Multimodal Brain Visualization

TL;DR

This paper presents a new interactive visualization method for human brain connectivity data that simplifies complex MRI-based diagrams, making them more intuitive and easier to explore across multiple datasets and modalities.

Contribution

It introduces shape-preserving 2D and 3D mappings of cortical surfaces and clustering of MRI connections to create more accessible and interactive brain connectivity visualizations.

Findings

Visualizations are more intuitive and easier to compute.

Facilitates exploration of multiple datasets and modalities.

Improves understanding of brain connectivity structures.

Abstract

Current connectivity diagrams of human brain image data are either overly complex or overly simplistic. In this work we introduce simple yet accurate interactive visual representations of multiple brain image structures and the connectivity among them. We map cortical surfaces extracted from human brain magnetic resonance imaging (MRI) data onto 2D surfaces that preserve shape (angle), extent (area), and spatial (neighborhood) information for 2D (circular disk) and 3D (spherical) mapping, split these surfaces into separate patches, and cluster functional and diffusion tractography MRI connections between pairs of these patches. The resulting visualizations are easier to compute on and more visually intuitive to interact with than the original data, and facilitate simultaneous exploration of multiple data sets, modalities, and statistical maps.