Computational Cognitive Neuroscience (P01490)

? Credit Points : 10 ? SCQF Level : 11 ? Acronym : INF-P-CCN

In this course we study computational approaches to understanding cognitive processes, using massively parallel networks.

We study biologically-inspired learning rules for connectionist networks, and their application in connectionist models of perception, memory and language.

Entry Requirements

? Pre-requisites : Experience in programming or simulation systems desirable. No background in Neuroscience or cognitive science is required.

Subject Areas

Home subject area

Cognitive Science, (School of Informatics, Schedule O)

Delivery Information

? Normal year taken : Postgraduate

? Delivery Period : Semester 2 (Blocks 3-4)

? Contact Teaching Time : 2 hour(s) per week for 10 weeks

First Class Information

Date	Start	End	Room	Area	Additional Information
10/01/2006	12:00	13:00			Forrest Hill, Room A9/11

All of the following classes

Type	Day	Start	End	Area
Lecture	Tuesday	12:10	13:00	Central
Lecture	Friday	12:10	13:00	Central

Summary of Intended Learning Outcomes

After the course students should be able to:

- Describe a cognitive architecture of the brain.
- Contrast the applicability of several connectionist learning rules.
- Understand the limitation of current connectionist models.
- Design a simple computational model of a cognitive process and relate it to the literature and understand the underlyng assumptions.
- Write a simple memory model in PDP++