Guillaume Marrelec

Automated extraction of mutual independence patterns using Bayesian comparison of partition models

Mutual independence is a key concept in statistics that characterizes the structural relationships between variables. Existing methods to investigate mutual independence rely on the definition of...

A Bayesian alternative to mutual information for the hierarchical clustering of dependent random variables

The use of mutual information as a similarity measure in agglomerative hierarchical clustering (AHC) raises an important issue: some correction needs to be applied for the dimensionality of...

Conditional independence graphs for functional connectivity in functional MRI

NEDICA: Detection of group functional networks in FMRI using spatial independent component analysis

Identification of functional cortico-subcortical networks in resting-state FMRI: a combined NEDICA and GLM analysis

Robust estimation of the hemodynamic response function in asynchronous multitasks multisessions event-related fMRI paradigms

Conditional integration as a way of measuring mediated interactions between large-scale brain networks in functional MRI

A Level Set Method for Building Anatomical Connectivity Paths Between Brain Areas Using DTI

Selection of Spatially Independent Components to Explain Functional Connectivity In fMRI

Identification of A Large-Scale Functional Network In Functional Magnetic Resonance Imaging

Estimation of the Hemodynamic Response Function in Event-Related Functional MRI: Directed Acyclic Graphs for a General Bayesian Inference Framework

Extracting Transient Phase-Amplitude Coupling from Resting-State EEG Signals

Heading for data-driven measures of effective connectivity in functional MRI

An inferential measure of dependence between two systems using Bayesian model comparison

We propose to quantify dependence between two systems $X$ and $Y$ in a dataset $D$ based on the Bayesian comparison of two models: one, $H_0$, of statistical independence and another one, $H_1$,...

Cumulants of multiinformation density in the case of a multivariate normal distribution

We consider a generalization of information density to a partitioning into $N \geq 2$ subvectors. We calculate its cumulant-generating function and its cumulants, showing that these quantities are...