Emergence is a profound subject that straddles many scientific disciplines, including the
formation of galaxies and how consciousness arises from the collective activity of neurons …

Competing and complementary models of resting-state brain dynamics contribute to our
phenomenological and mechanistic understanding of whole-brain coordination and …

This paper introduces a model-agnostic approach to study statistical synergy, a form of
emergence in which patterns at large scales are not traceable from lower scales. Our …

Integrated Information Theory (IIT) is a prominent theory of consciousness that has at its
centre measures that quantify the extent to which a system generates more information than …

The formulation of the Partial Information Decomposition (PID) framework by Williams and
Beer in 2010 attracted a significant amount of attention to the problem of defining redundant …

What are the distinct ways in which a set of predictor variables can provide information about
a target variable? When does a variable provide unique information, when do variables …

Abstract Information theoretic measures can be used to identify nonlinear interactions
between source and target variables through reductions in uncertainty. In information …

The human brain generates a rich repertoire of spatio-temporal activity patterns, which
support a wide variety of motor and cognitive functions. These patterns of activity change …

Multivariate information decompositions hold promise to yield insight into complex systems,
and stand out for their ability to identify synergistic phenomena. However, the adoption of …

Accurately determining dependency structure is critical to understanding a complex system's
organization. We recently showed that the transfer entropy fails in a key aspect of this …