Seizure forecasting: where do we stand?

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• dc.contributor.author Andrzejak, Ralph Gregor
• dc.contributor.author Zaveri, Hitten P.
• dc.contributor.author Schulze-Bonhage, Andreas
• dc.contributor.author Leguia, Marc G.
• dc.contributor.author Stacey, William C.
• dc.contributor.author Richardson, Mark P.
• dc.contributor.author Kuhlmann, Levin
• dc.contributor.author Lehnertz, Klaus
• dc.date.accessioned 2023-06-30T06:45:13Z
• dc.date.available 2023-06-30T06:45:13Z
• dc.date.issued 2023
• dc.description.abstract A lot of mileage has been made recently on the long and winding road toward seizure forecasting. Here we briefly review some selected milestones passed along the way, which were discussed at the International Conference for Technology and Analysis of Seizures—ICTALS 2022—convened at the University of Bern, Switzerland. Major impetus was gained recently from wearable and implantable devices that record not only electroencephalography, but also data on motor behavior, acoustic signals, and various signals of the autonomic nervous system. This multimodal monitoring can be performed for ultralong timescales covering months or years. Accordingly, features and metrics extracted from these data now assess seizure dynamics with a greater degree of completeness. Most prominently, this has allowed the confirmation of the long-suspected cyclical nature of interictal epileptiform activity, seizure risk, and seizures. The timescales cover daily, multi-day, and yearly cycles. Progress has also been fueled by approaches originating from the interdisciplinary field of network science. Considering epilepsy as a large-scale network disorder yielded novel perspectives on the pre-ictal dynamics of the evolving epileptic brain. In addition to discrete predictions that a seizure will take place in a specified prediction horizon, the community broadened the scope to probabilistic forecasts of a seizure risk evolving continuously in time. This shift of gears triggered the incorporation of additional metrics to quantify the performance of forecasting algorithms, which should be compared to the chance performance of constrained stochastic null models. An imminent task of utmost importance is to find optimal ways to communicate the output of seizure-forecasting algorithms to patients, caretakers, and clinicians, so that they can have socioeconomic impact and improve patients' well-being.
• dc.description.sponsorship Epilepsy Foundation, Epilepsy Innovation Institute My Seizure Gauge; Medical Research Council Centre for Neurodevelopmental Disorders, Grant/ Award Number: Ref MR/N026063/1; National Health and Medical Research Council, Grant/Award Number: GNT1160815 and GNT1183119; National Institutes of Health, Grant/ Award Number: NIH NS094399 and NIH NS109062; Spanish Ministry of Science and Innovation and the State Research Agency, Grant/Award Number: PID2020-118196GBI00/ MICIN/AEI/10.13039/50110001103; Swebilius Foundation.; University of Bern, the Inselspital, University Hospital Bern, the Alliance for Epilepsy Research, the Swiss National Science Foundation, UCB, FHC, the Wyss Center for bio- and neuro-engineering, the American Epilepsy Society (AES), the CURE epilepsy Foundation, Ripple neuro, Sintetica, DIXI medical, UNEEG medical and NeuroPace.
• dc.format.mimetype application/pdf
• dc.identifier.citation Andrzejak RG, Zaveri HP, Schulze-Bonhage A, Leguia MG, Stacey WC, Richardson MP, Kuhlmann L, Lehnertz K. Seizure forecasting: where do we stand?. Epilepsia. 2023;64(S3):S62-71. DOI: 10.1111/epi.17546
• dc.identifier.doi http://dx.doi.org/10.1111/epi.17546
• dc.identifier.issn 0013-9580
• dc.identifier.uri http://hdl.handle.net/10230/57419
• dc.language.iso eng
• dc.publisher Wiley
• dc.relation.ispartof Epilepsia. 2023;64(S3):S62-71.
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2020-118196GBI00
• dc.rights © 2023 The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword monitoring devices
• dc.subject.keyword multimodal monitoring
• dc.subject.keyword network theory of epilepsy
• dc.subject.keyword quality of life
• dc.subject.keyword seizure control
• dc.subject.keyword seizure cycles
• dc.subject.keyword seizure prediction
• dc.subject.keyword seizure risk
• dc.subject.keyword wearables
• dc.title Seizure forecasting: where do we stand?
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion