Abstract
The human brain has the capacity to rapidly change state, and in epilepsy these state changes can be catastrophic, resulting in loss of consciousness, injury and even death. Using long-term intracranial electroencephalography (iEEG) recordings from fourteen patients with focal epilepsy, key signatures of critical slowing down prior to seizures was monitored.
Seizure risk was associated with a combination of these signals together with epileptiform discharges. These results provide strong validation of theoretical models and demonstrate that critical slowing down is a reliable indicator that could be used in seizure forecasting algorithms.
Authors
Matias I. Maturana, Christian Meisel, Katrina Dell, Philippa J. Karoly, Wendyl D’Souza, David B. Grayden, Anthony N. Burkitt, Premysl Jiruska, Jan Kudlacek, Jaroslav Hlinka, Mark J. Cook, Levin Kuhlmann & Dean R. Freestone
Mathematical models of brain activity, such as critical slowing, can be used to understand seizure cycles and to improve forecasting accuracy. The combination of theory and applied signal processing in this research form the best forecasting results to date.