• DocumentCode
    3560612
  • Title

    Identifying fMRI Model Violations With Lagrange Multiplier Tests

  • Author

    Cassidy, Ben ; Long, Christopher J. ; Rae, Caroline ; Solo, Victor

  • Author_Institution
    Sch. of Electr. Eng., Univ. of New South Wales, Sydney, NSW, Australia
  • Volume
    31
  • Issue
    7
  • fYear
    2012
  • fDate
    7/1/2012 12:00:00 AM
  • Firstpage
    1481
  • Lastpage
    1492
  • Abstract
    The standard modeling framework in functional magnetic resonance imaging (fMRI) is predicated on assumptions of linearity, time invariance and stationarity. These assumptions are rarely checked because doing so requires specialized software, although failure to do so can lead to bias and mistaken inference. Identifying model violations is an essential but largely neglected step in standard fMRI data analysis. Using Lagrange multiplier testing methods we have developed simple and efficient procedures for detecting model violations such as nonlinearity, nonstationarity and validity of the common double gamma specification for hemodynamic response. These procedures are computationally cheap and can easily be added to a conventional analysis. The test statistic is calculated at each voxel and displayed as a spatial anomaly map which shows regions where a model is violated. The methodology is illustrated with a large number of real data examples.
  • Keywords
    biomedical MRI; data analysis; haemodynamics; modelling; Lagrange multiplier tests; common double gamma specification; fMRI data analysis; fMRI model violations; functional magnetic resonance imaging; hemodynamic response; nonlinearity; nonstationarity; spatial anomaly map; standard modeling framework; time invariance; Approximation methods; Computational modeling; Frequency domain analysis; Maximum likelihood estimation; Noise; Software; Testing; Functional magnetic resonance imaging (fMRI); hemodynamic response function; model criticism; Brain; Computer Simulation; Hemodynamics; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Models, Theoretical; ROC Curve; Signal Processing, Computer-Assisted; Signal-To-Noise Ratio;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • Conference_Location
    4/19/2012 12:00:00 AM
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/TMI.2012.2195327
  • Filename
    6187731