Literature DB >> 24793829

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

David Degras1, Martin A Lindquist2.   

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.
Copyright © 2014 Elsevier Inc. All rights reserved.

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Year:  2014        PMID: 24793829      PMCID: PMC4099312          DOI: 10.1016/j.neuroimage.2014.04.052

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  29 in total

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Journal:  Neuroimage       Date:  2004-05       Impact factor: 6.556

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7.  The variability of human, BOLD hemodynamic responses.

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Journal:  Neuroimage       Date:  1998-11       Impact factor: 6.556

8.  Event-related fMRI: characterizing differential responses.

Authors:  K J Friston; P Fletcher; O Josephs; A Holmes; M D Rugg; R Turner
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Authors:  K J Worsley; K J Friston
Journal:  Neuroimage       Date:  1995-09       Impact factor: 6.556

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  11 in total

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Authors:  Jia Liu; Ben A Duffy; David Bernal-Casas; Zhongnan Fang; Jin Hyung Lee
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Review 6.  Building a Science of Individual Differences from fMRI.

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9.  A method to compare the discriminatory power of data-driven methods: Application to ICA and IVA.

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10.  Detecting the subtle shape differences in hemodynamic responses at the group level.

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