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9.29J / 8.261J Introduction to Computational Neuroscience, Spring 2002

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Author(s)
Seung, H. Sebastian
Alternative Title
Introduction to Computational Neuroscience
Date Issued
June 2002
Abstract
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.
Subjects
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
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology. Department of Physics
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