EIS503C
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EIS503C - Introduction to Computational Neuroscience
Course ID
028670
Course Description
This course covers the basic simulation techniques for biophysical modeling. Topics include: single and multi compartmental models, intrinsic neuron properties and dendritic integration and large networks of biophysical neurons with realistic stochastic synaptic transmission. Graduate-level requirements include a term project, including hands on simulation and research-level literature searches. Projects will include the analyses of real data.
Min Units
3
Max Units
3
Repeatable for Credit
No
Grading Basis
GRD - Regular Grades A, B, C, D, E
Career
Graduate
Course Attributes
CE - CL (Cross Listed), GIDP - EIS (Entomology & Insect Science)
Course Requisites
Cross Listed Courses
May be convened with
Component
Lecture
Optional Component
No