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Explore Interregional EEG Correlations Changed by Sport Training Using Feature Selection.

Jia Gao1, Wei Wang1, Ji Zhang2

  • 1Laboratory of Machine Learning and Cognition, Nanjing Normal University, Nanjing 210097, China.

Computational Intelligence and Neuroscience
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Sport training significantly alters brain network connectivity. Electroencephalography (EEG) analysis revealed that correlations between specific brain regions changed, improving classification accuracy between trained athletes and controls.

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Area of Science:

  • Neuroscience
  • Sports Science
  • Biomedical Engineering

Background:

  • Understanding the neural underpinnings of athletic training is crucial for optimizing performance and recovery.
  • Electroencephalography (EEG) offers a non-invasive method to study brain activity and functional connectivity.

Purpose of the Study:

  • To investigate how sport training affects interregional brain correlations using EEG signals.
  • To differentiate between individuals with and without professional sport training based on EEG-derived brain network features.

Main Methods:

  • Acquired 19-channel EEG data from professional athletes and a control group.
  • Calculated Pearson Correlation Coefficients between all EEG channel pairs to represent brain network features.
  • Employed Partial Least Square (PLS) for feature selection to identify the most discriminative network correlations.
  • Utilized classification techniques to assess group differences based on selected EEG features.

Main Results:

  • Classification accuracy improved from 88.13% (using overall EEG energy) to 97.19% (using EEG correlation measurements).
  • The most significant change attributed to sport training was a decrease in the correlation between the left inferior frontal and left middle temporal regions.

Conclusions:

  • EEG-based interregional correlation analysis is a highly effective method for distinguishing between athletes and non-athletes.
  • Sport training induces specific alterations in functional brain connectivity, particularly impacting frontal-temporal pathways.