fmriprep

What problem does it solve?

fMRIPrep output review is difficult because BOLD derivatives, confounds, spaces, and reports must be interpreted together to plan downstream fMRI analysis safely and reproducibly.

Core Features & Use Cases

• Derivative & report interpretation: Understand what fMRIPrep generated (e.g., spaces, transforms, and derivative types) and how to read the per-subject HTML/QC reports.
• Confounds-driven planning: Identify high-value confound artifacts and columns (e.g., motion, DVARS, framewise displacement, aCompCor) to select what to use before analysis.
• BIDS-aware routing: Translate between BIDS inputs and fMRIPrep derivative conventions so you can route outputs into tools like Nilearn without mismatched spaces or metadata.
• Use case example: You receive a subject-level fMRIPrep derivatives folder and need to choose which confound regressors and output space to use for a first-level GLM while avoiding space/transform mismatches.

Quick Start

Use the fmriprep skill to review an existing fMRIPrep derivatives folder and recommend what confounds and output spaces are appropriate for downstream analysis planning.