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EEG and MEG data analysis in SPM8.

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TLDR
SPM8 is integrated with the FieldTrip toolbox, making it possible for users to combine a variety of standard analysis methods with new schemes implemented in SPM and build custom analysis tools using powerful graphical user interface (GUI) and batching tools.
Abstract
SPM is a free and open source software written in MATLAB (The MathWorks, Inc.). In addition to standard M/EEG preprocessing, we presently offer three main analysis tools: (i) statistical analysis of scalp-maps, time-frequency images, and volumetric 3D source reconstruction images based on the general linear model, with correction for multiple comparisons using random field theory; (ii) Bayesian M/EEG source reconstruction, including support for group studies, simultaneous EEG and MEG, and fMRI priors; (iii) dynamic causal modelling (DCM), an approach combining neural modelling with data analysis for which there are several variants dealing with evoked responses, steady state responses (power spectra and cross-spectra), induced responses, and phase coupling. SPM8 is integrated with the FieldTrip toolbox , making it possible for users to combine a variety of standard analysis methods with new schemes implemented in SPM and build custom analysis tools using powerful graphical user interface (GUI) and batching tools.

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Journal ArticleDOI

MEG and EEG data analysis with MNE-Python

TL;DR: MNE-Python as discussed by the authors is an open-source software package that provides state-of-the-art algorithms implemented in Python that cover multiple methods of data preprocessing, source localization, statistical analysis, and estimation of functional connectivity between distributed brain regions.
Journal ArticleDOI

MNE software for processing MEG and EEG data

TL;DR: Detailed information about the MNE package is given and typical use cases are described while also warning about potential caveats in analysis.

MEG and EEG data analysis with MNE-Python

TL;DR: MNE-Python is an open-source software package that addresses this challenge by providing state-of-the-art algorithms implemented in Python that cover multiple methods of data preprocessing, source localization, statistical analysis, and estimation of functional connectivity between distributed brain regions.
Journal ArticleDOI

Brain templates and atlases

TL;DR: This review article summarizes the evolution of stereotaxic space in term of the basic principles and associated conceptual challenges, the creation of population atlases and the future trends that can be expected in atlas evolution.
Journal ArticleDOI

EEG Source Imaging: A Practical Review of the Analysis Steps.

TL;DR: This review explains several steps needed to pass from the recording of the EEG to 3-dimensional images of neuronal activity and illustrates them in a comprehensive analysis pipeline integrated in a stand-alone freely available academic software: Cartool.
References
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