MiRA › Tutorials › Brain network

How do I visualize a multilayer brain network in MiRA?

A multilayer connectome represents the brain as regions (nodes) linked by structural or functional connections, with each layer a subject, condition, or time point. MiRA renders this as a stacked 3D network in the browser — no installation, no code — and MiRA works for any unipartite multilayer network, not only ecological ones.

The dataset

The human brain structural connectome (Keresztes et al. 2022) has 3 layers, 124 nodes, 372 state nodes, and 1,827 within-layer plus 220 between-layer links. Each layer is a time point; nodes are brain regions; interlayer links couple the same region across layers. It is undirected and unipartite.

Walkthrough

Open MiRA, click Load Example Data, and choose Human brain structural connectome.
In Network Mode, rotate and pan the stacked 3D view to see the three layers and the interlayer links coupling the same regions across time.
In the Nodes panel, size nodes by degree to find hub regions, and colour by any region attribute present in the data.
Use the Intralayer Links threshold to hide weak connections and expose the strong structural backbone within each layer.
Switch to Grid View to compare the three layers as small multiples, then to Meta-Network Mode for an aggregated single-layer summary of cross-layer connectivity.
Open Dashboard Mode for degree distributions, the presence matrix, and the layer-similarity heatmap quantifying how connectivity changes between time points.

Beyond ecology. Although MiRA was built with biology in mind, it renders any multilayer network. Connectomes, protein–protein interaction networks, and social networks all load through the same JSON or CSV format.

Use your own data

Represent each subject, condition, or time point as a layer, couple repeated regions with interlayer links, and export to MiRA's JSON or CSV format. Then use Load Data and follow the same steps.