Cam-CAN Pipeline (Claude Skill)

End-to-end workflow for the Cam-CAN (Cambridge Centre for Ageing and Neuroscience) dataset, including BIDS validation, multimodal processing of sMRI, rs-fMRI, task-fMRI, and MEG, phenotype extraction, and QC integration.

   
Type Claude Skill
Supplier CUHK-AIM-Group (community OSS, MIT)
Availability GA — part of the NeuroClaw neuroimaging skill library
Pricing Free / OSS (MIT)
Capabilities Read/Write — Claude runs the skill’s Python locally (Bash), not as an MCP tool

How to install

  • Claude Code — clone and copy the skill into your skills directory:
    git clone https://github.com/CUHK-AIM-Group/NeuroClaw
    cp -r NeuroClaw/skills/camcan-skill ~/.claude/skills/
    

    Project-scoped alternative: copy into .claude/skills/ instead. NeuroClaw skills assume the collection’s shared helpers (claw-shell, modality tool skills) and the upstream neuroimaging stack (FreeSurfer/FSL/fMRIPrep/etc.) — install those dependencies, or run the bundled installer for the full environment:

    cd NeuroClaw && python installer/setup.py
    

    which configures the Python env, CUDA/GPU, and the neuroimaging tools.

What it does

Use this skill whenever the user wants an end-to-end workflow for the Cam-CAN (Cambridge Centre for Ageing and Neuroscience) dataset, including BIDS validation, multimodal processing of sMRI, rs-fMRI, task-fMRI, and MEG, phenotype extraction, and QC integration. Triggers include: ‘Cam-CAN’, ‘CamCAN’, ‘process Cam-CAN data’, ‘Cam-CAN MEG’, ‘Cam-CAN fMRI’, or any request to run the Cam-CAN multimodal pipeline.

Primary use cases: ‘Cam-CAN’, ‘CamCAN’, ‘process Cam-CAN data’, ‘Cam-CAN MEG’, ‘Cam-CAN fMRI’, or any request to run the Cam-CAN multimodal pipeline.

Notes

Distributed as a SKILL.md (plus code examples) in the NeuroClaw skill library — Claude executes it locally via Bash/Python rather than as an MCP server. Upstream license: MIT. The skill directory upstream is skills/camcan-skill.

Sources


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