A network-level test of the role of the co-activated default mode network in episodic recall and social cognition
Cortex; a journal devoted to the study of the nervous system and behavior(2023)
Abstract
Resting-state network research is extremely influential, yet the functions of many net-works remain unknown. In part, this is due to typical (e.g., univariate) analyses indepen-dently testing the function of individual regions and not examining the full set of regions that form a network whilst co-activated. Connectivity is dynamic and the function of a region may change based on its current connections. Therefore, determining the function of a network requires assessment at this network-level. Yet popular theories implicating the default mode network (DMN) in episodic memory and social cognition, rest principally upon analyses performed at the level of individual brain regions. Here we use independent component analysis to formally test the role of the DMN in episodic and social processing at the network level. As well as an episodic retrieval task, two independent datasets were employed to assess DMN function across the breadth of social cognition; a person knowledge judgement and a theory of mind task. Each task dataset was separated into networks of co-activated regions. In each, the co-activated DMN, was identified through comparison to an a priori template and its relation to the task model assessed. This co -activated DMN did not show greater activity in episodic or social tasks than high-level baseline conditions. Thus, no evidence was found to support hypotheses that the co -activated DMN is involved in explicit episodic or social tasks at a network-level. The net-works associated with these processes are described. Implications for prior univariate findings and the functional significance of the co-activated DMN are considered.& COPY; 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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Key words
Default mode network,Episodic memory,Independent component analysis,Resting-state networks,Social cognition
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