Conference proceeding
Closed-Loop Seizure Prediction and Prevention in Rats with Kainate-Induced Seizures
2011 5TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING (NER), pp 426-429
01 Jan 2011
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Many studies have shown that continuous or intermittent electrical stimulation of the brain can reduce or prevent the occurrence of epileptic seizures in humans and animal models. However, there have been relatively few studies that assess the effects of stimulation delivered just prior to seizure onset. Here we use a kainate-induced seizure model in the rat to test a closed-loop seizure prediction and prevention system. An algorithm was created that extracts a measure from the activity of populations of single neurons, and predicts the probability of a seizure in real time. Once a seizure is predicted, high frequency current pulses are applied to the hippocampus to attempt to inhibit the network and prevent the seizure from occurring. Results show that although not every seizure could be prevented, the majority of stimulation trials delayed or prevented a pending seizure. These results suggest that a closed-loop seizure prediction algorithm based on neuronal activity coupled with intracranial stimulation may be more effective than random stimulation at preventing the onset of seizures.
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Details
- Title
- Closed-Loop Seizure Prediction and Prevention in Rats with Kainate-Induced Seizures
- Creators
- Dane W. Grasse - Drexel UniversitySuganya Karunakaran - Drexel UniversityKaren A. Moxon - Drexel UniversityIEEE
- Publication Details
- 2011 5TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING (NER), pp 426-429
- Series
- International IEEE EMBS Conference on Neural Engineering
- Publisher
- IEEE
- Number of pages
- 4
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000298735800101
- Scopus ID
- 2-s2.0-79960347284
- Other Identifier
- 991019170321304721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Engineering, Biomedical
- Neurosciences