• DocumentCode
    3438695
  • Title

    Analysis of coexisting neuronal populations in optogenetic and conventional BOLD data

  • Author

    Voss, H.U. ; Domingos, A.I.

  • Author_Institution
    Dept. of Radiol., Weill Cornell Med. Coll., New York, NY, USA
  • fYear
    2012
  • fDate
    1-1 Dec. 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Modeling the hidden neuronal and hemodynamic sources of the blood-oxygenation-level-dependent (BOLD) signal allows for location-dependent parameter estimation that potentially contains more information about brain activation than the general linear model. Here we propose a generalization of the Buxton-Mandeville-Friston BOLD model for more than one neuronal population sharing common hemodynamics within a voxel and demonstrate that new hemodynamic response functions can result. Further, it is demonstrated that two neuronal contributions can be disentangled by parameter estimation from simulated data under certain conditions including differing neuronal efficacies and relaxation parameters. Finally, previously unexplained observations in optogenetic fMRI data are successfully modeled using this approach. This mapping of neuronal and hemodynamic sources could provide novel functional markers for not necessarily optogenetic clinical applications in a more specific way than standard clinical MRI protocols.
  • Keywords
    biomedical MRI; blood; brain; haemodynamics; neurophysiology; parameter estimation; Buxton-Mandeville-Friston BOLD model; blood-oxygenation-level-dependent signal; brain activation; coexisting neuronal population analysis; conventional BOLD data; data simulation; functional markers; general linear model; hemodynamic response; hemodynamic sources; hidden neuronal source modelling; location-dependent parameter estimation; neuronal efficacy; neuronal relaxation parameters; optogenetic BOLD data; optogenetic clinical applications; optogenetic fMRI data; standard clinical MRI protocols; Computational modeling; Data models; Hemodynamics; Mathematical model; Numerical models; Sociology; Statistics; BOLD effect; estimation of hidden states; functional MRI; neuronal source mapping; nonlinear dynamical system modeling; unscented Kalman filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing in Medicine and Biology Symposium (SPMB), 2012 IEEE
  • Conference_Location
    New York, NY
  • Print_ISBN
    978-1-4673-5665-7
  • Type

    conf

  • DOI
    10.1109/SPMB.2012.6469467
  • Filename
    6469467