Rxivist logo

Ultra-high field (10.5 T) resting state fMRI in the macaque

By Essa Yacoub, Mark D Grier, Edward J Auerbach, Russell L Lagore, Noam Harel, Kamil U─čurbil, Gregor Adriany, Anna Zilverstand, Benjamin Y Hayden, Sarah R Heilbronner, Jan Zimmermann

Posted 23 May 2020
bioRxiv DOI: 10.1101/2020.05.21.109595 (published DOI: 10.1016/j.neuroimage.2020.117349)

Resting state functional connectivity refers to the temporal correlations between spontaneous hemodynamic signals obtained using functional magnetic resonance imaging. This technique has demonstrated that the structure and dynamics of identifiable networks are altered in psychiatric and neurological disease states. Thus, resting state network organizations can be used as a diagnostic, or prognostic recovery indicator. However, much about the physiological basis of this technique is unknown. Thus, providing a translational bridge to an optimal animal model, the macaque, in which invasive circuit manipulations are possible, is of utmost importance. Current approaches to resting state measurements in macaques face unique challenges associated with signal-to-noise, the need for invasive contrast agents, and within-subject designs. These limitations can, in principle, be overcome through ultra-high magnetic fields. However, ultra-high field imaging has yet to be adapted for fMRI in macaques. Here, we demonstrate that the combination of high channel count transmitter and receiver arrays, optimized pulse sequences, and careful anesthesia regimens, allows for detailed within-subject resting state analysis at ultra-high resolutions. In this study, we uncover thirty spatially detailed resting state components that are highly robust across individual macaques and closely resemble the quality and findings of connectomes from large human datasets. This detailed map of the rsfMRI macaque connectome will be the basis for future neurobiological circuit manipulation work, providing valuable biological insights into human connectomics. ### Competing Interest Statement The authors have declared no competing interest.

Download data

  • Downloaded 946 times
  • Download rankings, all-time:
    • Site-wide: 30,901
    • In neuroscience: 3,973
  • Year to date:
    • Site-wide: 67,858
  • Since beginning of last month:
    • Site-wide: 40,250

Altmetric data

Downloads over time

Distribution of downloads per paper, site-wide