Volume 14 Supplement 1

Abstracts from the Twenty Second Annual Computational Neuroscience Meeting: CNS*2013

Open Access

Anticipated synchronization in neuronal motifs

  • Fernanda S Matias1, 2Email author,
  • Leonardo L Gollo2, 3,
  • Pedro V Carelli1,
  • Mauro Copelli1 and
  • Claudio R Mirasso2
BMC Neuroscience201314(Suppl 1):P275

DOI: 10.1186/1471-2202-14-S1-P275

Published: 8 July 2013

Anticipated synchronization (AS) is a counterintuitive stable dynamical regime discovered by Voss in the last decade [1]. It consists in the stable synchronized regime between two identical autonomous dynamical systems coupled (unidirectionally) in a master-slave (MS) configuration, if the slave also receives a negative delayed self-feedback. In such regime the slave predicts the master. Although AS has shown to be stable in a variety of theoretical studies [13] and in experimental observations [4] with semiconductor lasers and electronic circuits, studies in biological and neuronal systems are still lacking.

The first verification of AS in neuronal models was done between two FitzHugh-Nagumo neurons coupled in a MS configuration with negative delayed self-feedback and driven by white noise [2]. In neuronal networks, AS means that the slave (post-synaptic) neuron can fire spikes right before the master (pre-synaptic) neuron. However the slave delayed self-feedback that induces the anticipated synchronization as suggested by Voss is unrealistic in neuronal circuitry.

Recently, it has been shown that in a biologically plausible neuronal model, the self-feedback can be replaced by an inhibitory loop mediated by an interneuron and chemical synapses [5]. This master-slave-interneuron motif exhibits the usual delay synchronized (DS) regime for small values of the inhibitory synaptic conductance (g) as well as the AS regime for larger g. Moreover, the time delay between consecutive spikes of the master and the slave neurons is a function of the synaptic conductances. Both regimes were shown to be stable for a large set of parameters, different external currents, structural motif and neuron models [6]. Here we investigate the robustness of AS for others motifs, larger populations, neuronal heterogeneity and noise. In all the situations the transition from DS to AS is continuous and smooth.



We acknowledge financial support from CNPq, CAPES, FACEPE, PRONEX, PRONEM, INCeMaq, proyecto FISICOS (MICCIN-FEDER) and Govern de les Illes Balears.

Authors’ Affiliations

Departmento de Física, Universidade Federal de Pernambuco
Instituto de Física Interdisciplinar y Sistemas Complejos, CSIC-UIB, Campus Univesitat de les Illes Balears
Systems Neuroscience Group, Queensland Institute of Medical Research


  1. Voss HU: Anticipating chaotic synchronization. Phys Rev E. 2000, 61: 5115-5119. 10.1103/PhysRevE.61.5115.View ArticleGoogle Scholar
  2. Ciszak M, Calvo O, Masoller C, Mirasso CR, Toral R: Anticipating the response of excitable systems driven by random frocing. Phys Rev Lett. 2003, 90: 204102-204104.View ArticlePubMedGoogle Scholar
  3. Masoller C, Zanette DH: Anticipated synchronization in coupled chaotic maps with delays. Physica A. 2001, 300: 359-366. 10.1016/S0378-4371(01)00362-4.View ArticleGoogle Scholar
  4. Sivaprakasam S, Shahverdiev EM, Spencer PS, Shore KA: Experimental demonstration of anticipating synchronization in chaotic semiconductor lasers with optical feedback. Prys Rev Lett. 2001, 87: 154101-View ArticleGoogle Scholar
  5. Matias FS, Carelli PV, Mirasso CR, Copelli M: Anticipated synchronization in a biologically plausible model of neuronal motif. Phys Rev E. 2011, 84: 021922-021929.View ArticleGoogle Scholar
  6. Matias FS, Gollo LL, Carelli PV, Copelli M, Mirasso CR: Anticipated synchronization in neuronal network motifs. AIP Conference Proceedings. 2013, 1510: 210-212.View ArticleGoogle Scholar


© Matias et al; licensee BioMed Central Ltd. 2013

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.