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Updated: Oct 8, 2025

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

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Predicting children's math skills from task-based and resting-state functional brain connectivity.

Andrew Lynn¹, Eric D Wilkey², Gavin R Price^1,3

¹Department of Psychology and Human Development, Peabody College, Vanderbilt University, Nashville, TN 37212, USA.

Cerebral Cortex (New York, N.Y. : 1991)

|January 2, 2022

Summary

This summary is machine-generated.

Functional connectivity in the brain predicts children's math skills. Brain network patterns during rest and symbolic number tasks, but not nonsymbolic tasks, are key indicators of math ability.

Keywords:

childhood development functional connectivity math predictive modeling

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Area of Science:

Cognitive Neuroscience
Developmental Neuroscience
Neuroimaging

Background:

Predicting behavior from neural data is crucial for identifying individuals who may benefit from interventions.
Functional connectivity in brain networks is linked to math skills in children.

Purpose of the Study:

To investigate if functional connectivity during numerical processing and rest predicts children's math skills using connectome-based predictive modeling.
To explore the relationship between brain network patterns and mathematical abilities.

Main Methods:

Utilized connectome-based predictive modeling on a cohort of 31 children (average age 9.21 years).
Assessed functional connectivity during symbolic number comparison, nonsymbolic number comparison, and resting-state conditions.
Correlated predictive connectivity patterns with math skills.

Main Results:

Functional connectivity during symbolic number comparison and rest significantly predicted math skills.
Connectivity during nonsymbolic number comparison did not predict math skills.
Predictive connections differed between task states and were often negatively correlated with math skills (weaker connectivity predicted better performance).

Conclusions:

Children's math abilities are associated with specific, state-dependent patterns of functional brain connectivity.
Connectome-based predictive modeling offers a promising approach for understanding and potentially predicting future math skills.
Findings suggest that network segregation and regional specialization during different cognitive states are important for mathematical competence.