Working with Schemas, Predicting with Schemas

Electrocorticographic evidence of a common neurocognitive sequence for mentalizing about the self and others

Neuroimaging studies of mentalizing (i.e., theory of mind) consistently implicate the default mode network (DMN). Nevertheless, the social cognitive functions of individual DMN regions remain unclear, perhaps due to limited spatiotemporal resolution in neuroimaging. Here we use electrocorticography (ECoG) to directly record neuronal population activity while 16 human participants judge the psychological traits of themselves and others. Self- and other-mentalizing recruit near-identical cortical sites in a common spatiotemporal sequence. Activations begin in the visual cortex, followed by temporoparietal DMN regions, then finally in medial prefrontal regions. Moreover, regions with later activations exhibit stronger functional specificity for mentalizing, stronger associations with behavioral responses, and stronger self/other differentiation. Specifically, other-mentalizing evokes slower and longer activations than self-mentalizing across successive DMN regions, implying lengthier processing at higher levels of representation. Our results suggest a common neurocognitive pathway for self- and other-mentalizing that follows a complex spatiotemporal gradient of functional specialization across DMN and beyond.

Prior knowledge promotes hippocampal separation but cortical assimilation in the left inferior frontal gyrus

An adaptive memory system rarely learns information tabula rasa, but rather builds on prior knowledge to facilitate learning. How prior knowledge influences the neural representation of novel associations remains unknown. Here, participants associated pairs of faces in two conditions: a famous, highly familiar face with a novel face or two novel faces while undergoing fMRI. We examine multivoxel activity patterns corresponding to individual faces before and after learning. The activity patterns representing members of famous-novel pairs becomes separated in the hippocampus, that is, more distinct from one another through learning, in striking contrast to paired novel faces that become similar. In the left inferior frontal gyrus, however, prior knowledge leads to integration, and in a specific direction: the representation of the novel face becomes similar to that of the famous face after learning, suggesting assimilation of new into old memories. We propose that hippocampal separation might resolve interference between existing and newly learned information, allowing cortical assimilation. Thus, associative learning with versus without prior knowledge relies on radically different computations.

Prior knowledge strongly impacts new learning, but its influence on the neural representation of novel information is unknown. Here, the authors show multiple neural codes for learning: prior knowledge leads to integrated cortical representations, while promoting hippocampal separation.