Multi-Modality Visualization Tool

The visualization and exploration of neuroimaging data are 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 graphical interface which enables to visualize functional and statistical data (MEG and/or fMRI) on the cortex and subcortical surfaces, invasive electrodes activity and etc. 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 supports many types of analyzed data:

  • FsFast (FreeSurfer Functional Analysis Stream)
  • SPM (Statistical Parametric Mapping)
  • MNE (a software package for processing MEG and EEG)
  • MEG raw data (fif files)
  • FieldTrip (MATLAB software toolbox for neuroimaging analysis)

The users can also reprocess raw data using wrappers for FaFast and MNE-python (a python package for sensor and source-space analysis of MEG and EEG data).

Dr. Steven M. Stufflebeam, MD

Steven Stufflebeam, MD

Associate Professor in Radiology, Harvard Medical School
Radiologist, Massachusetts General Hospital
Medical Director, Martinos Center

  • sms@nmr.mgh.harvard.edu
Noam Peled, PhD

Noam Peled, PhD

Research Fellow in Radiology, Harvard Medical School
Research Fellow, Massachusetts General Hospital

  • npeled@mgh.harvard.edu
Ohad Felsenstein, M.Sc

Ohad Felsenstein M.Sc

PhD candidate at Gonda multidisciplinary Brain Research Center, Bar-Ilan university
Israel

  • ohad.felsenstein@biu.ac.il
Natalia Rozengard

Natalia Rozengard

Research Labatory Assistant, Massachusetts General Hospital
Graphic & Web designer

  • nrozengard@mgh.harvard.edu

Acknowledgments

This tool is being developed as part of the Transform DBS project.

Sponsored by:

  • The U.S. Army Research Office and Defense Advanced Research Projects Agency under Cooperative Agreement Number W911NF-14-2-0045.
  • The NCRR (S10RR014978) and NIH (S10RR031599,R01-NS069696, 5R01-NS060918, U01MH093765)

Suggested Citation

O.Felsenstein and N. Peled et al. (2017). MMVT – Multi-Modality Visualization Tool. GitHub Repository. https://github.com/pelednoam/mmvt DOI:10.5281/zenodo.438343