Computational Neuroscience

Contact Person: Philip S. Ulinski, CH 206, 702-8081, pulinski@midway.uchicago.edu

Computational neuroscience is a relatively new interdisciplinary area of inquiry that is concerned with how components of animal and human nervous systems interact to produce behaviors. It relies on quantitative and modeling approaches to understand the function of the nervous system and to design human-made devices that duplicate behaviors. Course work in computational neuroscience can prepare students for graduate studies in neurobiology or psychology, or in the mathematical or engineering sciences. It can lead to either traditional academic careers or to opportunities in the corporate world.

Neither undergraduate nor graduate degrees in computational neuroscience are available at the University of Chicago, but students concentrating in biological sciences, computer science, mathematics, physics, and psychology can easily fashion an organized course of study in computational neuroscience by selecting appropriate courses in the Common Core and in their electives.

Suggested Common Core Courses

BioSci 171-172-173 (Introductory Biology I, II, III)
Math 151-152 (Calculus I, II), or Math 161-162 (Honors Calculus I, II)
SocSci 141-142-143 (Mind I, II, III)

Suggested Electives*

BioSci 287-288-289 (Computational Neuroscience I, II, III)
Math 153 (Calculus III) or Math 163 (Honors Calculus III)
Math 195-196 (Mathematical Methods for Biological or Social Sciences I, II), or Math 200-201 (Mathematical Methods for Physical Sciences I, II)

*Students concentrating in biological sciences may also wish to elect BioSci 212 (Cellular Neurobiology), BioSci 215 (Experimental Approaches to Systems Neurobiology), and BioSci 287-288-289 (Computational Neuroscience I, II, III). Students concentrating in mathematics may wish to take higher-level courses in linear algebra, ordinary and partial differential equations, and probability and statistics. Students concentrating in psychology may wish to take Psych 207 (Experimental Approaches to Systems Neurobiology).

Faculty associated with this interdisciplinary area participate in a three-quarter sequence in computational neuroscience, teach upper level courses relevant to computational neuroscience, and participate in an ongoing Computational Neuroscience Seminar series. For further information on the study of computational neuroscience at the University of Chicago, contact Jack Cowan (Department of Mathematics, cowan@math.uchicago.edu), Terry Regier (Department of Psychology, regier@uchicago.edu), or Philip Ulinski (Department of Organismal Biology and Anatomy, pulinski@midway.uchicago.edu).

Faculty

JACK COWAN, Professor, Departments of Mathematics and Neurology, and the College

DOROTHY HANCK, Associate Professor, Department of Medicine, Committees on Cell Physiology and Neurobiology, and the College

DANIEL MARGOLIASH, Associate Professor, Departments of Organismal Biology & Anatomy, and Psychology, Committee on Neurobiology, and the College

MARTHA MCCLINTOCK, Professor, Department of Psychology, Committee on Neurobiology, and the College

JOHN MILTON, Associate Professsor, Department of Neurology, Committee on Neurobiology

HOWARD NUSBAUM, Professor, Department of Psychology and the College

YAN-YI PENG, Assistant Professor, Department of Pharmacological & Physiological Sciences and Committee on Neurobiology

JOEL POKORNY, Professor, Departments of Ophthalmology & Visual Science and Psychology

JAN-MARINO RAMIREZ, Assistant Professor, Department of Organismal Biology & Anatomy and Committee on Neurobiology

TERRY REGIER, Assistant Professor, Department of Psychology

STEVEN SHEVELL, Professor, Departments of Psychology and Ophthalmology & Visual Sciences, and the College

VIVIANNE SMITH-POKORNY, Professor, Departments of Ophthalmology & Visual Science and Psychology

V. LEO TOWLE, Associate Professor, Departments of Neurology and Surgery

PHILIP S. ULINSKI, Professor, Department of Organismal Biology & Anatomy, Committee on Neurobiology, and the College

HUGH WILSON, Professor, Departments of Ophthalmology & Visual Science and Psychology, Committee on Neurobiology, and the College

Courses

Computational Neuroscience Sequence

BioSci 287. Computational Neuroscience I: Neurons (=OrB/An 344). PQ: Prior course in cellular neurobiology or consent of instructor required. Prior or concurrent registration in Math 200 and 201 recommended. 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. P. Ulinski, Staff. Autumn.

BioSci 288. Computational Neuroscience II: Circuits (=OrB/An 345, Psych 324). PQ: BioSci 287 and a prior course in systems neurobiology, or consent of instructor, required. Prior or concurrent registration in Math 200 and 201 recommended. This course discusses the way in which individual neurons interact to form functioning circuits. Specific topics include central pattern generators, neuroethology of sensory systems, perception of visual motion and color, and an introduction to the mathematics of dynamical systems. D. Margoliash, Staff. Winter.

BioSci 289. Computational Neuroscience III: Networks (=OrB/An 346, Psych 344). PQ: Consent of instructor. This quarter discusses neural nets and cognitive neuroscience. Specific topics include brain imaging and cognition, an introduction to the mathematics of neural nets and connectionist modeling of psychological processes. T. Regier, Staff. Spring.

Courses in Cellular Neurobiology

BioSci 211. Cellular Neurobiology. PQ: Common Core biology and physics recommended. This course covers the cellular properties of neurons and glia (structure and function), membrane potential, action potential properties of voltage-gated and ligand-gated channels, mechanisms of synaptic transmission, the known cellular bases of memory, and cellular mechanisms of sensory transduction. D. Hanck, P. Lloyd. Spring.

BioSci 212. Cellular Neurobiology. PQ: Common Core biology and physics recommended. This course satisfies the lab requirements for the biological sciences concentration and fulfills one of the requirements of the Neuroscience specialization. This course is identical to BioSci 211 except that it has a lab, which focuses on electrophysiological techniques used in analysis of issues fundamental to neural processing at the cellular level, including monitoring membrane potential, carrying out voltage clamp of native and cloned ion channels, and investigating the control of synaptic transmission. D. Hanck, P. Lloyd. Spring. L.

BioSci 218. Ion Channels (=PhaPhy 332). PQ: BioSci 212 and 213, and consent of instructor. This course deals with the biological roles and structure-function relationships of voltage-gated and ligand-gated ion channels. Topics include permeation, gating, and interactions with pharmacological ligands. It focuses on biophysical methods through a consideration of classical papers, as well as readings in recent literature that use molecular techniques to probe basic channel properties. D. Nelson, Staff. Winter.

Neurbi 318. Cellular Neurobiology. 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. P. Lloyd. Autumn.

Neurbi 323. Molecular Neurobiology. This course is devoted to the examination of current research in the molecular biology of the nervous system. We explore the structure and function of macromolecules that control, propagate, and elicit neural signaling. Topics covered include (1) structural elements of neurons and glia, (2) structure and function of the synapse, (3) aspects of the molecular basis of neural signaling, and (4) gene expression in neural systems. Lectures draw on current journal literature to present a state-of-the-art background of the topic and the current questions being explored, as well as problems and aspects. W. Green, C. Palfrey. Winter.

Courses in Systems Neurobiology

BioSci 213. Systems and Behavioral Neurobiology. PQ: BioSci 211 or 212, or consent of instructor. This course satisfies the lab requirements for the biological sciences concentration and can be used to fulfill one of the requirements of the neuroscience specialization. Students are introduced to mammalian systems neuroscience with a focus on the anatomy and physiology of the visual, auditory, and motor control systems. The neural bases of form and motion perception, swimming, memory and bat sonar are examined in detail. Class assignments focus on computer simulations of neural circuits underlying these brain functions. Labs are devoted to mammalian neuroanatomy, electrophysiological recordings from neural circuits in brain slices, and visual psychophysics. H. Wilson. Autumn. L.

BioSci 215. Experimental Approaches to Systems Neurobiology (=Psych 207). PQ: BioSci 173, 195, or 212; or consent of instructor. Previous or concurrent registration in Phys 122, 132, or 142. This is a seminar-level course that considers problems concerned with the structure and function of the nervous system in invertebrates and vertebrates. Emphasis is placed on reading primary literature related to current research topics. The lab involves learning basic techniques in neurophysiology and beginning to apply them to research projects. D. Margoliash, J. Ramirez. Winter. L.

Neurbi 315. Mammalian Neuroanatomy. This is a lab-centered course that teaches students the basic anatomy of the mammalian CNS and PNS. This course is coordinated with Neurobi 316. Students learn the major structures present at each level of the neuraxis and to recognize them in rodents, cats, and primates. Somatosensory, visual, auditory, vestibular, and olfactory sensory systems are presented in more depth. For each of these sensory systems, as well as for the motor system, the nuclear organization and cellular architecture of selected regions is discussed. P. Mason, J. Goldberg, R. McCrea. Autumn. L.

Neurbi 316. Neurophysiology. This is a seminar course that teaches students the basic physiology of the mammalian CNS and PNS. Students study the physiology that is associated with the sensory and motor systems studied in Neurbi 315. In addition to reading review chapters, students read classic original articles. P. Mason, J. Goldberg, R. McCrea. Winter.

Courses in Psychophysics and Cognitive Science

Psych 256. Introduction to Cognitive Psychology (=Educ 256/356). Viewing the brain globally as an information processing or computational system has revolutionized the study and understanding of intelligence. This course introduces the theory, methods, and empirical results that underlie this approach to psychology. Topics include categorization, attention, memory, knowledge, language, and thought. Staff. Autumn.

Psych 280. Sensation and Perception (=Biopsy 280). This course centers on visual and auditory phenomena. Aside from the basic sensory discriminations (acuity, brightness, loudness, color, and pitch), more complex perceptual events, such as movement and space, are discussed. The biological underpinnings of these several phenomena are considered, as well as the role of learning in perception. H. Nusbaum. Winter.

Psych 387. Connectionist Modeling I: Techniques. PQ: Knowledge of programming, basic calculus, and linear algebra helpful. The first in a two-quarter sequence, this course provides an introduction to the computational techniques underlying the field of connectionist modeling. Topics include the Hopfield nets, perceptrons, and recurrent layered networks, together with supervised and unsupervised training algorithms for such networks. T. Regier. Winter.

Psych 391. Connectionist Modeling II: Applications. PQ: Knowledge of programming, basic calculus, and linear algebra helpful. The second in a two-quarter sequence, this course focuses on applications of connectionist modeling techniques. A number of applications illustrating the use of the concepts covered in the first course of this sequence are presented. Students are expected to conceive, design, implement, and present a project applying these modeling concepts. T. Regier. Spring.

Courses in Mathematics Related to Computational Neuroscience

BioSci 219. Nonlinear Dynamics for Neuroscience and Biopsychology. PQ: Prior calculus course. Following development of key concepts in linear differential equations, this course focuses on the nonlinear dynamics most relevant to neural networks and action potential generation. Mathematical topics include multiple steady states, hysteresis, bifurcation theory, limit cycles, and frequency entrainment. These are applied to analysis of neural networks for short-term memory, decision making, calculation of vector sums, and the Hodgkin-Huxley equations. Students are required to simulate and analyze a neural problem related to their interests. H. Wilson. Autumn.