Neuroimaging I
Course infoSchedule
Course moduleSOW-DGCN02
Credits (ECTS)6
CategoryMA (Master)
Language of instructionEnglish
Offered byRadboud University; Faculty of Social Sciences; Cognitive Neuroscience;
PreviousNext 3
prof. dr. E.J. Hermans
Other course modules lecturer
dr. N. Kohn
Other course modules lecturer
dr. N. Kohn
Other course modules lecturer
Contactperson for the course
dr. N. Kohn
Other course modules lecturer
dr. N. Kohn
Other course modules lecturer
Academic year2023
SEM1  (04/09/2023 to 26/01/2024)
Starting block
Course mode
Please note: if you do not yet have a master's registration, you are not yet registered for the tests for this course.
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.


Presumed foreknowledge

Test information
The course is concluded with a written exam. The exam contains of four parts based on the content of the course. This final exam makes up 80% of the grade. 3 mini-exams after the 3 major parts of the course make up the remaining 20%.

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
Test typeExam
OpportunitiesBlock SEM1, Block SEM2

NOTE: enrollment for a course automatically registers you for its exam. For participating in the resit, register again.