Frequency- and Network-Specific Changes in Functional Connectivity Reflect Pathophysiological Mechanisms across...

Area of Science:

• Neuroscience
• Systems Neuroscience
• Clinical Neurology

Background:

• Parkinson's disease (PD) is increasingly viewed as a disorder affecting large-scale brain networks.
• Understanding how frequency-specific functional connectivity changes across PD stages is crucial but poorly understood.

Purpose of the Study:

• To characterize cortico-cortical functional connectivity across the clinical spectrum of Parkinson's disease using high-density EEG.
• To identify stage-dependent network alterations and evaluate their diagnostic and prognostic relevance.

Main Methods:

• A cross-sectional study involving 140 PD patients (early, intermediate, advanced stages) and 57 healthy controls.
• High-density electroencephalography (EEG) was used to reconstruct cortico-cortical functional connectivity in source space across multiple frequency bands.
• Network-based statistics and machine-learning models were employed to analyze network alterations.

Main Results:

• Three distinct large-scale networks showed divergent trajectories: α-band (hypoconnectivity, cognitive/axial impairment), β-band (hyperconnectivity, bradykinesia), and high-γ (early increase, then breakdown, motor complications).
• Multiband integration achieved high accuracy in discriminating early PD from controls and stratifying disease stages.
• Band-specific networks predicted clinical milestones, with α connectivity linked to lower risk of cognitive/axial impairment and high-γ connectivity to reduced motor complication vulnerability.

Conclusions:

• Frequency-specific cortical networks serve as markers for PD stage and clinical vulnerability.
• High-density EEG-derived connectivity offers a scalable systems-level biomarker for PD diagnosis, staging, and risk stratification.