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

Seung, H. Sebastian

Author(s)

Seung, H. Sebastian

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Alternative title

Introduction to Computational Neuroscience

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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.

Date issued

2002-06

URI

http://hdl.handle.net/1721.1/35859

Department

Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences; Massachusetts Institute of Technology. Department of Physics

Other identifiers

9.29J-Spring2002

local: 9.29J

local: 8.261J

local: IMSCP-MD5-871dd32a126b2a044a2605ea539dd83e

Keywords

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

Collections

MIT OCW Archived Courses