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COURSE SYLLABUS

Intelligent Technology - Computational Neuroscience I 15 Credits

Framtidens intelligenta teknik - Teoretisk neurovetenskap I
First cycle, P0065A
Version
Course syllabus valid: Spring 2018 Sp 3 - Present
The version indicates the term and period for which this course syllabus is valid. The most recent version of the course syllabus is shown first.

Syllabus established
by Director of Undergraduate Studies Bo Jonsson, Department of Business Administration, Technology and Social Sciences 14 Feb 2014

Last revised
by Director of Undergraduate Studies Daniel Örtqvist, Department of Business Administration, Technology and Social Sciences 01 Jun 2017

Education level
First cycle
Grade scale
U G#
Subject
Theoretical Neuroscience
Subject group (SCB)
Other Subjects within Technology

Entry requirements

In order to meet the general entry requirements for first cycle studies you must have successfully completed upper secondary education and documented skills in English language and P0008A Intelligent Technology Cognitive Science and P0012A Intelligent Technology Computation & the Brain. Alternatively, corresponding knowledge acquired by university studies and/or working experience.


More information about English language requirements


Selection

The selection is based on 1-165 credits.



Course Aim
Fundamental knowledge and skills in Computational Neuroscience. The student is to integrate and elaborate upon knowledge gained from previous university courses in cognitive and biological neuroscience. Furthermore, the student will attain skills in simulating the information processes of the brain by means of computational models. The course is for everyone who wants to learn about a highly topical and exciting field of research.

Contents
Integration of the course content in P0008A Intelligent Technology – Cognitive Science and P0012A Intelligent Technology – Computation & the Brain, implying an elaboration upon knowledge about the neurological base for perception, cognition, emotion, action and motor control. Additionally, mathematical, computational and neural network models are used to simulate the information processes of the brain. One example of such a process is the treatment of information in the primary visual cortex, which can be simulated by means of Hebbs law. The law postulates that when a neuron A activates a second neuron B, the synaptic coupling between the two neurons is strengthened.

Realization
Internet course, comprising individual studies.

Examination
Assignments and laboratory sections.

Remarks
Students must register for the courses themselves, or contact ETS educational administration eduets@ltu.se, not later than three days after the quarter commences. Failure to do so can result in the place being lost. This rule also applies to students with a guaranteed place.

Taught in Swedish and English.
 
Associated courses in Intelligent Technology are:
P0008A Intelligent Technology of the future – Cognitive science;
P0012A Intelligent Technology – Computation & the Brain;
P0065A Intelligent Technology – Computational Neuroscience I;
P7010A Intelligent Technology – Cyborgs & Humanoid Robots;
P7045A Intelligent Technology – Neuroscience & Mathematics;
P7034A Intelligent Technology – Computational Neuroscience;
P7023A Intelligent Technology – Scientific Work.

Examiner
Peter Bengtsson

Literature. Valid from Autumn 2014 Sp 1 (May change until 10 weeks before course start)
Trappenberg, T. P. (2010). Fundamentals of Computational Neuroscience. 2nd Edition.
Additional literature will be added according to the teacher's instructions.

Course offered by
Department of Business Administration, Technology and Social Sciences

Items/credits
NumberTypeCreditsGrade
0001Assignment report and laboratory work15.0U G#

Study guidance
Study guidance for the course is to be found in our learning platform Canvas before the course starts. Students applying for single subject courses get more information in the Welcome letter. You will find the learning platform via My LTU.