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(Complete Item Description)
- 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.
- Subject:
- Science and Technology
- Grade Level:
- Post-secondary
- Collection:
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MIT OpenCourseWare
Remix and Share
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(Complete Item Description)
- Abstract:
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. Visit the Seung Lab Web site.
- Subject:
- Science and Technology
- Grade Level:
- Post-secondary
- Collection:
-
MIT OpenCourseWare
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