Altered Low-beta Characteristics in Individuals With Alcohol Use Disorder: A Pilot Resting Electroencephalography...

Area of Science:

• Neuroscience
• Clinical Psychology
• Biomarker Discovery

Background:

• Alcohol use disorder (AUD) pathophysiology is poorly understood, and current clinical assessments rely on subjective measures.
• Objective biomarkers for AUD diagnosis are lacking, hindering effective clinical evaluation and treatment.

Purpose of the Study:

• To explore resting-state electroencephalography (EEG) with power spectral analysis (PSA) and dynamic functional connectivity (dFC) as potential objective biomarkers for AUD.
• To differentiate individuals with AUD from healthy controls (HCs) using neurophysiological measures.

Main Methods:

• A case-control study involving resting-state EEG data collection from individuals with AUD and HCs.
• Power spectral analysis (PSA) to quantify EEG energy distribution and receiver operating characteristic (ROC) analysis for discriminatory capacity.
• Dynamic functional connectivity (dFC) analysis using a sliding window approach and weighted phase-lag index (wPLI) to identify brain states.

Main Results:

• The AUD group showed significantly elevated low-beta power at specific frontal and central electrode sites compared to HCs, with high diagnostic accuracy (AUC > 0.76).
• dFC analysis identified three distinct brain connectivity states (S1, S2, S3) with varying proportions.
• Correlations were found between identified connectivity patterns and clinical indices within the AUD cohort.

Conclusions:

• Resting-state EEG, particularly when analyzed with PSA and dFC, shows promise as a potential objective biomarker for AUD detection.
• Increased brain activity in medial frontal and left central gyri, along with low-beta frequency changes in dFC, are characteristic of AUD.