Estimations of neural networks by fluctuations of neuron spikes

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It has become possible to make simultaneous measurements of neural activity (spikes) in large numbers of neurons with large arrays of electrodes. Significant advantage of the statistical mechanical informatics (SMI) is to extract a macroscopic description of the system with a small number of parameters by performing reduction of many microscopic degrees of freedom. Hierarchy, reduction, and macroscopic description should also be essential in order to understand the brain. From this point of view, we proposed new SMI frameworks for neural network models, and methods for analyzing neuronal spike data based on the information theory and the Bayesian inference.