DocumentCode :
902613
Title :
Dynamical resetting of the human brain at epileptic seizures: application of nonlinear dynamics and global optimization techniques
Author :
Iasemidis, Leon D. ; Shiau, Deng-Shan ; Sackellares, J. Chris ; Pardalos, Panos M. ; Prasad, Awadhesh
Author_Institution :
Harrington Dept. of Bioeng., Arizona State Univ., Tempe, AZ, USA
Volume :
51
Issue :
3
fYear :
2004
fDate :
3/1/2004 12:00:00 AM
Firstpage :
493
Lastpage :
506
Abstract :
Epileptic seizures occur intermittently as a result of complex dynamical interactions among many regions of the brain. By applying signal processing techniques from the theory of nonlinear dynamics and global optimization to the analysis of long-term (3.6 to 12 days) continuous multichannel electroencephalographic recordings from four epileptic patients, we present evidence that epileptic seizures appear to serve as dynamical resetting mechanisms of the brain, that is the dynamically entrained brain areas before seizures disentrain faster and more frequently (p<0.05) at epileptic seizures than any other periods. We expect these results to shed light into the mechanisms of epileptogenesis, seizure intervention and control, as well as into investigations of intermittent spatiotemporal state transitions in other complex biological and physical systems.
Keywords :
Lyapunov methods; diseases; electroencephalography; medical signal processing; neurophysiology; nonlinear dynamical systems; spatiotemporal phenomena; 3.6 to 12 day; dynamical resetting mechanisms; electroencephalographic recordings; epileptic seizures; epileptogenesis; global optimization; human brain; nonlinear dynamics; signal processing techniques; spatiotemporal state transitions; Biomedical engineering; Biomedical imaging; Biomedical signal processing; Brain; Cerebral cortex; Epilepsy; Humans; Neurons; Neuroscience; Spatiotemporal phenomena; Adaptation, Physiological; Algorithms; Brain; Brain Mapping; Computer Simulation; Diagnosis, Computer-Assisted; Electroencephalography; Epilepsy; Humans; Models, Neurological; Nonlinear Dynamics; Signal Processing, Computer-Assisted; Stochastic Processes;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2003.821013
Filename :
1268219
Link To Document :
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