The collaborative is an ad hoc activity convened under the auspices of the Forum on Neuroscience and Nervous System Disorders at the National Academies of Sciences, Engineering, and Medicine (the National Academies). The work it produces does not necessarily represent the views of any one organization, the Forum, or the National Academies, and is not subjected to the review procedures of, nor is it a report or product of, the National Academies.

Neuroscience research in the 21st century has undergone a rapid expansion. Basic, translational, and clinical investigations are generating increasingly complex and large data sets, and innovation in the field increasingly requires large collaborations. Given the intricacy and interconnectedness of the brain, researchers generate data and use tools that often go beyond the storage and computational capacity of local resources. Cloud computing has evolved to support use of data aggregated from different research groups or locations, opening new possibilities for neuroscience research to address previously unsolvable questions (e.g., finding biomarkers of disability progression in multiple sclerosis) and use previously unimaginable techniques (e.g., real-time brain imaging in closed-loop neurofeedback treatment).

Several sub-disciplines within the neuroscience field, including neuroimaging, have forged ahead to create their own data cloud solutions. Various major initiatives globally are also developing and using cloud-based resources for neuroscience research, yet these initiatives generally are being developed independently despite the fact that there are many common unresolved issues, challenges, and questions. Individual labs generating and using cloud-based resources also are very interested in best practices and guidance in this domain. On September 24, 2019, the Forum on Neuroscience and Nervous System Disorders held a workshop, Neuroscience Data in the Cloud, discussing these and related opportunities and challenges in the burgeoning use of cloud technology to advance neuroscience research. One barrier discussed at the workshop was the difficulties new users face in effectively establishing, utilizing, and managing cloud storage and computation, including locating existing resources and adopting best practices and policies already developed by others.

The goal of this Action Collaborative, an ad hoc activity associated with the National Academies’ Forum on Neuroscience and Nervous System Disorders, is to develop an informational guide on using cloud-based resources for neuroscience research for investigators and administrators in the field at different levels of experience using such tools. While the guide is meant to be useful for neuroscientific data of all kinds, neuroimaging will be chosen as the use case given the existing cloud-based infrastructure and tools in this field.

Collaborative Activities

To achieve this goal, collaborative members first developed a use case scenario of an early-stage investigator with limited expertise in using cloud-based tools for neuroimaging research as an initial frame to illustrate the path of a typical research project. Collaborative members generated an evaluation matrix, comprising different types of concerns and issues that such an investigator would address if they wanted to conduct research that used cloud-based resources (access to computational resources, data size, privacy, security, costs, degree of data sharing, etc.). For each of those considerations, collaborative members generated best-case practices, as well as well-developed resources for gathering more information or training, things to avoid, relevant articles, and tools.

Collaborative members are actively working to make this information guide and these resources widely available for broader use by the research community and for them to become part of future training, including through the International Neuroinformatics Coordinating Facility.

Collaborative Members

Deanna Barch (Co-chair), Washington University in St. Louis
Maryann Martone (Co-chair), International Neuroinformatics Coordinating Facility
Jonathan Cohen, Princeton University
Nita Farahany, Duke University
Gregory Farber, National Institute of Mental Health
Magali Haas, Cohen Veterans Bioscience
Sean Horgan, Verily Life Sciences
David Kennedy, University of Massachusetts Medical Center
Tara Madhyastha, Amazon Web Services
Russell Poldrack, Stanford University