9.29J / 8.261J Introduction to Computational Neuroscience, Spring 2002
Author(s)Seung, H. Sebastian
Introduction to Computational Neuroscience
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Mathematical introduction to neural coding and dynamics. Convolution, correlation, linear systems, Fourier analysis, signal detection theory, probability theory, and information theory. Applications to neural coding, focusing on the visual system. Hodgkin-Huxley and related models of neural excitability, stochastic models of ion channels, cable theory, and models of synaptic transmission.
neural coding, dynamics, convolution, correlation, linear systems, Fourier analysis, signal detection theory, probability theory, information theory, neural excitability, stochastic models, ion channels, cable theory, 9.29J, 8.261J, 9.29, 8.261