MEG]PLS: A pipeline for MEG data analysis and partial least squares statistics

NeuroImage
Michael J CheungAnthony R McIntosh

Abstract

The emphasis of modern neurobiological theories has recently shifted from the independent function of brain areas to their interactions in the context of whole-brain networks. As a result, neuroimaging methods and analyses have also increasingly focused on network discovery. Magnetoencephalography (MEG) is a neuroimaging modality that captures neural activity with a high degree of temporal specificity, providing detailed, time varying maps of neural activity. Partial least squares (PLS) analysis is a multivariate framework that can be used to isolate distributed spatiotemporal patterns of neural activity that differentiate groups or cognitive tasks, to relate neural activity to behavior, and to capture large-scale network interactions. Here we introduce [MEG]PLS, a MATLAB-based platform that streamlines MEG data preprocessing, source reconstruction and PLS analysis in a single unified framework. [MEG]PLS facilitates MRI preprocessing, including segmentation and coregistration, MEG preprocessing, including filtering, epoching, and artifact correction, MEG sensor analysis, in both time and frequency domains, MEG source analysis, including multiple head models and beamforming algorithms, and combines these with a suite of PLS anal...Continue Reading

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Citations

Jun 30, 2016·Human Brain Mapping·Zainab FatimaAnthony Randal McIntosh
Dec 22, 2015·Neurobiology of Learning and Memory·Renante RondinaJennifer D Ryan
Feb 24, 2017·Nature Neuroscience·Sylvain Baillet
Sep 21, 2018·Frontiers in Neuroscience·Yegang HuYuping Wang
Apr 25, 2021·Nature Communications·Julian Q KosciessaDouglas D Garrett

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