NEU 425 - Theory and computational models in neuroscience - FS16
The aims of this course are to introduce modeling techniques and issues, review successful models, and develop critical thinking about computational models and theories in neuroscience. We will study and experiment with simple models of single cells and small networks. We will then study some models of simple animal behaviors and conclude with more complex models for mammalian cognition. Students will learn and work in MATLAB and will make their own model of a specific dynamic process or behavior for a course project.
Topics covered include simple spiking neuron models; mean-field models; basics of network models in neuroscience; models of brain dynamics and rhythms; models of simple motor behaviors; models of cognitive function.
Time & Location: Tu & Thu, 2:40pm-4:00pm. 346 Giltner Hall.
Instructor: M. Reimers, 326 Giltner Hall.
Text: Pascal Wallisch et al, MATLAB for Neuroscientists, 2nd edition
- Students should have some calculus and feel comfortable with formulas and computers.