Splay States in Finite Pulse-Coupled Networks of Excitable Neurons

The emergence and stability of splay states is studied in fully coupled finite networks of $N$ excitable quadratic integrate-and-fire neurons, connected via synapses modeled as pulses of finite amplitude and duration. For such synapses, by introducing two distinct types of synaptic events (pulse emission and termination), we were able to write down an exact event-driven map for the system and to evaluate the splay state solutions. For $M$ overlapping postsynaptic potentials, the linear stability analysis of the splay state should also take in account, besides the actual values of the membrane potentials, the firing times associated with the $M$ previous pulse emissions. As a matter of fact, it was possible, by introducing $M$ complementary variables, to rephrase the evolution of the network as an event-driven map and to derive an analytic expression for the Floquet spectrum. We find that, independently of $M$, the splay state is marginally stable with $N-2$ neutral directions. Furthermore, we have identif...

[1]  Dezhe Z Jin,et al.  Fast convergence of spike sequences to periodic patterns in recurrent networks. , 2002, Physical review letters.

[2]  Tilman Seidel,et al.  Breaking the Symmetry in a Car‐Following Model , 2006 .

[3]  Stephen Coombes,et al.  A Dynamical Theory of Spike Train Transitions in Networks of Integrate-and-Fire Oscillators , 2000, SIAM J. Appl. Math..

[4]  S. Strogatz,et al.  Splay states in globally coupled Josephson arrays: Analytical prediction of Floquet multipliers. , 1993, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[5]  Daniel J. Amit,et al.  Modeling brain function: the world of attractor neural networks, 1st Edition , 1989 .

[6]  Nicolas Brunel,et al.  Dynamics of Sparsely Connected Networks of Excitatory and Inhibitory Spiking Neurons , 2000, Journal of Computational Neuroscience.

[7]  Carson C. Chow,et al.  Stationary Bumps in Networks of Spiking Neurons , 2001, Neural Computation.

[8]  A. Winfree The geometry of biological time , 1991 .

[9]  Abbott,et al.  Asynchronous states in networks of pulse-coupled oscillators. , 1993, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[10]  N. Spruston,et al.  Dendritic glutamate receptor channels in rat hippocampal CA3 and CA1 pyramidal neurons. , 1995, The Journal of physiology.

[11]  Vreeswijk,et al.  Partial synchronization in populations of pulse-coupled oscillators. , 1996, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[12]  Roy,et al.  Observation of antiphase states in a multimode laser. , 1990, Physical review letters.

[13]  T. Sejnowski,et al.  Neurocomputational models of working memory , 2000, Nature Neuroscience.

[14]  Nichols,et al.  Ubiquitous neutral stability of splay-phase states. , 1992, Physical review. A, Atomic, molecular, and optical physics.

[15]  Antonio Politi,et al.  Stability of the splay state in pulse-coupled networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[16]  Rappel Dynamics of a globally coupled laser model. , 1994, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[17]  Wulfram Gerstner,et al.  Spiking Neuron Models , 2002 .

[18]  Germán Mato,et al.  Asynchronous States and the Emergence of Synchrony in Large Networks of Interacting Excitatory and Inhibitory Neurons , 2003, Neural Computation.

[19]  Stephen Coombes,et al.  Neuronal Networks with Gap Junctions: A Study of Piecewise Linear Planar Neuron Models , 2008, SIAM J. Appl. Dyn. Syst..

[20]  Schwartz,et al.  Interhyperhedral diffusion in Josephson-junction arrays. , 1992, Physical review letters.

[21]  G. Buzsáki,et al.  Gamma Oscillation by Synaptic Inhibition in a Hippocampal Interneuronal Network Model , 1996, The Journal of Neuroscience.

[22]  Peter Ashwin,et al.  Three identical oscillators with symmetric coupling , 1990 .

[23]  P C Bressloff,et al.  Mean-field theory of globally coupled integrate-and-fire neural oscillators with dynamic synapses. , 1999, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[24]  Peter Hadley,et al.  Dynamical states and stability of linear arrays of Josephson junctions , 1987 .

[25]  G. Ermentrout,et al.  Parabolic bursting in an excitable system coupled with a slow oscillation , 1986 .

[26]  Hansel,et al.  Clustering in globally coupled phase oscillators. , 1992, Physical review. A, Atomic, molecular, and optical physics.

[27]  J. Lamb,et al.  Time-reversal symmetry in dynamical systems: a survey , 1998 .

[28]  J. Assad,et al.  Beyond Poisson: Increased Spike-Time Regularity across Primate Parietal Cortex , 2009, Neuron.

[29]  Boris S. Gutkin,et al.  Turning On and Off with Excitation: The Role of Spike-Timing Asynchrony and Synchrony in Sustained Neural Activity , 2001, Journal of Computational Neuroscience.

[30]  Hakim,et al.  Dynamics of the globally coupled complex Ginzburg-Landau equation. , 1992, Physical review. A, Atomic, molecular, and optical physics.

[31]  Carson C. Chow Phase-locking in weakly heterogeneous neuronal networks , 1997, cond-mat/9709220.

[32]  D. Hansel,et al.  Existence and stability of persistent states in large neuronal networks. , 2001, Physical review letters.

[33]  Martin Golubitsky,et al.  Coupled arrays of Josephson junctions and bifurcation of maps with SN symmetry , 1991 .

[34]  Antonio Politi,et al.  Desynchronization in diluted neural networks. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[35]  David L. Sheinberg,et al.  Spike Count Reliability and the Poisson Hypothesis , 2006, The Journal of Neuroscience.

[36]  S. Strogatz,et al.  Constants of motion for superconducting Josephson arrays , 1994 .

[37]  Zachary P. Kilpatrick,et al.  Sparse Gamma Rhythms Arising through Clustering in Adapting Neuronal Networks , 2011, PLoS Comput. Biol..

[38]  P. Goldman-Rakic,et al.  Synaptic mechanisms and network dynamics underlying spatial working memory in a cortical network model. , 2000, Cerebral cortex.

[39]  J. Fuster,et al.  Inferotemporal neurons distinguish and retain behaviorally relevant features of visual stimuli. , 1981, Science.

[40]  Antonio Politi,et al.  Stability of splay states in globally coupled rotators. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[41]  P. Goldman-Rakic,et al.  Mnemonic coding of visual space in the monkey's dorsolateral prefrontal cortex. , 1989, Journal of neurophysiology.