Decision-making under risk and its correlates in schizophrenia.

Schizophrenia spectrum disorders (SSD) are associated with pervasive cognitive impairments, including deficits in decision-making under risk. However, there is inconclusive evidence regarding specific mechanisms underlying altered decision-making patterns. In this study, participants (33 SSD and 28 non-SSD) completed the Columbia Card Task, an explicit risk-taking task, to better understand risk preference and adjustment in dynamic decision-making. We found that while there is no group difference in overall risk-taking, risk preference, or optimal decision-making, risk adjustment to contextual factors (e.g., loss probability) is blunted in SSD. We also found associations between risk-taking/suboptimal decision-making and disorganized symptoms, excited symptoms, and role functioning, but no associations between decision-making and working memory. These results suggest that during a complex, dynamic risk-taking task, individuals with SSD exhibit less adaption to changing information about risk, which may reflect risk imperception.

Social victimization, default mode network connectivity, and psychotic-like experiences in adolescents.

Social victimization (SV) and altered neural connectivity have been associated with each other and psychotic-like experiences (PLE). However, research has not directly examined the associations between these variables, which may speak to mechanisms of psychosis-risk. Here, we utilized two-year follow-up data from the Adolescent Brain Cognitive Development study to test whether SV increases PLE through two neural networks mediating socio-affective processes: the default mode (DMN) and salience networks (SAN). We find that a latent SV factor was significantly associated with PLE outcomes. Simultaneous mediation analyses indicated that the DMN partially mediated the SV-PLE association while the SAN did not. Further, multigroup testing found that while Black and Hispanic adolescents experienced SV differently than their White peers, the DMN similarly partially mediated the effect of SV on PLE for these racial groups. These cross-sectional results highlight the importance of SV and its potential impact on social cognitive neural networks for psychosis risk.

Training volitional control of the theory of mind network with real-time fMRI neurofeedback.

Is there a way improve our ability to understand the minds of others? Towards addressing this question, here, we conducted a single-arm, proof-of-concept study to evaluate whether real-time fMRI neurofeedback (rtfMRI-NF) from the temporo-parietal junction (TPJ) leads to volitional control of the neural network subserving theory of mind (ToM; the process by which we attribute and reason about the mental states of others). As additional aims, we evaluated the strategies used to self-regulate the network and whether volitional control of the ToM network was moderated by participant characteristics and associated with improved performance on behavioral measures. Sixteen participants underwent fMRI while completing a task designed to individually-localize the TPJ, and then three separate rtfMRI-NF scans during which they completed multiple runs of a training task while receiving intermittent, activation-based feedback from the TPJ, and one run of a transfer task in which no neurofeedback was provided. Region-of-interest analyses demonstrated volitional control in most regions during the training tasks and during the transfer task, although the effects were smaller in magnitude and not observed in one of the neurofeedback targets for the transfer task. Text analysis demonstrated that volitional control was most strongly associated with thinking about prior social experiences when up-regulating the neural signal. Analysis of behavioral performance and brain-behavior associations largely did not reveal behavior changes except for a positive association between volitional control in RTPJ and changes in performance on one ToM task. Exploratory analysis suggested neurofeedback-related learning occurred, although some degree of volitional control appeared to be conferred with the initial self-regulation strategy provided to participants (i.e., without the neurofeedback signal). Critical study limitations include the lack of a control group and pre-rtfMRI transfer scan, which prevents a more direct assessment of neurofeedback-induced volitional control, and a small sample size, which may have led to an overestimate and/or unreliable estimate of study effects. Nonetheless, together, this study demonstrates the feasibility of training volitional control of a social cognitive brain network, which may have important clinical applications. Given the study's limitations, findings from this study should be replicated with more robust experimental designs.

Social affective forecasting and social anhedonia in schizophrenia-spectrum disorders: a daily diary study.

Social anhedonia (SA) is a trait-like phenomenon observed across schizophrenia-spectrum disorders (SSDs). While in-the-moment social pleasure experiences are intact in SSDs, anticipatory pleasure experiences may be disrupted. Thus, the prediction of future emotions in social situations, or social affective forecasting (SAF), may play a role in SA. Therefore, we utilized daily diary methods to examine SAF in SSD and the association between SAF and SA in 34 SSD and 43 non-SSD individuals. SAF was calculated as the absolute difference between anticipatory and consummatory ratings of 13 positive and negative emotions for daily social interactions reported across eight days. Results suggest that individuals with SSDs are less accurate in forecasting negative, but not positive emotions, for future social interactions. Further, poorer forecasting accuracy of negative emotions were associated with elevated levels of SA and lower social pleasure. Together, these data suggest that inaccuracies in forecasting negative emotions may be a worthwhile intervention target for reducing SA in SSDs.

Social cognition training improves recognition of distinct facial emotions and decreases misattribution errors in healthy individuals.

Facial emotion recognition is a key component of social cognition. Impaired facial emotion recognition is tied to poor psychological wellbeing and deficient social functioning. While previous research has demonstrated the potential for social cognition training to improve overall facial emotion recognition, questions remain regarding what aspects of emotion recognition improve. We report results from a randomized controlled trial that evaluates whether computerized social cognition training can improve recognition of distinct facial emotions in healthy participants. This investigation was designed to better understand the therapeutic potential of social cognition training for individuals with neuropsychiatric disorders. Fifty-five healthy adult participants were randomly assigned to an internet-based intervention during which they either completed social cognition training (SCT) or played control computer games (CON) for 10.5 h over 2-3 weeks. Facial emotion recognition was measured with the Penn ER-40, which was conducted before and after training. The following variables were collected and analyzed: facial emotion recognition accuracy for each emotion (i.e., anger, fear, happy, neutral (no emotional expression), and sad), reaction times for each emotion, and response error types (i.e., frequency of an emotion being chosen incorrectly, frequency of an emotion being missed, and frequency of an emotion being confused for another particular emotion). ANOVAs and t-tests were used to elucidate intervention effects both within and between groups. Results showed that the SCT group improved their accuracy for angry and neutral faces. They also improved their reaction times for neutral, fearful, and sad faces. Compared to the CON group, the SCT group had significantly faster reaction times to neutral faces after training. Lastly, the SCT group decreased their tendency to confuse angry faces for no emotional expression and to confuse no emotional expression for sad faces. In contrast, the CON group did not significantly improve their accuracy or reaction times on any emotional expression, and they did not improve their response error types. We conclude that social cognition training can improve recognition of distinct emotions in healthy participants and decrease response error patterns, suggesting it has the potential to improve impaired emotion recognition and social functioning in individuals with facial emotion recognition deficits.

Explaining the Association Between Urbanicity and Psychotic-Like Experiences in Pre-Adolescence: The Indirect Effect of Urban Exposures.

Urban living is a growing worldwide phenomenon with more than two-thirds of people expected to live in cities by 2050. Although there are many benefits to living in an urban environment, urbanicity has also been associated with deleterious health outcomes, including increased risk for psychotic outcomes particularly when the urban exposure occurs in pre-adolescence. However, the mechanisms underlying this association is unclear. Here, we utilize one-year follow-up data from a large (N=7,979), nationwide study of pre-adolescence in the United States to clarify why urbanicity (i.e., census-tract population density) might impact psychotic-like experiences (PLE) by looking at the indirect effect of eight candidate urbanicity-related physical (e.g., pollution) and social (e.g., poverty) exposures. Consistent with other work, we found that of the evaluated exposures related to urbanicity, several were also related to increased number of PLE: PM2.5, proximity to roads, census-level homes at-risk for exposure to lead paint, census-level poverty, and census-level income-disparity. These same urban-related exposures were also related to the persistence of PLE after 1 year, but not new onset of PLE. Mediation analysis revealed that a substantial proportion the urbanicity-PLE association (number and persistence) could be explained by PM2.5 (23-44%), families in poverty (68-93%), and income disparity (67-80%). Together, these findings suggest that specific urban-related exposures contribute to the existence and maintenance, but not onset of PLE, which might help to explain why those in urban environments are disproportionately at-risk for psychosis and point toward areas for public health intervention.

The Neural Basis of Social Cognition in Typically Developing Children and Its Relationship to Social Functioning.

Theory of mind (ToM), the ability to think about the perspectives, beliefs, and feelings of another, develops throughout childhood and adolescence and is an important skill for social interactions. This study examines neural activity in typically developing children during a novel ToM task - the Movie Mentalizing Task- and tests its relations to ToM behavioral performance and social functioning. In this fMRI task, children ages 8-13years (N=25) watched a brief movie clip and were asked to predict a character's mental state after a social interaction. Engaging in the Movie Mentalizing Task activated the ToM neural network. Moreover, greater neural activity in the ToM network, including the superior temporal gyrus and inferior frontal gyrus, was associated with better behavioral performance on independent ToM tasks and was related to better social functioning, though these results do not survive correction for multiple comparisons. Results offer a new affective theory of mind task for children in the scanner that robustly recruits activity in theory of mind regions.

The representation of mental state information in schizophrenia and first-degree relatives: a multivariate pattern analysis of fMRI data.

Individuals with a schizophrenia-spectrum disorder (SSD) and those at familial high risk (FHR) for SSDs experience social difficulties that are related to neural abnormalities in the network of brain regions recruited during theory of mind (ToM). Prior work with these groups has focused almost exclusively on characterizing the involvement of these regions in ToM. Here, we examine the representational content of these regions using multivariate pattern analysis. We analyzed two previously collected datasets of SSD, FHR and control participants who, while undergoing functional magnetic resonance imaging, completed the false-belief task in which they read stories describing beliefs or physical representations (e.g. photographs). Univariate and multivariate analyses were performed in regions of interest to evaluate group differences in task-based activation and representational content, respectively. Compared to non-SSDs, SSDs showed reduced decoding accuracy for the category of mental states in the right temporo-parietal junction-which was related to false-belief accuracy-and the dorsal medial prefrontal cortex (DMPFC) and reduced involvement of DMPFC for mental state understanding. FHR showed no differences in decoding accuracy or involvement compared to non-FHR. Given prior studies of disrupted neural involvement in FHR and the lack of decoding differences observed here, the onset of illness may involve processes that corrupt how mental state information is represented.

The efficacy of real-time functional magnetic resonance imaging neurofeedback for psychiatric illness: A meta-analysis of brain and behavioral outcomes.

Real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF) has gained popularity as an experimental treatment for a variety of psychiatric illnesses. However, there has yet to be a quantitative review regarding its efficacy. Here, we present the first meta-analysis of rtfMRI-NF for psychiatric disorders, evaluating its impact on brain and behavioral outcomes. Our literature review identified 17 studies and 105 effect sizes across brain and behavioral outcomes. We find that rtfMRI-NF produces a medium-sized effect on neural activity during training (g = .59, 95 % CI [.44, .75], p < .0001), a large-sized effect after training when no neurofeedback is provided (g = .84, 95 % CI [.37, 1.31], p = .005), and small-sized effects for behavioral outcomes (symptoms g = .37, 95 % CI [.16, .58], p = .002; cognition g = .23, 95 % CI [-.33, .78], p = .288). Mixed-effects analyses revealed few moderators. Together, these data suggest a positive impact of rtfMRI-NF on brain and behavioral outcomes, although more research is needed to determine how rtfMRI-NF works, for whom, and under what circumstances.

Comparability of social anhedonia across epidemiological dimensions: A multinational study of measurement invariance of the Revised Social Anhedonia Scale.

Social anhedonia, or the loss of motivation in and pleasure from social engagement, is an important feature in understanding the etiology and outcome of various psychopathologies. While the Revised Social Anhedonia Scale (RSAS) represents one of the most commonly used self-report measures of social anhedonia, little is known regarding the construct comparability across populations. We examined measurement invariance of the full and brief RSAS in a diverse, international sample of 14,064 participants across nine epidemiological dimensions, including gender, age, ethnicity, education, community income, continent, migrant status, ethnic density, and urbanicity. Both the full and brief RSAS, as represented by a three-factor structure, achieved metric invariance for all dimensions. The full version showed considerable scalar noninvariance for ethnicity and continent, which was significantly reduced in the brief version. These findings suggest that while the scales measure the same construct across diverse groups, mean comparisons are only appropriate for the brief, and not the full, version. Future research may consider using the brief RSAS to ensure cross-national comparability. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Decoding individual identity from brain activity elicited in imagining common experiences.

Everyone experiences common events differently. This leads to personal memories that presumably provide neural signatures of individual identity when events are reimagined. We present initial evidence that these signatures can be read from brain activity. To do this, we progress beyond previous work that has deployed generic group-level computational semantic models to distinguish between neural representations of different events, but not revealed interpersonal differences in event representations. We scanned 26 participants' brain activity using functional Magnetic Resonance Imaging as they vividly imagined themselves personally experiencing 20 common scenarios (e.g., dancing, shopping, wedding). Rather than adopting a one-size-fits-all approach to generically model scenarios, we constructed personal models from participants' verbal descriptions and self-ratings of sensory/motor/cognitive/spatiotemporal and emotional characteristics of the imagined experiences. We demonstrate that participants' neural representations are better predicted by their own models than other peoples'. This showcases how neuroimaging and personalized models can quantify individual-differences in imagined experiences.

Risk factors for loneliness: The high relative importance of age versus other factors.

Loneliness is a potent predictor of negative health outcomes, making it important to identify risk factors for loneliness. Though extant studies have identified characteristics associated with loneliness, less is known about the cumulative and relative importance of these factors, and how their interaction may impact loneliness. Here, 4,885 individuals ages 10-97 years from the US completed the three-item UCLA Loneliness Survey on TestMyBrain.org. Using census data, we calculated the population and community household income of participants' census area, and the proportion of individuals in the participant's census area that shared the participant's demographic characteristics (i.e., sociodemographic density). We evaluated the relative importance of three classes of variables for loneliness risk: those related to the person (e.g., age), place (e.g., community household income), and the interaction of person X place (sociodemographic density). We find that loneliness is highly prevalent and best explained by person (age) and place (community household income) characteristics. Of the variance in loneliness accounted for, the overwhelming majority was explained by age with loneliness peaking at 19 years and declining thereafter. The congruence between one's sociodemographic characteristics and that of one's neighborhood had no impact on loneliness. These data may have important implications for public health interventions.

Response patterns in the developing social brain are organized by social and emotion features and disrupted in children diagnosed with autism spectrum disorder.

Adults and children recruit a specific network of brain regions when engaged in "Theory of Mind" (ToM) reasoning. Recently, fMRI studies of adults have used multivariate analyses to provide a deeper characterization of responses in these regions. These analyses characterize representational distinctions within the social domain, rather than comparing responses across preferred (social) and non-preferred stimuli. Here, we conducted opportunistic multivariate analyses in two previously collected datasets (Experiment 1: n = 20 5-11 year old children and n = 37 adults; Experiment 2: n = 76 neurotypical and n = 29 5-12 year old children diagnosed with Autism Spectrum Disorder (ASD)) in order to characterize the structure of representations in the developing social brain, and in order to discover if this structure is disrupted in ASD. Children listened to stories that described characters' mental states (Mental), non-mentalistic social information (Social), and causal events in the environment (Physical), while undergoing fMRI. We measured the extent to which neural responses in ToM brain regions were organized according to two ToM-relevant models: 1) a condition model, which reflected the experimenter-generated condition labels, and 2) a data-driven emotion model, which organized stimuli according to their emotion content. We additionally constructed two control models based on linguistic and narrative features of the stories. In both experiments, the two ToM-relevant models outperformed the control models. The fit of the condition model increased with age in neurotypical children. Moreover, the fit of the condition model to neural response patterns was reduced in the RTPJ in children diagnosed with ASD. These results provide a first glimpse into the conceptual structure of information in ToM brain regions in childhood, and suggest that there are real, stable features that predict responses in these regions in children. Multivariate analyses are a promising approach for sensitively measuring conceptual and neural developmental change and individual differences in ToM.

Social cognition or social class and culture? On the interpretation of differences in social cognitive performance.

BACKGROUND: The ability to understand others' mental states carries profound consequences for mental and physical health, making efforts at validly and reliably assessing mental state understanding (MSU) of utmost importance. However, the most widely used and current NIMH-recommended task for assessing MSU - the Reading the Mind in the Eyes Task (RMET) - suffers from potential assessment issues, including reliance on a participant's vocabulary/intelligence and the use of culturally biased stimuli. Here, we evaluate the impact of demographic and sociocultural factors (age, gender, education, ethnicity, race) on the RMET and other social and non-social cognitive tasks in an effort to determine the extent to which the RMET may be unduly influenced by participant characteristics. METHODS: In total, 40 248 international, native-/primarily English-speaking participants between the ages of 10 and 70 completed one of five measures on TestMyBrain.org: RMET, a shortened version of RMET, a multiracial emotion identification task, an emotion discrimination task, and a non-social/non-verbal processing speed task (digit symbol matching). RESULTS: Contrary to other tasks, performance on the RMET increased across the lifespan. Education, race, and ethnicity explained more variance in RMET performance than the other tasks, and differences between levels of education, race, and ethnicity were more pronounced for the RMET than the other tasks such that more highly educated, non-Hispanic, and White/Caucasian individuals performed best. CONCLUSIONS: These data suggest that the RMET may be unduly influenced by social class and culture, posing a serious challenge to assessing MSU in clinical populations given shared variance between social status and psychiatric illness.

Social anhedonia, social networks, and psychotic-like experiences: A test of social deafferentation.

Social connection is robustly associated with physical and mental health. So important is social connection that it features prominently in several etiological theories of serious psychopathology. Most notably, the social deafferentation hypothesis of schizophrenia posits that social anhedonia (SA) and isolation cause neural changes that produce psychosis. Here, we test several tenants of this theory by examining the relation between SA, psychotic-like experiences (PLE), and social networks. We find that SA and PLE are related to social networks, and that the relation between SA and PLE can be explained, in part, by the impact of SA on social networks.

Continuity in the neural system supporting children's theory of mind development: Longitudinal links between task-independent EEG and task-dependent fMRI.

Children's explicit theory of mind (ToM) understandings change over early childhood. We examined whether there is longitudinal stability in the neurobiological bases of ToM across this time period. A previous study found that source-localized resting EEG alpha attributable to the dorsal medial prefrontal cortex (DMPFC) and right temporoparietal junction (RTPJ) was associated with children's performance on a battery of theory of mind tasks. Here, we investigated a small subset of children (N = 12) in that original study as a preliminary investigation of whether behavioral measures of ToM performance, and/or EEG localized to the DMPFC or RTPJ predicted ToM-specific fMRI responses 3.5 years later. Results showed that preschoolers' behavioral ToM-performance positively predicted later ToM-specific fMRI responses in the DMPFC. Preschoolers' resting EEG attributable to the DMPFC also predicted later ToM-specific fMRI responses in the DMPFC. Given the small sample, results represent a first exploration and require replication. Intriguingly, they suggest that early maturation of the area of the DMPFC related to ToM reasoning is positively linked with its specific recruitment for ToM reasoning later in development, affording implications for characterizing conceptual ToM development, and its underlying neural supports.

Neural correlates of theory-of-mind are associated with variation in children's everyday social cognition.

Theory of mind (ToM), the capacity to reason about others' mental states, is central to healthy social development. Neural mechanisms supporting ToM may contribute to individual differences in children's social cognitive behavior. Employing a false belief functional magnetic resonance imaging paradigm, we identified patterns of neural activity and connectivity elicited by ToM reasoning in school-age children (N = 32, ages 9-13). Next, we tested relations between these neural ToM correlates and children's everyday social cognition. Several key nodes of the neural ToM network showed greater activity when reasoning about false beliefs (ToM condition) vs non-mentalistic false content (control condition), including the bilateral temporoparietal junction (RTPJ and LTPJ), precuneus (PC) and right superior temporal sulcus. In addition, children demonstrated task-modulated changes in connectivity among these regions to support ToM relative to the control condition. ToM-related activity in the PC was negatively associated with variation in multiple aspects of children's social cognitive behavior. Together, these findings elucidate how nodes of the ToM network act and interact to support false belief reasoning in school-age children and suggest that neural ToM mechanisms are linked to variation in everyday social cognition.

The network structure of schizotypal personality traits in a population-based sample.

Outcomes for people with schizophrenia-spectrum disorders (SSDs) are generally poor, making it important to understand risk states and illness transition. The network approach, which conceptualizes psychopathology as a network of causally interacting symptoms, may hold promise in this regard. Here, we present a network analysis of schizotypal personality traits (i.e., schizophrenia-like cognitive, perceptual, affective, interpersonal, and behavioral anomalies that may index one's vulnerability for a SSD) using an international sample. We analyzed data from 9505 participants between the ages of 14-70 who completed the Schizotypal Personality Questionnaire-Brief on TestMyBrain.org. In line with other research, we find that the network of schizotypal traits is densely connected, characterized by three communities of items-interpersonal (I), disorganized (D), cognitive-perceptual (CP)-with I and D features exhibiting the greatest centrality (z-scored M strength: I = 0.56, D = 0.29, CP = -0.84; expected influence: I = 0.54, D = 0.33, CP = -0.84) and predictability (M I = 0.37, D = 0.43, CP = 0.23). Importantly, within our sample, we found the estimated network to be replicable (Network Comparison Test: network structure difference: M = 0.304, p = .420; global strength difference: S = 0.904, p = .530), and estimates of node centrality to be stable (correlation-stability coefficient = 0.75). Further, we find network differences between certain groups differing in levels of SSD risk as a function of age (network structure: difference M = 0.562, p < .001; global strength difference: S = 3.483, p = .012) and ethnic minority status (global strength difference: S = 11.488, p = .004). Together, these findings demonstrate the utility of using network approaches to understand SSD risk states as well as the replicability of network findings on schizotypal personality traits and related SSD risk concepts.

Emotion sensitivity across the lifespan: Mapping clinical risk periods to sensitivity to facial emotion intensity.

Face emotion perception is important for social functioning and mental health. In addition to recognizing categories of face emotion, accurate emotion perception relies on the ability to detect subtle differences in emotion intensity. The primary aim of this study was to examine participants' ability to discriminate the intensity of facial emotions (emotion sensitivity: ES) in three psychometrically matched ES tasks (fear, anger, or happiness), to identify developmental changes in sensitivity to face emotion intensity across the lifespan. We predicted that increased age would be associated with lower anger and fear ES, with minimal differences in happiness ES. Participants were 9,546 responders to a Web-based ES study (age range = 10 to 85 years old). Results of segmented linear regression confirmed our hypotheses and revealed differential patterns of ES based on age, sex, and emotion category. Females showed enhanced sensitivity to anger and fear relative to males, but similar sensitivity to happiness. While sensitivity to all emotions increased during adolescence and early adulthood, sensitivity to anger showed the largest increase, potentially related to the importance of anger perception during adolescent development. We also observed age-related decreases in both anger and fear sensitivity in older adults, with little to no change in happiness sensitivity. Unlike previous studies, the effect observed here could not be explained by task-related confounds (e.g., ceiling effects for happiness recognition), lending strong support to observed differences in ES for happiness, anger, and fear across age. Implications for everyday functioning and the development of psychopathology across the lifespan are discussed. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Change in Objective Measure of Empathic Accuracy Following Social Cognitive Training.

Background: The capacity for empathy plays an important role in interpersonal relationships and social functioning, and impairments in empathy can have negative effects on social interactions and overall social adjustment. This suggests that empathy may be a critical target for intervention in individuals who struggle with social interactions, yet it is unclear if the skills required for empathy are malleable. This study investigates the efficacy of targeted social cognitive training for improving empathic skills. Methods: Forty-five individuals (mean age = 24) were included in this study. Twenty-four individuals were allocated to the active social cognition training group and 21 individuals were allocated to a computer games control condition. Subjects completed approximately 10.5 h of training over two weeks. Pre- and post- training, they completed measures of empathy and emotion recognition, including the Interpersonal Reactivity Inventory (IRI) and an empathic accuracy task. ANOVA and regression analyses tested changes in participants' performance on the empathic accuracy task and scores on the IRI subscales were used to assess the effect of the social cognitive training. Results: Repeated measures ANOVA show that there is a significant group by timepoint interaction on the Empathic Accuracy task, with individuals who completed the social cognition training showing a significant improvement in performance following training. There were no significant changes for either group on any of the self-report IRI subscales. Individuals in the active training group show significant improvement on negative valence videos and a trend towards improvement on positive valence videos. In addition, individuals in social cognition active training group who reported higher intrinsic motivation demonstrated greater improvement on the Empathic Accuracy task. Conclusions: Individuals who completed a computerized social cognition training program demonstrated improved performance on a rater objective measure of empathic accuracy while individuals who completed a computer game control condition did not demonstrate any significant changes in their performance on the empathic accuracy task. These results suggest that targeted training in social cognition may increase empathic abilities, even in healthy individuals, and that this training may be beneficial to individuals with social cognitive deficits.