University of Rochester

Brain & Cognitive Sciences

BCS 547: Syllabus

Spring 2016

Wed 1:30-4pm

Instructor: Ralf Haefner

Office hours: after class and by appointment

About the course

This course will cover a range of mathematical theories describing various aspects of brain function: from sensory processing, to decision-making, memory, and motor control. We will focus primarily on the first two of these topics and address the questions of how stochastically spiking neurons can represent information about the outside world, infer knowlegde 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 cognitive functions. This course is meant to be accessible to any BCS grad student and I will review the necessary maths as we go along.

Who should take this course?

Anyone interested in current mathematical models of brain function, especially as they relate to neural responses. Much of this will be transferrable to other subfields of cognitive sciences, especially our discussion of statistical inference and decision-making, and computational modeling in general.

Prerequistes

Basic competence in computer programming (e.g. Matlab or Python), and basic math (linear algebra and analysis). Basic knowledge of neuroscience (e.g. BCS110 or similar) is desired by not necessary.

Readings

"Theoretical Neuroscience" by Dayan & Abbott, 2001 among others

Homework, Exams, Grading

There will be weekly or bi-weekly computer exercises for the first 2/3 of the course but no exams. The exercises will typically be simple implementations of models discussed in class. There will be a final project that can be either an extension of one of the exercises, or related to one's primary research interests. Grading is pass/fail.

Topics