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Predicting antisocial behavior using correlates of MAOA gene and orbital frontal cortex physiologies

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Predicting antisocial behavior using correlates of MAOA gene and orbital frontal cortex physiologies
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Klein, Eric
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Metropolitan State University of Denver
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Predicting Antisocial Behavior Using Correlates of MAO A Gene and Orbital Frontal Cortex
Physiologies
by Eric Klein
An undergraduate thesis submitted in partial completion of the Metropolitan State University of Denver Honors Program
May 2014
Dr. Chad Mortensen
Dr. Cynthia Erickson
Dr. Megan Hughes-Zarzo
Primary Advisor
Second Reader
Honors Program Director


Running head: SURVEYS, MAOA-L & OFC
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Predicting Antisocial Behavior Using Correlates of MAO A Gene and Orbital Frontal Cortex
Physiologies Eric M. Klein
Metropolitan State University of Denver


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Abstract
Various factors affect the capriciousness of survey data in wide scale research: Participant response rates are decreasing (Dey, 1997), considerations for sensitive topics are overlooked (Pryor, 2004), survey modality can be inappropriate, and inconsistency of construct is pervasive across studies (Burless & De Leo, 2001). Calls for increased consistency in survey research have been made. In this paper it is suggested that to increase empiricism and consistency, a basis in the physiological bases of survey research could be utilized. Two studies are presented to demonstrate the potential for this research. In the first, surveys selected for factors related to orbital frontal cortex abnormalities and the MAOA-L genotype are used to predict antisocial behavior by survey, as this behavior correlates to both of these physiologies. All selected factors: risk taking, low perspective taking, depression and gender, were found to be significant predictors. Results indicate strong potential for survey selection by physiological correlates. In a second study, a physiological state of arousal is primed with exercise induced increased heart rate. Physical arousal has been connected to aggression (Zillmann, 1989). Physical arousal is contrasted with median split groups based on an aggression survey for predicting aggressive prisoners dilemma gameplay. Relaxed participants played more aggressively, while survey groups were not significant. Results are discussed in reference to survey best practices. Topics are relevant to psychometrics and research methods.


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Predicting Antisocial Behavior Using Correlates of MAO A Gene and Orbital Frontal Cortex
A basic goal of the social sciences is behavioral prediction through research. A great deal of discussion occurs regarding the reliability of conventional research methods and their efficacy. In particular, large-scale research data is typically conducted by survey. Although a great amount of care is taken to develop these instruments, they are often indented to investigate psychological constructs, which are constantly changing as new discoveries are made. As this is the case, several different surveys may be used to investigate one trait as time progresses, and this leads to inconsistent findings in the literature (Burless & De Leo, 2001). Further, several other major obstacles in survey research obfuscate findings such as participant non-response and problems of modality and sensitive topics. To overcome these obstacles this paper suggests that as humans are largely biologically similar (Dupre, 2008), a possible route to increase the reliability of survey research is to select and develop surveys based on physiological correlates to behavior. Mind, body, and social context influence each other interdependently (Susman, 2001). This paper will demonstrate that due to these connections the predictive efficacy of survey research can be increased by the use of physiological correlates. To illustrate the potential for prediction based on physiology, two studies will be presented.
The first uses the example of antisocial behavior, which has been well correlated in previous research to two physiologies: the low transcribing genotype for monoamine oxidase-A gene, and irregularities of the orbital frontal cortex. The connection between these physiologies and antisocial behavior will be explained, as will the connection between these physiologies and four other factors: risk taking, perspective taking, depression and gender. These factors were used to attempt to predict self-reported antisocial behavior. The results of this study will be discussed in reference to the strength of prediction by physiological correlates.


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The second study described is an experiment where a physiological state was used in an attempt to predict behavior. The efficacies of physiology versus a survey examining particular personality traits are compared in predicting a behavior relevant to both. Specifically, aggression has been connected to physical arousal (Anderson, Deuser and DeNeve, 1995; Zillmann, 1988). In this experiment participants are primed with arousal by exercise induced increase in heart rate and surveyed for aggression. The arousal condition and the aggression survey were used in an attempt to predict participants aggressive gameplay on a prisoners dilemma task. Again, the results of this study will be discussed in reference to prediction by physiology.
Before introducing these studies however a clear understanding of the problem is required. The following sections will describe proliferation of large-scale survey research, and problems that can arise within this type of research. Threats to the research reliability and validity are discussed as well as a need to increase consistency in surveys. The solution to this problem by increasing the physiological bases of surveys is discussed initially in reference to existing literature and then in reference to the present studies.
Problems in Survey Research
It is nearly impossible to create a survey that perfectly resembles the characteristic for which it intends to study in any given population (Lohr, 2008). This is clearly a problem to overcome for researchers who wish to predict behavior using survey data. Survey design and efficacy is particularly important when the resulting data is used to decide clinical, institutional, or political outcomes. Assessment in these and many areas has become increasingly survey-based (Porter, 2004). The estimated total number of published research articles based on survey data has increased three fold from 1980 to 2010. These articles are used to determine policy in virtually every area of business and government (SaBenroth, 2013). Due to the vast proliferation


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of research by survey, instances of survey mismeasurement and misapplication have become more frequent. A prominent example of questionably applied large-scale survey research began in 2003. The Bush Administration budgeted $20 million dollars to fund an initiative to pilot increased institutional mental health screening in several states including New York. Patients visiting a general medical practitioner for almost any ailment would be screened for depression. Although psychiatrists and psychologists largely dismissed the concerns of opponents to the initiative, politicians and advocates for the disabled spoke out largely against it, citing concerns of privacy and misdiagnosis (Santora & Carey, 2005). Although this example invokes questions regarding survey research of sensitive topics, it specifically highlights the social importance of research best practices. To carefully explore potential pitfalls of survey research practices, the issues of participant non-response, sensitive topics, modality, and construct will be discussed. Participant Non-response: a Threat to Sample Representativeness
The modality, or medium of survey research is an important issue regarding methods for gathering sound data, especially as the demand for data increases. Although an intrinsic advantage to survey research is the ability to quickly and conveniently gather data, new issues have arisen as survey distribution has evolved. For instance, as the use of surveys has increased, response rates have fallen. In one meta-analysis, a sample set of national surveys ranging from the 1960s to the 1980s was analyzed. Over that time response rates dropped from an average of 60% to only 21% (Dey, 1997). The downward trend in survey response appears to be due to difficulties in communication of the intended material, and to participants unwillingness to divulge information (Porter, 2004).
Unwillingness to share information could be related to concerns about loss of privacy in the modern era of big data. Natural Resources Canada polled 2,200 people about their attitudes


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regarding online data collection just prior to the launch of Google Street View. The response was indicative of overall concern for individual privacy. More than half of the respondents indicated that they had experienced violations of privacy online, and 80% were concerned about the future risk of loosing their privacy. Only 18% indicated that they trusted corporations with the data that they collect (Schmidt, 2010). Users of digital services or network electronics are asked to agree with terms that allow providers to record data in areas including: users mobile location, application usage, browsing behavior, and frequent searches just to name a few (Chen, Mao, & Liu, 2014). Constant awareness that data is being collected from each person during most moments of the day might not only cause people to be more judicious about the facts they choose to divulge when surveyed, it could also cause mental fatigue. Research has indicated that if participants are asked to respond on a greater number of survey questions, that due to fatigue they respond less frequently. This is especially true when participants are given several different surveys in succession (Porter, Whitcomb, & Weitzer, 2004). It would not be unreasonable to partially attribute the cause of diminishing response rates to the fatigue experienced by the modem lay-person who is responding to requests for data, and providing covert data constantly everyday.
An in depth exploration of the causes of participant non-response would be beyond the scope of this paper. The relevant point is that non-response is an increasingly serious problem in survey research. Various research designs dictate specific sample sizes to satisfy the required statistical power for an analysis. Sufficient response rates assure confidence in any given research finding. If response rates are low, it compromises the ability to generalize the findings of a survey to the target population (Burless & De Leo, 2001). For example in an organizational study, participants nonresponse on a workplace attitude survey negatively correlated to


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workplace satisfaction (Fauth, Hattrup, Mueller and Roberts, 2012). The researchers thus learned less from a group of participants who they were trying to analyze, specifically because of the nature of the survey.
Sensitive Topics: a Cause of Non-response and Harm
A special category of surveys related to participant non-response and overall research design obstacles is that of sensitive topics. Subjects that comprise sensitive Topics surveys include: violence, drug use, trauma, sexual behavior, violations of policy, socially undesirable behavior, and other related topics (Pryor, 2004). In these cases, not only can non-response increase, but priming effects of asking sensitive topic questions could represent an experimental confound. The validity of sensitive topic survey responses is difficult to measure. Questions in sensitive topic surveys may cause immediate anxiety in the respondent, and further raise concern in the respondent about their privacy (Pryor, 2004). One factor that magnifies sensitive topics effects on the mentality and response rate of the respondent is the proximity of the researcher. In studies of drug and alcohol abuse, participants using self-administered surveys have displayed higher survey response rates versus participants who were responding to surveys that were administered by a researcher face-to-face (Aquilino, 1994). The difference observed between modalities is generally attributed to social desirability (Tourangeau & Smith, 1996; Turner, Lessler & Gfroerer, 1992). Increasing the privacy of the respondent can increase response rates on sensitive topic surveys. A study in Holland compared response rates on a sensitive topic survey between those who were surveyed in person and those who were surveyed by mail. The correspondence participants responded much more frequently. However, their overall response rate was still only 64% (Nederhof, 1985). With seemingly intrinsically low response rates, the design and sensitivity of sensitive topics studies is thus paramount to research design.


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Modality: Medium of a Survey Matters
The previously mentioned mental health screening initiative in New York was under debate out of concern for patients rights and privacy. This however, could also be an example of a less than optimal survey modality (or medium) for studying the intended personality trait. In this case, New York City was administering the Patient Health Questionnaire 9 (PHQ-9;
Kroenke & Spitzer, 2002) to adult primary care patients. This survey presents patients with nine questions designed to diagnose depression by DSMIV criteria such as whether he or she recently had Thoughts that you would be better off dead or of hurting yourself in some way. This question is specifically referring to suicide ideation, which falls within the area of sensitive topic surveys, and invokes research considerations previously discussed. One might not expect to have to evaluate his or herself on this level during a visit to their primary care physician, nor to deal with the anxiety involved with sensitive topics questions. Though as of 2007, the New York Department of Health had issued a general recommendation to doctors that they administer a depression questionnaire to all adult patients. Further, they added a two question pre-screen measure, Patient Health Questionnaire-2 (PHQ-2) to prequalify patients before administration of the PHQ-9. The PHQ-2 asks only for a yes or no response to whether patients had felt Little interest or pleasure in doing things, or if he or she was Feeling down, depressed, or hopeless (NYC Dept, of Health and Mental Hygiene, 2007). Considering the tendency for patients to respond less on ST surveys, especially when in proximity to an assessor, it seems unlikely that these two questions would illicit representative responses from patients who are expecting a normal check-up from their doctor. The New York Department of Health asserted that the PHQ-9 was not intended for formal diagnosis, but instead to guide recommendations for further screening of those who were found to be at risk for depression (Santora & Carey, 2005).


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Although this somewhat answers the concerns of those who were in political opposition to these practices because of misdiagnosis risk, it does not address two important research design issues:
1. There is the possibility that non-response to a sensitive topic survey in this context could influence the results, such that many if not most at risk go undetected. 2. Considering the anxiety associated with sensitive topics content, and possible lack of detection of depression in respondents, there is a considerable risk to respondents compared to the potential benefits. This example not only illustrates problems of survey modality in context of a research topic, but also illustrates the potential harm involved with survey practices.
Construct: a Threat to Validity
The misrepresentation or inconsistency in analysis of psychological constructs through survey research presents threats to research reliability and validity. Appropriate categorization of psychological constructs within survey items goes far beyond the breadth of this paper due to their intrinsically subjective nature. Though examples of inconsistencies between studies attempting to research or validate findings over like-topics are not difficult to find. The findings of a meta-analysis by Burless and De Leo (2001) examining large scale survey studies about suicidal behavior presented in-depth examples of such problems. Burless and De Leo reviewed 30 publications released between 1974 and 1999 that reported statistics from surveys examining suicidal behavior. One significant problem the researchers outlined was in reference to age and demographic of the sample population. Due to the assumption that suicide would be relevant to different age groups in different ways, there was a distinct bias in the number of questions related to certain subtopics within surveys targeted to age groups. In general population surveys, most questions were found to inquire about past behaviors in reference to suicide ideation. Surveys intended for adolescents however, mostly asked questions related to present or future


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potential suicide attempts (e.g., I would like to kill myself; p. 119). Burless and De Leo found that surveys targeted towards the elderly showed a bias in the number of questions related to value of life or Worthlessness of living (p. 120). Although different topics can have differing meanings across age groups, over representation of any subtopic to specific sample populations presents a problem for comparison or generalizability across groups, and across studies.
Between surveys targeted to the general population, Burless and De Leo (2001) found that items inquired about differing degrees of suicide ideation, and this made comparison for reliability impossible. Only a few studies investigated responses over isolated degrees of ideation. These studies however differed in their definitions and criteria for ideation and were thus also incomparable to other research. Without comparable data, reliability cannot be assessed. Further, without consistent definitions, construct validity is not present.
Burless and De Leo (2001) found that among research focusing specifically on suicide attempts, many studies failed to properly investigate this topic as an actual event. Studies that investigated this topic from a conceptual approach were inconsistent in their categorizations of levels of intent. Items in these studies would vary in their description of levels on the range from cry for help intent to intent for absolute self-destruction. It was also found that when researchers attempted to study the frequency of suicide attempts, the time periods in question were inconsistent. Further, the definition of what constituted an attempt varied. In some studies intently pointing a gun at his or herself would be called an attempt, where in others self-injury would be required. In these examples, threats to the valid analysis of an actual behavior have occurred due to inconsistencies in construct between surveys.
Empirical Consistency


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In the Burless and De Leo (2001) study, the researchers suggested that survey research should be done from a synchronized approach to obtain more comparable and meaningful outcomes. They further suggested several best practices specifically relevant to the study of suicide. Though they also make the suggestion that when researching a construct, surveys identical to those used in previous research should be utilized whenever possible. This would allow for both consistency of construct between studies, and comparison of results across various samples. Consistency of both construct and instruments designed to analyze them would seem relevant to the scientific process in almost any area. The problem with this suggestion is that psychological research is intrinsically subjective. To reductively restrict the number or type of surveys investigating any one topic could affect blindness to some facets of personality, behavior or lifespan development. Here a paradox is presented where a lax or expansive philosophy leads to problems of validity, or a reductive philosophy could lead to problems of sensitivity. A less absolutist approach might examine isolated strategies where subjectivity can be reduced without ignoring relevant groups or relevant data. The scientific process itself is predicated on empirical observations that can be consistently replicated. Hence a sensible empirical approach to research could be found in that which is consistent through all populations, specifically physiology.
A Solution in Physiology
The theory that physiology, mind and behavior are inexorably linked is accepted to varying degrees throughout the various disciplines of psychology. Early empirical research linking the workings of the brain with psychology was outlined in the nineteenth century by William James (James, 1962). The James-Lange theory eventually followed, which assumed that physiological responses to stimuli cause emotion. Later another hypothesis emerged: the Cannon-Bard theory that assumed emotional responses result in effects on physiology


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(Roeckelein, 2006). A further refinement of these theories was the Two-factor Theory of emotion, where emotion arises from attributions of physical arousal based on immediately salient cues (Schachter & Singer, 1962). These theories were precursors to modern branches of psychology such as behavioral genetics and neuroscience that are centered upon the study of the mind-body relationship. Modern iterations of mind-body interaction theories assume a dynamic interdependent relationship unifying the physiologies of brain and endocrine function with lifespan development, personal experience, and social context (Magnusson, 2001). Susman (2001) described antisocial behavior as an example behavior-type explained well by this sort of interaction. Research by Susman correlated lower levels of the hormones adrenaline and cortisol to antisocial deficits in emotional and physical regulation. This is only one example of an increasingly large body of findings across several disciplines, which illustrate that the mind and body are linked and influence one another.
The most important precept in considering physiology as a guide for psychological research is its consistency. The completion of the sequencing of the human genome showed that human DNA is 99.9% identical (Dupre, 2008). Essentially, we are all built in a very similar fashion. Considering the connection between the mind and body, people experience similar psychological effects and display similar behaviors based on similar physiologies. We experience similar effects when something in our body is abnormal. Thus specific physiologies could be used potentially as markers for consistency in survey research. The following text of this paper will illustrate the potential for reliability in this type of research by describing two studies: 1. A study that predicted scores on a personality measure by surveys related through physiological markers. 2. An experiment that contrasted the efficacy of a survey versus a physiological state in predicting a behavior.


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Study 1: Predicting Antisocial Behavior Scores With Measures of Risk Taking, Perspective Taking, Depression and Gender.
Due to strong correlations in physiology, antisocial behavior was the personality trait under analysis in the first experiment discussed here. Numerous studies have identified the strong continuity of these behaviors within individuals over time, and they are approximated to personality (Bonino, Cattelino, & Ciairano, 2005). In fact, these behaviors are identified as diagnostic criteria for antisocial personality disorder (ASPD), a clinical personality disorder outlined in the Diagnostic Statistical Manual of Mental Disorders (DSM-V, 2013). Antisocial behavior is defined by aggressive or impulsive actions that violate established social rules, norms or laws, and is often referred to in contrast to prosocial behavior (A PA Dictionary of Psychology, 2007). The ASPD diagnostic criteria outlined by the DSM-V also yield examples of the behaviors associated with an antisocial personality:
A pervasive pattern of disregard for and violation of the rights of others, occurring since age 15 years, as indicated by three (or more) of the following:
1. Failure to conform to social norms with respect to lawful behaviors, as indicated by repeatedly performing acts that are grounds for arrest.
2. Deceitfulness, as indicated by repeated lying, use of aliases, or conning others for personal profit or pleasure.
3. Impulsivity or failure to plan ahead.
4. Irritability and aggressiveness, as indicated by repeated physical fights or assaults.
5. Reckless disregard for safety of self or others.
6. Consistent irresponsibility, as indicated by repeated failure to sustain


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consistent work behavior or honor financial obligations.
7. Lack of remorse, as indicated by being indifferent to or rationalizing having hurt, mistreated, or stolen from another... (DSM-V, 2013, 301.7-F60.2)
An important distinction should be made, that the present study does not seek to diagnose, nor analyze ASPD in a sample population. ASPD is typically studied using research materials or diagnostic techniques that are not employed in this study. However ASPD is a named personality disorder and its diagnostic criteria and epidemiology comprise relevant examples of antisocial behavior. Further examples of the traits of someone with tendency for antisocial behavior can be observed in previously distinguished subtypes of antisocial behavior. Those who are high in physical aggression for instance, find affective self-regulation difficult, and engage in actions intended to physically hurt others. Those who are very impulsive tend to engage in theft or rule breaking. Those who engage in social aggression use social relationships as a means of harming others. Though the latter case does not involve law breaking, it does imply an antisocial lack of remorse (Bonino et al., 2005; Burt & Donnellan, 2009). While common definitions of antisocial behavior are accepted, prediction and risk factors involved are under debate. Likewise the current DSM-V criteria for the diagnosis of ASPD are also under review (Glenn, Johnson, & Raine, 2013). Thus outlining strong predictive factors related to this type of personality are beneficial on a wide scale.
Epidemiology of Antisocial Behavior
The prevalence of crime in the United States and other countries speaks to the impact that antisocial behavior can exert. There is of course a distinction between those with personalities predicated toward antisocial behavior, and those who commit isolated criminal events. However, the two do appear to coincide even to the extent of full personality disorders. In a review of


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epidemiological research studies conducted across many countries between 1980 and 1998, the rates of ASPD for instance, were found to consistently occur in general sample populations at the rate of between 1% and 3%. The rates of ASPD found in prison populations ranged from 40% to 60%, and was found to be the most prevalent personality disorder among inmates (Moran, 1999). Within the general population, antisocial behavior has been found to relate to age. Rates of antisocial behaviors have been found to peak among people in their early to mid-twenties, and to persist through the mid-thirties where the frequency of such behaviors becomes increasingly less common (Bonino et al., 2005). Antisocial behaviors have been correlated with various traits and attitudes. In regard to traits directly relevant to the present study, antisocial behavior associated with ASPD has been found to be comorbid with other personality disorders corollary to anxiety, depression, or substance abuse. Also antisocial behavior has been shown to be more pervasive in males rather than in females (Bonino et al., 2005; Glen et al., 2013). However, there is still conflicting data regarding the distinction between genders, where some studies have found the social aggression subtype of antisocial behavior to relate more closely to females, while physical aggression has related more often to males (Burt & Donnellan, 2009). These associations in part selected for the factors used in the study that are correlated to antisocial behavior through physiology. There are two physiologies in particular that are well established in the literature in relation to antisocial behavior: the low transcribing allele genotype of the monoamine oxidase-A gene (MAOA-L), and irregularities in the orbital frontal cortex (OFC) of the brain.
MAOA-L and Antisocial Behavior
Monoamine oxidases are enzymes that catalyze the breakdown of aminergic neurotransmitters. Monoamine oxidase-A, the specific enzyme of interest here, catalyzes the breakdown of noradrenaline and serotonin (Oxford Concise Medical Dictionary, 2010). Of these


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two chemicals, serotonin or 5-hydroxytryptamine (5-HT) is of particular significance. Serotonin in the central nervous system originates in the raphe nuclei and projects throughout virtually the entire brain and spinal cord. A large family of 5-HT receptors exist which affect diverse cellular pathways when activated. Serotonin is notably related to the moderation of arousal, mood, aggression, and the sleep cycle. Reduced levels are associated with mood disorders such as depression. Monoamine oxidase inhibitors or serotonin uptake inhibitors (SSRI) increase the effect of serotonin at the synapse, and are often prescribed in the treatment of mood disorders (Martin & Hine, 2013). The gene that codes for the monoamine oxidase-A enzyme in humans is located on the X chromosome location Xpl 1.23-11.4. This gene contains a 30-base pair motive in its promoter, which is polymorphic. Various promoter alleles have been identified in upstream variable number tandem repeats (MAOA-uVTNR) where resulting genetic combinations will result in normal or low transcription of the monoamine oxidase-A enzyme (MAOA-L; Gallardo-Pujol, Andre s-Pueyo, & Maydeu-Olivares, 2013, Williams et al., 2009). Females heterozygous for mutant (L/H), homozygous for the wild-type (H/H), or males hemizygous for wild-type alleles (H/Y) generally experience normal levels of serotonin activity. Females are who are homozygous (L/L) or males hemizygous (L/Y) for mutant alleles transcribe lower amounts of monoamine oxidase-A, and experience increased levels of serotonin (MAOA-L). Sex differences go beyond genotype in this case, as monoamine oxidase-A transcription is directly regulated by estrogen. Receptors for estrogen are densely present in the amygdala, cingulate and orbital frontal cortices where local regulation of transcription would have various effects. Testosterone, which has long been thought a moderator of aggression, may also act directly on the MAOA-uVTNR promoter in regulating transcription (Buckholtz & Meyer-Lindenberg, 2008; Williams et


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al., 2009). With a basic understanding of the physiology of MAOA-L higher-level effects can be described.
The viable levels of serotonin catalysis due to MAOA-L have been found to have significant emotional and behavioral effects. These effects have been reliable and widely accepted to the extent that the presence of MAOA-L has been used in courtroom attempts to excuse criminal actions (Baum, 2013). In an early study regarding the behavioral effects of MAOA-L, Brunner, Nelen, Breakefield, Ropers, and van Oost (1993) identified a large family where the members, males in particular, were known for uncontrolled aggression and borderline mental retardation. The researchers genotyped the entire family as well as took urine samples. The genetic results indicated the pervasive presence of MAOA-L in the family, while the urine samples reveled decreased levels of monoamine oxidase-A catalytic products. This would seem almost counter intuitive considering that people who naturally experience reduced levels of serotonin typically suffer mood disorders, while MAOA-L affects an increase in serotonin. As it turns out, lifelong increases actually labialize 5-HT receptors throughout the brain. This desensitization has actually been found to uncouple neural circuits between the ventromedial prefrontal cortex and amygdala related to emotional decision making, and particularly in males irregular development of the orbital frontal cortex involved in behavioral regulation (Bortolato et al., 2011; Buckholtz & Meyer-Lindenberg, 2008; Dannlowski et al., 2009). Based on this mechanism, MAOA-L has been correlated to imbalances of threat related emotion (Williams et al., 2009), depression (Dannlowski et al., 2009; Melas et al., 2013), and substance abuse (Klein et al., 2011). It also seems to logically follow that these associations have also connected MAOA-L to general antisocial behavior. Gallardo-Pujol et al. (2013) genotyped participants and asked them to engage in a virtual reality social exclusion and aggression game. They found that


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MAOA-L participants behaved significantly more aggressively in gameplay, especially when socially excluded. Bortolato et al. (2011) genetically altered mice where they bred genotypes with various MAOA-uVTNR resistances to transcription. In one group of mice called MAO-ANeo, transcription of the enzyme was greatly reduced (an approximation to MAOA-L). In another group called MAO-AKnockout, transcription was removed almost completely. In behavioral evaluations, the researchers found that both groups were less social or interactive in comparison to normal mice. Further, the MAO-AKnockout group displayed markedly higher spatial aggression. In humans, MAOA-L is not thought to be the sole cause of antisocial behavior. Instead it is thought to set the stage for it through physical propensity. Much research has found that MAOA-L participants with increased antisocial behavior experienced a traumatic event or abusive upbringing during childhood. Such negative events in childhood are thought to trigger development down the path to antisocial behavior (Buckholtz & Meyer-Lindenberg, 2008; Gallardo-Pujol et al., 2013; Melas et al., 2013).
An interesting corollary to the effects of MAOA-L in development is the difference in physical brain structure. MAOA-L participants have been found to display diminished size and activity in the prefrontal cortex (Brunner et al. 1993; Buckholtz & Meyer-Lindenberg, 2008). Bortolato et al. (2011) found that both groups of mice modified to reduce monoamine oxidase-A transcription displayed dendritic irregularities in orbital frontal cortex (OFC) neurons. Klein et al. (2011) found that cocaine and substance users with the MAOA-L genotype were especially sensitive to losses in cortical grey matter, especially in OFC neurons. It would seem that the sensitivity of the OFC to MAOA-L would imply that as MAOA-L is associated with antisocial behavior, OFC irregularity might be part of the mechanism. This is further explored in the following discussion of the second physiological marker examined in the present study.


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OFC and Antisocial Behavior
Most students of psychology or physiology know the story of Phineas Gage. Over 150 years ago an accident with dynamite cause a railroad spike to pass through Phineas eye and exit the top of his head. He survived and made a strong recovery but displayed drastically different behavior. Gage became unreliable and behaved inappropriately in public. Nowadays it is currently thought that the region of Gages brain that suffered the most profound damage was the left OFC. This region is located on the ventral side of the brain just superior to the eyes. The OFC has been found to have many projections to the limbic system including the central amygdala. The endpoints of every sensory pathway project to the OFC. It has been theorized that sensation, memory and emotional content are integrated in this area. This is thought to function in part to give stimuli their meaning, and for learning the appropriateness of behaviors (Barbas, 2013). Many studies have found that abnormalities in the OFC lead to problematic social behaviors.
The role of OFC in social behavior is most easily understood when OFC function is impaired. Most impairments to OFC function lead to varying degrees of antisocial behavior. Generally disorganized behavior was observed in OFC lesioned mice, where they lost the ability to execute defensive or play behaviors depending on context (Pellis et al., 2006). Though more severe social deficits have been observed in simians and humans. Bachevalier, Machado, & Kazama (2011) lesioned regions of OFC in rhesus monkeys to observe differences in behavior. The results found that lesioned monkeys had more difficulty interpreting social cues, especially those conveying threat. OFC irregularity has not only been associated with more mild social effects but with actual psychoses. Histological research on neurons in the late 1970s showed that in schizophrenia patients, OFC triangle cells and pyramidal cells had developed in a


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disorganized and structurally unusual way (Beckmann & Senitz, 2002). This has since been corroborated with further research (Joshi, Fung, Rothwell, & Wei chert, 2012; Malla, Bodnar, Joober, & Lepage, 2011). Interestingly in fMRI studies of psychiatric patients, OFC deficits have been connected directly to the most socially destructive behaviors. Reduced OFC volumes explained 34% of the variance over a self-reported aggressive behavior history inventory (Gansler et al., 2009). OFC function has been found to be important in social perspective taking. fMRI imaging during a perspective taking task has shown increased OFC activation during emotional perspective taking imagery (Hynes, Baird & Grafton, 2006). Also OFC lesions have been implicated in depression. Kolb, Pellis and Robinson (2004) found that neonatal OFC lesions in rats led to deficits in social behavior that specifically inferred depression.
Likely the most commonly corroborated function of OFC in the literature is the moderation of risk versus reward decisions. fMRI research has shown that when participants with normal OFC function are asked to play a prisoners dilemma game, this area becomes very active, especially when a cycle of cooperation and reward occurs (Rilling et al., 2002). In a similar study, when participants were asked to play a reward game where they could choose between either a large but very unlikely reward, or a small but very likely reward, PET scan imaging showed increased blood flow in OFC, particularly in Brodmanns area 11 (Rogers et al., 1999). Conversely, those who have irregularities in OFC development or injury have difficulty with these sorts of tasks. In an fMRI study, where participants were asked to play a similar reward game, those with OFC lesions did not change their gameplay based on negative score feedback, despite confirmation that they were paying attention and understood the results (Hornak et al., 2004). More recently, similar findings were observed in rhesus monkeys, where OFC lesions not only led to disorganized reward learning, but also an inability for the monkeys


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to be satiated by food rewards (Bachevalier et al., 2011). These problems with risk reward assessment could relate partially to increased general impulsivity in decision making, which has been observed in participants with lesions or diminished activity in OFC (Berlin, Rolls, & Kischka, 2004; Gansler et al., 2009; Wolf, 2012).
Purpose
The present study sought to predict a measure of antisocial behavior tendency by factors correlated to OFC irregularities and MAOA-L. When examining the above review, four factors associated with these physiologies that are themselves distinct from antisocial behavior emerge as potential predictors:
1. Risk taking beyond proportionate rewards, which has been connected to OFC function (Bachevalier et al., 2011; Hornak et al., 2004; Rilling et al., 2002; Rogers etal., 1999).
2. Perspective taking, which neural imaging has connected to OFC function (Hynes et al., 2006).
3. Gender, based on observed sex differences in MAOA-L physiology (Brunner et al. 1993, Buckholtz & Meyer-Lindenberg, 2008; Williams et al., 2009). In particular, that males will express greater antisocial behavior, as MAOA-L is genetically sex linked, and that hemizygous males occur in higher probability than homozygous females.
4. Depression, OFC lesions have been shown to cause symptoms of depression (Kolb et al., 2004). MAOA-L in conjunction with childhood trauma was also shown to be a likely cause of depression (Melas et al., 2013).


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Surveys sensitive to each of these traits were selected. If the essential postulation of this paper is accurate, than these surveys will be strong predictors of antisocial tendency. Thus the hypothesis tested in this study was that surveys designed to assess risk taking, perspective taking, gender and depression when combined in multiple regression analysis, would predict a measure of antisocial behavior.
Method
Participants
Introductory psychology students (n = 148, 97 female, 49 male, and two transgender) over 18 years old (M= 23) participated in this study for partial course credit. Participants identified as 62.2% Caucasian, 11% multiracial, 8.8% Latino, 4.7% Asian, 3.4% African American, 3.4% Native American, and 6.5% various other backgrounds or did not respond. Materials
Perspective Taking.
To assess perspective taking, the Social Perspective Taking Propensity Scale (SPTP; Gehlbach et al., 2008) was used. This is a seven-item, five-point Likert scale with anchors ranging from Almost never to Almost all the time. This scale asks participants questions regarding the frequency of their perspective taking behaviors (e.g., How often do you try to look at everybodys side of a disagreement before you make a decision). This scale had been found reliable by the authors (a = .88). The Cognitive Perspective Taking Subscale (QCAEPT; Reniers, Corcoran, Drake, Shryane, & Vollm, 2011) also measures perspective taking. This is a 10-item, four-point Likert-type scale with anchors ranging from Strongly disagree to Strongly agree. Participants rate themselves in regard to statements describing perspective taking


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behaviors (e.g., I am good at predicting what someone will do). QCAEPT was found reliable by the authors (a = .85).
Risk Taking.
To measure risk taking, the Risk Behavior Attitudes Questionnaire (RBA; Dalton et al., 2010) was used. This scale is a three-item, four point Likert-type measure with anchors ranging from Very often to Hardly ever. Participants answer questions regarding the frequency of their risky behaviors (e.g., I do very dangerous things for fun). This scale was found to be reliable in the current study (a = .76). Also to assess risk taking the Risk Taking Tendency Measure (RTT; Brache, & Stockwell, 2011) was used. This is a 14-question scale where participants answer yes or no to questions regarding risky behaviors such as Do you smoke? The authors reported a reliability coefficient of (a = .62).
Depression.
To rate depression, the Center for Epidemiologic Studies Depression Scale (CES-D;
Radi off, 1977) was used. This is a 20-item, four-point Likert-type scale in which participants reported the frequency of depression symptoms (e.g., I felt that people dislike me) over a two-week period. This scale was found reliable in previous research (a = .84).
Antisocial Behavior.
To assess tendency for antisocial behavior, the Subtypes of Antisocial Behavior Questionnaire (STAB; Burt & Donnellan, 2009) was used. This is a 32-item, five-point Likert scale with anchors ranging from Never to Nearly all the time. Participants rate the frequency of their antisocial behaviors (e.g., Got into physical fights). This scale includes reliable subscales for: physical aggression (a = .84), social aggression (a = .83), and rule breaking (a = .71).
Gender.


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Gender was reported along with age, ethnicity and race in a demographics survey per APA guidelines.
Procedure
All surveys were administered using an online portal hosted by Sona Systems. Each question was presented in sequence as written within each survey. Each survey was presented in random order to avoid order effects. The only exception was that the demographic questions were always presented last. Participants signed into the system using a secure log-on, answered questions on all surveys and then logged-off The duration of this process did not exceed 60 minutes. See Figure 1 for an illustration of the study procedure.
Results
Evaluation of Assumptions
All scales were screened for missing data and outliers. For each scale z-scores were computed. Of the (n = 143) valid cases listwise, eight cases were excluded as major outliers with z-scores exceeding 3.00. To evaluate normality skewness values were computed. Scales exceeding a value of 1.96 for skewness divided by standard error of skewness were transformed (Abu Bader, 2010). For SPTP (skewness/SES = -2.63) the distribution was reflected and the square root of the scores was taken. For RBA (skewness/SES = 2.66) the square root of the scores was taken. For CES-D (skewness/SES = 3.61) the square root of the scores was taken. Finally, as all categorical variables must be dichotomous in multiple regression Reported gender was recoded into categories of male and not-male. This approach was taken as the hypothesis of this study assumes greater antisocial behavior among males, and because transgender participants cannot be categorized in reference to MAOA-L.


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Two surveys given to participants were not analyzed. To satisfy the requirements for multiple regression analysis, scales must not be co-linear (i.e., must not measure the same thing; Abu Bader 2010). For the same prediction factors, QCAEPT (perspective taking) and the RTT (risk taking) scales were found to be less preferable to SPTP and RBA respectively for reasons of reliability and validity. Both RBA and SPTP were found more reliable, with the larger discrepancy between RBA (a = .76) and RTT (a = .64) found in the present data. In the case of QCAEPT, the scale failed to correlate significantly to STAB (r = -.16, p = .07), thus violating the regression assumption of linearity.
Main analysis
To examine the hypothesis that RBA, SPTS, CES-D and Gender (male) would predict STAB scores, a multiple regression was conducted. The resulting regression found that these factors were all significant STAB predictors A2 = .32, / (4,130) = 15.38,/) < .001. The strongest predictor was RBA, which accounted for approximately 14% of the variance. SPTS accounted for another 7%, Gender for 5% and CED-D for 4% of the remaining variance. See Table 1 and Table 2 for regression coefficients. See Figure 2 for regression partial plots for all predictors.
Table 1. Coefficients of Regression Predicting Antisocial Behavior
R = .57 A2adj = .30 SE=. 29 F(4,130) = 15.38 p < .001
Predictors in the equation: SPTS, RBA, CES-D, Gender (Male)
Table 2. Coefficients of Factors Predicting Antisocial Behavior
Factors b t P
Risk Taking .36 4.87 < .001
Social Perspective Taking -.26 3.49 .001
Depression .24 3.22 .002
Male .23 3.22 .002


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Discussion
The hypothesis of the study was supported in the results. Measures of risk taking, perspective taking, depression, and gender, which were related in previous research to OFC and MAOA-L physiologies, predicted scores on an antisocial behavior measure. The strongest predictor was RBA, while all other factors accounted for relatively similar variance in scores. This infers a close predictive connection between risk taking and antisocial behavior. The results of this study reinforce the consensus in previous literature associating OFC to moderation of risk assessment, by its association thru antisocial behavior (Bachevalier et al., 2011; Homak et al., 2004; Rilling et al., 2002; Rogers et al., 1999). Another interesting result of this study was the finding of SPTP as a significant predictor of STAB scores. This is relevant because of the nonlinear relationship between STAB and QCAEPT, a scale meant to examine the same factor as SPTP. This speaks to the capriciousness of survey research. When two traits of personality are associated, through physiology or otherwise, surveys must adequately and reliably probe those traits or else the association may not be discovered. In this case evidence was found to support the association of perspective taking with antisocial behavior, and for very different assessments of perspective taking between surveys.
The main limitation of this study was the lack of ability to positively identify the MAOA-L and OFC physiologies in participants. The object of this research was to use these as physical markers for survey selection, and those surveys did predict the intended trait. However, even though an inference can be made, the successful prediction by these surveys cannot be completely attributed to their association to physiological markers, when those markers were not themselves analyzed. Another limitation of this study is that surveys were predicting other surveys, rather than surveys predicting observed behavior. The following experiment attempted


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to strengthen the overall argument in this paper by addressing the above limitations. Rather than relying on self-report, the following experiment attempted to influence and observe behavior first hand. Rather than inferring association through physiology, the following experiment primed actual physiological states as means of predicting behavior.
Experiment 2: Predicting Aggressive Gameplay by Survey and Physical Arousal
This experiment attempted to examine the essential idea of this paper from a different point of view. The first study illustrated the potential for selecting surveys related to physiological markers in predicting scores on a personality factor survey. The following experiment sought to compare the strength of a physiology, versus a common personality survey in prediction of behavior. To do this, a workable research design implied certain requirements for both the physiology and behavior involved. First, evidence of association between the physiology and the resulting behavior was required. Second, ideally the physiology would be a physiological state that could be primed. Although this has different implications for long versus short-term behavioral traits, it was preferable in research design. Priming a physiology was favorable compared to attempting to attain relevant sample sizes of naturally occurring permanent physiological traits. Third, it was necessary that the resulting behavior be described in either a clearly categorical or parametric manner. To satisfy these conditions and to dovetail with the findings of the previous study, the priming of physical arousal to affect aggression was analyzed.
Arousal and Aggression
Physical arousal is marked by aversive states of discomfort, elevated alert, or increased metabolic output (e.g., increased heart rate). Aversive states can be triggered by pain or uncomfortable environmental conditions. Increased metabolic rates can be induced through


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exercise. Physical arousal by exercise also causes activation of the sympathetic nervous system. This division of the autonomic nervous system is responsible for increased metabolic rates in skeletal and cardiac muscle. When activated, blood flow to these muscles is increased while blood flow to the outermost extremities and digestive system is decreased. These increases in metabolic output, and also an increase in alertness are partially influenced by the hormone norepinephrine (also called noradrenaline), when it is released as part of the sympathetic nervous response (Binder, Windhorst, & Hirokawa, 2009). Beyond just increased metabolic output, exercise has many health benefits such as increased strength and cardiovascular endurance. Further, for many it can be very enjoyable. Though this is not the case for everyone. The increased respiration, blood perfusion and increase in blood pressure can be one of the most stressful states commonly experienced in the body. Many experience various degrees of discomfort due to the effects of systems maintaining homeostasis during exercise (e.g., aches from the build up of lactic acid during anaerobic respiration; Xiang & Hester, 2012). During physical arousal, increased alertness and aversive sensation can influence aggression.
Physical arousal has been found to lead to aggressive behavior in previous research, and there are multiple theories explaining why this may happen. Two possible mechanisms discussed by Anderson and Bushman (2002) attribute physical arousal with alertness and discomfort. First, when aroused dominant (or well learned) tendencies tend to be magnified. So if one is provoked to aggress when already aroused, they are more likely to act on that tendency. Second, that physical arousal in some cases (e.g., exercise) may comprise aversive states. In these cases they can incite aggression just as a painful stimulus would. Another view on the connection between aggression and physical arousal was synthesized from the Two-factor Theory of emotion, where arousal can be labeled as various emotions based on available cues (Schachter & Singer, 1962).


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Based on this principle the Excitation Transfer Theory of aggression hypothesizes that arousal can be relabeled as anger when anger is provoked. This leads to anger motivated aggressive behavior after provocation (Zillman, 1988). In a study of particular interest, Anderson et al. (1995) explored two different dimensions of connection between physical arousal and aggression. The initial aim of the research was to study the hypothesis that as ambient temperature increases so does aggression. Participants would exercise in normal or noticeably elevated room temperatures while the researchers monitored their heart rates. Anderson et al. administered pre and post tests for attitudinal aggression. The researchers found that aggressive attitudes increased as both heart rates and temperature increased. The increase in aggressive attitude due to temperature is explainable simply as a reaction to an aversive stimulus. Though increased heart rate is an internal physiological state, and one that can be primed. This being the case, increased heart rate satisfied the first two requirements for this experiment: that the physiological state must be associated with the resulting behavior, and that it can be primed.
Thus the potential for predicting aggression during this physiological state of arousal by increased heart rate was investigated in the present experiment.
The Prisoners Dilemma
The requirements for priming in the present experiment were satisfied with arousal by increased heart rate. The Prisoners Dilemma Game (PDG) satisfies the third condition discussed regarding a resulting behavior. Unlike the Anderson et al. (1995) study, the present experiment sought to predict aggressive behavior rather than aggressive attitudes. The largest hurdle in regard to this is the fact that aggressive behavior is intrinsically dangerous. Research in psychology seeks to investigate behavior without causing harm to participants, so a safe way to enact aggression was required. The PDG presents an elegant solution to this problem. The PDG


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is an accumulation task (usually measured in monetary value) where the object is to accumulate the most money or score the highest. In PDG participants are given two choices: they may either defect from another person with whom they are anonymously grouped, or they may cooperate with that person. PDG creates incentive to defect from the other group member with the possibility of earning the highest possible score per turn. However, they are informed that should they make this choice, it will hurt the other group member by either greatly reducing or eliminating their payoff score. Otherwise they can choose to cooperate with the other group member. In this case they could receive a slightly reduced amount, but in this case the payoff is mutually beneficial to the other group member. There is of course a reciprocal risk in PDG of the participant having his or her own payoff reduced because of the choice from the other group member. However the reductions are comparable no matter the participants own choice. If both group members are randomly and anonymously assigned participants, there is the possibility that if one participant defects, the other will defect in response out of mistrust or retaliation. In this scenario, aggressive gameplay becomes a complicated interaction of various forces. Though when provocation is removed, participants gameplay becomes a product of their own tendencies. These scenarios have previously been achieved in research with the use of a virtual player.
Due to the anonymity of a participants other group member, this role can be replaced with a version of artificial intelligence in place of a second participant. By doing this, you can dictate behaviors in the virtual player that prevent provocative aggressive gameplay. One design that can be employed is the tit-for-tat virtual player paradigm. Descriptions of this can be found in Rilling et al. (2002) where the virtual player will cooperate by default to avoid provocation.
To maintain the appearance of a human or more intuitive other group member for participants,


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the virtual player will defect, but only after the participant defects first. A similar design, two-tits-for-tat was employed by Mokros (2008) in a study of the social behavior of psychopathic patients where psychopathic participants were found to defect significantly more often than those from the general population. This is a more conservative design where the virtual player defects only after two participant defections. In virtual player studies such as these where the provocation of the other (virtual) player has been removed, the decision to defect can be used as a measure of aggressive gameplay.
Purpose and Hypothesis
Based on general survey research practices and mind-body connection theories, both a physiological state and a survey would likely be predictive of behavior. This experiment sought to compare the predictive efficacy of both types of prediction. To test this participants aggressive PDG gameplay was examined when they were physically aroused by an increase in heart rate. These participants also completed an aggression inventory survey. The hypotheses of this experiment were that: 1. Physical arousal through mild exercise will prime aggressive gameplay. 2. A survey will predict participants aggressive gameplay. 3. An interaction where those who were primed with physical arousal will behave more or less aggressively depending on whether they scored high or low on an aggression survey.
Method
Participants
A group of mostly introductory psychology students (n = 96, 53 men, 42 women, and one transgendered) over 18 years old (M= 24) participated in this study for partial course credit. The sample was 63% Caucasian, 15% Latino, 12% multiracial, 5% African American and 5% of other or unknown backgrounds.


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Materials
Participants were assessed with the Aggression Questionnaire (Buss & Perry, 1992). The Aggression Questionnaire is a self-response aggression survey containing 29 questions regarding an aggressive personality. This survey includes subscales that score tendencies for physical aggression, verbal aggression, anger and hostility. Questions on this survey are rated on a five-point Likert scale with anchors ranging from 1 {extremely uncharacteristic of me) to 5 {extremely characteristic of me). Physical and verbal subscales ask questions about instrumental aggression such as Given enough provocation, I may hit another person. In this survey, anger is interpreted as an affective arousal and readiness for action. An example question from the anger subscale asks if it is characteristic of the participant that I have trouble controlling my temper. Hostility is interpreted in this survey as feelings of being wronged or injustice. I am sometimes eaten up with jealousy, is an example from this scale. Buss & Perry (1992) found this scale to be highly reliable with an overall alpha level of .89. Participants also were given questions regarding their demographics (i.e., age, gender ethnicity and race) per APA guidelines. These along with response sheets for the PDG were presented in a single packet.
Procedure
Participants engaged in activities to induce two levels of physical arousal. Following each activity, participants would play one round of the PDG. In the rest condition, a state of low physical arousal would be induced by a slow-breathing exercise designed to lower heart rate. Previous research has shown that when participants breathe at the rate of one full cycle of breath from inspiration to expiration per every 10 seconds, heart rate reliably decreases (Kaushik, Kaushik, Mahajan, & Rajesh, 2006). Participants relaxed and the researcher cued them to breathe in, followed five seconds later by a cue to breathe out, then five seconds later a cue to breathe in


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again, and so on. This continued for two minutes, followed by a break, then the exercise would be repeated for two more minutes. In the exercise condition, a state of increased physical arousal was induced by mild exercise to increase heart rate. Participants did an activity of their choosing where they would stand and move such that their legs were steadily in motion (e.g., jogging in place, jumping in place, or jumping jacks) at a pace they felt to be comfortable. This continued for two minutes, followed by a break, and then continued for two more minutes. Though some participants spent a considerable amount of energy in this activity, the exercise was kept light both out of concern for participants safety, and because nothing more difficult was necessary. Increased heart rate is achieved easily in humans when our legs are steadily in motion. Veins in the lower extremities act as a reservoir for blood, and during sustained muscle contractions the blood is squeezed out. This venous blood is returned to the heart, which quickly increase its rate and muscle exertion to handle the additional blood flow. This action along with further arousal also compounds with any further exercise exertion (Xiang & Hester, 2012). These two conditions and a corresponding PDG repetition for each were counterbalanced for order per experimental session.
The version of the PDG employed in this experiment was the tit-for-tat design as described in previous research (Mokros et al., 2008; Rilling et al., 2002). Due to the limited number of turns a specific adjustment to the virtual player behavior was made. In this version, on the final turn if the participant defected, the virtual player would defect on that turn. On all other turns, the virtual player defected on the turn following a participants defection. Participants were informed prior to the beginning of the game that they would be grouped with either another participant or a virtual player, but that the identity of the other group member would remain secret. As they were playing tit-for-tat, they were all grouped with the virtual player and this was


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later clarified to participants in debriefing. The rules of the game were presented to participants using a game scenario where they would compete for hypothetical money. The defection choice was described as being paid solo and the cooperation choice as being paid as a group. The amounts attached to each participant and virtual player choice pair were proportionate to those used by Mokros et al. (2008). Defections were worth eight dollars when the virtual player cooperates or one dollar when the virtual player defects (the latter would occur with two or more participant defections in a row). Cooperation was worth five dollars when the virtual player cooperates or no money when the virtual player defects (the latter would happen if the participant defects and then cooperates on the following turn). The full text of the scenario and game instructions presented to participants is shown in Appendix A.
During the PDG participants would write their choice on an answer sheet. After participants recorded their choice, the researcher would quickly inspect all the answer sheets and record each participants choice in a laptop computer. This was done within the view of the participants. The intended appearance was that their choices were being compared against each other. The spreadsheet where choices were entered was actually calculating virtual player responses and resulting scores to reduce experimenter error. The researcher would then write down the participants scores for that turn on each of their answer sheets based on tit-for-tat rules. The PDG would progress for 10 turns per repetition. The number of participant defections per repetition was analyzed such that more defections represented increasingly aggressive gameplay.
After both cycles of physical arousal condition and PDG were completed, participants completed survey responses. Participants completed the entire aggression survey first. They then filled out demographic information. When all surveys were complete, participants were


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debriefed and the sessions were concluded. See Figure 3 for an illustration of the experimental procedure.
Results
Evaluation of Assumptions
Each variable was screened for missing data and outliers. For each scale z-scores were computed. Of the (n = 92) valid cases pairwise, no cases exceeded a z-score of 3.00 thus none were excluded. To evaluate normality, skewness values were computed. No scales exceeded a value of 1.96 for skewness divided by standard error of skewness thus none were transformed (Abu Bader, 2010). Defection scores in both the relaxation and arousal conditions met these requirements. Aggression questionnaire scores were split at the median into high and low aggression survey groups for entry into the analysis.
Main Analysis
To analyze the effects of survey predicted aggression and physical arousal on aggressive gameplay, a mixed-factors ANOVA was conducted. A significant main effect of arousal condition on PDG defection was found F(i, 90) = 5.92,p = .02, r|p2 = .06, such that participants defected significantly more in the relaxation condition (M= 4.54, SI) = 3.24) than in the arousal condition (M= 3.75, SD = 3.00). This means that participants gameplay style was more aggressive immediately following relaxation than immediately following arousal. There was no significant difference found in defections between high and low aggression survey groups i, 90) < 0.001 ,p = .99, r|p2 < .001. Also no significant interaction was found between arousal and aggression survey defections 90) = 2.45,p= .12, r|p2 = .03. See Table 3 for means with
standard deviations, and Figure 4 for a chart of PDG defection scores across conditions.


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Table 3.
Descriptive Statistics of Within and Between Groups PDG Defections
Variables n M(SD)
Arousal Condition
High Survey Aggression 46 4.00(2.99)
Low Survey Aggression 46 3.50(3.03)
Total 92 3.75(3.00)
Relaxation Condition
High Survey Aggression 46 4.28(3.33)
Low Survey Aggression 46 4.80(3.16)
Total 92 4.54(3.24)
Discussion
The findings of this study do not support the hypotheses. The first hypothesis was based on the expectation that participants would play more aggressively during arousal versus relaxation. Though what was observed was exactly the opposite. The results were significant and in the reverse direction. Findings by Anderson et al. (1995) regarding physiological arousal and aggression were counter-intuitive to these results. An explanation for this discrepancy could be related to one of the limitations of this study: in this research design there is implied value for scoring higher. The object of the game is to accumulate the highest monetary score, and even if the money won is imaginary, there should be intrinsic motivation to play well. This was a consideration in the design of the virtual player such that participants would not explicitly know


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that defections lead to steadily lower scores. Though participants in the exercise condition could have been experiencing benefits of mild exercise. Theories as early as the beginning of the last century such as the Yerkes-Dodson hypothesis describe a connection between physical arousal and performance increases (Yerkes-Dodson law, 2006). It is possible, and it appeared to be the case by observation only, that during arousal participants were more attentive, focused and responsive to the score feedback from the virtual player. If this was true then participants would have been playing more optimally. The ideal play of the participants in scoring higher would overshadow any analysis based on aggressive tendency. This would then account for yet more evidence for theories related to Yerkes-Dodson and arousal induced performance increases. This principle of optimal play also relates to another limitation of this study, which was the small number of PDG turns, and that participants were aware of how many turns there would be. As described by Dawkins (1976), if participants are aware of when they will reach the last turn of a PDG, this awareness is likely to affect their defections by offensive or defensive strategy. Strategic behaviors such as these present a significant confound, especially when disbursed over a small sample of turns.
The second hypothesis of this study was that groups defined by aggression survey scores would predict aggressive gameplay. Again this was not supported and indeed seems very odd. Although the essential concern of this paper is the capriciousness of survey data, it would seem extremely unlikely that the vast majority of those who were categorized into the high aggression survey group were not relatively aggressive in comparison to those in the low aggression survey group. This would be especially true considering that there were no outliers. Thus no cases were likely pulling the cut point between groups away from central tendency. Since there is survey evidence of general aggression in participants grouped into the high aggression group regardless


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of their PDG gameplay, the sensitivity of PDG to aggression is called in to question. Findings from Mokros et al. (2008) seem contrary to this idea as psychopathic patients were found to defect more often then general population participants. Further, to defect from a group at the detriment of the member of that group is by definition an aggressive antisocial act. However, psychopathy does not imply aggressive behavior in every situation. Another common trait would be manipulation, which could be very relevant to the way one might play a PDG. It was actually theorized by Mokros et al. that many defections made by psychopaths were following manipulative attempts to lull participants into cooperation. Also, not all antisocial behaviors are based in social aggression. Various different subtypes of antisocial behavior based in physical aggression, social aggression or rule breaking have been delineated (Burt & Donnellan, 2009). Future research could possibly attempt a similar PDG manipulation in concert with scales meant to assess these subtypes.
To address the third hypothesis of this study, no significant effect of arousal based on aggression group was revealed, however the statistic was approaching significance. In a way however, to find significance on this dimension, with a bigger sample size for instance, would still not be practically important with such a small effect. Though interestingly, arousal condition defection scores between aggression survey groups begin to more closely approximate the hypothesized results. During arousal, the high aggression survey group defected more aggressively than the low aggression group. These differences are trends and not statistically significant but may be worth future investigation.
The main limitation of this study is the very nature of aggressive behavior as it is intrinsically dangerous. This behavior was selected due to an established connection in the literature to a physiological state. Though to carry out aggression is to attempt harm: one of the


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very outcomes that ethical research endeavors to avoid. PDG allows participants to carry out an aggressive choice in a safe environment, though it may simply not be a very strong approximation to ones aggressive behaviors. Future research then could find a more easily measured example behavior with a strongly correlated physiological state, or could identify another safe and more precise way to measure aggressive behavior.
Conclusions
Predicting Antisocial Behavior
In relation to the thesis that surveys could be made more reliable when selected in reference to physiological markers of behavior, the studies undertaken for this paper offer promising albeit mixed results. The most coherent message can be found in reference to the first study. Here several predictive factors, risk taking tendency, perspective taking, depression and gender, were selected based on physiological correlates to antisocial behavior. As the results show, every one of these factors contributed to the prediction of an antisocial behavior inventory. In this case it can clearly be said that one thing (or group of predicting factors) predicted the other as expected with little ambiguity. Though the lesser or complete lack of ability to use QCAEPT and RTT in predicting antisocial behavior reflects the very problem that this paper attempts to address. In this case the assertions of Burless and De Leo (2001) that consistency between surveys measuring the same construct should succumb to more stringent standardization is highlighted. In the case of the meta-analysis that they performed, they were not able to compare results of different surveys within a construct from multiple studies to answer questions about group differences. In the present study, predictive surveys were not only different in the resulting data yielded within one group, but also in the case of perspective taking, one survey was not even eligible for analysis while its analog was and significant. Whether or not survey


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research trends toward more physiological bases, a need for greater standardization within constructs is clearly evident in this study as well as in previous literature.
In regard specifically to antisocial behavior, any advance in prediction or early detection of antisocial tendencies is beneficial. Planty and Truman (2012) reporting for The Bureau of Justice Statistics showed that between the years 2010 and 2011, the rate of violent victimization, which includes rape, theft and assault victimization, increased 17%. The rate of property victimization, which includes burglary, motor vehicle theft and property theft, increased 11% over the same duration of time. Antisocial behavior is particularly difficult to analyze experimentally. Though it is also an excellent example of why it is important to attempt research regarding new ways of identifying those at risk for life-long problems. Antisocial behavior is destructive to the conventions that allow us all to live together peacefully. Further, it not only victimizes cooperative members of society, but the perpetrators of antisocial behavior themselves. Those with the tendency to act against laws or victimize others, by societal recourse often experience a low quality of life even if they are not punished within the justice system. Rather than assigning blame and exacting retribution, the more positive solution is to better understand how to find those who need help before it is too late. Some of those who oppose the use of the PHQ-2 and PHQ-9 in New York for instance, argue that mass survey screening for risk factors creates more problems than the data is worth. Surely, in the case of the New York depression screening, their point is valid as the efficacy of PHQ screening in detecting depression is probably greatly attenuated by the mode of administration. Further it may actually cause harm. Though unsound investigation of these risky or dangerous behaviors is the very reason to attempt to generate more valid and effective forms of investigation. If this can be found in physiological bases, every effort should be made to develop it.


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Aggression
As is the case with antisocial behavior, its corollary in aggression is difficult to safely analyze experimentally. Though unlike in the first study, the aggressive gameplay outcomes of the second experiment are harder to interpret. This experiment was in an unexpected way supportive of the central thesis regarding prediction by physiology. The intended argument based on a positive finding in the second experiment would be that: in supplement to the prediction of a personality trait by surveys correlated to physiology from the first study, here immediate behavior was predicted by the relevant physiology at hand. As previously outlined, the hypotheses of the second experiment were not confirmed. However the argument based on the results of this experiment is still relevant to the thesis of the paper. Based on a physiology at hand, a difference in behavior resulted. It was certainly not the behavior that the initially reviewed literature would suggest; though when the manipulation was re-examined a different body of literature allowed for a reasonable explanation of the results. This illustrates two important points: the objective nature of physiology and the further need to develop prediction based upon it. If physiology is going to cause an outcome in a specific scenario, it happens in an objective manner. It is not like an individually conceived survey where the properties of a construct can be endogenously reinterpreted subjectively. It has concrete properties anchored in physics and chemistry. This is not to say that a single physiology cannot lead to many subjective outcomes under various conditions. In fact, that is the nature of science, to study the application of any given thing in reference to any other given thing in existence. Here the second point applies. Just as we would with any analyzed molecular substance, we can subject a physiology to different conditions and see what behavior results. When we find stable and reliable scenarios and traits that result, we can apply them practically. This is actually the very basis of good


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psychometrics, and great research has been done in the past to correlate personality directly to behavior based on this sort of observation. The essential argument of this paper is that physiology is one more useful step up the ladder of understanding human behavior. With such an elaborate task in this endeavor, every reliable tool at hand is valuable.
Future Potential for Predicting Behavior Through Physiology
Further honing of survey research by physiological correlates will likely be facilitated by progress in the understanding of neurobiological mechanisms. In the field of computational neuroscience for instance, discoveries continue to be made leading to a more precise understanding of how the essential neuronal functions of the brain lead to behavior. For decades physiologists have analyzed the nervous and endocrine systems, examining distinct features leading to behavioral outcomes. More recently with the advent of new analytical techniques and technologies, even the neuronal basis for essential decision-making processes are beginning to be understood. For instance Newsome, Britten and Movshon (1989) performed single neuron recordings in the extra striate area MT of monkeys. During recording, monkeys were presented with a task where they were shown dots in motion. A fraction would move randomly and a fraction would move in one direction. The monkeys had to make a saccade to indicate which direction they had decided the coherent dots were moving. These recordings identified single neurons that were selective for a given direction and their anti-neuron selective for the opposite direction. The researchers found that the neuronal firing rates of direction selective neurons to be reliably indicative of the indicated stimulus direction. The monkeys choice closely corresponded to these firing rates as well. To further explore the neural mechanisms of decision and behavior Mazurek, Roitman, Ditterich and Shadlen (2003) used single neuron recordings in an area of the parietal lobe of Rhesus monkeys suspected to be related to visual discrimination


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decision-making. These neurons were found to be selective for the integral of corresponding MT directionally selective neurons firing over time. The study found that when these integrating neurons reached a certain threshold firing rate, the monkey would make a decision in the corresponding selected direction. In this study we see an example of a testable model of very basic decision making, and resulting behavior at the neuronal level. To have found that individual cells lead to behavioral decisions seems impressive enough, though subsequent studies have gone much further. Using fMRI imaging, neuroscientists can record the metabolic activation of the entire brain concurrently during a task or stimulus to infer the function of specific regions. Soon, Brass, Heinze and Haynes (2008) performed recordings of this type on human participants who were engaged in a similar decision task. Although in this study, rather than simply responding to a discrimination problem, participants arbitrarily made a simple choice between which button on a keypad they wanted to push on their own time. The only restriction was that once they had made the conscious decision about when to push the button and which one, that they press it right away. Here a most basic willful choice was being analyzed and what the researchers found was striking. Not only did the researchers find cortices in the brain that reliably moderated these choices, they found that they could predict these choices by the activation of neural cortices before the participants even knew they had made a decision. In fact even when adjusting for any delay that the participants reported between when they made a conscious decision and pressed the button, the researchers could see the genesis of the still unconscious decision up to 10 seconds before it was made. Further, they could reliably predict which button was to be pushed by about six seconds before participants consciously knew that they had chosen it. Aside from the fairly alarming implications that these findings have regarding the biological genesis of choice versus conscious freewill, the highly predictive potential of


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physiological techniques that exist even today are illustrated. Even more recently, these types of techniques have gone from reductively analyzing individual simple behaviors, to more complex generalization about personality. Di Domenico, Fournier, Ayaz and Ruocco (2013) imaged the brains of participants using fNRIS another process that records metabolic neural activation. In this study they examined activation of the medial prefrontal cortex, an area of the brain known to play a role in what the researchers and most in the social sciences refer to as the self. They asked participants to choose between possible vocations (e.g., a choice between being a dancer or a chemist). Having asked participants about what type of vocations they would find most satisfying in advance, the researchers tried to present them with either easier or more difficult decisions during imaging. It was found that, the medial prefrontal cortex was significantly more active during difficult decisions. The researchers inferred that they were observing cortical processes of the brain that enhance coherence in the self by moderating self-satisfaction decisions in reference to self-knowledge. Of course findings such as this are not as clear-cut as a direct numerical relationship between the firing rate of a single neuron and a simple behavioral result (e.g., Mazurek et al., 2003). However, again it implies the potential for analyzing complex physiology in reference to (in this case) fairly abstract concepts of behavior. Research of this type is taking the world further and further toward an understanding of the physical mechanisms of the mind. In doing so, this research informs us of physical scaffolding to behavior which can and will allow a more reliable prediction of behaviors.
The essential problem with todays inferential physiological techniques is that they are monetarily and logistically prohibitive. When it comes to large-scale applications in behavioral prediction, they are just not practical. To simply ask every child who might be at risk for developing an antisocial personality to spend weeks of his or her life in a neurology lab


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performing whatever sort of thought and mental dexterity task a researcher could conjure would be ridiculous. The potential lies in reliable principles that can be applied to practical research.
As previously discussed, survey practices are the norm for large-scale research. Their specific intention is to gather a large number of data points across expansive samples of participants such that as samples grow larger, the logistical cost remains comparable. Survey research can be done well when the research design and modality is developed in reference to the topic appropriately. The constant challenge to survey research is the subjective experiences of participants and the consistency of the construct between studies. Statistical analyses applied to survey data are specifically designed to adjust for individual differences between participants in a normal fashion. Though they do not account for common differences experienced by entire subgroups within a sample. Stereotype threat can be an example of this, where it has been shown that if a participants group membership is made salient, they will answer survey questions differently to avoid confirming their own stereotype (Steele & Aronson, 1995). Further, these tests for the most part begin with the assumption of a representative sample, and as shown in Burless and De Leo (2001) often key demographics are over or under represented. Then when statistical assumptions are met, often studies cannot be compared because of the subjective inconsistency between constructs within a topic. Consistency and standardization must be a priority of large-scale research in the future to attain the most meaningful and worthwhile results. As we see in the case of antisocial behavior, the stakes are too high in many cases for those in the behavioral sciences not to demand the absolute best practices of their discipline. When standardization does occur, it seems only practical to root as much of it as possible in the most consistent concrete traits and influences that apply to all humanity across groups.


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Although science is a long way from analyzing someones neural function conveniently in the day-to-day, it has already outlined many underlying physical influences on behavior that most of us share. These findings will continue to grow more relevant and expansive. It was even shown within this paper that using only published resources for reference and surveys selected based on physiological markers, a personality trait could be predicted with very modest logistical cost. It was also shown that immediate behavior could be primed based on physiological principles. The power of a concerted effort across research disciplines to apply knowledge of physiology in an effort to increase the reliability and validity of survey or other common forms of research would dwarf the fairly modest observations described here. Considering the weight that research findings carry in the world, and the needs of those who could benefit from valid research findings, any improvement to the practices of this research is well justified.


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Figure 1.
Procedure for Online Survey Study
Random Order
Surveys
Participants logged on the Sona Systems web portal and were presented six of the above surveys in random order. After completion of these surveys participants completed demographics questions and logged off


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Figure 2.
Regression Plots of Directional Relationships Between Criterion and Predicting Factors Partial Regression Plot of Antisocial Behavior as Predicted By Risk Behavior Attitudes
Partial Regression Plot of Antisocial Behavior as Predicted By Social Perspective Taking


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Figure 3.
Arousal and Prisoners Dilemma Experiment Procedure
Participants completed
aggression survey and demographics
Participants engaged in both five minutes of light exercise followed by one repetition of prisoner's dilemma game, and five minutes of slow-breathing relaxation followed by one repetition of prisoner's dilemma game. These two sequences occurred in counterbalanced order per session. After both sequences were completed, participants completed the Aggression Questionnaire and demographics questions.


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Figure 4.
Prisoners Dilemma Game Defections for Arousal and Aggression Groups
Prisoners Dilemma Game Defection Means by Group
Means for PDG defections per median-split high and low aggression survey groups. These graphs illustrate that there were no significant differences between aggression groups within each arousal condition. A significant difference was observed such that participants defected more during relaxation versus arousal.


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Appendix A
Instructions for the Prisoners Dilemma Game as presented to participants:
You are trying to win imaginary money for your favorite cause, this could be a charity or the phone youve always wanted, any cause you want. You will be anonymously grouped with another player who is also trying to win money for their favorite cause as well. Neither of you is trying to win more than the other, you are each trying to win as much for your cause as you can. This player may be another participant or a virtual player, but the identity of the other player will remain secret. To win money you will have two options for each round. You will have the option to play each round by either getting paid as a group or getting paid solo. If you choose to go solo, you could win the largest sum per round of $8, but only if the other player in your group chooses to get paid as a group. In this case the other player receives no money. If the other player in your group also chooses to go solo, in this case you both earn only $1 each. You can also choose to get paid as a group; in which case you could earn a sum of $5 per round, but only if the other player also chooses to get paid as a group. In that case, the other player also earns $5. If the player chooses to go solo in this case, they earn $8, and you earn no money for that round. There will be a chart at the end of your answer sheet to remind you of the possible payoffs. When I indicate, you may write down your first choice on the line provided. I will record the answers, provide your scores for that round, and the task will continue.


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Predicting Antisocial Behavior Using Correlates of MAOA Gene and Orbital Frontal Cortex Physiologies by Eric Klein An undergraduate thesis submitted in partial completion of the M etropolitan State University of D enver Honors Program May 2014 Dr. Chad Mortensen Dr. Cynthia Erickson Dr. Megan Hughes Zarzo Primary Advisor Second Reader Honors Program Director

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Running head: SURVEYS, MAOA L & OFC 1 Predicting Antisocial Behavior Using Correlates of MAOA Gene and Orbital Frontal Cortex Physiologies Eric M. Klein Metropolitan State University of Denver

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SURVEYS, MAOA L & OFC 2 Abstract Various factors affect the capriciousness of survey data in wide scale research : Participant response rates are decreasing (Dey, 1997) considerations for sensitive topics are overlooked (Pryor, 2004 ), survey modality can be inappropriate, and inconsistency of construct is pervasive across studies (Burless & De Leo, 2001) Calls for i ncreased consistency in survey research have been made. In this paper it is suggested that to increase empiricism and consistency, a basis in the physiological bases of survey research could be utilized. Two studies are presented to demonstrate the potenti al for this research. In the first, surveys selected for factors related to orbital frontal cortex abnormalities and the MAOA L genotype are used to predict antisocial behavior by survey as this behavior correlates to both of these physiologies. All selec ted factors: risk taking, low perspective taking, depression and gender, were found to be significant predictors. Results indicate strong potential for survey selection by physiological correlates. In a second study, a physiological state of arousal is pri med with exercise induced increased heart rate Physical arousal has been connected to aggression (Zillmann, 1989) Physical arousal is contrasted with median split groups based on an aggression survey for predicting aggressive prisoner's dilemma gameplay. Relaxed participants played more aggressively, while survey groups were not significant. Results are discussed in reference to survey best practices. Topics are relevant to psychometrics and research methods.

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SURVEYS, MAOA L & OFC 3 Predicting Antisocial Behavior Using Correlates of MAOA Gene and Orbital Frontal Cortex A basic goal of the social sciences is behavioral prediction through research. A great deal of discussion occurs regarding the reliability of conventional research methods and their efficacy. In particular, large scale research data is typically conducted by survey. Although a great amount of care is taken to develop these instruments, they are often indented to investigate psychological constructs which are constantly changing as new discoveries are made. As this is the case, several different surveys may be used to investigate one trait as time progresses, and this lead s to inconsistent findings in the literature (Burless & De Leo, 2001) Further, several other major obstacles in survey research obfuscate findings such as participant non response and problems of modality and sensitive topics. To overcome these obstacles t his paper suggests that as humans are largely biologically similar ( Dupre, 2008 ), a possible route to increase the reliability of survey research is to select and develop surveys based on physiological correlates to behavior. Mind, body, and social context influence each other interdependently ( Susman 2001) This paper will demonstrate that due to these connections the predictive efficacy of survey research can be increased by the use of physiological correlates. To illustrate the potential for prediction based on physiology, two studies will be presented. The first uses the example of antisocial behavior which has been well correlated in previo us research to two physiologies: the low transcribing genotype for monoamine oxidase A gene, and irregularities of the orbital frontal cortex. The connection between these physiologies and antisocial behavior will be explained, as will the connection between these physiologies and four other factors: risk taking, perspective taking, depression and gender. These fact ors were used to attempt to predict self reported antisocial behavior. The results of this study will be discussed in reference to the strength of prediction by physiological correlates.

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SURVEYS, MAOA L & OFC 4 The second study described is an experiment where a physiological st ate was used in an attempt to predict behavior. The efficacies of physiology versus a survey examining particular personality traits are compared in predicting a behavior relevant to both. Specifically, aggression has been connected to physical aro usal ( An derson, Deuser and DeNeve 1995; Zillmann, 1988) In this experiment participants are primed with arousal by exercise induced increase in heart rate and surveyed for aggression. The arousal condition and the aggression survey were used in an attempt to pre dict participants' aggressive gameplay on a prisoner's dilemma task Again, the results of this study will be discussed in reference to prediction by physiology. Before introducing these studies however a clear understanding of the problem is required. Th e following sections will describe proliferation of large scale survey research, and problems that can arise within this type of research. Threats to the research reliability and validity are discussed as well as a need to increase consistency in surveys. The solution to this problem by increasing the physiological bases of surveys is discussed initially in reference to existing literature and then in reference to the present studies. Problems in Survey Research I t is nearly impossible to create a survey t hat perfectly resembles the characteristic for which it intends to study in any given population (Lohr, 2008). This is clearly a problem to overcome for researchers who wish to predict behavior using survey data. Survey design and efficacy is particularly important when the resulting data is used to decide clinical, institutional, or political outcomes. Assessment in these and many areas has become increasingly survey based (Porter, 2004). The estimated total number of published research articles based on survey data has increased three fold from 1980 to 2010. These articles are used to determine policy in virtually every area of business and government (Sa§enroth, 2013). Due to the vast proliferation

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SURVEYS, MAOA L & OFC 5 of research by survey, instances of survey mismeasuremen t and misapplication have become more frequent. A prominent example of questionably applied large scale survey research began in 2003. The Bush Administration budgeted $20 million dollars to fund an initiative to pilot increased institutional mental health screening in several states including New York. Patients visiting a general medical practitioner for almost any ailment would be screened for depression. Although psychiatrists and psychologists largely dismissed the concerns of opponents to the initiativ e, politicians and advocates for the disabled spoke out largely against it, citing concerns of privacy and misdiagnosis (Santora & Carey, 2005). Although this example invokes questions regarding survey research of sensitive topics, it specifically highligh ts the social importance of research best practices. To carefully explore potential pitfalls of survey research practices, the issues of participant non response, sensitive topics, modality, and construct will be discussed. Participant Non response: a Thre at to Sample Representativeness The modality, or medium of survey research is an important issue regarding methods for gathering sound data, especially as the demand for data increases. Although an intrinsic advantage to survey research is the ability to quickly and conveniently gather d ata, new issues have arisen as survey distribution has evolved. For instance, as the use of surveys has increased, response rates have fallen. In one meta analysis, a sample set of national surveys ranging from the 1960's to the 1980's was analyzed. Over t hat time response rates dropped from an average of 60% to only 21% (Dey, 1997). The downward trend in survey response appears to be due to difficulties in communication of the intended material, and to participant's unwillingness to divulge information (Po rter, 2004). Unwillingness to share information could be related to concerns about loss of privacy in the modern era of big data. Natural Resources Canada polled 2,200 people about their attitudes

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SURVEYS, MAOA L & OFC 6 regarding online data collection just prior to the launch of Google Street View. The response was indicative of overall concern for individual privacy. More than half of the respondents indicated that they had experienced violations of privacy online, and 80% were concerned about the future risk of loosing their privacy. Only 18% indicated that they trusted corporations with the data that they collect (Schmidt, 2010). Users of digital services or network electronics are asked to agree with terms that allow providers to record data in areas including: users' mobile location, application usage, browsing behavior, and frequent searches just to name a few (Chen, Mao, & Liu, 2014). Constant awareness that data is being collected from each person during most moments of the day might not only cause people to be more judic ious about the facts they choose to divulge when surveyed, it could also cause mental fatigue. Research has indicated that if participants are asked to respond on a greater number of survey questions, that due to fatigue they respond less frequently. This is especially true when participants are given several different surveys in succession (Porter, Whitcomb, & Weitzer, 2004). It would not be unreasonable to partially attribute the cause of diminishing response rates to the fatigue experienced by the modern lay person who is responding to requests for data, and providing covert data constantly everyday. An in depth exploration of the causes of participant non response would be beyond the scope of this paper. The relevant point is that non response is an inc reasingly serious problem in survey research. Various research designs dictate specific sample sizes to satisfy the required statistical power for an analysis. Sufficient response rates assure confidence in any given research finding. If response rates ar e low, it compromises the ability to generalize the findings of a survey to the target population (Burless & De Leo, 2001). For example in an organizational study, participants' nonresponse on a workplace attitude survey negatively correlated to

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SURVEYS, MAOA L & OFC 7 workplace satisfaction (Fauth, Hattrup, Mueller and Roberts, 2012). The researchers thus learned less from a group of participants who they were trying to analyze, specifically because of the nature of the survey. Sensitive Topics: a Cause of Non response and Harm A special category of surveys related to participant non response and overall research design obstacles is that of sensitive topics. Subjects that comprise sensitive Topics surveys include: violence, drug use, trauma, sexual behavior, violations of polic y, socially undesirable behavior, and other related topics (Pryor, 2004). In these cases, not only can non response increase, but priming effects of asking sensitive topic questions could represent an experimental confound. The validity of sensitive topic survey responses is difficult to measure. Questions in sensitive topic surveys may cause immediate anxiety in the respondent, and further raise concern in the respondent about their privacy (Pryor, 2004). One factor that magnifies sensitive topics effects on the mentality and response rate of the respondent is the proximity of the researcher. In studies of drug and alcohol abuse, participants using self administered surveys have displayed higher survey response rates versus participants who were responding to surveys that were administered by a researcher face to face (Aquilino, 1994). The difference observed between modalities is generally attributed to social desirability (Tourangeau & Smith, 1996; Turner, Lessler & Gfroerer, 1992). Increasing the privacy of the respondent can increase response rates on sensitive topic surveys. A study in Holland compared response rates on a sensitive topic survey between those who were surveyed in person and those who were surveyed by mail. The correspondence participants responded much more frequently. However, their overall response rate was still only 64% (Nederhof, 1985). With seemingly intrinsically low response rates, the design and sensitivity of sensitive topics studies is thus paramount to research design.

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SURVEYS, MAOA L & OFC 8 Modalit y: Medium of a Survey Matters The previously mentioned mental health screening initiative in New York was under debate out of concern for patients' rights and privacy. This however, could also be an example of a less than optimal survey modality (or mediu m) for studying the intended personality trait. In this case, New York City was administering the Patient Health Questionnaire 9 (PHQ 9; Kroenke & Spitzer, 2002) to adult primary care patients. This survey presents patients with nine questions designed to diagnose depression by DSM IV criteria such as whether he or she recently had "Thoughts that you would be better off dead or of hurting yourself in some way." This question is specifically referring to suicide ideation, which falls within the area of sensi tive topic surveys, and invokes research considerations previously discussed. One might not expect to have to evaluate his or herself on this level during a visit to their primary care physician, nor to deal with the anxiety involved with sensitive topics questions. Though as of 2007, the New York Department of Health had issued a general recommendation to doctors that they administer a depression questionnaire to all adult patients. Further, they added a two question pre screen measure, Patient Health Ques tionnaire 2 (PHQ 2) to prequalify patients before administration of the PHQ 9. The PHQ 2 asks only for a yes or no response to whether patients had felt "Little interest or pleasure in doing things," or if he or she was "Feeling down, depressed, or hopeles s" (NYC Dept. of Health and Mental Hygiene, 2007). Considering the tendency for patients to respond less on ST surveys, especially when in proximity to an assessor, it seems unlikely that these two questions would illicit representative responses from pati ents who are expecting a normal check up from their doctor. The New York Department of Health asserted that the PHQ 9 was not intended for formal diagnosis, but instead to guide recommendations for further screening of those who were found to be at risk fo r depression (Santora & Carey, 2005).

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SURVEYS, MAOA L & OFC 9 Although this somewhat answers the concerns of those who were in political opposition to these practices because of misdiagnosis risk, it does not address two important research design issues: 1. There is the possibili ty that non response to a sensitive topic survey in this context could influence the results, such that many if not most at risk go undetected. 2. Considering the anxiety associated with sensitive topics content, and possible lack of detection of depressio n in respondents, there is a considerable risk to respondents compared to the potential benefits. This example not only illustrates problems of survey modality in context of a research topic, but also illustrates the potential harm involved with survey pra ctices. Construct: a Threat to Validity The misrepresentation or inconsistency in analysis of psychological constructs through survey research presents threats to research reliability and validity. Appropriate categorization of psychological constructs wi thin survey items goes far beyond the breadth of this paper due to their intrinsically subjective nature. Though examples of inconsistencies between studies attempting to research or validate findings over like topics are not difficult to find. The finding s of a meta analysis by Burless and De Leo (2001) examining large scale survey studies about suicidal behavior presented in depth examples of such problems. Burless and De Leo reviewed 30 publications released between 1974 and 1999 that reported statistics from surveys examining suicidal behavior. One significant problem the researchers outlined was in reference to age and demographic of the sample population. Due to the assumption that suicide would be relevant to different age groups in different ways, th ere was a distinct bias in the number of questions related to certain subtopics within surveys targeted to age groups. In general population surveys, most questions were found to inquire about past behaviors in reference to suicide ideation. Surveys intend ed for adolescents however, mostly asked questions related to present or future

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SURVEYS, MAOA L & OFC 10 potential suicide attempts (e.g., "I would like to kill myself"; p. 119). Burless and De Leo found that surveys targeted towards the elderly showed a bias in the number of ques tions related to value of life or "Worthlessness of living" (p. 120). Although different topics can have differing meanings across age groups, over representation of any subtopic to specific sample populations presents a problem for comparison or generaliz ability across groups, and across studies. Between surveys targeted to the general population, Burless and De Leo (2001) found that items inquired about differing degrees of suicide ideation, and this made comparison for reliability impossible. Only a few studies investigated responses over isolated degrees of ideation. These studies however differed in their definitions and criteria for ideation and were thus also incomparable to other research. Without comparable data, reliability cannot be assessed. Fur ther, without consistent definitions, construct validity is not present. Burless and De Leo (2001) found that among research focusing specifically on suicide attempts, many studies failed to properly investigate this topic as an actual event. Studies that investigated this topic from a conceptual approach were inconsistent in their categorizations of levels of intent. Items in these studies would vary in their description of levels on the range from cry for help intent to intent for absolute self destructi on. It was also found that when researchers attempted to study the frequency of suicide attempts, the time periods in question were inconsistent. Further, the definition of what constituted an attempt varied. In some studies intently pointing a gun at his or herself would be called an attempt, where in others self injury would be required. In these examples, threats to the valid analysis of an actual behavior have occurred due to inconsistencies in construct between surveys. Empirical Consistency

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SURVEYS, MAOA L & OFC 11 In the B urless and De Leo (2001) study, the researchers suggested that survey research should be done from a synchronized approach to obtain more comparable and meaningful outcomes. They further suggested several best practices specifically relevant to the study o f suicide. Though they also make the suggestion that when researching a construct, surveys identical to those used in previous research should be utilized whenever possible. This would allow for both consistency of construct between studies, and comparison of results across various samples. Consistency of both construct and instruments designed to analyze them would seem relevant to the scientific process in almost any area. The problem with this suggestion is that psychological research is intrinsically su bjective. To reductively restrict the number or type of surveys investigating any one topic could affect blindness to some facets of personality, behavior or lifespan development. Here a paradox is presented where a lax or expansive philosophy leads to pro blems of validity, or a reductive philosophy could lead to problems of sensitivity. A less absolutist approach might examine isolated strategies where subjectivity can be reduced without ignoring relevant groups or relevant data. The scientific process its elf is predicated on empirical observations that can be consistently replicated. Hence a sensible empirical approach to research could be found in that which is consistent through all populations, specifically physiology. A Solution in Physiology The theory that physiology, mind and behavior are inexorably linked is accepted to varying degrees throughout the various disciplines of psychology. Early empirical research linking the workings of the brain with psychology was outlined in the nineteenth c entury by William James (James, 1962). The James Lange theory eventually followed, which assumed that physiological responses to stimuli cause emotion. Later another hypothesis emerged: the Cannon Bard theory that assumed emotional responses result in effe cts on physiology

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SURVEYS, MAOA L & OFC 12 (Roeckelein, 2006). A further refinement of these theories was the Two factor Theory of emotion, where emotion arises from attributions of physical arousal based on immediately salient cues (Schachter & Singer, 1962). These theories were precursors to modern branches of psychology such as behavioral genetics and neuroscience that are centered upon the study of the mind body relationship. Modern iterations of mind body interaction theories assume a dynamic interdependent relationship unifyi ng the physiologies of brain and endocrine function with lifespan development, personal experience, and social context (Magnusson, 2001). Susman (2001) described antisocial behavior as an example behavior type explained well by this sort of interaction. Re search by Susman correlated lower levels of the hormones adrenaline and cortisol to antisocial deficits in emotional and physical regulation. This is only one example of an increasingly large body of findings across several disciplines, which illustrate th at the mind and body are linked and influence one another. The most important precept in considering physiology as a guide for psychological research is its consistency. The completion of the sequencing of the human genome showed that human DNA is 99.9% i dentical (Dupre, 2008). Essentially, we are all built in a very similar fashion. Considering the connection between the mind and body, people experience similar psychological effects and display similar behaviors based on similar physiologies. We experienc e similar effects when something in our body is abnormal. Thus specific physiologies could be used potentially as markers for consistency in survey research. The following text of this paper will illustrate the potential for reliability in this type of res earch by describing two studies: 1. A study that predicted scores on a personality measure by surveys related through physiological markers. 2. An experiment that contrasted the efficacy of a survey versus a physiological state in predicting a behavior.

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SURVEYS, MAOA L & OFC 13 S tudy 1: Predicting Antisocial Behavior Scores With Measures of Risk Taking, Perspective Taking, Depression and Gender. Due to strong correlations in physiology, antisocial behavior was the personality trait under analysis in the first experiment discussed here. Numerous studies have identified the strong continuity of these behaviors within individuals over time, and they are approximated to personality (Bonino, Cattelino, & Ciairano, 2005). In fact, these behaviors are identified as diagnostic criteria fo r antisocial personality disorder (ASPD), a clinical personality disorder outlined in the Diagnostic Statistical Manual of Mental Disorders ( DSM V 2013). Antisocial behavior is defined by aggressive or impulsive actions that violate established social rul es, norms or laws, and is often referred to in contrast to prosocial behavior ( APA Dictionary of Psychology 2007). The ASPD diagnostic criteria outlined by the DSM V also yield examples of the behaviors associated with an antisocial personality: A pervas ive pattern of disregard for and violation of the rights of others, occurring since age 15 years, as indicated by three (or more) of the following: 1. Failure to conform to social norms with respect to lawful behaviors, as indicated by repeatedly performing a cts that are grounds for arrest. 2. Deceitfulness, as indicated by repeated lying, use of aliases, or conning others for personal profit or pleasure. 3. Impulsivity or failure to plan ahead. 4. Irritability and aggressiveness, as indicated by repeated physical fights or assaults. 5. Reckless disregard for safety of self or others. 6. Consistent irresponsibility, as indicated by repeated failure to sustain

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SURVEYS, MAOA L & OFC 14 consistent work behavior or honor financial obligations. 7. Lack of remorse, as indicated by being indifferent to or rationalizing having hurt, mistreated, or stolen from another... ( DSM V 2013, 301.7 F60.2) An important distinction should be made, that the present study does not seek to diagnose, nor analyze ASPD in a sample population. ASPD is typically studied using research materials or diagnostic techniques that are not employed in this study. However ASPD is a named personality disorder and its diagnostic criteria and epidemiology comprise relevant examples of antisocial behavior. Further examples of the traits of someone with tendency for antisocial behavior can be observed in previously distinguished subtypes of antisocial behavior. Those who are high in physical aggression for instance, find affective self regulation difficult, and engage in actions intended to p hysically hurt others. Those who are very impulsive tend to engage in theft or rule breaking. Those who engage in social aggression use social relationships as a means of harming others. Though the latter case does not involve law breaking, it does imply a n antisocial lack of remorse (Bonino et al., 2005; Burt & Donnellan, 2009). While common definitions of antisocial behavior are accepted, prediction and risk factors involved are under debate. Likewise the current DSM V criteria for the diagnosis of ASPD a re also under review (Glenn, Johnson, & Raine, 2013). Thus outlining strong predictive factors related to this type of personality are beneficial on a wide scale. Epidemiology of Antisocial Behavior The prevalence of crime in the United States and other c ountries speaks to the impact that antisocial behavior can exert. There is of course a distinction between those with personalities predicated toward antisocial behavior, and those who commit isolated criminal events. However, the two do appear to coincide even to the extent of full personality disorders. In a review of

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SURVEYS, MAOA L & OFC 15 epidemiological research studies conducted across many countries between 1980 and 1998, the rates of ASPD for instance, were found to consistently occur in general sample populations at the rate of between 1% and 3%. The rates of ASPD found in prison populations ranged from 40% to 60%, and was found to be the most prevalent personality disorder among inmates (Moran, 1999). Within the general population, antisocial behavior has been found to r elate to age. Rates of antisocial behaviors have been found to peak among people in their early to mid twenties, and to persist through the mid thirties where the frequency of such behaviors becomes increasingly less common (Bonino et al., 2005). Antisocia l behaviors have been correlated with various traits and attitudes. In regard to traits directly relevant to the present study, antisocial behavior associated with ASPD has been found to be comorbid with other personality disorders corollary to anxiety, de pression, or substance abuse. Also antisocial behavior has been shown to be more pervasive in males rather than in females (Bonino et al., 2005; Glen et al., 2013). However, there is still conflicting data regarding the distinction between genders, where s ome studies have found the social aggression subtype of antisocial behavior to relate more closely to females, while physical aggression has related more often to males (Burt & Donnellan, 2009). These associations in part selected for the factors used in t he study that are correlated to antisocial behavior through physiology. There are two physiologies in particular that are well established in the literature in relation to antisocial behavior: the low transcribing allele genotype of the monoamine oxidase A gene (MAOA L), and irregularities in the orbital frontal cortex (OFC) of the brain. MAOA L and Antisocial Behavior Monoamine oxidases are enzymes that catalyze the breakdown of aminergic neurotransmitters. Monoamine oxidase A, the specific enzyme of int erest here, catalyzes the breakdown of noradrenaline and serotonin (Oxford Concise Medical Dictionary, 2010). Of these

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SURVEYS, MAOA L & OFC 16 two chemicals, serotonin or 5 hydroxytryptamine (5 HT) is of particular significance. Serotonin in the central nervous system originates in the raphe nuclei and projects throughout virtually the entire brain and spinal cord. A large family of 5 HT receptors exist which affect diverse cellular pathways when activated. Serotonin is notably related to the moderation of arousal, mood, aggressio n, and the sleep cycle. Reduced levels are associated with mood disorders such as depression. Monoamine oxidase inhibitors or serotonin uptake inhibitors (SSRI) increase the effect of serotonin at the synapse, and are often prescribed in the treatment of m ood disorders (Martin & Hine, 2013). The gene that codes for the monoamine oxidase A enzyme in humans is located on the X chromosome location Xp11.23 11.4. This gene contains a 30 base pair motive in its promoter, which is polymorphic. Various promoter all eles have been identified in upstream variable number tandem repeats (MAOA uVTNR) where resulting genetic combinations will result in normal or low transcription of the monoamine oxidase A enzyme (MAOA L; Gallardo Pujol, Andre s Pueyo, & Maydeu Olivares, 2013, Williams et al., 2009). Females heterozygous for mutant ( L/H ), homozygous for the wild type ( H/H ), or males hemizygous for wild type alleles ( H/Y) generally experience normal levels of serotonin activity. Females are who are homozygous ( L/L ) or males hemizygous ( L/Y ) for mutant alleles transcribe lower amounts of monoamine oxidase A, and experience increased levels of serotonin (MAOA L). Sex differences go beyond genotype in this case, as monoamine oxidase A transcription is directly regulated by estr ogen. Receptors for estrogen are densely present in the amygdala, cingulate and orbital frontal cortices where local regulation of transcription would have various effects. Testosterone, which has long been thought a moderator of aggression, may also act d irectly on the MAOA uVTNR promoter in regulating transcription (Buckholtz & Meyer Lindenberg, 2008; Williams et

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SURVEYS, MAOA L & OFC 17 al., 2009). With a basic understanding of the physiology of MAOA L higher level effects can be described. The viable levels of serotonin cataly sis due to MAOA L have been found to have significant emotional and behavioral effects. These effects have been reliable and widely accepted to the extent that the presence of MAOA L has been used in courtroom attempts to excuse criminal actions (Baum, 201 3). In an early study regarding the behavioral effects of MAOA L, Brunne r, Nelen, Breakefield, Ropers, and van Oost (1993) identified a large family where the members, males in particular, were known for uncontrolled aggression and borderline mental retard ation. The researchers genotyped the entire family as well as took urine samples. The genetic results indicated the pervasive presence of MAOA L in the family, while the urine samples reveled decreased levels of monoamine oxidase A catalytic products. This would seem almost counter intuitive considering that people who naturally experience reduced levels of serotonin typically suffer mood disorders, while MAOA L affects an increase in serotonin. As it turns out, lifelong increases actually labialize 5 HT re ceptors throughout the brain. This desensitization has actually been found to uncouple neural circuits between the ventromedial prefrontal cortex and amygdala related to emotional decision making, and particularly in males irregular development of the orbi tal frontal cortex involved in behavioral regulation (Bortolato et al., 2011; Buckholtz & Meyer Lindenberg, 2008; Dannlowski et al., 2009). Based on this mechanism, MAOA L has been correlated to imbalances of threat related emotion (Williams et al., 2009), depression (Dannlowski et al., 2009; Melas et al., 2013), and substance abuse (Klein et al., 2011). It also seems to logically follow that these associations have also connected MAOA L to general antisocial behavior. Gallardo Pujol et al. (2013) genotyped participants and asked them to engage in a virtual reality social exclusion and aggression game. They found that

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SURVEYS, MAOA L & OFC 18 MAOA L participants behaved significantly more aggressively in gameplay, especially when socially excluded. Bortolato et al. (2011) geneticall y altered mice where they bred genotypes with various MAOA uVTNR resistances to transcription. In one group of mice called MAO ANeo, transcription of the enzyme was greatly reduced (an approximation to MAOA L). In another group called MAO AKnockout, transc ription was removed almost completely. In behavioral evaluations, the researchers found that both groups were less social or interactive in comparison to normal mice. Further, the MAO AKnockout group displayed markedly higher spatial aggression. In humans, MAOA L is not thought to be the sole cause of antisocial behavior. Instead it is thought to set the stage for it through physical propensity. Much research has found that MAOA L participants with increased antisocial behavior experienced a traumatic event or abusive upbringing during childhood. Such negative events in childhood are thought to trigger development down the path to antisocial behavior (Buckholtz & Meyer Lindenberg, 2008; Gallardo Pujol et al., 2013; Melas et al., 2013). An interesting corolla ry to the effects of MAOA L in development is the difference in physical brain structure. MAOA L participants have been found to display diminished size and activity in the prefrontal cortex (Brunner et al. 1993; Buckholtz & Meyer Lindenberg, 2008). Bortol ato et al. (2011) found that both groups of mice modified to reduce monoamine oxidase A transcription displayed dendritic irregularities in orbital frontal cortex (OFC) neurons. Klein et al. (2011) found that cocaine and substance users with the MAOA L ge notype were especially sensitive to losses in cortical grey matter, especially in OFC neurons. It would seem that the sensitivity of the OFC to MAOA L would imply that as MAOA L is associated with antisocial behavior, OFC irregularity might be part of the mechanism. This is further explored in the following discussion of the second physiological marker examined in the present study.

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SURVEYS, MAOA L & OFC 19 OFC and Antisocial Behavior Most students of psychology or physiology know the story of Phineas Gage. Over 150 years ago an accident with dynamite cause a railroad spike to pass through Phineas' eye and exit the top of his head. He survived and made a strong recovery but displayed dr astically different behavior. Gage became unreliable and behaved inappropriately in public. Nowadays it is currently thought that the region of Gage's brain that suffered the most profound damage was the left OFC. This region is located on the ventral side of the brain just superior to the eyes. The OFC has been found to have many projections to the limbic system including the central amygdala. The endpoints of every sensory pathway project to the OFC. It has been theorized that sensation, memory and emotio nal content are integrated in this area. This is thought to function in part to give stimuli their meaning, and for learning the appropriateness of behaviors (Barbas, 2013). Many studies have found that abnormalities in the OFC lead to problematic social b ehaviors. The role of OFC in social behavior is most easily understood when OFC function is impaired. Most impairments to OFC function lead to varying degrees of antisocial behavior. Generally disorganized behavior was observed in OFC lesioned mice, wher e they lost the ability to execute defensive or play behaviors depending on context (Pellis et al., 2006). Though more severe social deficits have been observed in simians and humans. Bachevalier, Machado, & Kazama (2011) lesioned regions of OFC in rhesus monkeys to observe differences in behavior. The results found that lesioned monkeys had more difficulty interpreting social cues, especially those conveying threat. OFC irregularity has not only been associated with more mild social effects but with actual psychoses. Histological research on neurons in the late 1970's showed that in schizophrenia patients, OFC triangle cells and pyramidal cells had developed in a

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SURVEYS, MAOA L & OFC 20 disorganized and structurally unusual way (Beckmann & Senitz, 2002). This has since been corrob orated with further research (Joshi, Fung, Rothwell, & Weichert, 2012; Malla, Bodnar, Joober, & Lepage, 2011). Interestingly in fMRI studies of psychiatric patients, OFC deficits have been connected directly to the most socially destructive behaviors. Redu ced OFC volumes explained 34% of the variance over a self reported aggressive behavior history inventory (Gansler et al., 2009). OFC function has been found to be important in social perspective taking. fMRI imaging during a perspective taking task has sho wn increased OFC activation during emotional perspective taking imagery (Hynes, Baird & Grafton, 2006). Also OFC lesions have been implicated in depression. Kolb, Pellis and Robinson (2004) found that neonatal OFC lesions in rats led to deficits in social behavior that specifically inferred depression. Likely the most commonly corroborated function of OFC in the literature is the moderation of risk versus reward decisions. fMRI research has shown that when participants with normal OFC function are asked to play a prisoner's dilemma game, this area becomes very active, especially when a cycle of cooperation and reward occurs (Rilling et al., 2002). In a similar study, when participants were asked to play a reward game where they could choose between either a large but very unlikely reward, or a small but very likely reward, PET scan imaging showed increased blood flow in OFC, particularly in Brodmann's area 11 (Rogers et al., 1999). Conversely, those who have irregularities in OFC development or injury hav e difficulty with these sorts of tasks. In an fMRI study, where participants were asked to play a similar reward game, those with OFC lesions did not change their gameplay based on negative score feedback, despite confirmation that they were paying attenti on and understood the results (Hornak et al., 2004). More recently, similar findings were observed in rhesus monkeys, where OFC lesions not only led to disorganized reward learning, but also an inability for the monkeys

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SURVEYS, MAOA L & OFC 21 to be satiated by food rewards (Bach evalier et al., 2011). These problems with risk reward assessment could relate partially to increased general impulsivity in decision making, which has been observed in participants with lesions or diminished activity in OFC (Berlin, Rolls, & Kischka, 2004 ; Gansler et al., 2009; Wolf, 2012). Purpose The present study sought to predict a measure of antisocial behavior tendency by factors correlated to OFC irregularities and MAOA L. When examining the above review, four factors associated with these physiol ogies that are themselves distinct from antisocial behavior emerge as potential predictors: 1. Risk taking beyond proportionate rewards, which has been connected to OFC function (Bachevalier et al., 2011; Hornak et al., 2004; Rilling et al., 2002; Rogers et a l., 1999). 2. Perspective taking, which neural imaging has connected to OFC function (Hynes et al., 2006). 3. Gender, based on observed sex differences in MAOA L physiology (Brunner et al. 1993, Buckholtz & Meyer Lindenberg, 2008; Williams et al., 2009). In part icular, that males will express greater antisocial behavior, as MAOA L is genetically sex linked, and that hemizygous males occur in higher probability than homozygous females. 4. Depression, OFC lesions have been shown to cause symptoms of depression (Kolb e t al., 2004). MAOA L in conjunction with childhood trauma was also shown to be a likely cause of depression (Melas et al., 2013).

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SURVEYS, MAOA L & OFC 22 Surveys sensitive to each of these traits were selected. If the essential postulation of this paper is accurate, than these su rveys will be strong predictors of antisocial tendency. Thus the hypothesis tested in this study was that surveys designed to assess risk taking, perspective taking, gender and depression when combined in multiple regression analysis, would predict a measu re of antisocial behavior. Method Participants Introductory psychology students ( n = 148, 97 female, 49 male, and two transgender) over 18 years old ( M = 23) participated in this study for partial course credit. Participants identified as 62.2% Caucasian, 11% multiracial, 8.8% Latino, 4.7% Asian, 3.4% African American, 3.4% Native American, and 6.5% various other backgrounds or did not respond. Materials Perspective Taking. To assess perspective taking, the Social Perspective Taking Propensity Scale (SPTP; Gehlbach et al., 2008) was used. This is a seven item, five point Likert scale with anchors ranging from Almost never to Almost all the time This s cale asks participants questions regarding the frequency of their perspective taking behaviors (e.g., "How often do you try to look at everybody's side of a disagreement before you make a decision"). This scale had been found reliable by the authors (! = 88). The Cognitive Perspective Taking Subscale (QCAEPT; Reniers, Corcoran, Drake, Shryane, & Všllm, 2011) also measures perspective taking. This is a 10 item, four point Likert type scale with anchors ranging from Strongly disagree to Strongly agree Part icipants rate themselves in regard to statements describing perspective taking

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SURVEYS, MAOA L & OFC 23 behaviors (e.g., "I am good at predicting what someone will do"). QCAEPT was found reliable by the authors (! = .85). Risk Taking. To measure risk taking, the Risk Behavior At titudes Questionnaire (RBA; Dalton et al., 2010) was used. This scale is a three item, four point Likert type measure with anchors ranging from Very often to Hardly ever. Participants answer questions regarding the frequency of their risky behaviors (e.g., "I do very dangerous things for fun"). This scale was found to be reliable in the current study (! = .76). Also to assess risk taking the Risk Taking Tendency Measure (RTT; Brache, & Stockwell, 2011) was used. This is a 14 question scale where participant s answer yes or no to questions regarding risky behaviors such as "Do you smoke?" The authors reported a reliability coefficient of (! = .62). Depression. To rate depression, the Center for Epidemiologic Studies Depression Scale (CES D; Radloff, 1977) wa s used. This is a 20 item, four point Likert type scale in which participants reported the frequency of depression symptoms (e.g., I felt that people dislike me) over a two week period. This scale was found reliable in previous research (! = .84). Antisoc ial Behavior. To assess tendency for antisocial behavior, the Subtypes of Antisocial Behavior Questionnaire (STAB; Burt & Donnellan, 2009) was used. This is a 32 item, five point Likert scale with anchors ranging from Never to Nearly all the time Partici pants rate the frequency of their antisocial behaviors (e.g., "Got into physical fights"). This scale includes reliable subscales for: physical aggression (! = .84), social aggression (! = .83), and rule breaking (! = .71). Gender.

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SURVEYS, MAOA L & OFC 24 Gender was reported al ong with age, ethnicity and race in a demographics survey per APA guidelines. Procedure All surveys were administered using an online portal hosted by Sona Systems. Each question was presented in sequence as written within each survey. Each survey was p resented in random order to avoid order effects. The only exception was that the demographic questions were always presented last. Participants signed into the system using a secure log on, answered questions on all surveys and then logged off. The durati on of this process did not exceed 60 minutes. See Figure 1 for an illustration of the study procedure. Results Evaluation of Assumptions All scales were screened for missing data and outliers. For each scale z scores were computed. Of the ( n = 143) valid cases listwise, eight cases were excluded as major outliers with z scores exceeding 3.00. To evaluate normality skewness values were computed. Scales exceeding a value of 1.96 for skewness divided by standard error of skewness were transfo rmed (Abu Bader, 2010). For SPTP (skewness/SES = 2.63) the distribution was reflected and the square root of the scores was taken. For RBA (skewness/SES = 2.66) the square root of the scores was taken. For CES D (skewness/SES = 3.61) the square root of th e scores was taken. Finally, as all categorical variables must be dichotomous in multiple regression Reported gender was recoded into categories of male and not male. This approach was taken as the hypothesis of this study assumes greater antisocial behavi or among males, and because transgender participants cannot be categorized in reference to MAOA L.

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SURVEYS, MAOA L & OFC 25 Two surveys given to participants were not analyzed. To satisfy the requirements for multiple regression analysis, scales must not be co linear (i.e., must not measure the same thing; Abu Bader 2010). For the same prediction factors, QCAEPT (perspective taking) and the RTT (risk taking) scales were found to be less preferable to SPTP and RBA respectively for reasons of reliability and validity. Both RBA and S PTP were found more reliable, with the larger discrepancy between RBA (! = .76) and RTT (! = .64) found in the present data. In the case of QCAEPT, the scale failed to correlate significantly to STAB (r = .16, p = .07), thus violating the regression assum ption of linearity. Main analysis To examine the hypothesis that RBA, SPTS, CES D and Gender (male) would predict STAB scores, a multiple regression was conducted. The resulting regression found that these factors were all significant STAB predictors R 2 = .32, F (4,130) = 15.38, p < .001. The strongest predictor was RBA, which accounted for approximately 14% of the variance. SPTS accounted for another 7%, Gender for 5% and CED D for 4% of the remaining variance. See Table 1 and Table 2 for regression coeff icients. See Figure 2 for regression partial plots for all predictors. Table 2. Coefficients of Factors Predicting Antisocial Behavior Factors b t p Risk Taking .36 4.87 < .001 Social Perspective Taking .26 3.49 .001 Depression .24 3.22 .002 Male .23 3.22 .002 Table 1. Coefficients of Regression Predicting Antisocial Behavior R = .57 R 2 adj = .30 SE = .29 F (4,130) = 15.38 p < .001 Predictors in the equation: SPTS, RBA, CES D, Gender (Male)

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SURVEYS, MAOA L & OFC 26 Discussion The hypothesis of the study was supported in the results. Measures of risk taking, perspective taking, depression, and gender, which were related in previous research to OFC and MAOA L physiologies, predicted scores on an antisocial behavior measure. The s trongest predictor was RBA, while all other factors accounted for relatively similar variance in scores. This infers a close predictive connection between risk taking and antisocial behavior. The results of this study reinforce the consensus in previous li terature associating OFC to moderation of risk assessment, by its association thru antisocial behavior (Bachevalier et al., 2011; Hornak et al., 2004; Rilling et al., 2002; Rogers et al., 1999). Another interesting result of this study was the finding of S PTP as a significant predictor of STAB scores. This is relevant because of the non linear relationship between STAB and QCAEPT, a scale meant to examine the same factor as SPTP. This speaks to the capriciousness of survey research. When two traits of perso nality are associated, through physiology or otherwise, surveys must adequately and reliably probe those traits or else the association may not be discovered. In this case evidence was found to support the association of perspective taking with antisocial behavior, and for very different assessments of perspective taking between surveys. The main limitation of this study was the lack of ability to positively identify the MAOA L and OFC physiologies in participants. The object of this research was to use t hese as physical markers for survey selection, and those surveys did predict the intended trait. However, even though an inference can be made, the successful prediction by these surveys cannot be completely attributed to their association to physiological markers, when those markers were not themselves analyzed. Another limitation of this study is that surveys were predicting other surveys, rather than surveys predicting observed behavior. The following experiment attempted

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SURVEYS, MAOA L & OFC 27 to strengthen the overall argume nt in this paper by addressing the above limitations. Rather than relying on self report, the following experiment attempted to influence and observe behavior first hand. Rather than inferring association through physiology, the following experiment primed actual physiological states as means of predicting behavior. Experiment 2: Predicting Aggressive Gameplay by Survey and Physical Arousal This experiment attempted to examine the essential idea of this paper from a different point of view. The first stud y illustrated the potential for selecting surveys related to physiological markers in predicting scores on a personality factor survey. The following experiment sought to compare the strength of a physiology, versus a common personality survey in predictio n of behavior. To do this, a workable research design implied certain requirements for both the physiology and behavior involved. First, evidence of association between the physiology and the resulting behavior was required. Second, ideally the physiology would be a physiological state that could be primed. Although this has different implications for long versus short term behavioral traits, it was preferable in research design. Priming a physiology was favorable compared to attempting to attain relevant s ample sizes of naturally occurring permanent physiological traits. Third, it was necessary that the resulting behavior be described in either a clearly categorical or parametric manner. To satisfy these conditions and to dovetail with the findings of the p revious study, the priming of physical arousal to affect aggression was analyzed. Arousal and Aggression Physical arousal is marked by aversive states of discomfort, elevated alert, or increased metabolic output (e.g., increased heart rate). Aversive sta tes can be triggered by pain or uncomfortable environmental conditions. Increased metabolic rates can be induced through

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SURVEYS, MAOA L & OFC 28 exercise. Physical arousal by exercise also causes activation of the sympathetic nervous system. This division of the autonomic nervous system is responsible for increased metabolic rates in skeletal and cardiac muscle. When activated, blood flow to these muscles is increased while blood flow to the outermost extremities and digestive system is decreased. These increases in metabolic outp ut, and also an increase in alertness are partially influenced by the hormone norepinephrine (also called noradrenaline), when it is released as part of the sympathetic nervous response (Binder, Windhorst, & Hirokawa, 2009). Beyond just increased metabolic output, exercise has many health benefits such as increased strength and cardiovascular endurance. Further, for many it can be very enjoyable. Though this is not the case for everyone. The increased respiration, blood perfusion and increase in blood press ure can be one of the most stressful states commonly experienced in the body. Many experience various degrees of discomfort due to the effects of systems maintaining homeostasis during exercise (e.g., aches from the build up of lactic acid during anaerobic respiration; Xiang & Hester, 2012). During physical arousal, increased alertness and aversive sensation can influence aggression. Physical arousal has been found to lead to aggressive behavior in previous research, and there are multiple theories explai ning why this may happen. Two possible mechanisms discussed by Anderson and Bushman (2002) attribute physical arousal with alertness and discomfort. First, when aroused dominant (or well learned) tendencies tend to be magnified. So if one is provoked to ag gress when already aroused, they are more likely to act on that tendency. Second, that physical arousal in some cases (e.g., exercise) may comprise aversive states. In these cases they can incite aggression just as a painful stimulus would. Another view on the connection between aggression and physical arousal was synthesized from the Two factor Theory of emotion, where arousal can be labeled as various emotions based on available cues (Schachter & Singer, 1962)

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SURVEYS, MAOA L & OFC 29 Based on this principle t he Excitation Trans fer Theory of aggression hypothesizes that arousal can be relabeled as anger when anger is provoked. This leads to anger motivated aggressive behavior after provocation (Zillman, 1988). In a study of particular interest, Anderson et al. (1995) explored two different dimensions of connection between physical arousal and aggression. The initial aim of the research was to study the hypothesis that as ambient temperature increases so does aggression. Participants would exercise in normal or noticeably elevated room temperatures while the researchers monitored their heart rates. Anderson et al. administered pre and post tests for attitudinal aggression. The researchers found that aggressive attitudes increased as both heart rates and temperature increased. The in crease in aggressive attitude due to temperature is explainable simply as a reaction to an aversive stimulus. Though increased heart rate is an internal physiological state, and one that can be primed. This being the case, increased heart rate satisfied th e first two requirements for this experiment: that the physiological state must be associated with the resulting behavior, and that it can be primed. Thus the potential for predicting aggression during this physiological state of arousal by increased heart rate was investigated in the present experiment. The Prisoner's Dilemma The requirements for priming in the present experiment were satisfied with arousal by increased heart rate. The Prisoner's Dilemma Game (PDG) satisfies the third condition discussed regarding a resulting behavior. Unlike the Anderson et al. (1995) study, the present experiment sought to predict aggressive behavior rather than aggressive attitudes. The largest hurdle in regard to this is the fact that aggressive behavior is intrinsica lly dangerous. Research in psychology seeks to investigate behavior without causing harm to participants, so a safe way to enact aggression was required. The PDG presents an elegant solution to this problem. The PDG

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SURVEYS, MAOA L & OFC 30 is an accumulation task (usually measure d in monetary value) where the object is to accumulate the most money or score the highest. In PDG participants are given two choices: they may either defect from another person with whom they are anonymously grouped, or they may cooperate with that person PDG creates incentive to defect from the other group member with the possibility of earning the highest possible score per turn. However, they are informed that should they make this choice, it will hurt the other group member by either greatly reducing or eliminating their payoff score. Otherwise they can choose to cooperate with the other group member. In this case they could receive a slightly reduced amount, but in this case the payoff is mutually beneficial to the other group member. There is of cour se a reciprocal risk in PDG of the participant having his or her own payoff reduced because of the choice from the other group member. However the reductions are comparable no matter the participant's own choice. If both group members are randomly and anon ymously assigned participants, there is the possibility that if one participant defects, the other will defect in response out of mistrust or retaliation. In this scenario, aggressive gameplay becomes a complicated interaction of various forces. Though whe n provocation is removed, participants' gameplay becomes a product of their own tendencies. These scenarios have previously been achieved in research with the use of a virtual player. Due to the anonymity of a participant's other group member, this role c an be replaced with a version of artificial intelligence in place of a second participant. By doing this, you can dictate behaviors in the virtual player that prevent provocative aggressive gameplay. One design that can be employed is the tit for tat virtu al player paradigm. Descriptions of this can be found in Rilling et al. (2002) where the virtual player will cooperate by default to avoid provocation. To maintain the appearance of a human or more intuitive other group member for participants,

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SURVEYS, MAOA L & OFC 31 the virtual player will defect, but only after the participant defects first. A similar design, two tits for tat was employed by Mokros (2008) in a study of the social behavior of psychopathic patients where psychopathic participants were found to defect significantl y more often than those from the general population. This is a more conservative design where the virtual player defects only after two participant defections. In virtual player studies such as these where the provocation of the other (virtual) player has been removed, the decision to defect can be used as a measure of aggressive gameplay. Purpose and Hypothesis Based on general survey research practices and mind body connection theories, both a physiological state and a survey would likely be predictive of behavior. This experiment sought to compare the predictive efficacy of both types of prediction. To test this participants' aggressive PDG gameplay was examined when they were physically aroused by an increase in heart rate. These participants also comp leted an aggression inventory survey. The hypotheses of this experiment were that: 1. Physical arousal through mild exercise will prime aggressive gameplay. 2. A survey will predict participants' aggressive gameplay. 3. An interaction where those who were primed with physical arousal will behave more or less aggressively depending on whether they scored high or low on an aggression survey. Method Participants A group of mostly introductory psychology students ( n = 96, 53 men, 42 women, and one transgendered) over 18 years old ( M = 24) participated in this study for partial course credit. The sample was 63% Caucasian, 15% Latino, 12% multiracial, 5% African American and 5% of other or unknown backgrounds.

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SURVEYS, MAOA L & OFC 32 Materials Participants were assessed wi th the Aggression Questionnaire (Buss & Perry, 1992). The Aggression Questionnaire is a self response aggression survey containing 29 questions regarding an aggressive personality. This survey includes subscales that score tendencies for physical aggressio n, verbal aggression, anger and hostility. Questions on this survey are rated on a five point Likert scale with anchors ranging from 1 ( extremely uncharacteristic of me ) to 5 ( extremely characteristic of me ). Physical and verbal subscales ask questions abo ut instrumental aggression such as "Given enough provocation, I may hit another person." In this survey, anger is interpreted as an affective arousal and readiness for action. An example question from the anger subscale asks if it is characteristic of the participant that "I have trouble controlling my temper." Hostility is interpreted in this survey as feelings of being wronged or injustice. "I am sometimes eaten up with jealousy," is an example from this scale. Buss & Perry (1992) found this scale to be h ighly reliable with an overall alpha level of .89. Participants also were given questions regarding their demographics (i.e., age, gender ethnicity and race) per APA guidelines. These along with response sheets for the PDG were presented in a single packet Procedure Participants engaged in activities to induce two levels of physical arousal. Following each activity, participants would play one round of the PDG. In the rest condition, a state of low physical arousal would be induced by a slow breathing ex ercise designed to lower heart rate. Previous research has shown that when participants breathe at the rate of one full cycle of breath from inspiration to expiration per every 10 seconds, heart rate reliably decreases (Kaushik, Kaushik, Mahajan, & Rajesh, 2006). Participants relaxed and the researcher cued them to breathe in, followed five seconds later by a cue to breathe out, then five seconds later a cue to breathe in

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SURVEYS, MAOA L & OFC 33 again, and so on. This continued for two minutes, followed by a break, then the exerci se would be repeated for two more minutes. In the exercise condition, a state of increased physical arousal was induced by mild exercise to increase heart rate. Participants did an activity of their choosing where they would stand and move such that their legs were steadily in motion (e.g., jogging in place, jumping in place, or jumping jacks) at a pace they felt to be comfortable. This continued for two minutes, followed by a break, and then continued for two more minutes. Though some participants spent a considerable amount of energy in this activity, the exercise was kept light both out of concern for participants' safety, and because nothing more difficult was necessary. Increased heart rate is achieved easily in humans when our legs are steadily in moti on. Veins in the lower extremities act as a reservoir for blood, and during sustained muscle contractions the blood is squeezed out. This venous blood is returned to the heart, which quickly increase its rate and muscle exertion to handle the additional bl ood flow. This action along with further arousal also compounds with any further exercise exertion (Xiang & Hester, 2012). These two conditions and a corresponding PDG repetition for each were counterbalanced for order per experimental session. The versio n of the PDG employed in this experiment was the tit for tat design as described in previous research (Mokros et al., 2008; Rilling et al., 2002). Due to the limited number of turns a specific adjustment to the virtual player behavior was made. In this ver sion, on the final turn if the participant defected, the virtual player would defect on that turn. On all other turns, the virtual player defected on the turn following a participant's defection. Participants were informed prior to the beginning of the gam e that they would be grouped with either another participant or a virtual player, but that the identity of the other group member would remain secret. As they were playing tit for tat, they were all grouped with the virtual player and this was

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SURVEYS, MAOA L & OFC 34 later clarif ied to participants in debriefing. The rules of the game were presented to participants using a game scenario where they would compete for hypothetical money. The defection choice was described as being paid solo and the cooperation choice as being paid as a group The amounts attached to each participant and virtual player choice pair were proportionate to those used by Mokros et al. (2008). Defections were worth eight dollars when the virtual player cooperates or one dollar when the virtual player defects (the latter would occur with two or more participant defections in a row). Cooperation was worth five dollars when the virtual player cooperates or no money when the virtual player defects (the latter would happen if the participant defects and then coope rates on the following turn). The full text of the scenario and game instructions presented to participants is shown in Appendix A. During the PDG participants would write their choice on an answer sheet. After participants recorded their choice, the res earcher would quickly inspect all the answer sheets and record each participant's choice in a laptop computer. This was done within the view of the participants. The intended appearance was that their choices were being compared against each other. The spr eadsheet where choices were entered was actually calculating virtual player responses and resulting scores to reduce experimenter error. The researcher would then write down the participants' scores for that turn on each of their answer sheets based on tit for tat rules. The PDG would progress for 10 turns per repetition. The number of participant defections per repetition was analyzed such that more defections represented increasingly aggressive gameplay. After both cycles of physical arousal condition and PDG were completed, participants completed survey responses. Participants completed the entire aggression survey first. They then filled out demographic information. When all surveys were complete, participants were

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SURVEYS, MAOA L & OFC 35 debriefed and the sessions were conc lude d. See Figure 3 for an illustration of the experimental procedure. Results Evaluation of Assumptions Each variable was screened for missing data and outliers. For each scale z scores were computed. Of the ( n = 92) valid cases pairwise, no cases excee ded a z score of 3.00 thus none were excluded. To evaluate normality, skewness values were computed. No scales exceeded a value of 1.96 for skewness divided by standard error of skewness thus none were transformed (Abu Bader, 2010). Defection scores in both the relaxation and arousal conditions met these requirements. Aggression questionnaire scores were split at the median into high and low aggression survey groups for entry into the analysis. Main Analysis To analyze the effects of survey predicted aggression and physical arousal on aggressive gameplay, a mixed factors ANOVA was conducted. A significant main effect of arousal condition on PDG defection was found F (1, 90) = 5.92, p = .02, p # = .06, such that participants defected significantly more i n the relaxation condition ( M = 4.54, SD = 3.24) than in the arousal condition ( M = 3.75, SD = 3.00). This means that participants' gameplay style was more aggressive immediately following relaxation than immediately following arousal. There was no significant difference found in defections between high and low aggression survey groups F (1, 90) < 0.001, p = .99, p # < .001. Also no significant interaction was found between arousal and aggression survey defections F (1, 90) = 2.45, p = .12, p # = .03. See Table 3 for means with s tandard deviations, and Figure 4 for a chart of PDG defection scores ac ross conditions.

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SURVEYS, MAOA L & OFC 36 Discussion The findings of this study do not support the hypotheses. The first hypothesis was based on the expectation that participants would play more aggressively during arousal versus relaxation. Though what was observed was exactly the opposite. The results were significant and in the reverse direction. Findings by Anderson et al. (1995) regarding physiological arousal and aggression were counter intuitive to these results. An explanation for this discrepancy could be related to one of the limitations of this stu dy: in this research design there is implied value for scoring higher. The object of the game is to accumulate the highest monetary score, and even if the money won is imaginary, there should be intrinsic motivation to play well. This was a consideration i n the design of the virtual player such that participants would not explicitly know Table 3. Descriptive Statistics of Within and Between Groups PDG Defections Variables n M ( SD ) Arousal Condition High Survey Aggression 46 4.00(2.99) Low Survey Aggression 46 3.50(3.03) Total 92 3.75(3.00) Relaxation Condition High Survey Aggression 46 4.28(3.33) Low Survey Aggression 46 4.80(3.16) Total 92 4.54(3.24)

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SURVEYS, MAOA L & OFC 37 that defections lead to steadily lower scores. Though participants in the exercise condition could have been experiencing benefits of mild exercise. Theories as early as th e beginning of the last century such as the Yerkes Dodson hypothesis describe a connection between physical arousal and performance increases (Yerkes Dodson law, 2006). It is possible, and it appeared to be the case by observation only, that during arousal participants were more attentive, focused and responsive to the score feedback from the virtual player. If this was true then participants would have been playing more optimally. The ideal play of the participants in scoring higher would overshadow any an alysis based on aggressive tendency. This would then account for yet more evidence for theories related to Yerkes Dodson and arousal induced performance increases. This principle of optimal play also relates to another limitation of this study, which was t he small number of PDG turns, and that participants were aware of how many turns there would be. As described by Dawkins (1976), if participants are aware of when they will reach the last turn of a PDG, this awareness is likely to affect their defections b y offensive or defensive strategy. Strategic behaviors such as these present a significant confound, especially when disbursed over a small sample of turns. The second hypothesis of this study was that groups defined by aggression survey scores would pre dict aggressive gameplay. Again this was not supported and indeed seems very odd. Although the essential concern of this paper is the capriciousness of survey data, it would seem extremely unlikely that the vast majority of those who were categorized into the high aggression survey group were not relatively aggressive in comparison to those in the low aggression survey group. This would be especially true considering that there were no outliers. Thus no cases were likely pulling the cut point between groups away from central tendency. Since there is survey evidence of general aggression in participants grouped into the high aggression group regardless

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SURVEYS, MAOA L & OFC 38 of their PDG gameplay, the sensitivity of PDG to aggression is called in to question. Findings from Mokros e t al. (2008) seem contrary to this idea as psychopathic patients were found to defect more often then general population participants. Further, to defect from a group at the detriment of the member of that group is by definition an aggressive antisocial ac t. However, psychopathy does not imply aggressive behavior in every situation. Another common trait would be manipulation, which could be very relevant to the way one might play a PDG. It was actually theorized by Mokros et al. that many defections made by psychopaths were following manipulative attempts to lull participants into cooperation. Also, not all antisocial behaviors are based in social aggression. Various different subtypes of antisocial behavior based in physical aggression, social aggression or rule breaking have been delineated (Burt & Donnellan, 2009). Future research could possibly attempt a similar PDG manipulation in concert with scales meant to assess these subtypes. To address the third hypothesis of this study, no significant effect of arousal based on aggression group was revealed, however the statistic was approaching significance. In a way however, to find significance on this dimension, with a bigger sample size for instance, would still not be practically important with such a smal l effect. Though interestingly, arousal condition defection scores between aggression survey groups begin to more closely approximate the hypothesized results. During arousal, the high aggression survey group defected more aggressively than the low aggress ion group. These differences are trends and not statistically significant but may be worth future investigation. The main limitation of this study is the very nature of aggressive behavior as it is intrinsically dangerous. This behavior was selected due to an established connection in the literature to a physiological state. Though to carry out aggression is to attempt harm: one of the

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SURVEYS, MAOA L & OFC 39 very outcomes that ethical research endeavors to avoid. PDG allows participants to carry out an aggressive choice in a sa fe environment, though it may simply not be a very strong approximation to one's aggressive behaviors. Future research then could find a more easily measured example behavior with a strongly correlated physiological state, or could identify another safe an d more precise way to measure aggressive behavior. Conclusions Predicting Antisocial Behavior In relation to the thesis that surveys could be made more reliable when selected in reference to physiological markers of behavior, the studies undertaken for this paper offer promising albeit mixed results. The most coherent message can be found in refere nce to the first study. Here several predictive factors, risk taking tendency, perspective taking, depression and gender, were selected based on physiological correlates to antisocial behavior. As the results show, every one of these factors contributed to the prediction of an antisocial behavior inventory. In this case it can clearly be said that one thing (or group of predicting factors) predicted the other as expected with little ambiguity. Though the lesser or complete lack of ability to use QCAEPT and RTT in predicting antisocial behavior reflects the very problem that this paper attempts to address. In this case the assertions of Burless and De Leo (2001) that consistency between surveys measuring the same construct should succumb to more stringent sta ndardization is highlighted. In the case of the meta analysis that they performed, they were not able to compare results of different surveys within a construct from multiple studies to answer questions about group differences. In the present study, predic tive surveys were not only different in the resulting data yielded within one group, but also in the case of perspective taking, one survey was not even eligible for analysis while its analog was and significant. Whether or not survey

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SURVEYS, MAOA L & OFC 40 research trends towar d more physiological bases, a need for greater standardization within constructs is clearly evident in this study as well as in previous literature. In regard specifically to antisocial behavior, any advance in prediction or early detection of antisocial tendencies is beneficial. Planty and Truman (2012) reporting for The Bureau of Justice Statistics showed that between the years 2010 and 2011, the rate of violent victimization, which includes rape, theft and assault victimization, increased 17%. The rate of property victimization, which includes burglary, motor vehicle theft and property theft, increased 11% over the same duration of time. Antisocial behavior is particularly difficult to analyze experimentally. Though it is also an excellent example of wh y it is important to attempt research regarding new ways of identifying those at risk for life long problems. Antisocial behavior is destructive to the conventions that allow us all to live together peacefully. Further, it not only victimizes cooperative m embers of society, but the perpetrators of antisocial behavior themselves. Those with the tendency to act against laws or victimize others, by societal recourse often experience a low quality of life even if they are not punished within the justice system. Rather than assigning blame and exacting retribution, the more positive solution is to better understand how to find those who need help before it is too late. Some of those who oppose the use of the PHQ 2 and PHQ 9 in New York for instance, argue that ma ss survey screening for risk factors creates more problems than the data is worth. Surely, in the case of the New York depression screening, their point is valid as the efficacy of PHQ screening in detecting depression is probably greatly attenuated by the mode of administration. Further it may actually cause harm. Though unsound investigation of these risky or dangerous behaviors is the very reason to attempt to generate more valid and effective forms of investigation. If this can be found in physiological bases, every effort should be made to develop it.

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SURVEYS, MAOA L & OFC 41 Aggression As is the case with antisocial behavior, its corollary in aggression is difficult to safely analyze experimentally. Though unlike in the first study, the aggressive gameplay outcomes of the se cond experiment are harder to interpret. This experiment was in an unexpected way supportive of the central thesis regarding prediction by physiology. The intended argument based on a positive finding in the second experiment would be that: in supplement t o the prediction of a personality trait by surveys correlated to physiology from the first study, here immediate behavior was predicted by the relevant physiology at hand. As previously outlined, the hypotheses of the second experiment were not confirmed. However the argument based on the results of this experiment is still relevant to the thesis of the paper. Based on a physiology at hand, a difference in behavior resulted. It was certainly not the behavior that the initially reviewed literature would sugg est; though when the manipulation was re examined a different body of literature allowed for a reasonable explanation of the results. This illustrates two important points: the objective nature of physiology and the further need to develop prediction based upon it. If physiology is going to cause an outcome in a specific scenario, it happens in an objective manner. It is not like an individually conceived survey where the properties of a construct can be endogenously reinterpreted subjectively. It has concr ete properties anchored in physics and chemistry. This is not to say that a single physiology cannot lead to many subjective outcomes under various conditions. In fact, that is the nature of science, to study the application of any given thing in reference to any other given thing in existence. Here the second point applies. Just as we would with any analyzed molecular substance, we can subject a physiology to different conditions and see what behavior results. When we find stable and reliable scenarios and traits that result, we can apply them practically. This is actually the very basis of good

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SURVEYS, MAOA L & OFC 42 psychometrics, and great research has been done in the past to correlate personality directly to behavior based on this sort of observation. The essential argument of this paper is that physiology is one more useful step up the ladder of understanding human behavior. With such an elaborate task in this endeavor, every reliable tool at hand is valuable. Future Potential for Predicting Behavior Through Physiology Fur ther honing of survey research by physiological correlates will likely be facilitated by progress in the understanding of neurobiological mechanisms. In the field of computational neuroscience for instance, discoveries continue to be made leading to a more precise understanding of how the essential neuronal functions of the brain lead to behavior. For decades physiologists have analyzed the nervous and endocrine systems, examining distinct features leading to behavioral outcomes. More recently with the adve nt of new analytical techniques and technologies, even the neuronal basis for essential decision making processes are beginning to be understood. For instance Newsome, Britten and Movshon (1989) performed single neuron recordings in the extra striate area MT of monkeys. During recording, monkeys were presented with a task where they were shown dots in motion. A fraction would move randomly and a fraction would move in one direction. The monkeys had to make a saccade to indicate which direction they had deci ded the coherent dots were moving. These recordings identified single neurons that were selective for a given direction and their "anti neuron" selective for the opposite direction. The researchers found that the neuronal firing rates of direction selectiv e neurons to be reliably indicative of the indicated stimulus direction. The monkey's choice closely corresponded to these firing rates as well. To further explore the neural mechanisms of decision and behavior Mazurek, Roitman, Ditterich and Shadlen (2003 ) used single neuron recordings in an area of the parietal lobe of Rhesus monkeys suspected to be related to visual discrimination

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SURVEYS, MAOA L & OFC 43 decision making. These neurons were found to be selective for the integral of corresponding MT directionally selective neuron 's firing over time. The study found that when these integrating neurons reached a certain threshold firing rate, the monkey would make a decision in the corresponding selected direction. In this study we see an example of a testable model of very basic de cision making, and resulting behavior at the neuronal level. To have found that individual cells lead to behavioral decisions seems impressive enough, though subsequent studies have gone much further. Using fMRI imaging, neuroscientists can record the meta bolic activation of the entire brain concurrently during a task or stimulus to infer the function of specific regions. Soon, Brass, Heinze and Haynes (2008) performed recordings of this type on human participants who were engaged in a similar decision task Although in this study, rather than simply responding to a discrimination problem, participants arbitrarily made a simple choice between which button on a keypad they wanted to push on their own time. The only restriction was that once they had made the conscious decision about when to push the button and which one, that they press it right away. Here a most basic willful choice was being analyzed and what the researchers found was striking. Not only did the researchers find cortices in the brain that rel iably moderated these choices, they found that they could predict these choices by the activation of neural cortices before the participants even knew they had made a decision. In fact even when adjusting for any delay that the participants reported betwee n when they made a conscious decision and pressed the button, the researchers could see the genesis of the still unconscious decision up to 10 seconds before it was made. Further, they could reliably predict which button was to be pushed by about six secon ds before participants consciously knew that they had chosen it. Aside from the fairly alarming implications that these findings have regarding the biological genesis of choice versus conscious freewill, the highly predictive potential of

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SURVEYS, MAOA L & OFC 44 physiological tec hniques that exist even today are illustrated. Even more recently, these types of techniques have gone from reductively analyzing individual simple behaviors, to more complex generalization about personality. Di Domenico, Fournier, Ayaz and Ruocco (2013) i maged the brains of participants using fNRIS another process that records metabolic neural activation. In this study they examined activation of the medial prefrontal cortex, an area of the brain known to play a role in what the researchers and most in the social sciences refer to as the self. They asked participants to choose between possible vocations (e.g., a choice between being a dancer or a chemist). Having asked participants' about what type of vocations they would find most satisfying in advance, th e researchers tried to present them with either easier or more difficult decisions during imaging. It was found that, the medial prefrontal cortex was significantly more active during difficult decisions. The researchers inferred that they were observing c ortical processes of the brain that enhance coherence in the self by moderating self satisfaction decisions in reference to self knowledge. Of course findings such as this are not as clear cut as a direct numerical relationship between the firing rate of a single neuron and a simple behavioral result (e.g., Mazurek et al., 2003). However, again it implies the potential for analyzing complex physiology in reference to (in this case) fairly abstract concepts of behavior. Research of this type is taking the wo rld further and further toward an understanding of the physical mechanisms of the mind. In doing so, this research informs us of physical scaffolding to behavior which can and will allow a more reliable prediction of behaviors. The essential problem with today's inferential physiological techniques is that they are monetarily and logistically prohibitive. When it comes to large scale applications in behavioral prediction, they are just not practical. To simply ask every child who might be at risk for devel oping an antisocial personality to spend weeks of his or her life in a neurology lab

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SURVEYS, MAOA L & OFC 45 performing whatever sort of thought and mental dexterity task a researcher could conjure would be ridiculous. The potential lies in reliable principles that can be applied to practical research. As previously discussed, survey practices are the norm for large scale research. Their specific intention is to gather a large number of data points across expansive samples of participants such that as samples grow larger, the log istical cost remains comparable. Survey research can be done well when the research design and modality is developed in reference to the topic appropriately. The constant challenge to survey research is the subjective experiences of participants and the co nsistency of the construct between studies. Statistical analyses applied to survey data are specifically designed to adjust for individual differences between participants in a normal fashion. Though they do not account for common differences experienced b y entire subgroups within a sample. Stereotype threat can be an example of this, where it has been shown that if a participant's group membership is made salient, they will answer survey questions differently to avoid confirming their own stereotype (Steel e & Aronson, 1995). Further, these tests for the most part begin with the assumption of a representative sample, and as shown in Burless and De Leo (2001) often key demographics are over or under represented. Then when statistical assumptions are met, ofte n studies cannot be compared because of the subjective inconsistency between constructs within a topic. Consistency and standardization must be a priority of large scale research in the future to attain the most meaningful and worthwhile results. As we see in the case of antisocial behavior, the stakes are too high in many cases for those in the behavioral sciences not to demand the absolute best practices of their discipline. When standardization does occur, it seems only practical to root as much of it as possible in the most consistent concrete traits and influences that apply to all humanity across groups.

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SURVEYS, MAOA L & OFC 46 Although science is a long way from analyzing someone's neural function conveniently in the day to day, it has already outlined many underlying physi cal influences on behavior that most of us share. These findings will continue to grow more relevant and expansive. It was even shown within this paper that using only published resources for reference and surveys selected based on physiological markers, a personality trait could be predicted with very modest logistical cost. It was also shown that immediate behavior could be primed based on physiological principles. The power of a concerted effort across research disciplines to apply knowledge of physiolog y in an effort to increase the reliability and validity of survey or other common forms of research would dwarf the fairly modest observations described here. Considering the weight that research findings carry in the world, and the needs of those who coul d benefit from valid research findings, any improvement to the practices of this research is well justified.

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SURVEYS, MAOA L & OFC 54 Rilling, J. K., Gutman, D. A., Zeh, T. R., Pagnoni, G., Berns, G. S., Kilts, C. D., Clinton, D. (2002). A neural basis for social cooperation. Neuron, 35 395 405. doi:10.1016/S0896 6273(02)00755 9 Roeckelein, J. E. (2006). Elsevier's dictionary of psychological theories Amsterdam: Elsevier. Retrieved from http://tb4cz3en3e.search.serialssolutions.com/?sid=sersol&SS_jc=TC0000082129&title= Elsevier%27s%20dictionary%20of%20psychological%20theories Rogers, R. D., Owen, A. M., Middleton, H. C., Willia ms, E. J., Pickard, J. D., Sahakian, B. J., & Robbins, T. W. (1999). Choosing between small, likely rewards and large, unlikely rewards activates inferior and orbital prefrontal cortex. The Journal of Neuroscience, 20 (19), 9029 9038. Retrieved from http:// www.jneurosci.org/content/19/20/9029 Santora, M. & Carey, B. (2005). What's worse, missed diagnosis or misdiagnosis? Pittsburgh Post Gazette A3. Sa§enroth, D. (2013). The Impact of Personality on Participation Decisions in Surveys DE: Springer Verlag. doi:10.1007/978 3 658 01781 1 S chac h ter S., & S inger J. E. (1962). Cognitive, social, and physiological determinants of emotional state. Psychological Review, 69 (5), 379 399. doi:10.1037/h0046234 Schmidt, S. (2010, January 26). Online privacy sketchy: survey. The Leader Post p. C8. Retrieved April 9, 2014, from www.lexisnexis.com/hottopics/lnacademic Soon, C. S., Brass, M., Heinze, H., & Haynes, J. (2008). Unconscious determinants of free decisions in the human brain. Nature Neuroscience, 11 (5), 543 545. doi:10.1038/nn.2112

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SURVEYS, MAOA L & OFC 55 Steele, C. M., & Aronson, J. (1995). Stereotype threat and the intellectual test performance of african americans. Journal of Personality and Social Psychology, 69 (5), 7 97 811. doi:10.1037/0022 3514.69.5.797 Task Force on DSM V, & American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental Disorders: DSM V Washington, DC: American Psychiatric Association. The New York City Department of Health a nd Mental Hygiene (2007). Detecting and treating depression in adults. City Health Information 26 (9), 59 66. Retrieved April 20, 2014, from http://www.nyc.gov/html/doh/downloads/pdf/chi/chi26 9.pdf Tourangeau, R., & Smith, T. W. (1996). Asking sensitive q uestions: The impact of data collection mode, question format, and question context. The Public Opinion Quarterly, 60 (2), 275 304. doi:10.1086/297751 Turner, C., Lessler, J., & Gfroerer, L. (1992). Future directions for research and practice. In Turner, C. Lessler, J., & Gfroerer, L. (Eds.), Survey Measurement of Drug Use: Methodological Studies 299 306. Washington, DC: Government Printing House. VandenBos, G. R., & American Psychological Association. (2007). APA Dictionary of Psychology Washington, DC: American Psychological Association. Williams, L. M., Gordon, E., Gatt, J. M., Kuan, S. A., Dobson Stone, C., Palmer, D. M., Schofield, P. R. (2009). A polymorphism of the MAOA gene is associated with emotional brain markers and personality traits on an antisocial index. Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology, 34 (7), 1797. doi:10.1038/npp.2009.1

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SURVEYS, MAOA L & OFC 56 Wolf, R. C., Thomann, P. A., Sambataro, F., Vasic, N., Schmid, M., & Wolf, N. D. (2012). Orbitofronta l cortex and impulsivity in borderline personality disorder: An MRI study of baseline brain perfusion. European Archives of Psychiatry and Clinical Neuroscience, 262 (8), 677 685. doi:10.1007/s00406 012 0303 1 Xiang, L., & Hester, R. L. (2012). Cardiovascular responses to exercise San Rafael, CA: Morgan & Claypool Life Sciences. doi:10.4199/C00040ED1V01Y201109ISP027 Yerkes Dodson law. (2006). In Elsevier's dictionary of psychological theories Retrieved from http://0 literati.credoreference.com. skyline.ucdenver.edu/content/entry/estpsyctheory/yerkes_dod son_law/0. Zillmann, D. (1988). Cognition excitation interdependences in aggressive behavior. Aggressive Behavior, 14 (1), 51 64. doi: 10.1002/1098 2337(1988)14:1<51::AID AB2480140107>3.0.CO;2 C

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SURVEYS, MAOA L & OFC 57 F igure 1. Procedure for Online Survey Study _____________________________________________________________________________________ _____________________________________________________________________________________ Participants logged on the Sona Systems web portal and were presented six of the above surveys in random order. After completion of these surveys participants completed demographics questions and logged off. _____________________________________________________________________________________

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SURVEYS, MAOA L & OFC 58 Figure 2 Regression Plots of Directional Relationships Between Criterion and Predicting Factors _____________________________________________________________________________________ Partial Regression Plot of Antisocial Behavior as Predicted By Risk Beh avior Attitudes _____________________________________________________________________________________ Partial Regression Plot of Antisocial Behavior as Predicted By Social Perspective Taking

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SURVEYS, MAOA L & OFC 59 _____________________________________________________________________________________ Partial Regression Plot of Antisocial Behavior as Predicted By Depression _____________________________________________________________________________________ Antisoci al Behavior Scores Between Male and Not Male Participants _____________________________________________________________________________________ Graphs demonstrate the directional relationship of predicting factors. As risky behaviors increase, antisocial behavior increases. As social perspective taking increases, antisocial behavior decreases. As depression increases antisocial behavior increases. Antisocial behavior is greater in males than those who are not male. ________________________________________ _____________________________________________ !"#$ !"%$ !"&$ !"'$ !"($ !")$ !"*$ !"+$ #$ #"!$ ,-.$/012$ /012$ Antisocial Behavior

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SURVEYS, MAOA L & OFC 60 Figure 3 Arousal and Prisoner's Dilemma Experiment Procedure _____________________________________________________________________________________ _______________________________________________________________________________________ Participants engaged in both five minutes of light exercise followed by one repetition of prisoner's dilemma game, and five minutes of slow breathing relaxation followe d by one repetition of prisoner's dilemma game. These two sequences occurred in counterbalanced order per session. After both sequences were completed, participants completed the Aggression Questionnaire and demographics questions. _______________________ ______________________________________________________________

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SURVEYS, MAOA L & OFC 61 Figure 4 Prisoner's Dilemma Game Defections for Arousal and Aggression Groups _____________________________________________________________________________ _______________________________ _______________________________________________ Means for PDG defections per median split high and low aggression survey groups. These graphs illustrate that there were no significant differences between aggression groups within each arousal condition. A s ignificant difference was observed such that participants defected more during relaxation versus arousal. ______________________________________________________________________________ 3$ !$ #$ %$ &$ '$ ($ Relaxation Condition Arousal Condition Prisoners Dilemma Game Defections Prisoners Dilemma Game Defection Means by Group High Aggression Low Aggression

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SURVEYS, MAOA L & OFC 62 Appendix A Instructions for the Prisoner's Dilemma Game as presented to participants: You are trying to win imaginary money for your favorite cause, this could be a charity or the phone you've always wanted, any cause you want. You will be anonymously grouped with another player who is also trying to win money for their favorite cause as well. Neither of you is trying to win more than the other, you are each trying to win as much for your cause as you can. This player may be another participant or a virtual player, but the identity of the other player will remain s ecret. To win money you will have two options for each round. You will have the option to play each round by either getting paid as a group or getting paid solo. If you choose to go solo, you could win the largest sum per round of $8, but only if the other player in your group chooses to get paid as a group. In this case the other player receives no money. If the other player in your group also chooses to go solo, in this case you both earn only $1 each. You can also choose to get paid as a group; in which case you could earn a sum of $5 per round, but only if the other player also chooses to get paid as a group. In that case, the other player also earns $5. If the player chooses to go solo in this case, they earn $8, and you earn no money for that round. Th ere will be a chart at the end of your answer sheet to remind you of the possible payoffs. When I indicate, you may write down your first choice on the line provided. I will record the answers, provide your scores for that round, and the task will continue