ArticleImaging neuroscience (Cambridge, Mass.)2026
Development of a 24-channel 3T phased-array coil for fMRI in awake monkeys: Mitigating spatiotemporal artifacts in ferumoxytol-weighted functional connectivity estimation.
Article in Imaging neuroscience (Cambridge, Mass.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Functional mapping of auditory responses to complex sounds under light anesthesia in rhesus macaques.Open research Europe · 2025Article
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Authors and funding
10 authors.
Funding
Abstract
Functional magnetic resonance imaging (fMRI) of awake macaque monkeys holds promise for advancing our understanding of primate brain organization, including humans. However, estimating functional connectivity in awake animals is challenging due to the limited duration of imaging sessions and the relatively low sensitivity to neural activity. To overcome these challenges, we developed a 24-channel 3T receive radiofrequency (RF) coil optimized for parallel imaging of awake macaques. This enabled the acquisition of cross-plane and in-plane accelerated ferumoxytol-weighted resting-state fMRI. The Human Connectome Project-style data processing pipelines were adapted to address the unique preprocessing demands of cerebral blood volume-weighted (CBVw) imaging, including motion correction, functional-to-structural image co-registration, and training a multi-run independent component analysis-based X-noiseifier (ICA-FIX) classifier for removal of structured artifacts. Our CBVw fMRI approach resulted in an elevated contrast-to-noise ratio compared with blood oxygenation level-dependent (BOLD) imaging in anesthetized macaques. However, structured imaging artifacts still contributed more variance to the functional timeseries than neural activity. By applying the ICA-FIX classifier, we achieved highly reproducible parcellated functional connectivity at the single-subject level, with test-retest matrix correlations and subject identification accuracy comparable with those observed in humans. At the group level, we identified dense functional networks with spatial features homologous to those observed in humans. The developed RF receive coil, image acquisition protocols, and data analysis pipelines are publicly available, providing the broader scientific community with tools to leverage these advances for further research.
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