KARIM OWEISS TO TEACH NEW COURSE
EEL 5934 Neural Signals, Systems and Technology to be taught in Spring 2015
Spring 2015: EEL 5934
Neural Signals, Systems & Technology
Instructor: Karim G. Oweiss, Ph.D. Phone: (352) 294-1898 E-mail: email@example.com
Meeting Time and Location: Tuesdays 8:30AM-10:25AM, Thursdays 9:35AM-10:25AM in BLK 415
Credits: 3 credit hours
First Most Important Question: Why should I take this course?
Neural Engineering is an interdisciplinary field of research that focuses on novel tools and
techniques to investigate the structure and function of the nervous system and potentially manipulate
its behavior to bypass/repair damaged or pathological circuits and restore lost functions. There is a
misconception that neural engineering is an emerging field of science while, in fact, it is more than a
century old. Dating back to the late 1800’s findings that the brain uses electricity to carry out motor
functions1, classical examples include the use of electrical circuit analysis techniques to model nerve
cell activity (1963 Nobel Prize in Phys. and Med.2), feedback control techniques in patch clamp
recording to identify the function of single ion channels in living cells (1991 Nobel Prize in Phys. and
Med.3) and electromagnetic field theory for Magnetic Resonance Imaging (MRI) of the body (2003
Nobel Prize in Phys. and Med.4). Nonetheless, this field has been witnessing a revolutionary progress
in the last few years, mainly attributed to striking advances in the engineering of measurement
devices, molecular biology techniques to manipulate cell-type specific discharge pattern, and
sophisticated models of neural ensembles at exceedingly high temporal and spatial resolutions. It
consequently gained strong interest to be at the stage to deliver long-lasting impact on basic and
clinical neuroscience research.
In this course, we will discuss classic and modern topics of this re-emerging discipline, with the
goal of shedding some light onto how engineering principles have been – and continue to be –
instrumental in addressing basic and translational neuroscience questions. Most importantly, we will
discuss the biophysical principles of neural signaling, the characterization of neural circuits and
systems, the design principles of technology for interfacing with biological neural systems, and finally
provide an overview of clinical applications and industrial opportunities for neurotechnology ventures.
Because of its interdisciplinary nature, we will draw upon many areas of research such as systems
and computational neuroscience, molecular neurobiology, neurophysiology, micro-electromechanical
systems and nanotechnology, signal processing and information theory, among many others5.
Second Most Important Question: Am I ready to take this course?
Prerequisite: While there are no formal prerequisites, it is expected that students interested in this
topic will have a graduate standing in engineering and/or neuroscience (or undergraduate senior
standing with approval from the instructor). Even if class material may span topics in one discipline
unfamiliar to students in the other discipline, it is expected that students will acquire the necessary
knowledge during the semester, either by reading supplementary material or through interaction with
Third Most Important Question: How the course will be graded?
Grading: Four homework assignments worth 20% (5% each); two essays worth 20% (10% each);
class participation, discussion & presentations (20%); final project/term paper (40%).
1. Fritsch, G., and Hitzig, E. (1870). Uber die elektrische Erregbarkeit des Grosshirns. Arch. Anat. Physiol. Wiss. Med.
5. K. Oweiss (ed.), Statistical