SummaryNon-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience. Unfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMatE Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design, and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 25 independent data collections aggregated across 22 sites (total = 217 non-human primates). We also outline the unique pitfalls and challenges that should be considered in the analysis of non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets.

In the absence of external stimuli or task demands, correlations in spontaneous brain activity (functional connectivity) reflect patterns of anatomical connectivity. Hence, resting-state functional connectivity has been used as a proxy measure for structural connectivity and as a biomarker for brain changes in disease. To relate changes in functional connectivity to physiological changes in the brain, it is important to understand how correlations in functional connectivity depend on the physical integrity of brain tissue. The causal nature of this relationship has been called into question by patient data suggesting that decreased structural connectivity does not necessarily lead to decreased functional connectivity. Here we provide evidence for a causal but complex relationship between structural connectivity and functional connectivity: we tested interhemispheric functional connectivity before and after corpus callosum section in rhesus monkeys. We found that forebrain commissurotomy severely reduced interhemispheric functional connectivity, but surprisingly, this effect was greatly mitigated if the anterior commissure was left intact. Furthermore, intact structural connections increased their functional connectivity in line with the hypothesis that the inputs to each node are normalized. We conclude that functional connectivity is likely driven by corticocortical white matter connections but with complex network interactions such that a near-normal pattern of functional connectivity can be maintained by just a few indirect structural connections. These surprising results highlight the importance of network-level interactions in functional connectivity and may cast light on various paradoxical findings concerning changes in functional connectivity in disease states.resting-state connectivity | macaque | fMRI | split brain R esting-state functional connectivity [intrinsic correlations in activity between brain areas, measured in the absence of overt stimulation or task demands (1, 2)] provides a powerful tool for understanding the global organization of the brain (3-6), charting its connectional structure (e.g., refs. 7-11), and detecting brain changes in disease. Functional connectivity changes have been identified in diverse conditions including Alzheimer's disease (6, 12-14), Parkinson's disease (15, 16), multiple sclerosis (17, 18), autism (19), depression (20, 21), and schizophrenia (22, 23).To relate changes in functional connectivity to physiological changes in the brain, it is important to understand how functional connectivity depends on the physical integrity of brain tissue. However, there is a disparity in the conclusions that have been drawn from work on the healthy brain and patient studies. It is generally accepted that in the healthy brain, functional connectivity correlates with structural connectivity (the presence and integrity of white matter connections) (3,24,25), and computational modeling suggests that structural connectivity shapes and constrains functional connectivity (3,24). Howeve...