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 : For Informatics PG students only, or by special permission of the School. Experience in programming or simulation systems desirable. No background in Neuroscience or cognitive science is required.

Subject Areas

Home subject area

Cognitive Neuroscience, (School of Informatics, Schedule O)

Other subject areas

Vision, Perception and Action, (School of Informatics, Schedule O)

Neuroinformatics, (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
08/01/2007	11:10	12:00			Room A9/11, Forrest Hill

All of the following classes

Type	Day	Start	End	Area
Lecture	Monday	11:10	12:00	Central
Lecture	Thursday	11:10	12:00	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++