Epilepsy remains a devastating and poorly understood illness whose therapies are inadequate for many patients and, in large degree, unchanged for decades. The experiments proposed in this project utilize novel microelectrode recording techniques in patients with epilepsy as well as quantitative features and large data sets to obtain information about the neuronal dynamics underlying epilepsy at an unprecedented level of resolution. The primary hypothesis of this project is that this high resolution, multi-scale information can be applied to separate seizures into different classes which differ in the mechanisms which underlie seizure initiation. More specifically, we will be examining the role and interplay of widespread networks, different cortical layers, infraslow activity and both excitatory and inhibitory single neuronal activity as seizures start. We expect to find substantial differences in these different features of neural action in different kinds of seizures. This knowledge will foster the development of a more complete understanding of seizures and how they can be better detected, predicted and ultimately controlled.
The experiments proposed in this project utilize novel microelectrode recording techniques as well as automatic clustering approaches based on quantitative features and large data sets to obtain information about the neuronal dynamics underlying epilepsy at an unprecedented level of resolution. We hope to use these assessments to better understand multiscale neurophysiological processes and demonstrate that there are different types of seizures which have contrasting mechanisms underlying their initiation. This knowledge will foster the development of a more complete understanding of the seizure and how it can be better detected, predicted and treated.
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