Evidence map›Paper›PMID 38467606›Full record

ArticleNature communications2024

A multi-demand operating system underlying diverse cognitive tasks.

Weidong Cai, Jalil Taghia, Vinod Menon

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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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.

Weidong CaiDepartment of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA. wdcai@stanford.edu.ORCID 0000-0001-9581-7774
Jalil TaghiaDepartment of Information Technology, Uppsala University, Uppsala, Sweden.
Vinod MenonDepartment of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA. menon@stanford.edu.ORCID 0000-0003-1622-9857

Funding

Integrative computational models of latent behavioral and neural constructs in children: a longitudinal developmental big-data approachR01MH121069 · NIMH · STANFORD UNIVERSITY · PI MENON, VINOD · 2019 to 2023
$3.9M
Methods for Dynamic Causal Interactions in Human Brain Function and DysfunctionR01NS086085 · NINDS · STANFORD UNIVERSITY · PI MENON, VINOD · 2014 to 2025
$3.9M
An integrative framework of cognitive control and reward modulation in children with ADHD: from brain dynamics to clinical symptomsR01MH124816 · NIMH · STANFORD UNIVERSITY · PI CAI, WEIDONG · 2021 to 2025
$3.7M
Computational modeling of dynamic causal brain circuits underlying cognitive dysfunction in Alzheimer's diseaseRF1NS086085 · NINDS · STANFORD UNIVERSITY · PI MENON, VINOD · 2021 to 2021
$2.0M
Novel Bayesian linear dynamical systems-based methods for discovering human brain circuit dynamics in health and diseaseR01EB022907 · NIBIB · STANFORD UNIVERSITY · PI MENON, VINOD · 2016 to 2018
$1.6M
Dynamic Brain Mechanisms of Proactive and Reactive Control in Childhood ADHDK01MH105625 · NIMH · STANFORD UNIVERSITY · PI CAI, WEIDONG · 2015 to 2018
$676k
NIBIB NIH HHS R01 EB022907NIMH NIH HHS K01 MH105625NIMH NIH HHS R01 MH121069NIMH NIH HHS R01 MH124816NINDS NIH HHS R01 NS086085NINDS NIH HHS RF1 NS086085
6 · The paper itself

Abstract

The existence of a multiple-demand cortical system with an adaptive, domain-general, role in cognition has been proposed, but the underlying dynamic mechanisms and their links to cognitive control abilities are poorly understood. Here we use a probabilistic generative Bayesian model of brain circuit dynamics to determine dynamic brain states across multiple cognitive domains, independent datasets, and participant groups, including task fMRI data from Human Connectome Project, Dual Mechanisms of Cognitive Control study and a neurodevelopment study. We discover a shared brain state across seven distinct cognitive tasks and found that the dynamics of this shared brain state predicted cognitive control abilities in each task. Our findings reveal the flexible engagement of dynamic brain processes across multiple cognitive domains and participant groups, and uncover the generative mechanisms underlying the functioning of a domain-general cognitive operating system. Our computational framework opens promising avenues for probing neurocognitive function and dysfunction.

Indexed as

BrainConnectomeBayes TheoremCognitionHumansMagnetic Resonance ImagingModels, StatisticalNerve Net

Identifiers

PMID38467606
PMCPMC10928152

What OpenQuestion holds

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LicenceCC BY
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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.