fMRI Preprocessing Pipeline Guide
fMRI Preprocessing Pipeline Guide
Purpose
fMRI preprocessing transforms raw scanner data into a form suitable for statistical analysis. Unlike generic data cleaning, every preprocessing decision in fMRI involves domain-specific trade-offs: choosing the wrong step order can introduce artifacts that mimic neural signal, smoothing at the wrong scale destroys the spatial information needed for multivariate analyses, and failing to correct for susceptibility distortions misaligns brain regions by several millimeters.
A competent programmer without neuroimaging training would get many of these decisions wrong. This skill encodes the domain knowledge required to make correct preprocessing choices for different analysis goals.
When to Use This Skill
- Setting up a preprocessing pipeline for task fMRI, resting-state fMRI, or MVPA
- Choosing between preprocessing tools (fMRIPrep, FSL, SPM, AFNI)
- Deciding which steps to include, skip, or modify for a specific analysis type
- Performing quality control on preprocessed data
- Reviewing or troubleshooting an existing preprocessing pipeline
- Selecting parameters for motion correction, smoothing, or normalization
Research Planning Protocol
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