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Firing Time (firing + time)
Selected AbstractsHierarchical model of the population dynamics of hippocampal dentate granule cellsHIPPOCAMPUS, Issue 5 2002G.A. Chauvet Abstract A hierarchical modeling approach is used as the basis for a mathematical representation of the population activity of hippocampal dentate granule cells. Using neural field equations, the variation in time and space of dentate granule cell activity is derived from the summed synaptic potential and summed action potential responses of a population of granule cells evoked by monosynaptic excitatory input from entorhinal cortical afferents. In this formulation of the problem, we have considered a two-level hierarchy: the synapses of entorhinal cortical axons define the first level of organization, and dentate granule cells, which include these synapses, define the second, higher level of organization. The model is specified by two state field variables, for membrane potential and for synaptic efficacy, respectively, with both evolving according to different time scales. The two state field variables introduce new parameters, physiological and anatomical, which characterize the dentate from the point of view of neuronal and synaptic populations: (1) a set of geometrical constraints corresponding to the morphological properties of granule cells and anatomical characteristics of entorhinal-dentate connections; and (2) a set of neuronal parameters corresponding to physiological mechanisms. Assuming no interaction between granule cells, i.e., neither ephaptic nor synaptic coupling, the model is shown to be mathematically tractable and allows solution of the field equations leading to the determination of activity. This treatment leads to the definition of two state variables, volume of stimulated synapses and firing time, which describe observed activity. Numerical simulations are used to investigate the populational characterization of the dentate by individual parameters: (1) the relationship between the conditions of stimulation of active perforant path fibers, e.g., stimulating intensity, and activity in the granule cell layer; and (2) the influence of geometry on the generation of activity, i.e., the influence of neuron density and synaptic density-connectivity. As an example application of the model, the granule cell population spike is reconstructed and compared with experimental data. Hippocampus 2002;12:698,712. © 2002 Wiley-Liss, Inc. [source] High efficiency screen-printed EFG Si solar cells through rapid thermal processing-induced bulk lifetime enhancementPROGRESS IN PHOTOVOLTAICS: RESEARCH & APPLICATIONS, Issue 1 2005K. Nakayashiki Abstract This paper shows that one second (1,s) firing of Si solar cells with screen-printed Al on the back and SiNx anti-reflection coating on the front can produce a high quality Al-doped back-surface-field (Al-BSF) and significantly enhance SiNx -induced defect hydrogenation in the bulk Si. Open-circuit voltage, internal quantum efficiency measurements, and cross-sectional scanning electron microscopy pictures on float-zone silicon cells revealed that 1,s firing in rapid thermal processing at 750°C produces just as good a BSF as 60,s firing, indicating that the quality of Al-BSF region is not a strong function of RTP firing time at 750°C. Analysis of edge-defined film-fed grown (EFG) Si cells showed that short-term firing is much more effective in improving the hydrogen passivation of bulk defects in EFG Si. Average minority-carrier lifetime in EFG wafers improved from ,3 to ,33,,s by 60,s firing but reached as high as 95,s with 1,s firing, resulting in 15·6% efficient screen-printed cells on EFG Si. Copyright © 2004 John Wiley & Sons, Ltd. [source] Fault tolerant control design via hybrid petri nets,ASIAN JOURNAL OF CONTROL, Issue 5 2010Hao Yang Abstract This paper proposes a novel fault tolerant control (FTC) scheme for hybrid systems modeled by hybrid Petri nets (HPNs). The HPNs model consists of discrete and continuous PNs. The faults are represented by unobservable discrete transitions or the normal observable discrete transitions with abnormal firing time in discrete PNs. First, an observer-based fault diagnosis method is proposed to estimate the marking in discrete places with unknown initial marking and diagnose the faulty behavior simultaneously. Then, an adaptive fault tolerant controller is designed to maintain the general mutual exclusion constraints (GMEC) of discrete PNs, and a scheme that adjusts firing speeds of continuous transitions is provided to maintain the optimality of continuous PNs. Finally, an example of an intelligent transportation system consisting of automated vehicles on a bridge is included to demonstrate the effectiveness of our developed techniques. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society [source] Bayesian Nonparametric Modeling for Comparison of Single-Neuron Firing IntensitiesBIOMETRICS, Issue 1 2010Athanasios Kottas Summary We propose a fully inferential model-based approach to the problem of comparing the firing patterns of a neuron recorded under two distinct experimental conditions. The methodology is based on nonhomogeneous Poisson process models for the firing times of each condition with flexible nonparametric mixture prior models for the corresponding intensity functions. We demonstrate posterior inferences from a global analysis, which may be used to compare the two conditions over the entire experimental time window, as well as from a pointwise analysis at selected time points to detect local deviations of firing patterns from one condition to another. We apply our method on two neurons recorded from the primary motor cortex area of a monkey's brain while performing a sequence of reaching tasks. [source] | ||||||||||