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Resting-state background features demonstrate multidien cycles in long-term EEG device recordings
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 c...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10350154/ https://www.ncbi.nlm.nih.gov/pubmed/37461688 http://dx.doi.org/10.1101/2023.07.05.23291521 |
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author | Ojemann, William K.S. Scheid, Brittany H. Mouchtaris, Sofia Lucas, Alfredo LaRocque, Joshua J. Aguila, Carlos Ashourvan, Arian Caciagli, Lorenzo Davis, Kathryn A. Conrad, Erin C. Litt, Brian |
author_facet | Ojemann, William K.S. Scheid, Brittany H. Mouchtaris, Sofia Lucas, Alfredo LaRocque, Joshua J. Aguila, Carlos Ashourvan, Arian Caciagli, Lorenzo Davis, Kathryn A. Conrad, Erin C. Litt, Brian |
author_sort | Ojemann, William K.S. |
collection | PubMed |
description | 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 disrupt 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 disrupt 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. |
format | Online Article Text |
id | pubmed-10350154 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-103501542023-07-17 Resting-state background features demonstrate multidien cycles in long-term EEG device recordings Ojemann, William K.S. Scheid, Brittany H. Mouchtaris, Sofia Lucas, Alfredo LaRocque, Joshua J. Aguila, Carlos Ashourvan, Arian Caciagli, Lorenzo Davis, Kathryn A. Conrad, Erin C. Litt, Brian medRxiv Article 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 disrupt 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 disrupt 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. Cold Spring Harbor Laboratory 2023-07-07 /pmc/articles/PMC10350154/ /pubmed/37461688 http://dx.doi.org/10.1101/2023.07.05.23291521 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Ojemann, William K.S. Scheid, Brittany H. Mouchtaris, Sofia Lucas, Alfredo LaRocque, Joshua J. Aguila, Carlos Ashourvan, Arian Caciagli, Lorenzo Davis, Kathryn A. Conrad, Erin C. Litt, Brian Resting-state background features demonstrate multidien cycles in long-term EEG device recordings |
title | Resting-state background features demonstrate multidien cycles in long-term EEG device recordings |
title_full | Resting-state background features demonstrate multidien cycles in long-term EEG device recordings |
title_fullStr | Resting-state background features demonstrate multidien cycles in long-term EEG device recordings |
title_full_unstemmed | Resting-state background features demonstrate multidien cycles in long-term EEG device recordings |
title_short | Resting-state background features demonstrate multidien cycles in long-term EEG device recordings |
title_sort | resting-state background features demonstrate multidien cycles in long-term eeg device recordings |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10350154/ https://www.ncbi.nlm.nih.gov/pubmed/37461688 http://dx.doi.org/10.1101/2023.07.05.23291521 |
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