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Between-Frequency Topographical and Dynamic High-Order Functional Connectivity for Driving Drowsiness Assessment.

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    New methods using high-order functional connectivity (HOFC) reveal significant changes in brain activity during driving drowsiness. These findings offer complementary insights beyond traditional measures for detecting driver fatigue.

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    Area of Science:

    • Neuroscience
    • Cognitive Science
    • Biomedical Engineering

    Background:

    • Previous research on driving drowsiness primarily used spectral power and basic functional connectivity.
    • These methods often overlook complex inter-frequency and higher-order brain synchronizations.

    Purpose of the Study:

    • To investigate inter-regional synchronizations using high-order functional connectivity (HOFC) and envelope correlation.
    • To explore dynamic and topographical properties of brain activity between frequency bands.
    • To develop and validate novel metrics for assessing driving drowsiness.

    Main Methods:

    • Utilized electroencephalography (EEG) data from 30 healthy subjects across two driving sessions.
    • Applied high-order functional connectivity (HOFC), associated-HOFC, and global metrics.
    • Analyzed dynamic interactions and topographical properties within and between frequency bands (theta, alpha, beta).

    Main Results:

    • Reliably significant changes in HOFC and associated-HOFC metrics were observed, particularly involving the alpha band.
    • Increased connection-level metrics were noted in frontal-central, central-central, and central-parietal/occipital areas.
    • Global metrics for dynamic-HOFC showed significant increments in alpha, theta-alpha, and alpha-beta bands, indicating increased drowsiness.

    Conclusions:

    • Within-band and between-frequency topographical and dynamic functional connectivity provide valuable information for drowsiness detection.
    • These advanced HOFC metrics offer complementary insights compared to traditional low-order functional connectivity (LOFC).
    • The developed metrics demonstrate reliability and potential for real-world driving safety applications.