VRNConnect: Towards More Intuitive Interaction of 3D Brain Connectivity Data in Virtual Environments

With more and more availability of both functional Magnetic Resonance Imaging (fMRI) and Diffusion Tensor Imaging (DTI), there is increasing interest and evidence that brain network analysis can enable new possibilities to understand brain function and disease. We have developed an open-source virtual reality (VR) platform, VRNConnect, for exploring brain connectivity data to enable researchers, students, and clinicians to map the different regions of the brain and study their functions in a more interactive, intuitive and engaging way. VRNConnect allows users to interact with the data to view various graph network measurements such as node strength, degree, and clustering coefficient by using the Brain Connectivity Analysis tools during runtime. We performed a user study to de-termine the intuitiveness and usability of the platform as well as looked at differences in controller versus gesture interaction methods. Results showed that VRNConnect is easy to use, easy to learn and intuitive. In terms of the interaction methods, almost all participants performed significantly better, doing tasks with the controller as opposed to hand gestures in both task completion time and task errors. VRNConnect showed promising results in both usability scale (SUS) and cognitive load (NASA TLX), showing the potential to be used as an academic and analytical tool, with a customizable design for importing connectivity data from different modalities and flexible and intuitive interaction methods.