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Bipartite Functional Fractionation within the Default Network Supports Disparate Forms of Internally Oriented Cognition
Author(s) -
Rocco Chiou,
Gina F. Humphreys,
Matthew A. Lambon Ralph
Publication year - 2020
Publication title -
cerebral cortex
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.694
H-Index - 250
eISSN - 1460-2199
pISSN - 1047-3211
DOI - 10.1093/cercor/bhaa130
Subject(s) - cognitive psychology , cognition , psychology , default mode network , cognitive science , task (project management) , computer science , neuroscience , management , economics
Our understanding about the functionality of the brain's default network (DN) has significantly evolved over the past decade. Whereas traditional views define this network based on its suspension/disengagement during task-oriented behavior, contemporary accounts have characterized various situations wherein the DN actively contributes to task performance. However, it is unclear how different task-contexts drive componential regions of the DN to coalesce into a unitary network and fractionate into different subnetworks. Here we report a compendium of evidence that provides answers to these questions. Across multiple analyses, we found a striking dyadic structure within the DN in terms of the profiles of task-triggered fMRI response and effective connectivity, significantly extending beyond previous inferences based on meta-analysis and resting-state activities. In this dichotomy, one subset of DN regions prefers mental activities "interfacing with" perceptible events, while the other subset prefers activities "detached from" perceptible events. While both show a common "aversion" to sensory-motoric activities, their differential preferences manifest a subdivision that sheds light upon the taxonomy of the brain's memory systems. This dichotomy is consistent with proposals of a macroscale gradational structure spanning across the cerebrum. This gradient increases its representational complexity, from primitive sensory-motoric processing, through lexical-semantic representations, to elaborated self-generated thoughts.

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