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Transient synchrony in delayed coupled neuronal networks

Transient synchrony in delayed coupled neuronal networks Esfahani and Valizadeh BMC Neuroscience 2015, 16(Suppl 1):P269 http://www.biomedcentral.com/1471-2202/16/S1/P269 POSTER PRESENTATION Open Access Transient synchrony in delayed coupled neuronal networks 1* 1,2 Zahra G Esfahani , Alireza Valizadeh From 24th Annual Computational Neuroscience Meeting: CNS*2015 Prague, Czech Republic. 18-23 July 2015 In this study, we propose that in a pool of neurons recur- sensory or control input (Figure 1). It is important to note rently coupled through delayed synaptic connections that such an ability of the network to select frequencies of transient patterns of synchrony can be observed due to the oscillation is based on the presence of the delay in the changing incoming stimuli, in continuance of some communication between neurons. In a network in which recent works [1]. Transient synchrony between spiking the components communicate instantaneously–with activity of the neurons has been reported in different sen- delays ignored–the neurons either spike synchronously or asynchronously depending on the connections properties sory tasks e.g. visual and olfactory system [2,3]. We have shown that the critical role of the delay is to and regardless of the value of the input current and the prepare connections that their synchronizing/desynchro- frequency of the spiking of the neurons. nizing effect changes when they receive different levels of stimuli [4,5]. In a suitable range of parameters, need not to Conclusion be fine-tuned, an initially incoherent firing of the neurons We have shown that the ability of a neural network to can turn to coherent network oscillation when the mean switch between coherent and incoherent firing, may input is changed -not necessarily increased–through be dependent on the delay in communication between Figure 1 Raster Plot of an all-to-all network of 200 homogenously coupled neurons with time dependent stimuli (the violet curve), which switches between asynchronous incoherent state to a synchronous state when the input is changed. All the neurons are excitatory and external input to each neuron comprises a constant current chosen from a narrow normal distribution and an independent Gaussian white noise. The blue diagram presents the network activity. * Correspondence: nzahra-ghasemiiasbs@ac.ir Department of Physics, Institute for Advanced Studies in Basic Sciences, Zanjan, Iran Full list of author information is available at the end of the article © 2015 Esfahani and Valizadeh This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/ publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Esfahani and Valizadeh BMC Neuroscience 2015, 16(Suppl 1):P269 Page 2 of 2 http://www.biomedcentral.com/1471-2202/16/S1/P269 neurons. It has been shown that two reciprocally coupled neurons can fire inphase if the delays lie in the region where the phase response curve of the neurons have negative slope, otherwise their firing is antiphase. In the larger networks where the neurons connect to several other neurons, inphase firing state remains stable where instead of antiphase state, several stable states appear. This is related to geometric frustration in condensed matter physics where a plenitude of distinct ground states are ensued by the lattice structure as in Ising system. Authors’ details Department of Physics, Institute for Advanced Studies in Basic Sciences, Zanjan, Iran. School of Cognitive Sciences, IPM, Niavaran, Tehran, Iran. Published: 18 December 2015 References 1. Gollo LLeonardo, Breakspear Michael: The frustrated brain: from dynamics on motifs to communities and networks. Philo. Trans. of the Royal Society B: Biol. Sci 2014, 369(1653):20130532. 2. Maxim Bazhenov, et al: Model of transient oscillatory synchronization in the locust antennal lobe. Neuron 2001, 30(2):553-567. 3. Tatsuya Mima, et al: Transient interhemispheric neuronal synchrony correlates with object recognition. The Journal of Neuroscience 2001, 21(11):3942-3948. 4. Sadjad Sadeghi, Valizadeh Alireza: Synchronization of delayed coupled neurons in presence of inhomogeneity. Journal of computational neuroscience 2014, 36(1):55-66. 5. Esfahani GhZahra, Valizadeh Alireza: Zero-Lag Synchronization Despite Inhomogeneities in a Relay System. PloS one 2014, 9(12):e11268. doi:10.1186/1471-2202-16-S1-P269 Cite this article as: Esfahani and Valizadeh: Transient synchrony in delayed coupled neuronal networks. BMC Neuroscience 2015 16(Suppl 1): P269. Submit your next manuscript to BioMed Central and take full advantage of: • Convenient online submission • Thorough peer review • No space constraints or color figure charges • Immediate publication on acceptance • Inclusion in PubMed, CAS, Scopus and Google Scholar • Research which is freely available for redistribution Submit your manuscript at www.biomedcentral.com/submit http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png BMC Neuroscience Springer Journals

Transient synchrony in delayed coupled neuronal networks

BMC Neuroscience , Volume 16 (1) – Dec 4, 2015

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Publisher
Springer Journals
Copyright
Copyright © 2015 by Esfahani and Valizadeh
Subject
Biomedicine; Neurosciences; Neurobiology; Animal Models
eISSN
1471-2202
DOI
10.1186/1471-2202-16-S1-P269
Publisher site
See Article on Publisher Site

Abstract

Esfahani and Valizadeh BMC Neuroscience 2015, 16(Suppl 1):P269 http://www.biomedcentral.com/1471-2202/16/S1/P269 POSTER PRESENTATION Open Access Transient synchrony in delayed coupled neuronal networks 1* 1,2 Zahra G Esfahani , Alireza Valizadeh From 24th Annual Computational Neuroscience Meeting: CNS*2015 Prague, Czech Republic. 18-23 July 2015 In this study, we propose that in a pool of neurons recur- sensory or control input (Figure 1). It is important to note rently coupled through delayed synaptic connections that such an ability of the network to select frequencies of transient patterns of synchrony can be observed due to the oscillation is based on the presence of the delay in the changing incoming stimuli, in continuance of some communication between neurons. In a network in which recent works [1]. Transient synchrony between spiking the components communicate instantaneously–with activity of the neurons has been reported in different sen- delays ignored–the neurons either spike synchronously or asynchronously depending on the connections properties sory tasks e.g. visual and olfactory system [2,3]. We have shown that the critical role of the delay is to and regardless of the value of the input current and the prepare connections that their synchronizing/desynchro- frequency of the spiking of the neurons. nizing effect changes when they receive different levels of stimuli [4,5]. In a suitable range of parameters, need not to Conclusion be fine-tuned, an initially incoherent firing of the neurons We have shown that the ability of a neural network to can turn to coherent network oscillation when the mean switch between coherent and incoherent firing, may input is changed -not necessarily increased–through be dependent on the delay in communication between Figure 1 Raster Plot of an all-to-all network of 200 homogenously coupled neurons with time dependent stimuli (the violet curve), which switches between asynchronous incoherent state to a synchronous state when the input is changed. All the neurons are excitatory and external input to each neuron comprises a constant current chosen from a narrow normal distribution and an independent Gaussian white noise. The blue diagram presents the network activity. * Correspondence: nzahra-ghasemiiasbs@ac.ir Department of Physics, Institute for Advanced Studies in Basic Sciences, Zanjan, Iran Full list of author information is available at the end of the article © 2015 Esfahani and Valizadeh This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/ publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Esfahani and Valizadeh BMC Neuroscience 2015, 16(Suppl 1):P269 Page 2 of 2 http://www.biomedcentral.com/1471-2202/16/S1/P269 neurons. It has been shown that two reciprocally coupled neurons can fire inphase if the delays lie in the region where the phase response curve of the neurons have negative slope, otherwise their firing is antiphase. In the larger networks where the neurons connect to several other neurons, inphase firing state remains stable where instead of antiphase state, several stable states appear. This is related to geometric frustration in condensed matter physics where a plenitude of distinct ground states are ensued by the lattice structure as in Ising system. Authors’ details Department of Physics, Institute for Advanced Studies in Basic Sciences, Zanjan, Iran. School of Cognitive Sciences, IPM, Niavaran, Tehran, Iran. Published: 18 December 2015 References 1. Gollo LLeonardo, Breakspear Michael: The frustrated brain: from dynamics on motifs to communities and networks. Philo. Trans. of the Royal Society B: Biol. Sci 2014, 369(1653):20130532. 2. Maxim Bazhenov, et al: Model of transient oscillatory synchronization in the locust antennal lobe. Neuron 2001, 30(2):553-567. 3. Tatsuya Mima, et al: Transient interhemispheric neuronal synchrony correlates with object recognition. The Journal of Neuroscience 2001, 21(11):3942-3948. 4. Sadjad Sadeghi, Valizadeh Alireza: Synchronization of delayed coupled neurons in presence of inhomogeneity. Journal of computational neuroscience 2014, 36(1):55-66. 5. Esfahani GhZahra, Valizadeh Alireza: Zero-Lag Synchronization Despite Inhomogeneities in a Relay System. PloS one 2014, 9(12):e11268. doi:10.1186/1471-2202-16-S1-P269 Cite this article as: Esfahani and Valizadeh: Transient synchrony in delayed coupled neuronal networks. BMC Neuroscience 2015 16(Suppl 1): P269. Submit your next manuscript to BioMed Central and take full advantage of: • Convenient online submission • Thorough peer review • No space constraints or color figure charges • Immediate publication on acceptance • Inclusion in PubMed, CAS, Scopus and Google Scholar • Research which is freely available for redistribution Submit your manuscript at www.biomedcentral.com/submit

Journal

BMC NeuroscienceSpringer Journals

Published: Dec 4, 2015

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