BCSC 247: Syllabus
Fall 2025
Tue/Thu 12:30 PM - 1:45 PM / Location: Dewey 2-110D
Personnel
Instructor: Ralf Haefner
Office Hours: Tue & Thu 1:45-2:30 pm
Teaching Assistants:
Rithwik Cherian
Recitation time: Friday, time TBD, Location: TBD
Prerequisites for the course: Programming skills (MATLAB or Python preferred), knowledge in linear algebra and analysis
Course Description
This course will cover a range of mathematical theories describing various aspects of brain function with a focus on visual processing and decision-making. We will address the questions of how stochastically spiking neurons can represent information about the outside world, infer knowledge about behaviorally relevant variables and make decisions based on them. The focus of the course will not be on the biological details of neuronal activity, but on mathematical and computational models of how this activity might support perception, decision-making, and action selection.
Assignments
There will be 5 assignments, all involving programming. They will typically be implementations of models discussed in class in order to apply and deepen understanding. Assignments will include additional questions for graduate students.
Readings
There is no assigned textbook for this class.
Readings come from "Theoretical Neuroscience" by Dayan & Abbott, 2001 (pdf available online) as well as other sources which will be posted on Blackboard.
Readings on programming (both available as ebooks at library):
Matlab for Neuroscientists
Neural data science: a primer with Matlab and Python
Grading
Undergraduate students (4 credits):
In class participation (10%); Assignments (40%); Midterm exam (20%), Final exam (20%), Quizzes (10%)
Graduate students (4 credits):
In class participation (10%); Assignments (40%); Midterm exam (20%), Final exam (20%), Quizzes (10%)
This course follows the College credit hour policy for four-credit courses. This course meets twice weekly for three academic hours per week. The course also includes a recitation for one academic hour per week.
Class attendance is expected
Blackboard will be used for assignments, grading, and slides.
Slack will be used for general communication and discussion.
Collaboration
Collaboration in teams of 2 or 3 students is encouraged but not required. All assignments must be completed and submitted individually, with individual results, based on individual simulations.
ChatGPT & other generative AI is permitted but needs to be acknowledged/credited when used.