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[ELECTROPHYSIOLOGIC ANALYSIS OF MENTAL ARITHMETIC TASK BY THE "MINIMUM SPANNING TREE" METHOD].

Roland Boha, Tóth Brigitta, Zsófia Kardos

    Ideggyogyaszati Szemle
    |July 30, 2016
    PubMed
    Summary

    Graph theory analysis using the minimal spanning tree method reveals brain network changes during mental arithmetic. This approach effectively identifies neural networks associated with cognitive functions.

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    Area of Science:

    • Neuroscience
    • Graph Theory
    • Cognitive Science

    Context:

    • Mental arithmetic relies on working memory, but separating its neural basis from arithmetic processing is challenging.
    • Graph theoretical analysis offers novel methods for investigating brain functional connectivity.
    • Understanding cognitive function reorganization is crucial for both theoretical and clinical neuroscience.

    Purpose:

    • To investigate brain functional connection rearrangements induced by basic arithmetic using graph theory.
    • To differentiate neural networks involved in cognitive functions, specifically separating working memory from arithmetic processing.
    • To assess the utility of the minimal spanning tree (MST) method for analyzing task-related brain network changes.

    Summary:

    • The study analyzed electroencephalography (EEG) data from young adults performing passive viewing, number recognition, and mental arithmetic tasks.
    • The minimal spanning tree (MST) method, based on phase lag index (PLI), was applied in the theta (4-8 Hz) frequency band.
    • Task-related changes in graph indices like diameter, eccentricity, and fraction of leaves were observed, indicating distinct network reorganizations for different cognitive functions.

    Impact:

    • Task-related changes in graph indices can identify specific neural networks underlying dominant cognitive functions.
    • The minimal spanning tree method is a suitable tool for analyzing brain reorganization related to cognitive tasks.
    • Findings contribute to a deeper understanding of brain dynamics during cognitive load and may inform clinical investigations.