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Revision 12 as of 2021-08-06 19:18:02
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MEG corticomuscular coherence

Authors: Raymundo Cassani

Corticomuscular coherence relates to the synchrony between electrophisiological signals (MEG, EEG or ECoG) recorded from the contralateral motor cortex, and EMG signal from a muscle during voluntary movement. This synchrony has its origin mainly in the descending communication in corticospinal pathways between primary motor cortex (M1) and muscles. This tutorial replicates the processing pipeline and analysis presented in the Analysis of corticomuscular coherence FieldTrip tutorial.

Contents

  1. Background
  2. Dataset description
  3. Download and installation
    1. Download and installation
  4. Importing anatomy data
  5. Access the recordings
  6. Handle events
  7. Pre-process recordings
  8. Importing the recordings
    1. Epoching
  9. Source analysis
  10. Coherence
    1. Sensor level
    2. Source level
  11. Script
  12. Additional documentation

Background

Coherence is a classic method to measure the linear relationship between two signals in the frequency domain. Previous studies (Conway et al., 1995, Kilner et al., 2000) have used coherence to study the relationship between MEG signals from M1 and muscles, and they have shown synchronized activity in the 15–30 Hz range during maintained voluntary contractions.

IMAGE OF EXPERIMENT, SIGNALS and COHERENCE

Dataset description

The dataset is comprised of MEG and EMG recordings recorded from one subject in a experiment in which the subject

to lift her hand and exert a constant force against a lever. The force was monitored by strain gauges on the lever. The subject performed two blocks of 20 trials in which either the left or the right wrist was extended for about 10 seconds.

We will calculate the coherence between the MEG and the EMG when the subject extended her LEFT wrist, while keeping the right forearm muscle relaxed. The first step is to read the data. In this section we will apply automatic artifact rejection. Preprocessing requires the original MEG dataset, which is available from ftp://ftp.fieldtriptoolbox.org/pub/fieldtrip/tutorial/SubjectCMC.zip.

Download and installation

  • Requirements: You have already followed all the introduction tutorials and you have a working copy of Brainstorm installed on your computer.

  • Go to the Download page of this website, and download the file: sample_epilepsy.zip

  • Unzip it in a folder that is not in any of the Brainstorm folders (program folder or database folder)

  • Start Brainstorm (Matlab scripts or stand-alone version)
  • Select the menu File > Create new protocol. Name it "TutorialEpilepsy" and select the options:

    • "No, use individual anatomy",

    • "No, use one channel file per acquisition run".

Download and installation

ftp://ftp.fieldtriptoolbox.org/pub/fieldtrip/tutorial/SubjectCMC.zip

The next sections will describe how to link import the subject's anatomy, reviewing raw data, managing event markers, pre-processing, epoching, source estimation and computation of coherence in the sensor and sources domain. Only data for the lifting with the left hand is analyzed.

Importing anatomy data

1. Create protocol 1.

Access the recordings

1. How to link the MEG recordings

Handle events

Fusion all the left events

Pre-process recordings

Removing artifacts

Importing the recordings

Epoching

Source analysis

Coherence

Sensor level

Source level

Script

This should be label as advanced.

Additional documentation

Articles

  • Conway BA, Halliday DM, Farmer SF, Shahani U, Maas P, Weir AI, et al.
    Synchronization between motor cortex and spinal motoneuronal pool during the performance of a maintained motor task in man.
    The Journal of Physiology. 1995 Dec 15;489(3):917–24.

  • Kilner JM, Baker SN, Salenius S, Hari R, Lemon RN.
    Human Cortical Muscle Coherence Is Directly Related to Specific Motor Parameters.
    J Neurosci. 2000 Dec 1;20(23):8838–45.

  • Liu J, Sheng Y, Liu H.
    https://doi.org/10.3389/fnhum.2019.00100Corticomuscular%20Coherence%20and%20Its%20Applications:%20A%20Review. Front Hum Neurosci. 2019 Mar 20;13:100.

Tutorials

  • Tutorial: Volume source estimation

Forum discussions

  • Forum: Minimum norm units (pA.m): http://neuroimage.usc.edu/forums/showthread.php?1246





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