Studying the behavior of individual members in communities of dynamic networks can help neuroscientists understand how interactions between neurons in brain networks change over time. Visualizing those temporal features is challenging, especially for networks embedded within spatial structures, such as brain networks.
Two projects led by Chihua Ma, Animated dual-representation
, provide visual analytics tools to better understand how the functional behavior of the brain changes over time, how such behaviors are related to the spatial structure of the brain, and how communities of neurons with similar functionality evolve over time.
The first project was presented at EuroVis’15
and incorporates interactive animated dual-representation of the connectivity between brain regions as it changes over time. The enhanced node-link diagram and distance matrix visualizations are coordinated, each serving as interfaces for each other to better enable visual analytics tasks using dynamic brain network data. The second project was recently accepted for publication in the Journal of Imaging Science and Technology
; it provides a novel interactive multi-view visualization system to assist neuroscientists in their exploration of dynamic brain networks from multiple perspectives. These projects are collaborations with the computer scientists Tanya Berger-Wolf, Robert Kenyon, and Angus Forbes of UIC, and the neuroscientist Daniel Llano of UIUC.