The Neural Correlates of Consciousness: A Spectral Exponent Approach to Diagnosing Disorders of Consciousness.
Ying Zhao, Anqi Wang, Weiqiao Zhao, Nantu Hu, Steven Laureys, Haibo Di
Brain sciences April 4, 2025 DOI: 10.3390/brainsci15040377 via PubMed
Summary
AI-generated from the abstractA neurophysiological biomarker called the spectral exponent (SE), which measures the steepness of the aperiodic (1/f) slope of EEG activity, can help distinguish levels of consciousness in patients with disorders of consciousness (DoC). In a study of 15 DoC patients, 9 conscious brain-injured controls, and 23 healthy controls, narrowband SE (1-20 Hz) differentiated DoC patients from controls and minimally conscious from vegetative/unresponsive states. SE correlated positively with behavioral scores on the CRS-R, particularly the visual subscale. Longitudinal tracking in one patient showed a reduction in SE negativity, flattening of the 1/f slope, and parallel behavioral recovery. The SE offers an objective complement to subjective behavioral assessments.
Study at a glance
| Characteristics | Observational cohort Longitudinal Peer reviewed |
|---|---|
| Sample size | 47 |
| Population | Patients with disorder of consciousness, conscious brain-injured controls, and healthy controls |
| Keywords | EEG Biomarker Disorder of consciousness Spectral exponent Neuroscience Brain monitoring |
| Citations | 5 |
| Key finding | Narrowband spectral exponent (1-20 Hz) differentiates disorder of consciousness patients from controls and minimally conscious from vegetative/unresponsive states, and correlates with behavioral consciousness scores. |
Abstract
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. 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. Narrowband SE (1-20 Hz) showed superior diagnostic sensitivity, differentiating DoC from controls (HC vs. DoC: p < 0.0001; BI vs. DoC: 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. 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.