Synchronization measurement of multiple neuronal populations.
The purpose of the present paper is to develop a method, based on equal-time correlation, correlation matrix analysis and surrogate resampling, that is able to quantify and describe properties of synchronization of population neuronal activity recorded simultaneously from multiple sites. Initially, Lorenz-type oscillators were used to model multiple time series with different patterns of synchronization. Eigenvalue and eigenvector decomposition was then applied to identify "clusters" of locally synchronized activity and to calculate a "global synchronization index." This method was then applied to multichannel data recorded from an in vitro model of epileptic seizures. The results demonstrate that this novel method can be successfully used to analyze synchronization between multiple neuronal population series.
Li
Xiaoli
X
The Centre of Excellence for Research in Computational Intelligence and Applications, School of Computer Science, The University of Birmingham, Birmingham, UK. xiaoli.avh@gmail.com
Cui
Dong
D
Jiruska
Premysl
P
Fox
John E
JE
Yao
Xin
X
Jefferys
John G R
JG
D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004594:Electrophysiology; D008297:Male; D008564:Membrane Potentials / Q000502:physiology; D008959:Models, Neurological; D015233:Models, Statistical; D009474:Neurons / Q000502:physiology*; D051381:Rats; D017207:Rats, Sprague-Dawley; D012640:Seizures / Q000139:chemically induced / Q000503:physiopathology