Abstract Brain connectivity data are high-dimensional and are often modelled as graphs comprising in the order of ∼102–104 nodes connected by around 103–106 edges. Generating useful visualizations is essential for reducing and understanding such complexity. Indeed, this complexity offers a particular challenge for transparent science, since investigators must often choose a specific snapshot of a visualization for publication that often overlooks much of the rich detail present in the data. A further challenge for neuroscience is that brains are physical systems, and it is often important to consider how topological properties of the connectome, which can be visualized within arbitrarily abstract spaces, relate to their physical embedding. Most available tools offer visualizations for physically or topologically embedded representations without a clear mapping between the two. Here, we introduce NeuroMArVL, a novel, open-source web-based brain connectome visualisation tool that offers numerous features for moving seamlessly between, and interacting with, different physical and topological representations of connectome data. Critically, visualisation data and parameters can be saved locally or on the webserver as shareable links, facilitating reuse, collaboration, and open, transparent reporting of results in publications. The software can be freely accessed at https://immersive.erc.monash.edu/neuromarvl/.
Adamson et al. (Mon,) studied this question.