Neuroscience Forum - View Single Post - Introduction to Computational Neuroscience

James · 02-20-2009, 11:31 PM

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

02-20-2009, 11:31 PM	#1 (permalink)
James Senior Member Join Date: Feb 2009 Posts: 769	Introduction to Computational Neuroscience - Free Course from MIT 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.