Social network analysis (SNA) is a core pursuit of analyzing social networks today. In
addition to the usual statistical techniques of data analysis, these networks are investigated …

The power of any kind of network approach lies in the ability to simplify a complex system so
that one can better understand its function as a whole. Sometimes it is beneficial, however …

Complex systems, composed at the most basic level of units and their interactions, describe
phenomena in a wide variety of domains, from neuroscience to computer science and …

Graph theory provides a language for studying the structure of relations, and it is often used
to study interactions over time too. However, it poorly captures the intrinsically temporal and …

Complex networks have emerged as a simple yet powerful framework to represent and
analyze a wide range of complex systems. The problem of ranking the nodes and the edges …

For several years it has been argued that neural synchronisation is crucial for cognition. The
idea that synchronised temporal patterns between different neural groups carries …

Persistence is an important characteristic of many complex systems in nature, related to how
long the system remains at a certain state before changing to a different one. The study of …

The central nervous system is composed of many individual units–from cells to areas–that
are connected with one another in a complex pattern of functional interactions that supports …

This book explores social mechanisms that drive network change and link them to
computationally sound models of changing structure to detect patterns. This text identifies …

Network neuroscience has become an established paradigm to tackle questions related to
the functional and structural connectome of the brain. Recently, interest has been growing in …