Computational Neuroscience Minor

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. You can substitute a more advanced course for a more elementary one with permission of the minor advisors.  However, you may not use high school credits (including AP or IB) to substitute for any course in the 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.

Students interested in the minor should meet with an advisor to discuss their coursework and should complete the minor application form (Download Application for a Minor). Students within the Neuroscience program and other majors with a life sciences background should contact Dr. Johannes Burge (Psychology Department). Students from other majors, such as physics, math and engineering should contact Dr. Vijay Balasubramanian (Physics Department). After having their Application approved, students who would like to declare the minor must make an official request to declare the major on the College website at https://srfs.upenn.edu/registrar/forms

 

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 (NRSC 1110/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 (PHYS 5585). This coursework will be complemented with relevant experience in a laboratory performing theoretical or computational neuroscience research.

NRSC 1110/BIBB 109: Introduction to Brain and Behavior

CIS 1100/110: Introduction to Computer Programming (or CIS 1200/120)

PHYS 5585/PHYS 585: Theoretical and Computational Neuroscience

Independent Research (NRSC/BIBB, BIOL, COGS, PSYC, EE, BE, CIS, PHYS, MATH - Independent Research may also be performed in other fields departments provided it is relevant to computational neuroscience and is approved by the minor advisors)

(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 2400/MATH 240: Differential Equations and Linear Algebra

MATH 2410/MATH 241: Fourier Analysis and Complex Analysis

ESE 6740/674: 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 5200/520: Machine Learning

ESE 5390/539: Hardware/Software Co-Design for Machine Learning

PHYS 2280/PHYS 280: Physical models of Biological Systems

PSYC 7390: Special Topics in Perception

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.

BE 5660 (BE 566): Network Neuroscience

BIOL 4110 / BIOL 5110 / NRSC 4110 (BIBB 479): Neural Systems and Behavior

COGS 1001 (COGS 101): Introduction to Cognitive Science

NGG 5720 (NGG 572): The Electrical Language of Cells

NRSC 2205: Cellular Basis of Learning and Memory

NRSC 2110 (BIBB 251): Molecular and Cellular Neurobiology

NRSC 4421: Functional Imaging of the Human Brain

NRSC 4442 (BIBB 442): Neurobiological Basis of Learning and Memory

PSYC 1340 (PSYC 111): Perception      

PSYC 1230 / NRSC 2249 (BIBB 249): Cognitive Neuroscience

PSYC 2555 / NRSC 2273 (BIBB 473): Neuroeconomics

PSYC 4230 - Introduction to functional magnetic resonance imaging (fMRI) research

 

BE 5210/521: Brain-Computer Interfaces

ESE 3130/313: Robotics and Bio-inspired Systems

ESE 4060/406: Control of Systems

ESE 4080/408: Communication Systems

ESE 5730/573: Building Brains in Silicon