Spatiotemporal dynamics on small-world neuronal networks: The roles of two types of time-delayed coupling

We investigate temporal coherence and spatial synchronization on small-world networks consisting of noisy Terman–Wang (TW) excitable neurons in dependence on two types of time-delayed coupling: {x_j(t − τ) − x_i(t)} and {x_j(t − τ) − x_i(t − τ)}. For the former case, we show that time delay in the coupling can dramatically enhance temporal coherence and spatial synchrony of the noise-induced spike trains. In addition, if the delay time τ is tuned to nearly match the intrinsic spike period of the neuronal network, the system dynamics reaches a most ordered state, which is both periodic in time and nearly synchronized in space, demonstrating an interesting resonance phenomenon with delay. For the latter case, however, we cannot achieve a similar spatiotemporal ordered state, but the neuronal dynamics exhibits interesting synchronization transitions with time delay from zigzag fronts of excitations to dynamic clustering anti-phase synchronization (APS), and further to clustered chimera states which have spatially distributed anti-phase coherence separated by incoherence. Furthermore, we also show how these findings are influenced by the change of the noise intensity and the rewiring probability of the small-world networks. Finally, qualitative analysis is given to illustrate the numerical results.     

Networks of probabilistic events in discrete time

The usual methods of applying Bayesian networks to the modeling of temporal processes, such as Dean and Kanazawa’s dynamic Bayesian networks (DBNs), consist in discretizing time and creating an instance of each random variable for each point in time. We present a new approach called network of probabilistic events in discrete time (NPEDT), for temporal reasoning with uncertainty in domains involving probabilistic events. Under this approach, time is discretized and each value of a variable represents the instant at which a certain event may occur. This is the main difference with respect to DBNs, in which the value of a variable V_i represents the state of a real-world property at time t_i. Therefore, our method is more appropriate for temporal fault diagnosis, because only one variable is necessary for representing the occurrence of a fault and, as a consequence, the networks involved are much simpler than those obtained by using DBNs. In contrast, DBNs are more appropriate for monitoring tasks, since they explicitly represent the state of the system at each moment. We also introduce in this paper several types of temporal noisy gates, which facilitate the acquisition and representation of uncertain temporal knowledge. They constitute a generalization of traditional canonical models of multicausal interactions, such as the noisy OR-gate, which have been usually applied to static domains. We illustrate the approach with the example domain of modeling the evolution of traffic jams produced on the outskirts of a city, after the occurrence of an event that obliges traffic to stop indefinitely.     

Singular control problems in bounded intervals

We consider optimal control problems for one-dimensional diffusion processes y _x (t) = y ^v _x (t), solutions dy _x (t) = g(y _x (t) dt + σ(y _x (t)(dw) + dv _t with y _x(0) = x& isinv;[a,b], the control processes v _t are increasing, positive, and adapted. Several types of expected cost structures associated with each policy v(.) are adopted, e.g. discounted cost, long term average cost and time average cost. Our work is related to [2,6,12,14,16 and 21], where diffusions are allowed to evolve in the whole space, and to [13] and [20], where diffusions evolve only in bounded regions. We shall present some analytic results about value functions, mainly their characterizations, by simple dynamic programming arguments. Several simple examples are explicitly solved to illustrate the singular behaviour of our problems     

Sequential nonlinear estimation with nonaugmented priors

How can the basic compatibility of theory and observations be investigated for nonlinear processes without requiring stochastic characterizations for residual error terms? The present paper proposes a flexible least-cost approach. For each possible estimatex for the sequence of process states, letc _D (x) andx _M(x) denote the costs incurred for deviations away from the prior dynamic specifications and prior measurement specifications, respectively. Define the cost-efficiency frontier to be the greatest lower bound for the set of all possible cost pairs [c _D (x),c _M(x)], conditional on the given observations. State sequence estimatesx that attain the cost-efficiency frontier indicate the possible ways that the actual process could have developed over time in a manner minimally incompatible with the prior dynamic and measurement specifications. An algorithm is developed for the exact sequential updating of the cost-efficient state sequence estimates as the duration of the process increases and additional observations are obtained.     

Conditional Resolvability of Honeycomb and Hexagonal Networks

Given a graph G = (V, E), a set W í V{W \subseteq V} is said to be a resolving set if for each pair of distinct vertices u, v ? V{u, v \in V} there is a vertex x in W such that d(u, x) 1 d(v, x){d(u, x) \neq d(v, x)} . The resolving number of G is the minimum cardinality of all resolving sets. In this paper, conditions are imposed on resolving sets and certain conditional resolving parameters are studied for honeycomb and hexagonal networks.     

Approximate solutions for expanding search games on general networks

We study the classical problem introduced by R. Isaacs and S. Gal of minimizing the time to find a hidden point H on a network Q moving from a known starting point. Rather than adopting the traditional continuous unit speed path paradigm, we use the dynamic “expanding search” paradigm recently introduced by the authors. Here the regions S(t) that have been searched by time t are increasing from the starting point and have total length t. Roughly speaking the search follows a sequence of arcs \(a_i\) such that each one starts at some point of an earlier one. This type of search is often carried out by real life search teams in the hunt for missing persons, escaped convicts, terrorists or lost airplanes. The paper which introduced this type of search solved the adversarial problem (where H is hidden to maximize the time to be found) for the cases where Q is a tree or is 2-arc-connected. This paper’s main contribution is to give two strategy classes which can be used on any network and have expected search times which are within a factor close to 1 of the value of the game (minimax search time). These strategies classes are respectively optimal for trees and 2-arc-connected networks. We also solve the game for circle-and-spike networks, which can be considered as the simplest class of networks for which a solution was previously unknown.

     

Dynamic scheduling in multiclass queueing networks: Stability under discrete-review policies

This paper describes a family of discrete-review policies for scheduling open multiclass queueing networks. Each of the policies in the family is derived from what we call a dynamic reward function: such a function associates with each queue length vector q and each job class k a positive value r _k (q), which is treated as a reward rate for time devoted to processing class k jobs. Assuming that each station has a traffic intensity parameter less than one, all policies in the family considered are shown to be stable. In such a policy, system status is reviewed at discrete points in time, and at each such point the controller formulates a processing plan for the next review period, based on the queue length vector observed. Stability is proved by combining elementary large deviations theory with an analysis of an associated fluid control problem. These results are extended to systems with class dependent setup times as well as systems with alternate routing and admission control capabilities. This revised version was published online in June 2006 with corrections to the Cover Date.     

On a Vlasov–Schrödinger–Poisson Model

Abstract

A Vlasov–Schrödinger–Poisson system is studied, modeling the transport and interactions of electrons in a bidimensional electron gas. The particles are assumed to have a wave behaviour in the confinement direction (z) and to behave like point particles in the directions parallel to the electron gas (x). For each fixed x and at each time t, the eigenfunctions and the eigenenergies of the Schrödinger operator in the z are computed. The occupation number of each eigenfunction is computed through the resolution of a Vlasov equation in the x direction, the force field being the gradient of the eigenenergy. The whole system is coupled to the Poisson equation for the electrostatic interaction. Existence of weak solutions is shown for boundary value problems in the stationary and time-dependent regimes.     

On qualitative analysis of delay systems and xΔ = f(t, x, xσ) on time scales

Here we solve two problems presented in paper [9] (C C Tisdell and A Zaidi, Basic qualitative and quantitative results for solutions to nonlinear, dynamic equations on time scales with an application to economic modelling, Nonlinear Anal. 68 (2008) 3504–3524). We study existence and uniqueness of solutions for delay systems and first-order dynamic equations of the form x ^Δ = f (t,x,x ^σ ) on time scales by using the Banach’s fixed-point theorem. Some examples are presented to illustrate the efficiency of the proposed results.     

Graphic requirements for multistability and attractive cycles in a Boolean dynamical framework

To each Boolean function and each x{0,1}ⁿ, we associate a signed directed graph G(x), and we show that the existence of a positive circuit in G(x) for some x is a necessary condition for the existence of several fixed points in the dynamics (the sign of a circuit being defined as the product of the signs of its edges), and that the existence of a negative circuit is a necessary condition for the existence of an attractive cycle. These two results are inspired by rules for discrete models of genetic regulatory networks proposed by the biologist R. Thomas. The proof of the first result is modelled after a recent proof of the discrete Jacobian conjecture.     

Convergence to Equilibrium for a Thin-Film Equation on a Cylindrical Surface

The degenerate parabolic equation u _t + ? _x [u ³(u _xxx  + u _x  ? sin x)] = 0 models the evolution of a thin liquid film on a stationary horizontal cylinder. It is shown here that for each mass there is a unique steady state, given by a droplet hanging from the bottom of the cylinder that meets the dry region with zero contact angle. The droplet minimizes the associated energy functional and attracts all strong solutions that satisfy certain energy and entropy inequalities, including all positive solutions. The distance of solutions from the steady state cannot decay faster than a power law.     

Equilibrium resource distribution in a network model

A network is modeled by a weighted undirected graph G. Some certain time invariable resource is assigned to each node and is distributed among the incident edges at each time (time is assumed to be discrete). A state of the network corresponds to a distribution of resources of all nodes among the edges of G. At each time a vertex i evaluates its relationship with an adjacent vertex j according to a given function c _ij (x _ij , x _ji ) of the resources x _ij and x _ji provided by the nodes i and j to the edge (i, j). Since resources of the nodes are redistributed at every time, the state of the system varies in time. Some sufficient conditions are found for the existence of the limit and equilibrium states of the model; and precise formulas are given to compute these states in the case of a special function c _ij for an arbitrary graph G.     

The linear quadratic minimum-time problem for a class of discrete systems

We consider a linear discrete-time systems controlled by inputs on L ²([0, t _N ], U), where (t _i )_{1?≤?i?≤?N} is a given sequence of times. The final time t _N (or N) is considered to be free. Given an initial state x ₀ and a final one x _d , we investigate the optimal control which steers the system from x ₀ to x _d with a minimal cost J(N, u) that includes the final time and energy terms. We treat this problem for both infinte and finite dimensional state space. We use a method similar to the Hilbert Uniqueness Method. A numerical simulation is given.     

A New Approach to Cycling in a 2-locus 2-allele Genetic Model

In the reproductive process new genetic types arise due to crossing over and recombination at the meiotic stage. A simplified biological model will be developed which incorporates this effect and the effect of selection. Although a chromosome may contain thousands of genes we will consider a simplified model consisting of two genetic loci, each containing two alleles of some gene.

The model will be then turned into a difference equation or mapping model x* = G(x,r) where x represents the frequency distribution of genotypes in a certain infinite population, x* is this distribution one generation later and r is the recombination parameter. For a certain choice of fitness and recombination parameters the mapping exhibits several fixed points. As r is varied one of the fixed points of the mapping loses its stability due to a conjugate pair of eigenvalues of the linearized mapping leaving the unit disk. It is shown that the required non-resonance conditions and “nonlinear damping” condition are satisfied and thus the fixed point undergoes a Neimark–Sacker bifurcation to a cycling or oscillatory state.

Once a cycling orbit is established one can conclude that genetic variation (over time) of the population can be maintained. This work reformulates and proves earlier observations of Alan Hastings in a way that makes the treatment of chromosomes with more genetic loci more straightforward.     

Static and Dynamic Path Selection on Expander Graphs: A Random Walk Approach

This paper addresses the problem of virtual circuit switching in bounded degree expander graphs. We study the static and dynamic versions of this problem. Our solutions are based on the rapidly mixing properties of random walks on expander graphs. In the static version of the problem an algorithm is required to route a path between each of K pairs of vertices so that no edge is used by more than g paths. A natural approach to this problem is through a multicommodity flow reduction. However, we show that the random walk approach leads to significantly stronger‐results than those recently obtained by Leighton and Rao [Proc. of 9th International Parallel Processing Symposium, 1995] using the multicommodity flow setup. In the dynamic version of the problem connection requests are continuously injected into the network. Once a connection is established it utilizes a path (a virtual circuit) for a certain time until the communication terminates and the path is deleted. Again each edge in the network should not be used by more than g paths at once. The dynamic version is a better model for the practical use of communication networks. Our random walk approach gives a simple and fully distributed solution for this problem. We show that if the injection to the network and the duration of connection are both controlled by Poisson processes then our algorithm achieves a steady state utilization of the network which is similar to the utilization achieved in the static case situation. ©1999 John Wiley & Sons, Inc. Random Struct. Alg., 14, 87–109, 1999     

Threshold phenomena in the transient behaviour of Markovian models of communication networks and databases

This paper accompanies a talk given at the Workshop on Mathematical Methods in Queueing Networks held at the Mathematical Sciences Institute at Cornell University in August 1988. In earlier work we had exhibited a threshold phenomenon in the transient behaviour of a closed network of ./M/1 nodes: When there areN customers circulating, and the initial state isx, letd _x ^N (t) denote the total variation distance between the distribution at timet and the stationary distribution. Let d^N(t) = max _x d _x ^N (t). We explicitly founda _N proportional toN such thatd ^N(ta_N)1 forevery t<1, andd ^N(ta_N)0 forevery t>1. Thus it appears that the network has not yet converged to stationarity uptoa _N , but has converged to stationarity aftera _N , soa _N can be naturally interpreted as the settling time of the network. Here we briefly deal with some other similar models — closed networks of ./M/m nodes, a well studied model for circuit switched networks, and a model of Mitra for studying concurrency control in databases. Similar threshold phenomena are established in the transient behaviour of these models.Research supported by the National Science Foundation, Grant No. NCR 8710840.     

Network search games with immobile hider,without a designated searcher starting point

In the (zero-sum) search game Γ(G, x) proposed by Isaacs, the Hider picks a point H in the network G and the Searcher picks a unit speed path S(t) in G with S(0) = x. The payoff to the maximizing Hider is the time T = T(S, H) = min{t : S(t) = H} required for the Searcher to find the Hider. An extensive theory of such games has been developed in the literature. This paper considers the related games Γ(G), where the requirement S(0) = x is dropped, and the Searcher is allowed to choose his starting point. This game has been solved by Dagan and Gal for the important case where G is a tree, and by Alpern for trees with Eulerian networks attached. Here, we extend those results to a wider class of networks, employing theory initiated by Reijnierse and Potters and completed by Gal, for the fixed-start games Γ(G, x). Our results may be more easily interpreted as determining the best worst-case method of searching a network from an arbitrary starting point.     

The Perturbed Plane-Wave Solutions of the Cubic Schrödinger Equation

A detailed analysis is given to the solution of the cubic Schrödinger equation iq_t + q_xx + 2|q|²q = 0 under the boundary conditions as |x|→∞. The inverse-scattering technique is used, and the asymptotic state is a series of solitons. However, there is no soliton whose amplitude is stationary in time. Each soliton has a definite velocity and “pulsates” in time with a definite period. The interaction of two solitons is considered, and a possible extension to the perturbed periodic wave [q(x + T,t) = q(x,t) as |x|→∞] is discussed.     

Polynomials of binomial type and compound Poisson processes

Let q_nand s_n, n ε N, respectively, be a set of polynomials of binomial type and a Sheffer set related to it, both having positive coefficients. Then q_n(x), x > 0 is connected with the probability that a compound Poisson process starting at zero is in state n at time τx andq_n(x)/q_n(1) is the probability generating function of the number of jumps of this process in [0, τ] given that it is in state n at time τ. The s_n admit similar interpretations when the initial distribution of the compound Poisson process is not concentrated at zero. The possible limits for n → ∞ ofq_n(x)/q_n(1)ands_n(x)/s_n(1) are studied.     

Discrimination Between B-Processes is Impossible

Two series of binary observations x ₁,x ₁,… and y ₁,y ₂,… are presented: x _n and y _n are given at each time n∈ℕ. It is assumed that the sequences are generated independently of each other by two B-processes. The question of interest is whether the sequences represent a typical realization of two different processes or of the same one. It is demonstrated that this is impossible to decide, in the sense that every discrimination procedure is bound to err with non-negligible frequency when presented with sequences from some B-processes. This contrasts with earlier positive results on B-processes, in particular, those showing that there are consistent [`(d)]\bar{d} -distance estimates for this class of processes, and on ergodic processes, in particular, those establishing consistent change point estimates.