neuroimaging-qc

Features and purpose

Evidence-based QC decision-making for neuroimaging data. Interpret QC metrics from any pipeline (fMRIPrep, MRIQC, FreeSurfer, MNE-Python, Homer3, custom outputs) to make justified inclusion/exclusion decisions. Covers fMRI, EEG, fNIRS, and structural MRI across populations (adults, infants, adolescents, clinical) and paradigms (resting-state, task, naturalistic, sleep). Use when filtering subjects based on QC outputs, setting exclusion thresholds, justifying QC criteria for methods sections, or parsing QC files programmatically with Python.

Quick start

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.