Exploring the Human Connectome Topology in Group Studies

TL;DR

This paper investigates how visual analytics tools can enhance the analysis of brain connectomes in group studies, introduces NeuroCave for immersive connectome visualization, and demonstrates its utility through clinical neuroscience case studies.

Contribution

It presents NeuroCave, a novel immersive visualization tool designed to support group connectome analysis in clinical neuroscience, addressing limitations of existing tools.

Findings

Discovered connectome patterns linked to cognitive differences.

Revealed intrinsic brain structures through visualization.

Validated NeuroCave's effectiveness in clinical case studies.

Abstract

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.