Masked features of task states found in individual brain networks.

Completing complex tasks requires that we flexibly integrate information across brain areas. While studies have shown how functional networks are altered during different tasks, this work has generally focused on a cross-subject approach, emphasizing features that are common across people. Here we used extended sampling "precision" fMRI data to test the extent to which task states generalize across people or are individually specific. We trained classifiers to decode state using functional network data in single-person datasets across 5 diverse task states. Classifiers were then tested on either independent data from the same person or new individuals. Individualized classifiers were able to generalize to new participants. However, classification performance was significantly higher within a person, a pattern consistent across model types, people, tasks, feature subsets, and even for decoding very similar task conditions. Notably, these findings also replicated in a new independent dataset. These results suggest that individual-focused approaches can uncover robust features of brain states, including features obscured in cross-subject analyses. Individual-focused approaches have the potential to deepen our understanding of brain interactions during complex cognition.

Distributed midbrain responses signal the content of positive identity prediction errors.

Recent work across species has shown that midbrain dopamine neurons signal not only errors in the prediction of reward value but also in the prediction of value-neutral sensory features. To support learning of associative structures in downstream areas, identity prediction errors (iPEs) should signal specific information about the mis-predicted outcome. Here, we used pattern-based analysis of functional magnetic resonance imaging (fMRI) data acquired during reversal learning to characterize the information content of iPE responses in the human midbrain. We find that fMRI responses to value-neutral identity errors contain information about the identity of the unexpectedly received reward (positive iPE+) but not about the identity of the omitted reward (negative iPE-). Exploratory analyses revealed representations of iPE- in the dorsomedial prefrontal cortex. These results demonstrate that ensemble midbrain responses to value-neutral identity errors convey information about the identity of unexpectedly received outcomes, which could shape the formation of novel stimulus-outcome associations that constitute cognitive maps.

Social cognitive regions of human association cortex are selectively connected to the amygdala.

Reasoning about someone's thoughts and intentions - i.e., forming a theory of mind - is an important aspect of social cognition that relies on association areas of the brain that have expanded disproportionately in the human lineage. We recently showed that these association zones comprise parallel distributed networks that, despite occupying adjacent and interdigitated regions, serve dissociable functions. One network is selectively recruited by theory of mind processes. What circuit properties differentiate these parallel networks? Here, we show that social cognitive association areas are intrinsically and selectively connected to regions of the anterior medial temporal lobe that are implicated in emotional learning and social behaviors, including the amygdala at or near the basolateral complex and medial nucleus. The results suggest that social cognitive functions emerge through coordinated activity between amygdala circuits and a distributed association network, and indicate the medial nucleus may play an important role in social cognition in humans.

Reduced sensitivity to affiliation and psychopathic traits.

Psychopathy is characterized by affective and interpersonal deficits, deviant lifestyle, and antisocial behaviors. Much research has been dedicated to understanding the impairments in reinforcement learning, fear conditioning, and sensitivity to threat, distress, or fear in others, which are thought to underpin psychopathic traits. Fewer studies have examined deficits in affiliative processes, which could provide insight into mechanisms giving rise to the impairments in social bonding, closeness with others, and cooperation that also characterize individuals high on psychopathy. The current study examined whether reduced sensitivity to affiliation was related to psychopathic traits among 407 adults from the community (female, 59%). Sensitivity to affiliation was modeled as a latent construct capturing item-level variance shared across 4 measures that assessed sensitivity to emotional and physical cues of affiliation, including stimuli presented as videos or images, and via self-report ratings about sensitivity to positive affiliative and affective cues. Results indicated that lower sensitivity to affiliation was related to higher total psychopathy scores. In particular, in models parsing the overlap of psychopathy factor and facet scores, lower sensitivity to affiliation was uniquely related to higher Factor 1 and affective facet scores, as well as higher scores on a measure of callous-unemotional traits. Our findings provide support for the existence of important socioaffiliative and motivational deficits that may underpin the affective features of psychopathy and speak to the potential to target such mechanisms in interventions and treatments to reduce psychopathic traits. (PsycInfo Database Record (c) 2021 APA, all rights reserved).