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Inter-individual Variability of Functional Connectivity in Awake and Anesthetized Rhesus Monkeys

By Ting Xu, Darrick Sturgeon, Julian S.B. Ramirez, Sean Froudist-Walsh, Daniel S. Margulies, Charlie E. Schroeder, Damien A. Fair, Michael Milham

Posted 26 Jan 2019
bioRxiv DOI: 10.1101/531293 (published DOI: 10.1016/j.bpsc.2019.02.005)

Background: Nonhuman primate models (NHP) are commonly used to advance our understanding of brain function and organization. However, to date, they have offered few insights into individual differences among NHPs. In large part, this is due to the logistical challenges of NHP research, which limit most studies to five subjects or fewer. Methods: We leveraged the availability of a large-scale open NHP imaging resource to provide an initial examination of individual differences in the functional organization of the nonhuman primate brain. Specifically, we selected one awake fMRI dataset (Newcastle: n = 10) and two anesthetized fMRI data sets (Oxford: n = 19; UC-Davis: n = 19) to examine individual differences in functional connectivity characteristics across the cortex, as well as potential state dependencies. Results: We noted significant individual variations of functional connectivity across the macaque cortex. Similar to the findings in human, during the awake state, the primary sensory and motor cortices showed lower variability than the high-order association regions. This variability pattern was significantly correlated with T1w/T2w map, the degree of long-distance connectivity, but not short-distance connectivity. However, the inter-individual variability under anesthesia exhibited a very distinct pattern, with lower variability in medial frontal cortex, precuneus and somatomotor regions and higher variability in the lateral ventral frontal and insular cortices. Conclusions: This work has implications for our understanding of the evolutionary origins of individual variation in the human brain, as well as methodological implications that must be considered in any pursuit to study individual variation in NHP models.

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