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Published June 15, 2022 | Submitted + Supplemental Material + Published
Journal Article Open

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


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.

Additional Information

© 2022 The Authors. Human Brain Mapping published by Wiley Periodicals LLC. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. Issue Online: 19 May 2022; Version of Record online: 15 March 2022; Manuscript accepted: 28 February 2022; Manuscript revised: 12 January 2022; Manuscript received: 05 October 2021. This work was supported in part by the NIH (R01MH110630 and R00MH094409 to Daniel P. Kennedy and T32HD007475 Postdoctoral Traineeship to Lisa Byrge), the Simons Foundation Autism Research Initiative (Ralph Adolphs). For supercomputing resources, this work was supported in part by Lilly Endowment, Inc., through its support for the Indiana University Pervasive Technology Institute, and in part by the Indiana METACyt Initiative. The Indiana METACyt Initiative at IU was also supported in part by Lilly Endowment, Inc. We thank Susannah Ferguson, Brad Caron, Arispa Weigold, and Steven Lograsso for help with data collection and we are grateful to all our participants and their families. The authors declare no competing financial interests. Author Contributions: Lisa Byrge, Ralph Adolphs, and Daniel P. Kennedy conceptualized the project. Hu Cheng & Julian Michael Tyszka developed MRI protocols, coordinated them across sites, and continuously conducted scanner quality assurance. Lisa Byrge, Dorit Kliemann, and Indiana University and Caltech personnel collected data. Lisa Byrge, Dorit Kliemann, and Ye He preprocessed data and ensured data quality. Lisa Byrge & Daniel P. Kennedy developed the analysis approach and Lisa Byrge analyzed the data. Lisa Byrge drafted the manuscript with input from Daniel P. Kennedy and all co-authors provided feedback and approved the final version. Data Availability Statement: The primary data (Videos 1 and 2) analyzed for this manuscript is publicly in the National Database for Autism Research (NDAR; Hall et al., 2012; https://nda.nih.gov/about.html).

Attached Files

Published - Human_Brain_Mapping_-_2022_-_Byrge_-_Video‐evoked_fMRI_BOLD_responses_are_highly_consistent_across_different_data.pdf

Submitted - 2021.10.04.463088v1.full.pdf

Supplemental Material - hbm25830-sup-0001-supinfo.docx



Additional details

August 22, 2023
December 22, 2023