BCSC 247: Syllabus

Fall 2022

Tue/Thu 12:30 PM - 1:45 PM / Location: Meliora Room 224

Personnel

Instructor: Ralf Haefner
Office: Meliora Hall 313
Email:
Office hours: Tue/Thu 1:45-2:15pm

Teaching Assistant: Anton Pletenev
Room 416 Meliora Hall

Office hours:Fri TBA

Recitation time: Friday, Time and Room number to be announced

Prerequisites for the course: Basic programming skills (MATLAB, R, Python preferred), basic 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 and decision-making.

Assignments

There will be 6 assignments, all involving some programming. They will typically be simple 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):
Assignments (65%); regular short in-class tests (10%); Final exam (25%)

Graduate students (4 credits): Assignments (65%); regular short in-class tests (10%); Final exam (25%)

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 assignment and grading

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.

Academic Honesty

Bottom line: don’t cheat, don’t plagiarize. Cases of suspected misconduct will not be evaluated directly by us, but will be referred to the College Board on Academic Honesty. I take this policy very seriously. If you are unsure of something, please ask me!