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BMC Neuroscience

, 14:P37 | Cite as

Zero-lag synchronization in cortical motifs

  • Leonardo L Gollo
  • Claudio Mirasso
  • Olaf Sporns
  • Michael Breakspear
Open Access
Poster presentation

Keywords

Network Motif Conduction Delay Driving Motif Parameter Mismatch Cortical Motif 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Zero-lag synchronization between distant cortical areas has been observed in diverse experimental settings, and between many different regions of the brain [1, 2]. Several mechanisms have been proposed to account for such isochronous synchronization in the presence of long conduction delays: Of these, the phenomena of "dynamical relaying" - a mechanism that relies on a specific network motif (M9) - has proven to be the most robust with respect to parameter and system noise [2, 3, 4]. Surprisingly, despite a prevailing belief in the community, the common driving motif (M3) is an unreliable means of establishing zero-lag synchrony. Although dynamical relaying has been validated in empirical and computational studies [4], the deeper dynamical mechanisms and comparison to dynamics on other motifs is lacking (see Figure 1). Given the presence of different network motifs in cortical systems, such deeper insights are of high priority. By systematically comparing synchronization on a variety of small motifs, we establish that the presence of a single reciprocally connected pair - a "resonance pair" - plays a crucial role in disambiguating those motifs that foster zero-lag synchrony in the presence of conduction delays (such as dynamical relaying, M9) from those that do not (such as the common driving triad, M3). Remarkably, minor structural changes to M3 that incorporate a reciprocal pair (hence M6, M9, M3+1) recovers robust zero-lag synchrony. The findings are observed in computational models of spiking neurons, populations of spiking neurons and mean field neural models, and arise whether the systems are periodic, chaotic, noise-free or driven by stochastic inputs. The influence of the resonant pair is also robust to parameter mismatch and asymmetrical time delays amongst the elements of the motif. The synchronization of the commonly driven nodes is optimal when the driver node is part of a resonant pair, or is under the influence of another resonant pair (since its effect can propagate in the network). We call this manner of facilitating zero-lag synchrony resonance-induced synchronization and propose that it may be a critical feature of zero-lag synchrony in the brain.
Figure 1

Motifs and zero-lag cross-correlations between nodes 1 and 3 in mean field neural models for varying coupling strength (left panel) and delay (right panel).

References

  1. 1.
    Roelfsema PR, Engel AK, Konig P, Singer W: Visuomotor integration is associated with zero time-lag synchronization among cortical areas. Nature. 1997, 385: 157-161. 10.1038/385157a0.CrossRefPubMedGoogle Scholar
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    Vicente R, Gollo LL, Mirasso CR, Fischer I, Pipa G: Dynamical relaying can yield zero time lag neuronal synchrony despite long conduction delays. Proc Natl Acad Sci. 2008, 105 (44): 17157-17162. 10.1073/pnas.0809353105.PubMedCentralCrossRefPubMedGoogle Scholar
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    Gollo LL, Mirasso CR, Villa AE: Dynamic control for synchronization of separated cortical areas through thalamic relay. Neuroimage. 2010, 52 (3): 947-55. 10.1016/j.neuroimage.2009.11.058.CrossRefPubMedGoogle Scholar
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    Gollo LL, Mirasso CR, Atienza M, Crespo-Garcia M, Cantero JL: Theta band zero-lag long-range cortical synchronization via hippocampal dynamical relaying. PLoS ONE. 2011, 6 (3): e17756-10.1371/journal.pone.0017756.PubMedCentralCrossRefPubMedGoogle Scholar

Copyright information

© Gollo 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.

Authors and Affiliations

  • Leonardo L Gollo
    • 1
    • 2
  • Claudio Mirasso
    • 1
  • Olaf Sporns
    • 3
  • Michael Breakspear
    • 2
    • 4
    • 5
  1. 1.IFISC, Instituto de Física Interdisciplinar y Sistemas Complejos (CSIC-UIB)Palma de MallorcaSpain
  2. 2.Program of Mental Health ResearchQueensland Institute of Medical ResearchBrisbaneAustralia
  3. 3.Department of Psychological and Brain SciencesIndiana UniversityBloomingtonUSA
  4. 4.School of PsychiatryUniversity of New South Wales and The Black Dog InstituteSydneyAustralia
  5. 5.The Royal Brisbane and Woman's HospitalBrisbaneAustralia

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