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neural-connectivity-matrix-viewer

Visualize high-dimensional neural connectivity matrices in 3D from JSON data.

2|Updated Feb 12, 2026
Search Tags:#3d-visualization#EEG#neural#visualize#brain-connectivity#fMRI#MEG
One-click install
npx skills add https://github.com/hiyenwong/ai_collection --skill neural-connectivity-matrix-viewer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: neural-connectivity-matrix-viewer
Source: https://github.com/hiyenwong/ai_collection/tree/main/collection/skills/neural-connectivity-matrix-viewer
Command: npx skills add https://github.com/hiyenwong/ai_collection --skill neural-connectivity-matrix-viewer

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

High-dimensional neural connectivity data are difficult to interpret; this tool provides an interactive 3D visualization of brain-connectivity matrices to reveal network patterns.

Core Features & Use Cases

  • 3D stacked connectivity matrices to show source-target relationships across brain regions.
  • Multi-attribute visualization to display connection strength, distance, and other edge properties in sync.
  • Interactive exploration features including thresholding, node selection, subnetwork extraction, and dynamic rotation/zoom for intuitive data exploration.
  • Data preparation and integration workflows with Python tooling and MATLAB-to-JSON conversion examples.

Quick Start

Load a connectivity JSON and begin exploring with the threshold, node size, and color controls.

Frequently Asked Questions about neural-connectivity-matrix-viewer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I visualize a brain connectivity matrix in 3D?▼

To visualize brain connectivity in 3D, load a JSON file containing nodes and edges into the browser-based frontend. The tool renders high-dimensional neural networks as an interactive 3D stacked matrix for exploring brain region relationships.

Can I use this tool to visualize EEG and fMRI brain connectivity data?▼

Yes, the tool supports visualizing high-dimensional neural connectivity matrices from EEG, ECoG, MEG, and fMRI data. It renders brain network patterns as interactive 3D stacked matrices for exploring source-target relationships.

How do I convert MATLAB neural connectivity data to JSON for 3D visualization?▼

You convert MATLAB neural connectivity data to JSON using the provided optional Python tooling and MATLAB-to-JSON conversion examples. This prepares the required JSON nodes and edges structure for loading into the 3D visualization frontend.

What interactive features are available for exploring neural network patterns?▼

Interactive features for exploring neural network patterns include thresholding, node selection, subnetwork extraction, and dynamic rotation or zoom. Multi-attribute visualization also displays connection strength and edge distance in sync.

Does visualizing high-dimensional neural connectivity matrices require any external dependencies?▼

Visualizing high-dimensional neural connectivity matrices requires no external dependencies. The browser-based frontend loads JSON nodes and edges directly. Python tooling for data preparation and MATLAB-to-JSON conversion is entirely optional.

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