F125. Brain connectivity related to sleep-wake state: An intracranial EEG study

Abstract

Introduction Understanding brain connectivity in health and disease is a major challenge for basic and translational neuroscience. Direct EEG recordings from the brain surface (electrocorticography; ECoG) in epilepsy provide unique opportunity for studying human neuro-electric connectivity with reference to the wake, sleep and epileptic states. A major conundrum is reconciling the views of sleep being a disconnected state (Massimini et al., 2005) with the hypersynchronicity of sleep that favors seizure occurrence in the partial epilepsies, implying a heightened connectivity. Using spectral analysis and graph-theoretic measures (Bullmore and Sporns, 2009) applied to ECoG recordings in 6 patients undergoing continuous monitoring, we demonstrate how a reconciliation between these two scenarios is possible. Methods ECoG data in average reference format from six patients with refractory focal epilepsy undergoing prolonged pre-surgical video-EEG telemetry with subdural grid electrodes was analyzed. Segments of wakefulness and sleep (25–30 s long) were concatenated into contiguous epochs and normalized to zero mean and unit variance. Power spectra were computed by standard methods and the amplitude spectra curve-fitted empirically with a three-parameter function. The analysis was repeated over sliding windows of 30 s duration across the whole epoch. A fuzzy C-means method was used to cluster each parameter triplet into an activity score between [0–1], with 0 representing deep sleep, and 1 being alert wakefulness. The epoch time series were then filtered into the canonical Berger δ, θ, α, β and γ EEG bands. For each band, standard graph-theoretic measures were computed over sliding window segments across whole epochs to correspond with the activity score computations. Pearson correlations between the activity score and concurrently computed graph-theoretic connectivity metrics were calculated, and statistically significant correlations following Bonferroni correction (by a factor of 30) retained. Results We found that the coherence network modularity in the beta bands – relevant to high-frequency seizure-onset rhythms – correlated positively with wakefulness, while delta, theta and alpha modularity correlated negatively. An approximately reverse relationship was observed with respect to clustering coefficient. Conclusion Our results complement those obtained by resting state fMRI (Cox et al., 2014) and cortico-cortical evoked potentials (Usami et al., 2015) of sleep. We suggest that ECoG-based brain connectivity metrics are both state (sleep-wake) dependent and time-scale (waveform frequency) dependent. It is possible for the cortex to be ‘disconnected’ with respect to frequencies ostensibly underlying conscious wakefulness in the sleep state, yet ‘hyperconnected’ on time scales relevant to the transmission of epileptic seizures.