The Neuroscience Program has established a 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. Students must have a minimum of 3 courses that they count towards the minor and not towards any other major or minor.
This minor is an effective method of bringing together and rounding out the education of students from Neuroscience, 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 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 meeting with a Neuroscience advisor during advising hours to officially declare the minor.
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 (BIBB 109). Students will also take a course in computer science and 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 (BIBB 585). This coursework will be complemented with relevant experience in a laboratory performing theoretical or computational neuroscience research.
BIBB 109: Introduction to Brain and Behavior
CIS 110: Introduction to Computer Programming (or CIS 120)
PHYS 585 / NGG 594: Theoretical and Computational Neuroscience
Independent Research (BIBB, BIOL, COGS, PSYC, EE, BE, CIS)
(no more than two electives can be chosen from any one of these elective categories)
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.
MATH 240: Differential Equations and Linear Algebra
MATH 241: Fourier Analysis and Complex Analysis
ESE 674: Information Theory
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
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
BIBB 249: Cognitive Neuroscience
BIBB 251: Molecular and Cellular Neurobiology
BIOL 442/PSYC 421: Neurobiological Basis of Learning and Memory
BIO 451/BBB 479: Neural Systems and Behavior
BIBB 473: Neuroeconomics
PSYC 411: Modeling, Cognition and Memory
PSYC 429: Big Data, Memory and the Human Brain
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