|M.Sc Student||Khoury Iman|
|Subject||Reorgenization of the CA1 Hippocampal Network in the|
Chronic Kainate Model of Epilepsy
|Department||Department of Medicine||Supervisor||Professor Yitzhak Schiller|
|Full Thesis text|
Epilepsy is a common neurological disorder characterized by recurrent unprovoked seizures caused by various pathologic processes in the brain. When studying epilepsy one must distinguish between two fundamentally different processes: epileptogenesis which describes the process in which a normal brain develops susceptibility to seizure generation, and ictogenesis which is the process of initiation and maintenance of seizures in the epileptic brain.
The current treatment of epilepsy is based on the suppression of symptoms (seizures) by antiepileptic drugs (AEDs). However, the biggest clinical problem in epilepsy field is the inability to control seizures in 30% of epileptic patients due to drug resistance. One of the most promising potential treatments for drug resistant epilepsy is using closed loop neurostimulation which is planned to detect pre- ictal state preceding clinical seizures, and automatically generate appropriate stimulation to abort impending seizures and prevent initiation of full- blown clinical seizures. Nonetheless, the ideal solution for epilepsy will be preventing epileptogenesis (disease modifying therapy). So far, there are no treatments that modify the disease process in patients with a known increased risk of epilepsy due to genetic predisposition or a history of acquired brain injury, or in patients with a progressive course of epilepsy. Several studies have been concentrating on developing treatments to prevent epileptogenesis. The development of such anti-epileptogenesis treatment will be based on the specific abnormal neuronal reorganization characterizing epileptogenesis. Here lies the huge importance of understanding the neural changes and network dynamics leading to epileptogenesis.
One of the potential mechanisms that may underlie development of epilepsy (epileptogenesis) is reorganization of the network and change in the network topology, that in turn causes an increased tendency of the network to develop hyper-active and hyper-synchronized activity. In this study we investigated this possibility by comparing the functional network characteristics and network topology in control and epileptic rats.
We simultaneously recorded action potential firing from multiple neurons from the CA1 region of the hippocampus using multi-tetrode single-unit recordings from control rats (Sprague Dawley) and rats with chronic kainate induced temporal lobe epilepsy, in which spontaneous seizures developed after a kainate induced status epilepticus (SE). We used the multi-tetrode single-unit recordings, and especially the pair-wise cross correlations between recorded neurons to compare network synchronization, functional network properties and topology in normal and epileptic rats.
The main findings of this study were that the epileptic network undergoes reorganization with a higher functional connectivity and increased synchronization compared to control animals. These network changes may underlie the tendency to generate seizures in these rats. The main novelty of this study is implementation of graph theory based network analysis using single unit recording in temporal lobe epilepsy . We used graph theory tools to calculate the network properties including synchrony and connectivity. Whereas previous studies that dealt with characterizing epileptic network used MRI and fMRI. Therefore, the spatial resolution of MRI limits the study to macro network and not to local micro networks at the single cell level.