Visualizing data mining results with the brede tools

Abstract

A few neuroinformatics databases now exist that record results from neuroimaging studies in the form of brain coordinates in stereotaxic space. The Brede Toolbox was originally developed to extract, analyze and visualize data from one of them - the BrainMap database. Since then the Brede Toolbox has expanded and now includes its own database with coordinates along with ontologies for brain regions and functions: The Brede Database. With Brede Toolbox and Database combined, we setup automated workflows for extraction of data, mass meta-analytic data mining and visualizations. Most of the Web presence of the Brede Database is established by a single script executing a workflow involving these steps together with a final generation of Web pages with embedded visualizations and links to interactive three-dimensional models in the Virtual Reality Modeling Language. Apart from the Brede tools I briefly review alternate visualization tools and methods for Internet-based visualization and information visualization as well as portals for visualization tools.

Keywords: Brede; Web service; database; meta-analysis; neuroimaging; software; text mining; visualization.

Figure 1

Meta-analytic forest plot as a Web service with studies on personality genetics. Components in the Scalable Vector Graphics image file are hyperlinked and the content may be controlled interactively through a HTML form. Recent work with image-based meta-analysis has shown the possibility of constructing sensible forest and funnel plots for functional neuroimaging data (Salimi-Khorshidi et al., 2009b).

Figure 2

WebCaret server-side display of returned coordinates from the Surface Management System Database (SumsDB) with a query on ‘middle frontal gyrus’. The right window offers some control over the rendering and the buttons in the left window may rotate the cortical surface. SumsDB allows the query on a neuroanatomical label to be invoked from another program or Web site by simple Web linking, and the Brede Wiki automatically constructs such links.

Figure 3

Two examples of coordinates in a 3D corner cube visualization. (A) Coordinates from the five studies in the Brede Database authored by Edward T. Bullmore. The 3D glyphs have type and color according to paper: Dark blue (Phillips et al., 1997), light blue (Phillips et al., 1998), light green boxes (Bullmore et al., 1996), orange spheres (Hunkin et al., 2002), red (Calvert et al., 1999). (B) Cingulate coordinates colored according to the clustering results after a text mining of abstracts in the Brede Database. Dark magenta glyphs are from the ‘memory’ cluster while the light yellow are from the ‘pain’ cluster. From Nielsen et al. (2006a).

Figure 4

VRML visualizations with coordinate-based meta-analysis of data from BrainMap with isosurfaces in conditional probability densities. (A) Gaussian mixture model of the three main behavioral domains in BrainMap: Perception (red wireframe), cognition (green surface) and motion (‘M’-textured surface). From Nielsen and Hansen (1999). (B) Kernel density modeling of auditory (red wireframe) and vision (green) studies. From Nielsen and Hansen (2000b).

Figure 5

Corner cube visualization on the Web page of the Brede Database with results from a non-negative matrix factorization of experiments in the database.

Figure 6

Screenshot of the Web page for an experiment in Brede Database with a corner cube visualization of the coordinates in a experiment together with a wireframe indicating an isosurface of the kernel density estimate with the coordinates. An interactive rendering is provided with the link to a generated corner cube visualization in a VRML file.

Figure 7

The Web-based INC Interactive Talairach Atlas queried with a coordinate from the Brede Wiki.

Figure 8

Screenshot of a VRML rendering seeking to convey parts of the information surrounding a neuroimaging study: 3D icons for funding, research organization, researchers, software, subjects, and scanner placed in a torus.

Figure 9

A so-called ‘cluster bush’ visualization of the text mining results of the abstracts in the Brede Database. Each yellow dot is a cluster of articles and words in the article. The four words with highest load on each cluster are listed.

Figure 10

A ‘functional’ atlas generated from a combined data mining of text and brain coordinates from the Brede Database. (A) Corner cube visualization with labeled brain areas. (B) Automatically generated legend with words from the text mining of abstracts.

Figure 11

Visualization of data mining result of journal co-citation analysis with singular value decomposition on citation data from NeuroImage.

Figure 12

Coauthor bullseye plot (target diagram) with data from NeuroImage 1997–2000. A line between two authors indicates that they co-wrote a paper. The concentric circles indicate the number of articles written by the author in the corpus. The Brede Toolbox automatically constructs similar, albeit smaller, bullseye visualizations for each author represented in the Brede Database author ontology. These are available on the Web.

Figure 13

For presenting the Brede Database brain region ontology on the Web the workflow with the Brede Toolbox invokes the GraphViz program which generates hyperlinked plots of the brain region hierarchy, here for the ‘posterior cingulate gyrus’.