Authors :
Presenting Author: Nicholas Paleologos, BS – NYU Neuroscience Institute
Forouzan Farahani, Ph.D. – New York University Langone Health
Jiyun Shin, PhD – New York University Langone Health
Anna Maslarova, MD, PhD – NYU Neuroscience Institute
Simon Henin, Ph.D. – New York University Langone Health
Alia Seedat, BS – NYU Langone
György Buzsáki, MD PhD – New York University, Grossman School of Medicine
Anli Liu, M.D. – New York University Langone Health
Rationale:
Epidemiological studies show a link between metabolic disturbances, such as hyperglycemia and insulin resistance, and incidence of seizures. Yet, the central mechanisms of both homeostatic and pathological glucose regulation are poorly understood. The hippocampal sharp wave-ripple (SPW-R), which occurs during non-rapid eye movement (NREM) sleep, has been shown to trigger acute decreases in peripheral glucose levels in rats (Tingley et al. 2021). Human studies suggest that slow oscillations (SO) and spindles–NREM-dominant rhythms typically coupled to SPW-Rs–predict next-day glucose control. However, whether SPW-Rs play a direct role in modulating peripheral glucose in humans has not been established. Further, the effect of pathological patterns such as interictal epileptiform discharges (IEDs) and seizures on systemic glucose is unknown. Here we investigate how physiological and epileptiform hippocampal events impact peripheral glucose in epilepsy patients undergoing intracranial EEG (iEEG) monitoring.
Methods:
LFPs were obtained by resampling iEEG data at 512 Hz and re-referencing to a white matter contact. NREM sleep bouts were determined by calculating delta (0.5-4 Hz)-gamma (20-30 Hz) power ratio. IEDs were detected using a 10-60 Hz passband with a peak threshold of 15 SDs from background. SPW-Rs were identified using an 80-200 Hz passband and >= 5 SD threshold. Events were grouped into 1-min bins and aligned to continuous glucose monitoring data. The first derivative of the glucose signal (dGlucose) was used to analyze glycemic changes. Cross-correlations were computed between event rates and dGlucose. Instantaneous phase and power of SO (0.5-2 Hz) and spindles (9-16 Hz) were extracted using a Hilbert transform. Events were grouped based on their coupling to SOs or spindles to compare their differential impact on glucose dynamics. Significant phase-locking was assessed with Rayleigh’s test (p< 0.01).