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The influence of stationary synaptic activity on the PRC

The influence of stationary synaptic activity on the PRC Garcia et al. BMC Neuroscience 2011, 12(Suppl 1):P264 http://www.biomedcentral.com/1471-2202/12/S1/P264 POSTER PRESENTATION Open Access The influence of stationary synaptic activity on the PRC 1* 2,3 2,4 Guadalupe C Garcia , Gemma Huguet , John Rinzel From Twentieth Annual Computational Neuroscience Meeting: CNS*2011 Stockholm, Sweden. 23-28 July 2011 A useful measurable property of a neural oscillator is its conductance, for a constant value of the excitatory one, we Phase Response Curve (PRC). PRCs measure the phase- observed a switch from type I to type II PRC. We corre- shift resulting from perturbing the oscillator with a brief lated the shape of the PRC with the synchronization prop- stimulus at different times of the cycle. They have been erties. We studied the effect of the temporal dynamics of extensively used to understand the synchronous activity synaptic activation on the synchronization properties of a patterns emerging from a network of weakly coupled coupled pair of neurons, as we switched them from type I oscillators. to type II PRC. We characterized how solutions change PRCs have been classified into two types: type I (PRC is with these parameters in a network motif of two recipro- always positive) and type II (PRC has positive and nega- cally coupled neurons. tive regions) [1]. Theoretical results [2] have shown that the type of PRC combined with the temporal dynamics Author details of the synapses yield different synchronization properties 1 School of Engineering and Science, Jacobs University Bremen, Bremen, when two neurons are coupled together (neurons can Germany. Center for Neural Science, New York University, New York, USA. 3 4 Centre de Recerca Matemàtica, Barcelona, Spain. Courant Institute of synchronize in-phase, out of phase or in anti-phase). Mathematical Sciences, New York University, New York, USA. PRCs are typically measured in vitro, considering only the intrinsic properties of the neuron. However, in vivo Published: 18 July 2011 neurons constantly receive background synaptic inputs References that play an important role sculpting the dynamics of 1. Ermentrout GB: Type I membranes, Phase Resetting Curves, and neurons. Indeed experimental data showed that mem- Synchrony. Neural Computation 1996, 8(5):979-1001. braneexcitability[3] canchangeinresponsetovaria- 2. Vreeswijk C, Abbott LF, Ermentrout GB: When inhibition not excitation synchronizes neural firing. Journal of Computational Neuroscience 1994, tions in background synaptic activity [4]. 1(4):313-321. In this work we study the effects of the background 3. Rinzel J, Ermentrout GB: Analysis of Neural Excitability and Oscillations. In synaptic activity on the shape of the Phase Response Methods in neuronal modeling: from ions to networks.. 2 edition. Cambridge: MIT Press;Koch C and Segev I 1998. Curve, and its synchronization properties. To perform 4. Prescott SA, Ratte S, De Koninck Y, Sejnowski TJ: Pyramidal Neurons this study, we consider two neuron models: the Wang- Switch from Integrators In Vivo to Resonators Under in Vivo-Like Buzsáki model [5] and the Morris-Lecar model [6]. We Conditions. J. Neurophysiology 2008, 100(6):3030-3042. 5. Wang XJ, Buzsáki G: Gamma Oscillation by Synaptic Inhibition in explore the effect of a constant excitatory and inhibitory Hippocampal Interneuronal Network Model. The journal of Neuroscience synaptic conductance input (that can be seen as an aver- 1996, 16(20):6402-6413. age of the background input) on the type of membrane 6. Morris C, Lecar H: Voltage Oscillations in the Barnacle Giant Muscle Fiber. Biophysical Journal 1981, 35(1):193-213. excitability and PRC shape in the spiking regime. 7. Destexhe A, Rudolph M, Fellous JM, Sejnowski TJ: Fluctuating synaptic We found that changes in the mean background con- conductances recreate in vivo-like activity in neocortical neurons. ductances in a biologically plausible range [7] lead to Neuroscience 2001, 107(1):13-24. changes in the type of PRC. As we increased the inhibitory doi:10.1186/1471-2202-12-S1-P264 Cite this article as: Garcia et al.: The influence of stationary synaptic activity on the PRC. BMC Neuroscience 2011 12(Suppl 1):P264. * Correspondence: g.garcia@jacobs-university.de School of Engineering and Science, Jacobs University Bremen, Bremen, Germany Full list of author information is available at the end of the article © 2011 Garcia et al; licensee 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png BMC Neuroscience Springer Journals

The influence of stationary synaptic activity on the PRC

Garcia, Guadalupe; Huguet, Gemma; Rinzel, John
BMC Neuroscience , Volume 12 (1) – Jul 18, 2011
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Springer Journals
Copyright
Copyright © 2011 by Garcia et al; licensee BioMed Central Ltd.
Subject
Biomedicine; Neurosciences; Neurobiology; Animal Models
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1471-2202
DOI
10.1186/1471-2202-12-S1-P264
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Abstract

Garcia et al. BMC Neuroscience 2011, 12(Suppl 1):P264 http://www.biomedcentral.com/1471-2202/12/S1/P264 POSTER PRESENTATION Open Access The influence of stationary synaptic activity on the PRC 1* 2,3 2,4 Guadalupe C Garcia , Gemma Huguet , John Rinzel From Twentieth Annual Computational Neuroscience Meeting: CNS*2011 Stockholm, Sweden. 23-28 July 2011 A useful measurable property of a neural oscillator is its conductance, for a constant value of the excitatory one, we Phase Response Curve (PRC). PRCs measure the phase- observed a switch from type I to type II PRC. We corre- shift resulting from perturbing the oscillator with a brief lated the shape of the PRC with the synchronization prop- stimulus at different times of the cycle. They have been erties. We studied the effect of the temporal dynamics of extensively used to understand the synchronous activity synaptic activation on the synchronization properties of a patterns emerging from a network of weakly coupled coupled pair of neurons, as we switched them from type I oscillators. to type II PRC. We characterized how solutions change PRCs have been classified into two types: type I (PRC is with these parameters in a network motif of two recipro- always positive) and type II (PRC has positive and nega- cally coupled neurons. tive regions) [1]. Theoretical results [2] have shown that the type of PRC combined with the temporal dynamics Author details of the synapses yield different synchronization properties 1 School of Engineering and Science, Jacobs University Bremen, Bremen, when two neurons are coupled together (neurons can Germany. Center for Neural Science, New York University, New York, USA. 3 4 Centre de Recerca Matemàtica, Barcelona, Spain. Courant Institute of synchronize in-phase, out of phase or in anti-phase). Mathematical Sciences, New York University, New York, USA. PRCs are typically measured in vitro, considering only the intrinsic properties of the neuron. However, in vivo Published: 18 July 2011 neurons constantly receive background synaptic inputs References that play an important role sculpting the dynamics of 1. Ermentrout GB: Type I membranes, Phase Resetting Curves, and neurons. Indeed experimental data showed that mem- Synchrony. Neural Computation 1996, 8(5):979-1001. braneexcitability[3] canchangeinresponsetovaria- 2. Vreeswijk C, Abbott LF, Ermentrout GB: When inhibition not excitation synchronizes neural firing. Journal of Computational Neuroscience 1994, tions in background synaptic activity [4]. 1(4):313-321. In this work we study the effects of the background 3. Rinzel J, Ermentrout GB: Analysis of Neural Excitability and Oscillations. In synaptic activity on the shape of the Phase Response Methods in neuronal modeling: from ions to networks.. 2 edition. Cambridge: MIT Press;Koch C and Segev I 1998. Curve, and its synchronization properties. To perform 4. Prescott SA, Ratte S, De Koninck Y, Sejnowski TJ: Pyramidal Neurons this study, we consider two neuron models: the Wang- Switch from Integrators In Vivo to Resonators Under in Vivo-Like Buzsáki model [5] and the Morris-Lecar model [6]. We Conditions. J. Neurophysiology 2008, 100(6):3030-3042. 5. Wang XJ, Buzsáki G: Gamma Oscillation by Synaptic Inhibition in explore the effect of a constant excitatory and inhibitory Hippocampal Interneuronal Network Model. The journal of Neuroscience synaptic conductance input (that can be seen as an aver- 1996, 16(20):6402-6413. age of the background input) on the type of membrane 6. Morris C, Lecar H: Voltage Oscillations in the Barnacle Giant Muscle Fiber. Biophysical Journal 1981, 35(1):193-213. excitability and PRC shape in the spiking regime. 7. Destexhe A, Rudolph M, Fellous JM, Sejnowski TJ: Fluctuating synaptic We found that changes in the mean background con- conductances recreate in vivo-like activity in neocortical neurons. ductances in a biologically plausible range [7] lead to Neuroscience 2001, 107(1):13-24. changes in the type of PRC. As we increased the inhibitory doi:10.1186/1471-2202-12-S1-P264 Cite this article as: Garcia et al.: The influence of stationary synaptic activity on the PRC. BMC Neuroscience 2011 12(Suppl 1):P264. * Correspondence: g.garcia@jacobs-university.de School of Engineering and Science, Jacobs University Bremen, Bremen, Germany Full list of author information is available at the end of the article © 2011 Garcia et al; licensee 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.

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BMC Neuroscience – Springer Journals

Published: Jul 18, 2011

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