The development of new technologies for mapping structural and functional brain
connectivity has led to the creation of comprehensive network maps of neuronal circuits and …

We introduce comparative connectomics, the quantitative study of cross-species
commonalities and variations in brain network topology that aims to discover general …

The human brain can be represented as a graph in which neural units such as cells or small
volumes of tissue are heterogeneously connected to one another through structural or …

Many real-world networks, including nervous systems, exhibit meso-scale structure. This
means that their elements can be grouped into meaningful subnetworks. In general, these …

We formulate an info-clustering paradigm based on a multivariate information measure,
called multivariate mutual information, that naturally extends Shannon's mutual information …

In this work, a novel self-organizing model called growing neural forest (GNF) is presented. It
is based on the growing neural gas (GNG), which learns a general graph with no special …

There is considerable interest in elucidating the cluster structure of brain networks in terms
of modules, blocks or clusters of similar nodes. However, it is currently challenging to handle …

In the present work we study a family of generative network model and its applications for
modeling the human connectome. We introduce a minor but novel variant of the Mixed …

Network representations have been effectively employed to analyze complex systems
across various areas and applications, leading to the development of network science as a …

The human brain and its temporal behavior correlated with development, structure, and
function is a complex natural system even for its own kind. Coding and automation are …