Distinct EEG microstate signatures across different pain types

Abstract

Pain is associated with dynamic brain reorganization. Electroencephalographic microstates can characterize transient large-scale brain states, yet findings across pain studies are inconsistent. Two features may contribute: conditions have been studied in isolation, and analytical pipelines vary widely. We applied a harmonized analysis pipeline across three pain conditions: capsaicininduced pain, assessed within participants against a pain-free baseline, and non-chronic and chronic back pain, each compared with matched controls. Using a five-minute resting-state electroencephalographic recordings we examined microstate topography, temporal expression and transition probabilities, and directly compared pain related differences across pain states. We identified five microstates (A-E), corresponding to auditory, visual, salience, and attentional networks. Capsaicin pain showed increased expression of microstate C and reduced expression of microstates A, D and E. Transitions were redistributed towards microstate C, indicating a shift toward salience-related processing at the expense of sensory and attentional dynamics. In clinical back pain, effects were smaller and diverged by pain type: non-chronic back pain showed lower microstate C occurrence, opposite in direction to the capsaicin effect, whereas chronic back pain showed lower microstate D global explained variance, suggesting salience and attentional differences in clinical pain. Direct comparisons showed weaker pain-related increases in microstate C expression in both clinical back pain groups than capsaicin pain, with additional differences involving microstates A, D and E. These findings argue against a unitary EEG microstate signature of pain and instead reveal pain-type-specific patterns of large-scale brain dynamics, with microstate C providing the clearest distinction between experimental and clinical pain.