Bayesian inference of a directional brain network model for intracranial EEG data

Zhang, Tingting; Sun, Yinge; Li, Huazhang; Gao, Yan; Tanabe, Seiji; Miao, Ruizhong; Wang, Yaotian; Caffo, Brian; Quigg, Mark

doi:10.1016/j.csda.2019.106847

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Cited by 3 publications

(1 citation statement)

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“…To address this limitation, [20][21][22] proposed to use linear ODEs to approximate highdimensional brain systems (consisting of many regions). However, parameter estimation of deterministic ODE models is sensitive to the model specification, data noise, and data-sampling frequency.…”

Section: Introductionmentioning

confidence: 99%

A Bayesian State-Space Approach to Mapping Directional Brain Networks

Wang

Gao

et al. 2020

Preprint

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Section: Introductionmentioning

confidence: 99%

A Bayesian State-Space Approach to Mapping Directional Brain Networks

Wang

Gao

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

A Bayesian State-Space Approach to Mapping Directional Brain Networks

Wang

Gao

et al. 2021

Journal of the American Statistical Association

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Green’s matching: an efficient approach to parameter estimation in complex dynamic systems

Tan,

Zhang,

Wang

et al. 2024

Journal of the Royal Statistical Society Series B: Statistical Methodology

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Parameters of differential equations are essential to characterize intrinsic behaviours of dynamic systems. Numerous methods for estimating parameters in dynamic systems are computationally and/or statistically inadequate, especially for complex systems with general-order differential operators, such as motion dynamics. This article presents Green’s matching, a computationally tractable and statistically efficient two-step method, which only needs to approximate trajectories in dynamic systems but not their derivatives due to the inverse of differential operators by Green’s function. This yields a statistically optimal guarantee for parameter estimation in general-order equations, a feature not shared by existing methods, and provides an efficient framework for broad statistical inferences in complex dynamic systems.

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Bayesian inference of a directional brain network model for intracranial EEG data

Cited by 3 publications

References 52 publications

A Bayesian State-Space Approach to Mapping Directional Brain Networks

A Bayesian State-Space Approach to Mapping Directional Brain Networks

A Bayesian State-Space Approach to Mapping Directional Brain Networks

Green’s matching: an efficient approach to parameter estimation in complex dynamic systems

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