Evidence map›Paper›PMID 33542083›Full record

ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2021

The Functional Relevance of Task-State Functional Connectivity.

Michael W Cole, Takuya Ito, Carrisa Cocuzza, Ruben Sanchez-Romero

Abstract read
In one paragraph

Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers.

0numbers the graph read from it
0cells of the map it votes in
93citing 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

93 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

33 more citing papers are in PubMed but not listed here.

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

4 authors.

Michael W ColeCenter for Molecular & Behavioral Neuroscience, Rutgers University, Newark, New Jersey 07102 michael.cole@rutgers.edu.ORCID 0000-0003-4329-438X
Takuya ItoCenter for Molecular & Behavioral Neuroscience, Rutgers University, Newark, New Jersey 07102.
Carrisa CocuzzaCenter for Molecular & Behavioral Neuroscience, Rutgers University, Newark, New Jersey 07102.
Ruben Sanchez-RomeroCenter for Molecular & Behavioral Neuroscience, Rutgers University, Newark, New Jersey 07102.

Funding

Mapping the Human Connectome: Structure, Function, and HeritabilityU54MH091657 · NIMH · WASHINGTON UNIVERSITY · PI UGURBIL, KAMIL, VAN ESSEN, DAVID C · 2010 to 2014
$34.7M
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
Brain Network Mechanisms of Instructed LearningR01MH109520 · NIMH · RUTGERS THE STATE UNIV OF NJ NEWARK · PI COLE, MICHAEL WILLIAM · 2016 to 2020
$2.0M
NIA NIH HHS R01 AG055556NIMH NIH HHS R01 MH109520NIMH NIH HHS U54 MH091657
6 · The paper itself

Abstract

Resting-state functional connectivity has provided substantial insight into intrinsic brain network organization, yet the functional importance of task-related change from that intrinsic network organization remains unclear. Indeed, such task-related changes are known to be small, suggesting they may have only minimal functional relevance. Alternatively, despite their small amplitude, these task-related changes may be essential for the ability of the human brain to adaptively alter its functionality via rapid changes in inter-regional relationships. We used activity flow mapping-an approach for building empirically derived network models-to quantify the functional importance of task-state functional connectivity (above and beyond resting-state functional connectivity) in shaping cognitive task activations in the (female and male) human brain. We found that task-state functional connectivity could be used to better predict independent fMRI activations across all 24 task conditions and all 360 cortical regions tested. Further, we found that prediction accuracy was strongly driven by individual-specific functional connectivity patterns, while functional connectivity patterns from other tasks (task-general functional connectivity) still improved predictions beyond resting-state functional connectivity. Additionally, since activity flow models simulate how task-evoked activations (which underlie behavior) are generated, these results may provide mechanistic insight into why prior studies found correlations between task-state functional connectivity and individual differences in behavior. These findings suggest that task-related changes to functional connections play an important role in dynamically reshaping brain network organization, shifting the flow of neural activity during task performance.

Indexed as

AdultBrainCognitionFemaleHumansMagnetic Resonance ImagingMaleNerve NetPsychomotor PerformanceYoung Adultcomputational modelhuman connectome projectmachine learningnetwork coding modelsnetwork neurosciencetask connectivity

Identifiers

PMID33542083
PMCPMC8018740

What OpenQuestion holds

Textmetadata
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.