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Spectral brain connectivity in dementia: coherence, imaginary coherence and partial coherence analysis of EEG signals

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F25%3A00643764" target="_blank" >RIV/67985807:_____/25:00643764 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1088/1741-2552/ae1ea1" target="_blank" >https://doi.org/10.1088/1741-2552/ae1ea1</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1088/1741-2552/ae1ea1" target="_blank" >10.1088/1741-2552/ae1ea1</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Spectral brain connectivity in dementia: coherence, imaginary coherence and partial coherence analysis of EEG signals

  • Original language description

    OBJECTIVE. As the prevalence of dementia continues to rise, the need for accurate and early diagnostic tools becomes increasingly critical. Despite diverse underlying causes, dementia types share common cognitive symptoms, making accurate diagnosis essential for effective treatment. APPROACH: This study investigates electroencephalographic (EEG)-based spectral brain connectivity in individuals with Alzheimer's disease (AD, N=36), frontotemporal dementia (FTD, N=23), and healthy controls (HCs, N=29), with the dual aim of identifying condition-specific connectivity patterns and evaluating three coherence-based connectivity measures: coherence, imaginary coherence, and partial coherence. Resting-state, eyes-closed EEG data (19 channels) were analyzed, and connectivity was estimated across frequencies to assess both global and local network alterations. MAIN RESULTS: The results indicate that dementias (both AD and FTD) are characterized by decreased connectivity in higher frequency bands and increased connectivity in lower frequencies, reflecting respectively impaired neural communication and neurodegeneration. Moreover, the severity of cognitive impairment correlates with the spatial extent and magnitude of connectivity disruptions. Notably, partial coherence-unlike coherence and imaginary coherence-effectively distinguishes between the AD and FTD groups, suggesting that direct connectivity measures may provide more discriminative information for differential diagnosis. SIGNIFICANCE. These findings highlight the potential of EEG-based spectral connectivity analysis, particularly partial coherence, as a non-invasive tool to aid in the diagnosis and differential diagnosis of dementia subtypes, supporting early clinical decision-making.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    30103 - Neurosciences (including psychophysiology)

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Journal of Neural Engineering

  • ISSN

    1741-2560

  • e-ISSN

    1741-2552

  • Volume of the periodical

    22

  • Issue of the periodical within the volume

    6

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    18

  • Pages from-to

    066019

  • UT code for WoS article

    001625773900001

  • EID of the result in the Scopus database

    2-s2.0-105023209315