期刊
NEUROIMAGE
卷 236, 期 -, 页码 -出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2021.118082
关键词
MRI; Standardization; Non-human primate; Multi-site; PRIME-DE
资金
- McDonnell Center for Systems Neuroscience at Washington University
- program for Brain/MINDS
- Japan Agency for Medical Research and development, AMED [JP20dm037006]
- RIKEN Compass to Healthy Life Research Complex Program from Japan Science and Technology Agency, JST
- JSPS KAKENHI [JP20K15945]
- European Research Council (ERC) under the European Union [802482]
- Canadian Institutes of Health Research [FRN-148453]
- UMN Digital Technologies Initiative
- Lynne and Andrew Redleaf Foundation [DA041148, DA04112, MH115357, MH096773, RF1 MH116978, P50NS098573]
- Emmy Noether Program of the German Research Foundation [SCHW1683/2-1]
- NIH [MH-060974, R01-MH101555, RF1MH117040]
- KU Leuven grant [C14/17/109]
- Fonds Wetenschappelijk Onderzoek-Vlaanderen (FWO) [G0D5817N, G0B8617N, G0C1920N, VS02219N]
- European Union [945539]
- Natural Sciences and Engineering Research Council of Canada Discovery Grant [EB027061, DA048742, NSF-2024581]
- UMN AIRP
- [1U54MH091657]
- European Research Council (ERC) [802482] Funding Source: European Research Council (ERC)
Recent methodological advances in MRI have facilitated increased neuroimaging studies in non-human primates, with open data-sharing initiatives enhancing availability of NHP MRI data. Establishment of minimal standards for data acquisition protocols and analysis pipelines is crucial for multi-center studies to accelerate research progress.
Recent methodological advances in MRI have enabled substantial growth in neuroimaging studies of non-human primates (NHPs), while open data-sharing through the PRIME-DE initiative has increased the availability of NHP MRI data and the need for robust multi-subject multi-center analyses. Streamlined acquisition and analysis protocols would accelerate and improve these efforts. However, consensus on minimal standards for data acquisition protocols and analysis pipelines for NHP imaging remains to be established, particularly for multi-center studies. Here, we draw parallels between NHP and human neuroimaging and provide minimal guidelines for harmonizing and standardizing data acquisition. We advocate robust translation of widely used open-access toolkits that are well established for analyzing human data. We also encourage the use of validated, automated pre-processing tools for analyzing NHP data sets. These guidelines aim to refine methodological and analytical strategies for small and large-scale NHP neuroimaging data. This will improve reproducibility of results, and accelerate the convergence between NHP and human neuroimaging strategies which will ultimately benefit fundamental and translational brain science.
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