1. Multi-Modal Neuroimaging Analysis and Visualization Tool (MMVT)
- Author
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Felsenstein, O., Peled, N., Hahn, E., Rockhill, A. P., Frank, D., Libster, A M., Nossenson, Y., Folsom, L., Gholipour, T., Macadams, K., Rozengard, N., Paulk, A. C., Dougherty, D., Cash, S. S., Widge, A. S., Hämäläinen, M., and Stufflebeam, S.
- Subjects
Quantitative Biology - Neurons and Cognition - Abstract
Sophisticated visualization tools are essential for the presentation and exploration of human neuroimaging data. While two-dimensional orthogonal views of neuroimaging data are conventionally used to display activity and statistical analysis, three-dimensional (3D) representation is useful for showing the spatial distribution of a functional network, as well as its temporal evolution. For these purposes, there is currently no open-source, 3D neuroimaging tool that can simultaneously visualize desired combinations of MRI, CT, EEG, MEG, fMRI, PET, and intracranial EEG (i.e., ECoG, depth electrodes, and DBS). Here we present the Multi-Modal Visualization Tool (MMVT), which is designed for researchers to interact with their neuroimaging functional and anatomical data through simultaneous visualization of these existing imaging modalities. MMVT contains two separate modules: The first includes complete stand-alone pre-processing pipelines, from raw data to statistical maps. The second module is an add-on to the open-source, 3D-rendering program Blender. It is an interactive graphical interface that enables users to simultaneously visualize multi-modality functional and statistical data on the cortex and in subcortical surfaces as well as the activity of invasive electrodes. This tool also enables highly accurate 3D visualization of neuroanatomy, including the location of invasive electrodes relative to brain structures. Each of the modules and module features can be integrated, separate from the tool, into existing data pipelines. MMVT leverages open-source software to build a comprehensive tool for data visualization and exploration This gives the tool a distinct advantage in both clinical and research domains as each has highly specialized visual and processing needs., Comment: 28 pages, 8 figures
- Published
- 2019