Evidence map›Paper›PMID 41001503›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Neurocognitive characterization of behaviour and mental illness through time-varying brain network analysis.

Xiao Chang, Tianye Jia, Zening Fu, Shitong Xiang, Yunman Xia, Chao Xie, Jiyan Zou, Miao Cao, Jie Zhang, Tobias Banaschewski and 24 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

34 authors.

Xiao Chang
Tianye Jia
Zening Fu
Shitong Xiang
Yunman Xia
Chao Xie
Jiyan Zou
Miao Cao
Jie Zhang
Tobias Banaschewski
Arun Bokde
Sylvane Desrivieres
Herta Flor
Antoine Grigis
Hugh Garavan
Penny Gowland
Andreas Heinz
Rudiger Bruhl
Jean-Luc Martinot
Marie-Laure Paillere Martinot
Eric Artiges
Frauke Nees
Dimitri Papadopoulos Orfanos
Luise Poustka
Sarah Hohmann
Christian Baeuchl
Nilakshi Vaidya
Henrik Walter
Robert Whelan
Jianfeng Feng
Gunter Schumann

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cognitive processing in humans relies on regional brain activity and large-scale, whole-brain network interactions which evolve in a time-dependent manner. Traditional task-based neuroimaging analysis does not sufficiently consider this temporal dimension, thus restricting the characterisation of networks and resulting in limited brain representation of cognition and behaviour. Time-varying, task-based neuroimaging analysis provides a unique opportunity to characterize brain functional network reconfiguration with ongoing task stimuli and may represent a better neural proxy for cognition and behaviour. In this study, we characterized functional network connectivity (FNC) fluctuations in resting-state and three reinforcement-related tasks, to illustrate network reconfiguration across multiple tasks. We further determined behavioural relevance of the whole-brain and regional FNC by relating network measurements with task performances and psychopathology. We found that several consistent whole-brain functional networks (FNC states) exist across resting-state and task fMRI sessions, and FNC state occurrences are sensitive to the most prominent task stimuli within a task session. In contrast, pair-wise, regional FNC could distinguish specific task conditions. When tested for correlation with psychopathology symptoms as well as clinical depression and alcohol use disorder in independent samples, we showed that FNC derived from time-varying analysis could account for a much higher amount of variance compared to FNC derived from static connectivity. Our results suggest that cognitive processing modulates task-relevant, regional FNC and changes whole-brain functional network connectivity, thus broadly affecting brain network architecture. By considering the different FNC states, time-varying connectivity provides a more comprehensive representation of brain interactions and thus may serve as a more precise neural correlate in quantifying an individual's risk for psychopathology.

Identifiers

PMID41001503
PMCPMC12458501

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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.