A complete understanding of the brain requires an integrated description of the numerous
scales and levels of neural organization. This means studying the interplay of genes and …

The brain is a highly complex system. Most of such complexity stems from the intermingled
connections between its parts, which give rise to rich dynamics and to the emergence of …

This unique textbook provides an introduction to statistical inference with network data. The
authors present a self-contained derivation and mathematical formulation of methods …

Antimony is a scarce strategic metal and plays an extremely important role in the modern
societies. Due to the increasing demands for various antimony-containing products, it is …

The network architecture of the human brain contributes in shaping neural activity,
influencing cognitive and behavioral processes. The availability of neuroimaging data …

Exponential-family Random Graph Models (ERGMs) constitute a large statistical framework
for modeling dense and sparse random graphs with short-or long-tailed degree distributions …

Human brain connectivity is complex. Graph-theory-based analysis has become a powerful
and popular approach for analyzing brain imaging data, largely because of its potential to …

Most social network analyses conducted in hospitality and tourism studies are merely
descriptive. Despite the recent popularity of exponential-family of random graph models …

Clinical network neuroscience, the study of brain network topology in neurological and
psychiatric diseases, has become a mainstay field within clinical neuroscience. Being a …

The uncertainty underlying real-world phenomena has attracted attention toward statistical
analysis approaches. In this regard, many problems can be modeled as networks. Thus, the …