Autistic Traits and Social Anxiety Predict Differential Performance on Social Cognitive Tasks in Typically Developing Young Adults

The current work examined the unique contribution that autistic traits and social anxiety have on tasks examining attention and emotion processing. In Study 1, 119 typically-developing college students completed a flanker task assessing the control of attention to target faces and away from distracting faces during emotion identification. In Study 2, 208 typically-developing college students performed a visual search task which required identification of whether a series of 8 or 16 emotional faces depicted the same or different emotions. Participants with more self-reported autistic traits performed more slowly on the flanker task in Study 1 than those with fewer autistic traits when stimuli depicted complex emotions. In Study 2, participants higher in social anxiety performed less accurately on trials showing all complex faces; participants with autistic traits showed no differences. These studies suggest that traits related to autism and to social anxiety differentially impact social cognitive processing

Differences in social decision-making between proposers and responders during the ultimatum game: an eeg study

The Ultimatum Game (UG) is a typical paradigm to investigate social decision-making. Although the behavior of humans in this task is already well established, the underlying brain processes remain poorly understood. Previous investigations using event-related potentials (ERPs) revealed three major components related to cognitive processes in participants engaged in the responder condition, the early ERP component P2, the feedback-related negativity (FRN) and a late positive wave (late positive component, LPC). However, the comparison of the ERP waveforms between the responder and proposer conditions has never been studied. Therefore, to investigate condition-related electrophysiological changes, we applied the UG paradigm and compared parameters of the P2, LPC and FRN components in twenty healthy participants. For the responder condition, we found a significantly decreased amplitude and delayed latency for the P2 component, whereas the mean amplitudes of the LPC and FRN increased compared to the proposer condition. Additionally, the proposer condition elicited an early component consisting of a negative deflection around 190 ms, in the upward slope of the P2, probably as a result of early conflict-related processing. Using independent component analysis (ICA), we extracted one functional component time-locked to this deflection, and with source reconstruction (LAURA) we found the anterior cingulate cortex (ACC) as one of the underlying sources. Overall, our findings indicate that intensity and time-course of neuronal systems engaged in the decision-making processes diverge between both UG conditions, suggesting differential cognitive processes. Understanding the electrophysiological bases of decision-making and social interactions in controls could be useful to further detect which steps are impaired in psychiatric patients in their ability to attribute mental states (such as beliefs, intents, or desires) to oneself and others. This ability is called mentalizing (also known as theory of mind)

The Things You Do:Internal Models of Others' Expected Behaviour Guide Action Observation

Predictions allow humans to manage uncertainties within social interactions. Here, we investigate how explicit and implicit person models-how different people behave in different situations-shape these predictions. In a novel action identification task, participants judged whether actors interacted with or withdrew from objects. In two experiments, we manipulated, unbeknownst to participants, the two actors action likelihoods across situations, such that one actor typically interacted with one object and withdrew from the other, while the other actor showed the opposite behaviour. In Experiment 2, participants additionally received explicit information about the two individuals that either matched or mismatched their actual behaviours. The data revealed direct but dissociable effects of both kinds of person information on action identification. Implicit action likelihoods affected response times, speeding up the identification of typical relative to atypical actions, irrespective of the explicit knowledge about the individual's behaviour. Explicit person knowledge, in contrast, affected error rates, causing participants to respond according to expectations instead of observed behaviour, even when they were aware that the explicit information might not be valid. Together, the data show that internal models of others' behaviour are routinely re-activated during action observation. They provide first evidence of a person-specific social anticipation system, which predicts forthcoming actions from both explicit information and an individuals' prior behaviour in a situation. These data link action observation to recent models of predictive coding in the non-social domain where similar dissociations between implicit effects on stimulus identification and explicit behavioural wagers have been reported

THINGS: A database of 1,854 object concepts and more than 26,000 naturalistic object images

In recent years, the use of a large number of object concepts and naturalistic object images has been growing strongly in cognitive neuroscience research. Classical databases of object concepts are based mostly on a manually curated set of concepts. Further, databases of naturalistic object images typically consist of single images of objects cropped from their background, or a large number of naturalistic images of varying quality, requiring elaborate manual image curation. Here we provide a set of 1,854 diverse object concepts sampled systematically from concrete picturable and nameable nouns in the American English language. Using these object concepts, we conducted a large-scale web image search to compile a database of 26,107 high-quality naturalistic images of those objects, with 12 or more object images per concept and all images cropped to square size. Using crowdsourcing, we provide higher-level category membership for the 27 most common categories and validate them by relating them to representations in a semantic embedding derived from large text corpora. Finally, by feeding images through a deep convolutional neural network, we demonstrate that they exhibit high selectivity for different object concepts, while at the same time preserving variability of different object images within each concept. Together, the THINGS database provides a rich resource of object concepts and object images and offers a tool for both systematic and large-scale naturalistic research in the fields of psychology, neuroscience, and computer science

THINGS: A database of 1,854 object concepts and more than 26,000 naturalistic object images

In recent years, the use of a large number of object concepts and naturalistic object images has been growing strongly in cognitive neuroscience research. Classical databases of object concepts are based mostly on a manually curated set of concepts. Further, databases of naturalistic object images typically consist of single images of objects cropped from their background, or a large number of naturalistic images of varying quality, requiring elaborate manual image curation. Here we provide a set of 1,854 diverse object concepts sampled systematically from concrete picturable and nameable nouns in the American English language. Using these object concepts, we conducted a large-scale web image search to compile a database of 26,107 high-quality naturalistic images of those objects, with 12 or more object images per concept and all images cropped to square size. Using crowdsourcing, we provide higher-level category membership for the 27 most common categories and validate them by relating them to representations in a semantic embedding derived from large text corpora. Finally, by feeding images through a deep convolutional neural network, we demonstrate that they exhibit high selectivity for different object concepts, while at the same time preserving variability of different object images within each concept. Together, the THINGS database provides a rich resource of object concepts and object images and offers a tool for both systematic and large-scale naturalistic research in the fields of psychology, neuroscience, and computer science

Example of visual search task trial.

<p>Example of visual search task trial.</p

Example of flanker task trial.

<p>Example of flanker task trial.</p

Accuracy as a function of flanker complexity, target complexity, and SPAI for trials with 16 faces.

<p>Fig 5a depicts basic distractors while Fig 5b shows complex distractors. The asterisk indicates statistical significance at <i>p</i> < .05. Error bars represent standard errors.</p

Accuracy as a function of number of stimuli and AQ.

<p>The asterisks indicate statistical significance at <i>p</i> < .05. Error bars represent standard errors.</p