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An MRI Study on Effects of Math Education on Brain Development Using Multi-Instance Contrastive Learning.

Yupei Zhang1,2, Shuhui Liu1,2, Xuequn Shang1,2

  • 1School of Computer Science, Northwestern Polytechnical University, Xi'an, China.

Frontiers in Psychology
|December 13, 2021
PubMed
Summary

Mathematical education impacts brain development, as shown by MRI scans of the intraparietal sulcus. A new contrastive learning model accurately classified students based on math study, revealing brain differences.

Keywords:
MRIbrain developmentcontrastive learningeducational cognitivemathematical learningmulti-instance learning

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Educational Psychology

Background:

  • Previous research focused on biochemical changes in the left middle frontal gyrus.
  • The intraparietal sulcus (IPS) region's role in mathematical cognition and its structural changes remains underexplored.

Purpose of the Study:

  • To investigate the effects of mathematical education on brain development using MRI data.
  • To classify students into math and non-math groups based on brain MRI features from the IPS region.
  • To develop a novel contrastive learning (CL) model for multi-instance representation learning in neuroimaging.

Main Methods:

  • Utilized magnetic resonance imaging (MRI) scans from 123 adolescent students (72 math, 51 non-math).
  • Applied a contrastive learning (CL) model adapted for multi-instance representation learning on cropped IPS regions.
  • Fed the learned data representations into a linear neural network for classification.

Main Results:

  • The proposed CL model achieved 90.24% accuracy in classifying students based on mathematical education.
  • Demonstrated over 5% improvement compared to classical CL frameworks.
  • Identified distinct MRI-based representations in the IPS region correlating with mathematical engagement.

Conclusions:

  • Mathematical education is associated with discernible changes in the intraparietal sulcus (IPS) region of the brain.
  • The developed multi-instance contrastive learning model offers a robust method for neuroimaging analysis.
  • This study provides novel MRI insights into how mathematical learning shapes adolescent brain development.