TY - JOUR
T1 - Control of synchronization of brain dynamics leads to control of epileptic seizures in rodents
AU - Good, Levi B.
AU - Sabesan, Shivkumar
AU - Marsh, Steven T.
AU - Tsakalis, Konstantinos
AU - Treiman, David
AU - Iasemidis, Leon
N1 - Funding Information:
We would like to thank Victor Baidoon and Alexander Drachev of EEGsoft Inc. for their effort to make the JIT system operate in real-time. We would also like to thank the 7 anonymous reviewers for their constructive comments and suggestions. Support for this study has been provided in part by the National Institute of Health EB002089 BRP grant on Brain Dynamics, the Barrow Neurological Foundation, the Epilepsy Research Foundation of America and Ali Paris Fund for LKS Research, the National Science Foundation grant No. 0601740, and the Science Foundation Arizona (Competitive Advantage Award CAA 0281-08).
PY - 2009/6
Y1 - 2009/6
N2 - We have designed and implemented an automated, just-in-time stimulation, seizure control method using a seizure prediction method from nonlinear dynamics coupled with deep brain stimulation in the centromedial thalamic nuclei in epileptic rats. A comparison to periodic stimulation, with identical stimulation parameters, was also performed. The two schemes were compared in terms of their efficacy in control of seizures, as well as their effect on synchronization of brain dynamics. The automated just-in-time (JIT) stimulation showed reduction of seizure frequency and duration in 5 of the 6 rats, with significant reduction of seizure frequency (>50%) in 33% of the rats. This constituted a significant improvement over the efficacy of the periodic control scheme in the same animals. Actually, periodic stimulation showed an increase of seizure frequency in 50% of the rats, reduction of seizure frequency in 3 rats and significant reduction in 1 rat. Importantly, successful seizure control was highly correlated with desynchronization of brain dynamics. This study provides initial evidence for the use of closed-loop feedback control systems in epileptic seizures combining methods from seizure prediction and deep brain stimulation.
AB - We have designed and implemented an automated, just-in-time stimulation, seizure control method using a seizure prediction method from nonlinear dynamics coupled with deep brain stimulation in the centromedial thalamic nuclei in epileptic rats. A comparison to periodic stimulation, with identical stimulation parameters, was also performed. The two schemes were compared in terms of their efficacy in control of seizures, as well as their effect on synchronization of brain dynamics. The automated just-in-time (JIT) stimulation showed reduction of seizure frequency and duration in 5 of the 6 rats, with significant reduction of seizure frequency (>50%) in 33% of the rats. This constituted a significant improvement over the efficacy of the periodic control scheme in the same animals. Actually, periodic stimulation showed an increase of seizure frequency in 50% of the rats, reduction of seizure frequency in 3 rats and significant reduction in 1 rat. Importantly, successful seizure control was highly correlated with desynchronization of brain dynamics. This study provides initial evidence for the use of closed-loop feedback control systems in epileptic seizures combining methods from seizure prediction and deep brain stimulation.
KW - Control
KW - Deep brain stimulation
KW - Nonlinear
KW - Prediction
KW - Seizure
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U2 - 10.1142/S0129065709001951
DO - 10.1142/S0129065709001951
M3 - Article
C2 - 19575507
AN - SCOPUS:68149180516
SN - 0129-0657
VL - 19
SP - 173
EP - 196
JO - International Journal of Neural Systems
JF - International Journal of Neural Systems
IS - 3
ER -