Publication detail

Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering

HAVLÍČEK, M. FRISTON, K. JAN, J. BRÁZDIL, M. CALHOUN, V.

Original Title

Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering

Czech Title

Dynamické modelování neuronálních odezev v fMRI pomocí kubaturního Kalmanova filtru

English Title

Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering

Type

journal article

Language

en

Original Abstract

Introduction of new method for estimation of neuronal responses from hemodynamic responses of fMRI data. This method allows efficient joint estimation of hidden model states, parameters, and also input, through consequent application of cubature Kalman filter and cubature Rauch-Tung-Striebel smoother.

Czech abstract

Predstavení nové metody odhadu neuronálních odezev z hemodynamických odezev dat funkcní magnetické rezonance (fMRI). Tato metoda umoznuje úcinný soucasný odhad zkrytých stavu modelu, parametru, a také vstupu, skrze postupnou aplikaci kubaturního Kalmanova filtru and kubaturního Rauch-Tung-Striebelova vyhlazovace.

English abstract

Introduction of new method for estimation of neuronal responses from hemodynamic responses of fMRI data. This method allows efficient joint estimation of hidden model states, parameters, and also input, through consequent application of cubature Kalman filter and cubature Rauch-Tung-Striebel smoother.

Keywords

neuronal, deconvolution, fMRI, cubature, Kalman, smoother, hemodynamic model

RIV year

2011

Released

15.06.2011

Publisher

Elsevier

Location

USA

Pages from

2109

Pages to

2128

Pages count

21

BibTex


@article{BUT50444,
  author="Martin {Havlíček} and Karl J. {Friston} and Jiří {Jan} and Milan {Brázdil} and V.D. {Calhoun}",
  title="Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering",
  annote="Introduction of new method for estimation of neuronal responses from hemodynamic responses of fMRI data. This method allows efficient joint estimation of hidden model states, parameters, and also input, through consequent application of cubature Kalman filter and cubature Rauch-Tung-Striebel smoother.",
  address="Elsevier",
  chapter="50444",
  doi="10.1016/j.neuroimage.2011.03.005",
  institution="Elsevier",
  number="4",
  volume="56",
  year="2011",
  month="june",
  pages="2109--2128",
  publisher="Elsevier",
  type="journal article"
}