Abstract
EMEGS (electromagnetic encephalography software) is a MATLAB toolbox designed to provide novice as well as expert users in the field of neuroscience with a variety of functions to perform analysis of EEG and MEG data. The software consists of a set of graphical interfaces devoted to preprocessing, analysis, and visualization of electromagnetic data. Moreover, it can be extended using a plug-in interface. Here, an overview of the capabilities of the toolbox is provided, together with a simple tutorial for both a standard ERP analysis and a time-frequency analysis. Latest features and future directions of the software development are presented in the final section.
Highlights
EMEGS is an open-source software written in MATLAB and developed for the analysis of data collected with high density, whole head electroencephalography (EEG), and magnetoencephalography (MEG)
It allows to directly perform a variety of analyses and statistical tests on event-related potentials/event-related fields (ERP/ERF) data, such as inverse source estimations, current source density functions, MEG sensor position coregistration, fast Fourier transformation, principal component analysis, t-tests, repeated measures analysis of variance (ANOVA), permutation tests, regression, and correlation. It offers integration with R environment for statistical computing, allowing the calculation of advanced factorial designs directly on EEG and MEG data. This presentation of the software will be divided into three sections, which will provide an overview of the EMEGS project (Section 1), describe its analysis and visualization features (Section 2), and provide a perspective on future directions (Section 3)
EMEGS is not recommended if integration of very detailed a priori knowledge, such as number and location of underlying neural sources, is desired
Summary
EMEGS (electromagnetic encephalography software) is an open-source software written in MATLAB and developed for the analysis of data collected with high density, whole head electroencephalography (EEG), and magnetoencephalography (MEG). It comprises batch functions to segment and filter continuous data, statistically exclude artifacts, correct eye movement artifacts, average across trials, interpolate for missing or noisy sensors, and average across participants It offers a range of visualization modules for event-related potentials/event-related fields (ERP/ERF) curve plotting, wavelet spectrograms, data projection onto 3D models (sphere, realistic, or brain), and statistical coloring of P, t, or F values. The program tries to prevent typical novice user errors by giving warning messages and suggestions in case of rather unusual parameter settings or atypical combinations of methods (e.g., baseline correction of statistical values) It provides a pipeline for all major data analysis steps beginning with data preprocessing up to the final statistical analysis and visualization of results integrated within one program, avoiding the time consuming and, especially for beginners, often error-prone application of different analysis software components.
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