Electroencephalographic Resting-State Microstates are Unstable in Visual Snow Syndrome

Objective

To study large-scale network processing in visual snow syndrome (VSS) with and without migraine, we applied resting-state electroencephalographic microstate analysis.

Background

VSS is characterized by a spectrum of visual symptoms, with the main symptom being perceived as flickering dots throughout the visual field. The syndrome is associated with migraine and tinnitus and is considered a network disorder, but the cause and pathophysiology are still largely unknown.

Methods

In this case–control study, resting-state electroencephalography (EEG) recordings were selected from a cohort of 21 subjects with VSS (8 females, 33 ± 9.56 years, 14 migraines) and 21 matched controls (8 females, 33 ± 11.1 years, 14 migraines). An analysis of parameters between the four canonical microstate Classes A–D was performed.

Results

VSS patients showed an overall shorter duration (p = 0.001, Cohen's d = −0.48) and lower mean amplitude (p < 0.001, Cohen's d = −0.76) of microstates compared to the controls. In addition, we found an aberrant syntax of microstate Class A (auditive and visual processing) with more (p = 0.001, Cohen's d = 0.57) transitions to Class B (visual) and less (p = 0.011, d = −0.71) to Class C (interoceptive, salience) compared to controls.

Conclusion

Visual snow syndrome (VSS) is a complex disorder, affecting widespread neural network activity. In VSS, electroencephalography (EEG) microstate analysis revealed unstable microstates as well as aberrant transition probabilities, indicating disturbed large-scale network activity. The analysis of microstate dynamics in VSS complements the results of imaging with high temporal resolution and could contribute to the development of future treatment approaches.