NEUR 735: Computational Neuroscience Systems

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Course Information from the University Catalog

Credits: 3

Intensive introduction to systems neuroscience from quantitative perspective. Covers computational techniques used to study function of networks of neurons. Uses spike train statistics, neural encoding, and information theory to investigate behaviors that emerge from integrated actions of networks of neurons. May not be repeated for credit.
Recommended Prerequisite: NEUR 734 or permission of instructor.
Registration Restrictions:

Enrollment is limited to Graduate or Non-Degree level students.

Students in a Non-Degree Undergraduate degree may not enroll.

Schedule Type: Lecture
Grading:
This course is graded on the Graduate Regular scale.

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