In vivo functional brain mapping using ultra-high-field fMRI in awake common marmosets

The common marmoset (Callithrix jacchus) is gaining attention in the field of cognitive neuroscience. The development of an effective protocol for fMRI data acquisition in awake marmosets is a key factor in developing reliable comparative studies. Here, we describe a protocol to obtain fMRI data in...

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Detalles Bibliográficos
Autores principales: Zanini, Alessandro, Dureux, Audrey, Jafari, Azadeh, Gilbert, Kyle M., Zeman, Peter, Bellyou, Miranda, Li, Alex, Tuin, Cheryl Vander, Everling, Stefan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Protocol
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10520676/
https://www.ncbi.nlm.nih.gov/pubmed/37738120
http://dx.doi.org/10.1016/j.xpro.2023.102586
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author Zanini, Alessandro
Dureux, Audrey
Jafari, Azadeh
Gilbert, Kyle M.
Zeman, Peter
Bellyou, Miranda
Li, Alex
Tuin, Cheryl Vander
Everling, Stefan
author_facet Zanini, Alessandro
Dureux, Audrey
Jafari, Azadeh
Gilbert, Kyle M.
Zeman, Peter
Bellyou, Miranda
Li, Alex
Tuin, Cheryl Vander
Everling, Stefan
author_sort Zanini, Alessandro
collection PubMed
description The common marmoset (Callithrix jacchus) is gaining attention in the field of cognitive neuroscience. The development of an effective protocol for fMRI data acquisition in awake marmosets is a key factor in developing reliable comparative studies. Here, we describe a protocol to obtain fMRI data in awake marmosets using auditory and visual stimulation. We describe steps for surgical and anesthesia procedures, MRI training, and positioning the marmosets within an MRI-compatible body restraint. We then detail fMRI scanning and preprocessing of functional images. For complete details on the use and execution of this protocol, please refer to Jafari et al. (2023).(1)
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spelling pubmed-105206762023-09-27 In vivo functional brain mapping using ultra-high-field fMRI in awake common marmosets Zanini, Alessandro Dureux, Audrey Jafari, Azadeh Gilbert, Kyle M. Zeman, Peter Bellyou, Miranda Li, Alex Tuin, Cheryl Vander Everling, Stefan STAR Protoc Protocol The common marmoset (Callithrix jacchus) is gaining attention in the field of cognitive neuroscience. The development of an effective protocol for fMRI data acquisition in awake marmosets is a key factor in developing reliable comparative studies. Here, we describe a protocol to obtain fMRI data in awake marmosets using auditory and visual stimulation. We describe steps for surgical and anesthesia procedures, MRI training, and positioning the marmosets within an MRI-compatible body restraint. We then detail fMRI scanning and preprocessing of functional images. For complete details on the use and execution of this protocol, please refer to Jafari et al. (2023).(1) Elsevier 2023-09-21 /pmc/articles/PMC10520676/ /pubmed/37738120 http://dx.doi.org/10.1016/j.xpro.2023.102586 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Protocol
Zanini, Alessandro
Dureux, Audrey
Jafari, Azadeh
Gilbert, Kyle M.
Zeman, Peter
Bellyou, Miranda
Li, Alex
Tuin, Cheryl Vander
Everling, Stefan
In vivo functional brain mapping using ultra-high-field fMRI in awake common marmosets
title In vivo functional brain mapping using ultra-high-field fMRI in awake common marmosets
title_full In vivo functional brain mapping using ultra-high-field fMRI in awake common marmosets
title_fullStr In vivo functional brain mapping using ultra-high-field fMRI in awake common marmosets
title_full_unstemmed In vivo functional brain mapping using ultra-high-field fMRI in awake common marmosets
title_short In vivo functional brain mapping using ultra-high-field fMRI in awake common marmosets
title_sort in vivo functional brain mapping using ultra-high-field fmri in awake common marmosets
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10520676/
https://www.ncbi.nlm.nih.gov/pubmed/37738120
http://dx.doi.org/10.1016/j.xpro.2023.102586
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