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
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
30103 - Neurosciences (including psychophysiology)
Result continuities
Project
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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