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

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...

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Published inNeuroImage (Orlando, Fla.) Vol. 223; p. 117349
Main Authors Yacoub, Essa, Grier, Mark D., Auerbach, Edward J., Lagore, Russell L., Harel, Noam, Adriany, Gregor, Zilverstand, Anna, Hayden, Benjamin Y., Heilbronner, Sarah R., Uğurbil, Kamil, Zimmermann, Jan
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.12.2020
Elsevier Limited
Elsevier
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ISSN1053-8119
1095-9572
1095-9572
DOI10.1016/j.neuroimage.2020.117349

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Summary: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 contrast agents limiting translatability, and within-subject designs. These limitations can, in principle, be overcome through ultra-high magnetic fields. However, imaging at magnetic fields above 7T 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 single-subject resting state analysis at high resolutions using a 10.5 Tesla scanner. 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.
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Authors contributed equally to this work.
Credit
Essa Yacoub: Writing, Methodology, Investigation Mark D. Grier: Investigation, Validation Edward J. Auerbach: Methodology, Resources Russell L. Lagore: Methodology, Resources Noam Harel: Writing, Resources Kamil Ugurbil: Supervision, Writing, Funding acquisition Gregor Adriany: Methodology, Resources Anna Zilverstand: Conceptualization, Writing, Analysis Benjamin Y. Hayden: Conceptualization, Writing Sarah R. Heilbronner: Resources, Investigation, Writing, Funding acquisition Jan Zimmermann: Conceptualization, Formal analysis, Methodology, Resources, Investigation, Software, Writing, Funding acquisition
ISSN:1053-8119
1095-9572
1095-9572
DOI:10.1016/j.neuroimage.2020.117349