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#1 (permalink) |
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Senior Member
Join Date: Feb 2009
Posts: 769
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This course gives a mathematical introduction to neural coding and dynamics. Topics include convolution, correlation, linear systems, game theory, signal detection theory, probability theory, information theory, and reinforcement learning. Applications to neural coding, focusing on the visual system are covered, as well as Hodgkin-Huxley and other related models of neural excitability, stochastic models of ion channels, cable theory, and models of synaptic transmission.
MIT OpenCourseWare | Brain and Cognitive Sciences | 9.29J Introduction to Computational Neuroscience, Spring 2004 | Download this Course Last edited by James; 10-01-2009 at 12:05 AM. |
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#2 (permalink) |
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Junior Member
Join Date: Jun 2009
Location: India
Posts: 2
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Hi James,
There is nothing much about "stochastic models of ion channels" in this course material. I am a Graduate Programs and looking for a good material in stochastic models of ion channels. Can u suggest me something. |
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