MEG (Magnetoencephalography) Program

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Data preprocessing

The frequency spectrum of MEG/EEG data is rich and complex. Multiple processes take place simultaneously and engage neural populations at various spatial, temporal and frequency scales. The purpose of data pre-processing is to enhance the levels of signals of interest, while attenuating nuisances or even rejecting some episodes in the recordings that are tarnished by artifacts. In the following subsections, it is presupposed that the investigator is able to specify – even at a crude level of details – the basic temporal and frequency properties of the signals of interest carrying the effects being tested in the experiment. In a nutshell, it is important to target upfront, a well-defined range of brain dynamics in the course of the design of the paradigm and of the analysis pipeline.


(1) Digital filtering

Data filtering is a conceptually simple, though powerful technique to extract signals within a predefined frequency band of interest.

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(2) Advanced data correction techniques

Despite all the precautions to obtain clean signals from EEG and MEG sensors, electrophysiological traces are likely to be contaminated by a wide variety of artifacts.

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(3) Epoch averaging: evoked responses across trials

An enduring tradition of MEG/EEG signal analysis consists in enhancing brain responses that are evoked by a stimulus or an action, by averaging the data about each event across trials.

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(4) Epoch averaging: induced responses across trials

Massive event-related cell synchronization is not guaranteed to take place with consistent temporal phase with respect to the onset of the event. It is therefore relatively easy to imagine that averaging trials when such phase jitters occurs across event repetitions would lead to decreased effect sensitivity.

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(5) New trends and methods: connectivity/complexity analysis

The analysis of brain connectivity is a rapidly evolving field of Neuroscience, with significant contributions from new neuroimaging techniques and methods. While structural and functional connectivity has been emphasized with MRI-based techniques, the time resolution of MEG/EEG offers a unique perspective on the mechanisms of rapid neural connectivity engaging cell assemblies at multiple temporal and spatial scales.

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