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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2017/2018

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DRPS : Course Catalogue : School of Informatics : Informatics

Postgraduate Course: Computational Cognitive Neuroscience (INFR11036)

Course Outline
SchoolSchool of Informatics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryIn 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.
Course description *Encoding Information in populations of neurons.
*Decoding Information from populations of neurons.
*Models of Neurons and Networks of Neurons.
*Information transmission and Attention.
*Models of Learning and Plasticity.
*Models of Memory.
*Models of Decision Making.
*Models of Mental disorders.
*The Bayesian Brain.

Relevant QAA Computing Curriculum Sections: Artificial Intelligence
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements This course is open to all Informatics students including those on joint degrees. For external students where this course is not listed in your DPT, please seek special permission from the course organiser.

Some background in statistics, and calculus. Background in linear algebra and programming in Matlab is desirable.
Information for Visiting Students
Pre-requisitesNone
High Demand Course? Yes
Course Delivery Information
Academic year 2017/18, Available to all students (SV1) Quota:  None
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 20, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 78 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) The course is assessed by four assignments and a report.

You should expect to spend approximately 40 hours on the coursework for this course.

If delivered in semester 1, this course will have an option for semester 1 only visiting undergraduate students, providing assessment prior to the end of the calendar year.
Feedback Not entered
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Describe a cognitive architecture of the brain.
  2. Contrast the applicability of several connectionist learning rules.
  3. Understand the limitation of current connectionist models.
  4. Design a simple computational model of a cognitive process and relate it to the literature and understand the underlyng assumptions.
  5. Write a simple memory model in PDP++
Reading List
Computational Modelling in Cognition: Principles and Practice by Stephen Lewandowsky and Simon Farrell, Sage 2011
Additional Information
Course URL http://course.inf.ed.ac.uk/ccn
Graduate Attributes and Skills Not entered
KeywordsNot entered
Contacts
Course organiserDr Peggy Series
Tel: (0131 6)50 3088
Email: pseries@informatics.ed.ac.uk
Course secretaryMs Katey Lee
Tel: (0131 6)50 2701
Email: Katey.Lee@ed.ac.uk
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