nilearn-tool

Official

Nilearn-based ROI, connectivity, and GLM tools.

AuthorCUHK-AIM-Group
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Provides a reusable base/tool skill implementing concrete Nilearn workflows to turn preprocessed BOLD data into ROI time series, functional connectivity matrices, and optional GLM outputs, enabling researchers to build neuroimaging pipelines without rewriting core routines.

Core Features & Use Cases

  • ROI time series extraction from atlas/parcellation and standardization/detrending for downstream analysis
  • ROI-to-ROI connectivity computation and seed-based connectivity mapping
  • Optional first-/second-level GLM integration and basic model outputs
  • Curated reference snippets and a wrapper CLI routed through claw-shell for deterministic, reproducible results
  • Guidance on using curated snippets when implementing Nilearn-based workflows in larger experiments

Quick Start

Run the Nilearn-based tool to extract ROI timeseries and connectivity from a preprocessed BOLD image using a given atlas and output directory.

Dependency Matrix

Required Modules

nibabelnumpypandasnilearnscikit-learnscipy

Components

scripts

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: nilearn-tool
Download link: https://github.com/CUHK-AIM-Group/NeuroClaw/archive/main.zip#nilearn-tool

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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