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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30103 - Neurosciences (including psychophysiology)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název periodika

Journal of Neural Engineering

ISSN

1741-2560

e-ISSN

1741-2552

Svazek periodika

22

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

18

Strana od-do

066019

Kód UT WoS článku

001625773900001

EID výsledku v databázi Scopus

2-s2.0-105023209315