Coupling regularizes individual units in noisy populations.

The regularity of a noisy system can modulate in various ways. It is well known that coupling in a population can lower the variability of the entire network; the collective activity is more regular. Here, we show that diffusive (reciprocal) coupling of two simple Ornstein-Uhlenbeck (O-U) processes can regularize the individual, even when it is coupled to a noisier process. In cellular networks, the regularity of individual cells is important when a select few play a significant role. The regularizing effect of coupling surprisingly applies also to general nonlinear noisy oscillators. However, unlike with the O-U process, coupling-induced regularity is robust to different kinds of coupling. With two coupled noisy oscillators, we derive an asymptotic formula assuming weak noise and coupling for the variance of the period (i.e., spike times) that accurately captures this effect. Moreover, we find that reciprocal coupling can regularize the individual period of higher dimensional oscillators such as the Morris-Lecar and Brusselator models, even when coupled to noisier oscillators. Coupling can have a counterintuitive and beneficial effect on noisy systems. These results have implications for the role of connectivity with noisy oscillators and the modulation of variability of individual oscillators.

[1]  G Bard Ermentrout,et al.  Stochastic phase reduction for a general class of noisy limit cycle oscillators. , 2009, Physical review letters.

[2]  T. Hromádka,et al.  Sparse Representation of Sounds in the Unanesthetized Auditory Cortex , 2008, PLoS biology.

[3]  G. P. Moore,et al.  Neuronal spike trains and stochastic point processes. I. The single spike train. , 1967, Biophysical journal.

[4]  R. L. Stratonovich A New Representation for Stochastic Integrals and Equations , 1966 .

[5]  D DiFrancesco,et al.  Pacemaker mechanisms in cardiac tissue. , 1993, Annual review of physiology.

[6]  C. Morris,et al.  Voltage oscillations in the barnacle giant muscle fiber. , 1981, Biophysical journal.

[7]  Jürgen Kurths,et al.  Noise-induced phase synchronization and synchronization transitions in chaotic oscillators. , 2002, Physical review letters.

[8]  Cheng Ly,et al.  Synchronization dynamics of two coupled neural oscillators receiving shared and unshared noisy stimuli , 2009, Journal of Computational Neuroscience.

[9]  G Bard Ermentrout,et al.  Efficient estimation of phase-resetting curves in real neurons and its significance for neural-network modeling. , 2005, Physical review letters.

[10]  W Gerstner,et al.  Noise spectrum and signal transmission through a population of spiking neurons. , 1999, Network.

[11]  A. Winfree Patterns of phase compromise in biological cycles , 1974 .

[12]  G. Ermentrout,et al.  Reliability, synchrony and noise , 2008, Trends in Neurosciences.

[13]  G Bard Ermentrout,et al.  Class-II neurons display a higher degree of stochastic synchronization than class-I neurons. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[14]  J. Teramae,et al.  Robustness of the noise-induced phase synchronization in a general class of limit cycle oscillators. , 2004, Physical review letters.

[15]  I. Prigogine,et al.  On symmetry-breaking instabilities in dissipative systems , 1967 .

[16]  T. Sejnowski,et al.  Collective enhancement of precision in networks of coupled oscillators , 2001 .

[17]  Jason Wolfe,et al.  Sparse temporal coding of elementary tactile features during active whisker sensation , 2009, Nature Neuroscience.

[18]  J. Fox,et al.  Phase-locking and environmental fluctuations generate synchrony in a predator–prey community , 2009, Nature.

[19]  Kurths,et al.  Phase synchronization of chaotic oscillators. , 1996, Physical review letters.

[20]  R. Dehaan,et al.  Fluctuations in interbeat interval in rhythmic heart-cell clusters. Role of membrane voltage noise. , 1979, Biophysical journal.

[21]  R. Spigler,et al.  The Kuramoto model: A simple paradigm for synchronization phenomena , 2005 .

[22]  Carson C. Chow,et al.  Noise shaping in populations of coupled model neurons. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[23]  S. Leibler,et al.  Mechanisms of noise-resistance in genetic oscillators , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[24]  E. Wong,et al.  Riemann-Stieltjes approximations of stochastic integrals , 1969 .

[25]  Cheng Ly,et al.  Spike Train Statistics and Dynamics with Synaptic Input from any Renewal Process: A Population Density Approach , 2009, Neural Computation.

[26]  Brent Doiron,et al.  Non-classical receptive field mediates switch in a sensory neuron's frequency tuning , 2003, Nature.

[27]  Bard Ermentrout,et al.  Type I Membranes, Phase Resetting Curves, and Synchrony , 1996, Neural Computation.

[28]  Jürgen Kurths,et al.  Synchronization: Phase locking and frequency entrainment , 2001 .

[29]  Sten Grillner,et al.  Biological Pattern Generation: The Cellular and Computational Logic of Networks in Motion , 2006, Neuron.

[30]  Yoji Kawamura,et al.  Noise-induced synchronization and clustering in ensembles of uncoupled limit-cycle oscillators. , 2007, Physical review letters.

[31]  J. Rinzel,et al.  Emergence of organized bursting in clusters of pancreatic beta-cells by channel sharing. , 1988, Biophysical journal.

[32]  T. Sejnowski,et al.  Regulation of spike timing in visual cortical circuits , 2008, Nature Reviews Neuroscience.

[33]  S. Hughes,et al.  Synchronized Oscillations at α and θ Frequencies in the Lateral Geniculate Nucleus , 2004, Neuron.

[34]  Olivier Faugeras,et al.  The spikes trains probability distributions: A stochastic calculus approach , 2007, Journal of Physiology-Paris.