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Home / A hierarchical model for simultaneous detection and estimation in multi-subject fMRI studies.

A hierarchical model for simultaneous detection and estimation in multi-subject fMRI studies.

TitleA hierarchical model for simultaneous detection and estimation in multi-subject fMRI studies.
Publication TypeJournal Article
Year of Publication2014
AuthorsDegras D, Lindquist MA
JournalNeuroimage
Volume98
Pagination61-72
Date Published2014 Sep
ISSN1095-9572
Abstract

In this paper we introduce a new hierarchical model for the simultaneous detection of brain activation and estimation of the shape of the hemodynamic response in multi-subject fMRI studies. The proposed approach circumvents a major stumbling block in standard multi-subject fMRI data analysis, in that it both allows the shape of the hemodynamic response function to vary across region and subjects, while still providing a straightforward way to estimate population-level activation. An efficient estimation algorithm is presented, as is an inferential framework that allows for not only tests of activation, but also tests for deviations from some canonical shape. The model is validated through simulations and application to a multi-subject fMRI study of thermal pain.

DOI10.1016/j.neuroimage.2014.04.052
Alternate JournalNeuroimage
PubMed ID24793829
PubMed Central IDPMC4099312
Grant ListR01 EB016061 / EB / NIBIB NIH HHS / United States
R01EB016061 / EB / NIBIB NIH HHS / United States
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