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PIPEMAT-RS: Development and Validation of a Standardized MATLAB Pipeline for Resting-State EEG Preprocessing
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The pipeline system for Octave and Matlab (PSOM): a lightweight scripting framework and execution engine for

Pierre Bellec1, Sébastien Lavoie-Courchesne, Phil Dickinson

  • 1Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, Montréal QC, Canada.

Frontiers in Neuroinformatics
|April 12, 2012
PubMed
Summary

The Pipeline System for Octave and Matlab (PSOM) offers a flexible framework for neuroimaging data analysis pipelines. This system efficiently manages complex workflows, enabling parallel processing and reproducible research for large datasets.

Keywords:
MatlabOctavehigh-performance computingneuroimagingopen-sourceparallel computingpipelineworkflow

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Area of Science:

  • Neuroimaging analysis
  • Computational neuroscience
  • Data science

Background:

  • Neuroimaging database analysis involves complex, interconnected pipelines.
  • Existing frameworks may lack flexibility or introduce new language constructs.
  • Efficient management of analysis workflows is crucial for large-scale studies.

Purpose of the Study:

  • To introduce the Pipeline System for Octave and Matlab (PSOM) as a flexible framework for neuroimaging analysis pipelines.
  • To demonstrate PSOM's capabilities in managing complex workflows and enabling reproducible research.
  • To evaluate PSOM's performance in analyzing large neuroimaging databases.

Main Methods:

  • PSOM implements pipelines using standard Matlab data structures, defining commands, options, and file management.
  • The PSOM execution engine supports parallel job execution based on dependencies and resource availability.
  • PSOM automatically tracks execution history for full reproducibility and reprocesses only necessary pipeline stages.

Main Results:

  • PSOM enables parallel processing of analysis jobs on local computing resources.
  • It generates detailed execution records for complete analysis reproducibility.
  • Benchmark experiments on a 200-subject fMRI database demonstrated PSOM's power for large-scale data analysis.

Conclusions:

  • PSOM provides a powerful, flexible, and open-source solution for implementing and managing neuroimaging analysis pipelines.
  • The framework facilitates efficient analysis of large databases using local or distributed computing.
  • PSOM supports academic and commercial use without external dependencies beyond Matlab or Octave.