The gradient model of brain organization in decisions involving 'empathy for pain'

Description: Recent meta-analytic studies of social cognition and the functional imaging of empathy have exposed the overlap between their neural substrates and heteromodal association areas characterized by extensive long-range connectivity. The ‘gradient model’ of cortical organization proposes a close relationship between these heteromodal association areas and the default mode network. Here, we used a decision-making task and representational similarity analysis with classic ‘empathy for pain’ visual stimuli to probe the relationship between high-level representations of imminent pain in others and task deactivations as proposed by this model. High-level representations were found to co-localize with task deactivations or the transitions from activations to deactivations. These deactivations may be classified in two groups: those that load on the high end of the cortical gradient and are typically associated with the default mode network, and those that appeared to accompany functional repurposing of somatosensory cortex in the presence of visual stimuli. By considering the existing literature on these areas, we argue that a functional characterization in terms of simple mappings is unlikely, and propose an involvement in computing schematic representations providing top-down guidance to interpret incoming stimuli and predict outcomes. We anticipate that an increased understanding of schematic processing in the social and emotional domain may benefit models of cortical function relevant to understand social interactions and psychopathology.