Computational Neuroscience and Computing Networks
An Introduction to the biophysics of nerve cells and synapses, the mathematical description of neural networks, and how neurons represent information. Course will survey computational modeling and data analysis methods for neuroscience. Topics will include representation of visual information, spatial navigation, short-term memory, and decision-making. Two 90-minute lectures, one laboratory. Lectures in common with MOL 437. Graduate students will carry out and write up an in-depth semester-long project.
Sample reading list:
Dayan, P. and Abbott, L., Theoretical Neuroscience
Ballard, D.H., Introduction to Natural Computation
Kandel, E., Schwartz, J. and Jessell, T., Principles of Neural Science
Problem sets, oral presentations, and a project paper.
|41318||L01||3:00 pm - 4:20 pm||T Th||Enrolled:0 Limit:0||Canceled|
|41319||B01||7:30 pm - 10:20 pm||W||Enrolled:0 Limit:0||Canceled|