Computational Neuroscience Minor

The BBB Program has established a new cross-school, inter-disciplinary Minor in Computational Neuroscience, which is an emerging field involving the application of quantitative methods to the analysis of neural circuits and the brain. In brief, the Minor requires eight courses, four core classes and four electives, the latter encouraging breadth. No more than five of these courses can also be used to fulfill requirements for another major or minors.

We view this Minor as an effective method of bringing together and rounding out the education of students from BBB, Cognitive Science and Bioengineering, Physics, Math, and Computer Science. The minor provides quantitative skills to those already studying the brain, and teaches neuroscience to those already immersed in quantitative methodologies. More broadly, the Minor is also designed to address the challenges and opportunities for teaching quantitative methods to undergraduates preparing for careers in the life/health sciences. Many recent articles stress that future breakthroughs in medicine will come from researchers with strong quantitative backgrounds and with experience at systems-level analysis. For example, the AAMC has recently published a call to action stating that "scientific preparation for medical school should include exposure to multidisciplinary approaches to science, and quantitative approaches to biology." The new Minor in Computational Neuroscience takes such a quantitative, multi-disciplinary approach to the training of future leaders in the sciences of the brain.

Regular advising will be provided by Dr. Johannes Burge for students within the BBB program who have a life-sciences background, and by Dr. Vijay Balasubramanian (Physics Department) for students from other backgrounds (physics, engineering, math).  Students interested in the minor should contact the appropriate advisor before declaring the minor with the BBB Office.

Download Application for a Minor.

Required courses (4.5 c.u.)

Students will start with an introductory course that provides a general overview of how the brain contributes to different aspects of neural processing like sensory perception, movement control, and cognition (BBB 109). This will be followed by a more advanced course that analyzes the molecular and cellular basis of neuronal function (BBB 251). The final core course will provide a theoretical and computational perspective on the functional organization in the brain and investigate approaches to study how neurons and networks code and decode information (BBB 585). This coursework will be complemented with relevant experience in a laboratory performing theoretical or computational neuroscience research (BBB 399).

BIBB 109: Introduction to Brain and Behavior

BIBB 251: Molecular and Cellular Neurobiology

BIBB 399 or BE 490: Independent Research

PHYS 585 / NGG 594: Theoretical & Computational Neuroscience


Electives (4 c.u.) (no more than two electives can be chosen from any one of these elective categories)


Mathematical Foundations

Neuroscience is becoming an increasingly mathematical science. These courses provide students with critical mathematical tools that will prepare them for future work in the field.

BIOL 446;STAT 101/111;PSYC 020: Statistics

ESE 674: Information Theory

MATH 240: Differential Eqs. & Linear Algebra

MATH 241: Fourier Analysis & Complex Analysis

PSYC 429: Big Data, Memory and the Human Brain

PSYC 501: Mathematical Foundations for Language & Communication Sciences


Theory and Modeling

These courses introduce students to important theoretical and modeling frameworks, and expose students to how these frameworks and numerical methods can be applied to specific problems in neuroscience and psychology.

CIS 520: Machine Learning

ESE 539: Neural Networks, Chaos & Dynamics

PHYS 280: Physical models of Biological Systems

PSYC 739: Probabilistic Models of Perception and Cognition


Neuroscience and Cognitive Science

These courses build upon the Core Requirement courses to give students a more in-depth understanding of computationally-based approaches to studying the neural bases of perception and behavior.

CIS 140/PSYC 107: Introduction to Cognitive Science

PSYC 111: Perception      

PSYC 159: Memory and Attention

PSYC 411: Modeling Cognition and Memory

PSYC 429: Big Data, Memory and the Human Brain

BIBB 249: Cognitive Neuroscience

BIOL 442/PSYC 421: Neurobiological Basis of Learning and Memory

BIO 451/BBB 479: Neural Systems and Behavior

BIBB 473: Neuroeconomics

BE 566: Network Neuroscience

NGG 572: The Electrical Language of Cells



BE 521: Brain-Computer Interfaces

ESE 313: Robotics and Bio-inspired Systems

ESE 406: Control of Systems

ESE 408: Communication Systems

ESE 573: Building Brains in Silicon