Abstract
There is a wide variety of neuronal dynamics that are classified as seizures. This chapter poses the hypothesis that, as in any description of the physics of ensembles, the macroscopic phenomena of a seizure need to be characterized in terms of the interactions between the relevant neuronal subtypes taking part in this process. As in many non-biological pattern formation processes, persistently active states, including seizures, may depend on the interplay between inhibitory interneurons and excitatory principal (pyramidal) cells. The chapter discusses the characteristics of synchronization between interneurons and pyramidal cells in hippocampal seizures, using techniques to extract input synaptic currents from the output spikes recorded during intracellular recordings. It also describes strategies to minimize the effect of spurious correlations due to shared frequencies and finite data sample lengths. Thereafter, it contrasts these findings with the synchronization characteristics from human seizures and shows how an adaptation of canonical linear discrimination can be used with metrics of synchrony features. Furthermore, it describes how interneuron depolarization block may be an integral component in orchestrating the time course of seizures and how gap junction connectivity may synchronize such depolarization block among interneurons. Searching for the universality that might underlie the variety of seizure dynamics in human epilepsy remains an important open challenge.
Original language | English (US) |
---|---|
Title of host publication | Computational Neuroscience in Epilepsy |
Publisher | Elsevier Inc. |
Pages | 496-512 |
Number of pages | 17 |
ISBN (Print) | 9780123736499 |
DOIs | |
State | Published - 2008 |
All Science Journal Classification (ASJC) codes
- General Neuroscience