A brain atlas of axonal and synaptic delays based on modelling of cortico-cortical evoked potentials.

Epilepsy presurgical investigation may include focal intracortical single-pulse electrical stimulations with depth electrodes, which induce cortico-cortical evoked potentials at distant sites because of white matter connectivity. Cortico-cortical evoked potentials provide a unique window on functional brain networks because they contain sufficient information to infer dynamical properties of large-scale brain connectivity, such as preferred directionality and propagation latencies.  Here, we developed a biologically informed modelling approach to estimate the neural physiological parameters of brain functional networks from the cortico-cortical evoked potentials recorded in a large multicentric database.

Probabilistic functional tractography of the human cortex revisited.

In patients with pharmaco-resistant focal epilepsies investigated with intracranial electroencephalography (iEEG), direct electrical stimulations of a cortical region induce cortico-cortical evoked potentials (CCEP) in distant cerebral cortex, which properties can be used to infer large scale brain connectivity. In 2013, we proposed a new probabilistic functional tractography methodology to study human brain connectivity. We have now been revisiting this method in the F-TRACT project (f-tract.

Automatic bad channel detection in intracranial electroencephalographic recordings using ensemble machine learning.

Objective: Intracranial electroencephalographic (iEEG) recordings contain "bad channels", which show non-neuronal signals. Here, we developed a new method that automatically detects iEEG bad channels using machine learning of seven signal features.

Methods: The features quantified signals' variance, spatial-temporal correlation and nonlinear properties.

Estimation of Myocardial Strain and Contraction Phase From Cine MRI Using Variational Data Assimilation.

This paper presents a new method to estimate left ventricle deformations using variational data assimilation that combines image observations from cine MRI and a dynamic evolution model of the heart. The main contribution of the model is that it embeds parameters modeling the contraction / relaxation process. It estimates myocardial motion and contraction parameters simultaneously, providing accurate complementary information for diagnosis.