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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Multilayer brain network visualisation | MiRA Multilayer Network Visualisation</title>
<meta name="description"
content="Step-by-step walkthrough for visualizing a multilayer human brain connectome in MiRA, using the structural connectome dataset (Keresztes et al. 2022) with layers as time points.">
<link rel="canonical" href="https://mira.ecomplab.com/tutorial-brain-network.html">
<link rel="icon" type="image/svg+xml" href="assets/favicon.svg">
<meta property="og:type" content="article">
<meta property="og:site_name" content="MiRA — Multilayer Network Visualisation">
<meta property="og:title" content="Multilayer brain network visualisation with MiRA">
<meta property="og:description" content="Visualize a multilayer human brain connectome in the browser, no installation or code.">
<meta property="og:url" content="https://mira.ecomplab.com/tutorial-brain-network.html">
<meta property="og:image" content="https://mira.ecomplab.com/assets/social-card.png">
<meta name="twitter:card" content="summary_large_image">
<meta name="twitter:title" content="Multilayer brain network visualisation with MiRA">
<meta name="twitter:description" content="A connectome walkthrough using the Keresztes et al. 2022 dataset.">
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<link rel="stylesheet" href="css/content.css">
</head>
<body>
<header class="topbar">
<div class="inner">
<a href="index.html"><img src="assets/MiRA_logo.svg" alt="MiRA — Multilayer Interactive Rendering Application"></a>
<nav>
<a href="index.html">App</a>
<a href="docs/manual.html">Manual</a>
<a href="data-format.html">Data format</a>
<a href="compare.html">Why MiRA</a>
<a href="https://github.com/Ecological-Complexity-Lab/MiRA">GitHub</a>
</nav>
</div>
</header>
<div class="wrap">
<p class="crumbs"><a href="index.html">MiRA</a> › Tutorials › Brain network</p>
<h1>How do I visualize a multilayer brain network in MiRA?</h1>
<p class="lead">
A <strong>multilayer connectome</strong> 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.
</p>
<h2>The dataset</h2>
<p>
The <strong>human brain structural connectome</strong>
(<a href="https://doi.org/10.1038/s41598-022-06697-4">Keresztes et al. 2022</a>) 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.
</p>
<h2>Walkthrough</h2>
<ol class="steps">
<li>Open <a href="index.html">MiRA</a>, click <strong>Load Example Data</strong>, and choose
<em>Human brain structural connectome</em>.</li>
<li>In <strong>Network Mode</strong>, rotate and pan the stacked 3D view to see the three
layers and the interlayer links coupling the same regions across time.</li>
<li>In the <strong>Nodes</strong> panel, size nodes by degree to find hub regions, and colour
by any region attribute present in the data.</li>
<li>Use the <strong>Intralayer Links</strong> threshold to hide weak connections and expose
the strong structural backbone within each layer.</li>
<li>Switch to <strong>Grid View</strong> to compare the three layers as small multiples, then
to <strong>Meta-Network Mode</strong> for an aggregated single-layer summary of cross-layer
connectivity.</li>
<li>Open <strong>Dashboard Mode</strong> for degree distributions, the presence matrix, and
the layer-similarity heatmap quantifying how connectivity changes between time points.</li>
</ol>
<div class="callout">
<strong>Beyond ecology.</strong> 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 <a href="data-format.html">JSON or CSV format</a>.
</div>
<h2>Use your own data</h2>
<p>
Represent each subject, condition, or time point as a layer, couple repeated regions with
interlayer links, and export to MiRA's <a href="data-format.html">JSON or CSV format</a>. Then
use <strong>Load Data</strong> and follow the same steps.
</p>
<footer class="site">
MiRA (Multilayer Interactive Rendering Application) —
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<a href="docs/manual.html">manual</a> ·
<a href="compare.html">tool comparison</a> ·
<a href="https://arxiv.org/abs/2605.09597">preprint</a>
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