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fMRI-Preprocessing

Shell-based fMRI preprocessing and denoising pipelines used to compare the effect of different noise-removal strategies on the identification of resting-state networks (RSNs).

The repository implements multiple preprocessing and denoising variants based on motion regression, ICA-based cleanup (ICA-FIX), physiological signal regression, and their combinations.

Preprocessing outputs are used for group- and subject-level ICA analyses, followed by template matching with standard RSN's templates (Smith et al., 2009; Yeo et al, 2011).

Pipeline overview

The workflow is organized into three main stages: dataset configuration, preprocessing and denoising, and RSN extraction and evaluation.

1. Dataset and pipeline configuration

  • Edit settings_dataset.sh to define dataset-specific parameters.
  • Define dataset, task, run and denoise pipeline in main1.sh and main2.sh.

2. Preprocessing and denoising

  • Run main1.sh to perform initial (minimal) preprocessing.
  • Classify unknown ICA components returned by ICA-FIX and edit the corresponding .txt file in the mel.ica output directory.
  • Edit and run main2.sh to select and apply the denoising pipeline and registration options.

Supported denoising steps include:

  • Minimal preprocessing baseline: - B0 distortion correction, - Motion realignment, - Spatial smoothing, - High-pass temporal filtering
  • Motion realignment parameter regression
  • Motion outlier regression
  • ICA-based denoising using ICA-FIX
  • Regression of cerebrospinal fluid (CSF) and white matter (WM) signals
  • Single- and multi-stage nuisance regression strategies

3. ICA and RSN analysis

  • Perform ICA:
    • Group ICA: perform_group_ica.sh (preferred)
    • Single-session ICA: perform_singlesession_ica.sh
  • Match ICA components to reference RSN templates:
    • Group ICA: perform_group_ica2.sh (define the reference RSN template)
    • Single-session ICA: compute_dice.sh (define the reference RSN template)
  • Extract RSN features:
    • Group ICA: extract_rsns_group_features.sh
    • Single-session ICA: extract_rsns_features.sh

All scripts are intended to be opened and edited to define input variables prior to execution.

Software dependencies

All preprocessing, denoising, registration, and ICA steps in this repository are implemented using tools from (FMRIB Software Library) and executed via shell scripting.