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Individual-level functional connectivity predicts cognitive control efficiency.

Benjamin L Deck1, Apoorva Kelkar1, Brian Erickson1

  • 1Department of Psychological and Brain Sciences, Drexel University, 3201 Chestnut Street, Philadelphia, 19104, PA, USA.

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|October 11, 2023
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Summary
This summary is machine-generated.

Cognitive control (CC) relies on brain network interactions. This study shows that functional connectivity between networks like the fronto-parietal control network (FPCN-B) and lateral default-mode network (L-DMN) predicts individual switching and inhibiting abilities.

Keywords:
Cognitive controlNavonPredictionStroop

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Area of Science:

  • Neuroscience
  • Cognitive Psychology
  • Brain Imaging

Background:

  • Cognitive control (CC) is crucial for daily problem-solving and is impaired in various disorders.
  • The tri-partite model identifies switching, inhibiting, and updating as key CC behaviors.
  • Specific brain networks, including the fronto-parietal control network B (FPCN-B), dorsal attention network (DAN), cingulo-opercular network (CON), and lateral default-mode network (L-DMN), are implicated in CC behaviors.

Purpose of the Study:

  • To investigate the interaction between specific brain networks in predicting individual differences in cognitive switching and inhibiting.
  • To determine if functional connectivity patterns within and between the FPCN-B, DAN, CON, and L-DMN can predict CC behaviors.

Main Methods:

  • Participants underwent fMRI scanning while performing tasks requiring cognitive switching and inhibiting.
  • Support vector regression (SVR) models were employed to predict behavioral performance using individually-estimated functional connectivity.
  • Connectivity was analyzed between the FPCN-B, DAN, CON, and L-DMN.

Main Results:

  • Inter-network functional connectivity was found to predict individual differences in both inhibiting and switching behaviors.
  • The lateral default-mode network (L-DMN) was identified as playing a significant role in both switching and inhibiting tasks.
  • Individually estimated inter-network connections serve as reliable markers for CC behaviors.

Conclusions:

  • Interactions between brain networks, particularly involving the L-DMN, are fundamental to cognitive control.
  • Functional connectivity patterns offer a potential biomarker for assessing and understanding CC deficits.
  • Cognitive switching and inhibiting abilities arise from the dynamic interplay among distributed neural networks.