Video-evoked fMRI BOLD responses are highly consistent across different data acquisition sites.

harmonization inter-subject correlations naturalistic viewing reliability reproducibility synchrony video fMRI

Journal

Human brain mapping
ISSN: 1097-0193
Titre abrégé: Hum Brain Mapp
Pays: United States
ID NLM: 9419065

Informations de publication

Date de publication:
15 06 2022
Historique:
revised: 12 01 2022
received: 05 10 2021
accepted: 28 02 2022
pubmed: 16 3 2022
medline: 24 5 2022
entrez: 15 3 2022
Statut: ppublish

Résumé

Naturalistic imaging paradigms, in which participants view complex videos in the scanner, are increasingly used in human cognitive neuroscience. Videos evoke temporally synchronized brain responses that are similar across subjects as well as within subjects, but the reproducibility of these brain responses across different data acquisition sites has not yet been quantified. Here, we characterize the consistency of brain responses across independent samples of participants viewing the same videos in functional magnetic resonance imaging (fMRI) scanners at different sites (Indiana University and Caltech). We compared brain responses collected at these different sites for two carefully matched datasets with identical scanner models, acquisition, and preprocessing details, along with a third unmatched dataset in which these details varied. Our overall conclusion is that for matched and unmatched datasets alike, video-evoked brain responses have high consistency across these different sites, both when compared across groups and across pairs of individuals. As one might expect, differences between sites were larger for unmatched datasets than matched datasets. Residual differences between datasets could in part reflect participant-level variability rather than scanner- or data- related effects. Altogether our results indicate promise for the development and, critically, generalization of video fMRI studies of individual differences in healthy and clinical populations alike.

Identifiants

pubmed: 35289976
doi: 10.1002/hbm.25830
pmc: PMC9120552
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2972-2991

Subventions

Organisme : NICHD NIH HHS
ID : P50 HD103556
Pays : United States

Informations de copyright

© 2022 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.

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Auteurs

Lisa Byrge (L)

Department of Psychology, University of North Florida, Jacksonville, Florida, USA.
Biomedical Sciences Program, University of North Florida, Jacksonville, Florida, USA.

Dorit Kliemann (D)

Department of Psychological and Brain Sciences, The University of Iowa, Iowa City, Iowa, USA.
Iowa Neuroscience Institute, University of Iowa, Iowa, IA, USA.
Department of Psychiatry, University of Iowa, Iowa City, IA, USA.

Ye He (Y)

School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China.

Hu Cheng (H)

Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, USA.
Program in Neuroscience, Bloomington, Indiana, USA.

Julian Michael Tyszka (JM)

Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, California, USA.
Caltech Brain Imaging Center, California Institute of Technology, Pasadena, California, USA.

Ralph Adolphs (R)

Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, California, USA.
Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA.
Chen Neuroscience Institute, California Institute of Technology, Pasadena, California, USA.

Daniel P Kennedy (DP)

Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, USA.
Program in Neuroscience, Bloomington, Indiana, USA.
Cognitive Science Program, Indiana University, Bloomington, Indiana, USA.

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