudes for the two toddler groups included in this study were compared in Figure 7; young infant results from Small et al. (in prep) and adult pilot participants from the current study are also included for comparison. Results from a three-way repeated-measures ANOVA comparing ACC amplitudes for the toddler groups found a significant effect of age group [F (1, 33) = 10.10, p = 0.003] with significantly smaller ACC amplitudes in the older toddler group. There was no significant effect of electrode [F (2, 33) = 0.16, p = 0.856] and no significant interactions between age group and electrode [F (2, 33) = 0.17, p = 0.842]. No significant effects were found for IRN condition [F (2, 66) = 0.56, ε = 1.00, p = 0.576], or for interactions between either IRN condition and age group [F (2, 66) = 0.96, ε = 1.00, p = 0.387] and IRN condition and electrode [F (4, 66) = 0.93, ε = 1.00, p = 0.451], or among IRN condition, age group, and electrode [F (4, 66) = 0.09, ε = 1.00, p = 0.984].  Figure 7 The ACC P to N amplitude displayed for the 3 to 16 month olds (Small et al., in prep), the 22-35 month olds, the 36-59 month olds and adults for IRN4 (red), IRN8 (blue), IRN16 (green), and IRN32 (purple) experimental conditions. Error bars represent 1SD. 54  Results of a three-way repeated-measures ANOVA comparing the onset amplitude revealed no significant effects or interactions, although mean onset amplitudes were larger in the older group at electrode sites Cz and C4 (Table 5a). There were no significant effects between either age group [F (1, 33) = 1.56, p = 0.220] or electrode [F (2, 33) = 0.45, p = 0.640], and no significant interactions between age group and electrode [F (2, 33) = 0.27, p = 0.765]. No significant effects or interactions were found within IRN condition [F (2, 66) = 0.15, ε = 1.00, p = 0.857], between IRN condition and age group [F (2, 66) = 2.49, ε = 1.00, p = 0.091], or IRN condition and electrode [F (4, 66) = 0.61, ε = 1.00, p = 0.659], or among IRN condition, age group, and electrode [F (4, 66) = 0.03, ε = 1.00, p = 0.999].   55  Chapter 3:!Discussion and Conclusion 3.1! Discussion  The goal of the current study was to determine the maturational time course of the ACC response to IRN stimuli in children ages 1 to 4 years old. The results of this study found that every participant had components of an onset and ACC response for at least one electrode site in every IRN condition tested (except one older toddler which could not be evaluated for IRN4). Therefore, the change from noise to IRN stimuli can be detected in the cortex as young as 22 months old, even for low saliency changes.  When comparing between the toddler groups, the mean latency of the ACC response was significantly shorter for the older toddlers. This pattern was similar across conditions and electrodes. A shorter ACC latency with increasing age is expected as the myelination of the cortex continues, allowing for a faster transmission of information. Across both age groups, latency significantly decreased as the number of IRN iterations increased. This was expected based on previous IRN findings for adults and infants (Small et al., in prep).  ACC responses to low-saliency changes from noise to IRN4 can be identified in children as young as 22 months old. Responses to higher-saliency changes are found in the majority of young infants for IRN32 as young as 3 to 16 months old; however, only about half of infants younger than 16 months had responses to IRN16 stimuli (Small et al., in prep). This is consistent with previous research investigating IRN discrimination in children. Dawes and Bishop (2008) found adult-like behavioural thresholds using an IRN stimulus with eight iterations in 6-year-olds. Butler and colleagues found immature behavioural and MMN responses in 4- and 8-month-olds to an IRN stimulus with sixteen iterations (Butler, Folland, & Trainor, 2013; Butler & 56  Trainor, 2013). Together, these results indicate immature processing of these stimuli in young infants which continues to mature into early childhood.    The older toddlers had significantly smaller ACC amplitudes than the younger group. There were no other significant results for either onset or ACC amplitudes. Generally, there was a trend for the onset amplitude to be larger and the ACC onset to be smaller for the older toddler group compared to the younger group. This pattern was revealed across conditions and electrodes, although did not reach statistical significance. It was predicted that the amplitude of the ACC would increase with age as the cortex continues to mature, which was found for the onset response. However, when the younger and older children are compared to the adult means, there is a clear trend of a decrease in ACC amplitude with age (Figure 7). Amplitudes decrease between younger and older toddlers and between older toddlers and adults. This may be due to reorganization of the auditory cortex in childhood. Previous studies have found varying results in how maturation of the cortex affects CAEP responses. For example, Albrecht, Suchodoletz, and Uwer (2000) used dipole source analysis of pure-tone stimuli in an oddball paradigm to determine that there are minimal changes to the location or direction of the source of the onset CAEP response for 5-year-old children and adults. However, Bishop, Anderson, Reid, and Fox (2011) found that dipole sources differed depending on the electrode site when measuring the onset response using 1 kHz tones. These authors found a decrease in onset CAEP amplitude between 7 and 11 years old at frontal, temporal, and central electrode sites. Shafer, Yu, and Wagner (2015) looked at the MMN to changes in vowels and found that amplitudes of responses increased between 3- and 24-month-olds and between 2- and 5-year-olds with periods of stable amplitudes when measured at frontal electrode sites. The variability of these studies indicate that 57  there are maturational changes in the auditory cortex up to early adolescence and differences may be due to the electrode site analyzed, choice of stimulus, or paradigm used. This study was a preliminary step into determining whether the ACC elicited to IRN stimuli is feasible to use as a clinically objective measure of speech perception. The ACC response to IRN stimuli can be reliably measured in low-saliency conditions by 22 months of age and the response changes with maturation. However, more research is needed to determine the reliability of this response at an individual level across multiple testing sessions and to determine whether ACC responses to IRN stimuli correlate with speech audiometry tests currently used to assess populations with SNHL or ANSD before it can be implemented clinically. Additionally, the response will need to be measured in clinical populations to determine whether there are differences between an immature response in normal-hearing infants and infants with hearing loss. One limitation of this study is sample size which is often a challenge for pediatric research. A limited sample size and limited testing time within that sample resulted in unequal groups and large standard deviations. Additionally, results for the IRN32 condition could not be analyzed statistically (though visually, responses were present to all IRN32 stimuli). On average, participants completed three out of five conditions (30 minutes recording time) before losing interest.   Another limitation of this study is the use of IRN stimuli. Recently, it has been questioned whether IRN stimuli consist solely of temporal pitch information in adult neuroimaging studies (Barker, Plack, & Hall, 2013; Hall & Plack, 2009). The ability to discriminate between IRN stimuli may be determined by the resolution of TFS cues and adult listeners are unable to behaviourally discriminate between IRN pitches when TFS information is 58  removed (Yost, Patterson, & Sheft, 1998). However, listeners with cochlear implants were not able to perform a pitch ranking or melody recognition task above chance with IRN stimuli (Penninger et al., 2013). Cochlear implant processing strategies are unable to process the TFS, but also have poorer spectral resolution. Penninger et al. conclude that listeners with cochlear implants are able to perform these tasks with pure-tone stimuli as this causes activation of place-specific electrodes. However, IRN stimuli causes diffuse activation across all electrodes, indicating users are not able to take advantage of any spectral pitch information. In addition, listeners are not able to differentiate the noisy components of IRN stimuli from the pitch-inducing components due to their inability to process the TFS.  Studies using fMRI in adults have found that IRN stimuli may be processed in different areas than other temporal pitch stimuli (Barker, Plack, & Hall, 2013; Hall & Plack, 2009). This may indicate that the primary perception evoked by IRN stimuli is not strictly temporal pitch. However, when IRN stimuli were filtered to removed TFS cues, presumably keeping only the slow modulations, there was no change in the amount of activation (Barker, Plack, & Hall, 2013). Results of this study suggest that IRN stimuli may be processed in part by slow modulations, but pitch may also contribute as there was an increase in the amount of activation with changes in IRN saliency. Another limitation was that only the change from noise to IRN stimuli was tested. Due to testing time restraints, it was not feasible to test IRN to noise or changes between two IRN conditions (e.g., IRN4 to IRN8). It is possible that the change from noise to IRN was not perceived as a pitch change at all, rather a change in timbre. Investigating ACC responses to changes between IRN conditions may help to differentiate responses to pitch versus timbre. However, as with the search for spectral and temporal pitch processing areas, there has also been 59  found to be an overlap in areas of activation of pitch and timbre cues using fMRI (Allen, Burton, Olman, & Oxenham, 2017). Therefore, it is difficult to determine exactly which cues elicited the ACC response in the current study.   The search for a pitch processing area in the cortex is still under investigation, as is the question of whether IRN stimuli contain purely temporal pitch cues. However, studies have found differences in discrimination of IRN stimuli in populations with hearing loss (Shearer, Molis, Bennett, & Leek, 2018), and throughout maturation (Butler, Folland, & Trainor, 2013; Butler & Trainor, 2013; Small et al., in prep). This suggests that IRN stimuli may still be relevant for differentiating abilities in these populations but it is important to determine what the stimuli are testing before adopting it clinically. More research is needed in these populations, especially in determining correlation of IRN stimuli and measures of speech perception. As mentioned above, additional research is needed to determine if the ACC response can be elicited in infants with SNHL and ANSD. The ACC response has been found to be reliable and valid in adults, and future research should also determine whether this is the case for infants.  Furthermore, investigations are needed to determine whether the IRN stimuli are an appropriate measure for temporal processing or if another stimulus may be more advantageous. If ACC responses to IRN stimuli correlate with currently used speech audiometry tests in clinical populations then it may still be a useful stimulus. Finally, future investigations should continue follow the maturational timecourse of the ACC response into late childhood and adolescence. 3.2! Conclusion  This is the first study investigating the ACC response elicited to IRN stimuli in the toddler years, and only the second study to investigate the ACC response in this age group. The results indicate that children as young as 22 months old are able to detect changes to low-60  saliency changes between noise and IRN stimuli. Although the perceptual correlate of IRN stimuli is still under investigation, changes in maturation of the ACC to IRN stimuli have been found, indicating differences in discrimination of these stimuli. Future research should determine how these processing abilities correlate with functional speech abilities in infants and children with normal hearing, SNHL, and ANSD.  61  References Albrecht, R., Suchodoletz, W. V., & Uwer, R. (2000). The development of auditory evoked dipole source activity from childhood to adulthood. Clinical Neurophysiology, 111(12), 2268-2276. doi:10.1016/S1388-2457(00)00464-8 Alho, K., & Cheour, M. (1997). 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(1998). The role of the envelope in processing iterated ripple noise. The Journal of the Acoustical Society of America, 104(4), 2349-2361. doi:10.1121/1.423746  86  Young, E. D., & Sachs, M. B. (1979). Representation of steady-state vowels in the temporal aspects of the discharge patterns of populations of auditory-nerve fibers. The Journal of the Acoustical Society of America, 66(5), 1381-1403. doi:10.1121/1.383532  87  Appendices  Notes: (1) '---' denotes that data was not obtained for this individual (2) CNE denotes 'could not evaluate' (3) NR denotes 'no response'   88  A.1 Individual Toddler Amplitudes and Latencies  Table A.1 Individual onset toddler amplitude (µV) for each condition measured at Cz    IRN4 Onset IRN8 Onset IRN16 Onset IRN32 Onset Noise Onset P# Age P N P N P N P N P N T13 22 5.82 -1.64 5.83 0.64 6.99 -4.73 --- --- --- --- T04 23 13.45 -10.37 15.35 -6.17 --- --- --- --- 7.39 -7.18 T16 23 --- --- --- --- 8.56 -3.14 --- --- --- --- T21 24 5.50 1.33 CNE CNE CNE CNE --- --- --- --- T18 25 --- --- 7.69 0.64 --- --- --- --- 9.26 CNE T23 25 12.81 0.87 12.47 -4.38 12.36 -3.11 13.23 -2.15 --- --- T01 26 8.75 3.33 9.40 -4.23 8.52 5.62 -0.51 -5.80 2.42 CNE T29 28 5.70 -4.01 5.25 -0.10 5.79 -2.93 7.06 -4.29 6.70 -2.24 T15 30 8.88 -2.38 12.43 -0.43 14.13 -0.18 --- --- --- --- T26 30 10.32 -7.57 5.06 -11.45 7.71 -7.75 --- --- --- --- T22 31 14.84 -1.50 10.34 -4.60 13.66 -5.30 --- --- --- --- T19 32 13.35 2.08 --- --- 10.69 -0.44 7.50 -1.87 13.98 0.91 T25 32 --- --- 8.52 -9.68 --- --- --- --- --- --- T08 38 7.64 -3.25 --- --- --- --- 9.51 -3.18 6.01 0.28 T02 40 11.15 -0.67 5.22 -0.53 9.21 -0.11 --- --- --- --- T11 42 --- --- 9.71 -4.89 8.30 0.89 --- --- --- --- T20 44 12.66 -7.94 --- --- 12.33 -4.68 14.63 -5.09 18.38 -13.46 T27 45 18.91 -1.67 9.77 -3.59 13.91 -1.64 13.50 -6.74 --- --- T07 46 12.71 -6.22 11.79 -5.69 16.06 -1.31 --- --- --- --- T14 47 12.12 -3.44 8.28 -6.45 --- --- --- --- 12.63 -0.02 T10 49 --- --- CNE CNE 5.80 -4.36 --- --- --- --- T12 49 10.10 4.36 13.87 1.62 11.69 0.36 10.25 0.15 14.53 3.43 T17 50 --- --- --- --- 10.14 -4.99 --- --- 9.33 -2.82 T30 53 15.12 -1.46 --- --- --- --- --- --- --- --- T31 53 9.22 -5.74 11.61 -4.16 10.99 -4.03 11.37 -6.13 7.52 -6.61 T28 56 --- --- 13.88 -6.47 12.58 -5.61 --- --- --- --- T03 59 15.12 -9.12 --- --- --- --- 16.50 -7.15 12.59 -6.78 N 27 20 20 18 18 19 19 10 10 12 10 Mean 37.85 11.21 -2.75 9.80 -3.88 10.50 -2.50 10.30 -4.22 10.06 -3.45 Median 38 11.64 -2.03 9.74 -4.31 10.69 -3.11 10.81 -4.69 9.30 -2.53 Min 22 5.50 -10.37 5.06 -11.45 5.79 -7.75 -0.51 -7.15 2.42 -13.46 Max 59 18.91 4.36 15.35 1.62 16.06 5.62 16.50 0.15 18.38 3.43 SD 11.74 5.86 3.73 5.37 3.47 5.47 2.81 5.82 2.51 5.86 3.42   89  Table A.2 Individual toddler onset amplitude (µV) for each condition measured at C3    IRN4 Onset IRN8 Onset IRN16 Onset IRN32 Onset Noise Onset   P# Age P N P N P N P N P N    T13 22 CNE CNE 1.83 0.74 4.78 -6.20 --- --- --- ---   T04 23 8.42 -9.40 16.34 -5.08 --- --- --- --- 7.40 -3.23   T16 23 --- --- --- --- 5.64 -1.13 --- --- --- ---   T21 24 -0.39 -4.81 4.37 -2.94 3.70 0.30 --- --- --- ---   T18 25 --- --- 8.90 -0.33 --- --- --- --- 9.77 CNE   T23 25 10.45 1.17 10.93 -7.86 11.80 -3.76 11.55 -0.25 --- ---   T01 26 8.87 -6.48 11.08 -3.58 9.99 4.93 6.74 -3.71 -5.22 CNE   T29 28 4.74 -6.00 6.96 -1.94 12.99 -4.68 4.19 -6.29 6.84 0.07   T15 30 6.57 -0.48 12.24 -1.23 10.32 1.13 --- --- --- ---   T26 30 7.59 -7.44 3.89 -10.71 --- --- --- --- --- ---   T22 31 6.83 0.11 10.01 -4.61 10.99 -3.01 --- --- --- ---   T19 32 13.25 4.04 --- --- 11.56 1.77 8.41 -1.50 12.61 -0.91   T25 32 --- --- 4.89 -9.20 --- --- --- --- --- ---   T08 38 6.04 -3.10 --- --- --- --- 9.86 -4.90 4.65 -0.58   T02 40 15.97 7.35 9.32 2.99 13.33 3.57 --- --- --- ---   T11 42 --- --- 11.38 -1.62 8.52 0.84 --- --- --- ---   T20 44 18.02 -9.49 --- --- 16.22 -6.96 22.85 -3.30 16.76 -21.42   T27 45 17.88 -5.34 9.62 -4.64 10.48 -3.27 11.96 -9.44 --- ---   T07 46 10.72 -5.81 10.92 -3.58 12.57 -1.52 --- --- --- ---   T14 47 15.54 -3.34 9.39 -9.98 --- --- --- --- 14.91 0.52   T10 49 --- --- 6.60 NR 7.17 -3.71 --- --- --- ---   T12 49 10.76 3.43 12.75 0.63 10.63 -0.99 10.67 -0.77 15.62 4.22   T17 50 --- --- --- --- 10.93 -2.98 --- --- 9.09 -1.65   T30 53 12.17 -1.64 --- --- 4.99 -4.46 --- --- --- ---   T31 53 6.42 -7.14 8.58 -4.28 --- --- 8.08 -7.83 5.88 -5.92   T28 56 --- --- 9.10 -10.29 13.34 -5.18 --- --- --- ---   T03 59 14.75 -5.89 --- --- --- --- 12.35 -5.81 11.11 -5.22   N 27 19 19 20 19 20 20 10 10 12 11    Mean 37.85 11.77 -3.73 8.90 -3.78 9.31 -3.05 10.87 -4.50 11.22 -4.73   Median 38 11.86 -1.71 8.46 -4.23 9.61 -2.78 9.68 -3.78 10.31 -2.66   Min 22 3.39 -12.64 2.47 -11.90 4.27 -8.93 3.93 -8.68 5.13 -17.18   Max 59 18.27 1.38 18.87 1.83 18.04 1.62 21.19 -0.87 19.02 3.38   SD 11.74 6.66 3.95 5.18 3.43 5.22 2.82 6.20 2.63 6.48 4.53        90  Table A.3 Individual toddler onset amplitude (µV) for each condition measured at C4    IRN4 Onset IRN8 Onset IRN16 Onset IRN32 Onset Noise Onset P# Age P N P N P N P N P N T01 26 8.87 -6.48 11.08 -3.58 9.99 4.93 6.74 -3.71 -5.22 CNE T13 22 CNE CNE 1.83 0.74 4.78 -6.20 --- --- --- --- T04 23 8.42 -9.40 16.34 -5.08 --- --- --- --- 7.40 -3.23 T16 23 --- --- --- --- 5.64 -1.13 --- --- --- --- T21 24 -0.39 -4.81 4.37 -2.94 3.70 0.30 --- --- --- --- T18 25 --- --- 8.90 -0.33 --- --- --- --- 9.77 CNE T23 25 10.45 1.17 10.93 -7.86 11.80 -3.76 11.55 -0.25 --- --- T29 28 4.74 -6.00 6.96 -1.94 12.99 -4.68 4.19 -6.29 6.84 0.07 T15 30 6.57 -0.48 12.24 -1.23 10.32 1.13 --- --- --- --- T26 30 7.59 -7.44 3.89 -10.71 --- --- --- --- --- --- T22 31 6.83 0.11 10.01 -4.61 10.99 -3.01 --- --- --- --- T19 32 13.25 4.04 --- --- 11.56 1.77 8.41 -1.50 12.61 -0.91 T25 32 --- --- 4.89 -9.20 --- --- --- --- --- --- T08 38 6.04 -3.10 --- --- --- --- 9.86 -4.90 4.65 -0.58 T02 40 15.97 7.35 9.32 2.99 13.33 3.57 --- --- --- --- T11 42 --- --- 11.38 -1.62 8.52 0.84 --- --- --- --- T20 44 18.02 -9.49 --- --- 16.22 -6.96 22.85 -3.30 16.76 -21.42 T27 45 17.88 -5.34 9.62 -4.64 10.48 -3.27 11.96 -9.44 --- --- T07 46 10.72 -5.81 10.92 -3.58 12.57 -1.52 --- --- --- --- T14 47 15.54 -3.34 9.39 -9.98 --- --- --- --- 14.91 0.52 T10 49 --- --- 6.60 NR 7.17 -3.71 --- --- --- --- T12 49 10.76 3.43 12.75 0.63 10.63 -0.99 10.67 -0.77 15.62 4.22 T17 50 --- --- --- --- 10.93 -2.98 --- --- 9.09 -1.65 T30 53 12.17 -1.64 --- --- 4.99 -4.46 --- --- --- --- T31 53 6.42 -7.14 8.58 -4.28 --- --- 8.08 -7.83 5.88 -5.92 T28 56 --- --- 9.10 -10.29 13.34 -5.18 --- --- --- --- T03 59 14.75 -5.89 --- --- --- --- 12.35 -5.81 11.11 -5.22 N 27 19 19 20 19 19 19 10 10 12 10 Mean 37.85 10.24 -3.17 8.95 -4.08 10.00 -1.86 10.66 -4.38 9.12 -3.41 Median 38 10.45 -4.81 9.36 -3.58 10.63 -2.98 10.26 -4.30 9.43 -1.28 Min 22 -0.39 -9.49 1.83 -10.71 3.70 -6.96 4.19 -9.44 -5.22 -21.42 Max 59 18.02 7.35 16.34 2.99 16.22 4.93 22.85 -0.25 16.76 4.22 SD 11.74 6.25 4.19 4.96 3.84 5.44 2.86 6.01 2.80 6.04 4.43    91  Table A.4 Individual toddler onset latency (ms) for each condition measured at Cz    IRN4 Onset IRN8 Onset IRN16 Onset IRN32 Onset Noise Onset P# Age P N P N P N P N P N T13 22 168.84 239.79 205.81 255.28 189.82 264.77 --- --- --- --- T04 23 162.34 296.75 181.82 312.74 --- --- --- --- 181.82 319.74 T16 23 --- --- --- --- 204.81 299.75 --- --- --- --- T21 24 203.81 246.78 CNE CNE CNE CNE --- --- --- --- T18 25 --- --- 194.82 275.77 --- --- --- --- 194.82 CNE T23 25 192.82 286.76 187.20 275.77 153.84 281.26 151.84 282.76 --- --- T01 26 142.85 185.82 157.84 262.77 121.86 146.85 149.84 233.79 119.86 CNE T29 28 169.83 321.74 210.81 289.76 189.32 312.74 176.83 334.73 176.83 251.78 T15 30 189.82 326.73 152.84 241.79 189.82 274.77 --- --- --- --- T26 30 144.85 298.75 164.84 266.77 176.83 280.76 --- --- --- --- T22 31 171.83 346.72 185.82 303.75 181.82 255.78 --- --- --- --- T19 32 187.82 271.77 --- --- 183.82 271.77 151.84 266.77 169.83 350.72 T25 32 --- --- 181.33 344.73 --- --- --- --- --- --- T08 38 174.83 241.79 --- --- --- --- 187.82 271.77 172.83 208.81 T02 40 135.85 239.79 178.83 275.77 180.33 253.78 --- --- --- --- T11 42 --- --- 187.82 405.68 162.84 146.78 --- --- --- --- T20 44 142.85 305.75 --- --- 167.83 321.74 167.83 344.72 165.83 327.73 T27 45 142.85 237.79 155.84 264.77 166.83 253.78 151.84 258.78 --- --- T07 46 169.83 271.77 174.83 276.76 174.83 257.78 --- --- --- --- T14 47 182.33 301.75 161.84 284.76 --- --- --- --- 166.83 279.76 T10 49 --- --- CNE CNE 162.34 294.75 --- --- --- --- T12 49 185.82 266.77 172.83 288.76 174.83 257.78 172.83 244.78 171.83 264.77 T17 50 --- --- --- --- 147.85 298.75 --- --- 151.84 305.75 T30 53 190.82 310.74 --- --- --- --- --- --- --- --- T31 53 171.83 292.26 178.83 264.77 176.83 273.77 174.83 271.77 180.82 280.76 T28 56 --- --- 178.83 301.75 187.82 267.77 --- --- --- --- T03 59 187.32 293.26 --- --- --- --- 187.82 291.76 174.82 287.76 N 27 20 20 18 18 19 19 10 10 12 10 Mean 37.85 170.96 279.16 178.49 288.45 173.38 263.95 167.33 280.16 169.00 287.76 Median 38 171.83 289.51 178.83 276.27 176.83 271.77 170.33 271.77 172.33 284.26 Min 22 135.85 185.82 152.84 241.79 121.86 146.78 149.84 233.79 119.86 208.81 Max 59 203.81 346.72 210.81 405.68 204.81 321.74 187.82 344.72 194.82 350.72 SD 11.74 78.23 128.95 86.72 141.87 82.15 128.61 82.82 139.46 86.43 143.64     92  Table A.5 Individual toddler onset latency (ms) for each condition measured at C3    IRN4 Onset IRN8 Onset IRN16 Onset IRN32 Onset Noise Onset P# Age P N P N P N P N P N T01 26 172.83 267.77 151.84 257.78 162.84 244.78 154.33 244.78 167.83 305.75 T13 22 172.83 305.75 --- --- --- --- 180.82 291.76 176.83 284.76 T04 23 186.82 324.73 159.34 247.78 195.82 274.77 --- --- --- --- T16 23 140.85 285.76 --- --- 153.84 241.79 160.84 344.73 165.83 321.74 T21 24 --- --- --- --- 156.84 269.77 --- --- 149.84 296.75 T18 25 171.83 282.76 181.82 255.78 176.83 285.76 --- --- --- --- T23 25 --- --- 174.83 237.79 183.82 258.78 --- --- --- --- T29 28 157.84 281.75 162.84 277.76 --- --- --- --- 161.84 279.76 T15 30 --- --- 176.83 369.71 --- --- --- --- --- --- T26 30 203.81 276.27 174.83 223.80 174.83 250.78 --- --- --- --- T22 31 --- --- 189.82 271.77 --- --- --- --- 183.82 CNE T19 32 161.84 294.75 181.82 273.77 151.84 264.77 190.82 284.76 --- --- T25 32 162.84 269.77 174.83 271.77 174.83 251.78 --- --- --- --- T08 38 162.34 261.28 155.34 266.77 119.86 151.84 147.85 237.79 121.86 121.86 T02 40 --- --- 119.86 NR 151.84 267.77 --- --- --- --- T11 42 183.82 267.77 --- --- 183.82 266.77 151.84 262.77 171.83 355.72 T20 44 140.85 279.76 163.34 277.76 163.34 291.76 --- --- --- --- T27 45 161.34 296.75 190.82 312.74 --- --- --- --- 167.50 297.75 T07 46 142.85 252.78 207.81 257.28 156.84 266.77 --- --- --- --- T14 47 --- --- --- --- --- --- 191.32 273.77 167.83 207.81 T10 49 --- --- 191.32 273.77 167.33 285.76 --- --- --- --- T12 49 --- --- --- --- 177.83 301.25 --- --- --- --- T17 50 192.82 325.73 182.82 276.76 167.34 284.76 178.83 335.73 191.32 253.78 T30 53 189.82 309.74 --- --- --- --- --- --- --- --- T31 53 146.85 246.78 160.84 264.77 171.33 258.78 165.83 267.77 --- --- T28 56 133.85 237.79 179.33 271.77 176.83 257.78 --- --- --- --- T03 59 180.82 275.77 164.83 262.77 185.82 269.77 171.83 242.79 156.84 281.26 N 27 19 19 20 19 20 20 10 10 12 11 Mean 37.85 166.68 281.23 172.26 271.16 167.68 262.30 169.43 278.67 165.26 273.36 Median 38 162.84 279.76 174.83 271.77 169.33 266.77 168.83 270.77 167.67 284.76 Min 22 133.85 237.79 119.86 223.80 119.86 151.84 147.85 237.79 121.86 121.86 Max 59 203.81 325.73 207.81 369.71 195.82 301.25 191.32 344.73 191.32 355.72 SD 11.74 79.31 132.41 78.57 128.63 76.23 119.98 83.89 138.85 84.47 142.27     93  Table A.6 Individual toddler onset latency (ms) for each condition measured at C4    IRN4 Onset IRN8 Onset IRN16 Onset IRN32 Onset Noise Onset P# Age P N P N P N P N P N T13 22 178.83 295.75 --- --- --- --- 158.34 296.75 162.84 308.75 T04 23 169.33 318.74 178.83 234.79 180.82 268.77 --- --- --- --- T16 23 140.85 259.28 --- --- 147.85 260.77 167.83 339.73 160.84 296.75 T21 24 --- --- --- --- 142.85 286.76 --- --- 147.85 296.75 T18 25 194.82 287.76 183.82 303.75 189.82 278.76 --- --- --- --- T23 25 --- --- 147.35 273.77 157.84 246.78 --- --- --- --- T01 26 176.83 260.77 169.83 276.76 172.83 248.78 167.83 246.78 162.84 242.79 T29 28 164.83 304.75 157.84 281.76 --- --- --- --- 153.84 284.76 T15 30 --- --- 190.32 318.74 --- --- --- --- --- --- T26 30 154.34 237.79 157.34 246.78 158.84 210.81 --- --- --- --- T22 31 --- --- 194.82 276.76 --- --- --- --- 169.83 CNE T19 32 172.33 305.75 162.84 271.77 151.84 285.26 173.33 278.76 --- --- T25 32 167.83 266.77 167.83 257.78 172.83 253.78 --- --- --- --- T08 38 144.85 244.78 157.34 252.78 119.86 151.84 142.85 233.79 308.75 CNE T02 40 --- --- 189.82 NR 201.81 300.75 --- --- --- --- T11 42 181.82 267.77 --- --- 183.82 273.77 150.84 267.77 162.84 346.72 T20 44 166.34 296.75 160.84 280.76 --- --- --- --- --- --- T27 45 154.85 300.75 183.82 303.75 --- --- --- --- 180.82 237.79 T07 46 CNE CNE 170.81 290.26 158.34 266.77 --- --- --- --- T14 47 174.83 282.26 --- --- --- --- 180.82 271.77 171.83 201.81 T10 49 --- --- 190.32 301.75 178.83 241.79 --- --- --- --- T12 49 --- --- --- --- 164.83 227.80 --- --- --- --- T17 50 168.34 312.74 208.81 296.75 171.83 266.77 168.83 352.22 172.83 250.78 T30 53 167.83 300.75 --- --- 184.83 312.74 --- --- --- --- T31 53 140.85 233.79 168.84 262.77 173.83 287.76 156.84 242.79 --- --- T28 56 130.86 201.81 178.33 282.76 177.83 248.78 --- --- --- --- T03 59 167.83 278.76 165.83 266.77 --- --- 165.83 273.77 156.84 264.77 N 27 19 19 20 19 19 19 10 10 12 10 Mean 37.85 164.13 276.71 174.28 277.95 167.96 258.91 163.33 280.41 176.00 273.17 Median 38 167.83 282.26 170.32 276.76 172.83 266.77 166.83 272.77 162.84 274.77 Min 22 130.86 201.81 147.35 234.79 119.86 151.84 142.85 233.79 147.85 201.81 Max 59 194.82 318.74 208.81 318.74 201.81 312.74 180.82 352.22 308.75 346.72 SD 11.74 77.53 131.35 78.97 130.58 79.75 124.12 80.65 139.92 93.36 136.66    94  Table A.7 Individual toddler ACC amplitude (µV) for each condition measured at Cz    IRN4 ACC IRN8 ACC IRN16 ACC IRN32 ACC P# Age P N P N P N P N T13 22 6.77 -5.22 9.62 -3.22 5.78 -3.07 --- --- T04 23 1.91 -12.43 CNE CNE --- --- --- --- T16 23 --- --- --- --- 4.53 -3.12 --- --- T21 24 7.66 -5.68 6.28 -2.60 5.94 -8.64 --- --- T18 25 --- --- NR -3.79 --- --- --- --- T23 25 0.49 -8.39 5.88 -6.07 1.18 -6.14 4.68 -6.37 T01 26 NR -3.00 NR -0.68 NR 4.92 NR -4.65 T29 28 2.96 -3.34 -1.49 -7.83 3.91 -2.16 1.16 -3.18 T15 30 7.07 -3.79 NR -3.26 2.17 -1.83 --- --- T26 30 1.16 -5.45 4.91 0.90 5.76 -1.96 --- --- T22 31 10.90 -5.19 9.76 -3.82 3.82 -14.43 --- --- T19 32 7.16 -2.45 --- --- 8.21 -4.31 7.25 -9.63 T25 32 --- --- 5.55 -5.88 --- --- --- --- T08 38 2.68 -7.54 --- --- --- --- 3.12 -5.18 T02 40 1.34 -6.07 NR 1.95 4.42 -6.80 --- --- T11 42 --- --- 3.56 -2.91 2.27 -4.95 --- --- T20 44 1.65 -7.17 --- --- 4.20 -9.25 -1.54 -11.05 T27 45 3.99 -2.79 1.55 -4.47 4.78 -3.65 1.23 -9.00 T07 46 -1.20 -5.66 -3.33 -8.56 0.95 -6.79 --- --- T14 47 CNE CNE NR NR --- --- --- --- T10 49 --- --- 9.04 -2.50 1.64 -11.10 --- --- T12 49 NR -3.00 5.67 -2.23 2.78 -3.69 3.26 -6.48 T17 50 --- --- --- --- -0.81 -4.70 --- --- T30 53 0.13 -3.86 --- --- --- --- --- --- T31 53 2.13 -7.04 4.46 -2.75 4.52 -3.74 NR 0.55 T28 56 --- --- 5.60 -11.01 2.37 -3.44 --- --- T03 59 1.34 -6.07 --- --- --- --- 3.19 -3.44 N 27 17 19 14 18 19 20 8 10 Mean 37.85 3.42 -5.48 4.79 -3.82 3.60 -4.94 2.79 -5.84 Median 38 2.13 -5.45 5.57 -3.24 3.91 -4.02 3.16 -5.77 Min 22 -1.20 -12.43 -3.33 -11.01 -0.81 -14.43 -1.54 -11.05 Max 59 10.90 -2.45 9.76 1.95 8.21 4.92 7.25 0.55 SD 11.74 3.09 3.25 3.64 3.17 2.45 4.08 1.88 3.52     95  Table A.8 Individual toddler ACC amplitude (µV) for each condition measured at C3    IRN4 ACC IRN8 ACC IRN16 ACC IRN32 ACC P# Age P N P N P N P N T13 22 3.55 -6.46 10.58 -4.52 1.36 -9.80 --- --- T04 23 0.02 -11.17 4.04 -2.63 --- --- --- --- T16 23 --- --- --- --- 5.43 0.13 --- --- T21 24 11.66 -6.60 1.37 -9.74 9.02 -9.15 --- --- T18 25 --- --- NR -3.03 --- --- --- --- T23 25 2.42 -4.60 -1.12 -8.32 -0.72 -9.45 1.43 -8.78 T01 26 2.73 -2.02 4.75 -4.02 CNE 5.80 0.79 -14.44 T29 28 3.63 -2.43 -2.29 -8.95 2.58 -5.20 4.55 -6.31 T15 30 9.69 -4.08 NR -2.70 NR CNE --- --- T26 30 1.66 -6.11 -0.82 -5.44 8.88 -2.81 --- --- T22 31 8.15 -2.64 8.59 -4.76 -2.68 -12.31 --- --- T19 32 7.02 -1.86 --- --- 8.34 -3.68 7.53 -8.27 T25 32 --- --- 9.12 -9.35 --- --- --- --- T08 38 --- --- --- --- --- --- 6.59 -7.48 T02 40 CNE CNE 7.50 2.79 NR -5.06 --- --- T11 42 --- --- CNE -1.51 4.35 -1.70 --- --- T20 44 4.48 -8.20 --- --- 1.44 -12.20 -1.29 -11.64 T27 45 4.13 -2.65 0.42 -4.10 3.53 -5.62 1.02 -6.65 T07 46 0.10 -3.85 -2.49 -5.81 0.24 -5.90 --- --- T14 47 CNE CNE CNE CNE --- --- --- --- T10 49 --- --- 6.86 -3.56 1.20 -10.07 --- --- T12 49 NR 0.75 3.13 -5.83 2.00 -4.25 -0.43 -5.87 T17 50 --- --- --- --- CNE CNE --- --- T30 53 2.20 -4.27 --- --- --- --- --- --- T31 53 1.80 -3.34 NR -4.79 NR -2.31 3.18 -4.88 T28 56 --- --- 7.53 -6.69 5.67 -1.11 --- --- T03 59 NR NR --- --- --- --- NR NR N 27 15 16 15 19 15 18 9 9 Mean 37.85 4.21 -4.35 3.81 -4.89 3.38 -5.26 2.60 -8.26 Median 38 3.55 -3.96 4.04 -4.76 2.58 -5.13 1.43 -7.48 Min 22 0.02 -11.17 -2.49 -9.74 -2.68 -12.31 -1.29 -14.44 Max 59 11.66 0.75 10.58 2.79 9.02 5.80 7.53 -4.88 SD 11.74 3.31 3.07 3.78 3.39 3.11 4.56 2.11 4.31     96  Table A.9 Individual toddler ACC amplitude (µV) for each condition measured at C4    IRN4 ACC IRN8 ACC IRN16 ACC IRN32 ACC P# Age P N P N P N P N T13 22 0.50 -6.34 7.86 -3.57 3.62 -6.14 --- --- T04 23 -3.93 -21.91 1.22 -4.45 --- --- --- --- T16 23 --- --- --- --- CNE CNE --- --- T21 24 5.21 -5.45 8.98 -5.30 9.77 -7.14 --- --- T18 25 --- --- NR -2.57 --- --- --- --- T23 25 -1.01 -7.72 5.64 -7.94 3.30 -7.18 2.32 -7.13 T01 26 1.13 -7.44 -0.33 -14.93 NR 3.97 -1.82 -16.66 T29 28 CNE CNE -1.29 -7.30 2.64 -7.66 2.60 -3.29 T15 30 3.46 -5.23 NR -1.02 NR -3.46 --- --- T26 30 0.10 -6.89 1.19 -5.98 --- --- --- --- T22 31 7.51 -4.27 9.17 -1.06 2.17 -6.56 --- --- T19 32 9.40 -1.64 --- --- 10.96 -3.30 10.45 -11.11 T25 32 --- --- 3.61 -10.45 --- --- --- --- T08 38 0.25 -9.71 --- --- --- --- 3.61 -2.40 T02 40 3.25 -1.32 CNE 1.40 6.56 -4.48 --- --- T11 42 --- --- 4.14 -1.44 3.30 -6.59 --- --- T20 44 1.01 -8.50 --- --- 3.11 -10.55 0.98 -10.00 T27 45 3.63 -5.39 NR -5.51 5.03 -2.34 4.85 -8.03 T07 46 -1.10 -7.30 0.47 -7.76 -1.94 -6.70 --- --- T14 47 CNE CNE NR NR --- --- --- --- T10 49 --- --- 10.03 -1.18 3.41 -7.33 --- --- T12 49 NR 1.67 6.41 -2.85 3.71 -2.22 -0.43 -5.87 T17 50 --- --- --- --- 0.43 -4.70 --- --- T30 53 2.07 -7.03 --- --- 0.07 -2.43 --- --- T31 53 -0.25 -5.13 NR -3.12 --- --- 1.71 -6.83 T28 56 --- --- 4.05 -13.10 NR -0.56 --- --- T03 59 NR NR --- --- --- --- 2.81 -4.54 N 27 16 17 14 19 15 18 10 10 Mean 37.85 1.95 -6.45 4.37 -5.16 3.74 -4.74 2.71 -7.58 Median 38 1.07 -6.34 4.09 -4.45 3.30 -5.42 2.46 -6.98 Min 22 -3.93 -21.91 -1.29 -14.93 -1.94 -10.55 -1.82 -16.66 Max 59 9.40 1.67 10.03 1.40 10.96 3.97 10.45 -2.40 SD 11.74 2.75 4.98 3.47 4.31 3.12 3.52 2.37 4.48    97  Table A.10 Individual toddler ACC latency (ms) for each condition measured at Cz    IRN4 ACC IRN8 ACC IRN16 ACC IRN32 ACC P# Age P N P N P N P N T13 22 735.48 902.88 640.54 901.37 676.51 778.45 --- --- T04 23 726.48 814.43 CNE CNE --- --- --- --- T16 23 --- --- --- --- 591.57 666.53 --- --- T21 24 665.52 833.42 703.50 803.44 686.51 778.45 --- --- T18 25 --- --- NR 633.54 --- --- --- --- T23 25 796.44 887.38 615.55 758.46 701.50 848.41 654.53 751.47 T01 26 NR 760.46 NR 613.55 NR 794.44 NR 624.55 T29 28 733.48 830.42 558.59 617.55 678.51 776.45 726.48 792.44 T15 30 715.49 903.44 NR 606.56 649.53 749.47 --- --- T26 30 688.51 827.42 692.50 804.94 670.52 747.47 --- --- T22 31 735.48 860.40 697.50 794.45 688.51 772.45 --- --- T19 32 715.49 830.92 --- --- 679.51 746.47 670.52 762.46 T25 32 --- --- 618.55 817.43 --- --- --- --- T08 38 717.49 815.43 --- --- --- --- 659.03 778.95 T02 40 556.59 613.55 NR 636.54 683.51 749.47 --- --- T11 42 --- --- 543.60 631.54 656.53 728.48 --- --- T20 44 704.50 860.40 --- --- 665.52 763.46 712.49 776.45 T27 45 545.60 625.05 706.50 762.46 719.49 801.44 694.50 801.44 T07 46 726.48 770.46 660.52 766.46 613.55 803.44 --- --- T14 47 CNE CNE NR NR --- --- --- --- T10 49 --- --- 690.51 785.45 686.51 744.47 --- --- T12 49 NR 586.57 692.50 805.43 683.51 760.46 683.51 763.46 T17 50 --- --- --- --- 649.53 695.50 --- --- T30 53 790.44 989.38 --- --- --- --- --- --- T31 53 731.48 833.42 712.49 823.42 696.00 769.46 NR 670.52 T28 56 --- --- 652.53 726.49 665.52 762.46 --- --- T03 59 556.59 613.55 --- --- --- --- 568.58 618.55 N 27 17 19 14 18 19 20 8 10 Mean 37.85 696.56 797.84 656.10 738.28 670.65 761.86 671.20 734.03 Median 38 717.49 830.42 675.52 764.46 678.51 762.96 677.02 762.96 Min 22 545.60 586.57 543.60 606.56 591.57 666.53 568.58 618.55 Max 59 796.44 989.38 712.49 901.37 719.49 848.41 726.48 801.44 SD 11.74 347.82 382.75 336.31 362.21 313.05 341.83 313.33 363.51     98  Table A.11 Individual toddler ACC latency (ms) for each condition measured at C3    IRN4 ACC IRN8 ACC IRN16 ACC IRN32 ACC P# Age P N P N P N P N T13 22 733.48 910.37 645.53 889.38 659.03 781.45 --- --- T04 23 757.46 819.43 686.51 774.45 --- --- --- --- T16 23 --- --- --- --- 590.57 664.53 --- --- T21 24 692.50 862.40 695.50 851.41 638.54 817.43 --- --- T18 25 --- --- NR 624.55 --- --- --- --- T23 25 719.49 869.90 695.50 785.95 699.50 846.41 706.50 771.46 T01 26 609.56 686.51 692.50 758.46 CNE 796.44 658.53 781.44 T29 28 737.48 835.42 554.59 637.04 676.51 789.44 683.51 806.43 T15 30 719.49 800.44 NR 600.56 NR CNE --- --- T26 30 763.46 853.40 697.50 810.43 681.51 747.47 --- --- T22 31 740.47 835.42 695.50 830.42 690.51 756.46 --- --- T19 32 720.49 810.43 --- --- 676.51 747.47 676.51 762.46 T25 32 --- --- 609.56 836.42 --- --- --- --- T08 38 --- --- --- --- --- --- 662.03 765.46 T02 40 CNE CNE 538.60 629.54 NR 798.94 --- --- T11 42 --- --- CNE 609.56 656.53 728.48 --- --- T20 44 701.50 824.42 --- --- 667.52 755.47 692.45 781.45 T27 45 552.59 626.55 703.50 758.46 712.49 796.44 697.50 790.44 T07 46 719.49 621.96 729.48 771.46 712.49 801.44 --- --- T14 47 CNE CNE CNE CNE --- --- --- --- T10 49 --- --- 694.50 783.45 670.52 733.48 --- --- T12 49 NR 607.06 713.49 797.44 690.51 769.46 728.48 782.95 T17 50 --- --- --- --- CNE CNE --- --- T30 53 720.49 906.37 --- --- --- --- --- --- T31 53 735.48 844.41 NR 640.54 NR 581.57 695.50 774.45 T28 56 --- --- 649.53 728.48 643.54 712.49 --- --- T03 59 NR NR --- --- --- --- NR NR N 27 15 16 15 19 15 18 9 9 Mean 37.85 708.23 794.65 666.79 743.05 671.09 756.94 689.00 779.62 Median 38 720.49 829.92 694.50 771.46 676.51 762.96 692.45 781.44 Min 22 552.59 607.06 538.60 600.56 590.57 581.57 658.53 762.46 Max 59 763.46 910.37 729.48 889.38 712.49 846.41 728.48 806.43 SD 11.74 360.96 405.18 340.24 353.99 340.60 366.95 331.21 374.59     99  Table A.12 Individual toddler ACC latency (ms) for each condition measured at C4    IRN4 ACC IRN8 ACC IRN16 ACC IRN32 ACC P# Age P N P N P N P N T13 22 799.44 900.88 647.53 917.86 678.51 778.45 --- --- T04 23 728.48 815.43 720.49 797.44 --- --- --- --- T16 23 --- --- --- --- CNE CNE --- --- T21 24 726.48 894.38 583.57 801.44 609.56 797.44 --- --- T18 25 --- --- NR 645.53 --- --- --- --- T23 25 819.43 885.38 615.55 808.43 697.50 860.40 658.53 753.47 T01 26 604.56 683.51 692.50 753.47 NR 692.50 661.52 781.95 T29 28 CNE CNE 552.59 622.55 686.51 769.46 674.52 781.45 T15 30 690.51 789.44 NR 622.05 NR 771.46 --- --- T26 30 733.48 839.41 678.51 791.45 --- --- --- --- T22 31 733.48 823.42 703.50 817.43 703.50 771.46 --- --- T19 32 720.49 829.42 --- --- 676.51 747.47 670.52 758.46 T25 32 --- --- 633.04 805.43 --- --- --- --- T08 38 717.49 814.43 --- --- --- --- 678.51 790.95 T02 40 615.55 642.54 CNE 626.55 683.51 799.97 --- --- T11 42 --- --- 541.60 622.55 639.54 745.47 --- --- T20 44 701.50 862.40 --- --- 636.54 763.46 713.49 789.44 T27 45 541.60 590.57 NR 649.53 690.51 753.47 699.50 801.44 T07 46 724.48 814.43 631.54 756.46 722.49 805.43 --- --- T14 47 CNE CNE NR NR --- --- --- --- T10 49 --- --- 679.02 842.91 685.51 753.47 --- --- T12 49 NR 618.06 699.50 781.45 681.51 755.47 728.48 782.95 T17 50 --- --- --- --- 626.55 718.99 --- --- T30 53 713.49 900.37 --- --- 678.51 817.43 --- --- T31 53 724.49 833.42 NR 661.52 --- --- 660.52 792.44 T28 56 --- --- 649.53 742.47 NR 629.54 --- --- T03 59 NR NR --- --- --- --- 568.58 633.04 N 27 16 17 14 19 15 18 10 10 Mean 37.85 705.93 796.32 644.89 740.34 673.12 762.85 671.42 766.56 Median 38 722.49 823.42 648.53 756.46 681.51 766.46 672.52 782.45 Min 22 541.60 590.57 541.60 622.05 609.56 629.54 568.58 633.04 Max 59 819.43 900.88 720.49 917.86 722.49 860.40 728.48 801.44 SD 11.74 357.30 399.66 330.75 352.59 341.61 368.70 331.38 378.34    100  A.2 Individual Adult Pilot Amplitudes and Latencies Table A.13 Individual onset adult pilot amplitude (µV) for each condition measured at Cz   IRN4 Onset IRN8 Onset IRN16 Onset IRN32 Onset Noise Onset P# P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 A01 NR NR 10.02 -0.1 NR NR 8.053 -1.44 --- --- --- --- --- --- 3.88 1.88 3.25 1.934 5.607 -2.31 A02 1.92 -0.65 6.677 -0.46 1.93 -0.01 8.273 -1.78 2.27 0.53 7.17 0.86 1.87 0.37 8.03 -0.2 2.11 -1.15 6.469 0.175 A03 1.69 -1.53 8.335 -1.24 2.35 -1.2 8.086 -0.38 1.1 -2.5 7.24 -1.2 1.45 -2.7 9.59 0.86 1.44 -2.27 2.983 -1.35 A04 2.45 0.063 5.521 CNE 0.83 -1.41 6.244 -1.29 1.3 -2.4 3.8 -3.2 2.4 -1.6 7.02 2.03 1.63 -2.89 0.695 -2.81 A05 4.45 3.54 6.727 1.828 5.05 4.886 7.27 NR 4.11 3.27 6.9 2.01 5.07 4.94 8.24 2.97 1.15 1.042 2.399 -0.44 N 4 4 5 4 4 4 5 4 4 4 4 4 4 4 5 5 5 5 5 5 Mean 2.63 0.356 7.455 0.006 2.54 0.566 7.585 -1.22 2.2 -0.3 6.28 -0.4 2.7 0.27 7.35 1.5 1.92 -0.67 3.631 -1.35 Median 2.19 -0.29 6.727 -0.28 2.14 -0.61 8.053 -1.36 1.79 -0.9 7.04 -0.2 2.14 -0.6 8.03 1.88 1.63 -1.15 2.983 -1.35 Min 1.69 -1.53 5.521 -1.24 0.83 -1.41 6.244 -1.78 1.1 -2.5 3.8 -3.2 1.45 -2.7 3.88 -0.2 1.15 -2.89 0.695 -2.81 Max 4.45 3.54 10.02 1.828 5.05 4.886 8.273 -0.38 4.11 3.27 7.24 2.01 5.07 4.94 9.59 2.97 3.25 1.934 6.469 0.175 SD 1.6 1.93 1.747 1.13 1.92 2.564 0.843 0.752 1.54 2.38 3.15 2 1.85 2.91 2.14 1.22 0.82 2.087 2.373 1.248  101  Table A.14 Individual adult pilot onset amplitude (µV) for each condition measured at C3   IRN4 Onset IRN8 Onset IRN16 Onset IRN32 Onset Noise Onset P# P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 A01 NR NR 8.212 1.518 NR NR 6.334 -0.9 --- --- --- --- --- --- 3.64 1.62 2.49 2.193 4.142 -1.74 A02 1.87 -0.46 5.919 -0.28 1.85 -0.2 3.955 -1.26 2.25 0.44 6.35 0.94 2.06 0.65 7.11 0.12 2.07 -1.05 6.082 0.37 A03 1.37 -1.31 7.322 -0.74 1.98 -1.03 7.276 -0.06 0.83 -2.4 6.21 -1.1 1.18 -2.2 8.57 1.33 1.3 -1.79 2.71 -0.87 A04 2.77 0.813 4.38 CNE 1.29 0.311 4.901 -0.08 2.27 -0.4 4.45 -0.6 CNE 0.21 5.77 CNE 0.93 -2.25 0.945 -1.43 A05 3.62 2.508 4.819 0.608 5.14 4.971 6.04 NR 3.41 2.73 5.19 1.03 4.39 4.14 6.33 2.35 1.63 1.541 2.422 -0.23 N 4 4 5 4 4 4 5 4 4 4 4 4 3 4 5 4 5 5 5 5 Mean 2.41 0.388 6.13 0.277 2.57 1.014 5.701 -0.57 2.19 0.09 5.55 0.06 2.54 0.69 6.29 1.35 1.68 -0.27 3.26 -0.78 Median 2.32 0.176 5.919 0.166 1.92 0.056 6.04 -0.49 2.26 0 5.7 0.18 2.06 0.43 6.33 1.47 1.63 -1.05 2.71 -0.87 Min 1.37 -1.31 4.38 -0.74 1.29 -1.03 3.955 -1.26 0.83 -2.4 4.45 -1.1 1.18 -2.2 3.64 0.12 0.93 -2.25 0.945 -1.74 Max 3.62 2.508 8.212 1.518 5.14 4.971 7.276 -0.06 3.41 2.73 6.35 1.03 4.39 4.14 8.57 2.35 2.49 2.193 6.082 0.37 SD 1.38 1.448 1.626 0.874 1.9 2.377 1.293 0.579 1.34 1.84 2.6 0.94 1.82 2.29 1.81 1.01 0.62 2.012 1.943 0.861    102  Table A.15 Individual adult pilot onset amplitude (µV) for each condition measured at C4   IRN4 Onset IRN8 Onset IRN16 Onset IRN32 Onset Noise Onset P# P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 A01 NR NR 8.016 3.507 NR NR 6.821 -1.55 --- --- --- --- --- --- 3.88 2.51 3.26 1.705 4.904 -0.77 A02 0.84 -0.93 5.245 -0.58 3.64 -1.05 6.211 -1.54 0.79 -0.4 5.08 0.68 1.13 0.28 6.59 -0.9 1.39 -0.93 5.131 0.263 A03 1.88 -1.22 7.791 -0.86 2.45 -0.83 7.612 0.005 1.53 -2.3 6.82 -1.1 1.57 -2.1 8.62 1.17 1.5 -1.88 2.76 -1.12 A04 2.09 0.288 4.21 CNE 0.04 -1.13 4.002 -2.12 1.97 -1.1 3.82 -1 2.14 -1.5 5.29 CNE 1.11 -1.15 1.825 -2.2 A05 3.02 2.188 4.67 1.126 3.79 3.504 5.553 NR 3.04 2.21 4.69 -0.2 3.66 3.33 5.58 2.11 0.94 0.781 1.544 -0.83 N 4 4 5 4 4 4 5 4 4 4 4 4 4 4 5 4 5 5 5 5 Mean 1.96 0.081 5.986 0.8 2.48 0.123 6.04 -1.3 1.83 -0.4 5.1 -0.4 2.12 0 5.99 1.22 1.64 -0.29 3.233 -0.93 Median 1.98 -0.32 5.245 0.274 3.04 -0.94 6.211 -1.55 1.75 -0.7 4.88 -0.6 1.86 -0.6 5.58 1.64 1.39 -0.93 2.76 -0.83 Min 0.84 -1.22 4.21 -0.86 0.04 -1.13 4.002 -2.12 0.79 -2.3 3.82 -1.1 1.13 -2.1 3.88 -0.9 0.94 -1.88 1.544 -2.2 Max 3.02 2.188 8.016 3.507 3.79 3.504 7.612 0.005 3.04 2.21 6.82 0.68 3.66 3.33 8.62 2.51 3.26 1.705 5.131 0.263 SD 1.17 1.342 1.79 1.774 1.87 1.956 1.369 0.983 1.15 1.64 2.53 0.74 1.35 2.11 1.76 1.43 0.93 1.483 1.692 0.881    103  Table A.16 Individual adult pilot onset latency (ms) for each condition measured at Cz   IRN4 Onset IRN8 Onset IRN16 Onset  IRN32 Onset Noise Onset P# P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 A01 NR NR 202.8 312.7 NR NR 191.3 271.8 --- --- --- --- --- --- 119.9 142.9 130.9 172.8 224.8 362.7 A02 108.9 135.9 198.8 305.8 110.9 135.9 205.8 355.7 112.9 133.9 192.8 291.8 108.9 135.9 198.8 292.8 104.9 137.9 212.8 282.8 A03 101.9 160.8 221.8 298.8 103.9 153.8 228.8 337.7 99.9 147.3 232.8 301.8 97.9 153.8 224.8 307.8 101.9 153.8 221.8 323.7 A04 128.9 162.8 208.8 CNE 112.9 137.9 196.8 325.7 119.9 156.8 226.3 305.8 104.9 146.9 207.8 251.8 110.9 147.9 197.3 253.8 A05 115.9 135.9 183.8 294.8 117.9 133.9 172.8 NR 113.9 131.9 183.8 353.7 119.9 140.9 181.8 303.8 115.9 131.9 178.3 278.8 N 4 4 5 4 4 4 5 4 4 4 4 4 4 4 5 5 5 5 5 5 Mean 113.9 148.8 203.2 303.0 111.4 140.3 199.1 322.7 111.6 142.5 208.9 313.2 107.9 144.3 186.6 259.8 112.9 148.8 207.0 300.4 Median 112.4 148.3 202.8 302.3 111.9 136.9 196.8 331.7 113.4 140.6 209.6 303.8 106.9 143.9 198.8 292.8 110.9 147.9 212.8 282.8 Min 101.9 135.9 183.8 294.8 103.9 133.9 172.8 271.8 99.9 131.9 183.8 291.8 97.9 135.9 119.9 142.9 101.9 131.9 178.3 253.8 Max 128.9 162.8 221.8 312.7 117.9 153.8 228.8 355.7 119.9 156.8 232.8 353.7 119.9 153.8 224.8 307.8 130.9 172.8 224.8 362.7 SD 51.9 67.8 13.9 135.7 50.1 63.3 20.5 147.7 50.4 64.5 95.8 142.1 48.9 64.9 40.4 69.0 11.4 15.9 19.3 43.0  Table A.17 Individual adult pilot onset latency (ms) for each condition measured at C3   IRN4 Onset IRN8 Onset IRN16 Onset IRN32 Onset Noise Onset P# P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 A01 NR NR 201.3 310.7 NR NR 190.3 271.8 --- --- --- --- --- --- 121.9 140.9 115.9 189.8 224.8 361.7 A02 108.9 137.9 198.8 307.8 110.9 138.9 243.8 355.7 110.9 138.9 194.8 289.8 113.9 140.9 198.8 291.8 106.9 138.9 214.8 280.8 A03 99.9 160.8 221.8 300.8 104.9 156.8 230.8 339.7 101.9 160.8 232.8 305.8 95.9 153.8 221.8 309.7 101.9 151.8 223.8 323.7 A04 131.9 165.8 207.8 CNE 119.9 140.9 199.8 310.7 124.9 160.8 223.3 310.7 CNE 144.9 199.8 CNE 113.9 149.8 197.3 255.8 A05 115.9 133.9 174.8 300.8 119.9 131.9 158.8 NR 115.9 138.9 178.8 357.7 121.9 140.9 180.8 300.8 117.9 131.9 164.8 282.8 N 4 4 5 4 4 4 5 4 4 4 4 4 3 4 5 4 5 5 5 5 Mean 114.1 149.6 200.9 305.0 113.9 142.1 204.7 319.5 113.4 149.8 207.4 316.0 110.5 145.1 184.6 260.8 111.3 152.4 205.1 301.0 Median 112.4 149.3 201.3 304.3 115.4 139.9 199.8 325.2 113.4 149.8 209.1 308.2 113.9 142.9 198.8 296.3 113.9 149.8 214.8 282.8 Min 99.9 133.9 174.8 300.8 104.9 131.9 158.8 271.8 101.9 138.9 178.8 289.8 95.9 140.9 121.9 140.9 101.9 131.9 164.8 255.8 Max 131.9 165.8 221.8 310.7 119.9 156.8 243.8 355.7 124.9 160.8 232.8 357.7 121.9 153.8 221.8 309.7 117.9 189.8 224.8 361.7 SD 52.4 68.3 17.1 136.5 51.3 64.2 33.7 146.4 51.4 67.9 95.3 143.6 61.3 65.1 38.0 135.8 6.7 22.4 25.1 41.8  104  Table A.18 Individual adult pilot onset latency (ms) for each condition measured at C4   IRN4 Onset IRN8 Onset IRN16 Onset IRN32 Onset Noise Onset P# P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 A01 NR NR 199.3 242.8 NR NR 191.3 273.8 --- --- --- --- --- --- 119.9 135.9 142.9 172.8 223.8 307.8 A02 106.9 130.9 199.8 307.8 70.9 131.9 199.8 357.7 113.9 135.9 189.8 284.8 112.9 130.9 199.8 289.8 104.9 135.9 215.8 278.8 A03 104.8 162.8 223.8 300.8 108.9 156.8 228.8 337.7 101.9 160.8 232.8 305.8 97.9 155.9 223.8 305.8 101.9 153.8 224.8 323.7 A04 122.9 156.8 208.8 CNE 110.9 140.9 194.8 369.7 122.9 156.8 226.3 300.8 104.9 147.9 208.8 CNE 112.9 147.9 190.8 257.8 A05 112.9 133.9 180.8 287.8 113.9 138.9 171.8 NR 112.9 138.9 183.8 395.7 115.9 142.9 180.8 303.8 115.9 133.9 176.8 284.5 N 4 4 5 4 4 4 5 4 4 4 4 4 4 4 5 4 5 5 5 5 Mean 111.9 146.1 202.5 284.8 101.1 142.1 197.3 334.7 112.9 148.1 208.2 321.7 107.9 144.4 186.6 258.8 115.7 148.8 206.4 290.5 Median 109.9 145.3 199.8 294.3 109.9 139.9 194.8 347.7 113.4 147.8 208.1 303.3 108.9 145.4 199.8 296.8 112.9 147.9 215.8 284.5 Min 104.8 130.9 180.8 242.8 70.9 131.9 171.8 273.8 101.9 135.9 183.8 284.8 97.9 130.9 119.9 135.9 101.9 133.9 176.8 257.8 Max 122.9 162.8 223.8 307.8 113.9 156.8 228.8 369.7 122.9 160.8 232.8 395.7 115.9 155.9 223.8 305.8 142.9 172.8 224.8 323.7 SD 50.5 66.8 15.7 129.8 48.5 64.2 20.5 154.2 51.0 67.1 95.6 150.3 48.8 65.2 40.4 135.9 16.2 15.8 21.5 25.7  Table A.19 Individual adult pilot ACC amplitude (µV) for each condition measured at Cz   IRN4 ACC IRN8 ACC IRN16 ACC IRN32 ACC P# P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 A01 -0.431 -4.35 3.931 0.016 0.615 -4.607 -1.417 CNE --- --- --- --- --- --- 3.622 -3.429 A02 0.307 -2.619 1.458 -0.928 -1.046 -4.413 -0.119 -3.583 0.617 -4.481 0.9785 -3.204 0.643 -8.208 2.159 NR A03 0.531 -2.038 -1.148 -2.43 1.323 -3.073 -0.875 CNE 1.689 -4.5155 -2.584 -5.457 2.383 -5.223 -2.172 CNE A04 -0.897 -6.356 -2.829 -7.887 -1.943 -6.188 -3.562 CNE -1.297 -8.691 -6.411 CNE 3.312 -3.876 0.533 -3.683 A05 -0.989 -2.341 -0.328 -1.852 1.001 -1.914 -0.351 -2.689 -0.217 -5.721 -0.141 -3.19 0.72 -5.751 0.695 -4.492 N 5 5 5 5 5 5 5 2 4 4 4 3 4 4 5 3 Mean -0.2958 -3.5408 0.2168 -2.6162 -0.01 -4.039 -1.2648 -3.136 0.198 -5.852125 -2.039375 -3.9503333 1.7645 -5.7645 0.9674 -3.868 Median -0.431 -2.619 -0.328 -1.852 0.615 -4.413 -0.875 -3.136 0.2 -5.11825 -1.3625 -3.204 1.5515 -5.487 0.695 -3.683 Min -0.989 -6.356 -2.829 -7.887 -1.943 -6.188 -3.562 -3.583 -1.297 -8.691 -6.411 -5.457 0.643 -8.208 -2.172 -4.492 Max 0.531 -2.038 3.931 0.016 1.323 -1.914 -0.119 -2.689 1.689 -4.481 0.9785 -3.19 3.312 -3.876 3.622 -3.429 SD 0.691 1.812 2.587 3.089 1.414 1.622 1.378 1.746 1.100 3.128 2.977 2.352 1.380 3.017 2.156 2.155  105  Table A.20 Individual adult pilot ACC amplitude (µV) for each condition measured at C3   IRN4 ACC IRN8 ACC IRN16 ACC IRN32 ACC P# P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 A01 0.102 -3.149 4.672 -0.385 0.497 -4.87 -1.375 CNE --- --- --- --- --- --- 3.622 -3.429 A02 0.704 -1.935 1.702 -0.613 -0.178 -3.194 0.625 -2.486 0.786 -3.817 1.675 -2.049 0.507 -7.193 2.205 NR A03 0.071 -2.148 -1.35 -2.591 0.986 -2.666 -0.64 CNE 1.073 -4.1445 -2.286 -4.893 2.033 -4.644 -1.825 CNE A04 -0.591 -4.145 -2.895 -6.262 -1.761 -4.3855 -2.363 CNE -0.699 -5.45 -3.957 CNE 2.703 -2.497 0.385 -4.073 A05 -0.838 -1.664 -0.021 -1.772 1.02 -1.651 0.29 -2.027 -0.383 -4.607 0.136 -2.49 0.788 -3.984 1.099 -3.313 N 5 5 5 5 5 5 5 2 4 4 4 3 4 4 5 3 Mean -0.1104 -2.6082 0.4216 -2.3246 0.1128 -3.3533 -0.6926 -2.2565 0.19425 -4.504625 -1.108 -3.144 1.50775 -4.5795 1.0972 -3.605 Median 0.071 -2.148 -0.021 -1.772 0.497 -3.194 -0.64 -2.2565 0.2015 -4.37575 -1.075 -2.49 1.4105 -4.314 1.099 -3.429 Min -0.838 -4.145 -2.895 -6.262 -1.761 -4.87 -2.363 -2.486 -0.699 -5.45 -3.957 -4.893 0.507 -7.193 -1.825 -4.073 Max 0.704 -1.664 4.672 -0.385 1.02 -1.651 0.625 -2.027 1.073 -3.817 1.675 -2.049 2.703 -2.497 3.622 -3.313 SD 0.613 1.026 2.917 2.375 1.154 1.300 1.221 1.247 0.756 2.106 2.224 2.034 1.123 2.660 2.040 1.996   Table A.21 Individual adult pilot ACC amplitude (µV) for each condition measured at C4   IRN4 ACC IRN8 ACC IRN16 ACC IRN32 ACC P# P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 A01 -0.066 -3.25 4.281 CNE 0.014 -4.689 -1.356 CNE --- --- --- --- --- --- 3.999 -3.104 A02 0.318 -2.121 1.224 -0.615 -0.722 -3.412 0.253 CNE 0.242 -3.4242 0.5415 -2.708 0.923 -6.497 1.559 NR A03 0.804 -1.543 -9.8 -2.177 1.182 -3.219 -0.957 CNE 1.592 -3.971 -2.256 -5.036 2.406 -4.878 -1.742 CNE A04 0.625 -3.559 -0.596 -4.7 -1.647 -5.737 -4.073 CNE 0.367 -5.477 -3.948 CNE 2.063 -2.914 -0.515 -3.572 A05 -0.215 -1.337 0.256 -1.151 1.139 -1.416 -0.202 -2.626 -1.813 -5.037 -1.104 -3.284 0.644 -4.31 0.524 3.129 N 5 5 5 4 5 5 5 1 4 4 4 3 4 4 5 3 Mean 0.2932 -2.362 -0.927 -2.16075 -0.0068 -3.6946 -1.267 -2.626 0.097 -4.4773 -1.691625 -3.676 1.509 -4.64975 0.765 -1.182 Median 0.318 -2.121 0.256 -1.664 0.014 -3.412 -0.957 -2.626 0.3045 -4.504 -1.68 -3.284 1.493 -4.594 0.524 -3.104 Min -0.215 -3.559 -9.8 -4.7 -1.647 -5.737 -4.073 -2.626 -1.813 -5.477 -3.948 -5.036 0.644 -6.497 -1.742 -3.572 Max 0.804 -1.337 4.281 -0.615 1.182 -1.416 0.253 -2.626 1.592 -3.4242 0.5415 -2.708 2.406 -2.914 3.999 3.129 SD 0.436 1.000 5.291 1.843 1.217 1.632 1.690 1.174 1.223 2.163 1.805 2.188 1.003 2.444 2.184 2.723    106  Table A.22 Individual adult pilot ACC latency (ms) for each condition measured at Cz   IRN4 ACC IRN8 ACC IRN16 ACC IRN32 ACC P# P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 A01 662.5 690.5 805.4 862.4 641.5 692.5 713.5 CNE --- --- --- --- --- --- 751.5 880.4 A02 652.5 703.5 772.5 849.4 635.5 688.5 755.5 803.4 627.6 674.5 733.5 810.4 615.6 672.5 728.5 NR A03 658.5 720.5 778.5 864.4 636.5 710.5 769.5 CNE 599.6 700.5 742.5 808.4 624.6 679.5 729.5 CNE A04 622.6 679.5 726.5 810.4 643.5 697.5 726.5 CNE 626.6 683.5 749.5 CNE 604.6 676.5 733.5 785.5 A05 663.5 701.5 787.5 824.4 656.5 710.5 742.5 996.31 613.6 688.5 744.5 889.4 624.6 685.5 749.5 923.4 N 5 5 5 5 5 5 5 2 4 4 4 3 4 4 5 3 Mean 651.9 699.1 774.1 842.2 642.7 699.9 741.5 899.9 616.8 686.8 742.5 836.1 617.3 678.5 738.5 863.1 Median 658.5 701.5 778.5 849.4 641.5 697.5 742.5 899.9 620.1 686.0 743.5 810.4 620.1 678.0 733.5 880.4 Min 622.6 679.5 726.5 810.4 635.5 688.5 713.5 803.4 599.6 674.5 733.5 808.4 604.6 672.5 728.5 785.5 Max 663.5 720.5 805.4 864.4 656.5 710.5 769.5 996.3 627.6 700.5 749.5 889.4 624.6 685.5 751.5 923.4 SD 17.0 15.3 29.4 23.9 8.4 10.2 22.3 497.6 276.1 307.3 332.1 459.1 276.2 303.5 11.1 475.3  Table A.23 Individual adult pilot ACC latency (ms) for each condition measured at C3   IRN4 ACC IRN8 ACC IRN16 ACC IRN32 ACC P# P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 A01 662.5 702.0 810.4 864.4 649.5 692.5 713.5 CNE --- --- --- --- --- --- 751.5 880.4 A02 651.5 703.5 771.5 849.4 636.5 688.5 756.5 801.4 633.5 676.5 734.5 812.4 626.6 672.5 726.5 NR A03 652.5 722.5 780.5 864.4 635.5 708.5 767.5 CNE 601.6 699.5 742.5 806.4 624.6 678.5 733.5 CNE A04 635.5 681.5 726.5 819.4 643.5 694.0 278.5 CNE 624.6 678.5 735.0 CNE 613.6 669.5 737.5 790.4 A05 663.5 710.5 787.5 821.4 660.5 708.5 767.5 1007.4 613.6 688.5 735.5 885.4 618.6 683.5 749.5 925.4 N 5 5 5 5 5 5 5 2 4 4 4 3 4 4 5 3 Mean 653.1 704.0 775.3 843.8 645.1 698.4 656.7 904.4 618.3 685.8 736.9 834.7 620.8 676.0 739.7 865.4 Median 652.5 703.5 780.5 849.4 643.5 694.0 756.5 904.4 619.1 683.5 735.2 812.4 621.6 675.5 737.5 880.4 Min 635.5 681.5 726.5 819.4 635.5 688.5 278.5 801.4 601.6 676.5 734.5 806.4 613.6 669.5 726.5 790.4 Max 663.5 722.5 810.4 864.4 660.5 708.5 767.5 1007.4 633.5 699.5 742.5 885.4 626.6 683.5 751.5 925.4 SD 11.3 15.0 30.8 22.2 10.3 9.4 212.6 500.7 276.8 306.8 329.5 458.3 277.7 302.4 10.6 476.5  107    Table A.24 Individual adult pilot ACC latency (ms) for each condition measured at C4   IRN4 ACC IRN8 ACC IRN16 ACC IRN32 ACC P# P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 P1 N1 P2 N2 A01 666.5 701.5 808.4 CNE 647.5 690.5 712.5 CNE --- --- --- --- --- --- 751.5 880.4 A02 649.5 704.5 780.5 849.4 635.5 686.5 755.5 CNE 631.5 676.5 741.5 812.4 602.6 672.5 724.5 NR A03 654.5 724.5 783.5 860.4 636.5 710.5 772.5 CNE 601.6 695.5 742.5 806.4 627.6 685.5 731.5 CNE A04 622.6 674.5 724.5 814.4 645.5 697.5 726.5 CNE 627.6 688.5 720.5 CNE 602.6 681.5 728.5 781.45 A05 663.5 703.5 776.5 823.4 649.5 695.5 742.5 975.3 645.5 685.5 740.5 891.4 615.6 683.5 747.5 916.4 N 5 5 5 4 5 5 5 1 4 4 4 3 4 4 5 3 Mean 651.3 701.7 774.7 836.9 642.9 696.1 741.9 975.3 626.5 686.5 736.2 836.7 612.1 680.8 736.7 859.4 Median 654.5 703.5 780.5 836.4 645.5 695.5 742.5 975.3 629.5 687.0 741.0 812.4 609.1 682.5 731.5 880.4 Min 622.6 674.5 724.5 814.4 635.5 686.5 712.5 975.3 601.6 676.5 720.5 806.4 602.6 672.5 724.5 781.5 Max 666.5 724.5 808.4 860.4 649.5 710.5 772.5 975.3 645.5 695.5 742.5 891.4 627.6 685.5 751.5 916.4 SD 17.5 17.8 30.7 374.7 6.5 9.1 23.6 436.2 280.6 307.1 329.4 459.5 273.9 304.5 12.0 473.3  

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