Default Mode Network activation at task switches reflects mental task-set structure
Summary
AI-generated from the abstractCore Default Mode Network (DMN) activity increases during switches between externally-focused tasks, but this response depends on how tasks are grouped by the order they were learned, not on the number of tasks. In an fMRI study, participants performed tasks while the number of relevant tasks varied, but DMN activation at switches was unaffected by task count. Instead, multivariate decoding showed the Core DMN hierarchically represents individual tasks, task domains, and higher-order groupings based on instruction order. The findings suggest that as instruction complexity increases, rules are organized into higher-level chunks, and Core DMN activity peaks at switches between those chunks.
Study at a glance
| Characteristics | fMRI study |
|---|---|
| Key finding | Core DMN activation at task switches depends on the order in which groups of tasks were learned, not on the number of currently relevant tasks. |
Abstract
Abstract Recent findings challenge traditional views of the Default Mode Network (DMN) as purely task-negative or self-oriented, showing increased DMN activity during demanding switches between externally-focused tasks (Crittenden et al., 2015; Smith et al., 2018; Zhou et al., 2024). However, it is unclear what modulates the DMN at switches, with transitions within a stimulus domain activating DMN regions in some studies but not others. Differences in the number of tasks suggest that complexity or structure of the set of tasks may be important. In this fMRI study, we examined whether the DMN’s response to task switches depends on the complexity of the active set of tasks, manipulated by the number of tasks in a run, or abstract task groupings based on instructional order. Core DMN activation at task switches was unaffected by the number of currently relevant tasks. Instead, it depended on the order in which groups of tasks had been learnt. Multivariate decoding revealed that Core DMN hierarchically represents individual tasks, task domains, and higher-order task groupings based on instruction order. We suggest that, as the complexity of instructions increases, rules are increasingly organized into higher-level chunks, and Core DMN activity is highest at switches between chunks.