Neuroimaging II: Haemodynamic Methods
Course infoSchedule
Course moduleSOW-DGCN37
Credits (ECTS)6
Language of instructionEnglish
Offered byRadboud University; Faculty of Social Sciences; Cognitive Neuroscience;
prof. dr. C.F. Beckmann
Other course modules lecturer
Contactperson for the course
prof. dr. D.G. Norris
Other course modules lecturer
prof. dr. D.G. Norris
Other course modules lecturer
dr. G.T. Sescousse
Other course modules lecturer
Academic year2017
SEM2  (05/02/2018 to 13/07/2018)
Starting block
Course mode
Registration using OSIRISYes
Course open to students from other facultiesNo
Waiting listNo
Placement procedure-
This course builds on the course Neuroimaging I (DGCN02). It aims to give students a deeper understanding of the imaging methods and analytical tools that are available to cognitive neuroscientists. At the conclusion of the course the student should be able to understand the underlying principles of data acquisition and analysis in fMRI. The course offers a systematic explanation of the acquisition experiment and hands on experience with the most commonly used data analysis techniques. It is mandatory for students wishing to perform an fMRI experiment in their master's project.
Data acquisition. The student will be taught how data are acquired and what the fundamental limitations of the techniques are. The basic principles of MRI will be taught. MRI using the echo planar imaging technique will be explained and modern developments in accelerating data acquisition introduced.Generalised image reconstruction in terms of k-space will be introduced and image acquisition and reconstruction in MRI explained in these terms.The complex nature of the BOLD response used for f(MRI) will be examined. The measurement of connectivity using both resting state fMRI and fibre tracking based on diffusion tensor measures will be introduced.
Data analysis. The main areas covered in this part of the course are: analysing structural MRI data including segmentation and assessment of grey matter volume; analysis of fMRI data both at the single subject and the group level using the general linear model; exploratory data analysis including the use of independent components, and their application to measuring functional connectivity; the assessment of structural connectivity using diffusion-weighted imaging.
Design aspects. An in-depth treatment will be given of the different experimental design types in imaging studies. The advantages and disadvantages of the different design types will be discussed, with emphasis on statistical efficiency. Students will be given the task to design an experiment and practice analysis.

Additional comments
COURSE: February 9 – June 29, 2018, Friday 8.45-10.30
April 10 –June 26, 2018, Tuesday 8.45-10.30
(Thursday May 31, 2018, 14.00-17.00 SPM practical Instruction room, DCCN)

Test information
EXAM: Monday July 2, 2018; 10.30-13.30
TYPE OF EXAM: written exam (3 hours) plus compulsory open-book exams for each section of the course.
NOTE: enrollment for a course automatically registers you for its exam. If you don't want to do the first exam you have to deregister for the exam in OSIRIS, but do not forget to sign up for the retake in OSIRIS.

Taking the exam for this course is only allowed after the course DGCN09 (Advanced math) has been passed successfully. If you have sufficient knowledge of mathematics you may request an exemption from this rule from the Examination Board.

Contact information
Prof. dr. D. Norris

Recommended materials
Course material
Lecture notes
Functional Magnetic Resonance Imaging, Scott A. Huettel, Allen W. Song, and Gregory McCarthy, (2nd edition 2009) ISBN:978-0-87893-286-3

Instructional modes
Assignment, hands-on practical exercises
Attendance MandatoryYes

Attendance MandatoryYes

Presentation, lectures, student assignments, hands-on practical exercises in recording and analysing fMRI, and MRI data.

Attendance MandatoryYes

written exam, compulsory open-book exams
Test weight1
OpportunitiesBlock HER, Block SEM2