1. A method for visualizing brain network connectivity in 3-dimensions (3D), comprising: receiving image data corresponding to a brain of interest; constructing a brain network from the image data by recursively clustering network nodes using knowledge of brain networks, wherein centroids of hierarchical clusters are determined and used as nodes to construct hierarchical brain networks to guide connections of a target network of the whole brain, wherein edges are started from leaf nodes and then converged toward ancestor nodes; rendering edges between nodes using B-Spline curves constructed from control points found by searching for a nearest common ancestor of two related nodes of the target network from the hierarchical brain networks; duplicating at least one control point for spline edges sharing a common ancestor to create an extra copy of said at least one control point; bundling spline edges by applying a global strength parameter β; displaying a 3D visualization of the brain network connectivity by rendering left/right view images into a frame buffer object (FBO) at full screen resolution, and attaching content from the FBO as textures to a corresponding viewer or viewers; and coloring edges by an alpha blending technique that blends a color of a start node and a color of an end node, wherein a local blending factor is a normalized distance to the start node and a global blending factor is a normalized line length.