S4: Motion Correction

Step Code: S4_motion_correction
Depends on: S3 (Functional Initialization & Crop)
Required by: S5 (Distortion Correction), S6 (Registration)

Purpose

S4 minimizes the impact of subject motion on the fMRI time series. Even small movements (< 1mm) can induce significant signal changes in spinal fMRI due to the small cross-sectional area of the cord. This step aligns all functional volumes to the robust reference created in S3.

No slice-timing correction

The pipeline performs no slice-timing correction — it never temporally resamples the BOLD series. This is a deliberate choice for cord fMRI, following the field standard (Eippert 2017; Kaptan 2023). Slice-timing metadata from the BIDS sidecar is used only later, by RETROICOR in S8, to phase the cardiac and respiratory regressors.

Algorithm Overview

The S4 step consists of two primary subtasks:

Subtask	Name	Description
S4.1	Motion Correction	Register all volumes to the reference using `sct_fmri_moco`
S4.2	Evaluation & QC	Compute motion metrics (FD, DVARS) and TSNR improvement

S4.1: Motion Correction

Rationale

Standard brain motion correction tools (like FSL MCFLIRT) assume a rigid body. The spinal cord, however, is a non-rigid structure that can deform. While fully non-rigid motion correction is complex, a slice-wise or polynomial-regularized approach is more effective for the cord. We use sct_fmri_moco with polynomial regularization to account for smooth deformations along the Z-axis.

Algorithm

Grouping - Volumes are grouped (e.g., adjacent 3-5 volumes) to improve SNR for registration if data is noisy (optional).
Registration - Each volume (or group) is registered to the S3 Robust Reference using slice-wise translation (Tx, Ty) regularized by a polynomial function along Z.
Resampling - The calculated transformations are applied to the original data using spline interpolation.

Command

sct_fmri_moco -i funccrop_bold.nii.gz -ref func_ref.nii.gz \
              -g 1 -param params.txt -x spline

QC: Motion Traces

What to look for:

✅ Smooth, low-amplitude traces (typically < 1-2 mm).
✅ Periodic motion often corresponds to respiration.
❌ FAIL: Sudden large jumps (> 2-3 mm) or continuous drift indicating scanner instability or severe patient discomfort.

S4.2: Evaluation

Rationale

We must quantify the success of motion correction. Two key metrics are used: 1. DVARS (Derivative of VARiance): Measures frame-to-frame intensity changes. Spikes in DVARS indicate sudden motion. 2. tSNR (temporal Signal-to-Noise Ratio): The mean signal divided by the standard deviation over time. Effective motion correction should increase tSNR in the cord.

Algorithm

Compute DVARS on the motion-corrected data.
Compute tSNR before and after motion correction.
Generate QC Reportlets.

QC: DVARS Plot

What to look for:

✅ Few or no spikes crossing the outlier threshold (dashed line).
✅ Lower overall variability compared to raw data (if plotted together).

QC: tSNR Comparison

What to look for:

✅ Right side (After) should be brighter/redder (higher tSNR) than the Left side (Before), especially inside the cord.
✅ Cord structure should be sharper.
❌ FAIL: tSNR decreases or cord becomes blurry.

Outputs

Derivatives

derivatives/spineprep/{dataset}/sub-{id}/func/
├── sub-{id}_task-{task}_desc-moco_bold.nii.gz        # Motion-corrected 4D data
├── sub-{id}_task-{task}_desc-moco_mean.nii.gz        # Mean of moco_bold
├── sub-{id}_task-{task}_desc-moco_params.tsv         # Motion parameters (Tx, Ty per frame)
└── sub-{id}_task-{task}_desc-confounds_timeseries.tsv # Updated with FD/DVARS

derivatives/spineprep/{dataset}/sub-{id}/figures/
├── sub-{id}_..._desc-S4_motion_traces.png
├── sub-{id}_..._desc-S4_dvars_plot.png
└── sub-{id}_..._desc-S4_tsnr_comparison.png

CLI Usage

# Run S4 for a single dataset
poetry run spineprep run S4_motion_correction \
  --dataset-key <KEY> \
  --datasets-local config/datasets_local.yaml \
  --out work/example

QC Status Logic

status = FAIL if:
  - Max displacement > 3mm (Tx or Ty)
  - Mean FD > 0.5mm
  - tSNR improvement < 0% (worsened)

status = WARN if:
  - Max displacement > 2mm
  - > 20% frames define as high motion (FD > 0.5mm)
  - tSNR improvement < 5%

status = PASS otherwise

References

SCT Motion Correction: De Leener et al. NeuroImage 145:24-43 (2017). DOI
Framewise Displacement (FD): Power et al. NeuroImage 59(3):2142-2154 (2012).

Last updated: February 2026