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Delineating the macroscale areal organization of the macaque cortex in vivo

By Ting Xu, Arnaud Falchier, Elinor L. Sullivan, Gary Linn, Julian Ramirez, Deborah Ross, Eric Feczko, Alexander Opitz, Jennifer Bagley, Darrick Sturgeon, Eric Earl, Oscar Miranda-Domínguez, Anders Perrone, R Cameron Craddock, Charles Schroeder, Stan Colcombe, Damien Fair, Michael P Milham

Posted 26 Jun 2017
bioRxiv DOI: 10.1101/155952 (published DOI: 10.1016/j.celrep.2018.03.049)

Complementing longstanding traditions centered around histology, functional magnetic resonance imaging approaches are rapidly maturing in their ability to delineate brain areal organization at the macroscale. In particular, automated approaches focused on the detection of gradient-based boundaries in functional connectivity (FC) properties between cortical areas have demonstrated the ability to characterize human brain organization at the individual level and recapitulate previously established cytoarchitectonic brain areas. The use of non-human primates (NHP) provides the opportunity to overcome critical barriers in the advancement of translational research. Here, we establish the data and scanning condition requirements for achieving reproducible, stable and internally valid areal parcellations at the individual levels, which have good correspondences with previously established postmortem areas; the inclusion of data from two independent imaging sites ensures the reproducibility of our findings. We demonstrate that highly reproducible areal organizations for fingerprinting can be achieved whether subjects were scanned under anesthesia or awake (rest, naturalistic viewing), though differences between awake and anesthetized states precluded the detection of individual differences across states. Individual differences were notably more stable across differing awake states. Comparison of awake and anesthetized states suggested a more nuanced picture of changes in connectivity for higher order association areas, as well as visual and motor cortex. These results establish feasibility and data requirements for the generation of reproducible individual-specific parcellations in NHP, as well as provide insights into the impact of scan state on findings.

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