Chaotic and statistical analysis of multiple unit neuronal activities on the learning stimuli
S.Y. Cho, B.Y. Kim, Y.S. Jang, H.T. Kim · 2005
Summary form only given. We are to apply the chaotic features in the analysis of neuronal activity recorded from brain area involved in learning. Neural plasticity during learning is a major theme in the neurobiology of learning and memory. We recorded the multiple-unit activities at four brain sites that involve the classical conditioning of rabbits' nictitating membrane responses. The neuronal data were analyzed using chaotic features including the box-counting dimension, fractal dimension and central tendency, as well as statistical features. The chaotic characteristics represent the change of neuronal response by learning. Each index showed the change within a trial, the change across the training sessions, and the differences between the trials showing the learned responses and the trials not showing. The chaotic characteristics could be useful indices in the representation of the neural plasticity.