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Resting-State Functional Connectivity in Mathematical Expertise.

Miseon Shim1, Han-Jeong Hwang1,2, Ulrike Kuhl3

  • 1Department of Electronics and Information Engineering, Korea University, Sejong 30019, Korea.

Brain Sciences
|April 3, 2021
PubMed
Summary

Expertise alters brain connectivity. Resting-state functional magnetic resonance imaging (fMRI) revealed distinct functional brain networks in mathematicians compared to non-mathematicians, with high accuracy. This suggests neural efficiency in experts.

Keywords:
expertisemachine learningmathematiciansneural efficiencyresting-state functional connectivitysupport vector machine

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Machine Learning

Background:

  • Understanding how expertise shapes brain function is crucial for cognitive neuroscience.
  • Resting-state functional magnetic resonance imaging (fMRI) allows non-invasive investigation of intrinsic brain connectivity.

Purpose of the Study:

  • To investigate differences in brain functional connectivity between individuals with varying levels of mathematical expertise.
  • To determine if machine learning can distinguish between mathematicians and non-mathematicians based on resting-state fMRI data.

Main Methods:

  • Utilized resting-state functional magnetic resonance imaging (fMRI) to measure spontaneous brain activity correlations in mathematicians and non-mathematicians.
  • Applied machine learning classification algorithms to identify distinct functional connectivity patterns between the groups.

Main Results:

  • Identified unique functional connectivity patterns: mathematicians showed altered frontal-thalamic-temporal connections, while non-mathematicians exhibited different medial-frontal and orbital-thalamic pathways.
  • Found a negative correlation between mathematical knowledge scores and the connection strength between the left and right caudate nucleus in mathematicians.
  • Achieved a classification accuracy of 91.19% in distinguishing between the two groups based on resting-state fMRI functional connectivity features.

Conclusions:

  • Mathematical expertise is associated with distinct resting-state functional brain networks.
  • Preconfigured functional connectivity and neural efficiency may contribute to expert performance.
  • Resting-state fMRI combined with machine learning offers a powerful tool for identifying neural correlates of expertise.