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Modeling Inter-Subject Variability in fMRI Activation Location: A Bayesian Hierarchical Spatial Model

Author

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  • Lei Xu
  • Timothy D. Johnson
  • Thomas E. Nichols
  • Derek E. Nee

Abstract

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Suggested Citation

  • Lei Xu & Timothy D. Johnson & Thomas E. Nichols & Derek E. Nee, 2009. "Modeling Inter-Subject Variability in fMRI Activation Location: A Bayesian Hierarchical Spatial Model," Biometrics, The International Biometric Society, vol. 65(4), pages 1041-1051, December.
    • Handle: RePEc:bla:biomet:v:65:y:2009:i:4:p:1041-1051
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2008.01190.x
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    References listed on IDEAS

    as
    1. Timothy D. Johnson, 2007. "Analysis of Pulsatile Hormone Concentration Profiles with Nonconstant Basal Concentration: A Bayesian Approach," Biometrics, The International Biometric Society, vol. 63(4), pages 1207-1217, December.
    2. Niels Væver Hartvig, 2002. "A Stochastic Geometry Model for Functional Magnetic Resonance Images," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 29(3), pages 333-353, September.
    3. Jörg Polzehl & Vladimir G. Spokoiny, 2001. "Functional and dynamic magnetic resonance imaging using vector adaptive weights smoothing," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 50(4), pages 485-501.
    4. Carmen Fernández & Peter J. Green, 2002. "Modelling spatially correlated data via mixtures: a Bayesian approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 805-826, October.
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    Cited by:

    1. Suyu Liu & Ying Yuan & Richard Castillo & Thomas Guerrero & Valen E. Johnson, 2014. "Evaluation of image registration spatial accuracy using a Bayesian hierarchical model," Biometrics, The International Biometric Society, vol. 70(2), pages 366-377, June.
    2. Zhe Yu & Raquel Prado & Erin Burke Quinlan & Steven C. Cramer & Hernando Ombao, 2016. "Understanding the Impact of Stroke on Brain Motor Function: A Hierarchical Bayesian Approach," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 549-563, April.
    3. repec:jss:jstsof:44:i14 is not listed on IDEAS
    4. Daniel Spencer & Rajarshi Guhaniyogi & Raquel Prado, 2020. "Joint Bayesian Estimation of Voxel Activation and Inter-regional Connectivity in fMRI Experiments," Psychometrika, Springer;The Psychometric Society, vol. 85(4), pages 845-869, December.

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