Social Neuroscience Exam 2 Review PDF

Social Neuroscience Exam 2 Review General tips for studying key topics to focus on = those that overlap between the lectures and textbook to quiz yourself, look at slides from lecture, and see if you can recall the main takeaways from each slide ○ if not, check your notes/textbook and figure out what...

Social Neuroscience Exam 2 Review General tips for studying key topics to focus on = those that overlap between the lectures and textbook to quiz yourself, look at slides from lecture, and see if you can recall the main takeaways from each slide ○ if not, check your notes/textbook and figure out what the point was be able to describe the main takeaways from studies mentioned in lecture slides ○ e.g., for slides that show data/results, describe what we can conclude about the findings be able to describe the main findings and/or arguments from additional readings — these slides primarily focus on lecture content, but don’t forget the readings! Cultural neuroscience What makes humans different? Modern human culture is too recently different from primates to have been biological evolution → what about social culture? The Social Brain Hypothesis returns! ○ Supported by the following studies: Dunbar (1992): Correlation between brain size and size of social group (humans = 150) Byrne & Corp (2004): Correlation between brain size and observations of tactical deception Reader & Laland (2002): Correlation between brain size and social learning, but also non-social intelligence (innovation, tool use) Joffe (1997): Brain size correlates with length of immaturity (i.e. greater role for social learning, ‘enculturation’) What is culture? Shared set of values, skills, artifacts, and beliefs amongst a group of individuals and differentiated across different groups Learned via a process of social learning from person to person, both within and across generations (not innate) May evolve independently from genes (think: memes) ○ Ideas can emerge and go “viral” across culture without genetic reason Cultural Differences in the Self Independent Self-Construal Interdependent Self-Construal Individualistic Promotes self-expression, own goals, direct communication Others help self-evaluation through social comparison Self esteem based on ability to express self and validate internal attributes Associated with US & Europe Collectivist Promotes belonging, appropriate behavior, indirect communication Others help defining self through relationships in context Self esteem based on ability to maintain harmony with social context Associated with East Asia Culture Gene Co-Evolution Theory 5HTT: serotonergic uptake transporter gene ○ long variant (l/l) → more serotonin uptake ○ short variant (s/s) → less serotonin uptake BUT associated with susceptibility to anxiety, fear conditioning, etc. e.g. Hariri et al. (2002): s/s group had greater amygdala response to fearful expressions than l/l Since Japan’s population has a greater s/s to l/l ratio, we would expect there to also be more susceptibility to anxiety, etc. However, the opposite is true! The US has greater prevalence of mood disorders. Culture Gene Co-Evolution Theory Theory: Perhaps interdependent culture has evolved in areas with more s/s allele to buffer against predisposed negative mood effects. Cultural Neuroscience Approaches Source Analysis: Try to discern where observed cultural differences/similarities come from, such as between independent and interdependent cultures. ○ Mainly relies on correlational data. ○ Culture Gene Co-Evolution Theory is an example of this! Cultural Mapping: Use cross-cultural neuroimaging to map different observed cultural patterns with neurological patterns. Cultural Mapping Studies Freeman et al. (2009): Reward regions activated to dominant behavior in Americans and subordinate behavior in Japanese, which correlated with self-reported dominance and subordination. Culturally reinforced behavior manifests through reward system. Zhu et al. (2007): When processing traits of self, mother, and a famous person, Chinese participants had mPFC activation in self and mother whereas American participants only activated self Manifestation of interdependent self-construal. Cultural Mapping Studies: Analytic vs. Holistic Hedden et al. (2008): Attentional network activated more to cultural nonpreferred judgments in frame and line task (e.g. relative for Americans) Self-construal affects visual perception and visual attention. Lin & Han (2006): When Chinese participants were primed global/local stimuli with “I” vs “we” narratives, they showed difference in global precedence effect. Self-construal can be influenced by priming. Masuda et al. (2008): Through eye tracking, Americans spent more time looking at focal child in image than Japanese participants, who looked at contextual figures, in order to judge emotion of focal child. Evidence for Western/local and East Asian/contextual associations. Highlighted Study: Freeman, Ma, Han, & Ambady (2013) Task: Judge the race of Chinese/White morphed faces in congruent, neutral, and incongruent backgrounds. Result: Chinese participants showed faster incorporation of context than Americans. ○ Maybe Chinese participants have extra preparedness to incorporate context. Cultural Mapping Studies: Analytic vs. Holistic Blais et al. (2008): Western participants looked more at eyes and mouth, whereas East Asian participants looked (on average) more at center of face. Maybe E.A. participants look more at whole face OR maybe cultural cues about eye contact, etc. affect this Jack et al.: Eyes seem to matter more for East Asian participants to recognize emotions, compared to the mouth mattering to Western participants. Cultural Emotional Dialects Perspective 1 (Ekman/Darwin/etc.) ○ Emotion is ultimately universal (e.g. 6 basic emotions), but display/discoding rules may exhibit cultural differences. Perspective 2 (Elfenbein/Ambady/etc.) ○ Emotion may IN PART be universal, but there is a culturally specific component as well. Cultural Emotional Dialects: Elfenbein’s Theory Those with similar cultural backgrounds (i.e. more shaded area) will be quicker/better at recognizing one another’s emotions. ○ Chiao et al. (2007): Amygdala shows stronger response to own-culture fear than other-culture fear. ○ Adams et al. (2009): Japanese and American students were more accurate at own-culture RME than other-culture RME. Both groups also showed higher activation in STS for own-culture displays than other-culture displays Origins of Culture: The Culture Pyramid Social Information Transfer: one member of a species can pick up something from another member, not necessarily goal-oriented. ○ Mammals, birds, fish, some invertebrates Traditions: learned and persisting methods to do things among a species. ○ Birds (e.g. birdsongs) Culture: a set of traditions persisting. ○ Monkeys and apes (e.g. different distributions of social games) Cumulative culture: cultural practices are advancing on their own ○ Only humans? Social Learning Whiten et al. (2005): When chimps are trained in one method to get food, members within the group will learn that tradition and resist using another group’s method when taught the second. Methods of Social Learning ○ Imitation: reproducing the goals (but not necessarily steps) of another ○ Mimicking: copying the action of another without understanding the goal of the action (e.g. talking parrot mimicking human speech) ○ Stimulus/local enhancement: drawing attention to an object/place may facilitate self discovery ○ Contagion: repetition of behaviors innate rather than learned (e.g. yawning) Imitation in Human Infants When watching woman bump button with hands occupied, infants use hands. ○ Infants understand the goal is probably just to press the button. When watching woman with hands free use her head, infants use head. ○ Infants think there must be a reason the woman is using her head when she doesn’t have to. Similar to theory of mind! ○ Despite not passing Sally-Anne. Imitation in Non-Human Primates Possible imitation can often be explained by stimulus/local enhancement effects. Pro imitation in chimps: ○ Chimps but not macaques can learn a do-as-I-do game with training. ○ When using tools to get rewards, chimps will omit irrelevant stages. Anti imitation in chimps: ○ Imitation is not prevalent in the wild and often must be trained in labs. ○ Imitation may serve a more social function in humans, whereas for chimp it’s just for survival reasons (to get food, etc.). Tools, Symbols, Extended Cognition neural recycling: neural resources, set aside for other functions in the evolutionary past, can be recruited by cultural innovations ○ e.g. reading and numeric recognition recruit similar resources in different cultures’ brains despite being a cultural invention extended cognition: the material world and cultural symbols can expand the cognitive capacities of humans ○ e.g. french controls did better than munduruku on exact subtraction as magnitude of numbers gets higher, but both did equally well on approximate addition / comparison Tool Use Humans use lots of tools spontaneously ○ Some theories suggest this actually facilitated cultural innovation Non-human primates must usually be trained to use tools Multi-sensory tool neurons have receptive fields that are receptive in a multisensory way and rapidly extend along tool as if extension of the actual body ○ Exhibited in primates trained on tool use Mirror Neurons Responds to both doing an action and watching someone else do action ○ Includes implied actions as well e.g. when the action is implied to happen behind a screen ○ Responds to accomplishing the same goal with different action steps e.g. normal pliers AND reverse pliers to pick something up Mirror Neurons Question: ○ Monkeys, chimps, humans all possess mirror neurons, BUT why do different species differ dramatically in spontaneous use (vs training) of imitation and tool use? Potential Answer: ○ Iriki & Sakura (2008): What is different between macaque brains before and after mastering tool use? Tool use → changes in gene expression: extra connections in IPS (has multisensory and mirror neurons) and TPJ (TOM) Conclusion: Maybe these pathways are innately developed in humans but only emerge in monkeys after deliberate training Groups, prejudice, & stereotyping mPFC & “the self” although we can’t say that your identity “lives” in the mPFC, this region is involved in thinking about oneself, e.g., making trait judgments about yourself, both positive & negative (Kelley et al., 2002; Moran et al., 2006) making trait judgments about others similar to yourself (Mitchell et al., 2005) hearing one’s own name thinking about arbitrary associations with oneself during attention & memory tasks (e.g., remembering a novel scene picture by imagining you and your friends visiting that location) reflecting on your own emotions Dividing up “the self” “a sense in which our self is located within the space occupied by our own bodies” this is disrupted during out of body experiences can occur in people with lesions in the rTPJ or using a virtual reality paradigm (where the participant observes a virtual avatar of their own body); Lenggenhager et al., (2007) Dividing up “the self” e.g., memory this can be influenced by: the tendency to remember past versions of oneself as similar to one’s present self ○ e.g., political attitudes; Marcus, 1986 the tendency to remember the past in a self-enhancing or flattering manner ○ ○ Sahdra & Ross, 2007 Ross & Wilson, 2002 Groups Johnson & Johnson, 1987 argue a group is a collection of individuals who: ○ ○ ○ ○ ○ ○ ○ interact with one another perceive themselves as belonging to a group are interdependent join together to achieve a goal try to satisfy some need through their joint association have interactions that are structured by a set of roles and norms influence each other a group can refer to a lot of different things, depending on what you’re interested in testing Social identity social identity: a collection of different group memberships (e.g., nationality, race, religion, political allegiances) different elements of one’s social identity can be prioritized in different situations: ○ Asian women perform/perceive themselves as better at math when ethnic identity is highlighted, but worse when gender identity is (Shih et al., 1999; Ambady et al., 2002) ○ White women hold more negative attitudes towards Black women when race vs. gender is highlighted (Mitchell, Nosek, & Banaji, 2003) Social identity: “the big three” age gender race processing these categories is automatic and obligatory, and spontaneously triggers stereotypes, attitudes, and behavioral tendencies associated with a particular identity/group membership Stereotyping stereotyping: perceiving members of a given category as possessing various common attributes ○ efficient way of organizing/storing information about people ○ source of bias & generalization in general, categorizing things into groups is an efficient cognitive shortcut ○ it is adaptive in many situations (e.g., easily recognizing a never-before-seen object as a “mug”) ○ however, categorizing people in this way is problematic can be assessed with mouse-tracking paradigms (Freeman & Ambady, 2009; Freeman et al., 2011) Freeman et al., 2011 paradigm: participants categorize individuals as either White or Black ○ individuals are either wearing high-status clothing (suit) or low-status clothing (janitor’s jumpsuit) method: computer mouse tracking ○ measuring how much partial attraction participants had to the opposite category result: visual perception of race is influenced by stereotypes ○ when a racially ambiguous individual is wearing low-status clothing, mouse trajectories will be “pulled” in the direction of the Black vs. White category label Prejudice prejudice: negative attitudes, emotions, or behaviors to members of a group on the basis of their membership of that group prejudice can be assessed using explicit (questionnaires) & implicit measures (e.g., electromyography, IAT) Stereotyping vs. prejudice stereotyping is more cognitive, whereas prejudice is more emotional ○ similarly, the two processes are associated with distinct brain networks: stereotyping: dorsal mPFC, anterior temporal lobe (ATL), lateral temporal lobe, inferior frontal gyrus (IFG) [regions associated with more cognitive processes, e.g., knowledge, memory, reasoning about others] prejudice: amygdala, insula, striatum, ventral mPFC, OFC [regions associated with emotion processing, empathy, disgust/pain, automatic responses, etc.] both can be either explicit or implicit The Implicit Association Test (IAT) uses two simultaneous categorization tasks: ○ one about social groups (e.g., categorizing faces as Black vs. White) ○ one about valence (e.g., categorizing adjectives as Good vs. Bad) compare reaction times (RTs) when tasks are congruent with a stereotype (e.g., White & Good map onto the same button) vs. incongruent (e.g., White & Bad use the same button) ○ faster RTs for congruent vs. incongruent trials → stronger biases incongruent congruent The IAT, continued can be used to assess other biases beyond race, e.g., nationality, politics, gender ○ emotional associations (e.g., Black – bad) → implicit measure of prejudice ○ semantic associations (e.g., Black – athletic) → implicit measure of stereotyping tends to predict implicit, but not explicit, measures of bias ○ IAT scores are stable across age ○ explicit measures of prejudice/stereotyping tend to decrease with age (e.g., due to learning, increased experience, and/or desirability bias) sensitive to current task demands (e.g., priming with well-liked Black individuals can lower pro-White anti-Black bias scores on an IAT) more recently, criticized for being not that reliable within individuals The amygdala & social bias Phelps et al. (2001): amygdala activity when viewing Black faces scales with (pro-White/anti-Black) IAT scores (but not explicit racism scores) ○ amygdala activity also correlates with startle eyeblink responses (to Black faces) Cunningham et al. (2004): when viewing out-group faces, amygdala activity is only observed during early stages of visual processing (~30 ms) ○ other regions like lateral PFC, which are often associated with cognitive control/self-regulation, come online later on (~500 ms) — which presumably reflects participants’ goals to be egalitarian/equitable/etc. Lieberman et al. (2005): both Black & White participants show increased amygdala activity to Black vs. White faces, although variation amongst Black individuals in this effect is higher ○ suggests that this response may be more about stereotypes than prejudice The amygdala & social bias (continued) Van Bavel et al. (2008): using minimal group paradigm, amygdala activation is greater to novel in-group members, relative to novel out-group members ○ minimal group paradigm: individuals belong to groups based on superficial attributes, such as the color/pattern of the clothes they wear ○ shows that amygdala responses to group members is influenced by motivation/task goals So what can we conclude about the amygdala? Amygdala activity does not reflect an ‘out-group neural signature’ but a complex evaluation that takes into account familiarity with particular members of the out-group, socio-cultural stereotypes, and motivation relevance. Bias as reduced mentalizing some work suggests that bias results in dehumanization, i.e., less mentalizing or thinking about outgroup members as people ○ Harris & Fiske, 2006: people arguably vary along two dimensions: competence and warmth groups that are perceived to be low in both (e.g., people who are unhoused or dealing with addiction) is associated with a lack of activation in the mPFC (a region associated with mentalizing) Control of prejudice knowing about stereotypes and prejudices — but not acting upon them — requires self-control people also vary in their motivations for controlling prejudicial attitudes: ○ internal: avoiding prejudiced behaviors due to intrinsic goals (e.g., wanting to be a good person) ○ external: avoiding prejudiced behaviors due to outside pressures (e.g., avoiding disapproval from others) ○ Amodio et al. (2003): greater internal motivations → lower IAT scores Kubota et al. (2012): propose that the ACC (anterior cingulate cortex) and dorsolateral PFC are involved in monitoring and controlling racial bias some anti-prejudice interventions do reduce IAT scores, but effects are usually short-term Top-down vs. bottom-up processing bottom-up processing: based on features of the stimulus itself ○ social examples: facial, vocal, & bodily cues top-down processing: based on learned expectations or knowledge ○ social examples: person knowledge, social context, stereotypes, goals/motivations, emotions top-down expectations influence stimulus perception ○ e.g., perceiving an ambiguous letter as A or H depending on the word it’s embedded within Dynamic interactive (DI) model TOP-DOWN BOTTOM-UP unlike the feed-forward model, the DI model argues that our stereotypes, attitudes, etc. influence how we categorize & perceive other people feed-forward model the feed-forward model argues that perception & social categorization happen first, and then we activate stereotypes, attitudes, etc. dynamic interactive model Dynamic interactive (DI) model the dynamic interactive model argues that social perception is flexible & is influenced by our current context/goals and our learned social knowledge predicts that our perception of a social stimulus (e.g., a racially-ambiguous face) will be shaped by top-down expectations, such as the stereotypes we associate with social categories the face could belong to ○ Freeman et al. (2011) — see this slide ○ other mouse-tracking studies (Freeman et al. (2008), JEP:G; Freeman et al. (2010), JESP; Freeman (2014), PBR): when categorizing faces with features that are “atypical” for a given race, mouse trajectories are biased toward the racial category more typically associated with those facial features relevant brain regions: fusiform gyrus (FG), orbitofrontal cortex (OFC), and anterior temporal lobe (ATL) Reverse correlation technique reverse correlation: goal is to try and identify what representation or mental image is in a perceiver’s mind when they imagine a member of a particular social group ○ start with a base face (a fuzzy, composite image of many different faces), then add various noise patterns on top of it (which will modify its features in a random variety of ways to generate new faces) ○ Dotsch et al. (2008): asked Dutch participants to judge these noisy faces as more vs. less Moroccan, then asked another set of participants to rate which faces were more trustworthy vs. criminal participants (in the second group of raters) who were higher in prejudice rated more prototypically Moroccan faces as less trustworthy ○ Brooks & Freeman (2018): used a similar approach for male vs. female faces & judgments of happiness vs. anger Stereotypes & visual perception: multivariate fMRI Stolier & Freeman (2017): participants categorize faces as male or female, in a standard mouse-tracking paradigm; some faces are more prototypically masculine/feminine than others ○ when participants showed greater mouse-tracking attraction toward the non-chosen category (e.g., for male faces with more feminine features), brain activity patterns in the fusiform gyrus (FG) look more similar to activity evoked when viewing typical/feminine female faces Stolier & Freeman (in prep): when participants view faces of a particular race, brain activity patterns in the anterior temporal lobe (ATL) look similar to patterns evoked when participants think about concepts stereotypically associated with that racial group ○ e.g., when viewing an Asian face, ATL activity looks similar to how it does when thinking about the word “shy” Stereotypes & visual perception Stolier & Freeman (2016): compares three ways of quantifying stereotypes: ○ stereotype knowledge (participants rate how strongly different traits are associated with different social groups) ○ mouse-tracking patterns during social categorization ○ neural representations (looking at activity patterns in OFC and rFG while participants view faces from different social groups) ○ main takeaways: these different ways of characterizing knowledge/biases about social groups are all linked to each other, e.g., stronger stereotype knowledge/beliefs will lead to stronger biases in visual perception these effects are not driven by objective visual similarity between certain social categories Stereotypes & visual perception (cont.) more on Stolier & Freeman (2016): Prediction: people’s conceptual knowledge (stereotype knowledge) and social perception (mouse tracking) relates to their neural representations (multivoxel pattern similarity) Method ○ computer mouse tracking ○ conceptual knowledge (participants rated stereotype knowledge like “to what extent does the typical american believe asian people are…”) phrased to avoid Social Desirability Bias ○ Neural Representations OFC and rFG Prediction was true (e.g., regions for male are more similar to Black than they are to Asian) Stereotyping patterns appear to manifest in the brain as well Black concept Angry concept Black faces Angry faces ≈ Stereotypes & visual perception: efficiency numerous studies have found that visual processing becomes more efficient when two stereotypes align with each other ○ for example: Black, male faces are more easily categorized as male than Asian, male faces Angry male faces are more easily categorized as male than happy, the opposite is true for female faces Stereotypes & visual perception: weapon identification weapon identification tasks: after perceiving a Black (vs. White) face, participants are more likely to identify an object as a gun vs. tool ○ Payne (2001); Payne (2006); Correll et al. (2002); Correll et al. (2015); Amodio (2014) Oh, Vartiainen, & Freeman (in prep) extended this work to fMRI, and found that after viewing Black (vs. White) faces, brain activity patterns while viewing a tool looked more similar to patterns evoked while viewing guns this work suggests that activated stereotypes (e.g., the association between Black individuals and violence) influences how we perceive visual objects Reading faces, bodies, & voices The Importance of Reading Faces, Bodies, Voices Studies show that reading faces bodies and voices can have a powerful impact on how we see others ○ Judgments of the competence of a professor from short, photoshopped, outlined video clips of the professor lecturing, could predict the end-of-semester evaluations of the professor ○ Competence judgments from faces of politicians predict electoral success ○ Power-related judgments predict CEOs’ company profits Social cues reveal all kinds of aspects about someone ○ ○ ○ ○ ○ ○ Personality traits Emotions Social categories (race, sex, age) Intentions Identity Social status How are faces processed? Features vs. configurations ○ Features = part-based processing of faces (process eyes, mouth, nose separately) ○ Configurations = holistic processing of faces (process whole face at once) All faces are actually very similar from an objective standpoint ○ Little statistical variation in physical features ○ Yet, to our brains, it seems like each person’s face is very distinct - the brain makes a lot out of a little Therefore, face perception relies on configural information — the sum of all of the little parts combined When faces are inverted, recognition is impaired, and featural processing dominates — we see the individual parts of the person’s face but can’t make out the bigger picture of who it is Importance of Configuration Configural processing explains how facial recognition can be so robust despite a variety of natural and unnatural transformations in faces ○ In other words, it explains how we can tell whose face it is even when a person makes all kinds of different faces ○ Even though the individual features of the person’s face are shifted, the overall configuration of their face remains largely the same ○ Seen even with animal faces, e.g. expert dog breeders use configural processing to identify individual dogs What would make faces special? Is there anything special about faces as a stimulus category or are they just like any other category of objects? Hay and Young (1982): ○ Uniqueness — are the perceptual/cognitive processes used for face recognition different in nature than those used for other stimuli? ○ Specificity — are these processes for face recognition organized in a separate system in the brain, or are they more interconnected? Models of Facial Recognition (Bruce & Young) Bruce and Young (1986) ○ Largely superseded by later models that incorporate fMRI evidence Models of Facial Recognition (Haxby) Haxby et al. ○ ○ Division into “core system” (directly faced related) and “extended system” (face-related, but also more general, processing emotion, visual information, audio, etc.) Evidence from fMRI Certain brain regions = core system STS, FFA, OFA Others = extended system Amygdala, anterior temporal, etc. Face-selective areas Fusiform face area (FFA) Codes facial identity Relatively specialized for faces but the FFA also responds to other stimuli people have a high degree of expertise in (e.g., birds for bird experts; Gauthier et al. (2000), and to novel creature-like stimuli called greebles (Gauthier et al., 1999) Haxby et al. (2001): if we look only at visual regions outside of the FFA, brain activity can still be used to discriminate faces (using fMRI classification analysis) Occipital face area (OFA) Relatively specialized for faces Codes physical aspects of the face (features) Superior temporal sulcus (STS) Responds to both faces and bodies Processes actions, e.g. lip movements Integrates audio and visual information Haxby et al. (2000): STS responds to changeable aspects of face (gaze, expression) Hoffman & Haxby (2000): Judging gaze direction activates STS not FFA, but judging face identity activates FFA not STS Prosopagnosia vs. Capgras illusion Prosopagnosia: also called “face blindness”; refers to a condition in which individuals are unable to recognize/identify faces Capgras delusion: a disorder in which an individual believes that the familiar person they are looking at has been replaced by a false double/clone healthy individuals typically show an elevated skin conductance response (SCR) when looking at familiar people ○ this response still occurs in prosopagnosia ○ but not in the Capgras delusion Recognizing emotional expressions there is a distinction between recognizing a face and being able to recognize its expression, and it’s still unclear from present research which regions are most implicated in the process of expression recognition impairments in recognizing facial expressions are more commonly linked to the ‘extended system’ (see Haxby’s model) ○ damage to the amygdala impairs fear recognition, damage to the insula impairs disgust recognition; both the OFC and regions involved in mental simulation also might play a role although the STS might also play a role, as a multi-modal integrative center (integrating audio, visual, emotional, other information) (e.g., Calder & Young, 2005) Trait impressions & evaluations people form impressions of others based on their faces very rapidly two dimensions of trait evaluation: trustworthiness & dominance (Oosterhof & Todorov, 2008) ○ faces can be organized along these dimensions amygdala activity shows both negative linear & nonlinear relationships to facial trustworthiness, in that activity is generally stronger for untrustworthy faces, but is also stronger for highly untrustworthy AND highly trustworthy faces compared to in-between faces (Engell et al., 2007; Said et al., 2009) ○ these effects occur even when face perception is non-conscious (Freeman et al., 2014) facial trustworthiness is more variable/changeable than dominance Basis of trait evaluations some trait evaluation are based on accurate & diagnostic cues ○ Facial width-to-height ratio (fWHR) relates to pubertal testosterone in men also predicts penalty minutes per game in hockey players relates to facial dominance: facial dominance may be relatively hard to change because it relates to fWHR, which is a relatively fixed physical characteristic ○ Sexually-dimorphic cues e.g. high fWHR associated with higher pubertal testosterone, and higher pubertal testosterone is linked to greater aggression in men Basis of trait evaluations (continued) are stereotypes/biases rooted in accuracy at all? ○ one common stereotype: gay men are more feminine; lesbian women are more masculine Freeman et al., 2010: tested whether participants could discriminate between gay & straight individuals; accuracy was better than chance, but not by much so while there might be some association between sexuality and how gender atypical someone’s face in, the relationship is very modest ○ Dorian Gray effects: over time, somebody’s traits/behaviors can manifest in their face (e.g., somebody who spends much of their youth being angry may develop angrier features over time) in general, there is a very complex interaction between biology, environmental factors, and behavior in determining one’s appearance Additional readings Adams Jr. et al. (2009): Cross-cultural Reading the Mind in the Eyes White & Asian participants view images of eyes from White and Asian faces, and have to select which of 4 different mental states (e.g., worried, friendly) the face reflected participants were more accurate in reading mental states from eyes when faces belonged to in-group vs. out-group members the superior temporal sulcus (STS) was also enhanced when participants viewed eyes from a face from their same culture the authors conclude that STS is generally involved in inferring others’ mental states, and that this processed is enhanced for within-culture reasoning Freeman & Johnson (2016): More Than Meets the Eye: Split-Second Social Perception the majority of this article discusses studies covered in the lecture! see slides here and here at the end of the “stereotypes” section ○ remember: you don’t need to memorize every detail of every study discussed here; just understand the main takeaways, and pay special attention to the sections that mention studies that came up in class Freeman et al. (2014): Amygdala Responsivity to High-Level Social Information from Unseen Faces using a paradigm where participants viewed faces that varied in their trustworthiness ○ backward masking approach used to ensure that faces were not processed consciously the amygdala shows negative linear effects of trustworthiness, i.e., stronger activation to untrustworthy faces ○ this presumably reflects a kind of “alarm bell” system, so that we can become rapidly aware of potential dangers but the amygdala also shows nonlinear effects, i.e., stronger activation to highly untrustworthy & highly trustworthy faces ○ this relates to the amygdala’s modulation by motivational relevance — highly trustworthy faces are worth paying attention to as well