biostudies-literatureBenozzo DFinnish Cultural FoundationFondazione Bruno KesslerDutch Research Council (NWO)e0177359https://www.ebi.ac.uk/biostudies/studies/S-EPMC5436686biostudies-literatureUnknown12(5)In many fields of science, there is the need of assessing the causal influences among time series. Especially in neuroscience, understanding the causal interactions between brain regions is of primary importance. A family of measures have been developed from the parametric implementation of the Granger criteria of causality based on the linear autoregressive modelling of the signals. We propose a new Bayesian method for linear model identification with a structured prior (GMEP) aiming to apply it as linear regression method in the context of the parametric Granger causal inference. GMEP assumes a Gaussian scale mixture distribution for the group sparsity prior and it enables flexible definition of the coefficient groups. Approximate posterior inference is achieved using Expectation PropagaPloS oneBayesian estimation of directed functional coupling from brain recordings.PMC5436686612.001.211639.072.513Avesani PJylanki POlivetti Evan Gerven MAJBenozzo DfalseBayesian estimation of directed functional coupling from brain recordings.In many fields of science, there is the need of assessing the causal influences among time series. Especially in neuroscience, understanding the causal interactions between brain regions is of primary importance. A family of measures have been developed from the parametric implementation of the Granger criteria of causality based on the linear autoregressive modelling of the signals. We propose a new Bayesian method for linear model identification with a structured prior (GMEP) aiming to apply it as linear regression method in the context of the parametric Granger causal inference. GMEP assumes a Gaussian scale mixture distribution for the group sparsity prior and it enables flexible definition of the coefficient groups. Approximate posterior inference is achieved using Expectation Propaga2017-01-01T00:00:00Z20172026-05-04T14:56:54.488Z2019-03-26T22:53:05ZS-EPMC54366862854506610.1371/journal.pone.0177359