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September 2022 Bayesian functional registration of fMRI activation maps
Guoqing Wang, Abhirup Datta, Martin A. Lindquist
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Ann. Appl. Stat. 16(3): 1676-1699 (September 2022). DOI: 10.1214/21-AOAS1562


Functional magnetic resonance imaging (fMRI) has provided invaluable insight into our understanding of human behavior. However, large interindividual differences in both brain anatomy and functional localization after anatomical alignment remain a major limitation in conducting group analyses and performing population level inference. This paper addresses this problem by developing and validating a new computational technique for reducing misalignment across individuals in functional brain systems by spatially transforming each subject’s functional data to a common reference map. Our proposed Bayesian functional registration approach allows us to assess differences in brain function across subjects and individual differences in activation topology. It combines intensity-based and feature-based information into an integrated framework and allows inference to be performed on the transformation via the posterior samples. We evaluate the method in a simulation study and apply it to data from a study of thermal pain. We find that the proposed approach provides increased sensitivity for group-level inference.

Funding Statement

The work presented in this paper was supported in part by NIH Grants R01 EB016061 and R01 EB026549 from the National Institute of Biomedical Imaging and Bioengineering and R01 MH116026 from the National Institute of Mental Health.


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Guoqing Wang. Abhirup Datta. Martin A. Lindquist. "Bayesian functional registration of fMRI activation maps." Ann. Appl. Stat. 16 (3) 1676 - 1699, September 2022.


Received: 1 November 2020; Revised: 1 October 2021; Published: September 2022
First available in Project Euclid: 19 July 2022

Digital Object Identifier: 10.1214/21-AOAS1562

Keywords: Bayesian methods , functional magnetic resonance imaging , group-level analysis , interindividual differences , pain , registration

Rights: Copyright © 2022 Institute of Mathematical Statistics


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Vol.16 • No. 3 • September 2022
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