2. They will be able to write their own analysis scripts in Matlab.
3. They understand that Matlab was developed for matrix calculations and are able to code accordingly.
During this course you will learn basic Matlab skills. The focus will be on brain imaging data, but the techniques are also applicable in other domains. Students will develop practical Matlab skills to analyze and visualize various types of signals.
Topics that will be covered: basic matrix algebra, basic programming concepts (e.g. functions, loops, logical operators), signals in the time domain, signals in the frequency domain (Fourier transformation), Linear Time Invariant Systems, multiple linear regression, convolution. This will all culminate in a frequency analysis of an MEG signal, resulting in a Time Frequency Representation, and the analysis, including contrasts, of a full brain fMRI dataset.
|Syllabus ‘Signal Processing and Matlab', available on Blackboard.
|There will be two introductory lectures to explain the rules for this course and to provide some background on the topics covered.
Students are supposed to hand in weekly assignments that they make in their own time - they make up 20% of the final grade.
There are 5 tutorial sessions. During these sessions, questions with regard to the assignments will be answered.Note that questions, possibly with supporting code, need to be handed in beforehand through Blackboard!
|The exam is a programming exercise that needs to be solved in 4h, this makes up for 80% of the final grade. The practical assignments make up for the remaining 20%. There will be no written exam.
|For this course you need basic knowledge about Linear Algebra, especially matrix multiplication, matrix inversion, solving a system of linear equations. Also some basic programming knowledge is needed (‘for', ‘while', program structure diagrams). If you have already taken PSB3BC35E (Signal Analysis and Matlab) in the psychology program, you should not take this course.
|Dr. Luc Selen; email@example.com