Curriculum

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Descriptions

ES_APPM 370: Introduction to Computational Neuroscience

Description

From neurons to networks. Ion channels, Hodgkin-Huxley framework, simplified models, cable equation, synapses, spike-triggered average and optimal stimulus. Feed-forward and recurrent firing-rate networks. Statistical approach, Bayesian modeling. A brief introduction to numerical methods is given.

Recommended Texts:
1. Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems by Peter Dayan and L. F. Abbott (main book)
2. Mathematical Physiology by James Keener and James Sneyd
3. Mathematical Foundations of Neuroscience by G. Bard Ermentrout and David Terman