About the Course
This course will introduce the concepts of computational
and theoretical neuroscience. It will cover (1) general principles
of theoretical neuroscience, including distributed representations
and information theory, (2) methods for single-cell modeling,
including compartmental and integrate-and-fire models, (3)
learning rules, including supervised, unsupervised, and reinforcement
learning models, and (4) specific systems models, taken from
the current theoretical neuroscience literature. Class time
will be divided between lecture and discussion. Readings each
week will be taken from the current scientific literature.
The class is designed for graduate students and for advanced
undergraduates. |
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Announcements
This course fulfills the electives Category B (Neural Systems
and Behavior) for undergraduate neuroscience major. For more
information on the degree see the Neuroscience
Major Requirements.
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