A hierarchical model for simultaneous detection and estimation in multi-subject fMRI studies.
Title | A hierarchical model for simultaneous detection and estimation in multi-subject fMRI studies. |
Publication Type | Journal Article |
Year of Publication | 2014 |
Authors | Degras D, Lindquist MA |
Journal | Neuroimage |
Volume | 98 |
Pagination | 61-72 |
Date Published | 2014 Sep |
ISSN | 1095-9572 |
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. |
DOI | 10.1016/j.neuroimage.2014.04.052 |
Alternate Journal | Neuroimage |
PubMed ID | 24793829 |
PubMed Central ID | PMC4099312 |
Grant List | R01 EB016061 / EB / NIBIB NIH HHS / United States R01EB016061 / EB / NIBIB NIH HHS / United States |