Evidence map›Paper›PMID 34261649›Full record

ArticleScience advances2021

Activity flow underlying abnormalities in brain activations and cognition in schizophrenia.

Luke J Hearne, Ravi D Mill, Brian P Keane, Grega Repovš, Alan Anticevic, Michael W Cole

Abstract read
In one paragraph

Article in Science advances, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

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  13. The Prediction of Brain Activity from Connectivity: Advances and Applications.The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry · 2024
    Review
  14. Article
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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

6 authors.

Luke J HearneCenter for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, USA. lukehearne@gmail.com.ORCID 0000-0002-2014-1148
Ravi D MillCenter for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, USA.ORCID 0000-0002-9249-8744
Brian P KeaneUniversity Behavioral Health Care, Department of Psychiatry, and Center for Cognitive Science, Rutgers University, Piscataway, NJ, USA.ORCID 0000-0002-7011-3380
Grega RepovšDepartment of Psychology, University of Ljubljana, Aškerčeva 2, Ljubljana SI-1000, Slovenia.ORCID 0000-0003-1837-3879
Alan AnticevicDepartment of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
Michael W ColeCenter for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, USA.ORCID 0000-0003-4329-438X

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Brain Network Mechanisms of Aging-Related Cognitive DeclineR01AG055556 · NIA · RUTGERS THE STATE UNIV OF NJ NEWARK · PI COLE, MICHAEL WILLIAM · 2017 to 2022
$2.3M
Characterizing Schizophrenia Progression via Multi-modal Neuroimaging and ComputationR01MH108590 · NIMH · YALE UNIVERSITY · PI ANTICEVIC, ALAN · 2016 to 2020
$2.0M
Brain Network Mechanisms of Instructed LearningR01MH109520 · NIMH · RUTGERS THE STATE UNIV OF NJ NEWARK · PI COLE, MICHAEL WILLIAM · 2016 to 2020
$2.0M
Mapping the Longitudinal Neurobiology of Early-course SchizophreniaR01MH112189 · NIMH · YALE UNIVERSITY · PI ANTICEVIC, ALAN · 2017 to 2021
$939k
Neural mechanisms of perceptual organization deficits across the schizo-bipolar spectrumK01MH108783 · NIMH · RUTGERS BIOMEDICAL/HEALTH SCIENCES-RBHS · PI KEANE, BRIAN PATRICK · 2016 to 2019
$680k
NCATS NIH HHS UL1 TR001863NIA NIH HHS R01 AG055556NIMH NIH HHS K01 MH108783NIMH NIH HHS R01 MH108590NIMH NIH HHS R01 MH109520NIMH NIH HHS R01 MH112189
6 · The paper itself

Abstract

Cognitive dysfunction is a core feature of many brain disorders, including schizophrenia (SZ), and has been linked to aberrant brain activations. However, it is unclear how these activation abnormalities emerge. We propose that aberrant flow of brain activity across functional connectivity (FC) pathways leads to altered activations that produce cognitive dysfunction in SZ. We tested this hypothesis using activity flow mapping, an approach that models the movement of task-related activity between brain regions as a function of FC. Using functional magnetic resonance imaging data from SZ individuals and healthy controls during a working memory task, we found that activity flow models accurately predict aberrant cognitive activations across multiple brain networks. Within the same framework, we simulated a connectivity-based clinical intervention, predicting specific treatments that normalized brain activations and behavior in patients. Our results suggest that dysfunctional task-evoked activity flow is a large-scale network mechanism contributing to cognitive dysfunction in SZ.

Indexed as

SchizophreniaBrainBrain MappingCognitionHumansMagnetic Resonance Imaging

Identifiers

PMID34261649
PMCPMC8279516

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.