Course Descriptions


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Neural Engineering

Course Descriptions

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Undergraduate Programs

Courses

Neuroscience Theme

This three quarter sequence introduces the basic concepts that relate the structure and function of the nervous system to behavior.  Students typically take the first course in the sequence in their first year in the program and the second two courses in their second year.

30000. Cellular Neurobiology (= NURB 31800)
Lloyd
This course is concerned with the structure and function of the nervous system at the cellular level. The cellular and subcellular components of neurons and their basic membrane and electrophysiological properties are described. Cellular and molecular aspects of interactions between neurons are studied. This leads to functional analyses of the mechanisms involved in the generation and modulation of behavior in selected model systems.

30116. Vertebrate Neural Systems (=NURB 31600)
Ragsdale and Mason
This lab-centered course teaches students the fundamental principles of vertebrate nervous system organization.  Students learn the major structures and the basic circuitry of the brain, spinal cord and peripheral nervous system.  Somatic, visual, auditory, vestibular and olfactory sensory systems are presented in particular depth.  A highlight of this course is that students become practiced at recognizing the nuclear organization and cellular architecture of many regions of brain in rodents, cats and primates.

30100. Behavioral Neurosciences
Margoliash
This course is concerned with the structure and function of systems of neurons, and how these are related to behavior. Common patterns of organization are described from the anatomical, physiological, and behavioral perspectives of analysis. The comparative approach is emphasized throughout. Laboratories include exposure to instrumentation and electronics, and involve work with live animals. A central goal of the laboratory is to expose students to in vivo extracellular electrophysiology in vertebrate preparations. Laboratories will be attended only on one day a week but may run well beyond the canonical period.

Mathematics Theme

This three quarter sequence introduces mathematical and statistical ideas and techniques used in the analysis of brain mechanisms.  Students entering these courses should have some background in linear algebra and ordinary differential equations.  Students with this background can take the first two courses in the sequence in their first year in the program.  They can take the third, elective course,  in either their first or second years.

32000. Mathematical and Statistical Methods for Neuroscience I
van Drongelen
This course deals with application of linear systems theory and signal processing to issues in neuroscience.  It emphasizes data analysis using the Matlab software package.

32100. Mathematical and Statistical Methods for Neuroscience II
van Drongelen
This course deals with the application of non-linear methods in signal processing and dynamical systems theory to issues in neuroscience.  Data analysis with Matlab is again emphasized.

The third course in this sequence is an elective course in one of the quantitative sciences relevant to neuroscience that can be selected by the student in consultation with the program chair.

Computational Neuroscience Theme

This three quarter sequence brings together the concepts from the neuroscience theme with the quantitative methods from the mathematical theme to discuss current issues in computational neuroscience.  Students entering these courses should have completed a one year sequence in calculus.  Students take these courses in their first year in the program.

33000. Computational Neuroscience I: Single Neuron Computation
Ulinski and Staff
This course briefly reviews the historical development of computational neuroscience and discusses the functional properties of individual neurons. The electrotonic structure of neurons, functional properties of synapses, and voltage gated ion channels are discussed.

33100. Computational Neuroscience II: Vision
Ulinski and Staff
This course considers computational approaches to vision. It discusses the basic anatomy and physiology of the retina and central visual pathways, and then examines computational approaches to vision based on linear and non linear systems theory
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33200. Computational Neuroscience III: Cognitive Neuroscience
Hatsopoulas
This course is concerned with the relationship of the nervous system to higher order behaviors such as perception and encoding, action, attention and learning and memory. Modern methods of imaging neural activity are introduced, and information theoretic methods for studying neural coding in individual neurons and populations of neurons are discussed.

Elective Courses

31000  Mathematical Methods for the Biological Sciences I (=BIOS 26210)
Kondrashov

31100  Mathematical Methods for the Biolgoical Sciences II (=BIOS 26211)
Kondrashov

31200  Mathematical Methods for the Biological Sciences III (=BIOS 26212)
Kondrashov

32607  Advanced Topics in Theoretical Neuroscience
Cowan

34600 Neurobiology of Disease I
Gomez and Staff

34700  Neurobiology of Disease II
Gomez and Staff

Neural Engineering Courses Available through
the Illinois Institute of Technology

These courses are offered on a semester basis.

35106 Neuromechanics of Human Movement
Kamper

35204  Neuroprosthetics
Troyk

35305  Electronics
Troyk

Reading and Research Courses

39900. Readings in Computational Neuroscience
Staff

Reading courses on various topics in computational neuroscience.

40100. Research in Computational Neuroscience
Staff

Research credit (varied units) for research undertaken by graduate students under the guidance of a faculty member of the Committee on Computational Neuroscience.