Time-Frequency functional connectivity alterations in Alzheimer's disease and frontotemporal dementia: An EEG...

Area of Science:

• Neuroscience
• Biomarker Discovery
• Neurodegenerative Diseases

Background:

• Alzheimer's disease (AD) and frontotemporal dementia (FTD) are major neurodegenerative disorders.
• Altered brain functional connectivity (FC) is a hallmark of AD and FTD.
• Over 100 million people worldwide are affected by these conditions.

Purpose of the Study:

• To identify distinct FC patterns as potential biomarkers for the differential diagnosis of AD and FTD.
• To investigate unique network alterations in AD and FTD using advanced EEG analysis.

Main Methods:

• Resting-state electroencephalography (EEG) data from AD patients, FTD patients, and healthy controls were analyzed.
• Time-frequency and bandpass filtering FC metrics were computed using Pearson's correlations, mutual information, and phase lag index.
• A support vector machine (SVM) with Leave-One-Out Cross-Validation was employed for classification.

Main Results:

• Both AD and FTD showed decreased frontal theta-band FC and increased posterior beta-band FC.
• AD uniquely exhibited decreased central theta-band FC compared to FTD.
• SVM achieved high classification accuracies: 95% for AD and 86% for FTD.

Conclusions:

• Altered FC patterns serve as reliable biomarkers for differentiating AD and FTD.
• This study provides novel insights into neurodegenerative pathologies by integrating diverse FC metrics.
• The findings highlight the potential for improved diagnostics in neurodegenerative diseases.