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Published in: Journal of Computational Neuroscience 2/2009

01-04-2009

Loss of phase-locking in non-weakly coupled inhibitory networks of type-I model neurons

Authors: Myongkeun Oh, Victor Matveev

Published in: Journal of Computational Neuroscience | Issue 2/2009

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Abstract

Synchronization of excitable cells coupled by reciprocal inhibition is a topic of significant interest due to the important role that inhibitory synaptic interaction plays in the generation and regulation of coherent rhythmic activity in a variety of neural systems. While recent work revealed the synchronizing influence of inhibitory coupling on the dynamics of many networks, it is known that strong coupling can destabilize phase-locked firing. Here we examine the loss of synchrony caused by an increase in inhibitory coupling in networks of type-I Morris–Lecar model oscillators, which is characterized by a period-doubling cascade and leads to mode-locked states with alternation in the firing order of the two cells, as reported recently by Maran and Canavier (J Comput Nerosci, 2008) for a network of Wang-Buzsáki model neurons. Although alternating-order firing has been previously reported as a near-synchronous state, we show that the stable phase difference between the spikes of the two Morris–Lecar cells can constitute as much as 70% of the unperturbed oscillation period. Further, we examine the generality of this phenomenon for a class of type-I oscillators that are close to their excitation thresholds, and provide an intuitive geometric description of such “leap-frog” dynamics. In the Morris–Lecar model network, the alternation in the firing order arises under the condition of fast closing of K +  channels at hyperpolarized potentials, which leads to slow dynamics of membrane potential upon synaptic inhibition, allowing the presynaptic cell to advance past the postsynaptic cell in each cycle of the oscillation. Further, we show that non-zero synaptic decay time is crucial for the existence of leap-frog firing in networks of phase oscillators. However, we demonstrate that leap-frog spiking can also be obtained in pulse-coupled inhibitory networks of one-dimensional oscillators with a multi-branched phase domain, for instance in a network of quadratic integrate-and-fire model cells. Finally, for the case of a homogeneous network, we establish quantitative conditions on the phase resetting properties of each cell necessary for stable alternating-order spiking, complementing the analysis of Goel and Ermentrout (Physica D 163:191–216, 2002) of the order-preserving phase transition map.

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Appendix
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Literature
go back to reference Acker, C. D., Kopell, N., & White, J. A. (2003). Synchronization of strongly coupled excitatory neurons: Relating network behavior to biophysics. Journal Comparative Neuroscience, 15, 71–90.CrossRef Acker, C. D., Kopell, N., & White, J. A. (2003). Synchronization of strongly coupled excitatory neurons: Relating network behavior to biophysics. Journal Comparative Neuroscience, 15, 71–90.CrossRef
go back to reference Bose, A., Kopell, N., & Terman, D. (2000). Almost synchronous solutions for pairs of neurons coupled by excitation. Physica D, 140, 69–94.CrossRef Bose, A., Kopell, N., & Terman, D. (2000). Almost synchronous solutions for pairs of neurons coupled by excitation. Physica D, 140, 69–94.CrossRef
go back to reference Bressloff, P. C., & Coombes, S. (1998). Desynchronization, mode locking, and bursting in strongly coupled integrate-and-fire oscillators. Physical Review Letters, 81, 2168–2171.CrossRef Bressloff, P. C., & Coombes, S. (1998). Desynchronization, mode locking, and bursting in strongly coupled integrate-and-fire oscillators. Physical Review Letters, 81, 2168–2171.CrossRef
go back to reference Bressloff, P. C., & Coombes, S. (2000). Dynamics of strongly-coupled spiking neurons. Neural Computation, 12, 91–129.PubMedCrossRef Bressloff, P. C., & Coombes, S. (2000). Dynamics of strongly-coupled spiking neurons. Neural Computation, 12, 91–129.PubMedCrossRef
go back to reference Brown, E., Moehlis, J., & Holmes, P. (2004). On the phase reduction and response dynamics of neural oscillator populations. Neural Computation, 16, 673–715.PubMedCrossRef Brown, E., Moehlis, J., & Holmes, P. (2004). On the phase reduction and response dynamics of neural oscillator populations. Neural Computation, 16, 673–715.PubMedCrossRef
go back to reference Canavier, C. C., Baxter, D. A., Clark, J. W., & Byrne, J. H. (1999). Control of multistability in ring circuits of oscillators. Biological Cybernetics, 80, 87–102.CrossRef Canavier, C. C., Baxter, D. A., Clark, J. W., & Byrne, J. H. (1999). Control of multistability in ring circuits of oscillators. Biological Cybernetics, 80, 87–102.CrossRef
go back to reference Ermentrout, G. B. (1996). Type I membranes, phase resetting curves, and synchrony. Neural Computation, 8, 979–1001.PubMedCrossRef Ermentrout, G. B. (1996). Type I membranes, phase resetting curves, and synchrony. Neural Computation, 8, 979–1001.PubMedCrossRef
go back to reference Ermentrout, G. B., & Kopell, N. (1984). Frequency plateaus in a chain of weakly coupled oscillators. SIAM Journal on Mathematical Analysis, 15, 215–237.CrossRef Ermentrout, G. B., & Kopell, N. (1984). Frequency plateaus in a chain of weakly coupled oscillators. SIAM Journal on Mathematical Analysis, 15, 215–237.CrossRef
go back to reference Ermentrout, G. B., & Kopell, N. (1990). Oscillator death in systems of coupled neural oscillators. SIAM Journal on Applied Mathematics, 50, 125–146.CrossRef Ermentrout, G. B., & Kopell, N. (1990). Oscillator death in systems of coupled neural oscillators. SIAM Journal on Applied Mathematics, 50, 125–146.CrossRef
go back to reference Ermentrout, G. B., & Kopell, N. (1991). Multiple pulse interactions and averaging in systems of coupled neural oscillators. Journal of Mathematical Biology, 29, 195–217.CrossRef Ermentrout, G. B., & Kopell, N. (1991). Multiple pulse interactions and averaging in systems of coupled neural oscillators. Journal of Mathematical Biology, 29, 195–217.CrossRef
go back to reference Glass, L., Guevara, M. R., Belair, J., & Shrier, A. (1984). Global bifurcations of a periodically forced biological oscillator. Physical Review, A 29, 1348–1357.CrossRef Glass, L., Guevara, M. R., Belair, J., & Shrier, A. (1984). Global bifurcations of a periodically forced biological oscillator. Physical Review, A 29, 1348–1357.CrossRef
go back to reference Goel, P., & Ermentrout, G. B. (2002). Synchrony, stability, and firing patterns in pulse-coupled oscillators. Physica D, 163, 191–216.CrossRef Goel, P., & Ermentrout, G. B. (2002). Synchrony, stability, and firing patterns in pulse-coupled oscillators. Physica D, 163, 191–216.CrossRef
go back to reference Golubitsky, M., Stewart, I., Buono, P. L., & Collins, J. J. (1999). Symmetry in locomotor central pattern generators and animal gaits. Nature, 401, 693–695.PubMedCrossRef Golubitsky, M., Stewart, I., Buono, P. L., & Collins, J. J. (1999). Symmetry in locomotor central pattern generators and animal gaits. Nature, 401, 693–695.PubMedCrossRef
go back to reference Golubitsky, M., Josic, K., & Shea-Brown, E. (2006). Winding numbers and average frequencies in phase oscillator networks. Journal of Nonlinear Science, 16, 201–231.CrossRef Golubitsky, M., Josic, K., & Shea-Brown, E. (2006). Winding numbers and average frequencies in phase oscillator networks. Journal of Nonlinear Science, 16, 201–231.CrossRef
go back to reference Hansel, D., Mato, G., & Meunier, C. (1995). Synchrony in excitatory neural networks. Neural Computation, 7, 307–337.PubMedCrossRef Hansel, D., Mato, G., & Meunier, C. (1995). Synchrony in excitatory neural networks. Neural Computation, 7, 307–337.PubMedCrossRef
go back to reference Hoppensteadt, F. C., & Izhikevich, E. M. (1997). Weakly connected neural networks. New York: Springer. Hoppensteadt, F. C., & Izhikevich, E. M. (1997). Weakly connected neural networks. New York: Springer.
go back to reference Izhikevich, E. M. (2000). Phase equations for relaxation oscillators. SIAM Journal on Applied Mathematics, 60, 1789–1805.CrossRef Izhikevich, E. M. (2000). Phase equations for relaxation oscillators. SIAM Journal on Applied Mathematics, 60, 1789–1805.CrossRef
go back to reference Izhikevich, E. M. (2006). Dynamics systems in neuroscience: The geometry of excitability and bursting. Chapter 10: Synchronization. Cambridge: MIT. Izhikevich, E. M. (2006). Dynamics systems in neuroscience: The geometry of excitability and bursting. Chapter 10: Synchronization. Cambridge: MIT.
go back to reference Izhikevich, E. M., & Kuramoto, Y. (2006). Weakly coupled oscillators. Encyclopedia of Mathematical Physics, Elsevier, 5, 448.CrossRef Izhikevich, E. M., & Kuramoto, Y. (2006). Weakly coupled oscillators. Encyclopedia of Mathematical Physics, Elsevier, 5, 448.CrossRef
go back to reference Jones, S. R., Pinto, D., Kaper, T., & Kopell, N. (2000). Alpha-frequency rhythms desynchronize over long cortical distances: A modelling study. Journal Computational Neuroscience, 9, 271–291.CrossRef Jones, S. R., Pinto, D., Kaper, T., & Kopell, N. (2000). Alpha-frequency rhythms desynchronize over long cortical distances: A modelling study. Journal Computational Neuroscience, 9, 271–291.CrossRef
go back to reference Kopell, N. (1988). Toward a theory of modeling central pattern generators. In A. H. Cohen, S. Rossignol, & S. Grillner (Eds.), Neural control of rhythms. New York: Wiley. Kopell, N. (1988). Toward a theory of modeling central pattern generators. In A. H. Cohen, S. Rossignol, & S. Grillner (Eds.), Neural control of rhythms. New York: Wiley.
go back to reference Kopell, N., Ermentrout, G. B., Whittington, M., & Traub, R. D. (2000). Gamma rhythms and beta rhythms have different synchronization properties. Proceedings of the National Academy of Sciences of United States America, 97, 1867–1872.CrossRef Kopell, N., Ermentrout, G. B., Whittington, M., & Traub, R. D. (2000). Gamma rhythms and beta rhythms have different synchronization properties. Proceedings of the National Academy of Sciences of United States America, 97, 1867–1872.CrossRef
go back to reference Kopell, N., & Ermentrout, G. B. (2002). Mechanisms of phase-locking and frequency control in pairs of coupled neural oscillators. In B. Fiedler (Ed.), Handbook on Dynamical Systems: Toward Applications. New York: Elsevier. Kopell, N., & Ermentrout, G. B. (2002). Mechanisms of phase-locking and frequency control in pairs of coupled neural oscillators. In B. Fiedler (Ed.), Handbook on Dynamical Systems: Toward Applications. New York: Elsevier.
go back to reference Kuramoto, Y. (1984). Chemical oscillations, waves, and turbulence. Berlin: Springer. Kuramoto, Y. (1984). Chemical oscillations, waves, and turbulence. Berlin: Springer.
go back to reference Maran, S. K., & Canavier, C. C. (2008). Using phase resetting to predict 1:1 and 2:2 locking in two neuron networks in which firing order is not always preserved. Journal of Computational Neroscience, 24, 37–55. Maran, S. K., & Canavier, C. C. (2008). Using phase resetting to predict 1:1 and 2:2 locking in two neuron networks in which firing order is not always preserved. Journal of Computational Neroscience, 24, 37–55.
go back to reference Mirollo, R. E., & Strogatz, S. H. (1990). Synchronization of pulse-coupled biological oscillators. SIAM Journal of Applied Mathemaics, 50, 1645–1662.CrossRef Mirollo, R. E., & Strogatz, S. H. (1990). Synchronization of pulse-coupled biological oscillators. SIAM Journal of Applied Mathemaics, 50, 1645–1662.CrossRef
go back to reference Morris, C., & Lecar, H. (1981). Voltage oscillations in the barnacle giant muscle fiber. Biophysical Journal, 35, 193–213.PubMedCrossRef Morris, C., & Lecar, H. (1981). Voltage oscillations in the barnacle giant muscle fiber. Biophysical Journal, 35, 193–213.PubMedCrossRef
go back to reference Netoff, T. I., Banks, M. I., Dorval, A. D., Acker, C. D., Haas, J. S., Kopell, N., et al. (2005). Synchronization in hybrid neuronal networks of the hippocampal formation. Journal of Neurophysiology, 93, 1197–1208.PubMedCrossRef Netoff, T. I., Banks, M. I., Dorval, A. D., Acker, C. D., Haas, J. S., Kopell, N., et al. (2005). Synchronization in hybrid neuronal networks of the hippocampal formation. Journal of Neurophysiology, 93, 1197–1208.PubMedCrossRef
go back to reference Oprisan, S. A., & Canavier, C. C. (2001). Stability analysis of rings of pulse-coupled oscillators: The effect of phase resetting in the second cycle after the pulse is important at synchrony and for long pulses. Journal of Difference. Equations and Dynamical Systems, 9, 243–258. Oprisan, S. A., & Canavier, C. C. (2001). Stability analysis of rings of pulse-coupled oscillators: The effect of phase resetting in the second cycle after the pulse is important at synchrony and for long pulses. Journal of Difference. Equations and Dynamical Systems, 9, 243–258.
go back to reference Oprisan, S. A., & Canavier, C. C. (2002). The influence of limit cycle topology on the phase resetting curve. Neural Computation, 14, 1027–1057.PubMedCrossRef Oprisan, S. A., & Canavier, C. C. (2002). The influence of limit cycle topology on the phase resetting curve. Neural Computation, 14, 1027–1057.PubMedCrossRef
go back to reference Oprisan, S. A., Prinz, A. A., & Canavier, C. C. (2004). Phase resetting and phase locking in hybrid circuits of one model and one biological neuron. Biophysical Journal, 87, 2283–2298.PubMedCrossRef Oprisan, S. A., Prinz, A. A., & Canavier, C. C. (2004). Phase resetting and phase locking in hybrid circuits of one model and one biological neuron. Biophysical Journal, 87, 2283–2298.PubMedCrossRef
go back to reference Peskin, C. S. (1975). Mathematical aspects of heart physiology. New York: New York University Courant Institute of Mathematical Sciences. Peskin, C. S. (1975). Mathematical aspects of heart physiology. New York: New York University Courant Institute of Mathematical Sciences.
go back to reference Rinzel, J., & Ermentrout, B. (1998). Analysis of neural excitability and oscillations. In C. Koch & I. Segev (Eds.), Methods in neuronal modeling: From ions to networks (2nd edn). Cambridge: MIT. Rinzel, J., & Ermentrout, B. (1998). Analysis of neural excitability and oscillations. In C. Koch & I. Segev (Eds.), Methods in neuronal modeling: From ions to networks (2nd edn). Cambridge: MIT.
go back to reference Rubin, J., & Terman, D. (2000). Geometric analysis of population rhythms in synaptically coupled neuronal networks. Neural Computation, 12, 597–645PubMedCrossRef Rubin, J., & Terman, D. (2000). Geometric analysis of population rhythms in synaptically coupled neuronal networks. Neural Computation, 12, 597–645PubMedCrossRef
go back to reference Sato, Y. D., & Shiino, M. (2007). Generalization of coupled spiking models and effects of the width of an action potential on synchronization phenomena. Physical Review E, 75, 011909.CrossRef Sato, Y. D., & Shiino, M. (2007). Generalization of coupled spiking models and effects of the width of an action potential on synchronization phenomena. Physical Review E, 75, 011909.CrossRef
go back to reference Somers, D., & Kopell, N. (1993). Rapid synchronization through fast threshold modulation. Biological Cybernetics, 68, 393–407.PubMedCrossRef Somers, D., & Kopell, N. (1993). Rapid synchronization through fast threshold modulation. Biological Cybernetics, 68, 393–407.PubMedCrossRef
go back to reference van Vreeswijk, C., Abbott, L. F., & Ermentrout, B. (1994). When inhibition not excitation synchronizes neural firing. Journal of Computational Neuroscience, 1, 313–321.PubMedCrossRef van Vreeswijk, C., Abbott, L. F., & Ermentrout, B. (1994). When inhibition not excitation synchronizes neural firing. Journal of Computational Neuroscience, 1, 313–321.PubMedCrossRef
go back to reference Wang, X. J., Buzsáki, G. (1996). Gamma oscillation by synaptic inhibition in a hippocampal interneuronal network model. Journal of Neuroscience, 16, 6402–6413.PubMed Wang, X. J., Buzsáki, G. (1996). Gamma oscillation by synaptic inhibition in a hippocampal interneuronal network model. Journal of Neuroscience, 16, 6402–6413.PubMed
go back to reference White, J. A., Chow, C. C., Ritt, J., Soto-Trevino, C., & Kopell, N. (1998). Dynamics in heterogeneous, mutually inhibited neurons. Journal of Computational Neuroscience, 5, 5–16.PubMedCrossRef White, J. A., Chow, C. C., Ritt, J., Soto-Trevino, C., & Kopell, N. (1998). Dynamics in heterogeneous, mutually inhibited neurons. Journal of Computational Neuroscience, 5, 5–16.PubMedCrossRef
go back to reference Winfree, A. T. (2001). The geometry of biological time (2nd edn). New York: Springer. Winfree, A. T. (2001). The geometry of biological time (2nd edn). New York: Springer.
Metadata
Title
Loss of phase-locking in non-weakly coupled inhibitory networks of type-I model neurons
Authors
Myongkeun Oh
Victor Matveev
Publication date
01-04-2009
Publisher
Springer US
Published in
Journal of Computational Neuroscience / Issue 2/2009
Print ISSN: 0929-5313
Electronic ISSN: 1573-6873
DOI
https://doi.org/10.1007/s10827-008-0112-8

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