7098291
Low correlation between random synaptic inputs impacts considerably on the output of the Hodgkin-Huxley model
Abstract The effects of positive and negative correlation, c , between ( N =100) random synaptic inputs (each firing at 100 Hz) on the mean and coefficient of variation (CV) of interspike interval (ISI) of the Hodgkin–Huxley model are examined, for different IPSP/EPSP frequency ratios, r . Mean (ISI) and CV are approximately constant (30–40 ms, and 0.75, respectively) under independence for r ∈[0,1], unlike the leaky IF small negative correlations ( c ≃−0.005) double mean ISI and increase CV by 25%.
7897839
Effects of Correlation and Degree of Balance in Random Synaptic Inputs on the Output of the Hodgkin-Huxley Model
We examine the effects of degree of balance between inhibitory and excitatory random synaptic inputs, and of positive correlation between the inputs on the mean and variability of the output of the classical Hodgkin-Huxley (HH) model for squid giant axon, using computer simulation. The mean interspike interval (ISI) and the coefficient of variation of ISI change little as the degree of balance changes, unlike the leaky integrate-and-fire model, frequently used in stochastic network modelling as an approximation to more biophysically based models. Low correlations (up to about 0.1) between 100 excitatory inputs each firing at 100 Hz reduce the mean(ISI) to below a third of its value when the inputs are independent, and CV by a factor of 5 from a near-Poisson range to one associated with regular firing.
10774169
Significance of random neuronal drive
Abstract Effectively random firing occurs frequently in the brain. Random components of neuronal drive are therefore often major influences on activity. We describe here how level of drive, inhibitory/excitatory balance, correlation between input streams, EPSP/IPSP characteristics, the nature of the postsynaptic neuron all affect pattern and level of firing, the influence often interacting in complex ways. Random firing might also be instrumental in facilitating synchronized firing. These factors are possibly important elements of the mechanisms by which some neural networks encode information. Clarifying them might therefore facilitate a deeper understanding of the nature of the neural code.
206848726
Viewing a Class of Neurodynamics on Parameter Space
Nearly all models in neural networks start from the assumption that the input-output characteristic is a sigmoidal function. On parameter space we present a systematic and feasible method for analyzing the whole spectrum of attractors-all saturated, all-but-one saturated, all-but-two saturated, etc. — of a neurodynamical system with a saturated sigmoidal function as its input-output characteristic. We present an argument which claims, under a mild condition, that only all saturated or all-but-one saturated attractors are observable for the neurodynamics. For any given all saturated configuration ξ (all-but-one saturated configuration η) the paper shows how to construct an exact parameter region R(ξ) (¯R(η)) such that if and only if the parameters fall within R(ξ) (¯R(η)), then ξ (η) is an attractor (a fixed point) of the dynamics. The parameter region for an all saturated fixed point attractor is independent of the specific choice of a saturated sigmoidal function, whereas for an all-but-one saturated fixed point it is sensitive to the input-output characteristic.
11160456
Structure of Lateral Inhibition in an Olfactory Bulb Model
It has been shown that mutual lateral inhibition of the projection neurones in the olfactory bulb, mediated by interneurones, serves to tune the representation of odours in the bulb and reduce the overlap between similaz odorants. In this paper we demonstrate that the parameters of the lateral interaction, specifically the relation of synaptic strength to cell separation and the effective overall gain of the network, have a significant effect on the strength and range of lateral inhibition in a simple model of the olfactory bulb.
877766
Inhibitory inputs increase a neurons's firing rate
Abstract Neurons are typically thought of as receiving information primarily through excitatory inputs, with inhibitory inputs playing a gating or regulating role. In this paper we demonstrate that increasing the strength of inhibitory inputs to the Hodgkin–Huxley and FitzHugh–Nagumo models can induce them to fire faster. This result is counter-intuitive and important in neural network modelling where inhibitory inputs are often neglected.
9973306
The Earth System Grid: Supporting the Next Generation of Climate Modeling Research
Understanding the Earth's climate system and how it might be changing is a preeminent scientific challenge. Global climate models are used to simulate past, present, and future climates, and experiments are executed continuously on an array of distributed supercomputers. The resulting data archive, spread over several sites, currently contains upwards of 100 TB of simulation data and is growing rapidly. Looking toward mid-decade and beyond, we must anticipate and prepare for distributed climate research data holdings of many petabytes. The Earth System Grid (ESG) is a collaborative interdisciplinary project aimed at addressing the challenge of enabling management, discovery, access, and analysis of these critically important datasets in a distributed and heterogeneous computational environment. The problem is fundamentally a Grid problem. Building upon the Globus toolkit and a variety of other technologies, ESG is developing an environment that addresses authentication, authorization for data access, large-scale data transport and management, services and abstractions for high-performance remote data access, mechanisms for scalable data replication, cataloging with rich semantic and syntactic information, data discovery, distributed monitoring, and Web-based portals for using the system.
4634224
Structural analysis of the KGD sequence loop of barbourin, an αIIbβ3-specific disintegrin
Disintegrins constitute a class of small proteins that inhibit platelet aggregation by binding to the fibrinogen receptor, also referred to as integrin αIIbβ3. Contrarily to other disintegrins that bind to a series of integrins via their Arg-Gly-Asp domain, the recognition site of barbourin contains a Lys-Gly-Asp sequence that ensures its specificity towards αIIbβ3. In this article, a three-dimensional model of barbourin is proposed using homology modeling and large-scale molecular dynamics simulations. The conformations of the Lys-Gly-Asp sequence of barbourin are analyzed and compared to those of peptidomimetics that exhibit similar specificity towards αIIbβ3. The tryptophan residue following the Lys-Gly-Asp sequence of the binding domain is shown to play a crucial role in the biological activity and the specificity of barbourin. Our results suggest that this disintegrin anchors to the binding pocket of the γ-chain of fibrinogen rather than to those of the Arg-Gly-Asp sequence.
153803859
Digital State at the Leading Edge
The impact of information technology (IT) on government in the last five years has been profound. Using the governments of Canada and Ontario (both recognized as international leaders in the use of IT) as case studies, Digital State at the Leading Edge is the first attempt to take a comprehensive view of the influence of IT on the whole of government, including areas such as political campaigning, public consultation, service delivery, knowledge management, and procurement.Exploring the concepts of channel choice, procurement market analysis, organizational integration, and digital leadership, this study looks at the inter-relationships among various aspects of the application of IT to government and politics. The authors seek to understand how IT is transforming government and what the nature of that transformation is. In the process, they offer an explanation of Canada's relative success, and conclude with practical advice to politicians and public servants about how to manage IT in government more effectively. Based on original research undertaken over the last five years, the findings of this innovative study will be of particular interest to those studying or working in the fields of public administration, political science, and information technology.
367503
Large-Scale Dependency Knowledge Acquisition and its Extrinsic Evaluation Through Word Sense Disambiguation
Knowledge plays a central role in intelligent systems. Manual knowledge acquisition is very inefficient and expensive. In this paper, we present (1) an automatic method to acquire a large amount of lexical-dependency knowledge, and (2) an innovative knowledge representation model to effectively minimize the impact of noise and improve knowledge quality. We also propose a new type of knowledge base evaluation-extrinsic evaluation, which evaluates knowledge by its impact to an external application. In our experiments we adopt Word Sense Disambiguation (WSD) as the extrinsic evaluation measure. Due to the lack of sufficient knowledge, existing WSD methods either are brittle and only capable of processing a limited number of topics or words, or provide only mediocre performance in real-world settings. With the support of acquired knowledge, our unsupervised WSD system significantly outperformed the best unsupervised systems participating in SemEval 2007, and achieved the disambiguation accuracy approaching top-performing supervised systems.
9288911
The search for a new model structure of β-Factor XIIa
We present the search for a new model of β-factor XIIa, a blood coagulation enzyme, with an unknown experimental 3D-structure. We decided to build not one but three different models using different homologous proteins as well as different techniques and different modellers. Additional studies, including extensive molecular dynamics simulations on the solvated state, allowed us to draw several conclusions concerning homology modelling, in general, and β-factor XIIa, in particular.