The *. mat file contains a struct, named D, which is converted to an meeg object by spm eeg load



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The *.mat file contains a struct, named D, which is converted to an meeg object by spm_eeg_load.

  • The *.mat file contains a struct, named D, which is converted to an meeg object by spm_eeg_load.

  • The *.dat file is memory-mapped and linked to the object.

  • Special functions called ‘methods’ provide a simple interface for getting information from the object and updating it and ensure that the header data remain consistent.









MEG:

  • MEG:

  • Requires quite complex sensor representation including locations and orientations of the coils and the way MEG channels are derived from the sensors.

  • Sensor representation is read automatically from the original dataset at conversion.

  • EEG:

  • Presently only requires electrode locations. In the future will also include a montage matrix to represent different referencing arrangements.

  • Usually electrode locations do not come with the EEG data.

  • SPM assigns default electrode locations for some common systems (extended 10-20, Biosemi, EGI – with user’s input).

  • Individually measured locations can be loaded; requires co-registration.



Coordinate systems can differ in their origin, units and orientation.

  • Coordinate systems can differ in their origin, units and orientation.

  • MNI coordinates are defined using landmarks inside the brain.

  • Head coordinates are defined based on the fiducials. Commonly used for MEG, but the definition differs between different MEG systems.

  • Device coordinates are defined relative to some point external to the subject and fixed with respect to the measuring device.

    • Advantage: head locations can be compared between different experiments and subjects.
    • Disadvantage: head location needs to be tracked.




In SPM8

  • In SPM8

  • Before co-registration

    • MEG sensors are represented in head coordinates in mm.
    • EEG sensors can be represented in any Cartesian coordinate system. Units are transformed to mm.
  • After co-registration

    • MEG sensor representation does not change. The head model is transformed to head coordinates.
    • EEG sensors are transformed to MNI coordinates.


Definition: Cutting segments around events.

  • Definition: Cutting segments around events.

  • Need to know:

  • What happens (event type, event value)

  • When it happens (time of the events)

  • Need to define:

  • Segment borders

  • Trial type (can be different triggers => single trial type)

  • Note:

  • SPM8 only supports fixed length trials (but there are ways to circumvent this).

  • The epoching function also performs baseline correction (using negative times as the baseline).



High-pass – remove the DC offset and slow trends in the data.

  • High-pass – remove the DC offset and slow trends in the data.

  • Low-pass – remove high-frequency noise. Similar to smoothing.

  • Notch (band-stop) – remove artefacts limited in frequency, most commonly line noise and its harmonics.

  • Band-pass – focus on the frequency of interest and remove the rest. More suitable for relatively narrow frequency ranges.







Re-referencing can be used to sensitize sensor level analysis to particular sources (at the expense of other sources).

  • Re-referencing can be used to sensitize sensor level analysis to particular sources (at the expense of other sources).

  • For other purposes (source reconstruction and DCM) it is presently necessary to use average reference. This will be relaxed in the future.

  • Re-referencing in SPM8 is done by the Montage function that can apply any linear weighting to the channels and has a wider range of applications.







































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