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bids-neuroimaging

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Aktualisiert1. Juli 2026 um 23:33

Plan and audit BIDS neuroimaging datasets, derivatives, validation, metadata, and reproducible preprocessing. Use when users mention BIDS, fMRI, MRI, EEG/MEG/iEEG, DICOM conversion, dataset_description.json, participants.tsv, or neuroimaging derivatives.

Installation

Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.

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Quelle

BaranziniLab

BaranziniLab/biorouter-skills

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Verwandte BerufeSOC

Basierend auf der SOC-Berufsklassifikation

Sonstige BiowissenschaftlerNatur- und Sozialwissenschaften·SOC 19-1029

SKILL.md

readonly

name	bids-neuroimaging
description	Plan and audit BIDS neuroimaging datasets, derivatives, validation, metadata, and reproducible preprocessing. Use when users mention BIDS, fMRI, MRI, EEG/MEG/iEEG, DICOM conversion, dataset_description.json, participants.tsv, or neuroimaging derivatives.
user-invocable	true
license	Apache-2.0

BIDS Neuroimaging

Source adaptation: BioRouter-original synthesis inspired by Scientific Agent Skills BIDS/neuroimaging patterns, rewritten under Apache-2.0.

When to Use

Use this skill when work touches the Brain Imaging Data Structure or neuroimaging dataset organization. Pair with biomedical-imaging-pathology for DICOM/PACS and image QC, and with neurophysiology-analysis for EEG/MEG/iEEG signal analysis.

Intake

Collect:

Modality: MRI/fMRI/dMRI, PET, EEG, MEG, iEEG, or multimodal.
Source data format and conversion path.
Dataset scope: raw BIDS, derivatives, or both.
Subject/session/task/run structure.
Required metadata sidecars and privacy constraints.
Intended pipeline: fMRIPrep, MRIQC, QSIPrep, MNE-BIDS, custom workflow, or archive deposit.

BIDS Audit

Check:

dataset_description.json, participants.tsv, README, CHANGES, and license files.
Subject/session folder naming.
Modality-specific filenames and entities.
JSON sidecars for acquisition parameters, task metadata, channels, electrodes, events, and coordinate systems.
Derivative dataset_description.json and source provenance.
Defacing/de-identification and protected metadata removal.

Validation Workflow

Run or plan bids-validator before analysis.
Separate warnings from errors and explain which affect inference.
Preserve conversion logs and DICOM/source provenance.
Check slice timing, phase encoding, intended-for fields, events timing, and channel metadata.
Confirm derivatives do not overwrite raw data.

Quality Gates

Do not treat a dataset as analysis-ready unless:

Validation status is reported.
Known validator warnings are triaged.
Subject/session/task/run counts match expectations.
Metadata needed by the preprocessing tool is present.
Privacy/de-identification status is explicit.

Output Shape

Return: dataset map, validation findings, required fixes, preprocessing route, and archive/readiness status.

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name	bids-neuroimaging
description	Plan and audit BIDS neuroimaging datasets, derivatives, validation, metadata, and reproducible preprocessing. Use when users mention BIDS, fMRI, MRI, EEG/MEG/iEEG, DICOM conversion, dataset_description.json, participants.tsv, or neuroimaging derivatives.
user-invocable	true
license	Apache-2.0

BIDS Neuroimaging

Source adaptation: BioRouter-original synthesis inspired by Scientific Agent Skills BIDS/neuroimaging patterns, rewritten under Apache-2.0.

When to Use

Intake

Collect:

Modality: MRI/fMRI/dMRI, PET, EEG, MEG, iEEG, or multimodal.
Source data format and conversion path.
Dataset scope: raw BIDS, derivatives, or both.
Subject/session/task/run structure.
Required metadata sidecars and privacy constraints.
Intended pipeline: fMRIPrep, MRIQC, QSIPrep, MNE-BIDS, custom workflow, or archive deposit.

BIDS Audit

Check:

dataset_description.json, participants.tsv, README, CHANGES, and license files.
Subject/session folder naming.
Modality-specific filenames and entities.
JSON sidecars for acquisition parameters, task metadata, channels, electrodes, events, and coordinate systems.
Derivative dataset_description.json and source provenance.
Defacing/de-identification and protected metadata removal.

Validation Workflow

Run or plan bids-validator before analysis.
Separate warnings from errors and explain which affect inference.
Preserve conversion logs and DICOM/source provenance.
Check slice timing, phase encoding, intended-for fields, events timing, and channel metadata.
Confirm derivatives do not overwrite raw data.

Quality Gates

Do not treat a dataset as analysis-ready unless:

Validation status is reported.
Known validator warnings are triaged.
Subject/session/task/run counts match expectations.
Metadata needed by the preprocessing tool is present.
Privacy/de-identification status is explicit.

Output Shape

Return: dataset map, validation findings, required fixes, preprocessing route, and archive/readiness status.