Epilepsy has been historically seen as a functional brain disorder associated with excessive
synchronization of large neuronal populations leading to a hypersynchronous state. Recent …

The problem of reconstructing nonlinear and complex dynamical systems from measured
data or time series is central to many scientific disciplines including physical, biological …

Causal inference in complex systems has been largely promoted by the proposal of some
advanced temporal causation models. However, temporal models have serious limitations …

Quantifying the spatial and interconnected structure of regional to continental scale droughts
is one of the unsolved global hydrology problems, which is important for understanding the …

Identifying causal networks is important for effective policy and management
recommendations on climate, epidemiology, financial regulation, and much else. We …

An important problem across many scientific fields is the identification of causal effects from
observational data alone. Recent methods (convergent cross mapping, CCM) have made …

For decades, the main ways to study the effect of one part of the nervous system upon
another have been either to stimulate or lesion the first part and investigate the outcome in …

One of the central questions in neuroscience is how communication in the brain is organized
under normal conditions and how this architecture breaks down in neurological disease. It …

Synchronization of chaos refers to a process wherein two (or many) chaotic systems (either
equivalent or nonequivalent) adjust a given property of their motion to a common behavior …

Many complex and interesting phenomena in nature are due to nonlinear phenomena. The
theory of nonlinear dynamical systems, also called 'chaos theory', has now progressed to a …