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
Link To Document :
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