BookA. Ravishankar Rao, Guillermo A. Cecchi, editors.
Contents:
Introduction
Adaptation and contraction theory for the synchronization of complex neural networks
Temporal coding is not only about cooperation, it is also about competition
Using non-oscillatory dynamics to disambiguate pattern mixtures
Functional constraints on network topology via generalized sparse
Evolution of time in neural networks, from the present to the past, and forward to the future
Synchronization of coupled pulse-type hardware neuron models for CPG model
A univesal abstract-time platform for real-time neural networks
Solving complex control tasks via simple rule(s), using chaotic dynamics in a recurrent neural network model
Time scale analysis of neuronal ensemble data used to feed neural network models
Simultaneous EEG-fMRI, integrating spatial and temporal resolution
Erratum to: Time scale analysis of neuronal ensemble data used to feed neural network models.