March 2024 Latent subgroup identification in image-on-scalar regression
Zikai Lin, Yajuan Si, Jian Kang
Author Affiliations +
Ann. Appl. Stat. 18(1): 468-486 (March 2024). DOI: 10.1214/23-AOAS1797


Image-on-scalar regression has been a popular approach to modeling the association between brain activities and scalar characteristics in neuroimaging research. The associations could be heterogeneous across individuals in the population, as indicated by recent large-scale neuroimaging studies, for example, the Adolescent Brain Cognitive Development (ABCD) Study. The ABCD data can inform our understanding of heterogeneous associations and how to leverage the heterogeneity and tailor interventions to increase the number of youths who benefit. It is of great interest to identify subgroups of individuals from the population such that: (1) within each subgroup the brain activities have homogeneous associations with the clinical measures; (2) across subgroups the associations are heterogeneous, and (3) the group allocation depends on individual characteristics. Existing image-on-scalar regression methods and clustering methods cannot directly achieve this goal. We propose a latent subgroup image-on-scalar regression model (LASIR) to analyze large-scale, multisite neuroimaging data with diverse sociodemographics. LASIR introduces the latent subgroup for each individual and group-specific, spatially varying effects, with an efficient stochastic expectation maximization algorithm for inferences. We demonstrate that LASIR outperforms existing alternatives for subgroup identification of brain activation patterns with functional magnetic resonance imaging data via comprehensive simulations and applications to the ABCD study. We have released our reproducible codes for public use with the software package available on Github.

Funding Statement

This work was partially supported by the NIH grants R21HD105204 (Si, Lin, Kang), U01MD017867 (Si), R01DA048993 (Kang), R01GM124061 (Kang), and R01MH105561 (Kang).


We appreciate the assistance of Drs. Chandra S. Sripada and Mike Angstadt for the ABCD study data processing and sharing.


Download Citation

Zikai Lin. Yajuan Si. Jian Kang. "Latent subgroup identification in image-on-scalar regression." Ann. Appl. Stat. 18 (1) 468 - 486, March 2024.


Received: 1 May 2022; Revised: 1 June 2023; Published: March 2024
First available in Project Euclid: 31 January 2024

Digital Object Identifier: 10.1214/23-AOAS1797

Keywords: image-on-scalar regression , stochastic expectation maximization , subgroup identification , Voxelwise spatial correlation

Rights: Copyright © 2024 Institute of Mathematical Statistics


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Vol.18 • No. 1 • March 2024
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