Rhythmic behavior represents one of the most striking and ubiquitous manifestations of
functional evolution for a wide class of natural and man-made systems. The emergence of …

Time-delayed optoelectronic oscillators are at the center of a large body of scientific
literature. The complex behavior of these nonlinear oscillators has been thoroughly explored …

Our ability to manipulate the behavior of complex networks depends on the design of
efficient control algorithms and, critically, on the availability of an accurate and tractable …

The biologist JBS Haldane, when asked what we can learn about the Creator by examining
the world, is said to have replied “an inordinate fondness for beetles”[705]. Today's …

The concept of reservoir computing emerged from a specific machine learning paradigm
characterized by a three-layered architecture (input, reservoir, and output), where only the …

Graph theory is now becoming a standard tool in system-level neuroscience. However,
endowing observed brain anatomy and dynamics with a complex network structure does not …

When describing complex interconnected systems, one often has to go beyond the standard
network description to account for generalized interactions. Here, we establish a unified …

Networks in nature have complex interactions among agents. One significant phenomenon
induced by interactions is synchronization of coupled agents, and the interactive network …

Topological signals defined on nodes, links and higher dimensional simplices define the
dynamical state of a network or of a simplicial complex. As such, topological signals are …

Spontaneous symmetry breaking is central to our understanding of physics and explains
many natural phenomena, from cosmic scales to subatomic particles. Its use for applications …