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Connectome-Based Predictive Models of General and Specific Executive Functions.

Shijie Qu1,2, Yueyue Lydia Qu1,2, Kwangsun Yoo3,4,5

  • 1Department of Psychology, Yale University, New Haven, Connecticut, USA.

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|September 16, 2025
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Summary
This summary is machine-generated.

This study used brain connectivity to predict individual differences in executive functions like inhibition, shifting, and updating. Findings suggest a common executive function factor underlies these distinct cognitive processes.

Keywords:
connectomeexecutive functionsindividual differencepredictive modelstask‐based fMRI

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Area of Science:

  • Neuroscience
  • Cognitive Psychology
  • Brain Imaging

Background:

  • Executive functions are crucial for adaptive behavior and comprise inhibition, shifting, and updating.
  • Previous research explored individual components and their interrelations, but less focused on whole-brain connectivity for predicting performance differences.
  • Predicting individual differences in executive functions using brain network models remains an active area of investigation.

Purpose of the Study:

  • To build brain network models predicting individual differences in inhibition, shifting, and updating using functional MRI data.
  • To investigate the existence of a common executive function factor and its relationship with specific components.
  • To develop novel measures for disentangling shared and unique aspects of executive function components.

Main Methods:

  • Utilized the Connectome-based Predictive Modelling (CPM) approach with Human Connectome Project data.
  • Focused on functional MRI data acquired during 2-back tasks, outperforming resting-state and volumetric data.
  • Employed new measures to differentiate shared and unique contributions of executive function components.

Main Results:

  • Successfully predicted individual performance differences on tasks associated with inhibition, shifting, and updating.
  • Identified shared executive function predictive patterns within frontoparietal, default-mode, and dorsal attention networks.
  • Updating showed stronger cross-prediction with the general factor, while shifting and inhibition exhibited more distinct roles.

Conclusions:

  • Functional brain connectivity can predict individual differences in executive functions.
  • Evidence supports a common executive function factor, with updating playing a relatively prominent role.
  • The study introduces a novel approach to dissecting shared and specific components of executive functions from brain connectivity data.