The simultaneous recording of the activity of many neurons poses challenges for
multivariate data analysis. Here, we propose a general scheme of reconstruction of the …

Functional-effective connectivity and network topology are nowadays key issues for studying
brain physiological functions and pathologies. Inferring neuronal connectivity from …

Inferring connectivity in neuronal networks remains a key challenge in statistical
neuroscience. The “common input” problem presents a major roadblock: it is difficult to …

This article presents a review of computational methods for connectivity inference from
neural activity data derived from multi-electrode recordings or fluorescence imaging. We first …

We apply an information-theoretic treatment of action potential time series measured with
microelectrode arrays to estimate the connectivity of mammalian neuronal cell assemblies …

Identifying functional connectivity between neuronal elements is an essential first step
toward understanding how the brain orchestrates information processing at the single-cell …

Knowing brain connectivity is of great importance both in basic research and for clinical
applications. We are proposing a method to infer directed connectivity from zero-lag …

In this work, a novel approach based on the estimate of time-varying graph indices is
proposed in order to capture the basic schemes of communication within the functional brain …

Identifying the structure and dynamics of synaptic interactions between neurons is the first
step to understanding neural network dynamics. The presence of synaptic connections is …

Nowadays, the use of in vitro reduced models of neuronal networks to investigate the
interplay between structural-functional connectivity and the emerging collective dynamics is …