Showing papers on "Hidden Markov model published in 1972"

Markov Process of Maintained Impulse Activity in Central Single Neurons

Abstract: To clarify the stochast properties of the maintained impulse activity of the central nervous system, we proposed a measure of statistical dependency on the basis of Shannon's entropy. This measure could provide the Markov properties of the neural impulse sequences, representing the necessary and sufficient condition for the statistical dependence. The order of Markov process of the sequence is determined by the conditional entropy which is derived from the joint entropy. Here the joint entropy in the case of Gaussian process is directly related with the covariance matrix which is substituted for the matrix of the serial correlation coefficients. Therefore the condition to determine the order of Markov process is obtained by the equation of the matrices of the serial correlation coefficients. The order of Markov process of the neural impulse sequences recorded from the mesencephalic reticular formation (MRF), red nucleus (RN), and lateral geniculate nucleus (LGN) neurons has been estimated. The maintained impulse activity of the MRF and RN neurons had from the 2-nd to 4-th order Markov property, while that of the LGN had no Markov property, in the consecutive impulse sequences.