Evidence map›Paper›PMID 40800927›Full record

ArticleImaging neuroscience (Cambridge, Mass.)2025

Default mode network activation at task switches reflects mental task-set structure.

Ashley X Zhou, John Duncan, Daniel J Mitchell

Abstract read
In one paragraph

Article in Imaging neuroscience (Cambridge, Mass.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Sender-receiver subdivisions of the default mode network in perceptual and memory-guided cognition.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Ashley X ZhouMRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom.ORCID https://orcid.org/0009-0007-5711-6783
John DuncanMRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom.
Daniel J MitchellMRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom.ORCID https://orcid.org/0000-0001-8729-3886

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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;A. X. 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 depended on the number of tasks that could be encountered in a run, or on abstract task groupings defined by the temporal order in which they were learnt at instruction. 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 represented 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 organised into higher-level chunks, and Core DMN activity is the highest at switches between chunks.

Indexed as

cognitiondefault mode networkfunctional MRIMVPAswitching

Identifiers

PMID40800927
PMCPMC12319820

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.