Altered EEG-derived co-fluctuation structure in disorders of consciousness

EEG-derived functional connectivity (FC) enables high-temporal-resolution probing of neural mechanisms underlying disorders of consciousness (DOC). Unlike stationary conventional FC, dynamic FC (dFC) captures fast transient neural coupling. Recent fMRI studies introduced a co‑fluctuation framework to track moment‑to‑moment connectivity change, yet whether such co-fluctuation features can quantify consciousness status remains elusive. Here, we adapt this established co-fluctuation paradigm to resting-state EEG to characterize the temporal architectures of EEG-derived FC across varying conscious states. We decomposed the co-fluctuation time series into high-amplitude frames (HAF) and low-amplitude frames (LAF), comparing their dynamics between real brain data and null models. We then analyzed co-fluctuation activities across consciousness levels at both global and local spatial scales, examining spatial variability in these patterns. By integrating HAF and LAF parameters, we evaluated their diagnostic potential for distinguishing DOC states. Results revealed reduced stability of co-fluctuations with loss of consciousness, accompanied by a shift toward random system dynamics. DOC patients exhibited reduced spatial and temporal heterogeneity in co-fluctuation activities compared to healthy controls. Both high- and low-amplitude patterns provided useful metrics for detecting consciousness levels. These findings offer novel insights into the dynamic organization of brain networks in DOC, emphasizing the significance of co-fluctuation dynamics in characterizing brain states and suggesting potential biomarkers for assessing consciousness levels.

The online version contains supplementary material available at https://doi.org/10.1007/s11571-026-10580-7.