CALIFORNIA STATE UNIVERSITY, NORTHRIDGE

AN EVENT RELATED POTENTIAL EXAMINATION OF FACIAL AFFECT

PROCESSING IN PERSONS WITH SCHIZOTYPY

A thesis submitted in partial fulfillment of the requirements For the degree of Master of Arts in Psychology, Clinical Psychology

By

Jaime Morales

August 2016

The thesis of Jaime Morales is approved:

______Jose P. Abara, Ph.D. Date

______Gary S. Katz, Ph.D. Date

______Mark J. Sergi, Ph.D., Chair Date

California State University, Northridge

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Dedication

For my parents, whose strong work ethic has been a prime example to live by and whose constant support has helped me throughout my life. And for my sister, whose strength and unrelenting perseverance has laid down a path for me to follow.

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Acknowledgement

I would like to thank the following people from the Neuroscience Lab for all their hard work and assistance with the process of this project: Sharis Sarkissians and Theresa Trieu for their assistance in all aspects of EEG data analysis, and Solange Petrosspour for testing of participants.

I would also like to thank my committee members without whose support this thesis would not be possible. I am honored to know each and every one of them.

To my chair, Dr. Mark Sergi, for taking the time to edit my thesis and having the patience to continue supporting my work. Your expertise have helped me in my understanding of all constructs of this thesis. As my mentor and advisor, your expertise in social cognition and schizophrenia have inspired me to follow a similar career path. It has validated my career choices in clinical psychology, research in schizophrenia, and academia.

To Dr. Jose Abara, for all the support and guidance in EEG and the statistical analysis of this study. Your unrelenting dedication to your students is inspiring and one day I hope to follow such mentorship. Your expertise have influenced my journey as a graduate student and led me to greatly appreciate the neuroscientific perspectives of mental disorders.

To Dr. Gary Katz, for all the expert insight and guidance which have brought up interesting factors associated with this thesis. Through your practicum and classes I have learned a great amount about what it takes to succeed in the field of clinical psychology.

Your expertise and passion in the clinical field have set an example for me to follow.

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Table of Contents

Signature Page ii

Dedication iii

Acknowledgement iv

List of Tables vii

List of Figures viii

Abstract ix

Introduction 1

Schizophrenia and Schizotypy 1

Social Cognition 3

Social Cognition in Schizophrenia and Schizotypy 5

Facial Affect Recognition in Schizotypy 10

Electroencephalography 12

Facial Affect Recognition and ERPs in Schizophrenia and Schizotypy 15

Research Questions and Expected Findings 18

Methods 20

Participants 20

Procedure 20

EEG Processing and Analysis 22

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Statistical Analysis 23

Results 25

Discussion 31

Summary of Findings 31

Limitations and Future Research 33

References 37

Appendix A: Schizotypal Personality Questionnaire - Brief 51

Appendix B: Examples of Stimuli Images 53

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List of Tables

1 . Mean N170 amplitudes in microvolts (μV) across Groups, Emotion, and Lead 27

2 . Mean N170 amplitudes in microvolts (μV) across Groups, Emotion, and Lead 27

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List of Figures

1 . N170 and N250 amplitudes for Schizotypy and Control. 25

2 . Grand average waveforms for Schizotypy and Control. 26

3 . The amplitudes for N170 across Leads. 28

4 . The amplitudes for N250 across Emotions. 29

5 . The amplitudes for N250 across Leads. 30

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Abstract

AN EVENT RELATED POTENTIAL EXAMINATION OF FACIAL AFFECT

PROCESSING IN PERSONS WITH SCHIZOTYPY

By

Jaime Morales

Masters of Arts in Psychology, Clinical Psychology

Deficits in facial affect recognition have been widely investigated in schizophrenia. Their performance on facial affect recognition tasks have shown an apparent deficit in social cognitive processing, specifically on fear and neutral emotions.

It is still unclear if these impairments reflect a trait-like vulnerability for schizophrenia.

Investigators hoping to uncover a core deficit of schizophrenia spectrum disorders have highly valued utilization of the schizotypy population. Schizotypy is conceptualized as a subclinical manifestation of the same biological factors that give rise to schizophrenia and other schizophrenia spectrum disorders. Schizotypy provides a useful construct for understanding the development of schizophrenia spectrum disorders as it is dimensional and involves similar but lesser symptoms and dysfunction. Electroencephalography can advance our understanding of the neuronal processes involved in emotion recognition deficits of persons with schizophrenia or schizotypy, as this technology can identify deficits in both early facial structural encoding and the later facial affect decoding.

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The current study examined early structural encoding and facial affect decoding using electroencephalography methods during a continuous performance task (CPT). 20 participants high in schizotypy and 20 participants low in schizotypy were identified from a screening of over 1,200 undergraduate students at California State University,

Northridge. Event-related potentials (ERPs) were evaluated during a CPT involving facial affect recognition. Amplitudes for the facial structural encoding N170 and facial affect decoding N250 ERP components were captured and analyzed at the frontal, central, and posterior sites, specifically for fear and neutral facial expressions.

There were no significant differences between controls and schizotypes on N170 and N250 ERP amplitudes. N170 amplitudes followed the same topographical distribution for both groups, displaying greater negativity at the central site. Although this finding is unexpected, what is most interesting is that the greatest attenuation was at the parietal site for both groups. Also, N250 amplitudes followed the same topographical distribution for both groups, displaying greater negativity at the frontal and central sites.

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Introduction Schizophrenia and Schizotypy

Schizophrenia is a debilitating disorder which affects approximately 0.3%-0.7% of the U.S. population (American Psychiatric Association, 2013). Schizophrenia is a severe and chronic mental disorder characterized by dysfunctions in cognition, behavior, and emotion. Disturbances affect work performance, interpersonal relations, and self- care, which tend to be considerably below expected levels of achievement. These impairments often hinder a person’s ability to live independently.

Symptomology can be separated into three categories: positive, negative, and cognitive (American Psychiatric Association, 2013; National Institute of Mental Health.

2015). Positive symptoms include delusions, hallucinations, disorganized speech, and grossly disorganized or abnormal motor behavior. Negative symptoms involve diminished emotional expression, avolition (decreased motivation), alogia (diminished speech output), anhedonia (decreased ability to experience pleasure), and asociality (lack of interest in social interactions). Cognitive deficits are common and strongly linked to professional and functional impairment. Deficits in cognition are present in declarative memory, working memory, executive functioning, and attention (American Psychiatric

Association, 2013).

Persons with schizophrenia will have varied symptomology as this disorder is a heterogeneous clinical syndrome. Variation in the presentation of the disorder has brought upon a consensus that the disorder lies on a spectrum rather than a category of psychopathology (Asai, Yamauchi, Sugimori, Bando, & Tanno, 2010; Claridge, 1997;

Johns, & van Os, 2001; van Os, Hanssen, Bijl, & Ravelli, 2000; Verdoux, & van Os,

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2002). From a dimensional view of schizophrenia, deficits are likely to underlie the various levels of the spectrum and those who are susceptible to developing schizophrenia.

Schizotypy is considered a subclinical manifestation of the same etiological factors that give rise to schizophrenia and other schizophrenia spectrum disorders

(Barrantes-Vidal, Grant, & Kwapil, 2015; Lenzenweger, 2006a; Lenzenweger, 2011;

Meehl, 1962; Meehl, 1990). Schizotypy seems to follow the same three factor model of symptomology that organizes schizophrenia, including positive, negative, and cognitive symptoms (Vollema & Hoijtink, 2000; Vollema & van den Bosch, 1995). Schizotypy was made known to represent the inherited susceptibility to schizophrenia spectrum disorders expressed as a multidimensional personality structure (Barrantes-Vidal, et al.,

2015). According to Meehl, four primary symptoms are observed in schizotypy: mild associative loosening or cognitive slippage, interpersonal aversiveness or social fear, anhedonia, and ambivalence (Meehl, 1962; Meehl, 1990). In addition, social withdrawal, flat affect (Chapman, Chapman, Raulin, 1976), unusual sensory experiences, magical ideation, perceptual aberration, and referential thinking (Lenzenweger, 2006b), have been included in the characterization of schizotypy.

It is important to note that Meehl's model says that schizotypy, as a personality continuum, can manifest itself behaviorally and psychologically in various degrees of clinical symptomology (Lenzenweger, 1994). In other words, not all schizotypes will develop schizophrenia or schizophrenia spectrum disorders, but all schizotypes will display some evidence of their susceptibility in the form of some atypical psychological or psychobiological functioning. Even so, susceptibility to develop schizophrenia is much higher within the schizotypy population when compared to the general population

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(Barrantes-Vidal et al., 2015; Kendler, Thacker, & Walsh, 1996; Kwapil, Gross, Silvia, &

Barrantes-Vidal, 2013).

Persons with schizotypy may be identified utilizing psychometric questionnaires and therefore are considered “psychometric schizotypes” when elevated scores are present. The current study utilizes subjects from a pool of normal college students who scored high on a self-report inventory and thus are considered “psychometric schizotypes.” Studying schizotypy populations offers valuable information about the core features of schizophrenia as many confounds associated with schizophrenia research such as medication effects, social isolation, chronic hospitalization, and generalized cognitive deficits are not factors in the lives of persons with schizotypy.

Social Cognition

Apart from the symptomology found in the diagnostic criteria for schizophrenia spectrum disorders, there are also apparent deficits in social cognition. The term, social cognition, originated during the cognitive revolution of the 1960s and early 1970s within social psychologists (Penn, Sanna, & Roberts, 2008). The social cognition construct provides a general theoretical perspective that focuses on how people process information within social contexts. Social cognition occurs at the automatic and controlled levels of processing, and is influenced by motivational biases (Beer, & Ochsner, 2006). Social cognitive processes are used to decode and encode the social world. Simply put, it is the ability to construct representations of relationships between oneself and others, and to use those representations constructively to guide social interactions (Horan, Kern, Green, &

Penn, 2008). These social interactions are influenced by the ability to perceive, interpret,

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and generate responses to the intentions, personal temperament, and behaviors of others

(Green et al., 2008; McCleery et al., 2012).

Social cognition is a multi-dimensional construct that is typically broken down into five domains: theory of mind (ToM), social perception, social knowledge, attributional bias, and emotional processing (Bellack et al., 2007; Fett et al., 2011; Green et al., 2008; Penn et al., 2008). Theory of mind, also called mental state attribution, is the ability to understand that other people have mental states that differ from one’s own and to make correct presumptions about the manner of those mental states. This includes the understanding of false beliefs, intentions, humor, hints, deceptions, metaphors, irony, and blunders. (Baron-Cohen, Wheelwright, Hill, Raste, & Plumb, 2001; Frith, 2004; Brüne,

2005; Penn et al, 2008). Social perception is the ability to judge and understand social roles, social context, and societal rules. This includes relationship perception, which is the perception of the nature of relationships between people (Corrigan, Wallace, &

Green, 1992; Corrigan, & Green, 1993; Penn, Ritchie, Francis, Combs, & Martin, 2002;

Toomey, Schuldberg, Corrigan, & Green, 2002). Social knowledge, also referred as social schema, is one’s awareness of the roles, rules, and goals that characterize social situations to identify social cues (Corrigan, et al., 1992; Corrigan, & Green, 1993; Green et al., 2008). Attributional bias, also known as personalization bias, refers to how people explain the causes of positive and negative events (Green et al., 2005; Horan et al., 2008).

In general, positive events are attributed to oneself and negative events are attributed to others. Emotional processing refers to the use and perception of emotions. A key model by Mayer and colleagues, proposes a four-piece component model for emotional processing: composed of both emotional skills and cognition (Mayer, Salovey, Caruso, &

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Sitarenios, 2001; Green, et al., 2008; Horan, et al. 2008). The component model includes identification of emotions, facilitation of emotions, understanding of emotions, and management of emotions. Identifying emotions can be observed when trying to identify emotional expressions in faces and pictures. Facilitating emotions involves evaluating the usefulness of different emotions that are best suited for specific cognitive tasks and behaviors. Understanding emotions refers to the understanding of blends and moment to moment changes within emotions. Lastly, managing emotions examines the regulation of emotions within oneself and in relationships with others (Goldsmith, & Davidson, 2004;

Green, et al., 2005).

Social Cognition in Schizophrenia and Schizotypy

Schizophrenia patients show substantial deficits in several aspects of social cognition (Horan et al., 2008). Social cognitive deficits occur early in the illness, are stable across phases, and are predictive of functional outcome. There have been 4 distinct goals of social cognitive research in schizophrenia: one line of research focuses on social cognition and its relation to the development of specific clinical symptoms of schizophrenia; another line investigates social cognition's role in explaining functional outcome differences in schizophrenia; third, researchers hope to determine if social cognitive impairments are stable characterizations in schizophrenia or whether they fluctuate across time periods; lastly, researchers plan to investigate the use of social cognitive constructs to identify neural substrates that are potentially distinct from those of non-social cognitive domains (Green, et al., 2008; Green, Olivier, Crawley, Penn, &

Silverstein, 2005).

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Indeed, social cognitive deficits appear to be key determinants of functional outcome, including social and vocational outcome in schizophrenia (Kee, Green, Mintz,

& Brekke, 2003; Green, et al., 2005). These can be apparent in everyday functioning during independent living, interpersonal relationships, work functioning, and leisure time

(Couture, Penn, & Roberts, 2006; Flashman, & Green, 2004; Harvey, Green, Keefe, &

Velligan, 2004). Consequently, deficits in particular areas of social cognition will lead to social misperceptions, unexpected reactions to and from other persons, and ultimately social withdrawal (Green, et al., 2005; Penn et al., 2008). This provides a strong rationale for the need of intervention techniques at the social cognitive level. It is believed that social functioning can be improved if interventions are applied (Horan et al., 2008), and that both pharmacological and psychosocial interventions are included in treatment plan

(Green et al., 2008).

The social cognitive impairment in schizophrenia is associated with, but separate from, impairments in non-social cognition. Also, social cognition likely serves as a mediator between neurocognition and social functioning outcome (Addington, Saeedi, &

Addington, 2006a; Brekke, Kay, Lee, & Green, 2005; Sergi, Rassovsky, Nuechterlein, &

Green, 2006; Vaskinn et al., 2008), while also influencing social competence (Kalin et al., 2015). For all of these reasons, research in social cognition is highly valuable.

A number of studies have found that persons with schizophrenia perform significantly poorer on Theory of Mind (ToM) tasks when compared to controls (Frith,

2004; Harrington, Siegert, & McClure, 2005). Impairments in ToM have been demonstrated in early-onset schizophrenia, patients in remission, and apparent in first

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degree relatives of schizophrenic patients (Bora, Yücel, & Pantelis, 2009; Harrington, et al., 2005; Martin, Robinson, Dzafic, Reutens, & Mowry 2014). Numerous studies have reported links between impairments in ToM, neurocognition, negative symptoms, and deficits in functional outcome in schizophrenia patients (Brüne, 2005; Ventura et al.,

2015).

Difficulties in social perception and social knowledge have been associated with both poor community functioning (Fett, Viechtbauer et al., 2011; Savla, Vella,

Armstrong, Penn, & Twamley, 2013; Toomey, Wallace, Corrigan, Schuldberg, & Green,

1997), and cognitive impairment (Sergi, & Green, 2003; Wynn, Sergi, Dawson, Schell, &

Green, 2005). People with a longer duration of schizophrenia had greater deficits in social perception, which in turn were associated with inpatient status (Savla, et al., 2013).

In addition, Addington, Saeedi, and Addington (2006b), found that social perception and social knowledge, when combined, acted as a mediator of the relationship between cognition and interpersonal problem solving.

Attributional bias has been researched mostly in the context of patients who have paranoid or persecutory delusions (Harris, Oakley, & Picchioni, 2014). It’s been found that patients with persecutory delusions tend to attribute negative outcomes to others rather than to situational contexts. This has been termed a “personalizing bias” (Bentall,

Corcoran, Howard, Blackwood, & Kinderman, 2001). Results have also suggested an association between hostile attribution biases and violence in schizophrenia (Combs,

Penn, Wicher, & Waldheter, 2007).

Emotion processing has been the most extensively researched domain within social cognition and schizophrenia. Generally, individuals with schizophrenia exhibit

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impaired emotion perception, reduced self-reported positive experiences, impaired emotion regulation, and reduced emotion expression (Kohler, & Martin, 2006; Kohler,

Walker, Martin, Healey, & Moberg, 2010; Kring, 1999; Phillips, & Seidman, 2008).

Also, emotional processing is found to be associated with social problem solving and social functioning in schizophrenia (Fett, et al., 2011; Irani, Seligman, Kamath, Kohler,

& Gur, 2012; Maat et al., 2015). Of the four components that make up emotional processing (discussed earlier), emotion perception is the most widely studied component.

Emotion perception, also known as affect recognition, is an instrumental factor of nonverbal communication. Several studies in schizophrenia have suggested that emotion perception abilities are related to social competence and social functioning (Hooker, &

Park, 2002; Koeler, et al., 2010; Penn et al., 2000). Affect recognition impairments have been observed when persons with schizophrenia attempt to decode facial expressions

(Edwards, Jackson, & Pattison, 2002; Penn et al., 2000) and tone of voice (Bozikas et al.,

2006; Jahshan, Wynn, & Green, 2013). The extent and nature of the deficits in emotion recognition are still ambiguous (Edwards, et al., 2002; Trémeau, 2006). Impairments seem to primarily affect the ability to name and discriminate facial expressions (Penn, et al., 2000). Data has varied, but studies have found that patients with schizophrenia have performed worse at recognizing fear (Kohler et al., 2003; van't Wout et al., 2007), anger, sadness, and disgust (Barkhof, Sonneville, Meijer, & Haan, 2015; Edwards, Pattison,

Jackson, & Wales, 2001).

Impairments in affect recognition are found early in patients, usually during first episodes and are relatively stable over time: whether they be during acute psychosis or periods of remission (Streit, Wölwer, & Gaebel, 1997). Also, it has been found that

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siblings of patients with schizophrenia show impaired emotion recognition (Allott et al.,

2015; Erol, Mete, Sonmez, & Unal, 2010). This may suggest that emotion recognition is a heritable characteristic of schizophrenia.

People with schizotypy also evidence impairments in social cognition. However, the literature focusing on individuals with schizotypy have produced inconsistent results.

Higher schizotypy has been associated with poorer social functioning (Henry, Bailey, &

Rendell, 2008; Jahshan, & Sergi, 2007). Three aspects of social functioning have been found to be impaired: peer relationships, family relationships, and academic functioning

(Aguirre, Sergi, & Levy, 2008). Previous studies have suggested that persons with schizotypy have deficits in theory of mind, which may be associated with positive symptoms such as hallucination and delusion-like experiences (Barragan, Laurens,

Navarro, & Obiols, 2011; Gooding, & Pflum, 2011; Pflum, Gooding, & White, 2013). In contrast, a couple of studies have found no relation between schizotypy and theory of mind (Fernyhough, Jones, Whittle, Waterhouse, & Bentall, 2008; Jahshan, & Sergi,

2007). According to Holst (2005), there is no apparent deficit in social perception. One study found that attributions of people with schizotypy are more external, global, and stable for negative events while being more internal for positive events: as seen in schizophrenia (Mohammadzadeh, & Karimi, 2009).

Emotion perception is also the most widely researched area of social cognition in schizotypy. Persons with schizotypy are deficient in emotional intelligence (Aguirre,

Sergi, and Levy 2008). They have difficulties identifying and interpreting their own emotions, experience more negative emotions, experience less positive emotions, have trouble managing emotions, and lack the ability to utilize emotions (Berenbaum et al.,

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2006; Giakoumaki, 2016; Kerns, 2005). Although the literature on emotion recognition is not all in concordance, facial affect recognition is a growing field of emotion perception among schizotypy researchers, and the subject of this study.

Facial Affect Recognition in Schizotypy

Research on deficits in facial affect recognition in schizotypy is a growing field riddled with conflicting findings. Only a few studies have shown no relation between schizotypy and emotion recognition (Alfimova et al., 2009; Bell,& Halligan, 2015;

Toomey, & Schuldberg, 1995). The majority of studies have produced results suggesting emotion recognition deficits in schizotypes (Dickey et al., 2011), but vary on a wide array of components. Abbott and Green (2013), showed that the cognitive and disorganized factors of schizotypy, as observed in the Schizotypal Personality Questionnaire (SPQ), were not associated with affect recognition. However, the interpersonal factor, specifically the social anxiety component of the SPQ, did show significant reduction in affect recognition accuracy. This suggests that deficits in emotion recognition may be due to a vulnerability in interpersonal communication difficulties, as seen in schizophrenia. In contrast, another study found isolated perceptual aberration as a possible link to deficits in emotion recognition (Lee et al., 2015).

The literature has also looked at how the positive, negative, and disorganized symptoms in schizotypy mediate deficiencies. The salience of specific emotions are also observed. Individuals with negative symptoms in schizotypy have demonstrated reduced facial affect recognition and discrimination (Morrison, Brown, & Cohen, 2013), particularly with negative facial emotions (Kaplan, Rossell, 2014; Williams, Henry, &

Green, 2007). This suggests that facial affect recognition may be impaired across the

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schizophrenia spectrum. This also suggests that these deficits may be associated with the predisposition for negative symptoms of schizophrenia. In contrast, a couple of studies have shown opposing results with positive schizotypy being associated with emotion recognition (Abbott, & Byrne, 2013; Kerns, 2005). Abbott and Byrne (2013) noted that although negative schizotypy was not associated with emotion recognition overall, it was associated with errors in recognizing positive emotions. To add more ambiguity, another study found deficits in facial affect recognition in both positive and negative emotions

(sad and happy) (Mikhailova, Vladimirova, Iznak, Tsusulkovskaya, & Sushko, 1996).

It’s important to note that comorbidity with major depression may have been the underlying trait in deficits of emotion recognition. Interestingly, a couple of studies have shown that schizotypes tend to label neutral faces more negatively (Brown, & Cohen,

2010; van Rijn et al., 2011). Van Rijn, et al. (2011) suggested that persons at risk for psychosis may have the tendency to identify ambiguous stimuli as being ominous, similar to schizophrenia patients. Milkhailova, et al. (1996), noted that deficits were associated with dysfunction in the left hemisphere of the brain, as is observed in schizophrenia.

Going along the lines, Coy and Hutton (2013) found that schizotypes have increased right hemisphere activation during facial affect recognition tasks.

It is apparent that deficits in facial affect recognition are present in persons with schizophrenia. The debate is whether impairment is a specific deficit in emotion perception, or if the deficit in emotion perception is secondary to a generalized impairment in facial processing. Several studies have found evidence for a general facial recognition deficit (Norton, McBain, Holt, Ongur, and Chen 2009; Hooker & Park, 2002;

Kohler, Bilker, Hagendoorn, Gur, & Gur, 2000). However, other studies have found

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evidence for impairments in recognition of specific facial emotional expressions, where deficits are restricted to emotion perception with intact facial recognition (Edwards et al.,

2001; Shaw et al., 1999).

The past couple of decades have seen a rise in literature showing that persons with schizophrenia exhibit a physiological abnormality in early visual processing. Studies utilizing electroencephalography suggest a fundamental deficit in schizophrenia for the structural encoding and perceptual decoding of facial features (Herrmann, Eligring, &

Faligatter, 2004; McCleery et al., 2015; Turetsky et al., 2007). It is suggested that facial affect recognition deficits are the secondary or downstream result of earlier deficits in facial processing. Although there aren’t many schizotypy studies evaluating deficits in the encoding and decoding of facial features, the few that exist have shown promise that deficits are present. This study hopes to add to the literature.

Electroencephalography

Studies are starting to explore the neuronal bases of social cognition deficits in schizophrenia and schizotypy. Electroencephalography (EEG) methods use electrodes placed on the scalp to measure electrical activity generated by the changes in voltage from neuronal networks in the brain. The electrical currents measured are results of inhibitory and excitatory post-synaptic potentials of cortical neurons (Frodl-Bauch,

Bottlender, & Hegerl, 1999). The EEG method is advantageous for measuring cognitive processes because of its high temporal resolution. In comparison to fMRI procedures which record tens of times per minute, EEG records hundreds of events per second.

EEG recordings produce rhythmic sine waves that reflect fluctuations in voltage from neuronal network activations. These waves are described by their amplitudes, as

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measured by microvolts (μV). Voltage fluctuations are also characterized by their frequency or number of oscillations per second, as measured by hertz (Hz). Frequencies typically range from 1-70 Hz. This range of frequencies are broken down into four brain patterns: alpha, beta, theta, and delta. Alpha activity occurs between 8 and 13 Hz. It is most frequently observed at the posterior sites and recorded while individuals are resting.

It is also attenuated when individuals have their eyes open and when using attention and mental effort. Beta activity occurs between 13 and 35 Hz. It is observed when individuals are awake and attending to events in their environment or actively thinking. The beta rhythm is generally dependent upon normal cortical functioning and is typically lower than alpha rhythm. Theta activity occurs between 4 and 8 Hz. It’s sometimes observed during wakeful states, but is most commonly recorded during periods of drowsiness and lighter stages of sleep in adults. Finally, delta activity is observed in frequencies below 4

Hz and the signature characteristic of deep stages of sleep. It’s also the EEG frequency band with the highest amplitude.

Event-related potentials (ERPs) are averages of changes in electrical voltage in the continuous EEG recording. ERPs are time-locked to specific motor, sensory, and cognitive events (Donchin, 1984). Averaging voltage changes creates a recognizable waveform pattern. Due to the high temporal resolution of EEG, the use of ERPs help uncover changes in cognitive activity around time frames of behavioral response. It also captures the lack of response. Different ERP components are related to unique cognitive processes, as required by specific tasks (Spencer, Dien, & Donchin, 1999). These components help in the explanation of the underlying cognitive processes that are required to complete a task. The various ERP components are characterized by their 1)

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amplitude peaks (either positive or negative) of waveforms in μV, 2) latency of peaks after presentation of the stimulus in ms, and 3) topographical distribution of ERP amplitudes across the scalp. Two ERP components in particular, the N170 and the N250, have been closely linked to facial processing.

The N170 reflects a negative component of the event-related potential (ERP) peaking at about 130-200 ms after stimulus presentation (Eimer, 2011; Hinojosa,

Mercado, & Carretié, 2015). The N170 is most pronounced over parieto-occipital temporal scalp regions with greater amplitude over the right hemisphere. Further, it is generated in the posterior fusiform gyrus (Rossion, Joyce, Cottrell, & Tarr, 2003). It also marks the earliest difference in amplitude between faces and non-facial stimuli

(Linkenkaer-Hansen, Palva , Sams , Hietanen, Aronen, 1998).

The N170 has been shown to be dominant for faces and eyes (Taylor, Itier,

Allison, & Edmonds, 2001), and is either reduced or absent in response to non-facial stimuli (Bentin, Allison, Puce, Perez, & McCarthy, 1996; Itier & Taylor, 2004). The larger N170 for faces, when compared to non-face stimuli, has lead researchers to suggest that the N170 may reflect a neuronal mechanism for detection of human faces (Bentin, et al., 1996; Iidaka, Matsumoto, Haneda, Okada, & Sadato, 2006). Also, Bentin et al. (1996) showed that the N170 is not only detected in upright faces, but also for isolated eyes or inverted faces. This suggests the N170 to be related to structural encoding processes and precedes identification (Bentin, & Deouell, 2000).

Studies have suggested that facial affect recognition are reflected primarily in later ERP components, after the N170 structural encoding stage (Ashley, Vuilleumier,

Swick, 2004). Facial affect recognition used to be thought to take place around 400-

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600ms after stimulus presentation (Turetsky, et al., 2007). Only recently has research found facial affect recognition ERPs to be much earlier in time after stimulus presentation. Studies have shown that affect recognition ERPs occur immediately following structural encoding, at around 180-250 ms (Marinkovic, & Halgren, 1998;

Streit et al., 1999; Streit et al., 2001). The N250, a negative waveform that peaks approximately 250 ms after stimulus presentation, appears to be associated with the decoding of facial expression. Unlike the N170, the N250 is consistently found to be modulated by stimulus properties such as affective content (Streit et al., 2001), index face familiarity (Pierce et al., 2011), and index stimulus repetition (Kaufmann,

Schweinberger, & Burton, 2009). Streit et al. (2001), found the N250 to be most pronounced in the frontocentral midline region and is thought to reflect the decoding of facial information, such as the recognition of intricate features of the face that are associated with gender or particular emotions.

Facial Affect Recognition and ERPs in Schizophrenia and Schizotypy

The literature has shown an apparent deficit in facial affect recognition. However, studies utilizing EEG procedures to examine the ERPs associated with deficits have only recently flourished. Literature on deficits in the N170 and N250 ERPs during facial affect recognition tasks is a growing field riddled with mixed results. Wynn, Lee, Horan, and

Green (2008), found that N170 amplitudes did not differ between controls and patients, and that N250 amplitude was smaller in patients. In contrast, another study found both

N170 and N250 amplitudes to be significantly smaller in patients when compared to controls (Wynn, Jahshan, Altshuler, Glahn, & Green, 2013). To further confuse the picture, Turetsky et al. (2007), showed group differences for N170 amplitudes, but not

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for the N250. It is not to say that the N170 and N250 are the only ERPs important for facial affect recognition. A recent study found lower P300 amplitudes for fear emotion, but not for the P100, N170, and N250. This may suggest that the ability of basic visual processing is preserved in schizophrenia, whereas facial affect processing is impaired in later ERPs (Tempesta et al., 2014). Turetsky et al. (2007) also noted P300 abnormalities, but suggested that the earlier N170 explained the variance.

However, McCleery et al. (2015), conducted a meta-analysis of the literature on facial affect recognition and ERPs in order to clear up inconsistencies and evaluate trends. The meta-analysis evaluated 21 studies on the N170 component and six on the

N250 component. Results showed an apparent and consistent trend for moderate impairment in N170 and N250 ERP amplitudes in schizophrenia. The study suggested the behavioral deficits observed for facial affect recognition in schizophrenia are reflected in an underlying neuronal impairment for processing faces. According to McCleery et al.

(2015), findings suggest that persons with schizophrenia exhibit impairments in the bottom-up neuronal processes associated with face processing. This, in turn, may contribute to the higher order processing impairments in interpretation of facial expressions.

Interestingly, Frommann, Stroth, Brinkmeyer, Wölwer, and Luckhaus (2013), utilized male inpatients with schizophrenia who had a history of hands-on violent offences. When compared to patients with schizophrenia who had no history of violence, the violent group significantly performed poorer on affect recognition, especially on neutral and fear emotions. Larger amplitudes were found on the N250 component in the

FC3 of the frontal cortex. Frommann et al. (2013), suggested that greater deficits in affect

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recognition in combination with higher salience and arousal may contribute to the occurrence of violent acts in patients with schizophrenia.

Studies in schizophrenia on N170 and N250 utilize non-emotional and emotional judgment tasks respectively (McCleery et al., 2015; Turetsky et al., 2007). That is, N250 emotion recognition tasks are mainly characterized by presentations of pictures of different emotional expressions. Participants are asked to perceive which emotion is being displayed and select from a list of emotions. Some studies require a verbal response

(Streit, Wölwer, Brinkmeyer, Ihl, & Gaebel, 2001) and some require a motor response

(Turetsky et al., 2007; Tempesta et al., 2014). In contrast, facial affect recognition studies on N170 in schizophrenia tend to use a target/non-target paradigm or rather Go/NoGo paradigm, like the oddball task (McCleery et al., 2015). The oddball task is an experimental design where presentations of sequences of repetitive audio and/or visual stimuli are infrequently interrupted by a deviant stimulus (Huettel, & McCarthy, 2004).

Participants are asked to respond to a target stimulus while inhibiting responses to the non-target stimuli or vice versa (Grunewald et al., 2015). This design requires attention control for targets and inhibition control to avoid non-targets. Deviant stimuli may be pictures of butterflies, houses, cars, and/or specific facial expressions (McCleery et al.,

2015).

Studies of persons with schizotypy, utilizing electroencephalography procedures, are infrequent, leading to a limited interpretation of results. Grabyan (2011) showed that schizotypes performed significantly worse than controls in identification of the emotion fear during a facial affect recognition task. There were no significant differences between groups on the N250 and N170, as observed by their ERP amplitudes. Although no other

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studies have been found on ERPs and affect recognition in schizotypy, congruences between schizotypy and schizophrenia research allows for a better understanding of the core features of the disorder and the vulnerability for developing psychosis. For example, several studies have shown reduced amplitudes in the P50 ERP component in schizotypy

(Cadenhead, Light, Geyer, & Braff, 2000; Croft, Lee, Bertolot, & Gruzelier, 2001; Wan,

Crawford, & Boutros, 2006). Reduced P50 amplitudes are also found in schizophrenia and suggest this deficit to be a potential trait marker for schizophrenia. The current study hopes to build a stronger basis for ERP studies in schizotypy, while adding to the growing literature on facial affect recognition and schizotypy.

Research Questions and Expected Findings

The literature has extensively examined deficits in emotion perception and schizophrenia. Their performance on affect recognition tasks have shown an apparent deficit in social cognitive processing. However, the lack of literature on facial affect recognition and schizotypy leaves many questions unanswered. Utilizing EEG procedures can advance the understanding of the neuronal processes associated with early facial structural encoding and the later facial affect decoding: which may be a potential trait status for emotion recognition as seen in schizophrenia and other schizophrenia spectrum disorders. Also, the literature in schizophrenia have primarily seen deficits in affect recognition of negative emotions and neutral faces. Findings in schizotypy would be expected to follow such patterns.

The first question addressed is whether there are group differences in the structural encoding N170 and affect decoding N250 ERP components between psychometric schizotypes and control participants. It is predicted that the N170 amplitude

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will be more attenuated in the schizotypy group, specifically for the negative emotion fear and for the neutral emotion. It is also predicted that the N250 amplitudes will be more attenuated in the schizotypy group, specifically for the negative emotion fear and for the neutral emotion. Also, it is hypothesized that the N170 ERP group differences will be most pronounced in the posterior site. Finally, it is predicted that the N250 ERP group differences will be most pronounced in the anterior site.

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Methods Participants

Participants were recruited from an undergraduate subject pool of the Psychology

Department at California State University, Northridge (CSUN). Approximately 1,200 undergraduate students were screened for schizotypy using the 22-item Schizotypal

Personality Questionnaire-Brief (SPQ-B; Raine & Benishay, 1995; see Appendix A).

Based on SPQ-B scores, potential participants were contacted via telephone to schedule a time and date to be included in this study. Those who scored a total of 15 or higher or who scored a zero or one were contacted. High scorers on the SPQ-B formed the schizotypy group and low scorers made up the control group. The sample for the current study consisted of 44 participants. Of those, 22 formed the schizotypy group and 22 formed the control group. Exclusionary criteria included: left-handedness, excessive drug or alcohol use, stroke, severe head injury, current history of seizures, or the presence of a skin or scalp condition such as psoriasis or hair weaves. In addition, participants using the following medications were excluded: diet pills, pain killers, anxiolytics, anti-psychotics, and Benadryl. Participants were asked to abstain from alcohol and drug use at least 24 hours prior to testing. They were asked to refrain from drinking caffeine two hours prior to testing. Participants were also asked to enter the study room with little, to no makeup and that their hair and scalp be clean and dry.

Procedure

All data was collected in the Neuroscience Laboratory in Monterey Hall at

CSUN. Testers were blind to the participant's schizotypy scores at the time of testing.

Once informed consent was obtained, participants were asked to turn off all electronic

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devices and to be seated for electrode placement. Electrodes were placed according to the

International 10-20 System of Electrode Placement at the following midline leads: Fz,

Cz, Pz, and Oz.

Reference electrodes were attached to the two earlobes and the ground electrode was placed in the middle of the forehead. Vertical (VEOG) and horizontal (HEOG) eye movements were measured using four facial electrodes. The VEOG and HEOG electrodes were placed around the eyebrows and temple area. Prior to testing, impedance levels were checked and maintained at or below 15 kΩ at all electrode leads.

Electroencephalograph data was recorded using a Nueroscan amplifier and Neuroscan

Acquire software 4.0. While electrodes were being placed, participants were asked to fill out the Revised Social Anhedonia Scale (RSAS) (Eckblad, Chapman, Chapman, &

Mishlove, 1982).

Following electrode placement, participants were seated in a cubicle free of distracting materials. Participants were situated approximately two to three feet in front of a computer screen. The lights were turned off, allowing only natural light to enter the testing area. Participants were asked to keep their mouths unclenched and to minimize their blinking in order to minimize noise in recordings. Each participant was then presented with three separate continuous performing tasks (CPTs), each lasting approximately 10-12 minutes. Recordings from the second CPT, a measure of emotion recognition and working memory, produced the data for the current study. The first CPT followed an A-X paradigm and presented letters as stimuli. The third CPT also used images of facial expression of emotions, but required a verbal response. Before and after each of the CPT conditions were conducted, the Stanford Sleepiness Scale (Hoddes,

21

Zarcone, Smythe, Phillips, & Dement, 1973) was given to assess the participant’s level of alertness. Between the three CPT conditions, participants completed questions from the

Social Adjustment Scale Self-Report (SAS-SR; Weissman, Prusoff, Thompson, Harding,

& Myers, 1978), a measure of social functioning.

In the second CPT condition, participants were presented with a series of facial photographs from Ekman and Friesen’s Pictures of Facial Affect set (Ekman, & Friesen,

1975). Facial expressions were presented individually on the computer screen for 500 ms with an inter-trial interval of 1600 ms. The seven facial emotions displayed as stimuli were: fear, happiness, neutrality, sadness, surprise, disgust, and anger. These images had an equal distribution of sex. 387 stimuli images were presented, which lasted 10 minutes and 24 seconds. Participants were asked to press a button with their right index finger when they evaluated the facial expression displayed in a current stimulus to be happy and the preceding stimulus to also be happy. This presentation of two consecutive happy stimuli is known as the target or Go event. When presented with the target event, participants would press the button as quickly and accurately as possible. The behavioral responses were not used in this study. Rather, the electroencephalography data in condition two is the primary subject of this study. EEG recordings for stimuli events, fear and neutral were isolated for the purpose of this study. 36 events for fear emotion and 35 events for neutral emotion were used in this study. The EEG recordings for the other five emotions were not used.

EEG Processing and Analysis

Electrophysiological data was recorded and filtered within a frequency range: 0.1-

100 Hz. EEG data was filtered with a high pass of 0.3 Hz and a low pass of 25 Hz.

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Vertical and horizontal eye movements were also recorded. Trials from scalp leads were rejected if outside of +/- 100 micro volts (μV). Horizontal eye movements were rejected if outside of +/- 200 μV. The epoch for data was set to 300 ms pre-stimulus to 1700 ms post-stimulus. Baseline correction were made at 300 ms pre-stimulus onset. Vertical eye movements corrections followed a well-established method (Semlitsch, Anderer,

Schuster, & Presslich, 1986). All ERPs were based on a grand average for a stimulus type within the task. 2 control participants and 2 schizotypy participants had more than 50% of trials rejected and were not included in the analysis. Thus, the final sample size for each group in all analyses was 20 controls and 20 schizotypes.

Wynn and colleagues (2013), defined their N170 and N250 time windows as the peak activity observed by examination of the mean global field power averaged across an emotion identification task. They chose the width of the window to ensure that the mean activity of each ERP component was measured. The current study followed the same procedure. The N170 component was defined as the most prominent negative deflection of the waveform in the 90-170 ms post-stimulus window. The N250 component was defined as the most prominent negative deflection of the waveform in the 200-300 ms post-stimulus window.

Statistical Analysis

The current study is a 2 X 2 X 3 mixed design ANOVA comparing group

(schizotypy and control) as the between subjects factor, by emotion (fear, neutral), as a within subjects factor, and by lead (Fz, Cz, and Pz) as another within subjects factor. The dependent variables are the N170 and N250 amplitudes. For each ERP component (N170,

N250), a 2 (group) x 2 (picture type: fear, neutral) X 3 (lead) repeated measure analysis

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of variance (ANOVA) was run. A mixed ANOVA compares the mean differences between the two groups and the two within-subject factors (lead, emotion). The primary purpose of this design is to see if there is an interaction between lead, emotion, and group on the dependent variables: N170/N250 amplitudes. A 2x2x3 mixed design ANOVA allows us to look at the main effects for each of the three factors, look at the three two- way interactions, and look at the one three-way interaction. To adjust for a repeated measure analysis of variance the Greenhouse-Geisser correction was reported. ERP component amplitudes that had latencies outside of the 90-170 ms post-stimulus window and 200-300 ms post-stimulus window for N170 and N250 respectively, were not included in the analysis. Also, amplitudes for both N170 and N250, which were positive, were changed to 0.

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Results

There was no significant main effect of group (control, schizotypy) on the facial structure encoding N170 amplitudes, F(1,32) = .303, p > .05. Nor was there a significant main effect of group (control, schizotypy) on the facial affect decoding N250 amplitudes,

F(1,37) = .689, p > .05. Both results are contrary to expected findings and are displayed in Figure 1. ERP grand average waveforms for each group at each of the three leads can be seen in Figure 2. The N170 and N250 averages for each group at Fz, Cz, and Pz by emotion are reported in Table 1 & 2 respectively.

N170 N250 0

-1

-2 μV)

-3 Microvolts Microvolts ( -4

-5

-6

Control Schizotypy

Figure 1. Mean N170 and N250 amplitudes in microvolts (μV) for Schizotypy and Control.

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Figure 2. Overlapping grand average waveforms for Schizotypy and Control.

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Fear Neutral

Lead Group N M (SD) N M (SD)

Fz Control 16 -5.31 (2.80) 16 -4.81 (3.04)

Schizotypy 18 -6.28 (1.95) 18 -6.21 (3.12)

Total 34 -5.82 (2.40) 34 -5.55 (3.12)

Cz Control 16 -6.46 (3.05) 16 -5.33 (3.15)

Schizotypy 18 -6.40 (2.41) 18 -6.49 (3.48)

Total 34 -6.43 (2.69) 34 -5.94 (3.33)

Pz Control 16 -4.31 (3.20) 16 -3.77 (2.76)

Schizotypy 18 -3.82 (3.14) 18 -3.52 (3.32)

Total 34 -4.05 (3.13) 34 -3.64 (3.03)

Table 1. Mean N170 amplitudes in microvolts (μV) across Groups, Emotion, and Lead

Fear Neutral

Lead Group N M (SD) N M (SD)

Fz Control 19 -4.22 (2.65) 19 -5.33 (3.39)

Schizotypy 20 -5.66 (3.05) 20 -6.00 (2.91)

Total 39 -4.96 (2.92) 39 -5.67 (3.13)

Cz Control 19 -4.24 (3.14) 19 -5.42 (3.95)

Schizotypy 20 -5.17 (3.37) 20 -5.37 (3.41)

Total 39 -4.72 (3.25) 39 -5.40 (3.64)

Pz Control 19 -3.08 (3.48) 19 -4.73 (4.50)

Schizotypy 20 -4.58 (3.29) 20 -4.73 (3.34)

Total 39 -3.85 (3.43) 39 -4.73 (3.89)

Table 2. Mean N250 amplitudes in microvolts (μV) across Groups, Emotion, and Lead

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For N170, there was no significant main effect of emotion F(1,32) = 1.648, p >

.05. Fear and neutral expression evidenced similar negativities. However, there was a significant main effect of lead F(2,64) = 22.701, p < .05. Further inspection of the pairwise comparisons revealed that the Fz and Cz amplitudes were different (p < .05), the

Fz and Pz amplitudes were different (p < .05), and the Cz and Pz amplitudes were different (p < .05). The N170 was most pronounced in the central lead, followed by the frontal lead, and most attenuated in the posterior lead. This is displayed in Figure 3.

Contrary to expected findings, the N170 group x lead interaction was not significant

F(2,64) = 2.345, p > .05. There were also no significant differences in the N170 group x emotion F(1,32) = .978, p > .05 and lead x emotion F(2,64) = .106, p > .05 interactions.

The N170 group x lead x emotion three-way interaction was not significant F(2,64) =

.522, p > .05

Fz Cz Pz 0

-1

-2

μV) -3

-4 Microvolts ( Microvolts -5

-6

-7

Figure 3. The amplitudes for N170 across Leads.

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For N250, there was a significant main effect of emotion F(1,37) = 4.111, p < .05.

Overall, neutral emotion produced greater negativity than fear. This is displayed in Figure

4. There was also a significant main effect of lead F(2,74) = 3.933, p < .05. Further inspection of the pairwise comparisons revealed that the Fz and Cz amplitudes were not different (p > .05), the Fz and Pz amplitudes were different (p < .05), and the Cz and Pz amplitudes were different (p < .05). The N250 was most pronounced in the frontal lead, followed by the central lead, and most attenuated in the posterior lead. This is displayed in

Figure 5. Contrary to expected findings, the N250 group x lead interaction was not significant F(2,74) = .320, p > .05. There were also no significant differences in the N250 group x emotion F(1,37) = 2.020, p > .05 and lead x emotion F(2,74) = .244, p > .05 interactions. The N250 group x lead x emotion three-way interaction was not significant

F(2,74) = .714, p > .05.

Fear Neutral -4

-4.2

-4.4 μV) -4.6

-4.8 Microvolts ( Microvolts -5

-5.2

-5.4

Figure 4. The amplitudes for N250 across Emotions.

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Fz Cz Pz 0

-1

-2 μV)

-3

Microvolts ( Microvolts -4

-5

-6

Figure 5. The amplitudes for N250 across Leads.

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Discussion

The purpose of the present study was to examine: (1) differences between psychometric schizotypes and those low in schizotypy on the neuronal processes associated with facial structuring encoding, for fear and neutral emotions, (2) differences between psychometric schizotypes and those low in schizotypy on the neuronal processes associated with facial affect decoding, for fear and neutral emotions, (3) topographical distribution for the neuronal processes associated with facial structuring encoding, and

(4) topographical distribution for the neuronal processes associated with facial affect decoding. Deficits in the neuronal processes for those high in schizotypy, as measured by the event-related potential components N170 and N250, were predicted to mirror deficits in the schizophrenia population.

Summary of Findings

ERP analysis of the electroencephalography data did not support any of the hypotheses. There were no differences between psychometric schizotypes and controls on the N170 and N250 amplitudes. This finding of no differences is not consistent with the

N170 and N250 findings of studies of persons with schizophrenia. However, this finding was consistent with Grabyan (2011), who also found both N170 and N250 components to be intact in persons with schizotypy during a facial affect recognition task. This broadly implies that facial structural encoding and facial affect decoding are intact in schizotypes, but results should be interpreted lightly as there were several limitations that could have hindered results (explained later).

The two hypotheses relating to ERP distribution across group and lead were not supported. Examination of the interaction between group and lead for both N170 and

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N250 showed no significance; indicating that the topographical distribution for both

ERPs presented a similar pattern for both groups. Although there were no group by lead differences on N170 and N250 amplitudes, there were differences in overall amplitudes by lead. Unexpectedly, the overall N170 amplitudes were observed to have a greater negativity at the central midline region and a greater attenuation at the parietal midline region. This is contrary to the literature that characterizes the N170 to be most pronounced in the parieto-occipital temporal scalp regions. It is unclear why the N170 had an atypical distribution. However, obscurity in the N170 may have been due to high preparatory, perceptual, and/or cognitive task requirements. The rapid non-target stimuli presentation of facial expressions may have put less focus on facial structural processing and more focus on the salience of the emotion. That is, due to the fact that stimuli were solely faces, there were no resources allocated to the facial structuring N170 and an automatic classification of faces was produced. In addition, the overall N250 amplitudes were observed to have a greater negativity at both the frontal and central midline regions in comparison to the parietal midline region. This was expected since the literature has consistently characterized the N250 to be most pronounced at the frontocentral midline region.

Overall differences for the N250 across neutral and fear emotions showed that

N250 amplitudes were more negative for the neutral facial expression. It is important to note that the two emotional expressions did not produce different overall N170 amplitudes. This was expected as the N170 reflects a structural encoding neuronal mechanism for detection of human faces and precedes identification. This suggests that

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the task did differentiate between the N170 and N250, adding to the consensus between researchers that the N170 is not affected by emotional expression.

Limitations and Future Research

The currents study implies that no apparent impairment in facial affect recognition is observed in schizotypes, but results may have been hindered due to several methodological limitations. First, the current study pooled from a sample of college students. This suggests the sample was comprised of participants high in academic achievement. This sample is not generalizable to schizotypes in the general population. If the sample utilized a community selection, the results may have been different. Future studies may benefit from utilization of community samples.

Second, lesser schizotypy levels in the high schizotypy group may have impacted the findings. Identification as a high schizotypy participant required a score of 15 on the

Schizotypal Questionnaire-Brief (SPQ-B), but very few scores were above 17. A sample comprised of students scoring at least 19 would have been a better representation of true psychometric schizotypes and might produce significant findings. Future studies might raise the cut-off score for inclusion in to the high schizotypy group.

Third, the literature has consistently utilized the full version of the SPQ due to its stronger criterion and discriminant validity. The full version of the SPQ looks at many subordinate factors, while the SPQ-B does not. The use of the shorter SPQ-B for this study might have produced more false positives for high schizotypes, which might have hindered results. Future research would do well in using the full version of the SPQ or the recently published Schizotypal Personality Questionnaire- Brief Revised. The revision of

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the SPQ-B has added a few more items and has expanded the scoring system to include subordinate factors (Cohen, Matthews, Najolia, & Brown, 2010).

Fourth, this study was limited by the number of electrode placements used. The

N170 has been shown to have topographical maximal activity in electrodes P7, PO9, P8, and PO10. The N250 has been shown to have topographical maximal activity in electrodes C3, F3, FC1, C4, F4, and FC2 (Wynn, et al., 2008). This study only used the midline Fz, Cz, and Pz electrodes. It is possible these midline electrodes did not capture a strong representation of a N170 waveform and/or N250 waveform. Waveforms may be more attenuated at midline leads in comparison to lateral leads. If this is true, amplitudes from Fz, Cz, and Pz electrodes might not reflect the maximal activity of N170 and/or

N250 ERP components.

Fifth, Wynn, et al. (2013), defined the time window for both N170 and N250 separately for each group. This particular method reflects a more accurate assessment of the N170 and N250 and might be a more sensitive procedure for detecting group differences. The current study used a single time window for both groups to identify mean activity on the N170 and N250. Future studies may want to define time windows for ERPs separately for groups in order to detect differences better.

Lastly, the target/non-target paradigm focusing on a happy-happy combination target event might have influenced results. Most studies do not use a target vs non-target paradigm for facial affect recognition tasks on N250. Rather, a simpler emotion recognition task that doesn’t focus on specific target stimuli is consistently used. In contrast, N170 studies do use target/non-target tasks, but instead utilize pictures of butterflies, houses, and cars as deviant stimuli. Some N170 designs also use a specific

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emotion as a target stimulus, but not in a matching method as was used in this study.

Results may have been hindered due to the possibility that N170 and N250 are task specific. Also, both neutral and fear emotions were non-target events. It is possible that non-target events were influenced by the constant cognitive demands used for scanning of the target event. Thus, resource allocation might have been influenced by the task. It is also possible that N170 and N250 components were not captured during this task, but rather an N100 and N200. N100’s and N200’s are consistently found in target/non-target paradigms (Brown, Gonsalvez, Harris, Williams, & Gordon, 2002; Chun, 2011). N100s respond to manipulation of attention. N200s are evoked during conscious stimulus attention or visual discrimination tasks. N200s may also arise during classification tasks or when attention is focused on one object while ignoring others. Group differences might have been found if a different paradigm was used. Future studies in facial affect recognition and schizotypy might want to examine the third CPT task, which is more typical of emotion recognition tasks used for N250 studies in schizophrenia populations.

Looking at differences in ERP components between target and non-target emotions have not been examined in schizophrenia research. This is a possible new area of study which should be further examined. Inspection of this studies specific target/non- target paradigm in affect recognition leaves questions unanswered. Comparisons of the second task and the third task might help clear up questions on limitations. Furthermore, the task used in this study should undergo analytical procedure validation for use in facial affect recognition.

In summary, the present study looked at facial affect recognition in those scoring high in schizotypy and low in schizotypy using electroencephalography methods, in

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particular for fear and neutral emotions. There were no differences found between low schizotypes and high schizotypes in facial affect recognition. The null findings might have been influenced by methodological limitations. Further EEG studies of emotion processing in schizotypy are indicated.

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Appendix A

Schizotypal Personality Questionnaire - Brief

Please answer each item by circling Y (Yes) or N (No). Answer all items even if unsure of your answer. When you have finished, check over each one to make sure you have answered them all.

Y N 1. People sometimes find me aloof and distant.

Y N 2. Have you ever had the sense that some person or force is around you, even

though you cannot see anyone?

Y N 3. People sometimes comment on my unusual mannerisms and habits.

Y N 4. Are you sometimes sure that other people can tell what you are thinking?

Y N 5. Have you ever noticed a common event or object that seemed to be a special

sign for you?

Y N 6. Some people think that I am a very bizarre person.

Y N 7. I feel I have to be on my guard even with friends.

Y N 8. Some people find me a bit vague and elusive during a conversation.

Y N 9. Do you often pick up hidden threats or put-downs from what people say or

do?

Y N 10. When shopping, do you get the feeling that other people are taking notice

of you?

Y N 11. I feel very uncomfortable in social situations involving unfamiliar people.

Y N 12. Have you had experiences with astrology, seeing the future, UFOs, ESP or

a sixth sense?

Y N 13. I sometimes use words in unusual ways.

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Y N 14. Have you found that it is best not to let other people know too much about

you?

Y N 15. I tend to keep in the background on social occasions.

Y N 16. Do you ever suddenly feel distracted by distant sounds that you are not

normally aware of?

Y N 17. Do you often have to keep an eye out to stop people from taking advantage

of you?

Y N 18. Do you feel that you are unable to get "close" to people?

Y N 19. I am an odd, unusual person.

Y N 20. I find it hard to communicate clearly what I want to say to people.

Y N 21. I feel very uneasy talking to people I do not know well.

Y N 22. I tend to keep my feelings to myself.

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Appendix B Examples of Stimuli Images from the Continuous Performance Task (Happy Face Go)

Sadness Neutrality

Anger Happiness

Surprise Fear

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