Controlling synchronization in a neuron-level population model

被引:56
作者
Chakravarthy, Niranjan
Sabesan, Shivkumar
Iasemidis, Leon
Tsakalis, Kostas [1 ]
机构
[1] Arizona State Univ, Dept Elect Engn, Tempe, AZ 85287 USA
[2] Arizona State Univ, Harrington Dept Bioengn, Tempe, AZ 85287 USA
基金
美国国家科学基金会;
关键词
epileptic seizures; neural synchronization; computational neurophysiological model; feedback control;
D O I
10.1142/S0129065707000993
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We have studied coupled neural populations in an effort to understand basic mechanisms that maintain their normal synchronization level despite changes in the inter-population coupling levels. Towards this goal, we have incorporated coupling and internal feedback structures in a neuron-level population model from the literature. We study two forms of internal feedback - regulation of excitation, and compensation of excessive excitation with inhibition. We show that normal feedback actions quickly regulate/compensate an abnormally high coupling between the neural populations, whereas a pathology in these feedback actions can lead to abnormal synchronization and "seizure"-like high amplitude oscillations. We then develop an external control paradigm, termed feedback decoupling, as a robust synchronization control strategy. The external feedback decoupling controller acts to achieve the operational objective of maintaining normal-level synchronous behavior irrespective of the pathology in the internal feedback mechanisms. Results from such an analysis have an interesting physical interpretation and specific implications for the treatment of diseases such as epilepsy. The proposed remedy is consistent with a variety of recent observations in the human and animal epileptic brain, and with theories from nonlinear systems, adaptive systems, optimization, and neurophysiology.
引用
收藏
页码:123 / 138
页数:16
相关论文
共 44 条
[1]  
Astrom K. J., 1989, Proceedings of the 1989 American Control Conference (Cat. No.89CH2772-2), P1693
[2]  
Astrom K. J., 1995, PID CONTROLLERS THEO
[3]  
CHAKRAVARTHY N, 2007, THESIS ARIZONA STATE
[4]   Intracellular and computational characterization of the intracortical inhibitory control of synchronized thalamic inputs in vivo [J].
Contreras, D ;
Destexhe, A ;
Steriade, M .
JOURNAL OF NEUROPHYSIOLOGY, 1997, 78 (01) :335-350
[5]   Epilepsies as dynamical diseases of brain systems: Basic models of the transition between normal and epileptic activity [J].
da Silva, FL ;
Blanes, W ;
Kalitzin, SN ;
Parra, J ;
Suffczynski, P ;
Velis, DN .
EPILEPSIA, 2003, 44 :72-83
[6]   A neural mass model for MEG/EEG: coupling and neuronal dynamics [J].
David, O ;
Friston, KJ .
NEUROIMAGE, 2003, 20 (03) :1743-1755
[7]  
DESTEXHE A, 2001, THALAMOCORTICAL ASSE
[8]   Suppression and control of epileptiform activity by electrical stimulation: A review [J].
Durand, DM ;
Bikson, M .
PROCEEDINGS OF THE IEEE, 2001, 89 (07) :1065-1082
[9]   SIMULATION OF CHAOTIC EEG PATTERNS WITH A DYNAMIC-MODEL OF THE OLFACTORY SYSTEM [J].
FREEMAN, WJ .
BIOLOGICAL CYBERNETICS, 1987, 56 (2-3) :139-150
[10]   Epileptiform activity in a neocortical network: a mathematical model [J].
Giannakopoulos, F ;
Bihler, U ;
Hauptmann, C ;
Luhmann, HJ .
BIOLOGICAL CYBERNETICS, 2001, 85 (04) :257-268