Fluctuations in EEG band power at subject‐specific timescales over minutes to days explain changes in seizure evolutions - Panagiotopoulou, Mariella; Papasavvas, Christoforos A.; Schroeder, Gabrielle M.; Thomas, Rhys H.; Taylor, Peter N.; Wang, Yujiang (Human brain mapping, 2022)
Epilepsy is recognised as a dynamic disease, where both seizure susceptibility and seizure characteristics themselves change over time. Specifically, we recently quantified the variable electrographic spatio‐temporal seizure evolutions that exist within individual patients. This variability appears to follow subject‐specific circadian, or longer, timescale modulations. It is therefore important to know whether continuously recorded interictaliEEG features can capture signatures of these modulations over different timescales. In this study, we analyse continuous intracranial electroencephalographic (iEEG) recordings from video‐telemetry units and find fluctuations in iEEG band power over timescales ranging from minutes up to 12 days. As expected and in agreement with previous studies, we find that all subjects show a circadian fluctuation in their iEEG band power. We additionally detect other fluctuations of similar magnitude on subject‐specific timescales. Importantly, we find that a combination of these fluctuations on different timescales can explain changes in seizure evolutions in most subjects above chance level. These results suggest that subject‐specific fluctuations in iEEG band power over timescales of minutes to days may serve as markers of seizure modulating processes. We hope that future study can link these detected fluctuations to their biological driver(s). There is a critical need to better understand seizure modulating processes, as this will enable the development of novel treatment strategies that could minimise the seizure spread, duration or severity and therefore the clinical impact of seizures. Epileptic seizures change over time and have been shown to be modulated on circadian or longer timescales. It is an open question whether these changes can be explained by intrinsic fluctuations of each individual patient's physiology. We hypothesize that signal features derived from the continuous iEEG can serve as biomarkers of such intrinsic fluctuations. We find that a combination of iEEG marker fluctuations on different timescales can explain changes in seizure evolutions in most subjects above chance level.