Computational Neuroscience: From Channels to Networks Sample Syllabus
Description:
Brain function is ultimately determined by ion channels that generate neuronal firing and by the synapses that allow information transfer between neurons in a network. To facilitate analyses of this extremely complex process, neuroscientists often use computer simulations to make predictions, design experiments, and importantly, to improve their intuition. In this course, students will build a network from the ground up. Using simulations, students will examine how ion channels affect the firing of neurons, how synapses control information flow, how neural networks generate complex firing patterns, and how memory is stored. ‘Skeleton’ programs will be provided by the instructor, which the student can easily modify to explore the various processes that affect function.
Prerequisites: Co- or pre-requisite: Cellular and Molecular Neurobiology or by permission of the instructor. No programming experience is necessary. Students will be taught basic programming techniques in Matlab when needed.
Required Materials: Molecular and Cellular Physiology of Neurons; chapters available for free at http://www.degruyter.com/viewbooktoc/product/430001 MatLab (License available for free through NYU)
Grading: 20% will be based on weekly homework assignments; 20% on project proposal (oral presentation); 50% on project (written & oral); and 10% on class participation. For the projects, students will formulate and then test their hypotheses by performing simulations.
Course Organization: Class meets once a week for 2 hours. The first hour will be a discussion of the assigned material. The second hour will be devoted to performing simulations.
Learning Goals: Upon completion of the course, students will be able to use computer simulations to explore cellular and network function.