9.29J / 8.261J Introduction to Computational Neuroscience, Spring 2002
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 excitabi...
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| Format: | Learning Object |
| Language: | en-US |
| Published: |
2002
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| Online Access: | http://hdl.handle.net/1721.1/35859 |
| Summary: | 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. |
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