Interactive Web Application for Exploring Matrices of Neural Connectivity

TL;DR

This paper introduces a lightweight, browser-based visualization tool for exploring high-dimensional neural connectivity matrices, enabling scientists to interactively analyze complex brain data across various modalities.

Contribution

The authors developed an open-source, client-side web application that visualizes neural connectivity matrices in 3D, supporting dynamic manipulation and multi-dimensional data highlighting.

Findings

Successfully visualized ECoG connectivity data in-browser

Supports large matrices with interactive features

Eases exploration of neural connectivity patterns

Abstract

We present here a browser-based application for visualizing patterns of connectivity in 3D stacked data matrices with large numbers of pairwise relations. Visualizing a connectivity matrix, looking for trends and patterns, and dynamically manipulating these values is a challenge for scientists from diverse fields, including neuroscience and genomics. In particular, high-dimensional neural data include those acquired via electroencephalography (EEG), electrocorticography (ECoG), magnetoencephalography (MEG), and functional MRI. Neural connectivity data contains multivariate attributes for each edge between different brain regions, which motivated our lightweight, open source, easy-to-use visualization tool for the exploration of these connectivity matrices to highlight connections of interest. Here we present a client-side, mobile-compatible visualization tool written entirely in HTML5/JavaScript that allows in-browser manipulation of user-defined files for exploration of brain connectivity. Visualizations can highlight different aspects of the data simultaneously across different dimensions. Input files are in JSON format, and custom Python scripts have been written to parse MATLAB or Python data files into JSON-loadable format. We demonstrate the analysis of connectivity data acquired via human ECoG recordings as a domain-specific implementation of our application. We envision applications for this interactive tool in fields seeking to visualize pairwise connectivity.