Resting-state background features demonstrate multidien cycles in long-term EEG device recordings

William K S Ojemann; Brittany H Scheid; Sofia Mouchtaris; Alfredo Lucas; Joshua J LaRocque; Carlos Aguila; Arian Ashourvan; Lorenzo Caciagli; Kathryn A Davis; Erin C Conrad; Brian Litt

doi:10.1016/j.brs.2023.11.005

Resting-state background features demonstrate multidien cycles in long-term EEG device recordings

Brain Stimul. 2023 Nov-Dec;16(6):1709-1718. doi: 10.1016/j.brs.2023.11.005. Epub 2023 Nov 16.

Authors

Affiliations

¹ University of Pennsylvania, Department of Bioengineering, 210 S. 33rd Street, Philadelphia, PA, 19104, USA. Electronic address: wojemann@seas.upenn.edu.
² University of Pennsylvania, Department of Bioengineering, 210 S. 33rd Street, Philadelphia, PA, 19104, USA.
³ University of Pennsylvania, Department of Bioengineering, 210 S. 33rd Street, Philadelphia, PA, 19104, USA; University of Pennsylvania, Perelman School of Medicine, 3400 Civic Center Blvd, Philadelphia, PA, 19104, USA.
⁴ University of Pennsylvania, Department of Bioengineering, 210 S. 33rd Street, Philadelphia, PA, 19104, USA; Hospital of the University of Pennsylvania, Department of Neurology, 3400 Spruce St, Philadelphia, PA, 19104, USA.
⁵ The University of Kansas, Department of Psychology, 1415 Jayhawk Blvd, Lawrence, KS, 66045, USA.

PMID: 37979654
DOI: 10.1016/j.brs.2023.11.005

Abstract

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.

Keywords: Biomarkers; Epilepsy; Interictal; Neurostimulation; RNS; Spikes.

MeSH terms

Brain
Electroencephalography* / methods
Epilepsy* / therapy
Humans
Seizures / therapy

Substances

N,N-diisopropylethylamine