* NEU 330 / PSY 330 (STL)
Introduction to Connectionist Models: Bridging between Brain and Mind
A fundamental goal of cognitive neuroscience is to understand how psychological functions such as attention, memory, language, and decision making arise from computations performed by assemblies of neurons in the brain. This course will provide an introduction to the use of connectionist models (also known as neural network or parallel distributed processing models) as a tool for exploring how psychological functions are implemented in the brain, and how they go awry in patients with brain damage. Two 90-minute lectures, one laboratory.
Sample reading list:
Randall O'Reilly & Yuko Munakata, http://grey.colorado.edu/CompCogNeuro/index.php/CCNBook/Main
In weekly lab sessions, students will learn how to build neural network models using a powerful and intuitive neural network software package. Students will also complete simulation exercises where they explore the properties of various pre-built models of cognitive phenomena. For their final project, students will develop a neural network model that addresses some psychological phenomenon of interest to them, and write up the results of these simulations.
Paper in lieu of Final - 50%
Lab Reports - 25%
Problem set(s) - 25%
Prerequisites and Restrictions:
Prior exposure to basic concepts in cognitive psychology and neuroscience is useful for this course, as is some experience with computer programming. While the models we will be using are mathematically based, only algebra and some simple calculus-level concepts are required. The class will focus more on applying the modeling framework to psychological and neuroscientific data than on theoretical derivations. Interested freshmen and sophomores are encouraged to apply..
|41558||L01||11:00 am - 12:20 pm||M W||Green Hall 0-S-9||Enrolled:19 Limit:28|
|41559||B01||1:30 pm - 4:20 pm||W||Green Hall 0C13N||Enrolled:7 Limit:14|
|43821||B02||7:30 pm - 10:20 pm||Th||Green Hall 0C13N||Enrolled:12 Limit:16|