Lauri Parkkonen - Introduction to MEG
Welcome to this module on MEG basics! The following lectures will give you the theoretical background you need for MEG practice. You may expect information about the neurophysiological bases of M/EEG signals, advantages of MEG compared to other neuroimaging techniques and how are brain responses recorded in MEG. Besides, most frequent artefacts and basic steps in MEG data analysis are described, along with and a brief overview of the instrumentation needed.
Lecture 1: Introduction to MEG
Lecture 2: Principles of MEG and EEG
Lecture 3: The neurophysiological origin of MEG signals
Lecture 4: MEG and other neuroimaging methods
Lecture 5: MEG responses
Lecture 6: Basic concepts in MEG data analysis
Lecture 7: MEG instrumentation
Neurons are said to be active when they “talk to each other”, generating electromagnetic activity. EEG measures this activity through the potential distributed on the scalp, while MEG picks it up from the magnetic fields that extend from them outside the head.
Both MEG and EEG reflect the changes in neural activity over time, by tracking responses to external stimuli or time-dependant performance. This is then often combined with MRI to see the anatomical structure.
MEG and EEG signals are weak and need to be summed to be detectable. Temporal summation occurs in post-synaptic activity, which is slower than the presynaptic action potentials. Spatial summation is possible thanks to dendrites of pyramidal neurons, which are perpendicular to cortical surface. Also, concepts in MEG physics: impressed, primary and return (volume) currents; signal depth, cancellation, amplitude and strength factors, dipole moment, etc.
MEG is a direct non-invasive measurement of neural activity with high temporal resolution and decent spatial resolution. M/EEG have a very good temporal resolution, of the order of milliseconds, while in fMRI is of the order of seconds. However, spatial resolution much better fMRI, so they are worth combining. Regarding invasiveness: EEG/MEG/fMRI are non-invasive compared to PET/SPECT/FCoG/sEEG.
MEG responses are measured for any kind of stimuli or during resting state. There are evoked responses: synchronised to stimuli where we use trial averaging and control for habituation; and there are induced responses: oscillatory changes not locked to stimulation, where we average instantaneous amplitude instead of trials. The latter accounts for changes in functional connectivity between brain regions.
This is an of the steps in MEG data analysis: signal processing techniques to improve signal-to-noise ratio, source modelling techniques to estimate the location of neural activity (i.e. dipole modelling), visualization of the source superimposed on anatomical information, interferences suppression (external, magnetic interferences, biological artefacts…), filtering signal to the desired frequency band, independent component analysis, trial averaging, etc.
As MEG signals are extremely weak, we need a particular kind of instrumentation to pick them up: a magnetically shielded room is required to avoid external interference, given the relative weakness of our signal and superconductive quantum interference devices (SQUIDS) are key to record the signals. Different sensors are used: magnetometers, axial gradiometers and planar gradiometers. Superconductivity is achieved with liquid helium in which the sensors are embedded, kept at -269º Celsius.