Dynamic modeling of neuronal responses in fMRI using cubature
Kalman filtering

J 2011

Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering

HAVLÍČEK, Martin, Karl J. FRISTON, Jiří JAN, Milan BRÁZDIL, Vince D. CALHOUN et. al.

Basic information

Original name

Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering

Name in Czech

Dynamické modelování neuronálních odpovědí ve funkční fMRI s použitím Kalmanova kubaturního filtrování

Authors

HAVLÍČEK, Martin (203 Czech Republic), Karl J. FRISTON (826 United Kingdom of Great Britain and Northern Ireland), Jiří JAN (203 Czech Republic), Milan BRÁZDIL (203 Czech Republic, guarantor, belonging to the institution) and Vince D. CALHOUN (840 United States of America)

Edition

NeuroImage, ACADEMIC PRESS INC ELSEVIER SCIENCE, 2011, 1053-8119

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

30000 3. Medical and Health Sciences

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

Impact factor

Impact factor: 5.895

RIV identification code

RIV/00216224:14740/11:00055575

Organization unit

Central European Institute of Technology

DOI

http://dx.doi.org/10.1016/j.neuroimage.2011.03.005

UT WoS

000291457500023

Keywords in English

STOCHASTIC DIFFERENTIAL-EQUATIONS; BOLD HEMODYNAMIC-RESPONSES; LOCAL LINEARIZATION METHOD; CEREBRAL BLOOD-FLOW; BRAIN ACTIVATION; BALLOON MODEL; SYSTEMS; SIGNALS; NOISE; SIMULATION

Abstract

V originále

This paper presents a new approach to inverting (fitting) models of coupled dynamical systems based on state-of-the-art (cubature) Kalman filtering. Our scheme promises to provide a significant advance in characterizing the functional architectures of distributed neuronal systems, even in the absence of known exogenous (experimental) input; e.g., resting state fMRI studies and spontaneous fluctuations in electrophysiological studies. Importantly, unlike current Bayesian filters (e.g. DEM), our scheme provides estimates of time-varying parameters, which we will exploit in future work on the adaptation and enabling of connections in the brain.

Links

MSM0021622404, plan (intention)

Name: Vnitřní organizace a neurobiologické mechanismy funkčních systémů CNS

Investor: Ministry of Education, Youth and Sports of the CR, The internal organisation and neurobiological mechanisms of functional CNS systems under normal and pathological conditions.

Citovat

HAVLÍČEK, Martin, Karl J. FRISTON, Jiří JAN, Milan BRÁZDIL and Vince D. CALHOUN. Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering. NeuroImage. ACADEMIC PRESS INC ELSEVIER SCIENCE, 2011, vol. 56, No 4, p. 2109-2128. ISSN 1053-8119. Available from: https://dx.doi.org/10.1016/j.neuroimage.2011.03.005.

@article{971299,
   author = {Havlíček, Martin and Friston, Karl J. and Jan, Jiří and Brázdil, Milan and Calhoun, Vince D.},
   article_number = {4},
   doi = {http://dx.doi.org/10.1016/j.neuroimage.2011.03.005},
   keywords = {STOCHASTIC DIFFERENTIAL-EQUATIONS; BOLD HEMODYNAMIC-RESPONSES; LOCAL LINEARIZATION METHOD; CEREBRAL BLOOD-FLOW; BRAIN ACTIVATION; BALLOON MODEL; SYSTEMS; SIGNALS; NOISE; SIMULATION},
   language = {eng},
   issn = {1053-8119},
   journal = {NeuroImage},
   title = {Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering},
   volume = {56},
   year = {2011}
}

TY  - JOUR
ID  - 971299
AU  - Havlíček, Martin - Friston, Karl J. - Jan, Jiří - Brázdil, Milan - Calhoun, Vince D.
PY  - 2011
TI  - Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering
JF  - NeuroImage
VL  - 56
IS  - 4
SP  - 2109-2128
EP  - 2109-2128
PB  - ACADEMIC PRESS INC ELSEVIER SCIENCE
SN  - 10538119
KW  - STOCHASTIC DIFFERENTIAL-EQUATIONS
KW  - BOLD HEMODYNAMIC-RESPONSES
KW  - LOCAL LINEARIZATION METHOD
KW  - CEREBRAL BLOOD-FLOW
KW  - BRAIN ACTIVATION
KW  - BALLOON MODEL
KW  - SYSTEMS
KW  - SIGNALS
KW  - NOISE
KW  - SIMULATION
N2  - This paper presents a new approach to inverting (fitting) models of coupled dynamical systems based on state-of-the-art (cubature) Kalman filtering. Our scheme promises to provide a significant advance in characterizing the functional architectures of distributed neuronal systems, even in the absence of known exogenous (experimental) input; e.g., resting state fMRI studies and spontaneous fluctuations in electrophysiological studies. Importantly, unlike current Bayesian filters (e.g. DEM), our scheme provides estimates of time-varying parameters, which we will exploit in future work on the adaptation and enabling of connections in the brain.
ER  -

HAVLÍČEK, Martin, Karl J. FRISTON, Jiří JAN, Milan BRÁZDIL and Vince D. CALHOUN. Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering. \textit{NeuroImage}. ACADEMIC PRESS INC ELSEVIER SCIENCE, 2011, vol.~56, No~4, p.~2109-2128. ISSN~1053-8119. Available from: https://dx.doi.org/10.1016/j.neuroimage.2011.03.005.

Detailed Information on Publication Record