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

David Degras, Martin Lindquist

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Pages (from-to)61-72
Number of pages12
JournalNeuroImage
Volume98
DOIs
StatePublished - 2014

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Magnetic Resonance Imaging
Hemodynamics
Hot Temperature
Pain
Brain
Population

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Neurology
  • Medicine(all)

Cite this

A hierarchical model for simultaneous detection and estimation in multi-subject fMRI studies. / Degras, David; Lindquist, Martin.

In: NeuroImage, Vol. 98, 2014, p. 61-72.

Research output: Contribution to journalArticle

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