Contacts | Suggested General Education Courses | Suggested Electives | Computational Neuroscience Courses

Department Website: http://cns.bsd.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, in the mathematical or engineering sciences, or in areas of medicine such as neurology or psychiatry. It can lead either to traditional academic careers or to opportunities in the corporate world.

An undergraduate degree in computational neuroscience is not available at the University of Chicago, but a minor in computational neuroscience is offered by the Biological Sciences Collegiate Division. This minor is a good option for students who are majoring in biological sciences and are interested in mathematical approaches to biology; or for students who are majoring in computer science, mathematics, physics, psychology, or statistics and are interested in neuroscience. For details, see the Biological Sciences section in this catalog.

Students electing this minor must have completed, or placed out of, the equivalent of a year of collegiate-level calculus and must have completed the general education requirement for the biological sciences.

Summary of Requirements for the Minor in Computational Neuroscience

BIOS 24231Methods in Computational Neuroscience100
BIOS 24232Computational Approaches to Cognitive Neuroscience100
BIOS 24408Modeling and Signal Analysis for Neuroscientists100
BIOS 26210-26211Mathematical Methods for Biological Sciences I-II200
Total Units500

Instead of completing a formal minor, students can easily fashion an organized course of study in computational neuroscience by selecting appropriate general education courses and electives.

For updated information on computational neuroscience activities and undergraduate programs, visit cns.bsd.uchicago.edu.

Suggested General Education Courses

Students majoring in biological sciences can elect either the BIOS 20180s or the BIOS 20190s sequence.

One of the following sequences:200
Calculus I-II
Honors Calculus I-II
SOSC 14100-14200-14300Mind I-II-III300

Suggested Electives

BIOS 24203Introduction to Neuroscience100
BIOS 24204Cellular Neurobiology100
BIOS 24205Systems Neuroscience100
BIOS 24208Survey of Systems Neuroscience100
BIOS 24246Neurobiology of Disease I100
BIOS 24247Neurobiology of Disease II100
PSYC 20300Biological Psychology100
PSYC 20400Cognitive Psychology100
PSYC 20700Sensation and Perception100

Faculty

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.

Computational Neuroscience Courses

BIOS 24231. Methods in Computational Neuroscience. 100 Units.

Topics include (but are not limited to): Hodgkin-Huxley equations, Cable theory, Single neuron models, Information theory, Signal Detection theory, Reverse correlation, Relating neural responses to behavior, and Rate vs. temporal codes.

Instructor(s): S. Bensmaia     Terms Offered: Winter. L.
Prerequisite(s): BIOS 26210 and BIOS 26211 which must be taken concurrently, or consent of instructor.
Equivalent Course(s): CPNS 34231

BIOS 24232. Computational Approaches to Cognitive Neuroscience. 100 Units.

This course is concerned with the relationship of the nervous system to higher order behaviors (e.g., perception, object recognition, action, attention, learning, memory, and decision making). Psychophysical, functional imaging, and electrophysiological methods are introduced. Mathematical and statistical methods (e.g. neural networks and algorithms for studying neural encoding in individual neurons and decoding in populations of neurons) are discussed. Weekly lab sections allow students to program cognitive neuroscientific experiments and simulations.

Instructor(s): N. Hatsopoulos     Terms Offered: Spring
Prerequisite(s): BIOS 26210, a course in systems neuroscience, and knowlege using Matlab, or consent of instructor.
Equivalent Course(s): CPNS 33200, ORGB 34650, PSYC 34410,CPNS

BIOS 24246. Neurobiology of Disease I. 100 Units.

This seminar course is devoted to basic clinical and pathological features and pathogenic mechanisms of neurological diseases. The first semester is devoted to a broad set of disorders ranging from developmental to acquired disorders of the central and peripheral nervous system. Weekly seminars are given by experts in the clinical and scientific aspects of the disease under discussion. For each lecture, students are given a brief description of clinical and pathological features of a given set of neurological diseases followed by a more detailed description of the current status of knowledge of several of the prototypic pathogenic mechanisms.

Instructor(s): C. Gomez, Staff     Terms Offered: Winter
Prerequisite(s): NURB 31800 or BIOS 24203
Equivalent Course(s): CPNS 34600,NURB 34600,CCTS 40100

BIOS 24408. Modeling and Signal Analysis for Neuroscientists. 100 Units.

The course provides an introduction into signal analysis and modeling for neuroscientists. We cover linear and nonlinear techniques and model both single neurons and neuronal networks. The goal is to provide students with the mathematical background to understand the literature in this field, the principles of analysis and simulation software, and allow them to construct their own tools. Several of the 90-minute lectures include demonstrations and/or exercises in Matlab.

Instructor(s): W. van Drongelen      Terms Offered: Spring. L.
Prerequisite(s): BIOS 26210 and 26211, or consent of instructor.
Equivalent Course(s): CPNS 32111

BIOS 26210-26211. Mathematical Methods for Biological Sciences I-II.


BIOS 26210. Mathematical Methods for Biological Sciences I. 100 Units.

This course builds on the introduction to modeling course biology students take in the first year (BIOS 20151 or 152). It begins with a review of one-variable ordinary differential equations as models for biological processes changing with time, and proceeds to develop basic dynamical systems theory. Analytic skills include stability analysis, phase portraits, limit cycles, and bifurcations. Linear algebra concepts are introduced and developed, and Fourier methods are applied to data analysis. The methods are applied to diverse areas of biology, such as ecology, neuroscience, regulatory networks, and molecular structure. The students learn computations methods to implement the models in MATLAB.

Instructor(s): D. Kondrashov     Terms Offered: Autumn. L
Prerequisite(s): BIOS 20151 or BIOS 20152 or consent of the instructor
Equivalent Course(s): CPNS 31000,PSYC 36210

BIOS 26211. Mathematical Methods for Biological Sciences II. 100 Units.

This course is a continuation of BIOS 26210. The topics start with optimization problems, such as nonlinear least squares fitting, principal component analysis and sequence alignment. Stochastic models are introduced, such as Markov chains, birth-death processes, and diffusion processes, with applications including hidden Markov models, tumor population modeling, and networks of chemical reactions. In computer labs, students learn optimization methods and stochastic algorithms, e.g., Markov Chain, Monte Carlo, and Gillespie algorithm. Students complete an independent project on a topic of their interest.

Instructor(s): D. Kondrashov     Terms Offered: Winter. L.
Prerequisite(s): BIOS 26210 
Equivalent
Equivalent Course(s): CPNS 31100,PSYC 36211


Contacts

Undergraduate Primary Contact

Faculty Adviser
Nicholas G. Hatsopoulos
Anatomy Building, Room 202
773.702.5594
Email

Administrative Contact

Administrative Director
Nicole Kaminski-Ozturk
J233, SBRI
773.302.6371
Email