![]() It was shown that global coupling, either by square pulses or via electrical synapses (gap junctions), can lead to network synchronization with strong coherence. The collective effects of coupling on CR were subsequently investigated. At the resonance, the spike train looks almost periodic, despite the fact that the system is in an excitable regime, not tonic. In the low-noise regime, the spike train approaches a Poissonian incoherent behavior with small firing rate, whereas in the high-noise regime incoherence coexists with a large firing rate. In 1997, for instance, Pikovsky and Kurths unveiled the phenomenon of coherence resonance (CR), whereby an excitable system driven by white noise produces a spike train whose regularity (or coherence) attains a maximum at some finite value of the noise intensity. Įven single neurons, however, can reveal surprises. Recently, even the notion of networks of networks have emerged in the context of climate studies. With the emergence of complex networks becoming a research topic in itself, the effects of topology on synchronization have been thoroughly investigated (see e.g. Since the seminal work of Kuramoto, for example, several aspects of synchronization have been addressed. More generally, the last decades witnessed a surge in theoretical studies of collective phenomena of interacting nonlinear units. This interplay between nonlinearity, high dimensionality and noise is what renders the brain a difficult and interesting system to study. Neurons are highly nonlinear dynamical systems which are typically connected to tens of thousands of other neurons, the whole system being subjected to fluctuations whose stochasticity cannot be dismissed. ![]() The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.įunding: Financial support by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco (FACEPE) and special programs Programa de Apoio a Núcleos Emergentes (PRONEM) and Programa de Apoio a Núcleos de Excelência (PRONEX) are acknowledged. Received: JAccepted: OctoPublished: December 2, 2013Ĭopyright: © 2013 Medeiros, Copelli. PLoS ONE 8(12):Įditor: Daniele Marinazzo, Universiteit Gent, Belgium The results were reproduced by numerical simulations of a pair of synaptically coupled FitzHugh-Nagumo models.Ĭitation: Medeiros BNS, Copelli M (2013) Synaptic Symmetry Increases Coherence in a Pair of Excitable Electronic Neurons. We also show that synapses with a longer time scale sharpen the dependency of the coherence on the synaptic symmetry. Synaptic symmetry plays an important role in this process and, under the right choice of parameters, increases the network coherence beyond the value achieved at the resonance due to noise alone in uncoupled neurons. More interestingly, we show that the decrease of coherence can be reverted if we add a synapse of sufficient strength in the reverse direction. In particular, we show that increasing the strength of an unidirectional synapse leads to a decrease of coherence in the post-synaptic neuron. ![]() The coupling is provided by electronic circuits which mimic the dynamics of chemical AMPA synapses. We study how the synaptic connections in a pair of excitable electronic neurons affect the coherence of their spike trains when the neurons are submitted to noise from independent sources. ![]()
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