Computational Neuroscience

Computational Neuroscience

Introduction to Computational Neuroscience
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by Massachusetts Institute of Technology

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.



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Source: Massachusetts Institute of Technology

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Computational Neuroscience
Massachusetts Institute of Technology

Massachusetts Institute of Technology

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