Different aspects of the predictability problem in dynamical systems are reviewed. The deep
relation among Lyapunov exponents, Kolmogorov–Sinai entropy, Shannon entropy and …

Cortical evoked potentials are of interest primarily as tests of changing neuronal
excitabilities accompanying normal brain function. The first three steps in the anal ysis of …

Chaos: from simple models to complex systems aims to guide science and engineering
students through chaos and nonlinear dynamics from classical examples to the most recent …

Sensing and perceiving involve enormous numbers of widely distributed dendritic and
action potentials in cortex, before, during and after stimulus arrival but with differing …

Chaos in science has always been a fascinating realm since it challenges the usual
scientific approach of reductionism. While carefully distinguishing between complexity …

We study the dynamics of two symmetrically coupled populations of identical leaky integrate-
and-fire neurons characterized by an excitatory coupling. Upon varying the coupling …

In experiments, the dynamical behavior of systems is reflected in time series. Due to the
finiteness of the observational data set, it is not possible to reconstruct the invariant measure …

Dynamic excitatory-inhibitory (EI) balance is a paradigmatic mechanism invoked to explain
the irregular low firing activity observed in the cortex. However, we will show that the EI …

In dynamical systems, the growth of infinitesimal perturbations is well characterized by the
Lyapunov exponents. In many situations of interest, however, important phenomena involve …

We investigate a network of integrate-and-fire neurons characterized by a distribution of
spiking frequencies. Upon increasing the coupling strength, the model exhibits a transition …