The overall goal of this proposal is to expand the functionality and accessibility of Mango, a widely used, freely distributed, multi-platform, software application created by the PI and colleagues as a viewing- analysis tool for the neuroimaging community. Mango's primary design is to help researchers interpret results of brain imaging studies. It supports volumetric (3-D) structural (e.g., anatomical MRI and CT) as well as 3-D/4- D functional (e.g., fMRI, PET and SPECT) images in several standard formats, including DICOM, NIfTI, and Analyze. Mango supports multi-subject processing levels including per-subject images, statistical parametric images (SPIs), resting state network images (RSNs), as well as group-wise versions of SPIs, RSNs and meta- analytic synthetic images. Mango's functionality not only emphasizes visualization (e.g., function-structure overlays, surface rending, 3-D viewing, and flexible reslicing, with anatomical atlas overlays) but also provides important analytic tools (e.g., ROI statistics, histograms, and image calculators). Interpretative descriptions, keyed by coordinates, are derived from the meta-data fields of the BrainMap database, an NIH-funded projected developed by the PIs. We propose to significantly expand Mango's interpretive functionality, accessibility, and built-in features.
Aim 1 provides extensions to Mango's regional brain 'Behavior Analysis'tool by adding 'Paradigm Analysis', interpretation for a neighborhood about an x-y-z coordinate, and synthesis of Behavioral and Paradigm 'Similarity Networks'for co-active brain regions.
Aim 3 adds important new features including automated script building, 3-D visualization enhancements (overlays and cine), and a collection of features recommended by users. The proposed continuing software development project will provide broad access to Mango's excellent visualization capabilities and literature-informed interpretations for human brain images.
|Fox, Peter T; Lancaster, Jack L; Laird, Angela R et al. (2014) Meta-analysis in human neuroimaging: computational modeling of large-scale databases. Annu Rev Neurosci 37:409-34|
|Narayana, Shalini; Zhang, Wei; Rogers, William et al. (2014) Concurrent TMS to the primary motor cortex augments slow motor learning. Neuroimage 85 Pt 3:971-84|
|McKay, D Reese; Kochunov, Peter; Cykowski, Matthew D et al. (2013) Sulcal depth-position profile is a genetically mediated neuroscientific trait: description and characterization in the central sulcus. J Neurosci 33:15618-25|