TemplateFlow: a community archive of imaging templates and atlases for improved consistency in neuroimaging
Year: 2021
Type: preprint
Abstract: Neuroimaging templates and corresponding atlases play a central role in experimental workflows and are the foundation for reporting standardised results. The proliferation of templates and atlases is one relevant source of methodological variability across studies, which has been recently brought to attention as an important challenge to reproducibility in neuroscience. Unclear nomenclature, an overabundance of template variants and options, inadequate provenance tracking and maintenance, and poor concordance between atlases introduce further unreliability into reported results. We introduce TemplateFlow, a cloud-based repository of human and nonhuman imaging templates paired with a client application for programmatically accessing resources. TemplateFlow is designed to be extensible, providing a transparent pathway for researchers to contribute and vet templates and their associated atlases. Following software engineering best practices, TemplateFlow leverages technologies for unambiguous resource identification, data management, versioning and synchronisation, programmatic extensibility, and continuous integration. By equipping researchers with a robust resource for using and evaluating templates, TemplateFlow will contribute to increasing the reliability of neuroimaging results.
Source: Research Square
Institutions: Stanford University, MRC Cognition and Brain Sciences Unit, University of Cambridge, Karolinska Institutet, King's College London, Dartmouth College, Harvard University, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Centre Hospitalier Universitaire Vaudois, University of Lausanne
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
Funders: National Science Foundation, Laura and John Arnold Foundation, Wellcome Trust, King's College London, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Medical Research Council, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Institute of Biomedical Imaging and Bioengineering
Awards: Uncovering the interplay of structure, function, and dynamics of brain connectivity using MRI, Collaborative Proposal: CRCNS US-German Data Sharing Proposal: DataLad - a decentralized system for integrated discovery, management, and publication of digital objects of science, NIPreps: integrating neuroimaging preprocessing workflows across modalities, populations, and species, G339059223, Causal mapping of emotion networks with concurrent electrical stimulation and fMRI, DTP Bid Led by King's College London, Fractionating the human frontoparietal cortex: combining meta-analytic and real-time optimization approaches, BIDS-Derivatives: A data standard for derived data and models in the BRAIN Initiative, Fractionating the human frontoparietal cortex: combining meta-analytic and real-time optimization approaches, Nipype: Dataflows for Reproducible Biomedical Research, G8085324931, ReproNim: A Center for Reproducible Neuroimaging Computation, OpenNeuro: An open archive for analysis and sharing of BRAIN Initiative data
OpenAlex ID: W3126770633