[Paper Review] Gradients of brain organization: Smooth sailing from methods development to user community

Jessica Royer, Casey Paquola+11 more|arXiv (Cornell University)|Feb 16, 2024

Neuroscience, Education and Cognitive Function6 citations

TL;DR

This perspective reviews how gradient approaches to brain organization expanded from methodological development to broad community adoption, driven by data sharing, open-source tools, and inclusive workshops.

ABSTRACT

Multimodal neuroimaging grants a powerful in vivo window into the structure and function of the human brain. Recent methodological and conceptual advances have enabled investigations of the interplay between large-scale spatial trends, or gradients, in brain structure and function, offering a framework to unify principles of brain organization across multiple scales. Strong community enthusiasm for these techniques has been instrumental in their widespread adoption and implementation to answer key questions in neuroscience. Following a brief review of current literature on this framework, this perspective paper will highlight how pragmatic steps aiming to make gradient methods more accessible to the community propelled these techniques to the forefront of neuroscientific inquiry. More specifically, we will emphasize how interest for gradient methods was catalyzed by data sharing, open-source software development, as well as the organization of dedicated workshops led by a diverse team of early career researchers. To this end, we argue that the growing excitement for brain gradients is the result of coordinated and consistent efforts to build an inclusive community and can serve as a case in point for future innovations and conceptual advances in neuroinformatics. We close this perspective paper by discussing challenges for the continuous refinement of neuroscientific theory, methodological innovation, and real-world translation to maintain our collective progress towards integrated models of brain organization.

Motivation & Objective

• Summarize current literature on brain gradients and their organizational principle across scales.
• Highlight pragmatic steps that made gradient methods accessible to the neuroscience community.
• Argue that community-building efforts propelled the adoption and impact of gradient methods.
• Discuss challenges for refining neuroscientific theory, methods, and translation.
• Propose a model where coordinated, inclusive community practices sustain progress in neuroinformatics.

Proposed method

• Synthesize recent literature on brain gradients and their conceptual unification across brain structure and function.
• Emphasize the role of data sharing and open-source software in method dissemination.
• Highlight the impact of community activities (workshops, diverse leadership) on method uptake.
• Argue for a coordinated community approach as a blueprint for future neuroinformatics innovations.

Experimental results

Research questions

• RQ1 How have gradient methods for brain organization achieved widespread adoption in neuroscience?
• RQ2 What community practices (data sharing, software, workshops) most effectively catalyzed this adoption?
• RQ3 What challenges remain for refining gradient-based theories and translating them to real-world applications?

Key findings

• Gradient methods benefited from data sharing and open-source software, accelerating their adoption.
• Dedicated workshops and inclusive leadership by early-career researchers helped build a vibrant user community.
• Community-driven efforts are presented as a successful model for future neuroinformatics innovations.