Collective events and individual affect shape autobiographical memory.

How do collective events shape how we remember our lives? We leveraged advances in natural language processing as well as a rich, longitudinal assessment of 1,000 Americans throughout 2020 to examine how memory is influenced by two prominent factors: surprise and emotion. Autobiographical memory for 2020 displayed a unique signature: There was a substantial bump in March, aligning with pandemic onset and lockdowns, consistent across three memory collections 1 y apart. We further investigated how emotion, using both immediate and retrieved measures, predicted the amount and content of autobiographical memory: Negative affect increased recall across all measures, whereas its more clinical indices, depression and posttraumatic stress disorder, selectively increased nonepisodic recall. Finally, in a separate cohort, we found pandemic news to be better remembered, surprising, and negative, while lockdowns compressed remembered time. Our work connects laboratory findings to the real world and delineates the effects of acute versus clinical signatures of negative emotion on memory.

Posttraumatic stress disorder symptom trajectories in a 16-month COVID-19 pandemic period.

COVID-19 pandemic presents an unheralded opportunity to better understand trajectories of posttraumatic stress disorder (PTSD) symptoms across a prolonged period of social disruption and stress. We tracked PTSD symptoms among trauma-exposed individuals in the United States and sought to identify population-based variability in PTSD symptom trajectories and understand what, if any, early pandemic experiences predicted membership in one trajectory versus others. As part of a longitudinal study of U.S. residents during the pandemic, participants who reported at least one potentially traumatic experience in their lifetime (N = 1,206) at Wave 1 (April 2020) were included in the current study. PTSD symptoms were assessed using the PCL-5 at four time points extending to July 2021. Latent growth mixture modeling was used to identify heterogeneous symptom trajectories. Trajectory membership was regressed on experiences from the early stage of the pandemic as measured using the Epidemic-Pandemic Impacts Inventory in a model that controlled for variables with documented associations to PTSD trajectories, including age, sex, income, and trauma history. Four trajectories were identified, categorized as resilient (73.0%), recurring (13.3%), recovering (8.3%), and chronic (5.5%). Emotional and physical health problems and positive changes associated with the early phase of the pandemic were each significant predictors of trajectory membership over and above all other variables in the model. Predictors primarily differentiated the resilient trajectory from each of the other three trajectories. Distinct PTSD symptom trajectories during the COVID-19 pandemic suggest a need for targeted efforts to help individuals at most risk for ongoing distress.

Implicit Social Biases in People With Autism.

Implicit social biases are ubiquitous and are known to influence social behavior. A core diagnostic criterion of autism spectrum disorders (ASD) is abnormal social behavior. We investigated the extent to which individuals with ASD might show a specific attenuation of implicit social biases, using Implicit Association Tests (IATs) involving social (gender, race) and nonsocial (nature, shoes) categories. High-functioning adults with ASD showed intact but reduced IAT effects relative to healthy control participants. We observed no selective attenuation of implicit social (vs. nonsocial) biases in our ASD population. To extend these results, we supplemented our healthy control data with data collected from a large online sample from the general population and explored correlations between autistic traits and IAT effects. We observed no systematic relationship between autistic traits and implicit social biases in our online and control samples. Taken together, these results suggest that implicit social biases, as measured by the IAT, are largely intact in ASD.

Implicit race attitudes predict trustworthiness judgments and economic trust decisions.

Trust lies at the heart of every social interaction. Each day we face decisions in which we must accurately assess another individual's trustworthiness or risk suffering very real consequences. In a global marketplace of increasing heterogeneity with respect to nationality, race, and multiple other social categories, it is of great value to understand how implicitly held attitudes about group membership may support or undermine social trust and thereby implicitly shape the decisions we make. Recent behavioral and neuroimaging work suggests that a common mechanism may underlie the expression of implicit race bias and evaluations of trustworthiness, although no direct evidence of a connection exists. In two behavioral studies, we investigated the relationship between implicit race attitude (as measured by the Implicit Association Test) and social trust. We demonstrate that race disparity in both an individual's explicit evaluations of trustworthiness and, more crucially, his or her economic decisions to trust is predicted by that person's bias in implicit race attitude. Importantly, this relationship is robust and is independent of the individual's bias in explicit race attitude. These data demonstrate that the extent to which an individual invests in and trusts others with different racial backgrounds is related to the magnitude of that individual's implicit race bias. The core dimension of social trust can be shaped, to some degree, by attitudes that reside outside conscious awareness and intention.

COVID-Dynamic: A large-scale longitudinal study of socioemotional and behavioral change across the pandemic.

The COVID-19 pandemic has caused enormous societal upheaval globally. In the US, beyond the devastating toll on life and health, it triggered an economic shock unseen since the great depression and laid bare preexisting societal inequities. The full impacts of these personal, social, economic, and public-health challenges will not be known for years. To minimize societal costs and ensure future preparedness, it is critical to record the psychological and social experiences of individuals during such periods of high societal volatility. Here, we introduce, describe, and assess the COVID-Dynamic dataset, a within-participant longitudinal study conducted from April 2020 through January 2021, that captures the COVID-19 pandemic experiences of >1000 US residents. Each of 16 timepoints combines standard psychological assessments with novel surveys of emotion, social/political/moral attitudes, COVID-19-related behaviors, tasks assessing implicit attitudes and social decision-making, and external data to contextualize participants' responses. This dataset is a resource for researchers interested in COVID-19-specific questions and basic psychological phenomena, as well as clinicians and policy-makers looking to mitigate the effects of future calamities.

Alcohol, cannabis, and nicotine use have distinct associations with COVID-19 pandemic-related experiences: An exploratory Bayesian network analysis across two timepoints.

BACKGROUND: Substance use trends during the COVID-19 pandemic have been extensively documented. However, relatively less is known about the associations between pandemic-related experiences and substance use. METHOD: In July 2020 and January 2021, a broad U.S. community sample (N = 1123) completed online assessments of past month alcohol, cannabis, and nicotine use and the 92-item Epidemic-Pandemic Impacts Inventory, a multidimensional measure of pandemic-related experiences. We examined links between substance use frequency, and pandemic impact on emotional, physical, economic, and other key domains, using Bayesian Gaussian graphical networks in which edges represent significant associations between variables (referred to as nodes). Bayesian network comparison approaches were used to assess the evidence of stability (or change) in associations between the two timepoints. RESULTS: After controlling for all other nodes in the network, multiple significant edges connecting substance use nodes and pandemic-experience nodes were observed across both time points, including positive- (r range 0.07-0.23) and negative-associations (r range -0.25 to -0.11). Alcohol was positively associated with social and emotional pandemic impacts and negatively associated with economic impacts. Nicotine was positively associated with economic impact and negatively associated with social impact. Cannabis was positively associated with emotional impact. Network comparison suggested these associations were stable across the two timepoints. CONCLUSION: Alcohol, nicotine, and cannabis use had unique associations to a few specific domains among a broad range of pandemic-related experiences. Given the cross-sectional nature of these analyses with observational data, further investigation is needed to identify potential causal links.

Deconstructing Theory-of-Mind Impairment in High-Functioning Adults with Autism.

Inferring the beliefs, desires, and intentions of other people ("theory of mind," ToM) requires specialized psychological processes that represent the minds of others as distinct from our own [1-3]. ToM is engaged ubiquitously in our everyday social behavior and features a specific developmental trajectory [4] that is notably delayed in children with autism spectrum disorder (ASD) [5, 6]. In healthy individuals, model-based analyses of social learning and decision-making have successfully elucidated specific computational components of ToM processing [7-11]. However, the use of this approach to study ToM impairment in ASD has been extremely limited [10, 12]. To better characterize specific ToM impairment in ASD, we developed a novel learning task and applied model-based analyses in high-functioning adults with ASD and matched healthy controls. After completing a charitable donation task, participants performed a "mentalizer" task in which they observed another person (the agent) complete the same charity task. The mentalizer task probed the participants' ability to acquire and use ToM representations. To accurately predict agent behavior, participants needed to dynamically track the agent's beliefs (true or false) about an experimental context that varied over time and use that information to infer the agent's intentions from their actions. ASD participants were specifically impaired at using their estimates of agent belief to learn agent intentions, though their ability to track agent belief was intact and their reasoning about belief and intentions was rational. Furthermore, model parameters correlated with aspects of social functioning, e.g., ADOS severity scores [13]. Together, these results identify novel, and more specific, targets for future research.

fMRI activation in response to illusory contours and salient regions in the human lateral occipital complex.

Regions in the human Lateral Occipital Complex (LOC) show fMRI responses to illusory surfaces. We show that the LOC activation is due to the globally completed region and occurs even when the region is not bounded by illusory contours (ICs). Kanizsa-type stimuli were modified by rounding the corners of the "pacmen" inducers and misaligning them slightly. The impression of an enclosed, salient region (SR) remained, although ICs were no longer perceived (psychophysical data). fMRI activity was elevated for both the IC and SR stimuli, compared to their control stimuli. The LOC response to salient regions may be the result of fast but crude region-based segmentation processes, which are useful for selecting parts of cluttered images for more detailed, computationally intensive processing.

Getting to know you: general and specific neural computations for learning about people.

Learning about other peoples' attributes, e.g. whether an individual is generous or selfish, is central to human social cognition. It is well documented that a network of cortical regions is reliably activated when we engage social processes. However, little is known about the specific computations performed by these regions or whether such processing is specialized for the social domain. We investigated these questions using a task in which participants (N= 26) learned about four peoples' generosity by watching them choose to share money with third party partners, or not. In a non-social control condition, participants learned the win/loss rates of four lotteries. fMRI analysis revealed learning-related general (social + non-social) prediction error signals in the dorsomedial and dorsolateral prefrontal cortices (bilaterally), and in the right lateral parietal cortex. Socially specific (social > non-social) prediction error signals were found in the precuneus. Interestingly, the region that exhibited social prediction errors was a distinct subregion of the area in the precuneus and posterior cingulate cortex that exhibited a commonly reported main effect of higher overall activity for social vs non-social stimuli. These findings elucidate the domain--general and--specific computations underlying learning about other people and demonstrate the increased explanatory power of computational approaches to social cognition.

Brief Online Training Enhances Competitive Performance: Findings of the BBC Lab UK Psychological Skills Intervention Study.

In conjunction with BBC Lab UK, the present study developed 12 brief psychological skill interventions for online delivery. A protocol was designed that captured data via self-report measures, used video recordings to deliver interventions, involved a competitive concentration task against an individually matched computer opponent, and provided feedback on the effects of the interventions. Three psychological skills were used; imagery, self-talk, and if-then planning, with each skill directed to one of four different foci: outcome goal, process goal, instruction, or arousal-control. This resulted in 12 different intervention participant groups (randomly assigned) with a 13th group acting as a control. Participants (n = 44,742) completed a competitive task four times-practice, baseline, following an intervention, and again after repeating the intervention. Results revealed performance improved following practice with incremental effects for imagery-outcome, imagery-process, and self-talk-outcome and self-talk-process over the control group, with the same interventions increasing the intensity of effort invested, arousal and pleasant emotion. Arousal-control interventions associated with pleasant emotions, low arousal, and low effort invested in performance. Instructional interventions were not effective. Results offer support for the utility of online interventions in teaching psychological skills and suggest brief interventions that focus on increasing motivation, increased arousal, effort invested, and pleasant emotions were the most effective.

How should I regulate my emotions if I want to run faster?

The present study investigated the effects of emotion regulation strategies on self-reported emotions and 1600 m track running performance. In stage 1 of a three-stage study, participants (N = 15) reported emotional states associated with best, worst and ideal performance. Results indicated that a best and ideal emotional state for performance composed of feeling happy, calm, energetic and moderately anxious whereas the worst emotional state for performance composed of feeling downhearted, sluggish and highly anxious. In stage 2, emotion regulation interventions were developed using online material and supported by electronic feedback. One intervention motivated participants to increase the intensity of unpleasant emotions (e.g. feel more angry and anxious). A second intervention motivated participants to reduce the intensity of unpleasant emotions (e.g. feel less angry and anxious). In stage 3, using a repeated measures design, participants used each intervention before running a 1600 m time trial. Data were compared with a no treatment control condition. The intervention designed to increase the intensity of unpleasant emotions resulted in higher anxiety and lower calmness scores but no significant effects on 1600 m running time. The intervention designed to reduce the intensity of unpleasant emotions was associated with significantly slower times for the first 400 m. We suggest future research should investigate emotion regulation, emotion and performance using quasi-experimental methods with performance measures that are meaningful to participants.

Rapid detection of salient regions: evidence from apparent motion.

Most studies that have used Kanizsa-type illusory figures to investigate perceptual completion have treated the crisp bounding illusory contours (ICs) and the enclosed region as nondissociable stimulus attributes. However, there is evidence that enclosed "salient regions" (SRs; Stanley & Rubin, 2003) are detected even in cases when bounding ICs are not perceptually completed. Here we used apparent motion (AM) to test whether SRs are detected in the absence of crisp bounding ICs. Kanizsa-type stimuli were modified in ways that eliminated the bounding ICs, but the clear impression of an enclosed region remained. SR stimuli were embedded in an array of like inducers. On successive frames, the inducers in the array rotated in a way that resulted in translation of the enclosed region. Four speeds of translation were tested. Observers performed a two-alternative forced-choice task on the direction of translation. Perceptually completed SRs produced robust AM whether they were bound by crisp ICs or not-observer performance was as good and, in certain cases, even better for SRs with no bounding ICs. We interpret these findings within a theoretical framework that makes a distinction between region-based and contour-based segmentation processes that operate in concert to achieve segmentation of the visual scene.

Qualitative evaluation of a self-management intervention for people in the early stage of dementia.

Self-management programs are effective for people living with chronic illnesses. However, there has been little research addressing self-management for people with dementia in the early stages. This study presents a qualitative evaluation of the experiences of attending a novel self-management program and initial process evaluation. The program was designed with and for people with dementia. It addresses: (a) relationship with family, (b) maintenance of an active lifestyle, (c) psychological well-being, (d) techniques to cope with memory changes and (e) information about dementia. Six participants with early stage dementia completed the intervention that was co-delivered by lay and clinical professional tutors. Participants and tutors attended focus group and interviews at the end of the program to explore their perceptions of the intervention. These were audio-recorded, transcribed verbatim and analysed thematically. Participants reported enjoyment and benefits from the intervention. This was despite some reporting concerns relating to their memory difficulties. The program's flexible nature, focus on strengths and the opportunity to spend time with other people living with dementia were particularly well received. Participants and tutors outlined areas for further improvement. The program was feasible and its flexible delivery appeared to facilitate participant benefit. Emphasis should be placed on maintaining activity and relationships, improving positive well-being and social interaction during the program. Memory of the pleasant experience and strengths focus was evidenced, which may impact positively on quality of life. The results highlight the usefulness and acceptability of self-management for people with early stage dementia and provide initial support for the program's structure and content.

Toward a neural basis for social behavior.

Nearly 25 years ago, the shared interests of psychologists and biologists in understanding the neural basis of social behavior led to the inception of social neuroscience. In the past decade, this field has exploded, in large part due to the infusion of studies that use fMRI. At the same time, tensions have arisen about how to prioritize a diverse range of questions and about the authority of neurobiological data in answering them. The field is now poised to tackle some of the most interesting and important questions about human and animal behavior but at the same time faces uncertainty about how to achieve focus in its research and cohesion among the scientists who tackle it. The next 25 years offer the opportunity to alleviate some of these growing pains, as well as the challenge of answering large questions that encompass the nature and bounds of diverse social interactions (in humans, including interactions through the internet); how to characterize, and treat, social dysfunction in psychiatric illness; and how to compare social cognition in humans with that in other animals.

Race and reputation: perceived racial group trustworthiness influences the neural correlates of trust decisions.

Decisions to trust people with whom we have no personal history can be based on their social reputation-a product of what we can observe about them (their appearance, social group membership, etc.)-and our own beliefs. The striatum and amygdala have been identified as regions of the brain involved in trust decisions and trustworthiness estimation, respectively. However, it is unknown whether social reputation based on group membership modulates the involvement of these regions during trust decisions. To investigate this, we examined blood-oxygenation-level-dependent (BOLD) activity while participants completed a series of single-shot trust game interactions with real partners of varying races. At the time of choice, baseline BOLD responses in the striatum correlated with individuals' trust bias-that is, the overall disparity in decisions to trust Black versus White partners. BOLD signal in the striatum was higher when deciding to trust partners from the race group that the individual participant considered less trustworthy overall. In contrast, activation of the amygdala showed greater BOLD responses to Black versus White partners that scaled with the amount invested. These results suggest that the amygdala may represent emotionally relevant social group information as a subset of the general detection function it serves, whereas the striatum is involved in representing race-based reputations that shape trust decisions.

Cuing effects of faces are dependent on handedness and visual field.

Faces are unlike other visual objects we encounter, in that they alert us to potentially relevant social information. Both face processing and spatial attention are dominant in the right hemisphere of the human brain, with a stronger lateralization in right- than in left-handers. Here, we demonstrate behavioral evidence for an effect of handedness on performance in tasks using faces to direct attention. Nonpredictive, peripheral cues (faces or dots) directed exogenous attention to contrast-varying stimuli (Gabor patches)-a tilted target, a vertical distractor, or both; observers made orientation discriminations on the target stimuli. Whereas cuing with dots increased contrast sensitivity in both groups, cuing with faces increased contrast sensitivity in right- but not in left-handers, for whom opposite hemifield effects resulted in no net increase. Our results reveal that attention modulation by face cues critically depends on handedness and visual hemifield. These previously unreported interactions suggest that such lateralized systems may be functionally connected.

Cluster-based analysis of FMRI data.

We propose a method for the statistical analysis of fMRI data that tests cluster units rather than voxel units for activation. The advantages of this analysis over previous ones are both conceptual and statistical. Recognizing that the fundamental units of interest are the spatially contiguous clusters of voxels that are activated together, we set out to approximate these cluster units from the data by a clustering algorithm especially tailored for fMRI data. Testing the cluster units has a two-fold statistical advantage over testing each voxel separately: the signal to noise ratio within the unit tested is higher, and the number of hypotheses tests compared is smaller. We suggest controlling FDR on clusters, i.e., the proportion of clusters rejected erroneously out of all clusters rejected and explain the meaning of controlling this error rate. We introduce the powerful adaptive procedure to control the FDR on clusters. We apply our cluster-based analysis (CBA) to both an event-related and a block design fMRI vision experiment and demonstrate its increased power over voxel-by-voxel analysis in these examples as well as in simulations.