Revealing the structure of affective schematic representations in the medial prefrontal cortex

Abstract

Adaptive cognition is fostered by knowledge about the structure and value of our environment. Here, we hypothesize that these two kinds of information are inherently intertwined as affective schemas in the medial prefrontal cortex (mPFC). Schemas (e.g., of a social network) emerge by extracting commonalities across experiences and can be understood as graphs comprising nodes (e.g., people) and edges (e.g., their relationships). We sampled information about unique real-life environments (i.e., about personally familiar people and places) and probed their neural representations with fMRI. Using representational similarity analysis, we show that the mPFC encodes both, the nodes and the edges of the schema. Critically, the strength of the edges is not only determined by experience and centrality of a given node but also by its affective value. We thus account for the involvement of the mPFC in seemingly disparate functions and suggest that valuation emerges naturally from encoded memory representations.