Is There Electrophysiologic Evidence for Seizure-related Consolidation?
Abstract number :
3.298
Submission category :
3. Neurophysiology / 3G. Computational Analysis & Modeling of EEG
Year :
2024
Submission ID :
231
Source :
www.aesnet.org
Presentation date :
12/9/2024 12:00:00 AM
Published date :
Authors :
Presenting Author: Yurui Cao, BS – University of Illinois Urbana-Champaign
Vaclav Kremen, PhD, MS, EMBA – Department of Neurology, Mayo Clinic, Rochester MN USA
Krishnakant Saboo, PhD – University of California, San Francisco
Filip Mivalt, MS – Mayo Clinic
Vlad Sladky, BS – Department of Neurology, Mayo Clinic, Rochester MN USA
Aisha Abdul Razaq, MD – Mayo Clinic, Rochester MN USA
Jordan Clark, BS – Department of Neurology, Mayo Clinic, Rochester MN USA
Jamie Van Gompel, MD – Mayo Clinic
Kai Miller, MD, PhD – Mayo Clinic
Dora Hermes, PhD – Mayo Clinic
Paul Arnold, MD – University of Illinois Urbana-Champaign
Suguna Pappu, MD, PhD – Carle Foundation Hospital
Ravishankar Iyer, PhD – University of Illinois Urbana-Champaign
Gregory Worrell, MD, PhD – Mayo Clinic
Rationale: In mesial temporal lobe epilepsy (mTLE), seizures rarely occur during non-rapid eye movement (NREM) sleep, a period when the consolidation process usually takes place. Thalamo-hippocampal functional connectivity (THFC) is crucial for information transfer during consolidation and plays a role in seizure propagation. This study examines the temporal dynamics of THFC across different behavioral states and demonstrates evidence for seizure-related consolidation (SRC) during NREM sleep.
Methods: We continuously measured the brain local field potentials of patients with mTLE using a novel ambulatory sensing and stimulation device. We quantified the functional connectivity by computing features between the bipolar montage of electrodes from bilateral anterior nuclei of the thalamus and hippocampi: (1) relative entropy (REN), which measures the difference between amplitude distributions; and (2) phase locking value (PLV), which quantifies the degree of synchronization in phases. We computed these features using 10-second data segments across six different frequency bands, and then applied a moving average with a 5-minute window and 1-minute steps. We also examined delta band power. This study contains two main analyses: (1) comparing THFC changes between NREM sleep and wakefulness, where we test the differences in connectivity features distribution means of these two behavioral states with the Wilcoxon rank-sum test; and (2) comparing THFC and delta band power between sleep after seizures (post-SZ sleep) and sleep without daytime seizures (SZ-free sleep), where we compared the feature distributions during the first 4 hours of NREM sleep (early NREM), when the consolidation process usually happens, with the Kolmogorov–Smirnov test.
Results: Our study encompassed analysis of intracranial EEG (iEEG) recordings of four patients spanning 56 days. Notably, we identified a marked increase of THFC (p < 0.001) in NREM sleep compared to wakefulness on both the left side (in the delta, theta, alpha, and sigma bands, measured by REN) and the right side (in the sigma band, measured by PLV) of the brain. We also observed a marked decrease of THFC on the left (measured by REN) and right (measured by PLV) side during NREM sleep in the beta and low gamma bands. More importantly, we discovered a marked increase of delta power (p < 0.001) in two out of three patients (one patient was excluded because their data for SZ-free sleep were unavailable) during early NREM of post-SZ sleep compared to SZ-free sleep. We also found a marked increase of THFC (p < 0.001) in the alpha, sigma, and beta bands on the left side during early NREM of post-SZ sleep compared to SZ-free sleep.
Neurophysiology