NeuroMArVL: An interactive and collaborative web-based tool for visualizing brain networks

Area of Science:

• Neuroscience
• Computer Science
• Data Visualization

Background:

• Brain connectivity data is complex and high-dimensional, often modeled as graphs.
• Visualizing this complexity is crucial for understanding brain networks but challenging for transparent science.
• Existing tools often lack seamless integration between physical and topological representations of brain data.

Purpose of the Study:

• Introduce NeuroMArVL, an open-source, web-based tool for brain connectome visualization.
• Enable seamless interaction and movement between physical and topological representations of connectome data.
• Facilitate transparent science through shareable visualization data and parameters.

Main Methods:

• Development of a novel, web-based visualization tool, NeuroMArVL.
• Implementation of features for seamless transition between physical and topological brain network representations.
• Inclusion of functionalities for saving and sharing visualization data and parameters.

Main Results:

• NeuroMArVL provides a unified platform for exploring complex brain connectome data.
• The tool allows users to interact with both physical and topological views of brain networks.
• Visualization parameters and data can be saved as shareable links for collaboration and reproducibility.

Conclusions:

• NeuroMArVL enhances the exploration and understanding of high-dimensional brain connectivity data.
• The tool supports transparent science by enabling easy sharing and reuse of visualization outputs.
• NeuroMArVL offers a valuable resource for neuroscientists and researchers working with complex network data.