We propose a method which uses causality to obtain a measure of effective connectivity from fMRI data.
We propose a method which uses causality to obtain a measure of effective connectivity from fMRI data.
May 5, 2014 · In this paper we proposed a variational Bayesian causal connectivity method for fMRI. The method uses a VAR model for the neuronal time series ...
Variational Bayesian causal connectivity analysis for fMRI. https://doi.org/10.3389/fninf.2014.00045 · Full text. Journal: Frontiers in Neuroinformatics, 2014.
We propose a method which uses causality to obtain a measure of effective connectivity from fMRI data. The method uses a vector autoregressive model for the ...
We describe a Bayesian estimation and inference procedure for fMRI time series based on the use of General Linear Models with Autoregressive (AR) error ...
Variational Bayesian causal connectivity analysis for fMRI ; ISSN · 1662-5196 ; Year of publication · 2014 ; Volume · 8 ; Issue · MAY ; Type · Article.
Oct 1, 2018 · On the importance of modeling fMRI transients when estimating effective connectivity: a dynamic causal modeling study using ASL data.
Overall, the proposed Bayesian model pro- vides a flexible and robust framework for combining fMRI data of many subjects to characterize brain networks in ...
While these VAR-based models have significantly advanced the understanding of brain connectivity, they do not account for subject heterogeneity. ... Bayesian ...