The Neural Correlates of Consciousness: A Spectral Exponent Approach to Diagnosing Disorders of Consciousness

Abstract

Background/Objectives: Disorder of consciousness (DoC) poses diagnostic challenges due to behavioral assessment limitations. This study evaluates the spectral exponent (SE)—a neurophysiological biomarker quantifying the decay slope of electroencephalography (EEG) aperiodic activity—as an objective tool for consciousness stratification and clinical behavior scores correlation. Methods: The study involved 15 DoC patients, nine conscious brain-injured controls (BI), and 23 healthy controls (HC). Resting-state 32-channel EEG data were analyzed to compute SE across broadband (1–40 Hz) and narrowband (1–20 Hz, 20–40 Hz). Statistical frameworks included Bonferroni-corrected Kruskal–Wallis H tests, Bayesian ANOVA, and correlation analyses with CRS-R behavioral scores. Results: Narrowband SE (1–20 Hz) showed superior diagnostic sensitivity, differentiating DoC from controls (HC vs. DoC: p p = 0.0006) and MCS from VS/UWS (p = 0.0014). SE correlated positively with CRS-R index (1–20 Hz: r = 0.590, p = 0.021) and visual subscale (1–20 Hz: r = 0.684, p = 0.005). High-frequency (20–40 Hz) SE exhibited inconsistent results. Longitudinal tracking in an individual revealed a reduction in SE negativity, a flattening of the 1/f slope, and behavioral recovery occurring in parallel. Conclusions: Narrowband SE (1–20 Hz) is a robust biomarker for consciousness quantification, overcoming behavioral assessment subjectivity. Its correlation with visual function highlights potential clinical utility. Future studies should validate SE in larger cohorts and integrate multimodal neuroimaging.

Keywords

• disorder of consciousness
• spectral exponent
• EEG biomarker