Dynamic off-resonance correction improves functional image analysis in fMRI of awake behaving non-human primates.

fMRI non-human primate (NHP) off-resonance artifacts raw data correction simultaneous multi-slice

Journal

Frontiers in neuroimaging
ISSN: 2813-1193
Titre abrégé: Front Neuroimaging
Pays: Switzerland
ID NLM: 9918402387106676

Informations de publication

Date de publication:
2024
Historique:
received: 11 11 2023
accepted: 03 06 2024
medline: 10 7 2024
pubmed: 10 7 2024
entrez: 10 7 2024
Statut: epublish

Résumé

Use of functional MRI in awake non-human primate (NHPs) has recently increased. Scanning animals while awake makes data collection possible in the absence of anesthetic modulation and with an extended range of possible experimental designs. Robust awake NHP imaging however is challenging due to the strong artifacts caused by time-varying off-resonance changes introduced by the animal's body motion. In this study, we sought to thoroughly investigate the effect of a newly proposed dynamic off-resonance correction method on brain activation estimates using extended awake NHP data. We correct for dynamic B0 changes in reconstruction of highly accelerated simultaneous multi-slice EPI acquisitions by estimating and correcting for dynamic field perturbations. Functional MRI data were collected in four male rhesus monkeys performing a decision-making task in the scanner, and analyses of improvements in sensitivity and reliability were performed compared to conventional image reconstruction. Applying the correction resulted in reduced bias and improved temporal stability in the reconstructed time-series data. We found increased sensitivity to functional activation at the individual and group levels, as well as improved reliability of statistical parameter estimates. Our results show significant improvements in image fidelity using our proposed correction strategy, as well as greatly enhanced and more reliable activation estimates in GLM analyses.

Identifiants

pubmed: 38984197
doi: 10.3389/fnimg.2024.1336887
pmc: PMC11231096
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1336887

Informations de copyright

Copyright © 2024 Shahdloo, Khalighinejad, Priestley, Rushworth and Chiew.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Auteurs

Mo Shahdloo (M)

Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom.

Nima Khalighinejad (N)

Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom.

Luke Priestley (L)

Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom.

Matthew Rushworth (M)

Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom.

Mark Chiew (M)

Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom.
Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada.
Medical Biophysics, University of Toronto, Toronto, ON, Canada.

Classifications MeSH