The use of chaos control techniques to manipulate epileptiform bursting in rat hippocampus

D. J. Mogul*, Marc W Slutzky

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

Epilepsy afflicts between 1-2% of the world's population, yet many epileptic patients are not sufficiently helped by current pharmacological therapies. For these patients in whom the seizures are severe of frequent enough, surgical ablation of brain tissue is commonly performed to reduce or eliminate seizures. Recent reports have suggested that chaos control techniques may be useful for electrically manipulating epileptiform bursting behavior thereby obviating the need in some cases for difficult and potentially damaging surgery. We implemented chaos control of spontaneous bursting in the rat hippocampal slice using robust control techniques. We employed the stable manifold placement (SMP) method in which the system state is manipulated onto the stable manifold by exogenous stimulation. This then permits the bursting to evolve towards the attractor using the natural system dynamics to maintain approximate periodic bursting. An adaptive tracking algorithm was applied to overcome nonstationarity in system characteristics. Adaptive tracking improved control efficacy over basis SMP control. Thus, it may be feasible to use chaos control techniques to manipulate the aberrant neuronal electrical activity characteristic of epilepsy.

Original languageEnglish (US)
Pages (from-to)2023-2024
Number of pages2
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume3
StatePublished - Dec 1 2002
EventProceedings of the 2002 IEEE Engineering in Medicine and Biology 24th Annual Conference and the 2002 Fall Meeting of the Biomedical Engineering Society (BMES / EMBS) - Houston, TX, United States
Duration: Oct 23 2002Oct 26 2002

Keywords

  • Brain
  • Epilepsy
  • Neuroengineering

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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