title: CEREBRA: a 3-D visualization tool for brain network extracted from fMRI data.
abstract: In this paper, we introduce a new tool, CEREBRA, to visualize the 3D network of human brain, extracted from the fMRI data. The tool aims to analyze the brain connectivity by representing the selected voxels as the nodes of the network. The edge weights among the voxels are estimated by considering the relationships among the voxel time series. The tool enables the researchers to observe the active brain regions and the interactions among them by using graph theoretic measures, such as, the edge weight and node degree distributions. CEREBRA provides an interactive interface with basic display and editing options for the researchers to study their hypotheses about the connectivity of the brain network. CEREBRA interactively simplifies the network by selecting the active voxels and the most correlated edge weights. The researchers may remove the voxels and edges by using local and global thresholds selected on the window. The built-in graph reduction algorithms are then eliminate the irrelevant regions, voxels and edges and display various properties of the network. The toolbox is capable of space-time representation of the voxel time series and estimated arc weights by using the animated heat maps.
authors.forename: Baris
authors.initials: B
authors.lastname: Nasir
authors.forename: Fatos T
authors.initials: FT
authors.lastname: Yarman Vural
mesh_terms: D000465:Algorithms; D001921:Brain / Q000000981:diagnostic imaging*; D001931:Brain Mapping; D006801:Humans; D008279:Magnetic Resonance Imaging