Functional connectivity inference from fMRI data using multivariate information measures

Q Li - Neural Networks, 2022 - Elsevier
Shannon's entropy or an extension of Shannon's entropy can be used to quantify information
transmission between or among variables. Mutual information is the pair-wise information …

Measuring the rate of information exchange in point-process data with application to cardiovascular variability

G Mijatovic, R Pernice, A Perinelli… - Frontiers in Network …, 2022 - frontiersin.org
The amount of information exchanged per unit of time between two dynamic processes is an
important concept for the analysis of complex systems. Theoretical formulations and data …

Network representation of multicellular activity in pancreatic islets: Technical considerations for functional connectivity analysis

M Šterk, Y Zhang, V Pohorec, EP Leitgeb… - PLOS Computational …, 2024 - journals.plos.org
Within the islets of Langerhans, beta cells orchestrate synchronized insulin secretion, a
pivotal aspect of metabolic homeostasis. Despite the inherent heterogeneity and multimodal …

Estimation of complete mutual information exploiting nonlinear magnitude-phase dependence: Application to spatial FNC for complex-valued fMRI data

WX Li, QH Lin, CY Zhang, Y Han, HJ Li… - Journal of Neuroscience …, 2024 - Elsevier
Background Real-valued mutual information (MI) has been used in spatial functional
network connectivity (FNC) to measure high-order and nonlinear dependence between …

Measuring the Amount of Concomitant Firing during Neural Development

G Mijatovic, N Vukosavljevic… - 2022 IEEE 20th …, 2022 - ieeexplore.ieee.org
The aim of this work was to estimate and compare the amount of concomitant firing in the
neural dynamics of dissociated in-vitro cultures analyzed across various stages of …