Exploring the Human Connectome Topology in Group Studies
This work addresses the problem of analyzing brain network differences for clinical neuroscientists, but it is incremental as it builds on existing visualization methods with specific enhancements.
The paper tackles the challenge of visually comparing brain networks (connectomes) in clinical neuroscience group studies by introducing a novel visualization tool, NeuroCave, which uses immersive visualization and clustering techniques to support tasks like patient diagnosis and treatment. In evaluations, it discovers hidden connectome patterns related to sex differences in cognitive abilities and reveals the brain's intrinsic structure through topological visualization.
Visually comparing brain networks, or connectomes, is an essential task in the field of neuroscience. Especially relevant to the field of clinical neuroscience, group studies that examine differences between populations or changes over time within a population enable neuroscientists to reason about effective diagnoses and treatments for a range of neuropsychiatric disorders. In this paper, we specifically explore how visual analytics tools can be used to facilitate various clinical neuroscience tasks, in which observation and analysis of meaningful patterns in the connectome can support patient diagnosis and treatment. We conduct a survey of visualization tasks that enable clinical neuroscience activities, and further explore how existing connectome visualization tools support or fail to support these tasks. Based on our investigation of these tasks, we introduce a novel visualization tool, NeuroCave, to support group studies analyses. We discuss how our design decisions (the use of immersive visualization, the use of hierarchical clustering and dimensionality reduction techniques, and the choice of visual encodings) are motivated by these tasks. We evaluate NeuroCave through two use cases that illustrate the utility of interactive connectome visualization in clinical neuroscience contexts. In the first use case, we study sex differences using functional connectomes and discover hidden connectome patterns associated with well-known cognitive differences in spatial and verbal abilities. In the second use case, we show how the utility of visualizing the brain in different topological space coupled with clustering information can reveal the brain's intrinsic structure.