title: Effects of Spike Anticipation on the Spiking Dynamics of Neural Networks.
abstract: Synchronization is one of the central phenomena involved in information processing in living systems. It is known that the nervous system requires the coordinated activity of both local and distant neural populations. Such an interplay allows to merge different information modalities in a whole processing supporting high-level mental skills as understanding, memory, abstraction, etc. Though, the biological processes underlying synchronization in the brain are not fully understood there have been reported a variety of mechanisms supporting different types of synchronization both at theoretical and experimental level. One of the more intriguing of these phenomena is the anticipating synchronization, which has been recently reported in a pair of unidirectionally coupled artificial neurons under simple conditions (Pyragiene and Pyragas, 2013), where the slave neuron is able to anticipate in time the behavior of the master one. In this paper, we explore the effect of spike anticipation over the information processing performed by a neural network at functional and structural level. We show that the introduction of intermediary neurons in the network enhances spike anticipation and analyse how these variations in spike anticipation can significantly change the firing regime of the neural network according to its functional and structural properties. In addition we show that the interspike interval (ISI), one of the main features of the neural response associated with the information coding, can be closely related to spike anticipation by each spike, and how synaptic plasticity can be modulated through that relationship. This study has been performed through numerical simulation of a coupled system of Hindmarsh-Rose neurons.
authors.affiliation: Group of Biometrics, Biosignals and Security, Research Centre for Smart Buildings and Energy Efficiency (CeDInt), Technical University of Madrid Madrid, Spain ; Laboratory of Computational System Biology, Center for Biomedical Technology, Technical University of Madrid Madrid, Spain.
authors.forename: Daniel
authors.initials: D
authors.lastname: de Santos-Sierra
authors.affiliation: Department of Applied Mathematics (Biomathematics), School of Biological Sciences, Universidad Complutense de Madrid Madrid, Spain.
authors.forename: Abel
authors.initials: A
authors.lastname: Sanchez-Jimenez
authors.affiliation: Laboratory of Computational System Biology, Center for Biomedical Technology, Technical University of Madrid Madrid, Spain.
authors.forename: Mariano A
authors.initials: MA
authors.lastname: Garcia-Vellisca
authors.affiliation: Laboratory of Computational System Biology, Center for Biomedical Technology, Technical University of Madrid Madrid, Spain.
authors.forename: Adrian
authors.initials: A
authors.lastname: Navas
authors.affiliation: Group of Biometrics, Biosignals and Security, Research Centre for Smart Buildings and Energy Efficiency (CeDInt), Technical University of Madrid Madrid, Spain ; Department of Applied Mathematics, School of Mathematics, Universidad Complutense de Madrid Madrid, Spain.
authors.forename: Jose A
authors.initials: JA
authors.lastname: Villacorta-Atienza
keywords: chaotic dynamical systems; information processing; neural networks; spike anticipation; synchronization