Resting-State EEG Analysis Characterizes the Signature of CACNA1A-and GAA-FGF14-Related Channelopathies

Cerebellar ataxia frequently results from ion channel dysfunction, with CACNA1A- and GAA-FGF14-related diseases representing two of the most prevalent genetic etiologies. While both disorders may share overlapping clinical features, their pathophysiology remain distinct and incompletely understood. Advanced resting-state electroencephalogram (rsEEG) analysis is an established methodology to assess cortical dynamics and network dysfunction in brain disorders. We applied advanced rsEEG analysis to identify disease-specific electrophysiological patterns in CACNA1A- and GAA-FGF14-related diseases. Routine scalp EEG examinations from genetically confirmed patients were retrospectively collected at the Department of Neurology of the Medical University Innsbruck. EEGs from matched healthy controls were retrieved from a publicly available database. Using a Bayesian hierarchical modeling framework, we analyzed spectral bandpower and functional connectivity metrics. Compared to healthy controls, CACNA1A patients (n = 29) exhibited significantly increased theta-band power and reduced alpha peak frequency across all brain regions. Additionally, they showed enhanced functional connectivity in both the delta/theta and gamma frequency bands. In contrast, findings in the GAA-FGF14-related group (n = 15) largely overlapped with those of healthy controls, with only mild alterations characterized by increased beta power in posterior regions and a hyperconnectivity pattern in the alpha band. CACNA1A-related disease is associated with widespread cortical network dysfunction, aligning with the clinical observation of frequent cognitive and neuropsychiatric symptoms-unlike the pure motor presentation seen in GAA-FGF14-related disease. Advanced rsEEG analysis allows for the non-invasive and repeatable detection and quantification of these alterations, holding promise for the development of surrogate markers for rare channelopathies.