MND Skill (Dataset-Orchestration Layer)

Overview

mnd-skill is the NeuroClaw orchestration skill for the Motor Neuron Disease (MND) dataset from OpenNeuro ds005874.

It strictly follows the NeuroClaw hierarchical design principles:

• This skill only describes WHAT needs to be done and which tool skill to delegate to.
• It contains no implementation code or concrete commands.
• All concrete execution is delegated to existing base/tool skills via claw-shell.
• Companion scripts in scripts/ provide reference implementations for BIDS validation, phenotype extraction, and QC.

Core workflow (never bypassed):

1. Identify input MND data and target modalities.
2. Generate a numbered execution plan clearly stating WHAT needs to be done and which tool skill will handle each step.
3. Present the full plan, estimated runtime, resource requirements, and risks to the user and wait for explicit confirmation ("YES" / "execute" / "proceed").
4. On confirmation, delegate every step to the appropriate skill via claw-shell.
5. After execution, save all outputs in a clean directory structure (mnd_output/).

Research use only.

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Quick Reference

Task	What needs to be done	Delegate to	Expected output
BIDS validation	Validate MND BIDS structure	scripts/validate_mnd.py	Validation report
sMRI processing	Brain extraction, tissue segmentation	smri-skill	smri_output/ derivatives
rs-fMRI processing	Preprocessing, denoising, connectivity	fmri-skill	fmri_output/ derivatives
task-fMRI processing	Motor task GLM, activation analysis	fmri-skill	fmri_output/ task results
Phenotype extraction	Diagnosis, clinical measures	scripts/extract_mnd_phenotype.py	Merged phenotype CSV
QC summary	Per-subject quality control	scripts/mnd_qc_summary.py	QC summary + exclusion list

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Dataset Characteristics

• Cohort: 59 participants
  • Patient group: Motor Neuron Disease (e.g., ALS) patients
  • Control group: Healthy age-matched controls
• Modalities: rs-fMRI, task-fMRI (motor tasks)
• Format: BIDS-compliant
• Access: OpenNeuro ds005874
• License: CC0

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Supported Modalities

Modality	Description	Tasks/Conditions
rs-fMRI	Resting-state functional MRI	Eyes open/closed
task-fMRI	Task-based functional MRI	Motor tasks (finger tapping, hand grip)

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MND Task Paradigms

Task	Description	Duration
REST	Resting-state (eyes open/closed)	~8 min
MOTOR	Motor tasks (finger tapping, hand grip)	~5 min

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BIDS Preparation

Script: scripts/validate_mnd.py

Validates MND BIDS structure and generates a compliance report.

python skills/mnd-skill/scripts/validate_mnd.py \
  --input /path/to/MND/bids \
  --output /path/to/mnd_output/qc/bids_validation.csv

Features:

• BIDS directory structure validation
• Modality completeness check (rs-fMRI, task-fMRI)
• Participant group labeling (patient vs. control)
• Missing data identification

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Core Workflow (Never Bypassed)

1. Identify user target: full MND processing, imaging subset, phenotype extraction, or BIDS validation only.
2. Generate a numbered plan with tools, outputs, runtime, storage, and risks.
3. Wait for explicit confirmation (YES / execute / proceed).
4. On confirmation, run BIDS validation using scripts/validate_mnd.py.
5. Delegate to smri-skill for structural MRI processing (if available).
6. Delegate to fmri-skill for functional MRI processing (resting-state and motor task).
7. If phenotype extraction is requested, run scripts/extract_mnd_phenotype.py.
8. If QC summary is requested, run scripts/mnd_qc_summary.py.
9. Save outputs into mnd_output/.

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Modality Processing Delegation

Modality	Delegated skill	Typical tasks	Main outputs
sMRI (T1w)	smri-skill	brain extraction, tissue segmentation	smri_output/ derivatives
rs-fMRI	fmri-skill	preprocessing, denoising, connectivity	fmri_output/ connectivity
task-fMRI	fmri-skill	motor task GLM, activation analysis	fmri_output/ task results

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Standard Output Layout

mnd_output/
├── bids/                   # BIDS-staged data (or validation report)
├── smri/                   # Structural MRI derivatives
├── fmri/                   # Functional MRI derivatives (rest + motor)
├── phenotype/              # Merged phenotype tables (diagnosis, clinical)
├── qc/                     # QC summaries and exclusion lists
└── logs/                   # Processing logs

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Benchmark Adapter Guidance

For benchmark-style prompts, do not force the full orchestration when the task only asks for local MND data validation.

• If the task starts from MND data already present on disk and only asks for BIDS validation:
  • Skip the download stage
  • Default to the narrow path local MND discovery -> BIDS validation -> report
• In benchmark mode, do not require explicit confirmation before presenting the validation solution.

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Safety and Execution Policy

• No execution before explicit plan confirmation.
• All execution must be routed via claw-shell.
• Missing dependencies must be resolved by dependency-planner before running.

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Important Notes and Limitations

• MND is a clinical cohort; patient data requires careful handling.
• Case-control matching should be verified before group comparisons.
• Motor tasks are designed to probe motor network function; standard motor task GLM applies.
• The dataset is relatively small (59 participants); statistical power may be limited.
• mnd-skill is orchestration-only; detailed preprocessing logic remains in modality skills.

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When to Call This Skill

• User asks for end-to-end MND workflow.
• User asks to process MND fMRI data.
• User needs BIDS validation for MND data.
• User asks to extract MND phenotype data (diagnosis, clinical measures).
• User asks for motor network analysis in MND patients.

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Complementary / Related Skills

• smri-skill → structural MRI preprocessing
• fmri-skill → functional MRI preprocessing and analysis
• bids-organizer → BIDS validation and organization
• brain-visualization → visualization of derivatives
• dependency-planner → dependency resolution
• conda-env-manager → environment management
• claw-shell → command execution

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Reference

• OpenNeuro ds005874: https://openneuro.org/datasets/ds005874

Created At: 2026-05-06 13:31 HKT Last Updated At: 2026-05-06 13:31 HKT Author: chengwang96