Open-source platforms to investigate analytical flexibility in neuroimaging

Area of Science:

• Neuroimaging
• Computational Neuroscience
• Brain Imaging Analysis

Background:

• Brain imaging research faces challenges with analytical flexibility, where diverse tools yield inconsistent results on the same data.
• This variability compromises the reproducibility and robustness of neuroimaging studies.
• Existing software for addressing analytical flexibility is fragmented and poorly documented, hindering researchers' ability to ensure reliable findings.

Purpose of the Study:

• To catalog and describe software platforms for managing result variability in neuroimaging.
• To explore the use of computing platforms and neuroimaging pipeline frameworks in addressing analytical flexibility.
• To provide guidance on accessing, understanding, and utilizing these platforms to enhance brain imaging research reliability.

Main Methods:

• Systematic review and cataloging of software platforms and computational libraries relevant to neuroimaging analysis.
• Exploration of computing platforms and neuroimaging pipeline frameworks.
• Analysis of documentation and accessibility of these tools.

Main Results:

• Identified and described various software platforms and computational libraries designed to address analytical variability in brain imaging.
• Highlighted the role of computing platforms and pipeline frameworks in standardizing neuroimaging workflows.
• Assessed the current state of documentation and accessibility for tools managing analytical flexibility.

Conclusions:

• Researchers need accessible, well-documented tools to manage analytical flexibility in brain imaging.
• Utilizing cataloged software platforms and pipeline frameworks can improve the reproducibility and reliability of neuroimaging studies.
• Tailored recommendations are provided for different user groups based on their computational needs and intended tools.