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

BACKGROUND: Visual 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. METHODS: We 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. RESULTS: Relative 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. CONCLUSION: These 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.