119 citations · 183 across the 10 of their papers we have counts for
5 papers · 1 filter
Evolving reservoir computers reveals bidirectional coupling between predictive power and emergent dynamics
Hanna M. Tolle, Andrea I Luppi, Anil K. Seth +1
Biological neural networks can perform complex computations to predict their environment, far above the limited predictive capabilities of individual neurons. While conventional ap…
Information decomposition reveals hidden high-order contributions to temporal irreversibility
Andrea I Luppi, Fernando E. Rosas, Gustavo Deco +2
Temporal irreversibility, often referred to as the arrow of time, is a fundamental concept in statistical mechanics. Markers of irreversibility also provide a powerful characterisa…
Synergistic information supports modality integration and flexible learning in neural networks solving multiple tasks
Alexandra M. Proca, Fernando E. Rosas, Andrea I. Luppi +3
Striking progress has recently been made in understanding human cognition by analyzing how its neuronal underpinnings are engaged in different modes of information processing. Spec…
Greater than the parts: A review of the information decomposition approach to causal emergence
Pedro A. M. Mediano, Fernando E. Rosas, Andrea I. Luppi +5
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…
Towards an extended taxonomy of information dynamics via Integrated Information Decomposition
Pedro A. M. Mediano, Fernando E. Rosas, Andrea I Luppi +4
Complex systems, from the human brain to the global economy, are made of multiple elements that interact in such ways that the behaviour of the `whole' often seems to be more than…