Submitted on August 29, 2007
Accepted on September 30, 2007
Synchronization Measurement of Multiple Neuronal Populations Based on Correlation Matrix Analysis
Xiaoli Li1*, Dong Cui2, Premysl Jiruska3, John E Fox4, Xin Yao, and John Gordon Ralph Jefferys5
1 Computer Science, University of Birmingham, Birmingham, United Kingdom
2 Institute of Electrical Engineering, Yanshan University, Qinhuangdao, China
3 Neurophysiology, Division of Neuroscience, University of Birmingham, Birmingham, United Kingdom
4 Neurophysiology, University of Birmingham, Birmingham, United Kingdom
5 Division of Neuroscience (Neurophysiology), University of Birmingham, The Medical School, Birmingham, United Kingdom
* To whom correspondence should be addressed. E-mail: xiaoli.avh{at}gmail.com.
The purpose of the present paper is to develop a method, based on equal-time correlation, correlation matrix analysis and surrogate resampling, which 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". Then this method was 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.
