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An unforgettable apple : attention and memory for forbidden objects Truong, Grace 2013

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  AN UNFORGETTABLE APPLE: ATTENTION AND MEMORY FOR FORBIDDEN OBJECTS  by  GRACE TRUONG B.Sc., The University of British Columbia, 2009    A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF  THE REQUIREMENTS FOR THE DEGREE OF    MASTER OF ARTS  in   THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Psychology)  THE UNIVERSITY OF BRITISH COLUMBIA   (Vancouver)    August 2013  ? Grace Truong, 2013 	 ? ii	 ?Abstract Are we humans drawn to the forbidden?  From jumbo-sized soft drinks to illicit substances, the influence of prohibited ownership on subsequent demand has made this question a pressing one. We know that objects we ourselves own have a heightened psychological saliency, relative to comparable objects that are owned by others, but do these kinds of effects extend from self-owned to "forbidden" objects?  To address this question I developed a modified version of the Turk shopping paradigm in which ?purchased? items were assigned to various recipients. Participants sorted everyday objects labeled as self-owned, other-owned, and either forbidden to oneself (Experiment 1) or forbidden to everyone (Experiment 2). Subsequent surprise recognition memory tests revealed forbidden objects with high (Experiment 1) but not low self-relevance (Experiment 2) were recognized as well as self-owned objects and better than other-owned objects. In a third and final experiment I used event-related potentials (ERPs) to determine whether self-owned and self-forbidden objects, which showed a common memory advantage, are in fact treated the same at a neurocognitive-affective level.  I found that both object types were associated with enhanced cognitive analysis, relative to other-owned objects, as measured by the P300 ERP component.  However, I also found that self-forbidden objects uniquely triggered an enhanced response preceding the P300, in an ERP component (the N2) sensitive to more rapid, affect-related processing. Our findings thus suggest that while self-forbidden objects share a common cognitive signature with self-owned objects, they are unique in being identified more quickly at a neurocognitive level. 	 ? iii	 ?Preface  This project was approved by the UBC Behavioral Research Ethics Board.  Certificate numbers: H11-03209  (Experiments 1 & 2), H03-70419 (Experiment 3)    The following publication arose from work presented in this thesis:  Truong, G., Turk, D. J., & Handy, T. C. (In press). An Unforgettable Apple: Memory and Attention for Forbidden Objects. Cognitive, Affective, and Behavioral Neuroscience.  The content in this publication are located in various parts of this thesis across all the chapters, and have been integrated into this thesis. Figures and tables from this thesis were reprinted with the permission of Cognitive, Affective, and Behavioral Neuroscience.     Nathan Wispinski, Lara Cooper, Javier Granados-Samayoa, and Simon Ho assisted with data collection for each of the three experiments, while David Turk and Todd Handy made intellectual contributions at various stages of this research. Todd Handy was also involved in editing the manuscript.   	 ? iv	 ?Table of Contents Abstract ????????????????????????????...?????..ii Preface ??????????????????.????????????????.iii Table of Contents ????????????..?????????????..????.iv List of Tables ??????..????????????????????...????....v List of Figures ???..????????????????????.......?????? Acknowledgements ?????????????????????????????.vii Dedication ???????????????????????????????..?.viii Chapter 1: Introduction ???????????????????????????...1  1.1 The concept of ?mine? ????????????????...???????...1  1.2 Dominance of self-owned objects and the mere ownership effect ???????...3  1.3 Reactance and the salience of ?forbidden? ????????????????...5   1.4 The role of the self in ownership ????????????????????..7  1.5 Overview of experiments ???????????????????.????.9 1.6 Hypotheses ????????????????????????????..11 Chapter 2: Experiment One ?????????????????????????...13  2.1 Methods ??????????????????????.???????..13  2.2 Results ????????..?????????????????????...15  2.3 Discussion ???????????????????????????..?.17 Chapter 3: Experiment Two ?????????????????????????..19  3.1 Methods ???????????????????????..????....?.19  3.2 Results ????????????????????????..?..????.20  3.3 Discussion ????????????????.???????????.?.21 Chapter 4: Experiment Three ????????????????????????....23  4.1 Methods ??????????????????.???????????. 23  4.2 Results ??????????????????????????.??...?.25  4.3 Discussion ????????????????????????????...31 Chapter 5: Conclusion ???????????????????????..????..34  5.1 Strengths and limitations ???????????????????????.34  5.2 Connections to extant research ???????????.????????.?.36  5.3 Future directions ???????????????????????.??....38 References ????????????????????????????????....40 	 ? v	 ?List of Tables Table 4.1  Experiment 3: Mean amplitudes (?V) in N2 timeframe at selected electrode sites as a function of ownership category. Standard errors are in parentheses ?....? 27  Table 4.2  Experiment 3: Mean amplitudes (?V) in P300 timeframes (early and late) at selected electrode sites as a function of ownership category. Standard errors are in parentheses ??????????????????????????... 28                      	 ? vi	 ?List of Figures Figure 2.1 Experimental Paradigm ?????????????????????? 15 Figure 2.2  Percent recognition scores as a function of category for Experiment 1???... 17 Figure 3.1 Percent recognition scores as a function of category for Experiment 2 ??..? 21 Figure 4.1 ERP responses to ownership cues for Experiment 3 ??????????... 29 Figure 4.2 Topography maps pertaining to the ownership cues for the N2 (250-300 ms),                                     early P300 (375-450 ms), and late P300 (450-525 ms) time windows ???.... 30            	 ? vii	 ?Acknowledgments  I thank my supervisor, Dr. Todd C. Handy, for his support, guidance, and encouragement.   Thank you to all members of the Attentional Neuroscience Lab, especially Nathan Wispinski, Lara Cooper, Javier Granados-Samayoa, and Simon Ho. Without you, there would be no data. With you, there is an abundance of enthusiasm, hard work, and joy.   I would like to acknowledgement the members of my committee, Dr. Jim Enns and Dr. Geoff Hall, for their insights into this project.   Lastly, I express immeasurable gratitude to my family. Your belief in me makes all the difference.        	 ? viii	 ?Dedication ? mark      To Dr. Sam M. Doesberg When I asked, ?Really? I could do that?? You said, ?Yes.?	 ? 1	 ?Chapter 1: Introduction Going back to Eve and the apple, the idea that we have a particular affinity for ?forbidden fruit? is a common and recurring theme throughout history, art, and literature. The allure of things we cannot have seems to capture our imaginations and our attention. Yet, is this really the case? Like Eve, are we really drawn to things we are forbidden to have?    Here we framed the question empirically from the perspective of object ownership. Often considered a dichotomy, object ownership is comprised of two categories: other and mine. Of these categories, objects that are ?mine? are preferentially attended to and remembered relative to objects in the other category. Forbidden objects, that is, objects we cannot have, fall into the ?other? category. Assuming the dichotomy?s typical findings hold, one would expect that forbidden items would not be particularly memorable. However, this logic runs counter to both intuition and experience. Given this apparent contradiction, I aimed to answer three questions. First, are forbidden objects as strongly encoded as objects owned by the self? Second, does self-referential processing play a role in the encoding of forbidden objects like it does for objects owned by the self? Lastly, can forbidden objects be dissociated from the classic ownership dichotomy on an electrophysiological level? To answer these questions, I first examine the literature on ownership.    1.1 The concept of ?mine?  One of the most salient distinctions a person learns about in life exists to separate that which belongs to oneself and that which does not. Ownership, the delineation between things that are and are not tied to the self through agency and possession, is a ubiquitous concept and is 	 ? 2	 ?contemplated early and often. Representations of ownership begin in childhood and are refined throughout development (Blake & Harris, 2011; Cunningham, Vergunst, Macrae, & Turk, 2012). As early as 24 months old, toddlers are using possessive pronouns such as ?mine? and ?yours? (Hay, 2006) and by four years old, children develop stable heuristics for inferring who owns what (Friedman & Neary, 2008; Shaw, Li, & Olson, 2012).    The use of the term ?ownership? spans many concepts, as both concrete and abstract things can be owned. For example, social psychologists De Dreu and van Knippenberg (2005) use ownership of arguments or positions to explain the barriers to conflict resolution while neuropsychologist Tsakiris (Tsakiris, Hesse, Boy, Haggard, & Fink, 2007; Tsakiris 2010) discusses brain abnormalities that distort feelings over ownership over the body. The complexities of ownership continue to affect legal matters such as the rights of animals (Wells & Hepper, 1997) and the rules governing intellectual property (Hannah, 2004; Stark & Perfect, 2007). Common to all of these concepts is the idea that ownership matters; whether an idea or an arm or a puppy is possessed by the self or by some external being changes our perceptions and behaviors.    Despite its application in a number of areas, perhaps the most frequent use of  ?ownership? refers to owning material goods. What differentiates ownership of objects from owning other things is the transitory nature of the object-self relationship. Unlike one?s body, one?s possessions are not associated with the self from birth nor do they necessarily remain with the self for the remainder of one?s life. The ownership status of an object can change an infinite 	 ? 3	 ?number of times but somehow, while they are owned by the self, objects are afforded a host of special properties.    1.2 Dominance of self-owned objects and the mere ownership effect   When dichotomized as belonging to the self (?mine? or self-owned) or belonging to someone else (?not mine? or other-owned), there is a clear-cut winner in the cognitive processing of objects. Across a variety of domains and levels of analyses, self-owned objects are at an advantage.  The earliest signs of this advantage begin the moment the self sees an object. Items identified as self-owned almost immediately elicit higher levels of attention as measured by event-related potentials (Turk et al., 2011; Gray, Ambady, Lowenthal, & Deldin, 2004) and eye movements (Ashby, Dickert, & Gl?ckner, 2012). Before a person even touches the item, there is already enhanced relationship to it. Such differential attention may produce a cascade of other processing differences downstream. Ownership contexts have been shown to shift motivational focus such that seemingly basic sensory properties like object weight, thickness, and size can be perceived differently (Dai & Hsee, 2013). To a thirsty person, a glass of water that is ?mine? appears significantly smaller than an equivalent glass that is ?not mine? (Dai & Hsee, 2013).     Of the numerous aspects of cognition most likely to be altered by differences in attention, memory emerges as a measure that has shown the most consistent ownership effects. Indeed, several studies show that objects that have been first encoded as self-owned are recognized and explicitly remembered with greater accuracy later on (Cunningham, Turk, MacDonald, & Macrae, 2008; van den Bos, Cunningham, Conway, & Turk, 2010; Kesebir & Oishi, 2010; Cunningham, van den Bos, & Turk, 2011; Leshikar & Duarte, 2012). These memory effects may be tied to greater attention allocation (Turk et al., 2011).  	 ? 4	 ? In addition to memory, the self-ownership ?boost? also extends to subjective preference and assessments of worth. Areas related to reward processing show higher activation to self owned objects (Turk, van Bussel, Waiter, & Macrae, 2011). Furthermore, there is a correlation between self-ownership and preference. For example, Huang, Wang, and Shi (2009) found that possessions assigned to self-ownership are implicitly preferred to possessions assigned to other-ownership in an Implicit Association Test (IAT). This preference when placed in an economic context translates into perhaps the most famous self-ownership effect of all: the endowment effect. The endowment effect is observed when a buyer?s offer price (i.e., his or her willingness to pay) for an object such as a mug or a chocolate bar is significantly less than a seller?s offer price (i.e., his or her willingness to accept) (Kahneman, Knetsch, & Thaler, 1990; Knetsch, 1989). In other words, the non-owner (the buyer) assigns a lower economic value to an object than the object-owner (the seller). While some have argued this contrast in valuation is due to loss aversion (e.g., Kahneman & Tversky, 1979), Morewedge and colleagues (2009) demonstrated increased liking due to self-ownership was a better explanatory mechanism.   In considering the reason why self-owned items are more favored, there are many possible explanations. One?s possessions may prove themselves exceptionally valuable: some objects can be traded for other valuable objects (i.e., they have high economic value), others may be long-lasting and durable, still others may be used for a wide range of functions and preclude the need to acquire several single-function items. Self-owned objects may be remembered better because of highly salient visual properties or prolonged duration of exposure (i.e., you probably see your own items more than others? items). Yet, between two otherwise parallel or equivalent 	 ? 5	 ?items, a self-owned object will likely be rated more attractive or more memorable than a non-self owned object. When an object is rated more attractive or more memorable by an owner than a non-owner, this is termed the ?mere ownership? effect (Beggan, 1992). Moreover, this effect is still observed when ownership status is assigned in the moment and it remains after controlling for duration of exposure. Actual physical possession of an object is not even necessary; a representation of owning an object is sufficient (Sen & Johnson, 1997). By eliminating the potential confounds of history and familiarity with objects, Beggan established that ownership exerts its own influence independent of other factors. Many of the aforementioned studies exhibited the mere ownership effect, using objects selected by the experimenters and randomly assigned to ownership condition (Cunningham et al., 2008; Huang, Wang & Shi, 2009, Morewedge et al., 2009). It becomes apparent that self-owned objects appear to sit atop a cognitive processing hierarchy, relegating other-owned objects to lower levels of attention, memory and hedonic preference. Given this conclusion, our first experiment addressed whether ?forbidden? objects, or objects that we are specifically denied from owning, may have a comparable effect on our cognition.  In light of the common perception that, like Eve, we are in fact drawn to things we "can't" have, this predicted they might.   1.3 Reactance and the salience of ?forbidden?    Support for enhanced saliency of forbidden objects comes out of work on reactance theory. As described by Brehm (1966), when one?s choices are threatened or circumscribed one may experience feelings of arousal known as ?reactance? and act to reduce reactance by restoring a feeling of choice or freedom. To understand how this theory fits with ownership, it is imperative to consider each component of the theory. Before any reactance can be induced, the 	 ? 6	 ?limitation of choice must be explicitly presented (Brehm & Brehm, 1981). Situations in which an option is eliminated without a person?s knowledge do not generate reactance. In the context of object ownership, assignment of objects to either self-ownership or other-ownership does not bring choice-type information into the environment. When an element of restricted agency is added, for instance when there are objects that one ?cannot have?, then the issue of choice enters the picture and becomes salient.   Following a choice threat or choice elimination, a person may feel arousing negative affect. This negative affect has been labeled as ?hostility? or ?anger? and is accompanied by counterarguments (Rains, 2013). Upon experiencing these negative feelings, a person is compelled to act and reduce these feelings. In some respects, reactance parallels cognitive dissonance (Festinger, 1962) and the meaning maintenance model (Heine, Proulx, & Vohs, 2006) in which a situation arises that generates a state of unease that persons seek to reduce. There are two main approaches to lessening reactance: attempting to restore the lost freedom(s), and increasing motivation towards the lost freedoms or their intended outcomes (Brehm & Brehm, 1981). Restoring freedom involves making a person perceive a sense of regained control such as presenting a way he or she can ?fix? the situation so that all choices are once again available for selection (Schwarz, 1980). Of greater relevance to the current work is the enhancement of motivation towards intended choice outcomes. When motivation is increased, the attractiveness of an outcome also increases. Many studies have shown that when the intended outcome is possession of an object, subjective preference ratings for said object reliably increases (Brehm, Stires, Sensenig, & Shaban, 1966; Brehm & Rozen, 1971; Worchel, Lee, & Adewole, 1975). This has had particularly important implications for public health campaigns 	 ? 7	 ?that have used warning labels for unhealthy/unsafe products (e.g., fatty cottage cheese, violent video games), only to see those products appear more attractive in the eyes of consumers (Bushman, 1998; Bijvank, Konijn, Bushman & Roelofsma, 2009). Through the use of warning labels, products were singled out as restricted to the public. In other words, when these products were ?forbidden? to potential buyers, rather than take the warning labels as a call to avoid certain products, potential buyers paid more attention to the forbidden options.   Despite not belonging to a self-ownership category, work on reactance shows forbidden objects can parallel self-owned objects in terms of relative valuation. This premise led to the first research question: does the parallel between self-owned objects and forbidden objects exist for other behaviors such as memory? Experiment 1 sought to address this question. If it does, what might be the mechanism driving the memory bias?   1.4 The role of the self in ownership  If forbidden objects are remembered as well as objects owned by the self, there might be multiple mechanisms driving such an effect. One possibility is that the allusion to limitations of choice induced reactance-like arousal, leading to increased stimulus processing. Another but not mutually exclusive possibility is that enhanced memory for forbidden objects is driven by the same mechanism proposed to drive enhanced memory for self-owned objects, namely the self-reference effect. The relationship between the self and an object is considered the most fundamental mechanism for understanding ownership effects (Belk, 1988). Without a relationship to the self, objects that are ?owned? but by no one in particular fail to generate enhanced levels of preference (Nesselroade, Beggan, & Allison, 1999). The self-object 	 ? 8	 ?relationship appears to be bidirectional, with objects acting as external representations of self, and the self acting as a framework for elevating objects to higher importance.    According to McClelland (1987), the power to control objects is the key to viewing objects as extensions of self. Like an arm or a leg, an object can be wielded and manipulated in the pursuit of goals. Others view possessions as unchanging symbols of self that cue others to one?s personality (Gosling, Ko, Manarelli, & Morris, 2002), or help maintain self-identify in the face of life transitions (McCracken, 1987). The relationship between objects and the self can be close that losing possessions during natural disasters can produce grief comparable in intensity to losing loved ones (McLeod, 1984). From this perspective, objects can be used as tangible avatars for one?s identity. However, before objects are integrated into the self, they must first be processed in relation to the self by means of self-referential encoding.   Self-referential encoding (SRE) refers to the use of the self as a reference point during stimulus encoding and is often compared to other encoding strategies such structural, phonemic, semantic, and other-referential encoding (Rogers, Kuiper & Kirker, 1977) This type of encoding often yields a memory benefit for items encoded self-referentially (for a review, see Symons & Johnson, 1997). For instance, an adjective is more likely to be remembered when a person decides whether said adjective is descriptive of himself/herself than if a person decides whether the adjective is presented in uppercase or lowercase letters. Self-referential encoding can generate a memory advantage even when self-referencing is incidental to a task (Bower & Gilligan, 1979; Ganellen & Carver, 1985). Klein and Loftus (1988) have suggested the self promotes greater elaborative and organizational processing and this explains why associations 	 ? 9	 ?with the self may be more deeply encoded as well as more easily retrieved. Elaborative processing involves drawing multiple connections between a target and extant items in memory (e.g., this adjective describes me in situations X and Y), whereas organizational processing involves relating a target to items in the same category (e.g., this adjective is similar to another adjective in the study list that also applies to me). Because each person is rich with thoughts and memories about their own lives, especially relative to thoughts and memories about other people?s lives, ?self? becomes the most fruitful avenue for associative encoding. Accordingly, much research on ownership identifies self-relevance or self-referential processing as a primary factor in ownership-related effects (Morewedge et al., 2009; Serbun, Shih, & Gutchess, 2011; van den Bos et al., 2010; Turk et al., 2011a). If self-referential encoding is a mechanism for increasing recognition for forbidden objects, reducing the degree of self-relevance of the forbidden category should reduce encoding and subsequent recognition for forbidden objects. Experiment 2 tested this hypothesis.   1.5 Overview of experiments    Although self-owned objects may show comparable levels of recognition bias relative to other-owned objects, it does not suffice to conclude that self-owned and forbidden (to self) objects are necessarily treated the same cognitively. These two categories may not parallel each other neurocognitively and dissociations between forbidden and self-owned (and other-owned) objects may emerge during different stages of processing. To examine the fine-grain temporal processing of forbidden objects, I examined their associated event-related potentials, specifically the P300.   	 ? 10	 ?The P300 (also referred to as the P3) is a large positive ERP component. The P300 waveform emerges 300-400 ms after the presentation of a stimulus and is proposed to index attentional resources devoted to context-updating (for reviews, see Patel & Assam, 2005; Polich, 2007). Critically, previous research has shown the P300 is sensitive to self-relevant information such as one?s name or face (e.g., Berlad & Pratt, 1995; Ninomiya, Onitsuka, Chen, Sato, & Tashiro, 1998; Tacikowski & Nowicka, 2010; Zhao, Wu, Zimmer, & Fu, 2011). Specifically, P300 amplitude was greater for self-relevant stimuli compared to other people?s names and faces. The amplitude of the P300 has been shown to modulate for stimuli less explicitly recognized as self-relevant, such as one?s own handwriting (Chen et al., 2008), home province (Chen et al., 2011), and other autobiographical information (Gray, Ambady, Lowenthal, & Deldin, 2004).   More recently, Turk at el. (2011a) employed a modified ?shopping? paradigm and presented participants with common everyday objects, then informed participants via colored border cue that an object was ?purchased? and either self-owned or other-owned. ERPs time-locked to the presentation of the ownership cues showed self-ownership cues elicited greater P300s than other-ownership cues. Furthermore, attention to the periphery as indexed by P1 amplitude decreased during self but not other ownership cues. This experiment was a departure from previous ERP studies on self-relevance because it assigned self-relevance status immediately after object presentation, whereas the aforementioned experiments relied on previously established biographical information. By eliminating the confound of prior history/interaction with the stimuli, Turk et al. found an attentional bias for self-relevant items could be generated almost instantly upon assignment to self-ownership, an attentional ERP 	 ? 11	 ?equivalent to the ?mere ownership? effect.  If self-ownership cues and forbidden ownership cues are underpinned by self-relevance or self-referential encoding, they should both exhibit greater P300 amplitudes relative to other-ownership cues. However, these two categories may not show the same pattern across other ERP components. In Experiment 3, I examined the event-related potentials for each ownership category.    1.6 Hypotheses The goal of this work was to examine the cognitive properties of ?forbidden? objects from the perspective of object ownership. First, I tested whether forbidden objects would be remembered as well as self-owned objects. Secondly, I tested self-referential encoding as a possible mechanism in explaining stronger encoding for forbidden objects. Lastly, I looked at the electrophysiological signature for forbidden ownership cues, with the P300 being the primary waveform of analysis. As such, the current set of experiments tested the following hypotheses:  (1) When ownership status is assigned at the moment of object presentation and in the absence of other information about the stimuli, forbidden objects will be recognized at levels comparable to self-owned objects and both of these object types will be recognized significantly more often than other-owned objects.  (2) When the description of the forbidden category is altered such that it no longer makes specific reference to the individual, forbidden objects will no longer be recognized at levels comparable to self-owned objects. Rather, recognition is expected to drop to the level for that of 	 ? 12	 ?other-owned objects. Self-owned objects will still be recognized at greater levels than other-owned objects.   (3) The mean amplitude of the P300 ERP component will be greater (i.e., more positive) for self-ownership cues and forbidden ownership cues compared to other-ownership cues.  	 ? 13	 ?Chapter 2: Experiment One In this chapter, I conducted the first of three experiments, whereby the aim of the experiment was to examine whether rendering objects forbidden confers a memory advantage similar to that for self-owned objects. In order to address this question, I used a paradigm adapted from Cunningham et al. (2008). Participants viewed objects assigned to ?mine? (self-ownership), ?yours/not mine? (other-ownership) and a third, novel category: ?can?t have? (or forbidden). A subsequent old/new recognition test assessed memory for objects in each category. I analyzed the proportion of objects recognized as a function of ownership category. I found that forbidden objects were recognized with comparable accuracy to self-owned objects and both of these object types were recognized more often than other-owned objects. The results reveal that forbidden objects, despite not being not self-owned, can elicit strong encoding on par with objects owned by the self.   2.1 Methods Participants Thirty-six undergraduate students (29 women) recruited through a university human subject pool completed the experiment in exchange for partial course credit (Age: M = 20.70, SD = 3.48). All had normal or corrected-to-normal vision, no history of neurological problems, and provided written informed consent at the beginning of the study.   Stimuli and Paradigm The stimulus set included 210 digital images of frequently purchased everyday items (e.g., raspberries, milk, pasta). Each image was 250 x 250 pixels and contained a photograph of 	 ? 14	 ?the item on a white background. Half (105) of the images were randomly selected for use during the sorting task, and were equally divided between the three ownership categories. For the sorting task, a colored border around each image was used to cue ownership category. Borders were 25 pixels wide and were blue, red, and black for self-owned, other-owned, and forbidden items, respectively. The remaining non-cued items were used as foils for the subsequent memory test. All images were presented on a computer monitor (see Figure 2.1).   Participants completed a sorting task, followed by a memory test. During the first task, participants were told they would be sorting items that either belonged to them (self-owned), belonged to the experimenter (other-owned), or could not belong to them (forbidden) and that ownership category would be denoted by a colored border presented around the image. Participants were verbally quizzed before beginning the sorting task to ensure correct construal of the ownership conditions (e.g., objects with a black border could not be owned by the participant specifically rather than being unable to be owned by anyone in general). During explanation of the categories, the experimenter did not use the word ?forbidden?, instead describing the objects with a black border as ?objects you cannot own/have,? minimizing potential allusions to taboo or illegal objects. On each trial, an object was presented in the middle of the computer screen, at first by itself (for a variable interval of 400-600ms) then surrounded by a colored-border indicating ownership category (for a variable interval of 800-1200ms). Upon seeing the cue, participants were required to ?sort? the item via button press. As such, the paradigm was an adaptation of the ?shopping? paradigm used by Cunningham et al. (2008) and Turk et al. (2011a), but rather than a ?shopping? task, it was a more general ?sorting? task.  	 ? 15	 ?After completing the sorting task, participants were given a surprise ?Old/New? recognition memory test. All items from the sorting task and 105 similar but previously unseen items were presented sequentially in a randomized order. Participants indicated whether they recognized the image from the sorting task  (?old? and recognized) or not (?new? and not recognized or not previously seen) via button press. The item remained on screen until the participant responded or five seconds had elapsed at which point the next trial would begin. Participants were encouraged to guess on trials if they were uncertain.               2.2 Results Participants? object recognition scores for each ownership category were calculated by the percentage of ?old? objects correctly identified as previously seen out of the total number of Ownership cue [800-1200ms] Object image [400-600ms] Fixation [800-1200ms] Figure 2.1.  Sorting task paradigm for Experiments 1 and 2.  	 ? 16	 ??old? objects presented. As foils (?new? items) were never assigned to an ownership category, category-specific false alarm rates could not be determined. Rather, the average overall false alarm rate was 23%. As shown in Figure 2.2, recognition for self-owned objects and forbidden objects appeared higher than recognition for other-owned objects. This was confirmed by a repeated-measures ANOVA, which revealed a main effect of ownership category, F(2, 70) = 5.30, p = .007, partial ?2 = .13.  Post-hoc analyses via Tukey?s HSD revealed self-owned objects were better recognized than other-owned objects, ? = 5.73 with CI.95 = [1.68, 9.81], p = .007. Forbidden objects were also better recognized than other-owned objects, ? = 4.48 with CI.95 = [.85, 8.10], p = .015. Recognition between self-owned and forbidden objects did not significantly differ (p = .48). On average, participants responded very conservatively, selecting ?old? for only 34% across all trials, lower than 50% expected during random responding.                	 ? 17	 ?                Figure 2.2. Percent recognition scores as a function of category for Experiment 1. Error bars represent standard errors of the mean.   2.3 Discussion  The results from Experiment 1 replicate previous findings showing greater memory for self-owned items versus other-owned items. More importantly, however, it demonstrated a parallel effect for forbidden items relative to other-owned items. What drives this cognitive Self Other Forbidden0507525Percent Recognized (%)** *** p < .01     * p < .05	 ? 18	 ?advantage?  One possibility is that the allusion to limitations of choice induced reactance-like arousal, leading to increased stimulus processing. Another but not mutually exclusive possibility is that enhanced memory for forbidden objects is driven by the same mechanism proposed to drive enhanced memory for self-owned objects, namely the self-reference effect.  The forbidden objects of Experiment 1 may have triggered self-referential processing much in the same way as self-owned objects because they were always described as things ?you? could not have rather than things ?no one? could have. If self-relevance plays a role in increasing attention for forbidden objects, one might expect a decrease in self-relevance would lead to a decrease in attention to the same objects. In Experiment 2, self-relevance for forbidden objects was attenuated by altering the description from ?you cannot have? to ?no one can have.? Recognition memory was assessed for objects that were self-owned, other-owned, and forbidden to everyone. I predicted objects forbidden to everyone would elicit the same level of recognition as other-owned objects, with both being lower than self-owned objects.   	 ? 19	 ?Chapter 3: Experiment Two   This chapter describes the second of three experiments in which I explored the role of self-referential encoding as a mechanism for the ?forbidden? effect observed in Experiment 1. In order to address this question, I altered the degree of self-relevance and self-referential encoding by altering the description of the forbidden category to make it more general. I predicted that reducing the self-specificity of the forbidden category would weaken encoding of the category, and in turn diminish recognition for forbidden objects to the level for other-owned objects. Participants viewed objects assigned to categorization as ?mine? (self-ownership), ?yours/not mine? (other-ownership) and ?no one can have? (forbidden to everyone). A subsequent old/new recognition test assessed memory for objects in each category. I analyzed the proportion of objects recognized as a function of ownership category. I found that forbidden objects were no longer recognized as often as self-owned objects. Rather, recognition for this category did not differ significantly from other-owned objects. These results suggest self-referential encoding is a plausible mechanism for enhanced processing of forbidden objects.   3.1 Methods Participants  Thirty-seven undergraduate students (26 women) recruited through a university human subject pool completed the experiment in exchange for partial course credit (Age: M = 21.03, SD = 2.64). All had normal or corrected-to-normal vision, no history of neurological problems, and provided written informed consent at the beginning of the study.    	 ? 20	 ?Stimuli and Paradigm The stimuli and experimental procedures exactly mirrored Experiment 1 with the following exception:  to reduce the self-relevance of the ?forbidden? object category, it was described to participants as ?objects that could not be owned by anyone? (i.e., forbidden to everyone). Participants were verbally quizzed prior to the sorting task to ensure these ownership categories were understood.   3.2 Results Participants? object recognition scores for each ownership category were calculated in the same way as Experiment 1. The average overall false alarm rate was 24.73%. As shown in Figure 3.1, recognition of self-owned objects remained high relative to other-owned objects whereas recognition of forbidden objects dropped. A repeated-measures ANOVA revealed a main effect of ownership category, F(2, 72) = 4.04, p = .022, partial ?2 = .10. Post-hoc analyses via Tukey?s HSD revealed self-owned objects were better recognized than other-owned objects, ? = 5.24 with CI.95 = [1.41, 9.06], p = .009. Self-owned objects were also better recognized than objects forbidden (to everyone), ? = 4.39 with CI.95 = [.31, 8.47], p = .036. Recognition between other-owned and forbidden objects did not differ significantly (p = .68). Again, participants responded conservatively, selecting ?old? for only 40% across all trials.    	 ? 21	 ?                 Figure 3.1. Percent recognition scores as a function of category for Experiment 2. Error bars represent standard errors of the mean.   3.3 Discussion  Replicating the findings in Experiment 1, self-owned objects were better recognized than other-owned objects. Furthermore, as predicted, self-owned objects were better recognized than Self Other Forbidden0507525Percent Recognized (%)***** p < .01     * p < .05	 ? 22	 ?objects that were forbidden to everyone. The reduction of the memory boost for forbidden objects from Experiment 1 (forbidden to self) to Experiment 2 (forbidden to everyone) is consistent with extant literature on the self-reference effect, which states enhanced item-specific and relational processing afforded to the self leads to greater recall (Klein, 2012).   When forbidden objects are no longer explicitly self-relevant, the memorial advantage they share with self-owned objects also disappears, despite the objects still being ?forbidden?. The pattern of results across the first two experiments suggests that self-referential encoding is indeed a possible mechanism driving the forbidden effect and may affect recognition above and beyond any potential reactance caused by choice-reduction alone.  While such findings shed light on the nature of forbidden objects, it does not suffice to conclude that self-owned and forbidden (to self) objects are necessarily treated the same cognitively. Nor does it follow that self-referential encoding is the only means by which encoding of forbidden objects is intensified. These two categories may not parallel each other neurocognitively and dissociations between forbidden and self-owned (and other-owned) objects may emerge during different stages of processing. To explore these possibilities, in Experiment 3 I measured the event-related potentials elicited by cues indicating self-ownership, other-ownership, and forbidden ownership.     	 ? 23	 ?Chapter 4: Experiment Three The third experiment is covered in this chapter. The purpose of this experiment was to investigate the electrophysiological similarities and differences between self-ownership cues and forbidden-ownership cues. I recorded continuous electroencephalographic (EEG) activity while participants viewed frequently purchased everyday items on a computer screen during an ostensible ownership-category ?sorting? task. A colored border around each item denoted ownership category (self, other, forbidden to self) to which participants responded via button press. I analyzed event-related potentials time-locked to the presentation of the ownership cues. Self-ownership cues and forbidden-ownership cues both elicited increased P300 amplitudes relative to other-ownership cues, suggesting the engagement of self-referential attention toward these categories. Furthermore, forbidden-ownership cues were uniquely associated with greater N2 amplitude relative to self- and other-ownership cues. These results show there is common as well as dissociative processing for self-owned and forbidden ownership categories.   4.1 Methods Power Analysis A power calculation was conducted using G*Power (Faul, Erdfelder, & Buchner, 2007) for the P300 component time-locked to the ownership cues. Although the effect in Turk et al. (2011) was moderate in size (partial ?2 = 0.31), we chose a more conservative effect size (partial ?2 = 0.10) to determine an appropriate sample size. Within our chosen sample size (as follows) and effect size, power (1- ?) was approximately 0.80.   	 ? 24	 ?Participants Nineteen participants (11 women; 17 right-handed) completed the experiment in exchange for fifteen dollars (Age: M =21.89 SD = 2.18). All had normal or corrected-to-normal vision, no history of neurological problems, and provided written informed consent at the beginning of the study.    Stimuli The stimulus set consisted of the same 210 digital images used in Experiment 1 and Experiment 2. There were 70 images per ownership category (self-owned, other-owned, forbidden to self); ownership category was randomly assigned and again denoted by a colored border. The paradigm for this study was adapted from Turk et al. (2011a) and closely resembled the ?sorting? tasks from Studies 1 and 2. Participants ?sorted? items into ownership category upon cueing by a colored border and responded by button press. Each item was presented in the centre of a computer screen for 400-600 ms, and presented again but with a colored border for 800-1400 ms at which point participants responded. On-screen duration for stimuli was randomly varied to prevent temporal habituation to stimulus onset.   Electrophysiological Recording All electroencephalographic (EEG) activity was recorded relative to the CMS electrode, amplified (BioSemi Active 2 system) with a band-pass of 0.1?30 Hz (1/2 amplitude cutoffs), and digitized on-line at a sampling rate of 256 samples-per-second. In order to correct for and/or remove events relating to eye movements off-line, electrooculograms (EOGs) were recorded using electrodes inferior to the right eye, and on the outer canthus of both the left and right eyes. 	 ? 25	 ?Lastly, electrodes were recorded from the left and right mastoids; off-line, all EEG signals were re-referenced to their average.  Prior to re-referencing, computerized artifact rejection was performed offline to eliminate trials with detectable eye movements (> 1o), blinks, muscle potentials and amplifier blocking. Across participants, approximately 11% of trials were rejected based on these artifacts. For each participant, EEG was segmented for remaining events into 1000 ms epochs, starting 200 ms prior to event onset. These epochs were sorted by condition, signal-averaged, digitally low-pass Gaussian filtered (26.5 Hz half-amplitude cutoff) and baseline corrected to remove any linear slow-wave drifts prior to group-averaging for statistical analyses and illustration (-200 to 0 ms pre-stimulus baselines).   4.2 Results Since self-relevance has been found to reveal itself most robustly across a number of functional domains over cortical midline structures (Northoff et al., 2006), and since I sought to replicate the self versus other P300 difference found in Turk et al. (2011a) in addition to predicting a similar difference for forbidden versus other, ERP analysis focused a priori on parietal midline electrodes. Visual inspection of the ERP waveforms indicated possible effects of object condition in both the P300 and preceding N2 components.  Accordingly, both were statistically analyzed. Similar to Turk et al. (2011), accuracy was not analyzed as participants performed at ceiling.   N2. The N2 ERP component can be seen as a function of cue in Figure 4.1. We conducted an omnibus repeated-measures ANOVA that included ownership cue as a factor. As reported in Table 4.1, mean amplitude was measured at electrodes CPZ, P1, PZ, P2 and POZ over a 50 ms 	 ? 26	 ?time window (250-300 ms post-cue) centered on the approximate N2 peak in the grand-averaged waveforms. There was a significant main effect of cue, F(2, 36) = 8.22, p = .001, partial ?2 = .31. Post-hoc pairwise comparisons revealed N2 mean amplitude was larger for forbidden vs. self cues (p = .005), and for forbidden vs. other cues (p = .001). Amplitudes for self vs. other cues did not differ (p = .15).   P300. Visual inspection of the P300 waveform revealed morphological differences varying by time and cue (Figure 4.1). To more accurately account for the temporal nuances of the P300 waveform across conditions, we conducted an omnibus repeated-measures ANOVA with factors of ownership cue (self vs. other vs. forbidden) and time window (375-450 ms vs. 450-525 ms post-cue). As reported in Table 4.2, mean amplitude was examined for each time window at electrodes CPZ, P1, PZ, P2, and POZ. There was a significant time by cue interaction, F(2, 36) = 9.50, p = .002, partial ?2 =.35. There was a marginal main effect of cue, F(2, 36) = 3.60, p = .07, partial ?2 = .17.  Post-hoc pairwise comparisons for the late window revealed mean P300 amplitude was larger for self versus other cues (p = .006) and for forbidden versus other cues (p = .041). Mean amplitude for self versus forbidden cues did not significantly differ (p = .93). Waveforms in the early window did not differ (p = .051 for both self versus other and self versus forbidden, p = .85 for other versus forbidden).   	 ? 27	 ?Table 4.1.  Experiment 3: Mean Amplitudes (?V) in N2 timeframe at selected electrode sites as a function of ownership category. Standard errors are in parentheses.  Electrode Ownership Category  Self  Other Forbidden CPz  2.73 (0.54) 2.46 (0.49) 1.99 (0.46) P1 1.85 (0.45) 1.46 (0.40) 0.94 (0.35) Pz 2.51 (0.45) 2.03 (0.40) 1.41 (0.38)  P2 2.16 (0.44) 1.92 (0.37) 1.28 (0.35) POz 1.54 (0.44) 1.26 (0.35) 0.65 (0.33)  	 ? 28	 ?Table 4.2. Experiment 3: Mean Amplitudes (?V) in P300 timeframes (early and late) at selected electrode sites as a function of ownership category. Standard errors are in parentheses.  Ownership Category Electrode Self  Other Forbidden CPz Early Late  5.90 (0.61) 5.41 (0.57)  5.28 (0.49) 4.82 (0.53)  4.97 (0.50) 5.34 (0.52) P1 Early Late  4.81 (0.53) 4.22 (0.50)  3.99 (0.34) 3.35 (0.36)  3.89 (0.37) 4.10 (0.38) Pz Early Late  5.45 (0.54) 4.81 (0.54)  4.53 (0.43) 3.88 (0.48)  4.51 (0.40) 4.66 (0.41) P2 Early Late  4.99 (0.55) 4.27 (0.55)  4.39 (0.42) 3.65 (0.46)  4.28 (0.37) 4.24 (0.41) POz Early Late  3.89 (0.56) 3.13 (0.59)  3.12 (0.44) 2.33 (0.43)  3.42 (0.36) 3.35 (0.40)   	 ? 29	 ?                      Figure 4.1. ERP responses to ownership cues for Experiment 3. SelfOtherForbiddenN2 [250 - 300 ms]P300 early [375 - 450 ms]P300 late [450 - 525 ms]CPZP1 PZ P2POZ2 ?V400 800ms	 ? 30	 ?                   Figure 4.2. Topography maps pertaining to the ownership cues for the N2 (250-300 ms), early P300 (375-450 ms), and late P300 (450-525 ms) time windows.   N2early P300mine other forbiddenlate P300	 ? 31	 ?4.3 Discussion  At 250-300 ms post-stimulus, the forbidden cue elicited a greater negative deflection in the N2 relative to both the self and other cues. The ?self? and ?other? cues did not significantly differ during this time window. Analysis of the P300 revealed different responses to the ownership cues as a function of time window. Although the early window appeared to show the self-cues dissociating from the remaining two categories, this was not supported statistically. Analysis of the late window revealed an enhanced P300 for self-ownership cues and forbidden cues relative to other-ownership cues, a finding consistent with the first and second experiments as well as Turk et al. (2011) since P300 amplitude is greater when self-referencing is engaged. Taking the N2 and P300 findings together, it appears ?forbidden? is indeed distinct from ?self-owned?, and further, can be distinguished more quickly than ownership category. Nevertheless, commonality between these conditions was manifest in the P300, a frequent indicator of self-referent processing.   What explains the dissociation of ?forbidden? from the other ownership categories at the N2? One possibility is that it could signify a greater emotional response. Being told we cannot have something, even if it is not something particularly fascinating or desirable, may feel threatening or objectionable. Enhanced negativity in the 200-300 ms time window has been found when participants read emotional relative to neutral words (Kissler, Herbert, Peyk, & Junghofer, 2007; Herbert, Pauli, & Herbert, 2011) or see negatively emotional pictures relative to neutral pictures (Ma, Wang, Wang, Wang, & Wang, 2010). Early posterior negativity was also found when emotional words were presented during a grammatical decision task, suggesting incidental and automatic encoding of valence (Kissler, Herbert, Winkler, & Junghofer, 2009). 	 ? 32	 ?Pre-P300 negativity has been shown to be particularly sensitive to negative stimuli. Balconi and Pozzoli (2012) demonstrated the N2 is greater when viewing angry faces compared to neutral and happy faces. There may even be degree-dependent modulation of the N2 for unpleasant pictures (Yuan et al., 2012). The forbidden cue may thus evoke a rapid negative emotional response before ownership or self-relevance is processed.   Although we found a functional dissociation between the N2 and P300 in terms of how the different ownership conditions affected the two components, previous research has suggested that these components may reflect a common set of underlying processes (Folstein & van Petten, 2008).  To examine this possibility in the current data, and to provide additional insight into the shared vs. distinct neurocognitive aspects of our three ownership conditions, we plotted the scalp topographies of each component (N2, early P300 and late P300) as a function of condition (Figure 4.2). Specifically, the mean voltage measurements within each of the three time windows analyzed above were converted into topographic maps by means of a spherical spline interpolation algorithm (Perrin, Pernier, Bertrand, & Echallier, 1989). Visual inspection of these topographies support two general conclusions.  First, although the absolute voltage values change within each ownership condition, the topographic distribution of voltage minima and maxima remain relatively consistent across the three ERP time windows.  As such, this would be consistent with a common set of ERP-generating dipoles for the N2 and P300 data within each condition.  Second, although all topography plots show a voltage maxima at or near the midline parietal locations analyzed in the ERP waveforms, there were additional topographic features that clearly dissociate between conditions.  The "mine" and "forbidden" conditions shared a left occipital/temporal maxima that was absent in the "other" condition.  Likewise, over the right 	 ? 33	 ?central/frontal scalp sites there was a maxima in the "mine" condition and a minima in the "other" condition, with no corresponding feature in the "forbidden" condition.  This not only supports our conclusion that self and self-forbidden objects share certain neurocognitive features as discussed below, but that self-forbidden are nevertheless qualitatively distinct in terms of how we process them neurally.  	 ? 34	 ?Chapter 5: Conclusion Over the course of three experiments, I examined memorial and event-related potential changes relating to the psychological concept of ?forbidden? objects. In the first two experiments, I found evidence that objects labeled as forbidden to oneself are later recognized as well as objects labeled as self-owned (i.e., ?mine), whereas objects labeled as forbidden to everyone are later recognized significantly less, producing recognition rates equivalent to those for objects labeled as other-owned (i.e., ?not mine? or ?other?). A third experiment revealed greater amplitudes for self-owned and forbidden but not other-owned objects for a waveform widely associated with self-relevance. It also demonstrated the forbidden category was distinguished from the mine/other categories at the N2 component, a waveform linked with emotional stimuli.   5.1 Strengths and limitations  How do the current results advance our understanding of ownership? While previous research has focused on the numerous biases in favor of self-owned objects, the current studies highlight the importance of considering objects that lie outside of self-ownership. Belk (1988) argued that our possessions are extensions of ourselves and this notion that objects are not just things but clues to our very identities. Taking the current findings as evidence that forbidden objects engage self-referential processing similarly to self-owned objects, this may suggest objects reflect not just who we are but also who we cannot be. Furthermore, singling out objects as not simply un-owned but unable to be owned defies the mine/other dichotomy and, as our ERP data implies, triggers an emotional response.  Forbidden objects show that ownership is 	 ? 35	 ?more complex than a two-fold choice and that objects outside self-ownership can hold varying degrees of self-relevance.  I postulated that the relationship an object has with the self, or perhaps the relationship the self has with an object, influences how much attention is allotted to that object and consequently impacts how strongly the representation of that object is encoded in memory. While this argument is not a new one, the current work sought to expand on it by hypothesizing that an object that was not self-owned could still exhibit this relationship. In so far as self-referential encoding and recognition memory for forbidden objects positively covaried from Experiment 1 to Experiment 2, this postulation was supported and was further reinforced by our ERP evidence in Experiment 3. That such a relationship between a non-owned object and the self could be established at the moment of person-object introduction implies that the ?mere ownership? effect could be generalized to exist as a ?mere self-relevance? effect. To wit, the apple that cannot be mine is just as ?me? as if it were my own.    Returning to the theory of reactance, I found that the limitation of choice, through the inclusion of a forbidden category, only enhanced subsequent recognition performance when the description of the category made specific reference to the individual. When it explicitly applied to the general population, forbidden objects did not show a memory bias. While these results provide evidence for a self-reference effect in the cognitive processing of ?forbidden,? there may be a number of reasons why reactance alone did not prove to be a stronger influence. The first reason is the threat to choice may have been too small: the stimulus set contained everyday objects that were not (definitively) monetarily or sentimentally valuable to the participant and the 	 ? 36	 ?degree of reactance has been found to modulate with subjective value (Wortman & Brehm, 1975). Another reason is that I did not show the process of choice limitation. The experimental design was a sorting task in which the ownership category was given almost simultaneously with the stimulus. In this case, participants did not have opportunity to interact with an object before they were told they could not have it. Thus, it would have been unlikely that they felt strongly about having an object be forbidden. A third reason is that the issue of choice only came up for the forbidden category since the other two categories (mine and other) did not involve choosing. Choosing which objects belong to the self and which belong to others magnifies the self-ownership effect (Cunningham et al., 2011) and using a paradigm that involved the participant selecting their owned objects but not being allowed to select a certain subset of stimuli would have heightened the aspect of choice in the experiment. Although not a reason for why reactance without self-reference did not generate a memory bias, it is important to note the current work did not measure reactance in any way. It may have been the participants in Experiment 1 felt greater reactance than those in Experiment 2, independent of feelings of self-relevance. This is unlikely since the manipulations in Experiments 1 and 2 were parallel in every way besides self-specificity, but it is possible.   5.2 Connections to extant research The current results appear to be consistent with theoretically similar constructs such as thought suppression and social exclusion. Made prominent by Wegner et al. (1987), the attempt to suppress certain ?target? thoughts (most famously: a white bear) does not lead to a successful reduction in those thoughts but rather a surge of target thoughts during and/or after the period of suppression (for a review, see Wenzlaff & Wegner, 2000). From this perspective, the target 	 ? 37	 ?thought is construed as forbidden but cognitively surfaces frequently. Likewise, the presentation of a forbidden object increases rather than decreases attention to said object.   Relatedly, despite the absence of an explicit induction of negative emotion, the ERP results closely mirror neuroimaging work on social exclusion (e.g., Otten & Jonas, 2012). One common paradigm used for social exclusion research is the ?Cyberball? game. In this paradigm, a participant is told he or she will play an online game of ?catch? with other online players. The other online players are not other participants but rather virtual confederates whose ball-tossing behavior the experimenter manipulates. During the game, the participant passes the ball to the other players and the players pass the ball to the participant as well as to each other. At a certain point in the game, the other players stop throwing the ball to the participant for several consecutive trials and only throw to each other, thus inducing an experience of social exclusion or ostracism (Williams & Jarvis, 2006). Event-related potentials recorded during modified Cyberball manipulations show N2 as well as P300 modulations (Gutz, K?pper, Renneberg, & Niedeggen, 2011; Themanson, Khatcherian, Ball & Rosen, 2012). Specifically, when participants are temporarily excluded from play during a game of virtual ?catch?, N2 and P300 amplitudes significantly increase. In this respect, the current research and the Cyberball paradigm both utilize an externally-imposed ?forbidden? aspect to owning or exercising agency over the ball. Consequently, both may be eliciting negative affect and feelings of self-relevance (i.e., being singled out).   In comparing the current research with previous work on forbidden objects, it is interesting to note the methodological differences between warning label studies and the present 	 ? 38	 ?studies. For the former, labels specified an outstanding attribute of the forbidden objects (e.g., a video game was particularly violent) and/or the consequences of owning the forbidden option (e.g., ?fatty cream cheese will increase your risk of heart disease?), while the latter did not mention special qualities about the forbidden objects at all. Despite not having these distinguishing features, forbidden objects in the present studies were still recognized as well as self-owned objects.  This is consistent with Brehm et al.?s (1966) study showing a middle-ranked music record was subsequently rated more attractive when it was forbidden. It also suggests the forbidden label alone is sufficient for increased processing.   5.3 Future directions  Moving forward, it is critical to consider potential moderators to the forbidden effect, including various individual differences between participants and the psychological qualities of the objects. For example, certain cultural groups do not express the self-referencing effect as strongly and therefore may not exhibit typical ownership effects or the forbidden effect. Maddux et al. (2010) examined the endowment effect in East Asians, Asian Americans, and Americans of European descent. While European Americans replicated the typical endowment effect, East Asians and Asian Americans showed a significantly reduced gap between willingness to pay and willingness to accept. A follow-up study used priming in Chinese participants to manipulate self-construal (independent versus interdependent) and found the endowment effect was bigger when individuals were primed to think about themselves as independent and unique and that it was smaller (compared to no priming) when they were primed to think about themselves as part of a group. These findings suggest that ?self?-driven effects can be affected by the context in which the self is considered. Jonas et al. (2009) argue even reactance is dependent on cultural 	 ? 39	 ?differences in of whose freedoms or choices are threatened (the individual?s or the collective group). As such, similar priming manipulations might also reduce the memory advantage for self-owned and forbidden objects.    The objects in a stimulus set may themselves affect the degree to which the forbidden effect is observed. As mentioned previously, manipulations of subjective or objective value may affect the strength of stimulus encoding. Item valence has shown to moderate the endowment effect (Brenner, Rottenstreich, Sood & Bilgin, 2007) and may also play a role in attention towards objects and their ownership categories. Furthermore, evidence from the present experiments and other neuroimaging work (Kensinger, 2007; Steinmetz & Kensinger, 2009) indicate negative or arousing stimuli may increase memory accuracy. A stimulus set comprised completely of unattractive or emotionally arousing objects might erase categorical differences in memory.   In conclusion, when considered relative to objects of other ownership categories, forbidden objects are recognized as much as self-owned objects and more than other-owned objects but not when the forbidden category is explicitly described to apply to everyone. Event-related potentials associated with the forbidden category show mean amplitudes for the P300 equal to that for the self-ownership category and greater than those for the other-ownership category, echoing the role of self-relevance. However, greater N2 amplitudes for the forbidden category only point towards a dissociation of ?forbidden? from the classic mine/other ownership dichotomy. Future research should investigate other factors relevant to this effect.  	 ? 40	 ?References Ashby, N. J. S., Dickert, S., & Gl?ckner, A. (2012). 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