Authors :
Presenting Author: Ghassan Makhoul, BS – Vanderbilt University Medical Center
Bruno Hidalgo, BS – Vanderbilt University Medical Center
Derek Doss, PhD – Vanderbilt University
Graham Johnson, MD, PhD – Mayo
Addison Cavender, BS – Vanderbilt University Medical Center
Lucas Sainburg, BS – Vanderbilt University
Anas Reda, MS – Vanderbilt University Medical Center
Emily Liao, BE – Vanderbilt University Medical Center
Kate Wang, BS – Vanderbilt University Medical Center
Sameer Sundrani, – Vanderbilt University Medical Center
Shawniqua Williams Roberson, MEng, MD – Vanderbilt University Medical Center
Sarah Bick, MD – Vanderbilt University Medical Center
Victoria Morgan, PhD – Vanderbilt University Medical Center
Dario Englot, MD PhD – Vanderbilt University Medical Center
Rationale:
The relationship between epilepsy and sleep is bidirectional and complex. Nocturnal seizures disrupt sleep physiology, while sleep disruptions portend higher next-day seizure risk. Rapid eye movement (REM) sleep rebalances excitation-inhibition, which yields seizure protection specifically by lowering intercortical synchrony[1]. In normal sleep physiology, N3 should yield the highest cortical synchrony. However, for epilepsy patients, N3 sleep is the stage with most prominent interictal spikes[2]. Mesial temporal lobe epilepsy (mTLE) is known to produce seizures which preferentially damage subcortical structures leading to cascading interictal neurocognitive deficits. These same structures conduct the sleep stages. Thus, we hypothesized mTLE pathophysiology may similarly damage subcortical structures which underpin REM modulation of cortical networks. To assess this hypothesis, we analyzed stereo electroencephalography (SEEG) recordings from patients receiving epilepsy surgery and compared networks from patients with mTLE against those of lateral temporal lobe epilepsy (lTLE) and other focal epilepsies (OF).
Methods:
We studied SEEG recordings from 60 patients (23 mTLE, 17 lTLE, 20 OF) during nights where epileptologists did not identify epileptic activity. We automatically staged N2, N3, and REM sleep using a sleep stage classifier.
With post operative CTs and MRIs we designated Desikan Killiany (DK) atlas regions to SEEG contacts. For each sleep stage, we measured synchrony via phase locking values (PLV) between all contacts. We then averaged PLV across DK regions per sleep stage. We used linear mixed effects modelling (LME) to capture interaction between epilepsy type, sleep stage, and spectral band with years since diagnosis and monthly seizure burden as fixed effects. To account for heterogenous implant locations in the LME, we grouped contacts into frontal, parietal, temporal, occipital, limbic, and somatomotor regions. We compared regional PLV values across all 3 epilepsy types during each sleep stage per spectral band using Kruskal-Wallis test and used Mann-Whitney U for pairwise post hoc comparisons between groups.
Results:
lTLE and mTLE patients had higher global delta band PLV in REM compared to N3 than patients with OF epilepsies (p< .001, Fig 1A). Global high gamma band PLV was higher in REM compared to N3 sleep for patients with lTLE (p< 0.001, Fig, 2A). Specific region wise analysis found that frontal networks in lTLE patients demonstrated significantly higher synchrony than frontal regions in mTLE and OF, (p< .05, Kruskal Wallis omnibus test with Mann Whitney U post-hoc comparisons).