Neuroimaging I
Course infoSchedule
Course moduleSOW-DGCN02
Credits (ECTS)6
Language of instructionEnglish
Offered byRadboud University; Faculty of Social Sciences; Cognitive Neuroscience;
PreviousNext 1
dr. I.G.M. Cameron
Other course modules lecturer
prof. dr. E.J. Hermans
Other course modules lecturer
prof. dr. E.J. Hermans
Other course modules lecturer
dr. N. Kohn
Other course modules lecturer
Contactperson for the course
dr. N. Kohn
Other course modules lecturer
Academic year2017
SEM1  (04/09/2017 to 04/02/2018)
Starting block
Course mode
Registration using OSIRISYes
Course open to students from other facultiesNo
Waiting listNo
Placement procedure-
After completing this course, students are able to describe the basic principles of human cognitive neuroimaging. For all major neuroimaging modalities, they will be able to explain the relationship between neural activity and the measured signal. They will be able to evaluate strengths and weaknesses of different modalities for answering specific questions. They will be able to explain the basics of experimental designs and statistical analysis of neuroimagingstudies. Furthermore, students will be able to describe the physics underlying neuroimaging techniques.

Neuroimaging methodological aspects: This course will provide an overview of the currently most widely used neuroimaging methods in cognitive neuroscience (EEG/ERP, MEG, TMS, fMRI, PET). For each of these methods, the basic measurement technique and the relationship between the measured signal and neural activity will be discussed.  Special emphasis is placed on what can and cannot be inferred in terms of underlying brain activity.

Experimental design aspects: The course will discuss in detail how these methods are combined with experimental paradigms that isolate functional aspects of human cognition. It aims at making students aware of the relevant design issues in imaging experiments. It will also discuss the assumptions in mapping functional onto neural architecture.

Data analysis aspects: The course will provide an overview of the methods of processing the data, obtained with the different research methods commonly used in modern cognitive neuroscience. The underlying data analysis models will be discussed, e.g., the General Linear Model for fMRI.

Additional comments
COURSE: September 4, 2017 – January 22, 2018; Monday 10.45-12.30
LOCATION: DCC, Donders room, SpA.00.07
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.

Test information
EXAM: Friday January 26, 2018; 10.45-13.30
TYPE OF EXAM: written exam

Contact information
Dr. N. Kohn

Required materials
Course material
Lecture notes

Recommended materials
Raichle M. (2009) A brief history of human brain mapping. Trends in Neurosciences 32(2).
Hari R, Parkkonen L, Nangini C. The brain in time: insights from neuromagnetic recordings. Ann N Y Acad Sci. 2010 Mar;1191:89-109.
Steve Luck: An introduction to Event-Related Potentials and their neural origins. Available on Blackboard.
Sylvain Baillet: The Dowser in the Fields: Searching for MEG Sources. Available on Blackboard.
Jensen & Mazaheri: Shaping functional architecture by oscillatory alpha activity: gating by inhibition. Frontiers in Human Neuroscience. 2010; 4:186.
Huettel SA, Song AW, McCarthy G. Functional Magnetic Resonance Imaging, 2nd edition, 2009: Chapters 8,9,10
Smith (2004): Overview of fMRI analysis. The British Journal of Radiology 77;S167–S175.
Wassermann EM, Epstein CM, Ziemann U. Oxford Handbook of Transcranial Stimulation, 2008
MRI made Easy DVD (order e.g.:
Hallett (2007) Transcranial Magnetic Stimulation: A Primer. Neuron 55;187-199.

Instructional modes
Attendance MandatoryYes

Written exam
Test weight1
OpportunitiesBlock SEM1, Block SEM2