Evidence map›Paper›PMID 34188024›Full record

ArticleNature communications2021

Dynamic causal brain circuits during working memory and their functional controllability.

Weidong Cai, Srikanth Ryali, Ramkrishna Pasumarthy, Viswanath Talasila, Vinod Menon

Abstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 1 pooled it
–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

51 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Review
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  5. Converging on control: Rethinking treatment-resistant depression through network neuroscience.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2026
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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

5 authors.

Weidong CaiDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA. wdcai@stanford.edu.ORCID http://orcid.org/0000-0001-9581-7774
Srikanth RyaliDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA.ORCID http://orcid.org/0000-0001-9773-0381
Ramkrishna PasumarthyDepartment of Electrical Engineering, Robert Bosch Center of Data Sciences and Artificial Intelligence, Indian Institute of Technology Madras, Chennai, India.
Viswanath TalasilaDepartment of Electronics and Telecommunication Engineering, Center for Imaging Technologies, M.S. Ramaiah Institute of Technology, Bengaluru, India.
Vinod MenonDepartment of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA. menon@stanford.edu.ORCID http://orcid.org/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
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
Methods for Dynamic Causal Interactions in the Developing Human BrainK25HD074652 · NICHD · STANFORD UNIVERSITY · PI RYALI, SRIKANTH · 2013 to 2019
$663k
NIBIB NIH HHS R01 EB022907NICHD NIH HHS K25 HD074652NIMH NIH HHS K01 MH105625NIMH NIH HHS R01 MH121069NINDS NIH HHS R01 NS086085NINDS NIH HHS RF1 NS086085
6 · The paper itself

Abstract

Control processes associated with working memory play a central role in human cognition, but their underlying dynamic brain circuit mechanisms are poorly understood. Here we use system identification, network science, stability analysis, and control theory to probe functional circuit dynamics during working memory task performance. Our results show that dynamic signaling between distributed brain areas encompassing the salience (SN), fronto-parietal (FPN), and default mode networks can distinguish between working memory load and predict performance. Network analysis of directed causal influences suggests the anterior insula node of the SN and dorsolateral prefrontal cortex node of the FPN are causal outflow and inflow hubs, respectively. Network controllability decreases with working memory load and SN nodes show the highest functional controllability. Our findings reveal dissociable roles of the SN and FPN in systems control and provide novel insights into dynamic circuit mechanisms by which cognitive control circuits operate asymmetrically during cognition.

Indexed as

AdultBrainBrain MappingCerebral CortexExecutive FunctionFemaleGyrus CinguliHumansMaleMemory, Short-TermModels, NeurologicalNerve NetNeural PathwaysPrefrontal CortexReproducibility of ResultsYoung Adult

Identifiers

PMID34188024
PMCPMC8241851

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.