Human seizures couple across spatial scales through travelling wave dynamics
Note about supplementary videos: Each video frame is divided in two columns, with recordings from the ECoG on the left and recordings from the MEA on the right. For both columns, the top panels show the recorded voltages mapped over the position of the electrodes (cool colors represent negative voltages, while warm colors represent positive voltages). The labels A/B/C/D/E/F and a/b/c/d/e/f indicate the electrodes for which the detailed voltages are displayed on the bottom panels for ECoG and MEA, respectively. The red cross on the brain surface is the position of the center of the MEA. The MEA is tilted to represent its orientation with respect to the ECoG grid. Within each recording type (i.e., ECoG on the left and MEA on the right), bottom panels are divided into two plots that represent the voltages of the same channels but at different time scales (left: full seizure duration with 60 s of pre- and post-ictal data; right: moving window of 500 ms centered on the time of the current frame indicated by the green line on both plots). The red bar represents seizure onset.
Citation (published version)Louis-Emmanuel Martinet, Grant Fiddyment, Joseph Madsen, Emad Eskandar, Wilson Truccolo, Uri Eden, Sydney Cash, M Kramer. 2017. "Human seizures couple across spatial scales through travelling wave dynamics." Nature Communications, Volume 8, Issue 14896, pp. 1 - 13.
Epilepsy—the propensity toward recurrent, unprovoked seizures—is a devastating disease affecting 65 million people worldwide. Understanding and treating this disease remains a challenge, as seizures manifest through mechanisms and features that span spatial and temporal scales. Here we address this challenge through the analysis and modelling of human brain voltage activity recorded simultaneously across microscopic and macroscopic spatial scales. We show that during seizure large-scale neural populations spanning centimetres of cortex coordinate with small neural groups spanning cortical columns, and provide evidence that rapidly propagating waves of activity underlie this increased inter-scale coupling. We develop a corresponding computational model to propose specific mechanisms—namely, the effects of an increased extracellular potassium concentration diffusing in space—that support the observed spatiotemporal dynamics. Understanding the multi-scale, spatiotemporal dynamics of human seizures—and connecting these dynamics to specific biological mechanisms—promises new insights to treat this devastating disease.
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