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

Article in a journal

Field of Study

30000 3. Medical and Health Sciences

Country of publisher

United States of America

Confidentiality degree

is not subject to a state or trade secret

Impact factor

Impact factor: 5.895

RIV identification code

RIV/00216224:14740/11:00055575

Organization unit

Central European Institute of Technology

DOI

https://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

In the original language

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.

Cite

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://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 = {https://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://doi.org/10.1016/j.neuroimage.2011.03.005.

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