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A semi-parametric model of the hemodynamic response for multi-subject fMRI data.

Publication ,  Journal Article
Zhang, T; Li, F; Beckes, L; Coan, JA
Published in: NeuroImage
July 2013

A semi-parametric model for estimating hemodynamic response function (HRF) from multi-subject fMRI data is introduced within the context of the General Linear Model. The new model assumes that the HRFs for a fixed brain voxel under a given stimulus share the same unknown functional form across subjects, but differ in height, time to peak, and width. A nonparametric spline-smoothing method is developed to evaluate this common functional form, based on which subject-specific characteristics of the HRFs can be estimated. This semi-parametric model explicitly characterizes the common properties shared across subjects and is flexible in describing various brain hemodynamic activities across different regions and stimuli. In addition, the temporal differentiability of the employed spline basis enables an easy-to-compute way of evaluating latency and width differences in hemodynamic activity. The proposed method is applied to data collected as part of an ongoing study of socially mediated emotion regulation. Comparison with several existing methods is conducted through simulations and real data analysis.

Duke Scholars

Published In

NeuroImage

DOI

EISSN

1095-9572

ISSN

1053-8119

Publication Date

July 2013

Volume

75

Start / End Page

136 / 145

Related Subject Headings

  • Neurology & Neurosurgery
  • Models, Neurological
  • Magnetic Resonance Imaging
  • Linear Models
  • Image Interpretation, Computer-Assisted
  • Humans
  • Hemodynamics
  • Brain Mapping
  • Brain
  • Algorithms
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Zhang, T., Li, F., Beckes, L., & Coan, J. A. (2013). A semi-parametric model of the hemodynamic response for multi-subject fMRI data. NeuroImage, 75, 136–145. https://doi.org/10.1016/j.neuroimage.2013.02.048
Zhang, Tingting, Fan Li, Lane Beckes, and James A. Coan. “A semi-parametric model of the hemodynamic response for multi-subject fMRI data.NeuroImage 75 (July 2013): 136–45. https://doi.org/10.1016/j.neuroimage.2013.02.048.
Zhang T, Li F, Beckes L, Coan JA. A semi-parametric model of the hemodynamic response for multi-subject fMRI data. NeuroImage. 2013 Jul;75:136–45.
Zhang, Tingting, et al. “A semi-parametric model of the hemodynamic response for multi-subject fMRI data.NeuroImage, vol. 75, July 2013, pp. 136–45. Epmc, doi:10.1016/j.neuroimage.2013.02.048.
Zhang T, Li F, Beckes L, Coan JA. A semi-parametric model of the hemodynamic response for multi-subject fMRI data. NeuroImage. 2013 Jul;75:136–145.
Journal cover image

Published In

NeuroImage

DOI

EISSN

1095-9572

ISSN

1053-8119

Publication Date

July 2013

Volume

75

Start / End Page

136 / 145

Related Subject Headings

  • Neurology & Neurosurgery
  • Models, Neurological
  • Magnetic Resonance Imaging
  • Linear Models
  • Image Interpretation, Computer-Assisted
  • Humans
  • Hemodynamics
  • Brain Mapping
  • Brain
  • Algorithms