Visual analytics of brain networks

Identification of regions of interest (ROIs) is a fundamental issue in brain network construction and analysis. Recent studies demonstrate that multimodal neuroimaging approaches and joint analysis strategies are crucial for accurate, reliable and individualized identification of brain ROIs. In this paper, we present a novel approach of visual analytics and its open-source software for ROI definition and brain network construction. By combining neuroscience knowledge and computational intelligence capabilities, visual analytics can generate accurate, reliable and individualized ROIs for brain networks via joint modeling of multimodal neuroimaging data and an intuitive and real-time visual analytics interface. Furthermore, it can be used as a functional ROI optimization and prediction solution when fMRI data is unavailable or inadequate. We have applied this approach to an operation span working memory fMRI/DTI dataset, a schizophrenia DTI/resting state fMRI (R-fMRI) dataset, and a mild cognitive impairment DTI/R-fMRI dataset, in order to demonstrate the effectiveness of visual analytics. Our experimental results are encouraging. Prediction of missing ROI (Region of Interest) by visual analytics. (a): left occipital pole ROIs (highlighted in red) from 10 subjects with fiber tracts overlaid. (b) and (c) compare the prediction results by FSL FLIRT registration (b) and by our visual analytics (c). The ROIs are highlighted by yellow arrows. In each panel, the first image and third image show the ROI location from different views. The second image shows the corresponding fiber tracts, and the fourth image shows the functional connectivity network. ⺠Joint representation of multimodal brain imaging data. ⺠Real-time visualization and interaction of multimodal information for brain network nodes. ⺠Accurately predicting missing ROIs for individuals. ⺠Significantly improved accuracy in identifying brain ROIs and networks. ⺠Publicly available source codes and binaries for multiple operating systems.