A Network-level Test of the Role of the Co-activated Default Mode Network in Episodic Recall and Social Cognition
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- Jackson_episodic_social_ICA_Cortex_AAM
Accepted author manuscript, 4.79 MB, PDF document
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Resting-state network research is extremely influential, yet the functions of many networks remain unknown. In part, this is due to typical (e.g., univariate) analyses independently 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 networks associated with these processes are described. Implications for prior univariate findings and the functional significance of the co-activated DMN are considered.
Keywords
- default mode network, Episodic memory, independent component analysis, resting-state networks, Social cognition
Original language | English |
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Pages (from-to) | 141-159 |
Journal | Cortex |
Volume | 165 |
Early online date | 16 May 2023 |
Publication status | Published - Aug 2023 |