摘要：SummaryA range of abnormal electrical activity patterns termed epileptiform discharges can occur in the brains of persons with epilepsy. These epileptiform discharges can be monitored and recorded with implanted devices that deliver therapeutic neurostimulation. These continuous recordings provide an opportunity to study the behavioral correlates of epileptiform discharges as the patients go about their daily lives. Here, we captured the smartphone touchscreen interactions in eight patients in conjunction with electrographic recordings (accumulating 35,714 h) and by using an artificial neural network model addressed if the behavior reflected the epileptiform discharges. The personalized model outputs based on smartphone behavioral inputs corresponded well with the observed electrographic data (R: 0.2–0.6, median 0.4). The realistic reconstructions of epileptiform activity based on smartphone use demonstrate how day-to-day digital behavior may be converted to personalized markers of disease activity in epilepsyGraphical abstractDisplay OmittedHighlights•Brain implants can continuously log abnormal activity patterns in epilepsy.•Real-world behavioral implications of the abnormal activity are not clear.•An artificial neural network inferred brain activity based on smartphone behavior.•Diurnal and other behavioral patterns were leveraged by the network.Behavioral neuroscience; Bioengineering; Neural networks
