Both Default and Multiple-Demand Regions Represent Semantic Goal Information

Abstract

We used a semantic feature-matching task combined with multivoxel pattern decoding to test contrasting accounts of the role of the default mode network (DMN) in cognitive flexibility. By one view, DMN and multiple-demand cortex have opposing roles in cognition, with DMN and multiple-demand regions within the dorsal attention network (DAN) supporting internal and external cognition, respectively. Consequently, while multiple-demand regions can decode current goal information, semantically relevant DMN regions might decode conceptual similarity regardless of task demands. Alternatively, DMN regions, like multiple-demand cortex, might show sensitivity to changing task demands, since both networks dynamically alter their patterns of connectivity depending on the context. Our task required human participants (any sex) to integrate conceptual knowledge with changing task goals, such that successive decisions were based on different features of the items (color, shape, and size). This allowed us to simultaneously decode semantic category and current goal information using whole-brain searchlight decoding. As expected, multiple-demand cortex, including DAN and frontoparietal control network, represented information about currently relevant conceptual features. Similar decoding results were found in DMN, including in angular gyrus and posterior cingulate cortex, indicating that DMN and multiple-demand regions can support the same function rather than being strictly competitive. Semantic category could be decoded in lateral occipital cortex independently of task demands, but not in most regions of DMN. Conceptual information related to the current goal dominates the multivariate response within DMN, which supports flexible retrieval by modulating its response to suit the task demands, alongside regions of multiple-demand cortex.SIGNIFICANCE STATEMENT We tested contrasting accounts of default mode network (DMN) function using multivoxel pattern analysis. By one view, semantically relevant parts of DMN represent conceptual similarity, regardless of task context. By an alternative view, DMN tracks changing task demands. Our semantic feature-matching task required participants to integrate conceptual knowledge with task goals, such that successive decisions were based on different features of the items. We demonstrate that DMN regions can decode the current goal, as it is applied, alongside multiple-demand regions traditionally associated with cognitive control, speaking to how DMN supports flexible cognition.

Keywords: control; decoding; default mode network; feature representation; multiple demand; semantic.