Related Experiment Video
Updated: Jul 10, 2025
Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography
Published on: June 15, 2018
Resting-state background features demonstrate multidien cycles in long-term EEG device recordings
William K S Ojemann1, Brittany H Scheid1, Sofia Mouchtaris1
1University of Pennsylvania, Department of Bioengineering, 210 S. 33rd Street, Philadelphia, PA, 19104, USA.
Background:
Longitudinal EEG recorded by implanted devices is critical for understanding and managing epilepsy. Recent research reports patient-specific, multi-day cycles in device-detected epileptiform events that coincide with increased likelihood of clinical seizures. Understanding these cycles could elucidate mechanisms generating seizures and advance drug and neurostimulation therapies.
Objective/Hypothesis:
We hypothesize that seizure-correlated cycles are present in background neural activity, independent of interictal epileptiform spikes, and that neurostimulation may temporarily interrupt these cycles.
Methods:
We analyzed regularly-recorded seizure-free data epochs from 20 patients implanted with a responsive neurostimulation (RNS) device for at least 1.5 years, to explore the relationship between cycles in device-detected interictal epileptiform activity (dIEA), clinician-validated interictal spikes, background EEG features, and neurostimulation.
Results:
Background EEG features tracked the cycle phase of dIEA in all patients (AUC: 0.63 [0.56-0.67]) with a greater effect size compared to clinically annotated spike rate alone (AUC: 0.55 [0.53-0.61], p < 0.01). After accounting for circadian variation and spike rate, we observed significant population trends in elevated theta and beta band power and theta and alpha connectivity features at the cycle peaks (sign test, p < 0.05). In the period directly after stimulation we observe a decreased association between cycle phase and EEG features compared to background recordings (AUC: 0.58 [0.55-0.64]).
Conclusions:
Our findings suggest that seizure-correlated dIEA cycles are not solely due to epileptiform discharges but are associated with background measures of brain state; and that neurostimulation may temporarily interrupt these cycles. These results may help elucidate mechanisms underlying seizure generation, provide new biomarkers for seizure risk, and facilitate monitoring, treating, and managing epilepsy with implantable devices.
