This course on MEG is an introduction to methods for processing MEG data (e.g., brain connectivity). The lecture is complemented by hands-on sessions and independent study.
Parts of the lecture and exercises will be based on the textbook by
Hansen PC, Kringelbach ML, Salmelin R (2010) MEG: An Introduction to Methods, Oxford Univ Press, http://doi.org/10.1093/acprof:oso/9780195307238.001.0001
The textbook is freely available on the internet:https://brainmaster.com/software/pubs/brain/MEG%20-%20An%20Intro.pdf
Students do not have to have the book at hand to follow the course.
Students will gain theoretical and practical knowledge on magnetoencephalography and various methods and techniques.
Students learn concepts of brain sciences such as the neuron doctrine, how to measure neural activity outside the skull, questioning and interpreting such recordings. In particular, we will elaborate on the electromagnetic field of the brain and relate techniques that are capable of picking up components of brain activity.
1) Defines the components of magnetoencephalography (MEG) instrumentation and recording MEG from the human body.
2) Explains the topics that must be taken into account during data acquisition.
In this course we will present the theoretical concepts, neurophysiological principles and neurocognitive and clinical applications of MEG. We will also discuss the simultaneous recording of MEG with electroencephalogram (EEG) and the application of transcranial electrical stimulation such as transcranial alternating current stimulation (tACS), as it is particularly suitable for modulating brain oscillations that have been shown to correlate with cognitive processes.
Part 1: Introduction to electro- & magnetoencephalography (lecture)
Historical overview of magnetoencephalography - physics
What do we measure - physiology (collective activity)?
Different sensor (planar, gradient, SQUIDs, OPMs) and shielding techniques
The use of magnetoencephalography in cognitive neuroscience, brain science and other sciences - experimental
Parameters (noise sources, MEG compatibility)
Inverse problem and forward modelling
Source reconstruction methods (scanning and inverse methods)
Technical aspects (artefact correction, modelling current flow, etc.)
Safety issues and ethical considerations
Part 2: MEG in the practice (seminar)
Ongoing MEG, brain states, and event-related fields (ERF)
Data (pre)processing, sensor and source space
Physical concepts of source separation and noise reduction
Modulating cognitive functions (e.g. memory, attention, and perception)
Clinical applications of MEG
Hands-on experience in the MEG facilities of the neuroimaging center