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: koweiss@ufl.edu

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

the instructor.

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%).

References:

1. Fritsch, G., and Hitzig, E. (1870). Uber die elektrische Erregbarkeit des Grosshirns. Arch. Anat. Physiol. Wiss. Med.

37, 300–332.

2. http://www.nobelprize.org/nobel_prizes/medicine/laureates/1963/

3. http://www.nobelprize.org/nobel_prizes/medicine/laureates/1991/

4. http://www.nobelprize.org/nobel_prizes/medicine/laureates/2003/

5. K. Oweiss (ed.), Statistical