Resting state EEG: spectral and connectivity analyses in post-anoxic comatose patients

Thomas Kustermann, LREN Department of Clinical Neurosciences

Electrophysiological studies provided evidence of distinct patterns of connectivity configurations during sleep, anesthesia and in different categories of disorders of consciousness patients. Currently, no study has quantified the topological properties of functional brain networks of comatose patients during the first two days of coma, and how these properties relate to their long-term outcome.

We analyzed high-density electroencephalography resting state recordings from the first two days of post-anoxic coma. During the first day, we included 76 patients (within them 55 later awoke). For each patient, we computed the power spectra and derived a connectivity matrix based on the imagery coherence between all electrode couples. Cluster permutation analysis of the power spectra revealed differences (p<0.01) between survivors and non-survivors on the first day of coma in low frequencies centered around 10 Hz spread across the whole electrodes montage. The analysis of the topological properties in the connectivity matrices of the first day revealed significant (p < 0.05) differences in the clustering coefficient, participation coefficient and characteristic path length of the brain networks between survivors and non-survivors.

Together, these results show topological differences of the functional brain network in deeply unconscious patients who will later awake from coma in comparison to patients who will not survive. These findings can provide novel quantitative markers for predicting comatose patients’ outcome during the first day of coma.