Students may choose two or more from the following four courses.

Register for these courses in WEBSTAC. Full description and course history can be found on the WashU Course listings website (WUCRSL).

BME 572:  Biological Neural Computation
(Spring course)

Course Master: Barani Raman (BME)

Description: This course will consider the computations performed by the biological nervous system with a particular focus on neural circuits and population-level encoding/decoding. Topics include, Hodgkin-Huxley equations, phase-plane analysis, reduction of Hodgkin-Huxley equations, models of neural circuits, plasticity and learning, and pattern recognition & machine learning algorithms for analyzing neural data. Note: Graduate students in psychology or neuroscience who are in the Cognitive, Computational, and Systems Neuroscience curriculum pathway may register in L41 5657 for three credits. For non-BME majors, conceptual understanding, and selection/application of right neural data analysis technique will be stressed. Hence homework assignments/examinations for the two sections will be different, however all students are required to participate in a semester long independent project as part of the course. Calculus, Differential Equations, Basic Probability and Linear Algebra Undergraduates need permission of the instructor. L41 5657 prerequisites: Permission from the instructor

ESE 5xx:  Machine Learning & Optimization in Analysis & Modeling of Neural Circuits
(Spring course)

Course Masters: Team taught

Description: Check back for course description.

BME 5501: Translational Neuroengineering
(Spring course)

Course Master: Dan Moran (BME)

Description: This course focuses on the design of bioelectric devices for use in clinical patients. Neural stimulators (e.g. deep brain, vagal) will be the basis for a case-study approach to designing and developing new bioelectrical medical devices. This project-based course will introduce the student to the use of finite element solvers to design novel stimulators. In addition to the engineering design aspects, issues such as product liability, FDA approval, etc. will be discussed

BME 474:  Open Challenges in Systems Neuroscience

Course Master: Dennis Barbour (BME)

Description: The objective of this course is to introduce advanced graduate engineering students to key challenges for the next generation of systems neuroscientists. One-half of the course will introduce students to the neural bases of canonical behavioral motifs following the text of 23 Problems in Systems Neuroscience. One-half of the course will have students identify and present a proposal for how to study an open challenge in the treatment of neurological/psychiatric disorders (e.g., dystonia, epilepsy, depression, addiction) at either circuit or system level. Grades will be assigned to correspond with performance on the written report covering an open-challenge. Prerequisites: Completion of departmental mathematics requirements. This course will also be open to non-engineers upon request.