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Common functional localizers to enhance NHP & cross-species neuroscience imaging research.

Authors :
Russ, Brian E
Petkov, Christopher I
Kwok, Sze Chai
Zhu, Qi
Belin, Pascal
Vanduffel, Wim
Hamed, Suliann Ben
Source :
NeuroImage. Aug2021, Vol. 237, pN.PAG-N.PAG. 1p.
Publication Year :
2021

Abstract

• Value of fMRI localizer protocols to NHP & cross-species neuroscience research. • Commonly used or novel localizers within NHPs, & keys implementation criteria. • Open access repository of well-established localizer on PRIME-RE platform. Functional localizers are invaluable as they can help define regions of interest, provide cross-study comparisons, and most importantly, allow for the aggregation and meta-analyses of data across studies and laboratories. To achieve these goals within the non-human primate (NHP) imaging community, there is a pressing need for the use of standardized and validated localizers that can be readily implemented across different groups. The goal of this paper is to provide an overview of the value of localizer protocols to imaging research and we describe a number of commonly used or novel localizers within NHPs, and keys to implement them across studies. As has been shown with the aggregation of resting-state imaging data in the original PRIME-DE submissions, we believe that the field is ready to apply the same initiative for task-based functional localizers in NHP imaging. By coming together to collect large datasets across research group, implementing the same functional localizers, and sharing the localizers and data via PRIME-DE, it is now possible to fully test their robustness, selectivity and specificity. To do this, we reviewed a number of common localizers and we created a repository of well-established localizer that are easily accessible and implemented through the PRIME-RE platform. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10538119
Volume :
237
Database :
Academic Search Index
Journal :
NeuroImage
Publication Type :
Academic Journal
Accession number :
151173574
Full Text :
https://doi.org/10.1016/j.neuroimage.2021.118203