Multi-Modality Visualization Tool


The visualization and exploration of neuroimaging data is important for the analysis of anatomical and functional images and statistical parametric maps. While two-dimensional orthogonal views of neuroimaging data are used to display activity and statistical analysis, real three-dimensional (3d) depictions are helpful for showing the spatial distribution of a functional network, as well as its temporal evolution. For our best knowledge, currently there is no neuroimaging 3d tool which can visualize both MEG, fMRI and invasive electrodes (ECOG, depth electrodes, DBS, etc.). Here we present the multi-modality visualization tool (MMVT). The tool was built for researchers who wish to have a better understanding of their neuroimaging anatomical and functional data. The true power of the tool is by visualizing and analyzing data from multi-modalities. MMVT is built as two separated modules: The first is implemented as an add-on in 'Blender”, an open-source 3d visualization software. The add-on is an interactive graphic interface which enable to visualize functional and statistical data (MEG and/or fMRI) on the cortex and subcortical surfaces, invasive electrodes activity and so on. The tool can also be used for a better 3d visualization of the anatomical data and the invasive electrodes locations. The other module is a standalone software, for importing and preprocessing. The users can select the data they want to import to Blender and how they want to process it. The module support many types of analyzed data, like FsFast (FreeSurfer Functional Analysis Stream) and SPM (Statistical Parametric Mapping) for fMRI, MNE (a software package for processing MEG and EEG) raw data for MEG and FieldTrip (MATLAB software toolbox for neuroimaging analysis) data structures for the invasive electrodes. The users can also reprocess raw data using a wrappers for FaFast and mne-python (a python package for sensor and source-space analysis of MEG and EEG data)..

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More information and the code for this tool can be found on github