Unmasking the noise: aberrant cortical oscillations in visual snow syndrome.

backgroundVisual snow syndrome (VSS) is characterised by persistent visual static and disabling perceptual disturbances, yet its underlying neural mechanisms remain poorly understood and are frequently confounded by migraine comorbidity.

methodsWe examined resting-state cortical oscillatory activity in VSS (n = 30) using EEG with distributed source modelling. Absolute and normalised spectral power was quantified across cortical regions, and machine-learning classifiers were trained to identify diagnostic spectral signatures.

resultsRelative to healthy controls (HC, n = 47), VSS showed a frequency-dependent redistribution of power, with increased low-frequency (delta–alpha) activity across parieto-occipital and frontal cortices, and reduced high-frequency (beta–high frequency oscillation) activity. When contrasted with migraine-only controls (n = 45), VSS with migraine (n = 25) exhibited additional enhancements of low-frequency activity within the parietal cortex. Machine-learning models reliably discriminated VSS from both HC and migraine-only patients using distinct sets of spectral features. Among the acceptable models, classification of VSS versus HC achieved an accuracy > 0.80 and an area under the curve (AUC) > 0.81, while classification of VSS with migraine versus migraine-only achieved an accuracy > 0.75 and an AUC > 0.81. Across models, alpha-band activity in the frontal and parietal regions showed the strongest predictive contribution.

conclusionThese findings indicate that VSS is characterised by a distinct and spatially distributed pattern of cortical dysrhythmia that is not attributable to migraine, and identify parietal low-frequency oscillatory activity as a potential physiological signature and target for neuromodulation. CLINICAL TRIAL NUMBER: Not applicable.