Schematic depicting the network architecture.

<p>The generalized () network with mitral cells and granule cells is shown here. The simplified () network lacks mitral cells (MC).</p

Self-induced stochastic synchrony between a pair of Morris-Lecar model neurons and a leaky integrate-and-fire model neuron.

<p>(A) Rate of release of the LIF, “granule cell” showing switches between synchrony and asynchrony. (B–E) Sample voltages at four different time points corresponding to time in A, showing synchrony when is high and asynchrony when is low. High(low) granule cell activity during synchronized(unsynchronized) mitral cell activity can be observed. (F) Correlation coefficient calculated for the voltage data between the two mitral cells.</p

Evolution of in the presence of a single stable fixed point.

<p>(A) The temporal evolution of from various initial states. All initial states are attracted by the single stable fixed point. (B) Histogram of the final values of in different trials from (A). The green curve depicts the numerically calculated values of equation 7 (C) The dependence of the median probability on the amplitude of . (D) The curves depict distribution of phase differences drawn at various time points from simulations such as in (A). A slow development of synchrony on the order of hundreds of milliseconds is observed.</p

Evolution of in the bistable regime.

<p>(A) The temporal evolution of from various initial states. The initial states move randomly to either one of the stable fixed points. (B) Histogram of the final values of in different trials from (A). The green curve depicts the numerically calculated values of equation 7 for the indirect choice of . (C) The dependence of the steady state probability on the amplitude of . The taller peak of the bimodal distribution is depicted by the green curve. (D) Probability distribution of the phase difference between mitral cells for the two fixed points.</p

Self-organized synchronization in a stochastic feedback network of two mitral cells and one granule cell( network).

<p>(A) Probability density of the phase-difference for different strengths of input to the granule cell. The peak at zero phase difference increases with strength of the synapse. (B) Distribution of the values of , the shared Poisson rate of the granule cell for different strengths of the synapse. (C) Plots of for and . (D) Phase difference histograms for the network. The central peak exists without decay for even larger network sizes (data not shown) suggesting that stochastic synchronization is robust against larger network sizes.</p

Dependence of the total spike count of the granule cell on the phase-difference of the two oscillators for different input strengths () and integration times of the synapse ().

<p>Higher dependence of the firing rate on the phase difference is observed for weaker and shorter synapses. The firing rate is less dependent on the phase difference for stronger and longer synapses.</p

Related to Fig 3.

Phase diagram of networks with two dimensional spatial coupling. Same format as Fig 2B in the main text. The letters mark the locations of the parameters used in Fig 3A–3D. (TIFF)</p

Two-dimensional networks with input noise.

A. The input noise to each neuron consists of a correlated noise component (black) that is common for all neurons from the same population, and an independent noise component that is private to each neuron (gray). B-C. Snapshots of the firing rates of the excitatory population at three time frames for a network that generates traveling waves when there is no input noise (τi = 8, σi = 0.1, same parameters as in Fig 3A). The correlation of the input noise is c = 0.5, and the amplitude is σn = 0.04 (B) and σn = 0.08 (C).</p

Global picture for the simple 4-dimensional model.

<p>(A) Plots of for different periods of forcing with an amplitude of 0.65. (B) Phase diagram as the amplitude and period of the forcing vary; color code is the “depth” of the pattern (the difference between and ) with dark red/black the deepest. (Blue dots correspond to the four periods shown in A.) (C) Bifurcation diagram for Red curves are unstable periodic orbits and blue are stable. See text for details.</p

Sample two-dimensional patterns seen in a grid with periodic boundary conditions.

<p>Top row shows patterns seen with high frequency stimuli. Pairs show the results of different random initial conditions. Bottom row shows patterns seen at lower frequency; each pattern has the same period as the stimulus.</p