Biomedical Robotics: Special Advanced Topics in Biomedical Engineering ( BME 495 )
This is a new course and will be offered in the spring quarter. Its purpose is to provide a perspective on robotics technologies inspired by themes of medical research and practice. At the end of the course the students are expected to have gained an understanding of the basic theoretical and computational methods of robotics as well as the major applications in the biomedical field.
Instructors:
Sandro Mussa-Ivaldi, James Patton and Michael Kositsky. Prerequisites:
Good basic knowledge of differential equations, control theory. Some background in neurophysiology is desirable but not necessary.
Neural Control and Mechanics of Movement ( 765-469)
TMuscle mechanics and relevant spinal cord neurophysiology as the basis for understanding neural control of movement.
Instrumentation For Neuroscience (NUIN 455)
This is a lecture and laboratory course on practical aspects of general electrical and mechanical instrumentation ranging from power supplies, nuts, and screws, to machining, microprocessors, and computers. We will cover the basics of instrumentation theory, design, construction, use, and troubleshooting. We will emphasize basic machine shop practices, basic to intermediate level applications of active electronics devices (integrated circuits or ICs) that are used for laboratory design, the use of computers for data acquisition, and applying computer software (IGOR) for data analysis. Instructors: Jim Baker (director), Lee Miller (computer applications), Brett Foxwell (machinist).
Biological Imaging: Principles and Applications (IGP 415 or BME 495)
This course provides an introduction to basic image analysis techniques for the quantification of image-based data in the life sciences. The course includes lectures, computer laboratories, and student projects that apply the information learned in class. There are no prerequisites.
Topics include: basic imaging concepts and terminology, image acquisition, imaging processing hardware, image display, spatial image analysis (noise,filtering, enhancement, edge detection, segmentation), frequency image analysis (Fourier), introduction to fMRI, and analysis fMRI images. Phil Hockberger - Director, Instructors: Kevin McKenna, and Vania Apkarian.
Neural Control of Movement (NUIN 480)
This deals with the neural mechanisms whereby the brain and spinal cord process sensory information to control movement. The course will meet twice weekly for one and a half hours to discuss and interpret key literature selected from the field of motor control. Prior to each meeting, students will be asked to read one or two important recent publications, and one student will be assigned to give an in-depth presentation and interpretation of the papers. The instructor will give a brief orientation to the topic at the beginning of the session and will provide summary remarks after the student presentation at the second meeting. Session topics and papers will be selected by the course organizers with the aim of emphasizing the integrative role of the spinal cord, brainstem, cerebral cortex, basal ganglia and cerebellum in the generation and regulation of movement commands and in the translation of these commands into skilled motor acts.
Sensorimotor Integration (NUIN 452)
Skeletomotor and oculomotor control processes and their relation to sensory signals. Topics range from the classic accounts of motor performance to microelectrode studies in behaving animals.
Topics in Cognitive Neuroscience
The goal of this course is to introduce students to selected special topics in the field of cognitive neuroscience. A major aim of cognitive neuroscience is to bridge the gaps among cognitive science, communication science, systems and cellular neuroscience, brain imaging, and computational neuroscience. Due to the interdisciplinary nature of cognitive neuroscience, prior exposure to neuroscience, mathematics and/or cognitive psychology will be helpful. Prospective students should communicate with Jim Houk, Ken Paller, or any of the other course directors, to discuss whether their previous studies will provide adequate preparation. The course will explore the mechanisms by which neural networks generate voluntary actions, memory, thinking, problem solving, language and emotion and learn how these capabilities malfunction in persons with brain damage, mental illness and dementia.