Double coherence resonance in neuron models driven by discrete correlated noise

We study the influence of correlations among discrete stochastic excitatory or inhibitory inputs on the response of the FitzHugh-Nagumo neuron model. For any level of correlation the emitted signal exhibits at some finite noise intensity a maximal degree of regularity, i.e., a coherence resonance. Furthermore, for either inhibitory or excitatory correlated stimuli a {\it Double Coherence Resonance} (DCR) is observable. DCR refers to a (absolute) maximum coherence in the output occurring for an optimal combination of noise variance and correlation. All these effects can be explained by taking advantage of the discrete nature of the correlated inputs.Comment: 4 pages, 3 figures in eps, to appear in Physical Review Letter

Introduction

Since the awakening of the public and the medical educational establishment to the growing deficit of appropriately trained physicians to deliver primary care in the community, attention is now turned to the provision of educational programs appropriate for such physicians at the graduate and continuing educational levels. In the past, the inability to measure outcomes of patient care systems (that is, to use the scientific method in community settings) has hampered the union of the educational system with that of patient care. Many studies now are showing that outcomes are profoundly affected by communication and compliance between physician and patient. A partnership of the expertise of the medical center with the laboratory of the practice in the community equipped to measure the process of delivery, as well as outcomes, appears essential

The relationship of feeder grade of heifer calves to feedlot performance and carcass characteristics

LD2668 .T4 1947 S56Master of Scienc

The Importance of Effective Working Relationships Between Sales and Marketing

© Oxford University Press 2011. All rights reserved. This article examines the importance of effective working relationships between sales and marketing. It provides a framework for analysis and discussion concerning this important organizational relationship. It reviews current thinking on sales-marketing cross-functional relationships, identifies gaps in academic literature, and discusses a range of controllable and uncontrollable factors that may influence this interface. Many organizations are unsure how to manage the sales-marketing cross-functional relationship. The few empirical studies published to date examine the contextual conditions under which such relationships are enacted, e.g., the level of functional interdependence, power relations, and cultural differences. This article discusses the main types of variable that influence the effectiveness of such relationships. These include organizational structure variables, the types of interaction and communication prevalent in the cross-functional relationship, and key variables such as interpersonal trust

Computational inference in systems biology

Parameter inference in mathematical models of biological pathways, expressed as coupled ordinary differential equations (ODEs), is a challenging problem. The computational costs associated with repeatedly solving the ODEs are often high. Aimed at reducing this cost, new concepts using gradient matching have been proposed. This paper combines current adaptive gradient matching approaches, using Gaussian processes, with a parallel tempering scheme, and conducts a comparative evaluation with current methods used for parameter inference in ODEs

Delay Induced Excitability

We analyse the stochastic dynamics of a bistable system under the influence of time-delayed feedback. Assuming an asymmetric potential, we show the existence of a regime in which the systems dynamic displays excitability by calculating the relevant residence time distributions and correlation times. Experimentally we then observe this behaviour in the polarization dynamics of a vertical cavity surface emitting laser with opto-electronic feedback. Extending these observations to two-dimensional systems with dispersive coupling we finally show numerically that delay induced excitability can lead to the appearance of propagating wave-fronts and spirals.Comment: 5 pages, 6 figure

Modeling rhythmic patterns in the hippocampus

We investigate different dynamical regimes of neuronal network in the CA3 area of the hippocampus. The proposed neuronal circuit includes two fast- and two slowly-spiking cells which are interconnected by means of dynamical synapses. On the individual level, each neuron is modeled by FitzHugh-Nagumo equations. Three basic rhythmic patterns are observed: gamma-rhythm in which the fast neurons are uniformly spiking, theta-rhythm in which the individual spikes are separated by quiet epochs, and theta/gamma rhythm with repeated patches of spikes. We analyze the influence of asymmetry of synaptic strengths on the synchronization in the network and demonstrate that strong asymmetry reduces the variety of available dynamical states. The model network exhibits multistability; this results in occurrence of hysteresis in dependence on the conductances of individual connections. We show that switching between different rhythmic patterns in the network depends on the degree of synchronization between the slow cells.Comment: 10 pages, 9 figure

Emergence of Synchronous Oscillations in Neural Networks Excited by Noise

The presence of noise in non linear dynamical systems can play a constructive role, increasing the degree of order and coherence or evoking improvements in the performance of the system. An example of this positive influence in a biological system is the impulse transmission in neurons and the synchronization of a neural network. Integrating numerically the Fokker-Planck equation we show a self-induced synchronized oscillation. Such an oscillatory state appears in a neural network coupled with a feedback term, when this system is excited by noise and the noise strength is within a certain range.Comment: 12 pages, 18 figure

Dynamical mechanism of anticipating synchronization in excitable systems

We analyze the phenomenon of anticipating synchronization of two excitable systems with unidirectional delayed coupling which are subject to the same external forcing. We demonstrate for different paradigms of excitable system that, due to the coupling, the excitability threshold for the slave system is always lower than that for the master. As a consequence the two systems respond to a common external forcing with different response times. This allows to explain in a simple way the mechanism behind the phenomenon of anticipating synchronization.Comment: 4 pages including 7 figures. Submitted for publicatio