Segregation, connectivity, and gradients of deactivation in neural correlates of evidence in social decision making

Author:

Viviani RobertoORCID,Dommes Lisa,Bosch Julia E.,Labek KarinORCID

Abstract

AbstractFunctional imaging studies of sensory decision making have detected a signal associated with evidence for decisions that is consistent with data from single-cell recordings in laboratory animals. However, the generality of this finding and its implications on our understanding of the organization of the fMRI signal are not clear. In the present functional imaging study, we investigated decisions in an elementary social cognition domain to identify the neural correlates of evidence, their segregation, connectivity, and their relationship to task deactivations. Besides providing data in support of an evidence-related signal in a social cognition task, we were interested in embedding these neural correlates in models of supramodal associative cortex placed at the top of a hierarchy of processing areas. Participants were asked to decide which of two depicted individuals was saddest based on information rich in sensory features (facial expressions) or through contextual cues suggesting the mental state of others (stylized drawings of mourning individuals). The signal associated with evidence for the decision was located in two distinct networks differentially recruited depending on the information type. Using the largest peaks of the signal associated with evidence as seeds in a database of connectivity data, these two networks were retrieved. Furthermore, the hubs of these networks were located near or along a ribbon of cortex located between task activations and deactivations between areas affected by perceptual priming and the deactivated areas of the default network system. In associative cortex, these findings suggest gradients of progressive relative deactivation as a possible neural correlate of the cortical organization envisaged by structural models of cortical organization and by predictive coding theories of cortical function.

Publisher

Cold Spring Harbor Laboratory

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