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Sample records for spiked test spectra

  1. AMORE Mo-99 Spike Test Results

    Energy Technology Data Exchange (ETDEWEB)

    Youker, Amanda J. [Argonne National Lab. (ANL), Argonne, IL (United States); Krebs, John F. [Argonne National Lab. (ANL), Argonne, IL (United States); Quigley, Kevin J. [Argonne National Lab. (ANL), Argonne, IL (United States); Byrnes, James P. [Argonne National Lab. (ANL), Argonne, IL (United States); Rotsch, David A [Argonne National Lab. (ANL), Argonne, IL (United States); Brossard, Thomas [Argonne National Lab. (ANL), Argonne, IL (United States); Wesolowski, Kenneth [Argonne National Lab. (ANL), Argonne, IL (United States); Alford, Kurt [Argonne National Lab. (ANL), Argonne, IL (United States); Chemerisov, Sergey [Argonne National Lab. (ANL), Argonne, IL (United States); Vandegrift, George F. [Argonne National Lab. (ANL), Argonne, IL (United States)

    2017-09-27

    With funding from the National Nuclear Security Administrations Material Management and Minimization Office, Argonne National Laboratory (Argonne) is providing technical assistance to help accelerate the U.S. production of Mo-99 using a non-highly enriched uranium (non-HEU) source. A potential Mo-99 production pathway is by accelerator-initiated fissioning in a subcritical uranyl sulfate solution containing low enriched uranium (LEU). As part of the Argonne development effort, we are undertaking the AMORE (Argonne Molybdenum Research Experiment) project, which is essentially a pilot facility for all phases of Mo-99 production, recovery, and purification. Production of Mo-99 and other fission products in the subcritical target solution is initiated by putting an electron beam on a depleted uranium (DU) target; the fast neutrons produced in the DU target are thermalized and lead to fissioning of U-235. At the end of irradiation, Mo is recovered from the target solution and separated from uranium and most of the fission products by using a titania column. The Mo is stripped from the column with an alkaline solution. After acidification of the Mo product solution from the recovery column, the Mo is concentrated (and further purified) in a second titania column. The strip solution from the concentration column is then purified with the LEU Modified Cintichem process. A full description of the process can be found elsewhere [1–3]. The initial commissioning steps for the AMORE project include performing a Mo-99 spike test with pH 1 sulfuric acid in the target vessel without a beam on the target to demonstrate the initial Mo separation-and-recovery process, followed by the concentration column process. All glovebox operations were tested with cold solutions prior to performing the Mo-99 spike tests. Two Mo-99 spike tests with pH 1 sulfuric acid have been performed to date. Figure 1 shows the flow diagram for the remotely operated Mo-recovery system for the AMORE project

  2. Proficiency test on incurred and spiked pesticide residues in cereals

    DEFF Research Database (Denmark)

    Poulsen, Mette Erecius; Christensen, Hanne Bjerre; Herrmann, Susan Strange

    2009-01-01

    A proficiency test on incurred and spiked pesticide residues in wheat was organised in 2008. The test material was grown in 2007 and treated in the field with 14 pesticides formulations containing the active substances, alpha-cypermethrin, bifentrin, carbendazim, chlormequat, chlorpyrifos-methyl,...

  3. Self-Consistent Scheme for Spike-Train Power Spectra in Heterogeneous Sparse Networks.

    Science.gov (United States)

    Pena, Rodrigo F O; Vellmer, Sebastian; Bernardi, Davide; Roque, Antonio C; Lindner, Benjamin

    2018-01-01

    Recurrent networks of spiking neurons can be in an asynchronous state characterized by low or absent cross-correlations and spike statistics which resemble those of cortical neurons. Although spatial correlations are negligible in this state, neurons can show pronounced temporal correlations in their spike trains that can be quantified by the autocorrelation function or the spike-train power spectrum. Depending on cellular and network parameters, correlations display diverse patterns (ranging from simple refractory-period effects and stochastic oscillations to slow fluctuations) and it is generally not well-understood how these dependencies come about. Previous work has explored how the single-cell correlations in a homogeneous network (excitatory and inhibitory integrate-and-fire neurons with nearly balanced mean recurrent input) can be determined numerically from an iterative single-neuron simulation. Such a scheme is based on the fact that every neuron is driven by the network noise (i.e., the input currents from all its presynaptic partners) but also contributes to the network noise, leading to a self-consistency condition for the input and output spectra. Here we first extend this scheme to homogeneous networks with strong recurrent inhibition and a synaptic filter, in which instabilities of the previous scheme are avoided by an averaging procedure. We then extend the scheme to heterogeneous networks in which (i) different neural subpopulations (e.g., excitatory and inhibitory neurons) have different cellular or connectivity parameters; (ii) the number and strength of the input connections are random (Erdős-Rényi topology) and thus different among neurons. In all heterogeneous cases, neurons are lumped in different classes each of which is represented by a single neuron in the iterative scheme; in addition, we make a Gaussian approximation of the input current to the neuron. These approximations seem to be justified over a broad range of parameters as

  4. Special Electrophysiological Tests: Brain Spiking, EEG Spectral Coherence

    Science.gov (United States)

    1983-01-01

    Mental Sciences 9TIC E-~ MAY (In Press) Handbook of Diagnostic Procedifre, Spectrum Pblications, Jamaica , New York. > This wk was pa -tially supported...likelihood is sufficiently small, then we reject the hypothesis that an EEG record containing N spikes in a time t is a normal record, - ,- - Flor several...significantly from zero, one may concl de that the two signal processes in question are related through ,o linear transformation over the spectral

  5. Extracting ion emission lines from femtosecond-laser plasma x-ray spectra heavily contaminated by spikes

    International Nuclear Information System (INIS)

    Gasilov, S. V.; Faenov, A. Ya.; Pikuz, T. A.; Villoresi, P.; Poletto, L.; Stagira, S.; Calegari, F.; Vozzi, C.; Nisoli, M.

    2007-01-01

    Nowadays charged-coupled device (CCD) detectors are widely used for the registration of multicharged ions x-ray spectra. These spectra are generated in a plasma during interaction of ultrashort, ultraintense laser pulses with solid targets. Strong parasitic radiation from the plasma affects CCD detectors and contaminates resulting spectra, so that spectral features can be completely covered by noise even during measurements with a very short accumulation time. In this work we propose a ''mean to median'' (M2M) algorithm for noise suppression in femtosecond laser plasma x-ray spectra. Series of spectra is necessary for the identification of corrupted data points by the developed method. The algorithm was tested with model spectra which reflect main features of experimental data. In practice we used it for extracting information about spectral lines of Ne-like Fe ions and He-like Al ions which allowed us to calculate plasma parameters. It is demonstrated that M2M method is able to clean spectra with more than 10% of corrupted pixels. Fluctuations in intensity of spectral lines induced by laser instability do not affect validity of the proposed method

  6. Preparation and characterization of nickel-spiked freshwater sediments for toxicity tests: toward more environmentally realistic nickel partitioning.

    Science.gov (United States)

    Brumbaugh, William G; Besser, John M; Ingersoll, Christopher G; May, Thomas W; Ivey, Chris D; Schlekat, Christian E; Garman, Emily Rogevich

    2013-11-01

    Two spiking methods were compared and nickel (Ni) partitioning was evaluated during a series of toxicity tests with 8 different freshwater sediments having a range of physicochemical characteristics. A 2-step spiking approach with immediate pH adjustment by addition of NaOH at a 2:1 molar ratio to the spiked Ni was effective in producing consistent pH and other chemical characteristics across a range of Ni spiking levels. When Ni was spiked into sediment having a high acid-volatile sulfide and organic matter content, a total equilibration period of at least 10 wk was needed to stabilize Ni partitioning. However, highest spiking levels evidently exceeded sediment binding capacities; therefore, a 7-d equilibration in toxicity test chambers and 8 volume-additions/d of aerobic overlying water were used to avoid unrealistic Ni partitioning during toxicity testing. The 7-d pretest equilibration allowed excess spiked Ni and other ions from pH adjustment to diffuse from sediment porewater and promoted development of an environmentally relevant, 0.5- to 1-cm oxic/suboxic sediment layer in the test chambers. Among the 8 different spiked sediments, the logarithm of sediment/porewater distribution coefficient values (log Kd ) for Ni during the toxicity tests ranged from 3.5 to 4.5. These Kd values closely match the range of values reported for various field Ni-contaminated sediments, indicating that testing conditions with our spiked sediments were environmentally realistic. © 2013 SETAC.

  7. Breaking HIV News to Clients: SPIKES Strategy in Post-Test Counseling Session

    Directory of Open Access Journals (Sweden)

    Hamid Emadi-Koochak

    2016-05-01

    Full Text Available Breaking bad news is one of the most burdensome tasks physicians face in their everyday practice. It becomes even more challenging in the context of HIV+ patients because of stigma and discrimination. The aim of the current study is to evaluate the quality of giving HIV seroconversion news according to SPIKES protocol. Numbers of 154 consecutive HIV+ patients from Imam Khomeini Hospital testing and counseling center were enrolled in this study. Patients were inquired about how they were given the HIV news and whether or not they received pre- and post-test counseling sessions. Around 51% of them were men, 80% had high school education, and 56% were employed. Regarding marital status, 32% were single, and 52% were married at the time of the interview. Among them, 31% had received the HIV news in a counseling center, and only 29% had pre-test counseling. SPIKES criteria were significantly met when the HIV news was given in an HIV counseling and testing center (P.value<0.05. Low coverage of HIV counseling services was observed in the study. SPIKES criteria were significantly met when the HIV seroconversion news was given in a counseling center. The need to further train staff to deliver HIV news seems a priority in the field of HIV care and treatment.

  8. Spiked proteomic standard dataset for testing label-free quantitative software and statistical methods.

    Science.gov (United States)

    Ramus, Claire; Hovasse, Agnès; Marcellin, Marlène; Hesse, Anne-Marie; Mouton-Barbosa, Emmanuelle; Bouyssié, David; Vaca, Sebastian; Carapito, Christine; Chaoui, Karima; Bruley, Christophe; Garin, Jérôme; Cianférani, Sarah; Ferro, Myriam; Dorssaeler, Alain Van; Burlet-Schiltz, Odile; Schaeffer, Christine; Couté, Yohann; Gonzalez de Peredo, Anne

    2016-03-01

    This data article describes a controlled, spiked proteomic dataset for which the "ground truth" of variant proteins is known. It is based on the LC-MS analysis of samples composed of a fixed background of yeast lysate and different spiked amounts of the UPS1 mixture of 48 recombinant proteins. It can be used to objectively evaluate bioinformatic pipelines for label-free quantitative analysis, and their ability to detect variant proteins with good sensitivity and low false discovery rate in large-scale proteomic studies. More specifically, it can be useful for tuning software tools parameters, but also testing new algorithms for label-free quantitative analysis, or for evaluation of downstream statistical methods. The raw MS files can be downloaded from ProteomeXchange with identifier PXD001819. Starting from some raw files of this dataset, we also provide here some processed data obtained through various bioinformatics tools (including MaxQuant, Skyline, MFPaQ, IRMa-hEIDI and Scaffold) in different workflows, to exemplify the use of such data in the context of software benchmarking, as discussed in details in the accompanying manuscript [1]. The experimental design used here for data processing takes advantage of the different spike levels introduced in the samples composing the dataset, and processed data are merged in a single file to facilitate the evaluation and illustration of software tools results for the detection of variant proteins with different absolute expression levels and fold change values.

  9. Comparison of spike and aerosol challenge tests for the recovery of viable influenza virus from non-woven fabrics.

    Science.gov (United States)

    Zuo, Zhili; de Abin, Martha; Chander, Yogesh; Kuehn, Thomas H; Goyal, Sagar M; Pui, David Y H

    2013-09-01

    To experimentally determine the survival kinetics of influenza virus on personal protective equipment (PPE) and to evaluate the risk of virus transfer from PPE, it is important to compare the effects on virus recovery of the method used to contaminate the PPE with virus and the type of eluent used to recover it. Avian influenza virus (AIV) was applied as a liquid suspension (spike test) and as an aerosol to three types of non-woven fabrics [polypropylene (PP), polyester (PET), and polyamide (Nylon)] that are commonly used in the manufacture of PPE. This was followed by virus recovery using eight different eluents (phosphate-buffered saline, minimum essential medium, and 1.5% or 3.0% beef extract at pH 7, 8, or 9). For spike tests, no statistically significant difference was found in virus recovery using any of the eluents tested. Hydrophobic surfaces (PP and PET) yielded higher spiked virus recovery than hydrophilic Nylon. From all materials, the virus recovery was much lower in aerosol challenge tests than in spike tests. Significant differences were found in the recovery of viable AIV from non-woven fabrics between spike and aerosol challenge tests. The findings of this study demonstrate the need for realistic aerosol challenge tests rather than liquid spike tests in studies of virus survival on surfaces where airborne transmission of influenza virus may get involved. © 2013 John Wiley & Sons Ltd.

  10. Quantitative testing of buprenorphine and norbuprenorphine to identify urine sample spiking during office-based opioid treatment.

    Science.gov (United States)

    Suzuki, Joji; Zinser, Jennifer; Issa, Mohammed; Rodriguez, Claudia

    2017-01-01

    Patients may spike urine samples with buprenorphine during office-based opioid treatment to simulate adherence to prescribed buprenorphine, potentially to conceal diversion of medications. However, routine immunoassay screens do not detect instances of spiking, as these would simply result in a positive result. The aim of this study was to report on the experience of using quantitative urine testing for buprenorphine and norbuprenorphine to facilitate the identification of urine spiking. This is a retrospective chart review of 168 consecutive patients enrolled in outpatient buprenorphine treatment at an urban academic medical setting between May 2013 and August 2014. All urine samples submitted were subjected to quantitative urine toxicology testing for buprenorphine and norbuprenorphine. Norbuprenorphine-to-buprenorphine ratio of less than 0.02 were further examined for possible spiking. Demographic and clinical variables were also extracted from medical records. Clinical and demographic variables of those who did and did not spike their urines were compared. Statistically significant variables from the univariate testing were entered as predictors of spiking in a regression analysis. A total of 168 patients were included, submitting a total of 2275 urine samples. Patients provided on average 13.6 (SD = 9.9) samples, and were in treatment for an average 153.1 days (SD = 142.2). In total, 8 samples (0.35%) from 8 patients (4.8%) were deemed to be spiked. All of the samples suspected of spiking contained buprenorphine levels greater than 2000 ng/mL, with a mean norbuprenorphine level of 11.9 ng/mL. Spiked samples were submitted by 6 patients (75.0%) during the intensive outpatient (IOP) phase of treatment, 2 patients (25.0%) during the weekly phase, and none from the monthly phase. Regression analysis indicated that history of intravenous drug use and submission of cocaine-positive urine samples at baseline were significant predictors of urine spiking. Even

  11. Structure Computation of Quiet Spike[Trademark] Flight-Test Data During Envelope Expansion

    Science.gov (United States)

    Kukreja, Sunil L.

    2008-01-01

    System identification or mathematical modeling is used in the aerospace community for development of simulation models for robust control law design. These models are often described as linear time-invariant processes. Nevertheless, it is well known that the underlying process is often nonlinear. The reason for using a linear approach has been due to the lack of a proper set of tools for the identification of nonlinear systems. Over the past several decades, the controls and biomedical communities have made great advances in developing tools for the identification of nonlinear systems. These approaches are robust and readily applicable to aerospace systems. In this paper, we show the application of one such nonlinear system identification technique, structure detection, for the analysis of F-15B Quiet Spike(TradeMark) aeroservoelastic flight-test data. Structure detection is concerned with the selection of a subset of candidate terms that best describe the observed output. This is a necessary procedure to compute an efficient system description that may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modeling may be of critical importance for the development of robust parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion, which may save significant development time and costs. The objectives of this study are to demonstrate via analysis of F-15B Quiet Spike aeroservoelastic flight-test data for several flight conditions that 1) linear models are inefficient for modeling aeroservoelastic data, 2) nonlinear identification provides a parsimonious model description while providing a high percent fit for cross-validated data, and 3) the model structure and parameters vary as the flight condition is altered.

  12. Ecotoxicological assessment of the pharmaceutical compound Triclosan to freshwater invertebrates with emphasis to spiked sediment tests

    International Nuclear Information System (INIS)

    Pusceddu, Fabio Hermes

    2009-01-01

    The increasing of Pharmaceutical and Personal Care Products (PPCPs) occurrence in the aquatic environment cause adverse effects on the human health and aquatic communities. The environmental risk of the PPCPs associated with the possibility of synergic effects between PCPPs and the increase of the use of synthetic organic compounds, unchained a great concern on the toxic potential to biota aquatic. Triclosan (5-chloro-2-(2,4-dichlorophenoxy)-phenol) is a pharmaceutical compound widely used due your antibacterial mechanism effect, found in at least 932 products such as shampoos, toilet soaps, deodorants, lotions, toothpaste, detergents, socks and underwear, among others. Currently, studies about the Triclosan toxicity in the water and, mainly in the sediment, are poorly. We have the knowledge that the photodegradation of this product results into dichlorodibenzo-p-dioxin, and now it has great discussion on environmental agencies, like EPA, about the release or restriction of this product. The aim of this work is to assess the effects of Triclosan on mortality of insect larvae Chironomus xanthus and mortality and reproduction inhibition of microcrustacea Ceriodaphnia dubia exposed to Triclosan spiked sediments based on standard methods EPA and OECD. The EC50;96H obtained on acute toxicity tests with C. xanthus was 45,26 mg.Kg -1 . The chronic toxicity tests with C. dubia using spiked sediments were performed following the procedure in Burton and MacPherson (1995). A no-observed-effect concentrations and lowest-observed-effect concentration were 5,78 e 6,94 mg.Kg -1 , respectively. (author)

  13. Analysis of Isp-42, panda test with the spectra code

    International Nuclear Information System (INIS)

    Stempniewicz, M.M.

    2001-01-01

    International Standard Problems (ISP) are organized in order to assess the ability of computer codes to predict the outcome of accidents in Nuclear Power Plants. The ISP-42 test was performed at Paul Scherrer Institute in 1998, as a sequence of six phases, Phase A through F Blind and open calculations of ISP-42 were performed with the computer code SPECTRA for each of the six phases. SPECTRA is a general tool for thermal-hydraulic analyses. Results of blind calculations are in good agreement with experiment. For open calculations several modifications were made in the model. These were mainly corrections of some input errors made in the model used for blind analysis. Some small improvements to the nodalization were made. Results of open calculations are generally closer to the experiment than the blind results. For phase D the containment pressure prediction was somewhat worse in the open calculation. Based on comparisons of blind and open results with experiment several conclusions may be drawn: - use of long ID structures, in contact with pool and atmosphere should be avoided, - PCC units are better represented with larger amount of Control Volumes, - two parallel junctions should be used to represent large openings between vessels, like drywell air line, etc., - careful verification of input decks is needed, - stratification models in SPECTRA are useful for cases with light gas injection; for complex cases a complementary SPECTRA-CFD analysis may be performed. (author)

  14. WSEAT Shock Testing Margin Assessment Using Energy Spectra Final Report.

    Energy Technology Data Exchange (ETDEWEB)

    Sisemore, Carl; Babuska, Vit; Booher, Jason

    2018-02-01

    Several programs at Sandia National Laboratories have adopted energy spectra as a metric to relate the severity of mechanical insults to structural capacity. The purpose being to gain insight into the system's capability, reliability, and to quantify the ultimate margin between the normal operating envelope and the likely system failure point -- a system margin assessment. The fundamental concern with the use of energy metrics was that the applicability domain and implementation details were not completely defined for many problems of interest. The goal of this WSEAT project was to examine that domain of applicability and work out the necessary implementation details. The goal of this project was to provide experimental validation for the energy spectra based methods in the context of margin assessment as they relate to shock environments. The extensive test results concluded that failure predictions using energy methods did not agree with failure predictions using S-N data. As a result, a modification to the energy methods was developed following the form of Basquin's equation to incorporate the power law exponent for fatigue damage. This update to the energy-based framework brings the energy based metrics into agreement with experimental data and historical S-N data.

  15. Effects of sediment-spiked lufenuron on benthic macroinvertebrates in outdoor microcosms and single-species toxicity tests

    Energy Technology Data Exchange (ETDEWEB)

    Brock, T.C.M., E-mail: theo.brock@wur.nl [Alterra, Wageningen University and Research Centre, P.O. Box 47, 6700 AA Wageningen (Netherlands); Bas, D.A. [Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam (Netherlands); Belgers, J.D.M. [Alterra, Wageningen University and Research Centre, P.O. Box 47, 6700 AA Wageningen (Netherlands); Bibbe, L. [Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam (Netherlands); Boerwinkel, M-C.; Crum, S.J.H. [Alterra, Wageningen University and Research Centre, P.O. Box 47, 6700 AA Wageningen (Netherlands); Diepens, N.J. [Department of Aquatic Ecology and Water Quality Management, Wageningen University, P.O. Box 47, 6700 AA Wageningen (Netherlands); Kraak, M.H.S.; Vonk, J.A. [Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam (Netherlands); Roessink, I. [Alterra, Wageningen University and Research Centre, P.O. Box 47, 6700 AA Wageningen (Netherlands)

    2016-08-15

    Highlights: • In outdoor microcosms constructed with lufenuron-spiked sediment we observed that this insecticide persistent in the sediment compartment. • Sediment exposure to lufenuron caused population-level declines (insects and crustaceans) and increases (mainly oligochaete worms) of benthic invertebrates. • The direct and indirect effects observed in the microcosms were supported by results of sediment-spiked single species tests with Chironomus riparius, Hyalella azteca and Lumbriculus variegatus. • The tier-1 effect assessment procedure for sediment organisms recommended by the European Food Safety Authority is protective for the treatment-related responses observed in the microcosm test. - Abstract: Sediment ecotoxicity studies were conducted with lufenuron to (i) complement the results of a water-spiked mesocosm experiment with this lipophilic benzoylurea insecticide, (ii) to explore the predictive value of laboratory single-species tests for population and community-level responses of benthic macroinvertebrates, and (iii) to calibrate the tier-1 effect assessment procedure for sediment organisms. For this purpose the concentration-response relationships for macroinvertebrates between sediment-spiked microcosms and those of 28-d sediment-spiked single-species toxicity tests with Chironomus riparius, Hyalella azteca and Lumbriculus variegatus were compared. Lufenuron persisted in the sediment of the microcosms. On average, 87.7% of the initial lufenuron concentration could still be detected in the sediment after 12 weeks. Overall, benthic insects and crustaceans showed treatment-related declines and oligochaetes treatment-related increases. The lowest population-level NOEC in the microcosms was 0.79 μg lufenuron/g organic carbon in dry sediment (μg a.s./g OC) for Tanytarsini, Chironomini and Dero sp. Multivariate analysis of the responses of benthic macroinvertebrates revealed a community-level NOEC of 0.79 μg a.s./g OC. The treatment

  16. Effects of sediment-spiked lufenuron on benthic macroinvertebrates in outdoor microcosms and single-species toxicity tests.

    Science.gov (United States)

    Brock, T C M; Bas, D A; Belgers, J D M; Bibbe, L; Boerwinkel, M-C; Crum, S J H; Diepens, N J; Kraak, M H S; Vonk, J A; Roessink, I

    2016-08-01

    Sediment ecotoxicity studies were conducted with lufenuron to (i) complement the results of a water-spiked mesocosm experiment with this lipophilic benzoylurea insecticide, (ii) to explore the predictive value of laboratory single-species tests for population and community-level responses of benthic macroinvertebrates, and (iii) to calibrate the tier-1 effect assessment procedure for sediment organisms. For this purpose the concentration-response relationships for macroinvertebrates between sediment-spiked microcosms and those of 28-d sediment-spiked single-species toxicity tests with Chironomus riparius, Hyalella azteca and Lumbriculus variegatus were compared. Lufenuron persisted in the sediment of the microcosms. On average, 87.7% of the initial lufenuron concentration could still be detected in the sediment after 12 weeks. Overall, benthic insects and crustaceans showed treatment-related declines and oligochaetes treatment-related increases. The lowest population-level NOEC in the microcosms was 0.79μg lufenuron/g organic carbon in dry sediment (μg a.s./g OC) for Tanytarsini, Chironomini and Dero sp. Multivariate analysis of the responses of benthic macroinvertebrates revealed a community-level NOEC of 0.79μg a.s./g OC. The treatment-related responses observed in the microcosms are in accordance with the results of the 28-d laboratory toxicity tests. These tests showed that the insect C. riparius and the crustacean H. azteca were approximately two orders of magnitude more sensitive than the oligochaete L. variegatus. In our laboratory tests, using field-collected sediment, the lowest 28-d EC10 (0.49μg a.s./g OC) was observed for C. riparius (endpoint survival), while for the standard OECD test with this species, using artificial sediment, a NOEC of 2.35μg a.s./g OC (endpoint emergence) is reported. In this particular case, the sediment tier-1 effect assessment using the chronic EC10 (field-collected sediment) or chronic NOEC (artificial sediment) of C

  17. Sequential motor task (Luria's Fist-Edge-Palm Test in children with benign focal epilepsy of childhood with centrotemporal spikes

    Directory of Open Access Journals (Sweden)

    Carmen Silvia Molleis Galego Miziara

    2013-06-01

    Full Text Available This study evaluated the sequential motor manual actions in children with benign focal epilepsy of childhood with centrotemporal spikes (BECTS and compares the results with matched control group, through the application of Luria's fist-edge-palm test. The children with BECTS underwent interictal single photon emission computed tomography (SPECT and School Performance Test (SPT. Significant difference occurred between the study and control groups for manual motor action through three equal and three different movements. Children with lower school performance had higher error rate in the imitation of hand gestures. Another factor significantly associated with the failure was the abnormality in SPECT. Children with BECTS showed abnormalities in the test that evaluated manual motor programming/planning. This study may suggest that the functional changes related to epileptiform activity in rolandic region interfere with the executive function in children with BECTS.

  18. Putative null distributions corresponding to tests of differential expression in the Golden Spike dataset are intensity dependent

    Directory of Open Access Journals (Sweden)

    Gaile Daniel P

    2007-04-01

    Full Text Available Abstract Background We provide a re-analysis of the Golden Spike dataset, a first generation "spike-in" control microarray dataset. The original analysis of the Golden Spike dataset was presented in a manuscript by Choe et al. and raised questions concerning the performance of several statistical methods for the control of the false discovery rate (across a set of tests for differential expression. These original findings are now in question as it has been reported that the p-values associated with the tests of differential expression for null probesets (i.e., probesets designed to be fold change 1 across the two arms of the experiment are not uniformly distributed. Two recent publications have speculated as to the reasons the null distributions are non-uniform. A publication by Dabney and Storey concludes that the non-uniform distributions of null p-values are the direct consequence of an experimental design which requires technical replicates to approximate biological replicates. Irizarry et al. identify four characteristics of the feature level data (three related to experimental design and one artifact. Irizarry et al. argue that the four observed characteristics imply that the assumptions common to most pre-processing algorithms are not satisfied and hence the expression measure methodologies considered by Choe et al. are likely to be flawed. Results We replicate and extend the analyses of Dabney and Storey and present our results in the context of a two stage analysis. We provide evidence that the Stage I pre-processing algorithms considered in Dabney and Storey fail to provide expression values that are adequately centered or scaled. Furthermore, we demonstrate that the distributions of the p-values, test statistics, and probabilities associated with the relative locations and variabilities of the Stage II expression values vary with signal intensity. We provide diagnostic plots and a simple logistic regression based test statistic to

  19. Initial pressure spike and its propagation phenomena in sodium-water reaction tests for MONJU steam generators

    International Nuclear Information System (INIS)

    Sato, M.; Hiroi, H.; Tanaka, N.; Hori, M.

    1977-01-01

    With the objective of demonstrating the safe design of steam generators for prototype LMFBR MONJU against the postulated large-leak accident, a number of large-leak sodium-water reaction tests have been conducted using the SWAT-1 and SWAT-3 rigs. Investigation of the potential effects of pressure load on the system is one of the major concerns in these tests. This paper reports the behavior of initial pressure spike in the reaction vessel, its propagation phenomena to the simulated secondary cooling system, and the comparisons with the computer code for one-dimensional pressure wave propagation problems. Both rigs used are the scaled-down models of the helically coiled steam generators of MONJU. The SWAT-1 rig is a simplified model and consists of a reaction vessel (1/8 scale of MONJU evaporator with 0.4 m dia. and 2.5 m height) and a pressure relief system i.e., a pressure relief line and a reaction products tank. On the other hand, the SWAT-3 rig is a 1/2.5 scale of MONJU SG system and consists of an evaporator (reaction vessel with 1.3 m dia. and 6.35 m height), a superheater, an intermediate heat exchanger (IHX), a piping system simulating the secondary cooling circuit and a pressure relief system. The both water injection systems consist of a water injection line with a rupture disk installed in front of injection hole and an electrically heated water tank. Choice of water injection rates in the scaled-down models is made based on the method of iso-velocity modeling. Test results indicated that the characteristics of the initial pressure spike are dominated by those of initial water injection which are controlled by the conditions of water heater and the size of water injection hole, etc

  20. Analysis of remotely accrued complex gamma ray spectra - proficiency test

    Energy Technology Data Exchange (ETDEWEB)

    Dowdall, M. (Norwegian Radiation Protection Authority (Norway))

    2009-03-15

    This report presents details pertaining to an exercise conducted as part of the NKS-B programme using synthetic gamma ray spectra to simulate the type of data that may be encountered in the early phase of a nuclear accident. The aim of the exercise was to provide participants with an opportunity to exercise in the type of situation and with the type of data that may result after a nuclear accident. Attempting to conduct such exercise internationally using actual samples presents practical and logistical difficulties and a synthetic spectrum was employed to negate some of these problems. A HPGe spectrum was synthesized containing a range of typical fallout isotopes and distributed, along with calibration information, to the participant laboratories. The participants were required to submit results within three hours of receipt and with the option of submitting further results within one week. The results provided by the laboratories indicate that all laboratories were able to identify and quantify some of the isotopes but only some labs were in a position to identify and quantify virtually all the constituents of the spectrum. Results indicate that there remain some problems with aspects such as true coincidence summation and using file formats with which labs may not be familiar with. The exercise provided a useful opportunity in exploring the possibilities of using synthetic spectra for exercise purposes and offered participants the chance to practice with the sort of scenario that may result after an accident. (au)

  1. Components of Program for Analysis of Spectra and Their Testing

    Directory of Open Access Journals (Sweden)

    Ivan Taufer

    2013-11-01

    Full Text Available The spectral analysis of aqueous solutions of multi-component mixtures is used for identification and distinguishing of individual componentsin the mixture and subsequent determination of protonation constants and absorptivities of differently protonated particles in the solution in steadystate (Meloun and Havel 1985, (Leggett 1985. Apart from that also determined are the distribution diagrams, i.e. concentration proportions ofthe individual components at different pH values. The spectra are measured with various concentrations of the basic components (one or severalpolyvalent weak acids or bases and various pH values within the chosen range of wavelengths. The obtained absorbance response area has to beanalyzed by non-linear regression using specialized algorithms. These algorithms have to meet certain requirements concerning the possibility ofcalculations and the level of outputs. A typical example is the SQUAD(84 program, which was gradually modified and extended, see, e.g., (Melounet al. 1986, (Meloun et al. 2012.

  2. Leach tests on grouts made with actual and trace metal-spiked synthetic phosphate/sulfate waste

    International Nuclear Information System (INIS)

    Serne, R.J.; Martin, W.J.; LeGore, V.L.; Lindenmeier, C.W.; McLaurine, S.B.; Martin, P.F.C.; Lokken, R.O.

    1989-10-01

    Pacific Northwest Laboratory conducted experiments to produce empirical leach rate data for phosphate-sulfate waste (PSW) grout. Effective diffusivities were measured for various radionuclides ( 90 Sr, 99 Tc, 14 C, 129 I, 137 Cs, 60 Co, 54 Mn, and U), stable major components (NO 3 - , SO 4 2- , H 3 BO 3 , K and Na) and the trace constituents Ag, As, Cd, Hg, Pb, and Se. Two types of leach tests were used on samples of actual PSW grout and synthetic PSW grout: the American Nuclear Society (ANS) 16.1 intermittent replacement leach test and a static leach test. Grout produced from both synthetic and real PSW showed low leach rates for the trace metal constituents and most of the waste radionuclides. Many of the spiked trace metals and radionuclides were not detected in any leachates. None of the effluents contained measurable quantities of 137 Cs, 60 Co, 54 Mn, 109 Cd, 51 Cr, 210 Pb, 203 Hg, or As. For those trace species with detectable leach rates, 125 I appeared to have the greatest leach rate, followed by 99 Tc, 75 Se, and finally U, 14 C, and 110m Ag. Leach rates for nitrate are between those for I and Tc, but there is much scatter in the nitrate data because of the very low nitrate inventory. 32 refs., 6 figs., 15 tabs

  3. A distribution-free test for anomalous gamma-ray spectra

    International Nuclear Information System (INIS)

    Chan, Kung-sik; Li, Jinzheng; Eichinger, William; Bai, Er-Wei

    2014-01-01

    Gamma-ray spectra are increasingly acquired in monitoring cross-border traffic, or in an area search for lost or orphan special nuclear material (SNM). The signal in such data is generally weak, resulting in poorly resolved spectra, thereby making it hard to detect the presence of SNM. We develop a new test for detecting anomalous spectra by characterizing the complete shape change in a spectrum from background radiation; the proposed method may serve as a tripwire for routine screening for SNM. We show that, with increasing detection time, the limiting distribution of the test is given by some functional of the Brownian bridge. The efficacy of the proposed method is illustrated by simulations. - Highlights: • We develop a new non-parametric test for detecting anomalous gamma-ray spectra. • The proposed test has good empirical power for detecting weak signals. • It can serve as an effective tripwire for invoking more thorough scrutiny of the source

  4. Analysis of design floor response spectra and testing of the electrical systems

    International Nuclear Information System (INIS)

    Ambriashvili, Y.

    1996-01-01

    This report covers the following activities as foreseen according to the working plan of 'Atmoenergoproject': analysis of calculated floor response spectra used during the design of Kozloduy NPP and comparison with other spectra recommended for this NPP; analysis of floor response spectrum for the most important systems (reactor, main coolant loop, electrical systems); tests of main electrical systems and analysis of the results on seismic stability of those systems. Results of the response spectra analysis are given, some of the electrical systems are identified by the Kozloduy authorities to be analyzed in future according to the results of the test on seismicity

  5. Leach tests on grouts made with actual and trace metal-spiked synthetic phosphate/sulfate waste

    Energy Technology Data Exchange (ETDEWEB)

    Serne, R.J.; Martin, W.J.; LeGore, V.L.; Lindenmeier, C.W.; McLaurine, S.B.; Martin, P.F.C.; Lokken, R.O.

    1989-10-01

    Pacific Northwest Laboratory conducted experiments to produce empirical leach rate data for phosphate-sulfate waste (PSW) grout. Effective diffusivities were measured for various radionuclides ({sup 90}Sr, {sup 99}Tc, {sup 14}C, {sup 129}I, {sup 137}Cs, {sup 60}Co, {sup 54}Mn, and U), stable major components (NO{sub 3}{sup {minus}}, SO{sub 4}{sup 2{minus}}, H{sub 3}BO{sub 3}, K and Na) and the trace constituents Ag, As, Cd, Hg, Pb, and Se. Two types of leach tests were used on samples of actual PSW grout and synthetic PSW grout: the American Nuclear Society (ANS) 16.1 intermittent replacement leach test and a static leach test. Grout produced from both synthetic and real PSW showed low leach rates for the trace metal constituents and most of the waste radionuclides. Many of the spiked trace metals and radionuclides were not detected in any leachates. None of the effluents contained measurable quantities of {sup 137}Cs, {sup 60}Co, {sup 54}Mn, {sup 109}Cd, {sup 51}Cr, {sup 210}Pb, {sup 203}Hg, or As. For those trace species with detectable leach rates, {sup 125}I appeared to have the greatest leach rate, followed by {sup 99}Tc, {sup 75}Se, and finally U, {sup 14}C, and {sup 110m}Ag. Leach rates for nitrate are between those for I and Tc, but there is much scatter in the nitrate data because of the very low nitrate inventory. 32 refs., 6 figs., 15 tabs.

  6. Quantitative Evaluation of gamma-Spectrum Analysis Methods using IAEA Test Spectra

    DEFF Research Database (Denmark)

    Nielsen, Sven Poul

    1982-01-01

    A description is given of a γ-spectrum analysis method based on nonlinear least-squares fitting. The quality of the method is investigated by using statistical tests on the results from analyses of IAEA test spectra. By applying an empirical correction factor of 0.75 to the calculated peak-area u...

  7. Ecotoxicological assessment of the pharmaceutical compound Triclosan to freshwater invertebrates with emphasis to spiked sediment tests; Avaliacao ecotoxicologica do farmaco Triclosan para invertebrados de agua doce com enfase em ensaios com sedimento marcado ('spiked sediment')

    Energy Technology Data Exchange (ETDEWEB)

    Pusceddu, Fabio Hermes

    2009-07-01

    The increasing of Pharmaceutical and Personal Care Products (PPCPs) occurrence in the aquatic environment cause adverse effects on the human health and aquatic communities. The environmental risk of the PPCPs associated with the possibility of synergic effects between PCPPs and the increase of the use of synthetic organic compounds, unchained a great concern on the toxic potential to biota aquatic. Triclosan (5-chloro-2-(2,4-dichlorophenoxy)-phenol) is a pharmaceutical compound widely used due your antibacterial mechanism effect, found in at least 932 products such as shampoos, toilet soaps, deodorants, lotions, toothpaste, detergents, socks and underwear, among others. Currently, studies about the Triclosan toxicity in the water and, mainly in the sediment, are poorly. We have the knowledge that the photodegradation of this product results into dichlorodibenzo-p-dioxin, and now it has great discussion on environmental agencies, like EPA, about the release or restriction of this product. The aim of this work is to assess the effects of Triclosan on mortality of insect larvae Chironomus xanthus and mortality and reproduction inhibition of microcrustacea Ceriodaphnia dubia exposed to Triclosan spiked sediments based on standard methods EPA and OECD. The EC50;96H obtained on acute toxicity tests with C. xanthus was 45,26 mg.Kg{sup -1}. The chronic toxicity tests with C. dubia using spiked sediments were performed following the procedure in Burton and MacPherson (1995). A no-observed-effect concentrations and lowest-observed-effect concentration were 5,78 e 6,94 mg.Kg{sup -1}, respectively. (author)

  8. The 2002 IAEA test spectra for low-level {gamma}-ray spectrometry software

    Energy Technology Data Exchange (ETDEWEB)

    Los Arcos, Jose Mo [Laboratorio de Patrones Nacionales, Asociado al C.E.M., CIEMAT, Avda. Complutense 22, Madrid 28040 (Spain); Blaauw, Menno [Interfaculty Reactor Institute, University of Technology Delft, Mekelweg 15, 2629 JB Delft (Netherlands)]. E-mail: blaauw@iri.tudelft.nl; Fazinic, Stjepko [International Atomic Energy Agency, P.O. Box 100, Wagramerstrasse 5, A-1400 Vienna (Austria); Kolotov, Vladimir P. [Institute of Geochemistry and Analytical Chemistry of Russian Academy of Sciences, Kosygin str. 19, Moscow B-334, 117975 (Russian Federation)

    2005-01-01

    Test spectra for low-level {gamma}-ray spectrometry were acquired and made available to the general public at www.iri.tudelft.nl/{approx}rc/fmr/iaea2002. As opposed to the 1995 test spectra, where reference values were made available only for the peak energies and areas, the new set of test spectra was acquired with certified sources, so that the reference values are radionuclide activities. Two well-defined detection geometries were employed: a 500ml Marinelli beaker on a 33% relative efficiency HPGe detector; and a 100ml pillbox on a 96% HPGe detector. The complete set addresses various issues that are especially important in low-level gamma-ray spectrometry, i.e. determination of efficiency curves in the presence of coincidence summing, differences in source geometry and density between standard and sample, poor statistics, shielding of background by the sample, use of low X- or {gamma}-ray energies and the assumption of secular equilibrium of the natural radionuclides. The set was used in an IAEA intercomparison of software packages in December, 2002, reported on in a separate paper.

  9. Deep Spiking Networks

    NARCIS (Netherlands)

    O'Connor, P.; Welling, M.

    2016-01-01

    We introduce an algorithm to do backpropagation on a spiking network. Our network is "spiking" in the sense that our neurons accumulate their activation into a potential over time, and only send out a signal (a "spike") when this potential crosses a threshold and the neuron is reset. Neurons only

  10. Serial Spike Time Correlations Affect Probability Distribution of Joint Spike Events.

    Science.gov (United States)

    Shahi, Mina; van Vreeswijk, Carl; Pipa, Gordon

    2016-01-01

    Detecting the existence of temporally coordinated spiking activity, and its role in information processing in the cortex, has remained a major challenge for neuroscience research. Different methods and approaches have been suggested to test whether the observed synchronized events are significantly different from those expected by chance. To analyze the simultaneous spike trains for precise spike correlation, these methods typically model the spike trains as a Poisson process implying that the generation of each spike is independent of all the other spikes. However, studies have shown that neural spike trains exhibit dependence among spike sequences, such as the absolute and relative refractory periods which govern the spike probability of the oncoming action potential based on the time of the last spike, or the bursting behavior, which is characterized by short epochs of rapid action potentials, followed by longer episodes of silence. Here we investigate non-renewal processes with the inter-spike interval distribution model that incorporates spike-history dependence of individual neurons. For that, we use the Monte Carlo method to estimate the full shape of the coincidence count distribution and to generate false positives for coincidence detection. The results show that compared to the distributions based on homogeneous Poisson processes, and also non-Poisson processes, the width of the distribution of joint spike events changes. Non-renewal processes can lead to both heavy tailed or narrow coincidence distribution. We conclude that small differences in the exact autostructure of the point process can cause large differences in the width of a coincidence distribution. Therefore, manipulations of the autostructure for the estimation of significance of joint spike events seem to be inadequate.

  11. Stochastic Variational Learning in Recurrent Spiking Networks

    Directory of Open Access Journals (Sweden)

    Danilo eJimenez Rezende

    2014-04-01

    Full Text Available The ability to learn and perform statistical inference with biologically plausible recurrent network of spiking neurons is an important step towards understanding perception and reasoning. Here we derive and investigate a new learning rule for recurrent spiking networks with hidden neurons, combining principles from variational learning and reinforcement learning. Our network defines a generative model over spike train histories and the derived learning rule has the form of a local Spike Timing Dependent Plasticity rule modulated by global factors (neuromodulators conveying information about ``novelty on a statistically rigorous ground.Simulations show that our model is able to learn bothstationary and non-stationary patterns of spike trains.We also propose one experiment that could potentially be performed with animals in order to test the dynamics of the predicted novelty signal.

  12. Calculation of neutron spectra produced in neutron generator target: Code testing.

    Science.gov (United States)

    Gaganov, V V

    2018-03-01

    DT-neutron spectra calculated using the SRIANG code was benchmarked against the results obtained by widely used Monte Carlo codes: PROFIL, SHORIN, TARGET, ENEA-JSI, MCUNED, DDT and NEUSDESC. The comparison of the spectra obtained by different codes confirmed the correctness of SRIANG calculations. The cross-checking of the compared spectra revealed some systematic features and possible errors of analysed codes. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. Performance of a nuclide identification of HYPERGAM on the IAEA 2002 test spectra

    International Nuclear Information System (INIS)

    Park, B. G.; Jung, N. S.; Kim, J. H.; Choi, H. D.; Park, C. S.

    2010-01-01

    An important part of the γ-ray spectrum analysis software is the ability to identify radionuclides on the spectrum, and to determine activity of each radionuclide. Rapid determination and a low number of missing and false hit are required to the γ-ray spectrum analysis software to be useful. HyperGam has been developed to analyze an HPGe γ-ray spectrum by Applied Nuclear Physics Group in Seoul National University. Through a series of subsequent studies, the on-line analysis as well as the off-line analysis was possible. In addition, the automatic algorithm of nuclide identification has been developed to identify the peaks on the spectrum considering with yield, efficiency, energy and peak area of the γ-ray line from radionuclide. In this study, the performance of the nuclide identification of HyperGam is tested by using the IAEA 2002 set of test spectra and is compared to the well-known γ-ray spectrum analysis software

  14. A field test of the effect of spiked ivermectin concentrations on the biodiversity of coprophagous dung insects in Switzerland.

    Science.gov (United States)

    Jochmann, Ralf; Lipkow, Erhard; Blanckenhorn, Wolf U

    2016-08-01

    Veterinary medical product residues can cause severe damage in the dung ecosystem. Depending on the manner of application and the time after treatment, the excreted concentration of a given pharmaceutical varies. The popular anthelmintic drug ivermectin can be applied to livestock in several different ways and is fecally excreted over a period of days to months after application. In a field experiment replicated in summer and autumn, the authors mixed 6 ivermectin concentrations plus a null control into fresh cow dung to assess the reaction of the dung insect community. Taxon richness of the insect dung fauna emerging from the dung, but not Hill diversity ((1) D) or the total number of individuals (abundance), decreased as ivermectin concentration increased. Corresponding declines in the number of emerging insects were found for most larger brachyceran flies and hymenopteran parasitoids, but not for most smaller nematoceran flies or beetles (except Hydrophilidae). Parallel pitfall traps recovered all major dung organism groups that emerged from the experimental dung, although at times in vastly different numbers. Ivermectin generally did not change the attractiveness of dung: differences in emergence therefore reflect differences in survival of coprophagous offspring of colonizing insects. Because sample size was limited to 6 replicates, the authors generally recommend more than 10 (seasonal) replicates and also testing higher concentrations than used in the present study as positive controls in future studies. Results accord with parallel experiments in which the substance was applied and passed through the cow's digestive system. In principle, therefore, the authors' experimental design is suitable for such higher-tier field tests of the response of the entire dung community to pharmaceutical residues, at least for ivermectin. Environ Toxicol Chem 2016;35:1947-1952. © 2015 SETAC. © 2015 SETAC.

  15. Factors correlated with volleyball spike velocity.

    Science.gov (United States)

    Forthomme, Bénédicte; Croisier, Jean-Louis; Ciccarone, Guido; Crielaard, Jean-Michel; Cloes, Marc

    2005-10-01

    Spike effectiveness represents a determining element in volleyball. To compete at a high level, the player must, in particular, produce a spike characterized by a high ball velocity. Some muscular and physical features could influence ball velocity during the volleyball spike. Descriptive laboratory study. A total of 19 male volleyball players from the 2 highest Belgian national divisions underwent an isokinetic assessment of the dominant shoulder and elbow. Ball velocity performance (radar gun) during a spike test, morphological feature, and jump capacity (ergo jump) of the player were measured. We tested the relationship between the isokinetic parameters or physical features and field performances represented by spike velocity. We also compared first-division and second-division player data. Spike velocity correlated significantly with strength performance of the dominant shoulder (internal rotators) and of the dominant elbow (flexors and extensors) in the concentric mode. Negative correlations were established with the concentric external rotator on internal rotator ratio at 400 deg/s and with the mixed ratio (external rotator at 60 deg/s in the eccentric mode on internal rotator at 240 deg/s in the concentric mode). Positive correlations appeared with both the volleyball players' jump capacity and body mass index. First-division players differed from second-division players by higher ball velocity and increased jump capacity. Some specific strength and physical characteristics correlated significantly with spike performance in high-level volleyball practice. Our results could provide useful information for training management and propose some reflections on injury prevention.

  16. Tests of simulated Gaia BP/RP spectra with LDS (Low Dispersion Spectroscopy) photographic sky surveys

    International Nuclear Information System (INIS)

    Hudec, René; Hudec, Lukáš

    2011-01-01

    The LDS (Low Dispersion Spectroscopy) performed in various extended sky surveys with optical telescopes using objective prism and photographic plates offers an interesting opportunity to test simulated low-dispersion spectra for the Gaia BP/RP photometers and to compare them with real data, especially for objects with strong emission lines. We present a review of astrophysics with LDS performed in the past, as well as an overview of existing extended sky surveys (with photographic plates) providing LDS data. Some of them provide almost complete coverage of the northern or southern hemisphere (e.g. the Northern and Southern Mt Wilson - Michigan Hα surveys or the German La Paz Bolivia Southern Spectral Sky Survey). We show examples of these data and discuss a comparison of existing LDS plate data with expected/simulated Gaia BP/RP data. We show examples of real data for objects with very strong and wide emission features confirming that such features will be detectable with Gaia BP/RP. We also discuss the importance of Gaia RP/BP low-dispersion spectroscopy for astrophysical studies.

  17. Characterization of 200-UP-1 Aquifer Sediments and Results of Sorption-Desorption Tests Using Spiked Uncontaminated Groundwater

    Energy Technology Data Exchange (ETDEWEB)

    Um, Wooyong; Serne, R JEFFREY.; Bjornstad, Bruce N.; Schaef, Herbert T.; Brown, Christopher F.; Legore, Virginia L.; Geiszler, Keith N.; Baum, Steven R.; Valenta, Michelle M.; Kutnyakov, Igor V.; Vickerman, Tanya S.; Lindberg, Michael J.

    2005-11-16

    increasing concentrations of carbonate up to a point. Then as carbonate and calcium concentrations in the groundwater reach values that exceed the solubility limit for the mineral calcite there is a slight increase in U(VI) Kd likely caused by uranium co-precipitation with the fresh calcite. If remediation of the UP-1 groundwater plume is required, such as pump and treat, it is recommended that the aquifer be treated with chemicals to increase pH and alkalinity and decrease dissolved calcium and magnesium [so that the precipitation of calcite is prevented]. Alternative methods to immobilize the uranium in place might be more effective than trying to remove the uranium by pump and treat. Unfortunately, no aquifer sediments were obtained that contained enough Hanford generated uranium to perform quantitative desorption tests germane to the UP-1 plume remediation issue. Recommended Kd values that should be used for risk predictions for the UP-1 groundwater plume traveling through the lithologies within the aquifer present at the UP-1 (and by proxy ZP-1) operable units were provided. The recommended values Kd values are chosen to include some conservatism (lower values are emphasized from the available range) as is standard risk assessment practice. In general, desorption Kd values for aged contaminated sediments can be larger than Kd values determined in short-term laboratory experiments. To accommodate the potential for desorption hysteresis and other complications, a second suite of uranium desorption Kd values were provided to be used to estimate removal of uranium by pump and treat techniques.

  18. Control method for multi-input multi-output non-Gaussian random vibration test with cross spectra consideration

    Directory of Open Access Journals (Sweden)

    Ronghui ZHENG

    2017-12-01

    Full Text Available A control method for Multi-Input Multi-Output (MIMO non-Gaussian random vibration test with cross spectra consideration is proposed in the paper. The aim of the proposed control method is to replicate the specified references composed of auto spectral densities, cross spectral densities and kurtoses on the test article in the laboratory. It is found that the cross spectral densities will bring intractable coupling problems and induce difficulty for the control of the multi-output kurtoses. Hence, a sequential phase modification method is put forward to solve the coupling problems in multi-input multi-output non-Gaussian random vibration test. To achieve the specified responses, an improved zero memory nonlinear transformation is utilized first to modify the Fourier phases of the signals with sequential phase modification method to obtain one frame reference response signals which satisfy the reference spectra and reference kurtoses. Then, an inverse system method is used in frequency domain to obtain the continuous stationary drive signals. At the same time, the matrix power control algorithm is utilized to control the spectra and kurtoses of the response signals further. At the end of the paper, a simulation example with a cantilever beam and a vibration shaker test are implemented and the results support the proposed method very well. Keywords: Cross spectra, Kurtosis control, Multi-input multi-output, Non-Gaussian, Random vibration test

  19. Spectral components of cytosolic [Ca2+] spiking in neurons

    DEFF Research Database (Denmark)

    Kardos, J; Szilágyi, N; Juhász, G

    1998-01-01

    We show here, by means of evolutionary spectral analysis and synthesis of cytosolic Ca2+ ([Ca2+]c) spiking observed at the single cell level using digital imaging fluorescence microscopy of fura-2-loaded mouse cerebellar granule cells in culture, that [Ca2+]c spiking can be resolved into evolutio......We show here, by means of evolutionary spectral analysis and synthesis of cytosolic Ca2+ ([Ca2+]c) spiking observed at the single cell level using digital imaging fluorescence microscopy of fura-2-loaded mouse cerebellar granule cells in culture, that [Ca2+]c spiking can be resolved...... into evolutionary spectra of a characteristic set of frequencies. Non-delayed small spikes on top of sustained [Ca2+]c were synthesized by a main component frequency, 0.132+/-0.012 Hz, showing its maximal amplitude in phase with the start of depolarization (25 mM KCI) combined with caffeine (10 mM) application...

  20. The variational spiked oscillator

    International Nuclear Information System (INIS)

    Aguilera-Navarro, V.C.; Ullah, N.

    1992-08-01

    A variational analysis of the spiked harmonic oscillator Hamiltonian -d 2 / d x 2 + x 2 + δ/ x 5/2 , δ > 0, is reported in this work. A trial function satisfying Dirichlet boundary conditions is suggested. The results are excellent for a large range of values of the coupling parameter. (author)

  1. Training Deep Spiking Neural Networks Using Backpropagation.

    Science.gov (United States)

    Lee, Jun Haeng; Delbruck, Tobi; Pfeiffer, Michael

    2016-01-01

    Deep spiking neural networks (SNNs) hold the potential for improving the latency and energy efficiency of deep neural networks through data-driven event-based computation. However, training such networks is difficult due to the non-differentiable nature of spike events. In this paper, we introduce a novel technique, which treats the membrane potentials of spiking neurons as differentiable signals, where discontinuities at spike times are considered as noise. This enables an error backpropagation mechanism for deep SNNs that follows the same principles as in conventional deep networks, but works directly on spike signals and membrane potentials. Compared with previous methods relying on indirect training and conversion, our technique has the potential to capture the statistics of spikes more precisely. We evaluate the proposed framework on artificially generated events from the original MNIST handwritten digit benchmark, and also on the N-MNIST benchmark recorded with an event-based dynamic vision sensor, in which the proposed method reduces the error rate by a factor of more than three compared to the best previous SNN, and also achieves a higher accuracy than a conventional convolutional neural network (CNN) trained and tested on the same data. We demonstrate in the context of the MNIST task that thanks to their event-driven operation, deep SNNs (both fully connected and convolutional) trained with our method achieve accuracy equivalent with conventional neural networks. In the N-MNIST example, equivalent accuracy is achieved with about five times fewer computational operations.

  2. Testing the Planet-Metallicity Correlation in M-dwarfs with Gemini GNIRS Spectra

    Science.gov (United States)

    Hobson, M. J.; Jofré, E.; García, L.; Petrucci, R.; Gómez, M.

    2018-04-01

    While the planet-metallicity correlation for FGK main-sequence stars hosting giant planets is well established, it is less clear for M-dwarf stars. We determine stellar parameters and metallicities for 16 M-dwarf stars, 11 of which host planets, with near-infrared spectra from the Gemini Near-Infrared Spectrograph (GNIRS). We find that M-dwarfs with planets are preferentially metal-rich compared to those without planets. This result is supported by the analysis of a larger catalogue of 18 M stars with planets and 213 M stars without known planets T15, and demonstrates the utility of GNIRS spectra to obtain reliable stellar parameters of M stars. We also find that M dwarfs with giant planets are preferentially more metallic than those with low-mass planets, in agreement with previous results for solar-type stars. These results favor the core accretion model of planetary formation.

  3. Response Features Determining Spike Times

    Directory of Open Access Journals (Sweden)

    Barry J. Richmond

    1999-01-01

    redundant with that carried by the coarse structure. Thus, the existence of precisely timed spike patterns carrying stimulus-related information does not imply control of spike timing at precise time scales.

  4. SPITZER IRS SPECTRA OF LUMINOUS 8 μm SOURCES IN THE LARGE MAGELLANIC CLOUD: TESTING COLOR-BASED CLASSIFICATIONS

    International Nuclear Information System (INIS)

    Buchanan, Catherine L.; Kastner, Joel H.; Hrivnak, Bruce J.; Sahai, Raghvendra

    2009-01-01

    We present archival Spitzer Infrared Spectrograph (IRS) spectra of 19 luminous 8 μm selected sources in the Large Magellanic Cloud (LMC). The object classes derived from these spectra and from an additional 24 spectra in the literature are compared with classifications based on Two Micron All Sky Survey (2MASS)/MSX (J, H, K, and 8 μm) colors in order to test the 'JHK8' (Kastner et al.) classification scheme. The IRS spectra confirm the classifications of 22 of the 31 sources that can be classified under the JHK8 system. The spectroscopic classification of 12 objects that were unclassifiable in the JHK8 scheme allow us to characterize regions of the color-color diagrams that previously lacked spectroscopic verification, enabling refinements to the JHK8 classification system. The results of these new classifications are consistent with previous results concerning the identification of the most infrared-luminous objects in the LMC. In particular, while the IRS spectra reveal several new examples of asymptotic giant branch (AGB) stars with O-rich envelopes, such objects are still far outnumbered by carbon stars (C-rich AGB stars). We show that Spitzer IRAC/MIPS color-color diagrams provide improved discrimination between red supergiants and oxygen-rich and carbon-rich AGB stars relative to those based on 2MASS/MSX colors. These diagrams will enable the most luminous IR sources in Local Group galaxies to be classified with high confidence based on their Spitzer colors. Such characterizations of stellar populations will continue to be possible during Spitzer's warm mission through the use of IRAC [3.6]-[4.5] and 2MASS colors.

  5. Spiking neural network for recognizing spatiotemporal sequences of spikes

    International Nuclear Information System (INIS)

    Jin, Dezhe Z.

    2004-01-01

    Sensory neurons in many brain areas spike with precise timing to stimuli with temporal structures, and encode temporally complex stimuli into spatiotemporal spikes. How the downstream neurons read out such neural code is an important unsolved problem. In this paper, we describe a decoding scheme using a spiking recurrent neural network. The network consists of excitatory neurons that form a synfire chain, and two globally inhibitory interneurons of different types that provide delayed feedforward and fast feedback inhibition, respectively. The network signals recognition of a specific spatiotemporal sequence when the last excitatory neuron down the synfire chain spikes, which happens if and only if that sequence was present in the input spike stream. The recognition scheme is invariant to variations in the intervals between input spikes within some range. The computation of the network can be mapped into that of a finite state machine. Our network provides a simple way to decode spatiotemporal spikes with diverse types of neurons

  6. Epileptiform spike detection via convolutional neural networks

    DEFF Research Database (Denmark)

    Johansen, Alexander Rosenberg; Jin, Jing; Maszczyk, Tomasz

    2016-01-01

    The EEG of epileptic patients often contains sharp waveforms called "spikes", occurring between seizures. Detecting such spikes is crucial for diagnosing epilepsy. In this paper, we develop a convolutional neural network (CNN) for detecting spikes in EEG of epileptic patients in an automated...... fashion. The CNN has a convolutional architecture with filters of various sizes applied to the input layer, leaky ReLUs as activation functions, and a sigmoid output layer. Balanced mini-batches were applied to handle the imbalance in the data set. Leave-one-patient-out cross-validation was carried out...... to test the CNN and benchmark models on EEG data of five epilepsy patients. We achieved 0.947 AUC for the CNN, while the best performing benchmark model, Support Vector Machines with Gaussian kernel, achieved an AUC of 0.912....

  7. Zero crossing and ratio spectra derivative spectrophotometry for the dissolution tests of amlodipine and perindopril in their fixed dose formulations

    Directory of Open Access Journals (Sweden)

    Maczka Paulina

    2014-06-01

    Full Text Available Dissolution tests of amlodipine and perindopril from their fixed dose formulations were performed in 900 mL of phosphate buffer of pH 5.5 at 37°C using the paddle apparatus. Then, two simple and rapid derivative spectrophotometric methods were used for the quantitative measurements of amlodipine and perindopril. The first method was zero crossing first derivative spectrophotometry in which measuring of amplitudes at 253 nm for amlodipine and 229 nm for perindopril were used. The second method was ratio derivative spectrophotometry in which spectra of amlodipine over the linearity range were divided by one selected standard spectrum of perindopril and then amplitudes at 242 nm were measured. Similarly, spectra of perindopril were divided by one selected standard spectrum of amlodipine and then amplitudes at 298 nm were measured. Both of the methods were validated to meet official requirements and were demonstrated to be selective, precise and accurate. Since there is no official monograph for these drugs in binary formulations, the dissolution tests and quantification procedure presented here can be used as a quality control test for amlodipine and perindopril in respective dosage forms.

  8. Content uniformity and dissolution tests of triplicate mixtures by a double divisor-ratio spectra derivative method.

    Science.gov (United States)

    Markopoulou, Catherine K; Malliou, Eleftheria T; Koundourellis, John E

    2005-09-01

    The use of a UV double divisor-ratio spectra derivative calibration for the simultaneous analysis of synthetic samples and commercial tablet preparations without prior separation is proposed. The method was successfully applied to quantify three ternary mixtures, chlorpheniramine maleate and caffeine combined with paracetamol or acetylsalicylic acid and a mixture of acetylsalicylic acid combined with paracetamol and caffeine, using the information in the absorption spectra of appropriate solutions. Beer's law was obeyed in the concentration range of 0.84-4.21 microg/ml for chlorpheniramine maleate, 1.60-15.96 microg/ml for caffeine, 2.0-20.0 microg/ml for acetylsalicylic acid and 1.58-15.93 microg/ml for paracetamol. The whole procedure was applied to synthetic mixtures of pure drugs as well as to commercial preparations (Algon) by using content uniformity and dissolution tests (USP 24) and was found to be precise and reproducible. According to the dissolution profile test more than 84% of paracetamol and caffeine were dissolved within 20 min. Acetylsalicylic acid dissolved more slowly, taking about 45-60 min to dissolve completely. A chemometric method partial least squares (PLS) and a HPLC method were also employed to evaluate the same mixtures. The results of the proposed method were in excellent agreement with those obtained from PLS and HPLC methods and can be satisfactorily used for routine analysis of multicomponent dosage forms.

  9. Spike sorting for polytrodes: a divide and conquer approach

    Directory of Open Access Journals (Sweden)

    Nicholas V. Swindale

    2014-02-01

    Full Text Available In order to determine patterns of neural activity, spike signals recorded by extracellular electrodes have to be clustered (sorted with the aim of ensuring that each cluster represents all the spikes generated by an individual neuron. Many methods for spike sorting have been proposed but few are easily applicable to recordings from polytrodes which may have 16 or more recording sites. As with tetrodes, these are spaced sufficiently closely that signals from single neurons will usually be recorded on several adjacent sites. Although this offers a better chance of distinguishing neurons with similarly shaped spikes, sorting is difficult in such cases because of the high dimensionality of the space in which the signals must be classified. This report details a method for spike sorting based on a divide and conquer approach. Clusters are initially formed by assigning each event to the channel on which it is largest. Each channel-based cluster is then sub-divided into as many distinct clusters as possible. These are then recombined on the basis of pairwise tests into a final set of clusters. Pairwise tests are also performed to establish how distinct each cluster is from the others. A modified gradient ascent clustering (GAC algorithm is used to do the clustering. The method can sort spikes with minimal user input in times comparable to real time for recordings lasting up to 45 minutes. Our results illustrate some of the difficulties inherent in spike sorting, including changes in spike shape over time. We show that some physiologically distinct units may have very similar spike shapes. We show that RMS measures of spike shape similarity are not sensitive enough to discriminate clusters that can otherwise be separated by principal components analysis. Hence spike sorting based on least-squares matching to templates may be unreliable. Our methods should be applicable to tetrodes and scaleable to larger multi-electrode arrays (MEAs.

  10. Spike sorting for polytrodes: a divide and conquer approach.

    Science.gov (United States)

    Swindale, Nicholas V; Spacek, Martin A

    2014-01-01

    In order to determine patterns of neural activity, spike signals recorded by extracellular electrodes have to be clustered (sorted) with the aim of ensuring that each cluster represents all the spikes generated by an individual neuron. Many methods for spike sorting have been proposed but few are easily applicable to recordings from polytrodes which may have 16 or more recording sites. As with tetrodes, these are spaced sufficiently closely that signals from single neurons will usually be recorded on several adjacent sites. Although this offers a better chance of distinguishing neurons with similarly shaped spikes, sorting is difficult in such cases because of the high dimensionality of the space in which the signals must be classified. This report details a method for spike sorting based on a divide and conquer approach. Clusters are initially formed by assigning each event to the channel on which it is largest. Each channel-based cluster is then sub-divided into as many distinct clusters as possible. These are then recombined on the basis of pairwise tests into a final set of clusters. Pairwise tests are also performed to establish how distinct each cluster is from the others. A modified gradient ascent clustering (GAC) algorithm is used to do the clustering. The method can sort spikes with minimal user input in times comparable to real time for recordings lasting up to 45 min. Our results illustrate some of the difficulties inherent in spike sorting, including changes in spike shape over time. We show that some physiologically distinct units may have very similar spike shapes. We show that RMS measures of spike shape similarity are not sensitive enough to discriminate clusters that can otherwise be separated by principal components analysis (PCA). Hence spike sorting based on least-squares matching to templates may be unreliable. Our methods should be applicable to tetrodes and scalable to larger multi-electrode arrays (MEAs).

  11. Testing of a Code for the Calculation of Spectra of Neutrons Produced in a Target of a Neutron Generator

    Science.gov (United States)

    Gaganov, V. V.

    2017-12-01

    The correctness of calculations performed with the SRIANG code for modeling the spectra of DT neutrons is estimated by comparing the obtained spectra to the results of calculations carried out with five different codes based on the Monte Carlo method.

  12. EGFR T790M mutation testing of non-small cell lung cancer tissue and blood samples artificially spiked with circulating cell-free tumor DNA: results of a round robin trial.

    Science.gov (United States)

    Fassunke, Jana; Ihle, Michaela Angelika; Lenze, Dido; Lehmann, Annika; Hummel, Michael; Vollbrecht, Claudia; Penzel, Roland; Volckmar, Anna-Lena; Stenzinger, Albrecht; Endris, Volker; Jung, Andreas; Lehmann, Ulrich; Zeugner, Silke; Baretton, Gustavo; Kreipe, Hans; Schirmacher, Peter; Kirchner, Thomas; Dietel, Manfred; Büttner, Reinhard; Merkelbach-Bruse, Sabine

    2017-10-01

    The European Commision (EC) recently approved osimertinib for the treatment of adult patients with locally advanced or metastatic non-small-cell lung cancer (NSCLC) harboring EGFR T790M mutations. Besides tissue-based testing, blood samples containing cell-free circulating tumor DNA (ctDNA) can be used to interrogate T790M status. Herein, we describe the conditions and results of a round robin trial (RRT) for T790M mutation testing in NSCLC tissue specimens and peripheral blood samples spiked with cell line DNA mimicking tumor-derived ctDNA. The underlying objectives of this two-staged external quality assessment (EQA) approach were (a) to evaluate the accuracy of T790M mutations testing across multiple centers and (b) to investigate if a liquid biopsy-based testing for T790M mutations in spiked blood samples is feasible in routine diagnostic. Based on a successfully completed internal phase I RRT, an open RRT for EGFR T790M mutation testing in tumor tissue and blood samples was initiated. In total, 48 pathology centers participated in the EQA. Of these, 47 (97.9%) centers submitted their analyses within the pre-defined time frame and 44 (tissue), respectively, 40 (plasma) successfully passed the test. The overall success rates in the RRT phase II were 91.7% (tissue) and 83.3% (blood), respectively. Thirty-eight out of 48 participants (79.2%) successfully passed both parts of the RRT. The RRT for blood-based EGFR testing initiated in Germany is, to the best of our knowledge, the first of his kind in Europe. In summary, our results demonstrate that blood-based genotyping for EGFR resistance mutations can be successfully integrated in routine molecular diagnostics complementing the array of molecular methods already available at pathology centers in Germany.

  13. Prediction of Pseudo relative velocity response spectra at Yucca Mountain for underground nuclear explosions conducted in the Pahute Mesa testing area at the Nevada testing site

    International Nuclear Information System (INIS)

    Phillips, J.S.

    1991-12-01

    The Yucca Mountain Site Characterization Project (YMP), managed by the Office of Geologic Disposal of the Office of Civilian Radioactive Waste Management of the US Department of Energy, is examining the feasibility of siting a repository for commercial, high-level nuclear wastes at Yucca Mountain on and adjacent to the Nevada Test Site (NTS). This work, intended to extend our understanding of the ground motion at Yucca Mountain resulting from testing of nuclear weapons on the NTS, was funded by the Yucca Mountain project and the Military Applications Weapons Test Program. This report summarizes one aspect of the weapons test seismic investigations conducted in FY88. Pseudo relative velocity response spectra (PSRV) have been calculated for a large body of surface ground motions generated by underground nuclear explosions. These spectra have been analyzed and fit using multiple linear regression techniques to develop a credible prediction technique for surface PSRVs. In addition, a technique for estimating downhole PSRVs at specific stations is included. A data summary, data analysis, prediction development, prediction evaluation, software summary and FORTRAN listing of the prediction technique are included in this report

  14. Coronavirus spike-receptor interactions

    NARCIS (Netherlands)

    Mou, H.

    2015-01-01

    Coronaviruses cause important diseases in humans and animals. Coronavirus infection starts with the virus binding with its spike proteins to molecules present on the surface of host cells that act as receptors. This spike-receptor interaction is highly specific and determines the virus’ cell, tissue

  15. A robust and biologically plausible spike pattern recognition network.

    Science.gov (United States)

    Larson, Eric; Perrone, Ben P; Sen, Kamal; Billimoria, Cyrus P

    2010-11-17

    The neural mechanisms that enable recognition of spiking patterns in the brain are currently unknown. This is especially relevant in sensory systems, in which the brain has to detect such patterns and recognize relevant stimuli by processing peripheral inputs; in particular, it is unclear how sensory systems can recognize time-varying stimuli by processing spiking activity. Because auditory stimuli are represented by time-varying fluctuations in frequency content, it is useful to consider how such stimuli can be recognized by neural processing. Previous models for sound recognition have used preprocessed or low-level auditory signals as input, but complex natural sounds such as speech are thought to be processed in auditory cortex, and brain regions involved in object recognition in general must deal with the natural variability present in spike trains. Thus, we used neural recordings to investigate how a spike pattern recognition system could deal with the intrinsic variability and diverse response properties of cortical spike trains. We propose a biologically plausible computational spike pattern recognition model that uses an excitatory chain of neurons to spatially preserve the temporal representation of the spike pattern. Using a single neural recording as input, the model can be trained using a spike-timing-dependent plasticity-based learning rule to recognize neural responses to 20 different bird songs with >98% accuracy and can be stimulated to evoke reverse spike pattern playback. Although we test spike train recognition performance in an auditory task, this model can be applied to recognize sufficiently reliable spike patterns from any neuronal system.

  16. The Omega-Infinity Limit of Single Spikes

    CERN Document Server

    Axenides, Minos; Linardopoulos, Georgios

    A new infinite-size limit of strings in RxS2 is presented. The limit is obtained from single spike strings by letting their angular velocity omega become infinite. We derive the energy-momenta relation of omega-infinity single spikes as their linear velocity v-->1 and their angular momentum J-->1. Generally, the v-->1, J-->1 limit of single spikes is singular and has to be excluded from the spectrum and be studied separately. We discover that the dispersion relation of omega-infinity single spikes contains logarithms in the limit J-->1. This result is somewhat surprising, since the logarithmic behavior in the string spectra is typically associated with their motion in non-compact spaces such as AdS. Omega-infinity single spikes seem to completely cover the surface of the 2-sphere they occupy, so that they may essentially be viewed as some sort of "brany strings". A proof of the sphere-filling property of omega-infinity single spikes is given in the appendix.

  17. Spike detection II: automatic, perception-based detection and clustering.

    Science.gov (United States)

    Wilson, S B; Turner, C A; Emerson, R G; Scheuer, M L

    1999-03-01

    We developed perception-based spike detection and clustering algorithms. The detection algorithm employs a novel, multiple monotonic neural network (MMNN). It is tested on two short-duration EEG databases containing 2400 spikes from 50 epilepsy patients and 10 control subjects. Previous studies are compared for database difficulty and reliability and algorithm accuracy. Automatic grouping of spikes via hierarchical clustering (using topology and morphology) is visually compared with hand marked grouping on a single record. The MMNN algorithm is found to operate close to the ability of a human expert while alleviating problems related to overtraining. The hierarchical and hand marked spike groupings are found to be strikingly similar. An automatic detection algorithm need not be as accurate as a human expert to be clinically useful. A user interface that allows the neurologist to quickly delete artifacts and determine whether there are multiple spike generators is sufficient.

  18. Testing Accretion Disk Wind Models of Broad Absorption Line Quasars with SDSS Spectra

    Science.gov (United States)

    Lindgren, Sean; Gabel, Jack

    2017-06-01

    We present an investigation of a large sample of broad absorption line (BAL) quasars (QSO) from the Sloan Digital Sky Survey (SDSS) Data Release 5 (DR5). Properties of the BALs, such as absorption equivalent width, outflow velocities, and depth of BAL, are obtained from analysis by Gibson et al. We perform correlation analysis on these data to test the predictions made by the radiation driven, accretion disk streamline model of Murray and Chiang. We find the CIV BAL maximum velocity and the continuum luminosity are correlated, consistent with radiation driven models. The mean minimum velocity of CIV is lower in low ionization BALs (LoBALs), than highly ionized BALs (HiBALS), suggesting an orientation effect consistent with the Murray and Chiang model. Finally, we find that HiBALs greatly outnumber LoBALs in the general BAL population, supporting prediction of the Murray and Chiang model that HiBALs have a greater global covering factor than LoBALs.

  19. Synchronous spikes are necessary but not sufficient for a synchrony code in populations of spiking neurons.

    Science.gov (United States)

    Grewe, Jan; Kruscha, Alexandra; Lindner, Benjamin; Benda, Jan

    2017-03-07

    Synchronous activity in populations of neurons potentially encodes special stimulus features. Selective readout of either synchronous or asynchronous activity allows formation of two streams of information processing. Theoretical work predicts that such a synchrony code is a fundamental feature of populations of spiking neurons if they operate in specific noise and stimulus regimes. Here we experimentally test the theoretical predictions by quantifying and comparing neuronal response properties in tuberous and ampullary electroreceptor afferents of the weakly electric fish Apteronotus leptorhynchus These related systems show similar levels of synchronous activity, but only in the more irregularly firing tuberous afferents a synchrony code is established, whereas in the more regularly firing ampullary afferents it is not. The mere existence of synchronous activity is thus not sufficient for a synchrony code. Single-cell features such as the irregularity of spiking and the frequency dependence of the neuron's transfer function determine whether synchronous spikes possess a distinct meaning for the encoding of time-dependent signals.

  20. Wavelet analysis of epileptic spikes

    CERN Document Server

    Latka, M; Kozik, A; West, B J; Latka, Miroslaw; Was, Ziemowit; Kozik, Andrzej; West, Bruce J.

    2003-01-01

    Interictal spikes and sharp waves in human EEG are characteristic signatures of epilepsy. These potentials originate as a result of synchronous, pathological discharge of many neurons. The reliable detection of such potentials has been the long standing problem in EEG analysis, especially after long-term monitoring became common in investigation of epileptic patients. The traditional definition of a spike is based on its amplitude, duration, sharpness, and emergence from its background. However, spike detection systems built solely around this definition are not reliable due to the presence of numerous transients and artifacts. We use wavelet transform to analyze the properties of EEG manifestations of epilepsy. We demonstrate that the behavior of wavelet transform of epileptic spikes across scales can constitute the foundation of a relatively simple yet effective detection algorithm.

  1. Estimating short-term synaptic plasticity from pre- and postsynaptic spiking

    Science.gov (United States)

    Malyshev, Aleksey; Stevenson, Ian H.

    2017-01-01

    Short-term synaptic plasticity (STP) critically affects the processing of information in neuronal circuits by reversibly changing the effective strength of connections between neurons on time scales from milliseconds to a few seconds. STP is traditionally studied using intracellular recordings of postsynaptic potentials or currents evoked by presynaptic spikes. However, STP also affects the statistics of postsynaptic spikes. Here we present two model-based approaches for estimating synaptic weights and short-term plasticity from pre- and postsynaptic spike observations alone. We extend a generalized linear model (GLM) that predicts postsynaptic spiking as a function of the observed pre- and postsynaptic spikes and allow the connection strength (coupling term in the GLM) to vary as a function of time based on the history of presynaptic spikes. Our first model assumes that STP follows a Tsodyks-Markram description of vesicle depletion and recovery. In a second model, we introduce a functional description of STP where we estimate the coupling term as a biophysically unrestrained function of the presynaptic inter-spike intervals. To validate the models, we test the accuracy of STP estimation using the spiking of pre- and postsynaptic neurons with known synaptic dynamics. We first test our models using the responses of layer 2/3 pyramidal neurons to simulated presynaptic input with different types of STP, and then use simulated spike trains to examine the effects of spike-frequency adaptation, stochastic vesicle release, spike sorting errors, and common input. We find that, using only spike observations, both model-based methods can accurately reconstruct the time-varying synaptic weights of presynaptic inputs for different types of STP. Our models also capture the differences in postsynaptic spike responses to presynaptic spikes following short vs long inter-spike intervals, similar to results reported for thalamocortical connections. These models may thus be useful

  2. Computing the Absorption and Emission Spectra of 5-Methylcytidine in Different Solvents: A Test-Case for Different Solvation Models.

    Science.gov (United States)

    Martínez-Fernández, L; Pepino, A J; Segarra-Martí, J; Banyasz, A; Garavelli, M; Improta, R

    2016-09-13

    The optical spectra of 5-methylcytidine in three different solvents (tetrahydrofuran, acetonitrile, and water) is measured, showing that both the absorption and the emission maximum in water are significantly blue-shifted (0.08 eV). The absorption spectra are simulated based on CAM-B3LYP/TD-DFT calculations but including solvent effects with three different approaches: (i) a hybrid implicit/explicit full quantum mechanical approach, (ii) a mixed QM/MM static approach, and (iii) a QM/MM method exploiting the structures issuing from molecular dynamics classical simulations. Ab-initio Molecular dynamics simulations based on CAM-B3LYP functionals have also been performed. The adopted approaches all reproduce the main features of the experimental spectra, giving insights on the chemical-physical effects responsible for the solvent shifts in the spectra of 5-methylcytidine and providing the basis for discussing advantages and limitations of the adopted solvation models.

  3. Exploration of the Use of Spiking Detectors to Solve GNC Problems

    Data.gov (United States)

    National Aeronautics and Space Administration — This task is evaluating spiking sensor technology for Guidance, Navigation and Control applications, which includes detailed study, analysis and test for...

  4. X-Ray Emitting GHz-Peaked Spectrum Galaxies: Testing a Dynamical-Radiative Model with Broad-Band Spectra

    Energy Technology Data Exchange (ETDEWEB)

    Ostorero, L.; /Turin U. /INFN, Turin; Moderski, R.; /Warsaw, Copernicus Astron. Ctr. /KIPAC, Menlo Park; Stawarz, L.; /KIPAC, Menlo Park /Jagiellonian U., Astron. Observ.; Diaferio, A.; /Turin U. /INFN, Turin; Kowalska, I.; /Warsaw U. Observ.; Cheung, C.C.; /NASA, Goddard /Naval Research Lab, Wash., D.C.; Kataoka, J.; /Waseda U., RISE; Begelman, M.C.; /JILA, Boulder; Wagner, S.J.; /Heidelberg Observ.

    2010-06-07

    In a dynamical-radiative model we recently developed to describe the physics of compact, GHz-Peaked-Spectrum (GPS) sources, the relativistic jets propagate across the inner, kpc-sized region of the host galaxy, while the electron population of the expanding lobes evolves and emits synchrotron and inverse-Compton (IC) radiation. Interstellar-medium gas clouds engulfed by the expanding lobes, and photoionized by the active nucleus, are responsible for the radio spectral turnover through free-free absorption (FFA) of the synchrotron photons. The model provides a description of the evolution of the GPS spectral energy distribution (SED) with the source expansion, predicting significant and complex high-energy emission, from the X-ray to the {gamma}-ray frequency domain. Here, we test this model with the broad-band SEDs of a sample of eleven X-ray emitting GPS galaxies with Compact-Symmetric-Object (CSO) morphology, and show that: (i) the shape of the radio continuum at frequencies lower than the spectral turnover is indeed well accounted for by the FFA mechanism; (ii) the observed X-ray spectra can be interpreted as non-thermal radiation produced via IC scattering of the local radiation fields off the lobe particles, providing a viable alternative to the thermal, accretion-disk dominated scenario. We also show that the relation between the hydrogen column densities derived from the X-ray (N{sub H}) and radio (N{sub HI}) data of the sources is suggestive of a positive correlation, which, if confirmed by future observations, would provide further support to our scenario of high-energy emitting lobes.

  5. X-ray Emitting GHz-Peaked Spectrum Galaxies: Testing a Dynamical-Radiative Model with Broad-Band Spectra

    International Nuclear Information System (INIS)

    Ostorero, L.; Moderski, R.; Stawarz, L.; Diaferio, A.; Kowalska, I.; Cheung, C.C.; Kataoka, J.; Begelman, M.C.; Wagner, S.J.

    2010-01-01

    In a dynamical-radiative model we recently developed to describe the physics of compact, GHz-Peaked-Spectrum (GPS) sources, the relativistic jets propagate across the inner, kpc-sized region of the host galaxy, while the electron population of the expanding lobes evolves and emits synchrotron and inverse-Compton (IC) radiation. Interstellar-medium gas clouds engulfed by the expanding lobes, and photoionized by the active nucleus, are responsible for the radio spectral turnover through free-free absorption (FFA) of the synchrotron photons. The model provides a description of the evolution of the GPS spectral energy distribution (SED) with the source expansion, predicting significant and complex high-energy emission, from the X-ray to the γ-ray frequency domain. Here, we test this model with the broad-band SEDs of a sample of eleven X-ray emitting GPS galaxies with Compact-Symmetric-Object (CSO) morphology, and show that: (i) the shape of the radio continuum at frequencies lower than the spectral turnover is indeed well accounted for by the FFA mechanism; (ii) the observed X-ray spectra can be interpreted as non-thermal radiation produced via IC scattering of the local radiation fields off the lobe particles, providing a viable alternative to the thermal, accretion-disk dominated scenario. We also show that the relation between the hydrogen column densities derived from the X-ray (N H ) and radio (N HI ) data of the sources is suggestive of a positive correlation, which, if confirmed by future observations, would provide further support to our scenario of high-energy emitting lobes.

  6. Report on the IAEA-CU-2006-05 proficiency test on the determination of 137Cs and 210Pb in spiked soil

    International Nuclear Information System (INIS)

    Shakhashiro, A.; Azeredo, A.M.G. Da F.; Sansone, U.; Kim, C.-K.; Kis-Benedek, G.; Trinkl, A.; Benesch, T.; Schorn, R.; Tarjan, S.

    2006-04-01

    This report summarises the results of a proficiency test conducted within the frame of the agreement between the International Atomic Energy Agency and Hungarian National Food Investigation Institute, as IAEA collaborating Centre in the field of preparation of reference materials. This proficiency test was organized and conducted by the Chemistry Unit of the IAEA's Laboratories located in Seibersdorf (Austria). The soil test material was prepared according to a validated procedure by the Chemistry Unit staff. Full technical details of the proficiency test set of materials are described in the report. 40 test samples (reference materials) were distributed to the participating laboratories in January 2006. The deadline for receiving the results from the participants was set to 20 February 2006. The participating laboratories were requested to analyse the samples employing the methods used in their routine work, so that their performance on the test samples could be directly related to the real performance of the laboratory. Each laboratory was given a confidential code to assure the anonymity of the evaluation results. 8 laboratories from the 8 initially registered reported to the IAEA their results. The analytical results of the participating laboratories were compared with the reference values assigned to the reference materials, and a rating system was applied. The analytical results of both 137 Cs and 210 Pb were satisfactory. The analytical uncertainties associated with the results were, in general, appropriate for the analytes and matrices considered in the current proficiency test. With the advent of 'mutual recognition' on a world wide basis, it is now essential that laboratories participate in proficiency testing schemes that will provide an interpretation and assessment of results which is transparent to the participating laboratory and its 'customer'. New requirements coming into force (ISO/IEC 17025:2005) require that laboratories have to express their

  7. Rotation-vibration interactions in the spectra of polycyclic aromatic hydrocarbons: Quinoline as a test-case species

    International Nuclear Information System (INIS)

    Pirali, O.; Gruet, S.; Kisiel, Z.; Goubet, M.; Martin-Drumel, M. A.; Cuisset, A.; Hindle, F.; Mouret, G.

    2015-01-01

    Polycyclic aromatic hydrocarbons (PAHs) are highly relevant for astrophysics as possible, though controversial, carriers of the unidentified infrared emission bands that are observed in a number of different astronomical objects. In support of radio-astronomical observations, high resolution laboratory spectroscopy has already provided the rotational spectra in the vibrational ground state of several molecules of this type, although the rotational study of their dense infrared (IR) bands has only recently become possible using a limited number of experimental set-ups. To date, all of the rotationally resolved data have concerned unperturbed spectra. We presently report the results of a high resolution study of the three lowest vibrational states of quinoline C 9 H 7 N, an N-bearing naphthalene derivative. While the pure rotational ground state spectrum of quinoline is unperturbed, severe complications appear in the spectra of the ν 45 and ν 44 vibrational modes (located at about 168 cm −1 and 178 cm −1 , respectively). In order to study these effects in detail, we employed three different and complementary experimental techniques: Fourier-transform microwave spectroscopy, millimeter-wave spectroscopy, and Fourier-transform far-infrared spectroscopy with a synchrotron radiation source. Due to the high density of states in the IR spectra of molecules as large as PAHs, perturbations in the rotational spectra of excited states should be ubiquitous. Our study identifies for the first time this effect and provides some insights into an appropriate treatment of such perturbations

  8. Rotation-vibration interactions in the spectra of polycyclic aromatic hydrocarbons: Quinoline as a test-case species

    Science.gov (United States)

    Pirali, O.; Kisiel, Z.; Goubet, M.; Gruet, S.; Martin-Drumel, M. A.; Cuisset, A.; Hindle, F.; Mouret, G.

    2015-03-01

    Polycyclic aromatic hydrocarbons (PAHs) are highly relevant for astrophysics as possible, though controversial, carriers of the unidentified infrared emission bands that are observed in a number of different astronomical objects. In support of radio-astronomical observations, high resolution laboratory spectroscopy has already provided the rotational spectra in the vibrational ground state of several molecules of this type, although the rotational study of their dense infrared (IR) bands has only recently become possible using a limited number of experimental set-ups. To date, all of the rotationally resolved data have concerned unperturbed spectra. We presently report the results of a high resolution study of the three lowest vibrational states of quinoline C9H7N, an N-bearing naphthalene derivative. While the pure rotational ground state spectrum of quinoline is unperturbed, severe complications appear in the spectra of the ν45 and ν44 vibrational modes (located at about 168 cm-1 and 178 cm-1, respectively). In order to study these effects in detail, we employed three different and complementary experimental techniques: Fourier-transform microwave spectroscopy, millimeter-wave spectroscopy, and Fourier-transform far-infrared spectroscopy with a synchrotron radiation source. Due to the high density of states in the IR spectra of molecules as large as PAHs, perturbations in the rotational spectra of excited states should be ubiquitous. Our study identifies for the first time this effect and provides some insights into an appropriate treatment of such perturbations.

  9. Uroguanylin induces electroencephalographic spikes in rats

    Directory of Open Access Journals (Sweden)

    MDA. Teixeira

    Full Text Available Uroguanylin (UGN is an endogenous peptide that acts on membrane-bound guanylate cyclase receptors of intestinal and renal cells increasing cGMP production and regulating electrolyte and water epithelial transport. Recent research works demonstrate the expression of this peptide and its receptor in the central nervous system. The current work was undertaken in order to evaluate modifications of electroencephalographic spectra (EEG in anesthetized Wistar rats, submitted to intracisternal infusion of uroguanylin (0.0125 nmoles/min or 0.04 nmoles/min. The current observations demonstrate that 0.0125 nmoles/min and 0.04 nmoles/min intracisternal infusion of UGN significantly enhances amplitude and frequency of sharp waves and evoked spikes (p = 0.03. No statistical significance was observed on absolute alpha and theta spectra amplitude. The present data suggest that UGN acts on bioelectrogenesis of cortical cells by inducing hypersynchronic firing of neurons. This effect is blocked by nedocromil, suggesting that UGN acts by increasing the activity of chloride channels.

  10. Training spiking neural networks to associate spatio-temporal input-output spike patterns

    OpenAIRE

    Mohemmed, A; Schliebs, S; Matsuda, S; Kasabov, N

    2013-01-01

    In a previous work (Mohemmed et al., Method for training a spiking neuron to associate input–output spike trains) [1] we have proposed a supervised learning algorithm based on temporal coding to train a spiking neuron to associate input spatiotemporal spike patterns to desired output spike patterns. The algorithm is based on the conversion of spike trains into analogue signals and the application of the Widrow–Hoff learning rule. In this paper we present a mathematical formulation of the prop...

  11. BETA SPECTRA. I. Negatrons spectra

    International Nuclear Information System (INIS)

    Grau Malonda, A.; Garcia-Torano, E.

    1978-01-01

    Using the Fermi theory of beta decay, the beta spectra for 62 negatrons emitters have been computed introducing a correction factor for unique forbidden transitions. These spectra are plotted vs. energy, once normal i sed, and tabulated with the related Fermi functions. The average and median energies are calculated. (Author)

  12. Rotation-vibration interactions in the spectra of polycyclic aromatic hydrocarbons: Quinoline as a test-case species

    Energy Technology Data Exchange (ETDEWEB)

    Pirali, O.; Gruet, S. [AILES Beamline, Synchrotron SOLEIL, l’Orme des Merisiers, Saint-Aubin, 91192 Gif-sur-Yvette cedex (France); Institut des Sciences Moléculaires d’Orsay, UMR8214 CNRS – Université Paris-Sud, Bât. 210, 91405 Orsay cedex (France); Kisiel, Z. [Institute of Physics, Polish Academy of Sciences, Al. Lotników 32/46, 02-668 Warsaw (Poland); Goubet, M. [Laboratoire de Physique des Lasers, Atomes et Molécules, UMR 8523 CNRS - Université Lille 1, Bâtiment P5, F-59655 Villeneuve d’Ascq Cedex (France); Martin-Drumel, M. A.; Cuisset, A.; Hindle, F.; Mouret, G. [Laboratoire de Physico-Chimie de l’Atmosphère, EA-4493, Université du Littoral – Côte d’Opale, 59140 Dunkerque (France)

    2015-03-14

    Polycyclic aromatic hydrocarbons (PAHs) are highly relevant for astrophysics as possible, though controversial, carriers of the unidentified infrared emission bands that are observed in a number of different astronomical objects. In support of radio-astronomical observations, high resolution laboratory spectroscopy has already provided the rotational spectra in the vibrational ground state of several molecules of this type, although the rotational study of their dense infrared (IR) bands has only recently become possible using a limited number of experimental set-ups. To date, all of the rotationally resolved data have concerned unperturbed spectra. We presently report the results of a high resolution study of the three lowest vibrational states of quinoline C{sub 9}H{sub 7}N, an N-bearing naphthalene derivative. While the pure rotational ground state spectrum of quinoline is unperturbed, severe complications appear in the spectra of the ν{sub 45} and ν{sub 44} vibrational modes (located at about 168 cm{sup −1} and 178 cm{sup −1}, respectively). In order to study these effects in detail, we employed three different and complementary experimental techniques: Fourier-transform microwave spectroscopy, millimeter-wave spectroscopy, and Fourier-transform far-infrared spectroscopy with a synchrotron radiation source. Due to the high density of states in the IR spectra of molecules as large as PAHs, perturbations in the rotational spectra of excited states should be ubiquitous. Our study identifies for the first time this effect and provides some insights into an appropriate treatment of such perturbations.

  13. Joint Probability-Based Neuronal Spike Train Classification

    Directory of Open Access Journals (Sweden)

    Yan Chen

    2009-01-01

    Full Text Available Neuronal spike trains are used by the nervous system to encode and transmit information. Euclidean distance-based methods (EDBMs have been applied to quantify the similarity between temporally-discretized spike trains and model responses. In this study, using the same discretization procedure, we developed and applied a joint probability-based method (JPBM to classify individual spike trains of slowly adapting pulmonary stretch receptors (SARs. The activity of individual SARs was recorded in anaesthetized, paralysed adult male rabbits, which were artificially-ventilated at constant rate and one of three different volumes. Two-thirds of the responses to the 600 stimuli presented at each volume were used to construct three response models (one for each stimulus volume consisting of a series of time bins, each with spike probabilities. The remaining one-third of the responses where used as test responses to be classified into one of the three model responses. This was done by computing the joint probability of observing the same series of events (spikes or no spikes, dictated by the test response in a given model and determining which probability of the three was highest. The JPBM generally produced better classification accuracy than the EDBM, and both performed well above chance. Both methods were similarly affected by variations in discretization parameters, response epoch duration, and two different response alignment strategies. Increasing bin widths increased classification accuracy, which also improved with increased observation time, but primarily during periods of increasing lung inflation. Thus, the JPBM is a simple and effective method performing spike train classification.

  14. Neuronal coding and spiking randomness

    Czech Academy of Sciences Publication Activity Database

    Košťál, Lubomír; Lánský, Petr; Rospars, J. P.

    2007-01-01

    Roč. 26, č. 10 (2007), s. 2693-2988 ISSN 0953-816X R&D Projects: GA MŠk(CZ) LC554; GA AV ČR(CZ) 1ET400110401; GA AV ČR(CZ) KJB100110701 Grant - others:ECO-NET(FR) 112644PF Institutional research plan: CEZ:AV0Z50110509 Keywords : spike train * variability * neurovědy Subject RIV: FH - Neurology Impact factor: 3.673, year: 2007

  15. Prospective Coding by Spiking Neurons.

    Directory of Open Access Journals (Sweden)

    Johanni Brea

    2016-06-01

    Full Text Available Animals learn to make predictions, such as associating the sound of a bell with upcoming feeding or predicting a movement that a motor command is eliciting. How predictions are realized on the neuronal level and what plasticity rule underlies their learning is not well understood. Here we propose a biologically plausible synaptic plasticity rule to learn predictions on a single neuron level on a timescale of seconds. The learning rule allows a spiking two-compartment neuron to match its current firing rate to its own expected future discounted firing rate. For instance, if an originally neutral event is repeatedly followed by an event that elevates the firing rate of a neuron, the originally neutral event will eventually also elevate the neuron's firing rate. The plasticity rule is a form of spike timing dependent plasticity in which a presynaptic spike followed by a postsynaptic spike leads to potentiation. Even if the plasticity window has a width of 20 milliseconds, associations on the time scale of seconds can be learned. We illustrate prospective coding with three examples: learning to predict a time varying input, learning to predict the next stimulus in a delayed paired-associate task and learning with a recurrent network to reproduce a temporally compressed version of a sequence. We discuss the potential role of the learning mechanism in classical trace conditioning. In the special case that the signal to be predicted encodes reward, the neuron learns to predict the discounted future reward and learning is closely related to the temporal difference learning algorithm TD(λ.

  16. iSpike: a spiking neural interface for the iCub robot

    International Nuclear Information System (INIS)

    Gamez, D; Fidjeland, A K; Lazdins, E

    2012-01-01

    This paper presents iSpike: a C++ library that interfaces between spiking neural network simulators and the iCub humanoid robot. It uses a biologically inspired approach to convert the robot’s sensory information into spikes that are passed to the neural network simulator, and it decodes output spikes from the network into motor signals that are sent to control the robot. Applications of iSpike range from embodied models of the brain to the development of intelligent robots using biologically inspired spiking neural networks. iSpike is an open source library that is available for free download under the terms of the GPL. (paper)

  17. Eliminating thermal violin spikes from LIGO noise

    Energy Technology Data Exchange (ETDEWEB)

    Santamore, D. H.; Levin, Yuri

    2001-08-15

    We have developed a scheme for reducing LIGO suspension thermal noise close to violin-mode resonances. The idea is to monitor directly the thermally induced motion of a small portion of (a 'point' on) each suspension fiber, thereby recording the random forces driving the test-mass motion close to each violin-mode frequency. One can then suppress the thermal noise by optimally subtracting the recorded fiber motions from the measured motion of the test mass, i.e., from the LIGO output. The proposed method is a modification of an analogous but more technically difficult scheme by Braginsky, Levin and Vyatchanin for reducing broad-band suspension thermal noise. The efficiency of our method is limited by the sensitivity of the sensor used to monitor the fiber motion. If the sensor has no intrinsic noise (i.e. has unlimited sensitivity), then our method allows, in principle, a complete removal of violin spikes from the thermal-noise spectrum. We find that in LIGO-II interferometers, in order to suppress violin spikes below the shot-noise level, the intrinsic noise of the sensor must be less than {approx}2 x 10{sup -13} cm/Hz. This sensitivity is two orders of magnitude greater than that of currently available sensors.

  18. Eliminating thermal violin spikes from LIGO noise

    International Nuclear Information System (INIS)

    Santamore, D. H.; Levin, Yuri

    2001-01-01

    We have developed a scheme for reducing LIGO suspension thermal noise close to violin-mode resonances. The idea is to monitor directly the thermally induced motion of a small portion of (a 'point' on) each suspension fiber, thereby recording the random forces driving the test-mass motion close to each violin-mode frequency. One can then suppress the thermal noise by optimally subtracting the recorded fiber motions from the measured motion of the test mass, i.e., from the LIGO output. The proposed method is a modification of an analogous but more technically difficult scheme by Braginsky, Levin and Vyatchanin for reducing broad-band suspension thermal noise. The efficiency of our method is limited by the sensitivity of the sensor used to monitor the fiber motion. If the sensor has no intrinsic noise (i.e. has unlimited sensitivity), then our method allows, in principle, a complete removal of violin spikes from the thermal-noise spectrum. We find that in LIGO-II interferometers, in order to suppress violin spikes below the shot-noise level, the intrinsic noise of the sensor must be less than ∼2 x 10 -13 cm/Hz. This sensitivity is two orders of magnitude greater than that of currently available sensors

  19. MEASURING DETAILED CHEMICAL ABUNDANCES FROM CO-ADDED MEDIUM-RESOLUTION SPECTRA. I. TESTS USING MILKY WAY DWARF SPHEROIDAL GALAXIES AND GLOBULAR CLUSTERS

    International Nuclear Information System (INIS)

    Yang Lei; Peng, Eric W.; Kirby, Evan N.; Guhathakurta, Puragra; Cheng, Lucy

    2013-01-01

    The ability to measure metallicities and α-element abundances in individual red giant branch (RGB) stars using medium-resolution spectra (R ≈ 6000) is a valuable tool for deciphering the nature of Milky Way dwarf satellites and the history of the Galactic halo. Extending such studies to more distant systems like Andromeda is beyond the ability of the current generation of telescopes, but by co-adding the spectra of similar stars, we can attain the necessary signal-to-noise ratio (S/N) to make detailed abundance measurements. In this paper, we present a method to determine metallicities and α-element abundances using the co-addition of medium-resolution spectra. We test the method of spectral co-addition using high-S/N spectra of more than 1300 RGB stars from Milky Way globular clusters and dwarf spheroidal galaxies obtained with the Keck II telescope/DEIMOS spectrograph. We group similar stars using photometric criteria and compare the weighted ensemble average abundances ([Fe/H], [Mg/Fe], [Si/Fe], [Ca/Fe], and [Ti/Fe]) of individual stars in each group with the measurements made on the corresponding co-added spectrum. We find a high level of agreement between the two methods, which permits us to apply this co-added spectra technique to more distant RGB stars, like stars in the M31 satellite galaxies. This paper outlines our spectral co-addition and abundance measurement methodology and describes the potential biases in making these measurements.

  20. Measuring Detailed Chemical Abundances from Co-added Medium-resolution Spectra. I. Tests Using Milky Way Dwarf Spheroidal Galaxies and Globular Clusters

    Science.gov (United States)

    Yang, Lei; Kirby, Evan N.; Guhathakurta, Puragra; Peng, Eric W.; Cheng, Lucy

    2013-05-01

    The ability to measure metallicities and α-element abundances in individual red giant branch (RGB) stars using medium-resolution spectra (R ≈ 6000) is a valuable tool for deciphering the nature of Milky Way dwarf satellites and the history of the Galactic halo. Extending such studies to more distant systems like Andromeda is beyond the ability of the current generation of telescopes, but by co-adding the spectra of similar stars, we can attain the necessary signal-to-noise ratio (S/N) to make detailed abundance measurements. In this paper, we present a method to determine metallicities and α-element abundances using the co-addition of medium-resolution spectra. We test the method of spectral co-addition using high-S/N spectra of more than 1300 RGB stars from Milky Way globular clusters and dwarf spheroidal galaxies obtained with the Keck II telescope/DEIMOS spectrograph. We group similar stars using photometric criteria and compare the weighted ensemble average abundances ([Fe/H], [Mg/Fe], [Si/Fe], [Ca/Fe], and [Ti/Fe]) of individual stars in each group with the measurements made on the corresponding co-added spectrum. We find a high level of agreement between the two methods, which permits us to apply this co-added spectra technique to more distant RGB stars, like stars in the M31 satellite galaxies. This paper outlines our spectral co-addition and abundance measurement methodology and describes the potential biases in making these measurements. Data herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and NASA. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation.

  1. Information transmission with spiking Bayesian neurons

    International Nuclear Information System (INIS)

    Lochmann, Timm; Deneve, Sophie

    2008-01-01

    Spike trains of cortical neurons resulting from repeatedpresentations of a stimulus are variable and exhibit Poisson-like statistics. Many models of neural coding therefore assumed that sensory information is contained in instantaneous firing rates, not spike times. Here, we ask how much information about time-varying stimuli can be transmitted by spiking neurons with such input and output variability. In particular, does this variability imply spike generation to be intrinsically stochastic? We consider a model neuron that estimates optimally the current state of a time-varying binary variable (e.g. presence of a stimulus) by integrating incoming spikes. The unit signals its current estimate to other units with spikes whenever the estimate increased by a fixed amount. As shown previously, this computation results in integrate and fire dynamics with Poisson-like output spike trains. This output variability is entirely due to the stochastic input rather than noisy spike generation. As a result such a deterministic neuron can transmit most of the information about the time varying stimulus. This contrasts with a standard model of sensory neurons, the linear-nonlinear Poisson (LNP) model which assumes that most variability in output spike trains is due to stochastic spike generation. Although it yields the same firing statistics, we found that such noisy firing results in the loss of most information. Finally, we use this framework to compare potential effects of top-down attention versus bottom-up saliency on information transfer with spiking neurons

  2. Feature Representations for Neuromorphic Audio Spike Streams.

    Science.gov (United States)

    Anumula, Jithendar; Neil, Daniel; Delbruck, Tobi; Liu, Shih-Chii

    2018-01-01

    Event-driven neuromorphic spiking sensors such as the silicon retina and the silicon cochlea encode the external sensory stimuli as asynchronous streams of spikes across different channels or pixels. Combining state-of-art deep neural networks with the asynchronous outputs of these sensors has produced encouraging results on some datasets but remains challenging. While the lack of effective spiking networks to process the spike streams is one reason, the other reason is that the pre-processing methods required to convert the spike streams to frame-based features needed for the deep networks still require further investigation. This work investigates the effectiveness of synchronous and asynchronous frame-based features generated using spike count and constant event binning in combination with the use of a recurrent neural network for solving a classification task using N-TIDIGITS18 dataset. This spike-based dataset consists of recordings from the Dynamic Audio Sensor, a spiking silicon cochlea sensor, in response to the TIDIGITS audio dataset. We also propose a new pre-processing method which applies an exponential kernel on the output cochlea spikes so that the interspike timing information is better preserved. The results from the N-TIDIGITS18 dataset show that the exponential features perform better than the spike count features, with over 91% accuracy on the digit classification task. This accuracy corresponds to an improvement of at least 2.5% over the use of spike count features, establishing a new state of the art for this dataset.

  3. Visually Evoked Spiking Evolves While Spontaneous Ongoing Dynamics Persist

    DEFF Research Database (Denmark)

    Huys, Raoul; Jirsa, Viktor K; Darokhan, Ziauddin

    2016-01-01

    by evoked spiking. This study of laminar recordings of spontaneous spiking and visually evoked spiking of neurons in the ferret primary visual cortex shows that the spiking dynamics does not change: the spontaneous spiking as well as evoked spiking is controlled by a stable and persisting fixed point...

  4. Spike Pattern Recognition for Automatic Collimation Alignment

    CERN Document Server

    Azzopardi, Gabriella; Salvachua Ferrando, Belen Maria; Mereghetti, Alessio; Redaelli, Stefano; CERN. Geneva. ATS Department

    2017-01-01

    The LHC makes use of a collimation system to protect its sensitive equipment by intercepting potentially dangerous beam halo particles. The appropriate collimator settings to protect the machine against beam losses relies on a very precise alignment of all the collimators with respect to the beam. The beam center at each collimator is then found by touching the beam halo using an alignment procedure. Until now, in order to determine whether a collimator is aligned with the beam or not, a user is required to follow the collimator’s BLM loss data and detect spikes. A machine learning (ML) model was trained in order to automatically recognize spikes when a collimator is aligned. The model was loosely integrated with the alignment implementation to determine the classification performance and reliability, without effecting the alignment process itself. The model was tested on a number of collimators during this MD and the machine learning was able to output the classifications in real-time.

  5. A Spiking Neural Network in sEMG Feature Extraction.

    Science.gov (United States)

    Lobov, Sergey; Mironov, Vasiliy; Kastalskiy, Innokentiy; Kazantsev, Victor

    2015-11-03

    We have developed a novel algorithm for sEMG feature extraction and classification. It is based on a hybrid network composed of spiking and artificial neurons. The spiking neuron layer with mutual inhibition was assigned as feature extractor. We demonstrate that the classification accuracy of the proposed model could reach high values comparable with existing sEMG interface systems. Moreover, the algorithm sensibility for different sEMG collecting systems characteristics was estimated. Results showed rather equal accuracy, despite a significant sampling rate difference. The proposed algorithm was successfully tested for mobile robot control.

  6. Origin of heterogeneous spiking patterns from continuously distributed ion channel densities: a computational study in spinal dorsal horn neurons.

    Science.gov (United States)

    Balachandar, Arjun; Prescott, Steven A

    2018-01-20

    Distinct spiking patterns may arise from qualitative differences in ion channel expression (i.e. when different neurons express distinct ion channels) and/or when quantitative differences in expression levels qualitatively alter the spike generation process. We hypothesized that spiking patterns in neurons of the superficial dorsal horn (SDH) of spinal cord reflect both mechanisms. We reproduced SDH neuron spiking patterns by varying densities of K V 1- and A-type potassium conductances. Plotting the spiking patterns that emerge from different density combinations revealed spiking-pattern regions separated by boundaries (bifurcations). This map suggests that certain spiking pattern combinations occur when the distribution of potassium channel densities straddle boundaries, whereas other spiking patterns reflect distinct patterns of ion channel expression. The former mechanism may explain why certain spiking patterns co-occur in genetically identified neuron types. We also present algorithms to predict spiking pattern proportions from ion channel density distributions, and vice versa. Neurons are often classified by spiking pattern. Yet, some neurons exhibit distinct patterns under subtly different test conditions, which suggests that they operate near an abrupt transition, or bifurcation. A set of such neurons may exhibit heterogeneous spiking patterns not because of qualitative differences in which ion channels they express, but rather because quantitative differences in expression levels cause neurons to operate on opposite sides of a bifurcation. Neurons in the spinal dorsal horn, for example, respond to somatic current injection with patterns that include tonic, single, gap, delayed and reluctant spiking. It is unclear whether these patterns reflect five cell populations (defined by distinct ion channel expression patterns), heterogeneity within a single population, or some combination thereof. We reproduced all five spiking patterns in a computational model by

  7. A Hybrid Setarx Model for Spikes in Tight Electricity Markets

    Directory of Open Access Journals (Sweden)

    Carlo Lucheroni

    2012-01-01

    Full Text Available The paper discusses a simple looking but highly nonlinear regime-switching, self-excited threshold model for hourly electricity prices in continuous and discrete time. The regime structure of the model is linked to organizational features of the market. In continuous time, the model can include spikes without using jumps, by defining stochastic orbits. In passing from continuous time to discrete time, the stochastic orbits survive discretization and can be identified again as spikes. A calibration technique suitable for the discrete version of this model, which does not need deseasonalization or spike filtering, is developed, tested and applied to market data. The discussion of the properties of the model uses phase-space analysis, an approach uncommon in econometrics. (original abstract

  8. The dynamic relationship between cerebellar Purkinje cell simple spikes and the spikelet number of complex spikes.

    Science.gov (United States)

    Burroughs, Amelia; Wise, Andrew K; Xiao, Jianqiang; Houghton, Conor; Tang, Tianyu; Suh, Colleen Y; Lang, Eric J; Apps, Richard; Cerminara, Nadia L

    2017-01-01

    Purkinje cells are the sole output of the cerebellar cortex and fire two distinct types of action potential: simple spikes and complex spikes. Previous studies have mainly considered complex spikes as unitary events, even though the waveform is composed of varying numbers of spikelets. The extent to which differences in spikelet number affect simple spike activity (and vice versa) remains unclear. We found that complex spikes with greater numbers of spikelets are preceded by higher simple spike firing rates but, following the complex spike, simple spikes are reduced in a manner that is graded with spikelet number. This dynamic interaction has important implications for cerebellar information processing, and suggests that complex spike spikelet number may maintain Purkinje cells within their operational range. Purkinje cells are central to cerebellar function because they form the sole output of the cerebellar cortex. They exhibit two distinct types of action potential: simple spikes and complex spikes. It is widely accepted that interaction between these two types of impulse is central to cerebellar cortical information processing. Previous investigations of the interactions between simple spikes and complex spikes have mainly considered complex spikes as unitary events. However, complex spikes are composed of an initial large spike followed by a number of secondary components, termed spikelets. The number of spikelets within individual complex spikes is highly variable and the extent to which differences in complex spike spikelet number affects simple spike activity (and vice versa) remains poorly understood. In anaesthetized adult rats, we have found that Purkinje cells recorded from the posterior lobe vermis and hemisphere have high simple spike firing frequencies that precede complex spikes with greater numbers of spikelets. This finding was also evident in a small sample of Purkinje cells recorded from the posterior lobe hemisphere in awake cats. In addition

  9. Toxicity of nickel-spiked freshwater sediments to benthic invertebrates-Spiking methodology, species sensitivity, and nickel bioavailability

    Science.gov (United States)

    Besser, John M.; Brumbaugh, William G.; Kemble, Nile E.; Ivey, Chris D.; Kunz, James L.; Ingersoll, Christopher G.; Rudel, David

    2011-01-01

    This report summarizes data from studies of the toxicity and bioavailability of nickel in nickel-spiked freshwater sediments. The goal of these studies was to generate toxicity and chemistry data to support development of broadly applicable sediment quality guidelines for nickel. The studies were conducted as three tasks, which are presented here as three chapters: Task 1, Development of methods for preparation and toxicity testing of nickel-spiked freshwater sediments; Task 2, Sensitivity of benthic invertebrates to toxicity of nickel-spiked freshwater sediments; and Task 3, Effect of sediment characteristics on nickel bioavailability. Appendices with additional methodological details and raw chemistry and toxicity data for the three tasks are available online at http://pubs.usgs.gov/sir/2011/5225/downloads/.

  10. Robust spike-train learning in spike-event based weight update.

    Science.gov (United States)

    Shrestha, Sumit Bam; Song, Qing

    2017-12-01

    Supervised learning algorithms in a spiking neural network either learn a spike-train pattern for a single neuron receiving input spike-train from multiple input synapses or learn to output the first spike time in a feedforward network setting. In this paper, we build upon spike-event based weight update strategy to learn continuous spike-train in a spiking neural network with a hidden layer using a dead zone on-off based adaptive learning rate rule which ensures convergence of the learning process in the sense of weight convergence and robustness of the learning process to external disturbances. Based on different benchmark problems, we compare this new method with other relevant spike-train learning algorithms. The results show that the speed of learning is much improved and the rate of successful learning is also greatly improved. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. Upper limb biomechanics during the volleyball serve and spike.

    Science.gov (United States)

    Reeser, Jonathan C; Fleisig, Glenn S; Bolt, Becky; Ruan, Mianfang

    2010-09-01

    The shoulder is the third-most commonly injured body part in volleyball, with the majority of shoulder problems resulting from chronic overuse. Significant kinetic differences exist among specific types of volleyball serves and spikes. Controlled laboratory study. Fourteen healthy female collegiate volleyball players performed 5 successful trials of 4 skills: 2 directional spikes, an off-speed roll shot, and the float serve. Volunteers who were competent in jump serves (n, 5) performed 5 trials of that skill. A 240-Hz 3-dimensional automatic digitizing system captured each trial. Multivariate analysis of variance and post hoc paired t tests were used to compare kinetic parameters for the shoulder and elbow across all the skills (except the jump serve). A similar statistical analysis was performed for upper extremity kinematics. Forces, torques, and angular velocities at the shoulder and elbow were lowest for the roll shot and second-lowest for the float serve. No differences were detected between the cross-body and straight-ahead spikes. Although there was an insufficient number of participants to statistically analyze the jump serve, the data for it appear similar to those of the cross-body and straight-ahead spikes. Shoulder abduction at the instant of ball contact was approximately 130° for all skills, which is substantially greater than that previously reported for female athletes performing tennis serves or baseball pitches. Because shoulder kinetics were greatest during spiking, the volleyball player with symptoms of shoulder overuse may wish to reduce the number of repetitions performed during practice. Limiting the number of jump serves may also reduce the athlete's risk of overuse-related shoulder dysfunction. Volleyball-specific overhead skills, such as the spike and serve, produce considerable upper extremity force and torque, which may contribute to the risk of shoulder injury.

  12. Measurement and Analysis of the Neutron and Gamma-Ray Flux Spectra in a Neutronics Mock-Up of the HCPB Test Blanket Module

    International Nuclear Information System (INIS)

    Seidel, K.; Freiesleben, H.; Poenitz, E.; Klix, A.; Unholzer, S.; Batistoni, P.; Fischer, U.; Leichtle, D.

    2006-01-01

    The nuclear parameters of a breeding blanket, such as tritium production rate, nuclear heating, activation and dose rate, are calculated by integral folding of an energy dependent cross section (or coefficient) with the neutron (or gamma-ray) flux energy spectra. The uncertainties of the designed parameters are determined by the uncertainties of both the cross section data and the flux spectra obtained by transport calculations. Also the analysis of possible discrepancies between measured and calculated integral nuclear parameter represents a two-step procedure. First, the energy region and the amount of flux discrepancies has to be found out and second, the cross section data have to be checked. To this end, neutron and gamma-ray flux spectra in a mock-up of the EU Helium-Cooled Pebble Bed (HCPB) breeder Test Blanket Module (TBM), irradiated with 14 MeV neutrons, were measured and analysed by means of Monte Carlo transport calculations. The flux spectra were determined for the energy ranges that are relevant for the most important nuclear parameters of the TBM, which are the tritium production rate and the shielding capability. The fast neutron flux which determines the tritium production on 7 Li and dominates the shield design was measured by the pulse-height distribution obtained from an organic liquid scintillation detector. Simultaneously, the gamma-ray flux spectra were measured. The neutron flux at lower energies, down to thermal, which determines the tritium production on 6 Li, was measured with time-of-arrival spectroscopy. For this purpose, the TUD neutron generator was operated in pulsed mode (pulse width 10 μs, frequency 1 kHz) and the neutrons arriving at a 3 He proportional counter in the mock-up were recorded as a function of time after the source neutron pulse. The spectral distributions for the two positions in the mock-up, where measurements were carried out, were calculated with the Monte Carlo code MCNP, version 5, and nuclear data from the

  13. Sialic Acid Binding Properties of Soluble Coronavirus Spike (S1) Proteins: Differences between Infectious Bronchitis Virus and Transmissible Gastroenteritis Virus

    Science.gov (United States)

    Shahwan, Katarina; Hesse, Martina; Mork, Ann-Kathrin; Herrler, Georg; Winter, Christine

    2013-01-01

    The spike proteins of a number of coronaviruses are able to bind to sialic acids present on the cell surface. The importance of this sialic acid binding ability during infection is, however, quite different. We compared the spike protein of transmissible gastroenteritis virus (TGEV) and the spike protein of infectious bronchitis virus (IBV). Whereas sialic acid is the only receptor determinant known so far for IBV, TGEV requires interaction with its receptor aminopeptidase N to initiate infection of cells. Binding tests with soluble spike proteins carrying an IgG Fc-tag revealed pronounced differences between these two viral proteins. Binding of the IBV spike protein to host cells was in all experiments sialic acid dependent, whereas the soluble TGEV spike showed binding to APN but had no detectable sialic acid binding activity. Our results underline the different ways in which binding to sialoglycoconjugates is mediated by coronavirus spike proteins. PMID:23896748

  14. Sialic Acid Binding Properties of Soluble Coronavirus Spike (S1 Proteins: Differences between Infectious Bronchitis Virus and Transmissible Gastroenteritis Virus

    Directory of Open Access Journals (Sweden)

    Christine Winter

    2013-07-01

    Full Text Available The spike proteins of a number of coronaviruses are able to bind to sialic acids present on the cell surface. The importance of this sialic acid binding ability during infection is, however, quite different. We compared the spike protein of transmissible gastroenteritis virus (TGEV and the spike protein of infectious bronchitis virus (IBV. Whereas sialic acid is the only receptor determinant known so far for IBV, TGEV requires interaction with its receptor aminopeptidase N to initiate infection of cells. Binding tests with soluble spike proteins carrying an IgG Fc-tag revealed pronounced differences between these two viral proteins. Binding of the IBV spike protein to host cells was in all experiments sialic acid dependent, whereas the soluble TGEV spike showed binding to APN but had no detectable sialic acid binding activity. Our results underline the different ways in which binding to sialoglycoconjugates is mediated by coronavirus spike proteins.

  15. Spiking Neuron Network Helmholtz Machine

    Directory of Open Access Journals (Sweden)

    Pavel eSountsov

    2015-04-01

    Full Text Available An increasing amount of behavioral and neurophysiological data suggests that the brain performs optimal (or near-optimal probabilistic inference and learning during perception and other tasks. Although many machine learning algorithms exist that perform inference and learning in an optimal way, the complete description of how one of those algorithms (or a novel algorithm can be implemented in the brain is currently incomplete. There have been many proposed solutions that address how neurons can perform optimal inference but the question of how synaptic plasticity can implement optimal learning is rarely addressed. This paper aims to unify the two fields of probabilistic inference and synaptic plasticity by using a neuronal network of realistic model spiking neurons to implement a well studied computational model called the Helmholtz Machine. The Helmholtz Machine is amenable to neural implementation as the algorithm it uses to learn its parameters, called the wake-sleep algorithm, uses a local delta learning rule. Our spiking-neuron network implements both the delta rule and a small example of a Helmholtz machine. This neuronal network can learn an internal model of continuous-valued training data sets without supervision. The network can also perform inference on the learned internal models. We show how various biophysical features of the neural implementation constrain the parameters of the wake-sleep algorithm, such as the duration of the wake and sleep phases of learning and the minimal sample duration. We examine the deviations from optimal performance and tie them to the properties of the synaptic plasticity rule.

  16. The Second Spiking Threshold: Dynamics of Laminar Network Spiking in the Visual Cortex

    DEFF Research Database (Denmark)

    Forsberg, Lars E.; Bonde, Lars H.; Harvey, Michael A.

    2016-01-01

    visually evoked spiking driven by sharp transients. Here we examine whether this second threshold exists outside the granular layer and examine details of transitions between spiking states in ferrets exposed to moving objects. We found the second threshold, separating spiking states evoked by stationary...

  17. Probing HeII Reionization at z>3.5 with Resolved HeII Lyman Alpha Forest Spectra

    Science.gov (United States)

    Worseck, Gabor

    2017-08-01

    The advent of GALEX and COS have revolutionized our view of HeII reionization, the final major phase transition of the intergalactic medium. COS spectra of the HeII Lyman alpha forest have confirmed with high confidence the high HeII transmission that signifies the completion of HeII reionization at z 2.7. However, the handful of z>3.5 quasars observed to date show a set of HeII transmission 'spikes' and larger regions with non-zero transmission that suggest HeII reionization was well underway by z=4. This is in striking conflict with predictions from state-of-the-art radiative transfer simulations of a HeII reionization driven by bright quasars. Explaining these measurements may require either faint quasars or more exotic sources of hard photons at z>4, with concomitant implications for HI reionization. However, many of the observed spikes are unresolved in G140L spectra and are significantly impacted by Poisson noise. Current data cannot reliably probe the ionization state of helium at z>3.5.We request 41 orbits to obtain science-grade G130M spectra of the two UV-brightest HeII-transmitting QSOs at z>3.5 to confirm and resolve their HeII transmission spikes as an unequivocal test of early HeII reionization. These spectra are complemented by recently obtained data from 8m telescopes: (1) Echelle spectra of the coeval HI Lya forest to map the underlying density field that modulates the HeII absorption, and (2) Our dedicated survey for foreground QSOs that may source the HeII transmission. Our recent HST programs revealed the only two viable targets to resolve the z>3.5 HeII Lyman alpha forest, and to conclusively solve this riddle.

  18. Linking investment spikes and productivity growth

    NARCIS (Netherlands)

    Geylani, P.C.; Stefanou, S.E.

    2013-01-01

    We investigate the relationship between productivity growth and investment spikes using Census Bureau’s plant-level dataset for the U.S. food manufacturing industry. There are differences in productivity growth and investment spike patterns across different sub-industries and food manufacturing

  19. Analysis and solution of current spike occurred in dynamic compensation of self-powered neutron detectors

    International Nuclear Information System (INIS)

    Peng, Xingjie; Li, Qing; Wang, Kan

    2017-01-01

    Highlights: • The current spike problem is observed in the dynamic compensation process of SPNDs. • The current spike is caused by unphysical current change due to range switching. • Modification on the compensation algorithm is introduced to deal with current spike. - Abstract: Dynamic compensation methods are required to improve the response speed of the Self-Powered Neutron Detectors (SPNDs) and make it possible to apply the SPNDs for core monitoring and surveillance. During the experimental test of the compensation method based on linear matrix inequality (LMI), spikes are observed in the compensated SPND current. After analyzing the measurement data, the cause is fixed on the unphysical change of the uncompensated SPND current due to range switching. Then some modifications on the dynamic compensation algorithms are proposed to solve the current spike problem.

  20. Voltage spikes in Nb3Sn and NbTi strands

    Energy Technology Data Exchange (ETDEWEB)

    Bordini, B.; Ambrosio, G.; Barzi, E.; Carcagno, R.; Feher, S.; Kashikhin, V.V.; Lamm, M.J.; Orris, D.; Tartaglia, M.; Tompkins, J.C.; Turrioni, D.; Yamada, R.; Zlobin,; /Fermilab

    2005-09-01

    As part of the High Field Magnet program at Fermilab several NbTi and Nb{sub 3}Sn strands were tested with particular emphasis on the study of voltage spikes and their relationship to superconductor instabilities. The voltage spikes were detected under various experimental conditions using voltage-current (V-I) and voltage-field (V-H) methods. Two types of spikes, designated ''magnetization'' and ''transport current'' spikes, have been identified. Their origin is most likely related to magnetization flux jump and transport current redistribution, respectively. Many of the signals observed appear to be a combination of these two types of spikes; the combination of these two instability mechanisms should play a dominant role in determining the minimum quench current.

  1. Event-driven contrastive divergence for spiking neuromorphic systems.

    Science.gov (United States)

    Neftci, Emre; Das, Srinjoy; Pedroni, Bruno; Kreutz-Delgado, Kenneth; Cauwenberghs, Gert

    2013-01-01

    Restricted Boltzmann Machines (RBMs) and Deep Belief Networks have been demonstrated to perform efficiently in a variety of applications, such as dimensionality reduction, feature learning, and classification. Their implementation on neuromorphic hardware platforms emulating large-scale networks of spiking neurons can have significant advantages from the perspectives of scalability, power dissipation and real-time interfacing with the environment. However, the traditional RBM architecture and the commonly used training algorithm known as Contrastive Divergence (CD) are based on discrete updates and exact arithmetics which do not directly map onto a dynamical neural substrate. Here, we present an event-driven variation of CD to train a RBM constructed with Integrate & Fire (I&F) neurons, that is constrained by the limitations of existing and near future neuromorphic hardware platforms. Our strategy is based on neural sampling, which allows us to synthesize a spiking neural network that samples from a target Boltzmann distribution. The recurrent activity of the network replaces the discrete steps of the CD algorithm, while Spike Time Dependent Plasticity (STDP) carries out the weight updates in an online, asynchronous fashion. We demonstrate our approach by training an RBM composed of leaky I&F neurons with STDP synapses to learn a generative model of the MNIST hand-written digit dataset, and by testing it in recognition, generation and cue integration tasks. Our results contribute to a machine learning-driven approach for synthesizing networks of spiking neurons capable of carrying out practical, high-level functionality.

  2. Event-Driven Contrastive Divergence for Spiking Neuromorphic Systems

    Directory of Open Access Journals (Sweden)

    Emre eNeftci

    2014-01-01

    Full Text Available Restricted Boltzmann Machines (RBMs and Deep Belief Networks have been demonstrated to perform efficiently in variety of applications, such as dimensionality reduction, feature learning, and classification. Their implementation on neuromorphic hardware platforms emulating large-scale networks of spiking neurons can have significant advantages from the perspectives of scalability, power dissipation and real-time interfacing with the environment. However the traditional RBM architecture and the commonly used training algorithm known as Contrastive Divergence (CD are based on discrete updates and exact arithmetics which do not directly map onto a dynamical neural substrate. Here, we present an event-driven variation of CD to train a RBM constructed with Integrate & Fire (I&F neurons, that is constrained by the limitations of existing and near future neuromorphic hardware platforms. Our strategy is based on neural sampling, which allows us to synthesize a spiking neural network that samples from a target Boltzmann distribution. The reverberating activity of the network replaces the discrete steps of the CD algorithm, while Spike Time Dependent Plasticity (STDP carries out the weight updates in an online, asynchronous fashion.We demonstrate our approach by training an RBM composed of leaky I&F neurons with STDP synapses to learn a generative model of the MNIST hand-written digit dataset, and by testing it in recognition, generation and cue integration tasks. Our results contribute to a machine learning-driven approach for synthesizing networks of spiking neurons capable of carrying out practical, high-level functionality.

  3. Reconstruction of audio waveforms from spike trains of artificial cochlea models

    Science.gov (United States)

    Zai, Anja T.; Bhargava, Saurabh; Mesgarani, Nima; Liu, Shih-Chii

    2015-01-01

    Spiking cochlea models describe the analog processing and spike generation process within the biological cochlea. Reconstructing the audio input from the artificial cochlea spikes is therefore useful for understanding the fidelity of the information preserved in the spikes. The reconstruction process is challenging particularly for spikes from the mixed signal (analog/digital) integrated circuit (IC) cochleas because of multiple non-linearities in the model and the additional variance caused by random transistor mismatch. This work proposes an offline method for reconstructing the audio input from spike responses of both a particular spike-based hardware model called the AEREAR2 cochlea and an equivalent software cochlea model. This method was previously used to reconstruct the auditory stimulus based on the peri-stimulus histogram of spike responses recorded in the ferret auditory cortex. The reconstructed audio from the hardware cochlea is evaluated against an analogous software model using objective measures of speech quality and intelligibility; and further tested in a word recognition task. The reconstructed audio under low signal-to-noise (SNR) conditions (SNR < –5 dB) gives a better classification performance than the original SNR input in this word recognition task. PMID:26528113

  4. Reconstruction of audio waveforms from spike trains of artificial cochlea models

    Directory of Open Access Journals (Sweden)

    Anja eZai

    2015-10-01

    Full Text Available Spiking cochlea models describe the analog processing and spike generation process within the biological cochlea. Reconstructing the audio input from the artificial cochlea spikes is therefore useful for understanding the fidelity of the information preserved in the spikes. The reconstruction process is challenging particularly for spikes from the mixed signal (analog/digital integrated circuit (IC cochleas because of multiple nonlinearities in the model and the additional variance caused by random transistor mismatch. This work proposes an offline method for reconstructing the audio input from spike responses of both a particular spike-based hardware model called the AEREAR2 cochlea and an equivalent software cochlea model. This method was previously used to reconstruct the auditory stimulus based on the peri-stimulus histogram of spike responses recorded in the ferret auditory cortex. The reconstructed audio from the hardware cochlea is evaluated against an analogous software model using objective measures of speech quality and intelligibility; and further tested in a word recognition task. The reconstructed audio under low signal-to-noise (SNR conditions (SNR < -5 dB gives a better classification performance than the original SNR input in this word recognition task.

  5. To sort or not to sort: the impact of spike-sorting on neural decoding performance

    Science.gov (United States)

    Todorova, Sonia; Sadtler, Patrick; Batista, Aaron; Chase, Steven; Ventura, Valérie

    2014-10-01

    Objective. Brain-computer interfaces (BCIs) are a promising technology for restoring motor ability to paralyzed patients. Spiking-based BCIs have successfully been used in clinical trials to control multi-degree-of-freedom robotic devices. Current implementations of these devices require a lengthy spike-sorting step, which is an obstacle to moving this technology from the lab to the clinic. A viable alternative is to avoid spike-sorting, treating all threshold crossings of the voltage waveform on an electrode as coming from one putative neuron. It is not known, however, how much decoding information might be lost by ignoring spike identity. Approach. We present a full analysis of the effects of spike-sorting schemes on decoding performance. Specifically, we compare how well two common decoders, the optimal linear estimator and the Kalman filter, reconstruct the arm movements of non-human primates performing reaching tasks, when receiving input from various sorting schemes. The schemes we tested included: using threshold crossings without spike-sorting; expert-sorting discarding the noise; expert-sorting, including the noise as if it were another neuron; and automatic spike-sorting using waveform features. We also decoded from a joint statistical model for the waveforms and tuning curves, which does not involve an explicit spike-sorting step. Main results. Discarding the threshold crossings that cannot be assigned to neurons degrades decoding: no spikes should be discarded. Decoding based on spike-sorted units outperforms decoding based on electrodes voltage crossings: spike-sorting is useful. The four waveform based spike-sorting methods tested here yield similar decoding efficiencies: a fast and simple method is competitive. Decoding using the joint waveform and tuning model shows promise but is not consistently superior. Significance. Our results indicate that simple automated spike-sorting performs as well as the more computationally or manually intensive

  6. Memristors Empower Spiking Neurons With Stochasticity

    KAUST Repository

    Al-Shedivat, Maruan

    2015-06-01

    Recent theoretical studies have shown that probabilistic spiking can be interpreted as learning and inference in cortical microcircuits. This interpretation creates new opportunities for building neuromorphic systems driven by probabilistic learning algorithms. However, such systems must have two crucial features: 1) the neurons should follow a specific behavioral model, and 2) stochastic spiking should be implemented efficiently for it to be scalable. This paper proposes a memristor-based stochastically spiking neuron that fulfills these requirements. First, the analytical model of the memristor is enhanced so it can capture the behavioral stochasticity consistent with experimentally observed phenomena. The switching behavior of the memristor model is demonstrated to be akin to the firing of the stochastic spike response neuron model, the primary building block for probabilistic algorithms in spiking neural networks. Furthermore, the paper proposes a neural soma circuit that utilizes the intrinsic nondeterminism of memristive switching for efficient spike generation. The simulations and analysis of the behavior of a single stochastic neuron and a winner-take-all network built of such neurons and trained on handwritten digits confirm that the circuit can be used for building probabilistic sampling and pattern adaptation machinery in spiking networks. The findings constitute an important step towards scalable and efficient probabilistic neuromorphic platforms. © 2011 IEEE.

  7. Spike Bursts from an Excitable Optical System

    Science.gov (United States)

    Rios Leite, Jose R.; Rosero, Edison J.; Barbosa, Wendson A. S.; Tredicce, Jorge R.

    Diode Lasers with double optical feedback are shown to present power drop spikes with statistical distribution controllable by the ratio of the two feedback times. The average time between spikes and the variance within long time series are studied. The system is shown to be excitable and present bursting of spikes created with specific feedback time ratios and strength. A rate equation model, extending the Lang-Kobayashi single feedback for semiconductor lasers proves to match the experimental observations. Potential applications to construct network to mimic neural systems having controlled bursting properties in each unit will be discussed. Brazilian Agency CNPQ.

  8. Supervised Learning in Spiking Neural Networks for Precise Temporal Encoding.

    Science.gov (United States)

    Gardner, Brian; Grüning, André

    2016-01-01

    Precise spike timing as a means to encode information in neural networks is biologically supported, and is advantageous over frequency-based codes by processing input features on a much shorter time-scale. For these reasons, much recent attention has been focused on the development of supervised learning rules for spiking neural networks that utilise a temporal coding scheme. However, despite significant progress in this area, there still lack rules that have a theoretical basis, and yet can be considered biologically relevant. Here we examine the general conditions under which synaptic plasticity most effectively takes place to support the supervised learning of a precise temporal code. As part of our analysis we examine two spike-based learning methods: one of which relies on an instantaneous error signal to modify synaptic weights in a network (INST rule), and the other one relying on a filtered error signal for smoother synaptic weight modifications (FILT rule). We test the accuracy of the solutions provided by each rule with respect to their temporal encoding precision, and then measure the maximum number of input patterns they can learn to memorise using the precise timings of individual spikes as an indication of their storage capacity. Our results demonstrate the high performance of the FILT rule in most cases, underpinned by the rule's error-filtering mechanism, which is predicted to provide smooth convergence towards a desired solution during learning. We also find the FILT rule to be most efficient at performing input pattern memorisations, and most noticeably when patterns are identified using spikes with sub-millisecond temporal precision. In comparison with existing work, we determine the performance of the FILT rule to be consistent with that of the highly efficient E-learning Chronotron rule, but with the distinct advantage that our FILT rule is also implementable as an online method for increased biological realism.

  9. Sequential motor task (Luria's Fist-Edge-Palm Test in children with benign focal epilepsy of childhood with centrotemporal spikes Tarefa motora sequencial (Teste de Lúria punho-lado-palma em crianças com epilepsia focal benigna da infância com descarga centrotemporal

    Directory of Open Access Journals (Sweden)

    Carmen Silvia Molleis Galego Miziara

    2013-06-01

    Full Text Available This study evaluated the sequential motor manual actions in children with benign focal epilepsy of childhood with centrotemporal spikes (BECTS and compares the results with matched control group, through the application of Luria's fist-edge-palm test. The children with BECTS underwent interictal single photon emission computed tomography (SPECT and School Performance Test (SPT. Significant difference occurred between the study and control groups for manual motor action through three equal and three different movements. Children with lower school performance had higher error rate in the imitation of hand gestures. Another factor significantly associated with the failure was the abnormality in SPECT. Children with BECTS showed abnormalities in the test that evaluated manual motor programming/planning. This study may suggest that the functional changes related to epileptiform activity in rolandic region interfere with the executive function in children with BECTS.Esse estudo avaliou ações motoras manuais sequenciais em crianças com epilepsia focal benigna da infância com descarga centrotemporal (EBICT e comparou os resultados com o grupo controle pareado, através do teste de Lúria (punho-lado-palma. As crianças com EBICT realizaram single photon emission computed tomography (SPECT interictal e Teste de Desempenho Escolar (TDE. Foram encontradas diferenças significativas entre os dois grupos nas atividades motoras de três movimentos iguais e três movimentos diferentes. As crianças com piores resultados no TDE e com SPECT alterado apresentaram mais erros no teste de imitação manual. Crianças com epilepsia fracassaram nos testes de avaliação motora que envolvem programação/planejamento. Esse estudo sugere que mudanças funcionais relacionadas à atividade epileptiforme na região rolândica interfere com as funções executivas de crianças com EBICT.

  10. Inferring oscillatory modulation in neural spike trains.

    Science.gov (United States)

    Arai, Kensuke; Kass, Robert E

    2017-10-01

    Oscillations are observed at various frequency bands in continuous-valued neural recordings like the electroencephalogram (EEG) and local field potential (LFP) in bulk brain matter, and analysis of spike-field coherence reveals that spiking of single neurons often occurs at certain phases of the global oscillation. Oscillatory modulation has been examined in relation to continuous-valued oscillatory signals, and independently from the spike train alone, but behavior or stimulus triggered firing-rate modulation, spiking sparseness, presence of slow modulation not locked to stimuli and irregular oscillations with large variability in oscillatory periods, present challenges to searching for temporal structures present in the spike train. In order to study oscillatory modulation in real data collected under a variety of experimental conditions, we describe a flexible point-process framework we call the Latent Oscillatory Spike Train (LOST) model to decompose the instantaneous firing rate in biologically and behaviorally relevant factors: spiking refractoriness, event-locked firing rate non-stationarity, and trial-to-trial variability accounted for by baseline offset and a stochastic oscillatory modulation. We also extend the LOST model to accommodate changes in the modulatory structure over the duration of the experiment, and thereby discover trial-to-trial variability in the spike-field coherence of a rat primary motor cortical neuron to the LFP theta rhythm. Because LOST incorporates a latent stochastic auto-regressive term, LOST is able to detect oscillations when the firing rate is low, the modulation is weak, and when the modulating oscillation has a broad spectral peak.

  11. BioSense/SR-BioSpectra demonstrations of wide area/early warning for bioaerosol threats: program description and early test and evaluation results

    Science.gov (United States)

    Simard, Jean-Robert; Buteau, Sylvie; Lahaie, Pierre; Mathieu, Pierre; Roy, Gilles; Nadeau, Denis; McFee, John; Ho, Jim; Rowsell, Susan; Ho, Nicolas; Babin, François; Cantin, Daniel; Healey, Dave; Robinson, Jennifer; Wood, Scott; Hsu, Jack

    2011-11-01

    Threats associated with bioaerosol weapons have been around for several decades and have been mostly associated with terrorist activities or rogue nations. Up to the turn of the millennium, defence concepts against such menaces relied mainly on point or in-situ detection technologies. Over the last 10 years, significant efforts have been deployed by multiple countries to supplement the limited spatial coverage of a network of one or more point bio-detectors using lidar technology. The addition of such technology makes it possible to detect within seconds suspect aerosol clouds over area of several tens of square kilometers and track their trajectories. These additional capabilities are paramount in directing presumptive ID missions, mapping hazardous areas, establishing efficient counter-measures and supporting subsequent forensic investigations. In order to develop such capabilities, Defence Research and Development Canada (DRDC) and the Chemical, Biological, Radiological-Nuclear, and Explosives Research and Technology Initiative (CRTI) have supported two major demonstrations based on spectrally resolved Laser Induced Fluorescence (LIF) lidar: BioSense, aimed at defence military missions in wide open spaces, and SR-BioSpectra, aimed at surveillance of enclosed or semienclosed wide spaces common to defence and public security missions. This article first reviews briefly the modeling behind these demonstration concepts. Second, the lidar-adapted and the benchtop bioaerosol LIF chambers (BSL1), developed to challenge the constructed detection systems and to accelerate the population of the library of spectral LIF properties of bioaerosols and interferents of interest, will be described. Next, the most recent test and evaluation (T&E) results obtained with SR-BioSpectra and BioSense are reported. Finally, a brief discussion stating the way ahead for a complete defence suite is provided.

  12. Towards statistical summaries of spike train data.

    Science.gov (United States)

    Wu, Wei; Srivastava, Anuj

    2011-01-30

    Statistical inference has an important role in analysis of neural spike trains. While current approaches are mostly model-based, and designed for capturing the temporal evolution of the underlying stochastic processes, we focus on a data-driven approach where statistics are defined and computed in function spaces where individual spike trains are viewed as points. The first contribution of this paper is to endow spike train space with a parameterized family of metrics that takes into account different time warpings and generalizes several currently used metrics. These metrics are essentially penalized L(p) norms, involving appropriate functions of spike trains, with penalties associated with time-warpings. The second contribution of this paper is to derive a notion of a mean spike train in the case when p=2. We present an efficient recursive algorithm, termed Matching-Minimization algorithm, to compute the sample mean of a set of spike trains. The proposed metrics as well as the mean computations are demonstrated using an experimental recording from the motor cortex. Copyright © 2010 Elsevier B.V. All rights reserved.

  13. Macroscopic Description for Networks of Spiking Neurons

    Science.gov (United States)

    Montbrió, Ernest; Pazó, Diego; Roxin, Alex

    2015-04-01

    A major goal of neuroscience, statistical physics, and nonlinear dynamics is to understand how brain function arises from the collective dynamics of networks of spiking neurons. This challenge has been chiefly addressed through large-scale numerical simulations. Alternatively, researchers have formulated mean-field theories to gain insight into macroscopic states of large neuronal networks in terms of the collective firing activity of the neurons, or the firing rate. However, these theories have not succeeded in establishing an exact correspondence between the firing rate of the network and the underlying microscopic state of the spiking neurons. This has largely constrained the range of applicability of such macroscopic descriptions, particularly when trying to describe neuronal synchronization. Here, we provide the derivation of a set of exact macroscopic equations for a network of spiking neurons. Our results reveal that the spike generation mechanism of individual neurons introduces an effective coupling between two biophysically relevant macroscopic quantities, the firing rate and the mean membrane potential, which together govern the evolution of the neuronal network. The resulting equations exactly describe all possible macroscopic dynamical states of the network, including states of synchronous spiking activity. Finally, we show that the firing-rate description is related, via a conformal map, to a low-dimensional description in terms of the Kuramoto order parameter, called Ott-Antonsen theory. We anticipate that our results will be an important tool in investigating how large networks of spiking neurons self-organize in time to process and encode information in the brain.

  14. Investigation of Supply Current Spikes in Flash Memories Using Ion-Electron Emission Microscopy

    Science.gov (United States)

    Gerardin, S.; Bagatin, M.; Paccagnella, A.; Bisello, D.; Giubilato, P.; Mattiazzo, S.; Pantano, D.; Silvestrin, L.; Tessaro, M.; Wyss, J.; Ferlet-Cavrois, V.

    2013-12-01

    We studied the occurrence of supply current spikes and destructive events in NAND flash memories under heavy-ion exposure. In addition to broad-beam experiments, we used collimated beams and ion-electron emission microscopy to investigate the phenomena on two types of memories with different feature size. Current spikes on the supply current were observed in both devices, also with collimated beams, whereas destructive events occurred only with broad beam. We show that current spikes do not originate from charge-pump capacitors, as previously suggested, and propose that destructive events are due to the effects of temporally close heavy-ion hits on distinct areas of the tested chips.

  15. Binary Associative Memories as a Benchmark for Spiking Neuromorphic Hardware

    Directory of Open Access Journals (Sweden)

    Andreas Stöckel

    2017-08-01

    Full Text Available Large-scale neuromorphic hardware platforms, specialized computer systems for energy efficient simulation of spiking neural networks, are being developed around the world, for example as part of the European Human Brain Project (HBP. Due to conceptual differences, a universal performance analysis of these systems in terms of runtime, accuracy and energy efficiency is non-trivial, yet indispensable for further hard- and software development. In this paper we describe a scalable benchmark based on a spiking neural network implementation of the binary neural associative memory. We treat neuromorphic hardware and software simulators as black-boxes and execute exactly the same network description across all devices. Experiments on the HBP platforms under varying configurations of the associative memory show that the presented method allows to test the quality of the neuron model implementation, and to explain significant deviations from the expected reference output.

  16. Platinum stable isotope ratio measurements by double-spike multiple collector ICPMS

    DEFF Research Database (Denmark)

    Creech, John; Baker, Joel; Handler, Monica

    2013-01-01

    We present a new technique for the precise determination of platinum (Pt) stable isotope ratios by multiple-collector inductively coupled plasma mass spectrometry (MC-ICPMS) using two different Pt double-spikes ( Pt-Pt and Pt-Pt). Results are expressed relative to the IRMM-010 Pt isotope standard......) can be obtained on Pt stable isotope ratios with either double-spike. Elemental doping tests reveal that double-spike corrected Pt stable isotope ratios are insensitive to the presence of relatively high (up to 10%) levels of matrix elements, although the Pt-Pt double-spike is affected by an isobaric...... interference on Pt from Os. The Pt-Pt double-spike does not use Pt in the double-spike inversion and is unaffected by Os contamination, and is our recommended double-spike for use with natural samples. As part of this study, we re-determined the natural Pt isotopic composition of IRMM-010 by MC-ICPMS using...

  17. Google Searches for "Cheap Cigarettes" Spike at Tax Increases: Evidence from an Algorithm to Detect Spikes in Time Series Data.

    Science.gov (United States)

    Caputi, Theodore L

    2017-06-22

    Online cigarette dealers have lower prices than brick-and-mortar retailers and advertise tax-free status 1-8. Previous studies show smokers search out these online alternatives at the time of a cigarette tax increase 9-10. However, these studies rely upon researchers' decision to consider a specific date and preclude the possibility that researchers focus on the wrong date. The purpose of this study is to introduce an unbiased methodology to the field of observing search patterns and to use this methodology to determine whether smokers search Google for "cheap cigarettes" at cigarette tax increases and, if so, whether the increased level of searches persists. Publicly available data from Google Trends is used to observe standardized search volumes for the term, "cheap cigarettes." Seasonal Hybrid Extreme Studentized Deviate and E-Divisive with Means tests were performed to observe spikes and mean level shifts in search volume. Of the twelve cigarette tax increases studied, ten showed spikes in searches for "cheap cigarettes" within two weeks of the tax increase. However, the mean level shifts did not occur for any cigarette tax increase. Searches for "cheap cigarettes" spike around the time of a cigarette tax increase, but the mean level of searches does not shift in response to a tax increase. The SHESD and EDM tests are unbiased methodologies that can be used to identify spikes and mean level shifts in time series data without an a priori date to be studied. SHESD and EDM affirm spikes in interest are related to tax increases. Applies improved statistical techniques (SHESD and EDM) to Google search data related to cigarettes, reducing bias and increasing powerContributes to the body of evidence that state and federal tax increases are associated with spikes in searches for cheap cigarettes and may be good dates for increased online health messaging related to tobacco. © The Author 2017. Published by Oxford University Press on behalf of the Society for Research

  18. Enhancement of Spike-Timing-Dependent Plasticity in Spiking Neural Systems with Noise.

    Science.gov (United States)

    Nobukawa, Sou; Nishimura, Haruhiko

    2016-08-01

    Synaptic plasticity is widely recognized to support adaptable information processing in the brain. Spike-timing-dependent plasticity, one subtype of plasticity, can lead to synchronous spike propagation with temporal spiking coding information. Recently, it was reported that in a noisy environment, like the actual brain, the spike-timing-dependent plasticity may be made efficient by the effect of stochastic resonance. In the stochastic resonance, the presence of noise helps a nonlinear system in amplifying a weak (under barrier) signal. However, previous studies have ignored the full variety of spiking patterns and many relevant factors in neural dynamics. Thus, in order to prove the physiological possibility for the enhancement of spike-timing-dependent plasticity by stochastic resonance, it is necessary to demonstrate that this stochastic resonance arises in realistic cortical neural systems. In this study, we evaluate this stochastic resonance phenomenon in the realistic cortical neural system described by the Izhikevich neuron model and compare the characteristics of typical spiking patterns of regular spiking, intrinsically bursting and chattering experimentally observed in the cortex.

  19. Spiking Neurons for Analysis of Patterns

    Science.gov (United States)

    Huntsberger, Terrance

    2008-01-01

    Artificial neural networks comprising spiking neurons of a novel type have been conceived as improved pattern-analysis and pattern-recognition computational systems. These neurons are represented by a mathematical model denoted the state-variable model (SVM), which among other things, exploits a computational parallelism inherent in spiking-neuron geometry. Networks of SVM neurons offer advantages of speed and computational efficiency, relative to traditional artificial neural networks. The SVM also overcomes some of the limitations of prior spiking-neuron models. There are numerous potential pattern-recognition, tracking, and data-reduction (data preprocessing) applications for these SVM neural networks on Earth and in exploration of remote planets. Spiking neurons imitate biological neurons more closely than do the neurons of traditional artificial neural networks. A spiking neuron includes a central cell body (soma) surrounded by a tree-like interconnection network (dendrites). Spiking neurons are so named because they generate trains of output pulses (spikes) in response to inputs received from sensors or from other neurons. They gain their speed advantage over traditional neural networks by using the timing of individual spikes for computation, whereas traditional artificial neurons use averages of activity levels over time. Moreover, spiking neurons use the delays inherent in dendritic processing in order to efficiently encode the information content of incoming signals. Because traditional artificial neurons fail to capture this encoding, they have less processing capability, and so it is necessary to use more gates when implementing traditional artificial neurons in electronic circuitry. Such higher-order functions as dynamic tasking are effected by use of pools (collections) of spiking neurons interconnected by spike-transmitting fibers. The SVM includes adaptive thresholds and submodels of transport of ions (in imitation of such transport in biological

  20. Spike train encoding by regular-spiking cells of the visual cortex.

    Science.gov (United States)

    Carandini, M; Mechler, F; Leonard, C S; Movshon, J A

    1996-11-01

    1. To study the encoding of input currents into output spike trains by regular-spiking cells, we recorded intracellularly from slices of the guinea pig visual cortex while injecting step, sinusoidal, and broadband noise currents. 2. When measured with sinusoidal currents, the frequency tuning of the spike responses was markedly band-pass. The preferred frequency was between 8 and 30 Hz, and grew with stimulus amplitude and mean intensity. 3. Stimulation with broadband noise currents dramatically enhanced the gain of the spike responses at low and high frequencies, yielding an essentially flat frequency tuning between 0.1 and 130 Hz. 4. The averaged spike responses to sinusoidal currents exhibited two nonlinearities: rectification and spike synchronization. By contrast, no nonlinearity was evident in the averaged responses to broadband noise stimuli. 5. These properties of the spike responses were not present in the membrane potential responses. The latter were roughly linear, and their frequency tuning was low-pass and well fit by a single-compartment passive model of the cell membrane composed of a resistance and a capacitance in parallel (RC circuit). 6. To account for the spike responses, we used a "sandwich model" consisting of a low-pass linear filter (the RC circuit), a rectification nonlinearity, and a high-pass linear filter. The model is described by six parameters and predicts analog firing rates rather than discrete spikes. It provided satisfactory fits to the firing rate responses to steps, sinusoids, and broadband noise currents. 7. The properties of spike encoding are consistent with temporal nonlinearities of the visual responses in V1, such as the dependence of response frequency tuning and latency on stimulus contrast and bandwidth. We speculate that one of the roles of the high-frequency membrane potential fluctuations observed in vivo could be to amplify and linearize the responses to lower, stimulus-related frequencies.

  1. A Reinforcement Learning Framework for Spiking Networks with Dynamic Synapses

    Directory of Open Access Journals (Sweden)

    Karim El-Laithy

    2011-01-01

    Full Text Available An integration of both the Hebbian-based and reinforcement learning (RL rules is presented for dynamic synapses. The proposed framework permits the Hebbian rule to update the hidden synaptic model parameters regulating the synaptic response rather than the synaptic weights. This is performed using both the value and the sign of the temporal difference in the reward signal after each trial. Applying this framework, a spiking network with spike-timing-dependent synapses is tested to learn the exclusive-OR computation on a temporally coded basis. Reward values are calculated with the distance between the output spike train of the network and a reference target one. Results show that the network is able to capture the required dynamics and that the proposed framework can reveal indeed an integrated version of Hebbian and RL. The proposed framework is tractable and less computationally expensive. The framework is applicable to a wide class of synaptic models and is not restricted to the used neural representation. This generality, along with the reported results, supports adopting the introduced approach to benefit from the biologically plausible synaptic models in a wide range of intuitive signal processing.

  2. Archeomagnetic Intensity Spikes: Global or Regional Geomagnetic Field Features?

    Directory of Open Access Journals (Sweden)

    Monika Korte

    2018-03-01

    Full Text Available Variations of the geomagnetic field prior to direct observations are inferred from archeo- and paleomagnetic experiments. Seemingly unusual variations not seen in the present-day and historical field are of particular interest to constrain the full range of core dynamics. Recently, archeomagnetic intensity spikes, characterized by very high field values that appear to be associated with rapid secular variation rates, have been reported from several parts of the world. They were first noted in data from the Levant at around 900 BCE. A recent re-assessment of previous and new Levantine data, involving a rigorous quality assessment, interprets the observations as an extreme local geomagnetic high with at least two intensity spikes between the 11th and 8th centuries BCE. Subsequent reports of similar features from Asia, the Canary Islands and Texas raise the question of whether such features might be common occurrences, or whether they might even be part of a global magnetic field feature. Here we use spherical harmonic modeling to test two hypotheses: firstly, whether the Levantine and other potential spikes might be associated with higher dipole field intensity than shown by existing global field models around 1,000 BCE, and secondly, whether the observations from different parts of the world are compatible with a westward drifting intense flux patch. Our results suggest that the spikes originate from intense flux patches growing and decaying mostly in situ, combined with stronger and more variable dipole moment than shown by previous global field models. Axial dipole variations no more than 60% higher than observed in the present field, probably within the range of normal geodynamo behavior, seem sufficient to explain the observations.

  3. Spiking and LFP activity in PRR during symbolically instructed reaches.

    Science.gov (United States)

    Hwang, Eun Jung; Andersen, Richard A

    2012-02-01

    The spiking activity in the parietal reach region (PRR) represents the spatial goal of an impending reach when the reach is directed toward or away from a visual object. The local field potentials (LFPs) in this region also represent the reach goal when the reach is directed to a visual object. Thus PRR is a candidate area for reading out a patient's intended reach goals for neural prosthetic applications. For natural behaviors, reach goals are not always based on the location of a visual object, e.g., playing the piano following sheet music or moving following verbal directions. So far it has not been directly tested whether and how PRR represents reach goals in such cognitive, nonlocational conditions, and knowing the encoding properties in various task conditions would help in designing a reach goal decoder for prosthetic applications. To address this issue, we examined the macaque PRR under two reach conditions: reach goal determined by the stimulus location (direct) or shape (symbolic). For the same goal, the spiking activity near reach onset was indistinguishable between the two tasks, and thus a reach goal decoder trained with spiking activity in one task performed perfectly in the other. In contrast, the LFP activity at 20-40 Hz showed small but significantly enhanced reach goal tuning in the symbolic task, but its spatial preference remained the same. Consequently, a decoder trained with LFP activity performed worse in the other task than in the same task. These results suggest that LFP decoders in PRR should take into account the task context (e.g., locational vs. nonlocational) to be accurate, while spike decoders can robustly provide reach goal information regardless of the task context in various prosthetic applications.

  4. The electric potential of tripolar spikes

    International Nuclear Information System (INIS)

    Nocera, L.

    2010-01-01

    We present an analytical formula for the waveform of the electric potential associated with a tripolar spike in a plasma. This formula is based on the construction and on the subsequent solution of a differential equation for the waveform. We work out this equation as a direct consequence of the morphological and functional properties of the observed waveform, without making any reference to the velocity distributions of the electrons and of the ions which sustain the spike. In the approximation of small potential amplitudes, we solve this equation by quadrature. In particular, in the second order approximation, the solution of this equation is given in terms of elementary functions. This analytical solution is able to reproduce the potential waveforms associated with electron holes, ion holes, monotonic and nonmonotonic double layers and tripolar spikes, in excellent agreement with observations.

  5. Analog frontend for multichannel neuronal recording system with spike and LFP separation.

    Science.gov (United States)

    Perelman, Yevgeny; Ginosar, Ran

    2006-05-15

    A 0.35microm CMOS integrated circuit for multi-channel neuronal recording with twelve true-differential channels, band separation and digital offset calibration is presented. The measured signal is separated into a low-frequency local field potential and high-frequency spike data. Digitally programmable gains of up to 60 and 80 dB for the local field potential and spike bands are provided. DC offsets are compensated on both bands by means of digitally programmable DACs. Spike band is limited by a second order low-pass filter with digitally programmable cutoff frequency. The IC has been fabricated and tested. 3microV input referred noise on the spike data band was measured.

  6. The Site of Spontaneous Ectopic Spike Initiation Facilitates Signal Integration in a Sensory Neuron.

    Science.gov (United States)

    Städele, Carola; Stein, Wolfgang

    2016-06-22

    Essential to understanding the process of neuronal signal integration is the knowledge of where within a neuron action potentials (APs) are generated. Recent studies support the idea that the precise location where APs are initiated and the properties of spike initiation zones define the cell's information processing capabilities. Notably, the location of spike initiation can be modified homeostatically within neurons to adjust neuronal activity. Here we show that this potential mechanism for neuronal plasticity can also be exploited in a rapid and dynamic fashion. We tested whether dislocation of the spike initiation zone affects signal integration by studying ectopic spike initiation in the anterior gastric receptor neuron (AGR) of the stomatogastric nervous system of Cancer borealis Like many other vertebrate and invertebrate neurons, AGR can generate ectopic APs in regions distinct from the axon initial segment. Using voltage-sensitive dyes and electrophysiology, we determined that AGR's ectopic spike activity was consistently initiated in the neuropil region of the stomatogastric ganglion motor circuits. At least one neurite branched off the AGR axon in this area; and indeed, we found that AGR's ectopic spike activity was influenced by local motor neurons. This sensorimotor interaction was state-dependent in that focal axon modulation with the biogenic amine octopamine, abolished signal integration at the primary spike initiation zone by dislocating spike initiation to a distant region of the axon. We demonstrate that the site of ectopic spike initiation is important for signal integration and that axonal neuromodulation allows for a dynamic adjustment of signal integration. Although it is known that action potentials are initiated at specific sites in the axon, it remains to be determined how the precise location of action potential initiation affects neuronal activity and signal integration. We addressed this issue by studying ectopic spiking in the axon of

  7. Implementing Signature Neural Networks with Spiking Neurons.

    Science.gov (United States)

    Carrillo-Medina, José Luis; Latorre, Roberto

    2016-01-01

    Spiking Neural Networks constitute the most promising approach to develop realistic Artificial Neural Networks (ANNs). Unlike traditional firing rate-based paradigms, information coding in spiking models is based on the precise timing of individual spikes. It has been demonstrated that spiking ANNs can be successfully and efficiently applied to multiple realistic problems solvable with traditional strategies (e.g., data classification or pattern recognition). In recent years, major breakthroughs in neuroscience research have discovered new relevant computational principles in different living neural systems. Could ANNs benefit from some of these recent findings providing novel elements of inspiration? This is an intriguing question for the research community and the development of spiking ANNs including novel bio-inspired information coding and processing strategies is gaining attention. From this perspective, in this work, we adapt the core concepts of the recently proposed Signature Neural Network paradigm-i.e., neural signatures to identify each unit in the network, local information contextualization during the processing, and multicoding strategies for information propagation regarding the origin and the content of the data-to be employed in a spiking neural network. To the best of our knowledge, none of these mechanisms have been used yet in the context of ANNs of spiking neurons. This paper provides a proof-of-concept for their applicability in such networks. Computer simulations show that a simple network model like the discussed here exhibits complex self-organizing properties. The combination of multiple simultaneous encoding schemes allows the network to generate coexisting spatio-temporal patterns of activity encoding information in different spatio-temporal spaces. As a function of the network and/or intra-unit parameters shaping the corresponding encoding modality, different forms of competition among the evoked patterns can emerge even in the absence

  8. A 16-Channel Nonparametric Spike Detection ASIC Based on EC-PC Decomposition.

    Science.gov (United States)

    Wu, Tong; Xu, Jian; Lian, Yong; Khalili, Azam; Rastegarnia, Amir; Guan, Cuntai; Yang, Zhi

    2016-02-01

    In extracellular neural recording experiments, detecting neural spikes is an important step for reliable information decoding. A successful implementation in integrated circuits can achieve substantial data volume reduction, potentially enabling a wireless operation and closed-loop system. In this paper, we report a 16-channel neural spike detection chip based on a customized spike detection method named as exponential component-polynomial component (EC-PC) algorithm. This algorithm features a reliable prediction of spikes by applying a probability threshold. The chip takes raw data as input and outputs three data streams simultaneously: field potentials, band-pass filtered neural data, and spiking probability maps. The algorithm parameters are on-chip configured automatically based on input data, which avoids manual parameter tuning. The chip has been tested with both in vivo experiments for functional verification and bench-top experiments for quantitative performance assessment. The system has a total power consumption of 1.36 mW and occupies an area of 6.71 mm (2) for 16 channels. When tested on synthesized datasets with spikes and noise segments extracted from in vivo preparations and scaled according to required precisions, the chip outperforms other detectors. A credit card sized prototype board is developed to provide power and data management through a USB port.

  9. Span: spike pattern association neuron for learning spatio-temporal spike patterns.

    Science.gov (United States)

    Mohemmed, Ammar; Schliebs, Stefan; Matsuda, Satoshi; Kasabov, Nikola

    2012-08-01

    Spiking Neural Networks (SNN) were shown to be suitable tools for the processing of spatio-temporal information. However, due to their inherent complexity, the formulation of efficient supervised learning algorithms for SNN is difficult and remains an important problem in the research area. This article presents SPAN - a spiking neuron that is able to learn associations of arbitrary spike trains in a supervised fashion allowing the processing of spatio-temporal information encoded in the precise timing of spikes. The idea of the proposed algorithm is to transform spike trains during the learning phase into analog signals so that common mathematical operations can be performed on them. Using this conversion, it is possible to apply the well-known Widrow-Hoff rule directly to the transformed spike trains in order to adjust the synaptic weights and to achieve a desired input/output spike behavior of the neuron. In the presented experimental analysis, the proposed learning algorithm is evaluated regarding its learning capabilities, its memory capacity, its robustness to noisy stimuli and its classification performance. Differences and similarities of SPAN regarding two related algorithms, ReSuMe and Chronotron, are discussed.

  10. Improved SpikeProp for Using Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Falah Y. H. Ahmed

    2013-01-01

    Full Text Available A spiking neurons network encodes information in the timing of individual spike times. A novel supervised learning rule for SpikeProp is derived to overcome the discontinuities introduced by the spiking thresholding. This algorithm is based on an error-backpropagation learning rule suited for supervised learning of spiking neurons that use exact spike time coding. The SpikeProp is able to demonstrate the spiking neurons that can perform complex nonlinear classification in fast temporal coding. This study proposes enhancements of SpikeProp learning algorithm for supervised training of spiking networks which can deal with complex patterns. The proposed methods include the SpikeProp particle swarm optimization (PSO and angle driven dependency learning rate. These methods are presented to SpikeProp network for multilayer learning enhancement and weights optimization. Input and output patterns are encoded as spike trains of precisely timed spikes, and the network learns to transform the input trains into target output trains. With these enhancements, our proposed methods outperformed other conventional neural network architectures.

  11. Automatic online spike sorting with singular value decomposition and fuzzy C-mean clustering

    Directory of Open Access Journals (Sweden)

    Oliynyk Andriy

    2012-08-01

    Full Text Available Abstract Background Understanding how neurons contribute to perception, motor functions and cognition requires the reliable detection of spiking activity of individual neurons during a number of different experimental conditions. An important problem in computational neuroscience is thus to develop algorithms to automatically detect and sort the spiking activity of individual neurons from extracellular recordings. While many algorithms for spike sorting exist, the problem of accurate and fast online sorting still remains a challenging issue. Results Here we present a novel software tool, called FSPS (Fuzzy SPike Sorting, which is designed to optimize: (i fast and accurate detection, (ii offline sorting and (iii online classification of neuronal spikes with very limited or null human intervention. The method is based on a combination of Singular Value Decomposition for fast and highly accurate pre-processing of spike shapes, unsupervised Fuzzy C-mean, high-resolution alignment of extracted spike waveforms, optimal selection of the number of features to retain, automatic identification the number of clusters, and quantitative quality assessment of resulting clusters independent on their size. After being trained on a short testing data stream, the method can reliably perform supervised online classification and monitoring of single neuron activity. The generalized procedure has been implemented in our FSPS spike sorting software (available free for non-commercial academic applications at the address: http://www.spikesorting.com using LabVIEW (National Instruments, USA. We evaluated the performance of our algorithm both on benchmark simulated datasets with different levels of background noise and on real extracellular recordings from premotor cortex of Macaque monkeys. The results of these tests showed an excellent accuracy in discriminating low-amplitude and overlapping spikes under strong background noise. The performance of our method is

  12. Automatic online spike sorting with singular value decomposition and fuzzy C-mean clustering.

    Science.gov (United States)

    Oliynyk, Andriy; Bonifazzi, Claudio; Montani, Fernando; Fadiga, Luciano

    2012-08-08

    Understanding how neurons contribute to perception, motor functions and cognition requires the reliable detection of spiking activity of individual neurons during a number of different experimental conditions. An important problem in computational neuroscience is thus to develop algorithms to automatically detect and sort the spiking activity of individual neurons from extracellular recordings. While many algorithms for spike sorting exist, the problem of accurate and fast online sorting still remains a challenging issue. Here we present a novel software tool, called FSPS (Fuzzy SPike Sorting), which is designed to optimize: (i) fast and accurate detection, (ii) offline sorting and (iii) online classification of neuronal spikes with very limited or null human intervention. The method is based on a combination of Singular Value Decomposition for fast and highly accurate pre-processing of spike shapes, unsupervised Fuzzy C-mean, high-resolution alignment of extracted spike waveforms, optimal selection of the number of features to retain, automatic identification the number of clusters, and quantitative quality assessment of resulting clusters independent on their size. After being trained on a short testing data stream, the method can reliably perform supervised online classification and monitoring of single neuron activity. The generalized procedure has been implemented in our FSPS spike sorting software (available free for non-commercial academic applications at the address: http://www.spikesorting.com) using LabVIEW (National Instruments, USA). We evaluated the performance of our algorithm both on benchmark simulated datasets with different levels of background noise and on real extracellular recordings from premotor cortex of Macaque monkeys. The results of these tests showed an excellent accuracy in discriminating low-amplitude and overlapping spikes under strong background noise. The performance of our method is competitive with respect to other robust spike

  13. Spike-timing theory of working memory.

    Directory of Open Access Journals (Sweden)

    Botond Szatmáry

    Full Text Available Working memory (WM is the part of the brain's memory system that provides temporary storage and manipulation of information necessary for cognition. Although WM has limited capacity at any given time, it has vast memory content in the sense that it acts on the brain's nearly infinite repertoire of lifetime long-term memories. Using simulations, we show that large memory content and WM functionality emerge spontaneously if we take the spike-timing nature of neuronal processing into account. Here, memories are represented by extensively overlapping groups of neurons that exhibit stereotypical time-locked spatiotemporal spike-timing patterns, called polychronous patterns; and synapses forming such polychronous neuronal groups (PNGs are subject to associative synaptic plasticity in the form of both long-term and short-term spike-timing dependent plasticity. While long-term potentiation is essential in PNG formation, we show how short-term plasticity can temporarily strengthen the synapses of selected PNGs and lead to an increase in the spontaneous reactivation rate of these PNGs. This increased reactivation rate, consistent with in vivo recordings during WM tasks, results in high interspike interval variability and irregular, yet systematically changing, elevated firing rate profiles within the neurons of the selected PNGs. Additionally, our theory explains the relationship between such slowly changing firing rates and precisely timed spikes, and it reveals a novel relationship between WM and the perception of time on the order of seconds.

  14. Physics of volleyball: Spiking with a purpose

    Science.gov (United States)

    Behroozi, F.

    1998-05-01

    A few weeks ago our volleyball coach telephoned me with a problem: How high should a player jump to "spike" a "set" ball so it would clear the net and land at a known distance on the other side of the net?

  15. Investment spikes in Dutch greenhouse horticulture

    NARCIS (Netherlands)

    Goncharova, N.; Oskam, A.; Oude Lansink, A.G.J.M.; Vlist, van der A.J.; Verstegen, J.A.A.M.

    2008-01-01

    The presence of investment cycles demonstrates the long-run policy of firms investing in particular periods (investment spikes) with lower or zero investment levels in between, which contradicts the smooth pattern predicted by a convex adjustment model. This paper investigates the spells between

  16. Food Price Spikes, Price Insulation, and Poverty

    OpenAIRE

    Anderson, Kym; Ivanic, Maros; Martin, Will

    2013-01-01

    This paper has two purposes. It first considers the impact on world food prices of the changes in restrictions on trade in staple foods during the 2008 world food price crisis. Those changes -- reductions in import protection or increases in export restraints -- were meant to partially insulate domestic markets from the spike in international prices. The authors find that this insulation a...

  17. Gymnosporia montana Benth.(Mountain Spike Thorn)

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 23; Issue 2. Gymnosporia montana Benth. (Mountain Spike Thorn). Flowering Trees Volume 23 Issue 2 February 2018 pp 245-245. Fulltext. Click here to view fulltext PDF. Permanent link: http://www.ias.ac.in/article/fulltext/reso/023/02/0245-0245 ...

  18. Techniques for Handling Channeling in High Resolution Fourier Transform Spectra Recorded with Synchrotron Sources

    International Nuclear Information System (INIS)

    Ibrahim, Amr; PredoiCross, Adriana; Teillet, P. M.

    2010-01-01

    Seven different techniques in dealing the problem of channel spectra in Fourier transform Spectroscopy utilizing synchrotron source were examined and compared. Five of these techniques deal with the artifacts (spikes) in the recorded interferogram which in turn result in channel spectra within the spectral domain. Such interferogram editing method include replacing these spikes with zeros, straight line, fitted polynomial curve, rescaled spike and spike reduced with Gauss Function. Another two techniques try to target this issue in the spectral domain instead by either generating a synthetic background simulating the channels or measuring the channels parameters (amplitude, spacing and phase) to use in the spectral fitting program. Results showed spectral domain techniques produces higher quality results in terms of signal to noise and fitting residual. The effect of each method on the line parameters such as position, intensity are air broadening are also measured and discussed.

  19. Frequency Band Separability Feature Extraction Method With Weighted Haar Wavelet Implementation for Implantable Spike Sorting.

    Science.gov (United States)

    Yang, Yuning; Mason, Andrew J

    2017-06-01

    Hardware-efficient feature extraction is an important step for real-time and on-chip spike sorting. Based on an analysis of spike energy spectrum, a new feature set is developed using the positive and negative spike peaks in low and high frequency bands. A separability metric that evaluates the informativeness and noise sensitivity of features is introduced to optimize the cutoff frequency of each band. Haar-based discrete wavelet transform was chosen to implement memory- and hardware-efficient filters for extracting frequency band separability features. Specifically, peaks from the first level detail and the fourth level approximation were used to represent a spike. To improve clustering performance, the detail features were weighted into the same dynamic range as the approximation features. The new feature extraction method was tested at different signal-to-noise ratios using synthesized datasets consisting of considerable and various spike shapes extracted from real neural recordings. The results show that the new method has 3%-10% better spike sorting performance than other hardware-efficient methods while consuming comparable hardware resources.

  20. Spiking Neural P Systems with Communication on Request.

    Science.gov (United States)

    Pan, Linqiang; Păun, Gheorghe; Zhang, Gexiang; Neri, Ferrante

    2017-12-01

    Spiking Neural [Formula: see text] Systems are Neural System models characterized by the fact that each neuron mimics a biological cell and the communication between neurons is based on spikes. In the Spiking Neural [Formula: see text] systems investigated so far, the application of evolution rules depends on the contents of a neuron (checked by means of a regular expression). In these [Formula: see text] systems, a specified number of spikes are consumed and a specified number of spikes are produced, and then sent to each of the neurons linked by a synapse to the evolving neuron. [Formula: see text]In the present work, a novel communication strategy among neurons of Spiking Neural [Formula: see text] Systems is proposed. In the resulting models, called Spiking Neural [Formula: see text] Systems with Communication on Request, the spikes are requested from neighboring neurons, depending on the contents of the neuron (still checked by means of a regular expression). Unlike the traditional Spiking Neural [Formula: see text] systems, no spikes are consumed or created: the spikes are only moved along synapses and replicated (when two or more neurons request the contents of the same neuron). [Formula: see text]The Spiking Neural [Formula: see text] Systems with Communication on Request are proved to be computationally universal, that is, equivalent with Turing machines as long as two types of spikes are used. Following this work, further research questions are listed to be open problems.

  1. Impact of spike train autostructure on probability distribution of joint spike events.

    Science.gov (United States)

    Pipa, Gordon; Grün, Sonja; van Vreeswijk, Carl

    2013-05-01

    The discussion whether temporally coordinated spiking activity really exists and whether it is relevant has been heated over the past few years. To investigate this issue, several approaches have been taken to determine whether synchronized events occur significantly above chance, that is, whether they occur more often than expected if the neurons fire independently. Most investigations ignore or destroy the autostructure of the spiking activity of individual cells or assume Poissonian spiking as a model. Such methods that ignore the autostructure can significantly bias the coincidence statistics. Here, we study the influence of the autostructure on the probability distribution of coincident spiking events between tuples of mutually independent non-Poisson renewal processes. In particular, we consider two types of renewal processes that were suggested as appropriate models of experimental spike trains: a gamma and a log-normal process. For a gamma process, we characterize the shape of the distribution analytically with the Fano factor (FFc). In addition, we perform Monte Carlo estimations to derive the full shape of the distribution and the probability for false positives if a different process type is assumed as was actually present. We also determine how manipulations of such spike trains, here dithering, used for the generation of surrogate data change the distribution of coincident events and influence the significance estimation. We find, first, that the width of the coincidence count distribution and its FFc depend critically and in a nontrivial way on the detailed properties of the structure of the spike trains as characterized by the coefficient of variation CV. Second, the dependence of the FFc on the CV is complex and mostly nonmonotonic. Third, spike dithering, even if as small as a fraction of the interspike interval, can falsify the inference on coordinated firing.

  2. Spike detection algorithm improvement, spike waveforms projections with PCA and hierarchical classification

    OpenAIRE

    Biffi, Emilia; Ghezzi, Diego; Pedrocchi, Alessandra; Ferrigno, Giancarlo

    2008-01-01

    Definition of single spikes from multiunit spike trains plays a critical role in neurophysiology and in neuroengineering. Moreover, long period analysis are needed to study synaptic plasticity effects and observe the long and medium term development on which all central nervous system (CNS) learning functions are based. Therefore, the increasing importance of long period recordings makes necessary on-line and real time analysis, memory use optimization and data transmission rate improvement. ...

  3. Stochastic spike synchronization in a small-world neural network with spike-timing-dependent plasticity.

    Science.gov (United States)

    Kim, Sang-Yoon; Lim, Woochang

    2018-01-01

    We consider the Watts-Strogatz small-world network (SWN) consisting of subthreshold neurons which exhibit noise-induced spikings. This neuronal network has adaptive dynamic synaptic strengths governed by the spike-timing-dependent plasticity (STDP). In previous works without STDP, stochastic spike synchronization (SSS) between noise-induced spikings of subthreshold neurons was found to occur in a range of intermediate noise intensities. Here, we investigate the effect of additive STDP on the SSS by varying the noise intensity. Occurrence of a "Matthew" effect in synaptic plasticity is found due to a positive feedback process. As a result, good synchronization gets better via long-term potentiation of synaptic strengths, while bad synchronization gets worse via long-term depression. Emergences of long-term potentiation and long-term depression of synaptic strengths are intensively investigated via microscopic studies based on the pair-correlations between the pre- and the post-synaptic IISRs (instantaneous individual spike rates) as well as the distributions of time delays between the pre- and the post-synaptic spike times. Furthermore, the effects of multiplicative STDP (which depends on states) on the SSS are studied and discussed in comparison with the case of additive STDP (independent of states). These effects of STDP on the SSS in the SWN are also compared with those in the regular lattice and the random graph. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Composite load spectra for select space propulsion structural components

    Science.gov (United States)

    Newell, J. F.; Ho, H. W.; Kurth, R. E.

    1991-01-01

    The work performed to develop composite load spectra (CLS) for the Space Shuttle Main Engine (SSME) using probabilistic methods. The three methods were implemented to be the engine system influence model. RASCAL was chosen to be the principal method as most component load models were implemented with the method. Validation of RASCAL was performed. High accuracy comparable to the Monte Carlo method can be obtained if a large enough bin size is used. Generic probabilistic models were developed and implemented for load calculations using the probabilistic methods discussed above. Each engine mission, either a real fighter or a test, has three mission phases: the engine start transient phase, the steady state phase, and the engine cut off transient phase. Power level and engine operating inlet conditions change during a mission. The load calculation module provides the steady-state and quasi-steady state calculation procedures with duty-cycle-data option. The quasi-steady state procedure is for engine transient phase calculations. In addition, a few generic probabilistic load models were also developed for specific conditions. These include the fixed transient spike model, the poison arrival transient spike model, and the rare event model. These generic probabilistic load models provide sufficient latitude for simulating loads with specific conditions. For SSME components, turbine blades, transfer ducts, LOX post, and the high pressure oxidizer turbopump (HPOTP) discharge duct were selected for application of the CLS program. They include static pressure loads and dynamic pressure loads for all four components, centrifugal force for the turbine blade, temperatures of thermal loads for all four components, and structural vibration loads for the ducts and LOX posts.

  5. Automatic spike sorting for extracellular electrophysiological recording using unsupervised single linkage clustering based on grey relational analysis

    Science.gov (United States)

    Lai, Hsin-Yi; Chen, You-Yin; Lin, Sheng-Huang; Lo, Yu-Chun; Tsang, Siny; Chen, Shin-Yuan; Zhao, Wan-Ting; Chao, Wen-Hung; Chang, Yao-Chuan; Wu, Robby; Shih, Yen-Yu I.; Tsai, Sheng-Tsung; Jaw, Fu-Shan

    2011-06-01

    Automatic spike sorting is a prerequisite for neuroscience research on multichannel extracellular recordings of neuronal activity. A novel spike sorting framework, combining efficient feature extraction and an unsupervised clustering method, is described here. Wavelet transform (WT) is adopted to extract features from each detected spike, and the Kolmogorov-Smirnov test (KS test) is utilized to select discriminative wavelet coefficients from the extracted features. Next, an unsupervised single linkage clustering method based on grey relational analysis (GSLC) is applied for spike clustering. The GSLC uses the grey relational grade as the similarity measure, instead of the Euclidean distance for distance calculation; the number of clusters is automatically determined by the elbow criterion in the threshold-cumulative distribution. Four simulated data sets with four noise levels and electrophysiological data recorded from the subthalamic nucleus of eight patients with Parkinson's disease during deep brain stimulation surgery are used to evaluate the performance of GSLC. Feature extraction results from the use of WT with the KS test indicate a reduced number of feature coefficients, as well as good noise rejection, despite similar spike waveforms. Accordingly, the use of GSLC for spike sorting achieves high classification accuracy in all simulated data sets. Moreover, J-measure results in the electrophysiological data indicating that the quality of spike sorting is adequate with the use of GSLC.

  6. Barbed micro-spikes for micro-scale biopsy

    Science.gov (United States)

    Byun, Sangwon; Lim, Jung-Min; Paik, Seung-Joon; Lee, Ahra; Koo, Kyo-in; Park, Sunkil; Park, Jaehong; Choi, Byoung-Doo; Seo, Jong Mo; Kim, Kyung-ah; Chung, Hum; Song, Si Young; Jeon, Doyoung; Cho, Dongil

    2005-06-01

    Single-crystal silicon planar micro-spikes with protruding barbs are developed for micro-scale biopsy and the feasibility of using the micro-spike as a micro-scale biopsy tool is evaluated for the first time. The fabrication process utilizes a deep silicon etch to define the micro-spike outline, resulting in protruding barbs of various shapes. Shanks of the fabricated micro-spikes are 3 mm long, 100 µm thick and 250 µm wide. Barbs protruding from micro-spike shanks facilitate the biopsy procedure by tearing off and retaining samples from target tissues. Micro-spikes with barbs successfully extracted tissue samples from the small intestines of the anesthetized pig, whereas micro-spikes without barbs failed to obtain a biopsy sample. Parylene coating can be applied to improve the biocompatibility of the micro-spike without deteriorating the biopsy function of the micro-spike. In addition, to show that the biopsy with the micro-spike can be applied to tissue analysis, samples obtained by micro-spikes were examined using immunofluorescent staining. Nuclei and F-actin of cells which are extracted by the micro-spike from a transwell were clearly visualized by immunofluorescent staining.

  7. The Mutation Frequency in Different Spike Categories in Barley

    DEFF Research Database (Denmark)

    Frydenberg, O.; Doll, Hans; Sandfær, J.

    1964-01-01

    After gamma irradiation of barley seeds, a comparison has been made between the chlorophyll-mutant frequencies in X1 spikes that had multicellular bud meristems in the seeds at the time of treatment (denoted as pre-formed spikes) and X1 spikes having no recognizable meristems at the time...

  8. Thermal impact on spiking properties in Hodgkin–Huxley neuron ...

    Indian Academy of Sciences (India)

    Abstract. The effect of environmental temperature on neuronal spiking behaviors is investigated by numerically simulating the temperature dependence of spiking threshold of the Hodgkin–Huxley neuron subject to synaptic stimulus. We find that the spiking threshold exhibits a global minimum in a specific temperature range ...

  9. Cytoplasmic tail of Coronavirus spike protein has intracellular ...

    Indian Academy of Sciences (India)

    58

    Transfection ability of YFP tagged spike protein constructs are much more efficient. 220 compared to wild type spike construct, the reasons for which are unclear (data not. 221 shown). Because of efficient detection of YFP fluorescence and the limitations of spike. 222 specific antibodies, we decided to use the YFP tagged ...

  10. Clinical value of magnetoencephalographic spike propagation represented by spatiotemporal source analysis: correlation with surgical outcome.

    Science.gov (United States)

    Tanaka, Naoaki; Peters, Jurriaan M; Prohl, Anna K; Takaya, Shigetoshi; Madsen, Joseph R; Bourgeois, Blaise F; Dworetzky, Barbara A; Hämäläinen, Matti S; Stufflebeam, Steven M

    2014-02-01

    To investigate the correlation between spike propagation represented by spatiotemporal source analysis of magnetoencephalographic (MEG) spikes and surgical outcome in patients with temporal lobe epilepsy. Thirty-seven patients were divided into mesial (n=27) and non-mesial (n=10) groups based on the presurgical evaluation. In each patient, ten ipsilateral spikes were averaged, and spatiotemporal source maps of the averaged spike were obtained by using minimum norm estimate. Regions of interest (ROIs) were created including temporoparietal, inferior frontal, mesial temporal, anterior and posterior part of the lateral temporal cortex. We extracted activation values from the source maps and the threshold was set at half of the maximum activation at the peak latency. The leading and propagated areas of the spike were defined as those ROIs with activation reaching the threshold at the earliest and at the peak latencies, respectively. Surgical outcome was assessed based on Engel's classification. Binary variables were created from leading areas (restricted to the anterior and mesial temporal ROIs or not) and from propagation areas (involving the temporoparietal ROI or not), and for surgical outcome (Class I or not). Fisher's exact test was used for significance testing. In total and mesial group, restricted anterior/mesial temporal leading areas were correlated with Class I (p<0.05). Temporoparietal propagation was correlated with Class II-IV (p<0.05). For the non-mesial group, no significant relation was found. Spike propagation patterns represented by spatiotemporal source analysis of MEG spikes may provide useful information for prognostic implication in presurgical evaluation of epilepsy. Copyright © 2013 Elsevier B.V. All rights reserved.

  11. Spiked instantons from intersecting D-branes

    Directory of Open Access Journals (Sweden)

    Nikita Nekrasov

    2017-01-01

    Full Text Available The moduli space of spiked instantons that arises in the context of the BPS/CFT correspondence [22] is realised as the moduli space of classical vacua, i.e. low-energy open string field configurations, of a certain stack of intersecting D1-branes and D5-branes in Type IIB string theory. The presence of a constant B-field induces an interesting dynamics involving the tachyon condensation.

  12. Non-singular spiked harmonic oscillator

    International Nuclear Information System (INIS)

    Aguilera-Navarro, V.C.; Guardiola, R.

    1990-01-01

    A perturbative study of a class of non-singular spiked harmonic oscillators defined by the hamiltonian H = d sup(2)/dr sup(2) + r sup(2) + λ/r sup(α) in the domain [0,∞] is carried out, in the two extremes of a weak coupling and a strong coupling regimes. A path has been found to connect both expansions for α near 2. (author)

  13. Basalt FRP Spike Repairing of Wood Beams

    Directory of Open Access Journals (Sweden)

    Luca Righetti

    2015-08-01

    Full Text Available This article describes aspects within an experimental program aimed at improving the structural performance of cracked solid fir-wood beams repaired with Basalt Fiber Reinforced Polymer (BFRP spikes. Fir wood is characterized by its low density, low compression strength, and high level of defects, and it is likely to distort when dried and tends to fail under tension due to the presence of cracks, knots, or grain deviation. The proposed repair technique consists of the insertion of BFRP spikes into timber beams to restore the continuity of cracked sections. The experimental efforts deal with the evaluation of the bending strength and deformation properties of 24 timber beams. An artificially simulated cracking was produced by cutting the wood beams in half or notching. The obtained results for the repaired beams were compared with those of solid undamaged and damaged beams, and increases of beam capacity, bending strength and of modulus of elasticity, and analysis of failure modes was discussed. For notched beams, the application of the BFRP spikes was able to restore the original bending capacity of undamaged beams, while only a small part of the original capacity was recovered for beams that were cut in half.

  14. Spiking Neural P Systems With Scheduled Synapses.

    Science.gov (United States)

    Cabarle, Francis George C; Adorna, Henry N; Jiang, Min; Zeng, Xiangxiang

    2017-12-01

    Spiking neural P systems (SN P systems) are models of computation inspired by biological spiking neurons. SN P systems have neurons as spike processors, which are placed on the nodes of a directed and static graph (the edges in the graph are the synapses). In this paper, we introduce a variant called SN P systems with scheduled synapses (SSN P systems). SSN P systems are inspired and motivated by the structural dynamism of biological synapses, while incorporating ideas from nonstatic (i.e., dynamic) graphs and networks. In particular, synapses in SSN P systems are available only at specific durations according to their schedules. The SSN P systems model is a response to the problem of introducing durations to synapses of SN P systems. Since SN P systems are in essence static graphs, it is natural to consider them for dynamic graphs also. We introduce local and global schedule types, also taking inspiration from the above-mentioned sources. We prove that SSN P systems are computationally universal as number generators and acceptors for both schedule types, under a normal form (i.e., a simplifying set of restrictions). The introduction of synapse schedules for either schedule type proves useful in programming the system, despite restrictions in the normal form.

  15. SWAT: a spiking neural network training algorithm for classification problems.

    Science.gov (United States)

    Wade, John J; McDaid, Liam J; Santos, Jose A; Sayers, Heather M

    2010-11-01

    This paper presents a synaptic weight association training (SWAT) algorithm for spiking neural networks (SNNs). SWAT merges the Bienenstock-Cooper-Munro (BCM) learning rule with spike timing dependent plasticity (STDP). The STDP/BCM rule yields a unimodal weight distribution where the height of the plasticity window associated with STDP is modulated causing stability after a period of training. The SNN uses a single training neuron in the training phase where data associated with all classes is passed to this neuron. The rule then maps weights to the classifying output neurons to reflect similarities in the data across the classes. The SNN also includes both excitatory and inhibitory facilitating synapses which create a frequency routing capability allowing the information presented to the network to be routed to different hidden layer neurons. A variable neuron threshold level simulates the refractory period. SWAT is initially benchmarked against the nonlinearly separable Iris and Wisconsin Breast Cancer datasets. Results presented show that the proposed training algorithm exhibits a convergence accuracy of 95.5% and 96.2% for the Iris and Wisconsin training sets, respectively, and 95.3% and 96.7% for the testing sets, noise experiments show that SWAT has a good generalization capability. SWAT is also benchmarked using an isolated digit automatic speech recognition (ASR) system where a subset of the TI46 speech corpus is used. Results show that with SWAT as the classifier, the ASR system provides an accuracy of 98.875% for training and 95.25% for testing.

  16. Precise-Spike-Driven Synaptic Plasticity: Learning Hetero-Association of Spatiotemporal Spike Patterns

    Science.gov (United States)

    Yu, Qiang; Tang, Huajin; Tan, Kay Chen; Li, Haizhou

    2013-01-01

    A new learning rule (Precise-Spike-Driven (PSD) Synaptic Plasticity) is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe. PMID:24223789

  17. Precise-spike-driven synaptic plasticity: learning hetero-association of spatiotemporal spike patterns.

    Directory of Open Access Journals (Sweden)

    Qiang Yu

    Full Text Available A new learning rule (Precise-Spike-Driven (PSD Synaptic Plasticity is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe.

  18. Precise-spike-driven synaptic plasticity: learning hetero-association of spatiotemporal spike patterns.

    Science.gov (United States)

    Yu, Qiang; Tang, Huajin; Tan, Kay Chen; Li, Haizhou

    2013-01-01

    A new learning rule (Precise-Spike-Driven (PSD) Synaptic Plasticity) is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe.

  19. Nicotine-Mediated ADP to Spike Transition: Double Spiking in Septal Neurons.

    Science.gov (United States)

    Kodirov, Sodikdjon A; Wehrmeister, Michael; Colom, Luis

    2016-04-01

    The majority of neurons in lateral septum (LS) are electrically silent at resting membrane potential. Nicotine transiently excites a subset of neurons and occasionally leads to long lasting bursting activity upon longer applications. We have observed simultaneous changes in frequencies and amplitudes of spontaneous action potentials (AP) in the presence of nicotine. During the prolonged exposure, nicotine increased numbers of spikes within a burst. One of the hallmarks of nicotine effects was the occurrences of double spikes (known also as bursting). Alignment of 51 spontaneous spikes, triggered upon continuous application of nicotine, revealed that the slope of after-depolarizing potential gradually increased (1.4 vs. 3 mV/ms) and neuron fired the second AP, termed as double spiking. A transition from a single AP to double spikes increased the amplitude of after-hyperpolarizing potential. The amplitude of the second (premature) AP was smaller compared to the first one, and this correlation persisted in regard to their duration (half-width). A similar bursting activity in the presence of nicotine, to our knowledge, has not been reported previously in the septal structure in general and in LS in particular.

  20. Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling

    Science.gov (United States)

    Keshtkaran, Mohammad Reza; Yang, Zhi

    2017-06-01

    Objective. Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. Approach. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Main results. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. Significance. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

  1. Spike avalanches exhibit universal dynamics across the sleep-wake cycle.

    Directory of Open Access Journals (Sweden)

    Tiago L Ribeiro

    2010-11-01

    Full Text Available Scale-invariant neuronal avalanches have been observed in cell cultures and slices as well as anesthetized and awake brains, suggesting that the brain operates near criticality, i.e. within a narrow margin between avalanche propagation and extinction. In theory, criticality provides many desirable features for the behaving brain, optimizing computational capabilities, information transmission, sensitivity to sensory stimuli and size of memory repertoires. However, a thorough characterization of neuronal avalanches in freely-behaving (FB animals is still missing, thus raising doubts about their relevance for brain function.To address this issue, we employed chronically implanted multielectrode arrays (MEA to record avalanches of action potentials (spikes from the cerebral cortex and hippocampus of 14 rats, as they spontaneously traversed the wake-sleep cycle, explored novel objects or were subjected to anesthesia (AN. We then modeled spike avalanches to evaluate the impact of sparse MEA sampling on their statistics. We found that the size distribution of spike avalanches are well fit by lognormal distributions in FB animals, and by truncated power laws in the AN group. FB data surrogation markedly decreases the tail of the distribution, i.e. spike shuffling destroys the largest avalanches. The FB data are also characterized by multiple key features compatible with criticality in the temporal domain, such as 1/f spectra and long-term correlations as measured by detrended fluctuation analysis. These signatures are very stable across waking, slow-wave sleep and rapid-eye-movement sleep, but collapse during anesthesia. Likewise, waiting time distributions obey a single scaling function during all natural behavioral states, but not during anesthesia. Results are equivalent for neuronal ensembles recorded from visual and tactile areas of the cerebral cortex, as well as the hippocampus.Altogether, the data provide a comprehensive link between behavior

  2. Automatic identification of mass spectra

    International Nuclear Information System (INIS)

    Drabloes, F.

    1992-01-01

    Several approaches to preprocessing and comparison of low resolution mass spectra have been evaluated by various test methods related to library search. It is shown that there is a clear correlation between the nature of any contamination of a spectrum, the basic principle of the transformation or distance measure, and the performance of the identification system. The identification of functionality from low resolution spectra has also been evaluated using several classification methods. It is shown that there is an upper limit to the success of this approach, but also that this can be improved significantly by using a very limited amount of additional information. 10 refs

  3. Comparison of electrodialytic removal of Cu from spiked kaolinite, spiked soil and industrially polluted soil

    DEFF Research Database (Denmark)

    Ottosen, Lisbeth M.; Lepkova, Katarina; Kubal, Martin

    2006-01-01

    Electrokinetic remediation methods for removal of heavy metals from polluted soils have been subjected for quite intense research during the past years since these methods are well suitable for fine-grained soils where other remediation methods fail. Electrodialytic remediation is an electrokinetic...... remediation method which is based on applying an electric DC field and the use of ion exchange membranes that ensures the main transport of heavy metals to be out of the pollutes soil. An experimental investigation was made with electrodialytic removal of Cu from spiked kaolinite, spiked soil and industrially...... polluted soil under the same operational conditions (constant current density 0.2 mA/cm2 and duration 28 days). The results of the present paper show that caution must be taken when generalising results obtained in spiked kaolinite to remediation of industrially polluted soils, as it was shown...

  4. A high performing brain-machine interface driven by low-frequency local field potentials alone and together with spikes

    Science.gov (United States)

    Stavisky, Sergey D.; Kao, Jonathan C.; Nuyujukian, Paul; Ryu, Stephen I.; Shenoy, Krishna V.

    2015-06-01

    Objective. Brain-machine interfaces (BMIs) seek to enable people with movement disabilities to directly control prosthetic systems with their neural activity. Current high performance BMIs are driven by action potentials (spikes), but access to this signal often diminishes as sensors degrade over time. Decoding local field potentials (LFPs) as an alternative or complementary BMI control signal may improve performance when there is a paucity of spike signals. To date only a small handful of LFP decoding methods have been tested online; there remains a need to test different LFP decoding approaches and improve LFP-driven performance. There has also not been a reported demonstration of a hybrid BMI that decodes kinematics from both LFP and spikes. Here we first evaluate a BMI driven by the local motor potential (LMP), a low-pass filtered time-domain LFP amplitude feature. We then combine decoding of both LMP and spikes to implement a hybrid BMI. Approach. Spikes and LFP were recorded from two macaques implanted with multielectrode arrays in primary and premotor cortex while they performed a reaching task. We then evaluated closed-loop BMI control using biomimetic decoders driven by LMP, spikes, or both signals together. Main results. LMP decoding enabled quick and accurate cursor control which surpassed previously reported LFP BMI performance. Hybrid decoding of both spikes and LMP improved performance when spikes signal quality was mediocre to poor. Significance. These findings show that LMP is an effective BMI control signal which requires minimal power to extract and can substitute for or augment impoverished spikes signals. Use of this signal may lengthen the useful lifespan of BMIs and is therefore an important step towards clinically viable BMIs.

  5. Diallel analysis to study the genetic makeup of spike and yield ...

    African Journals Online (AJOL)

    Five wheat genotypes were crossed in complete diallel fashion for gene action studies of spike length, spikelets per spike, grains per spike, grain weight per spike ... High magnitude of narrow sense heritability (h2n.s) was noticed for spikelets per spike (79%), and grains per spike (88%) thus illustrated fixable and additive ...

  6. Mikkelson sweep/spike chisel plow shovel. Economic summary of the 1992 crop season

    Energy Technology Data Exchange (ETDEWEB)

    1992-12-31

    Profitability comparisons are reported between the Mikkelson Sweep/Spike Chisel Plow Shovel standard sweeps. This evaluation covers the first year of testing of the new Sweep/Spike design. The data are not averaged over treatments due to significant interaction between treatments and environmental factors. The cost of fuel, fall and spring, to perform the various treatments ranged from $1.27 to $3.36 per acre. Use of the sweep/spike shovel always reduced total fuel cost. Savings varied from $0.11 to $0.71 per acre depending on prior treatment. This means there will be money saved, to off-set expenses, when converting present chisel plows or for special options on new chisel plows, needed for use of the sweep/spike shovel. A summary of 1991--1992 energy measurements. They indicate that more power will be required to pull a chisel plow equipped with the sweep/spike shovel. A larger tractor, narrower chisel plow and/or slower speed will be required to avoid the wheel slippage problems encountered on soft or wet field surfaces.

  7. Extraction of temporally correlated features from dynamic vision sensors with spike-timing-dependent plasticity.

    Science.gov (United States)

    Bichler, Olivier; Querlioz, Damien; Thorpe, Simon J; Bourgoin, Jean-Philippe; Gamrat, Christian

    2012-08-01

    A biologically inspired approach to learning temporally correlated patterns from a spiking silicon retina is presented. Spikes are generated from the retina in response to relative changes in illumination at the pixel level and transmitted to a feed-forward spiking neural network. Neurons become sensitive to patterns of pixels with correlated activation times, in a fully unsupervised scheme. This is achieved using a special form of Spike-Timing-Dependent Plasticity which depresses synapses that did not recently contribute to the post-synaptic spike activation, regardless of their activation time. Competitive learning is implemented with lateral inhibition. When tested with real-life data, the system is able to extract complex and overlapping temporally correlated features such as car trajectories on a freeway, after only 10 min of traffic learning. Complete trajectories can be learned with a 98% detection rate using a second layer, still with unsupervised learning, and the system may be used as a car counter. The proposed neural network is extremely robust to noise and it can tolerate a high degree of synaptic and neuronal variability with little impact on performance. Such results show that a simple biologically inspired unsupervised learning scheme is capable of generating selectivity to complex meaningful events on the basis of relatively little sensory experience. Copyright © 2012 Elsevier Ltd. All rights reserved.

  8. Solving constraint satisfaction problems with networks of spiking neurons

    Directory of Open Access Journals (Sweden)

    Zeno eJonke

    2016-03-01

    Full Text Available Network of neurons in the brain apply – unlike processors in our current generation ofcomputer hardware – an event-based processing strategy, where short pulses (spikes areemitted sparsely by neurons to signal the occurrence of an event at a particular point intime. Such spike-based computations promise to be substantially more power-efficient thantraditional clocked processing schemes. However it turned out to be surprisingly difficult todesign networks of spiking neurons that can solve difficult computational problems on the levelof single spikes (rather than rates of spikes. We present here a new method for designingnetworks of spiking neurons via an energy function. Furthermore we show how the energyfunction of a network of stochastically firing neurons can be shaped in a quite transparentmanner by composing the networks of simple stereotypical network motifs. We show that thisdesign approach enables networks of spiking neurons to produce approximate solutions todifficult (NP-hard constraint satisfaction problems from the domains of planning/optimizationand verification/logical inference. The resulting networks employ noise as a computationalresource. Nevertheless the timing of spikes (rather than just spike rates plays an essential rolein their computations. Furthermore, networks of spiking neurons carry out for the Traveling Salesman Problem a more efficient stochastic search for good solutions compared with stochastic artificial neural networks (Boltzmann machines and Gibbs sampling.

  9. Is the thermal-spike model consistent with experimentally determined electron temperature?

    International Nuclear Information System (INIS)

    Ajryan, Eh.A.; Fedorov, A.V.; Kostenko, B.F.

    2000-01-01

    Carbon K-Auger electron spectra from amorphous carbon foils induced by fast heavy ions are theoretically investigated. The high-energy tail of the Auger structure showing a clear projectile charge dependence is analyzed within the thermal-spike model framework as well as in the frame of another model taking into account some kinetic features of the process. A poor comparison results between theoretically and experimentally determined temperatures are suggested to be due to an improper account of double electron excitations or due to shake-up processes which leave the system in a more energetic initial state than a statically screened core hole

  10. Spike-timing-dependent learning rule to encode spatiotemporal patterns in a network of spiking neurons

    Science.gov (United States)

    Yoshioka, Masahiko

    2002-01-01

    We study associative memory neural networks based on the Hodgkin-Huxley type of spiking neurons. We introduce the spike-timing-dependent learning rule, in which the time window with the negative part as well as the positive part is used to describe the biologically plausible synaptic plasticity. The learning rule is applied to encode a number of periodical spatiotemporal patterns, which are successfully reproduced in the periodical firing pattern of spiking neurons in the process of memory retrieval. The global inhibition is incorporated into the model so as to induce the gamma oscillation. The occurrence of gamma oscillation turns out to give appropriate spike timings for memory retrieval of discrete type of spatiotemporal pattern. The theoretical analysis to elucidate the stationary properties of perfect retrieval state is conducted in the limit of an infinite number of neurons and shows the good agreement with the result of numerical simulations. The result of this analysis indicates that the presence of the negative and positive parts in the form of the time window contributes to reduce the size of crosstalk term, implying that the time window with the negative and positive parts is suitable to encode a number of spatiotemporal patterns. We draw some phase diagrams, in which we find various types of phase transitions with change of the intensity of global inhibition.

  11. Phase Diagram of Spiking Neural Networks

    Directory of Open Access Journals (Sweden)

    Hamed eSeyed-Allaei

    2015-03-01

    Full Text Available In computer simulations of spiking neural networks, often it is assumed that every two neurons of the network are connected by a probablilty of 2%, 20% of neurons are inhibitory and 80% are excitatory. These common values are based on experiments, observations. but here, I take a different perspective, inspired by evolution. I simulate many networks, each with a different set of parameters, and then I try to figure out what makes the common values desirable by nature. Networks which are configured according to the common values, have the best dynamic range in response to an impulse and their dynamic range is more robust in respect to synaptic weights. In fact, evolution has favored networks of best dynamic range. I present a phase diagram that shows the dynamic ranges of different networks of different parameteres. This phase diagram gives an insight into the space of parameters -- excitatory to inhibitory ratio, sparseness of connections and synaptic weights. It may serve as a guideline to decide about the values of parameters in a simulation of spiking neural network.

  12. Spiking Neural Network in Precision Agriculture

    Directory of Open Access Journals (Sweden)

    Nadia Adnan Shiltagh

    2015-07-01

    Full Text Available In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN. Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN. In this work, the precision agriculture system is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce power consumption of sensor nodes Modified Chain-Cluster based Mixed (MCCM routing algorithm is used. According to MCCM, the sensors will send their packets that are less than threshold moisture level to the sink. The SNN with Modified Spike-Prop (MSP training algorithm is capable of identifying soil, irrigation periods and monitoring the soil moisture level, this means that SNN has the ability to be an identifier and monitor. By applying this system the particular agriculture area reaches to the desired moisture level.

  13. An Overview of Bayesian Methods for Neural Spike Train Analysis

    Directory of Open Access Journals (Sweden)

    Zhe Chen

    2013-01-01

    Full Text Available Neural spike train analysis is an important task in computational neuroscience which aims to understand neural mechanisms and gain insights into neural circuits. With the advancement of multielectrode recording and imaging technologies, it has become increasingly demanding to develop statistical tools for analyzing large neuronal ensemble spike activity. Here we present a tutorial overview of Bayesian methods and their representative applications in neural spike train analysis, at both single neuron and population levels. On the theoretical side, we focus on various approximate Bayesian inference techniques as applied to latent state and parameter estimation. On the application side, the topics include spike sorting, tuning curve estimation, neural encoding and decoding, deconvolution of spike trains from calcium imaging signals, and inference of neuronal functional connectivity and synchrony. Some research challenges and opportunities for neural spike train analysis are discussed.

  14. A new supervised learning algorithm for spiking neurons.

    Science.gov (United States)

    Xu, Yan; Zeng, Xiaoqin; Zhong, Shuiming

    2013-06-01

    The purpose of supervised learning with temporal encoding for spiking neurons is to make the neurons emit a specific spike train encoded by the precise firing times of spikes. If only running time is considered, the supervised learning for a spiking neuron is equivalent to distinguishing the times of desired output spikes and the other time during the running process of the neuron through adjusting synaptic weights, which can be regarded as a classification problem. Based on this idea, this letter proposes a new supervised learning method for spiking neurons with temporal encoding; it first transforms the supervised learning into a classification problem and then solves the problem by using the perceptron learning rule. The experiment results show that the proposed method has higher learning accuracy and efficiency over the existing learning methods, so it is more powerful for solving complex and real-time problems.

  15. Effects of Spike Anticipation on the Spiking Dynamics of Neural Networks

    Directory of Open Access Journals (Sweden)

    Daniel ede Santos-Sierra

    2015-11-01

    Full Text Available Synchronization is one of the central phenomena involved in information processing in living systems. It is known that the nervous system requires the coordinated activity of both local and distant neural populations. Such an interplay allows to merge different information modalities in a whole processing supporting high-level mental skills as understanding, memory, abstraction, etc. Though the biological processes underlying synchronization in the brain are not fully understood there have been reported a variety of mechanisms supporting different types of synchronization both at theoretical and experimental level. One of the more intriguing of these phenomena is the anticipating synchronization, which has been recently reported in a pair of unidirectionally coupled artificial neurons under simple conditions cite{Pyragas}, where the slave neuron is able to anticipate in time the behaviour of the master one. In this paper we explore the effect of spike anticipation over the information processing performed by a neural network at functional and structural level. We show that the introduction of intermediary neurons in the network enhances spike anticipation and analyse how these variations in spike anticipation can significantly change the firing regime of the neural network according to its functional and structural properties. In addition we show that the interspike interval (ISI, one of the main features of the neural response associated to the information coding, can be closely related to spike anticipation by each spike, and how synaptic plasticity can be modulated through that relationship. This study has been performed through numerical simulation of a coupled system of Hindmarsh-Rose neurons.

  16. Spectra of Graphs

    NARCIS (Netherlands)

    Brouwer, A.E.; Haemers, W.H.

    2012-01-01

    This book gives an elementary treatment of the basic material about graph spectra, both for ordinary, and Laplace and Seidel spectra. The text progresses systematically, by covering standard topics before presenting some new material on trees, strongly regular graphs, two-graphs, association

  17. Spectra of alkali atoms

    International Nuclear Information System (INIS)

    Santoso, Budi; Arumbinang, Haryono.

    1981-01-01

    Emission spectra of alkali atoms has been determined by using spectrometer at the ultraviolet to infra red waves range. The spectra emission can be obtained by absorption spectrophotometric analysis. Comparative evaluations between experimental data and data handbook obtained by spark method were also presented. (author tr.)

  18. The past and the future of Alzheimer’s disease CSF biomarkers – a journey towards validated biochemical tests covering the whole spectra of molecular events

    Directory of Open Access Journals (Sweden)

    Kaj eBlennow

    2015-09-01

    Full Text Available This paper gives a short review on cerebrospinal fluid (CSF biomarkers for Alzheimer’s disease (AD, from early developments to high-precision validated assays on fully automated lab analyzers. We also discuss developments on novel biomarkers, such as synaptic proteins and Aβ oligomers. Our vision for the future is that assaying a set of biomarkers in a single CSF tube can monitor the whole spectra of AD molecular pathogenic events. CSF biomarkers will have a central position not only for clinical diagnosis, but also for the understanding of the sequence of molecular events in the pathogenic process underlying AD and as tools to monitor the effects of novel drug candidates targeting these different mechanisms.

  19. Multimodal imaging of spike propagation: a technical case report.

    Science.gov (United States)

    Tanaka, N; Grant, P E; Suzuki, N; Madsen, J R; Bergin, A M; Hämäläinen, M S; Stufflebeam, S M

    2012-06-01

    We report an 11-year-old boy with intractable epilepsy, who had cortical dysplasia in the right superior frontal gyrus. Spatiotemporal source analysis of MEG and EEG spikes demonstrated a similar time course of spike propagation from the superior to inferior frontal gyri, as observed on intracranial EEG. The tractography reconstructed from DTI showed a fiber connection between these areas. Our multimodal approach demonstrates spike propagation and a white matter tract guiding the propagation.

  20. Spike timing precision in the visual front-end

    OpenAIRE

    Borghuis, B.G. (Bart Gerard)

    2003-01-01

    This thesis describes a series of investigations into the reliability of neural responses in the primary visual pathway. The results described in subsequent chapters are primarily based on extracellular recordings from single neurons in anaesthetized cats and area MT of an awake monkey, and computational model analysis. Comparison of spike timing precision in recorded and Poisson-simulated spike trains shows that spike timing in the front-end visual system is considerably more precise than on...

  1. Spike sorting for polytrodes: a divide and conquer approach

    OpenAIRE

    Swindale, Nicholas V.; Spacek, Martin A.

    2014-01-01

    In order to determine patterns of neural activity, spike signals recorded by extracellular electrodes have to be clustered (sorted) with the aim of ensuring that each cluster represents all the spikes generated by an individual neuron. Many methods for spike sorting have been proposed but few are easily applicable to recordings from polytrodes which may have 16 or more recording sites. As with tetrodes, these are spaced sufficiently closely that signals from single neurons will usually be rec...

  2. Spike correlations in a songbird agree with a simple markov population model.

    Directory of Open Access Journals (Sweden)

    Andrea P Weber

    2007-12-01

    Full Text Available The relationships between neural activity at the single-cell and the population levels are of central importance for understanding neural codes. In many sensory systems, collective behaviors in large cell groups can be described by pairwise spike correlations. Here, we test whether in a highly specialized premotor system of songbirds, pairwise spike correlations themselves can be seen as a simple corollary of an underlying random process. We test hypotheses on connectivity and network dynamics in the motor pathway of zebra finches using a high-level population model that is independent of detailed single-neuron properties. We assume that neural population activity evolves along a finite set of states during singing, and that during sleep population activity randomly switches back and forth between song states and a single resting state. Individual spike trains are generated by associating with each of the population states a particular firing mode, such as bursting or tonic firing. With an overall modification of one or two simple control parameters, the Markov model is able to reproduce observed firing statistics and spike correlations in different neuron types and behavioral states. Our results suggest that song- and sleep-related firing patterns are identical on short time scales and result from random sampling of a unique underlying theme. The efficiency of our population model may apply also to other neural systems in which population hypotheses can be tested on recordings from small neuron groups.

  3. Spike Frequency Adaptation in Neurons of the Central Nervous System.

    Science.gov (United States)

    Ha, Go Eun; Cheong, Eunji

    2017-08-01

    Neuronal firing patterns and frequencies determine the nature of encoded information of the neurons. Here we discuss the molecular identity and cellular mechanisms of spike-frequency adaptation in central nervous system (CNS) neurons. Calcium-activated potassium (K Ca ) channels such as BK Ca and SK Ca channels have long been known to be important mediators of spike adaptation via generation of a large afterhyperpolarization when neurons are hyper-activated. However, it has been shown that a strong hyperpolarization via these K Ca channels would cease action potential generation rather than reducing the frequency of spike generation. In some types of neurons, the strong hyperpolarization is followed by oscillatory activity in these neurons. Recently, spike-frequency adaptation in thalamocortical (TC) and CA1 hippocampal neurons is shown to be mediated by the Ca 2+ -activated Cl- channel (CACC), anoctamin-2 (ANO2). Knockdown of ANO2 in these neurons results in significantly reduced spike-frequency adaptation accompanied by increased number of spikes without shifting the firing mode, which suggests that ANO2 mediates a genuine form of spike adaptation, finely tuning the frequency of spikes in these neurons. Based on the finding of a broad expression of this new class of CACC in the brain, it can be proposed that the ANO2-mediated spike-frequency adaptation may be a general mechanism to control information transmission in the CNS neurons.

  4. Comparison of neuronal spike exchange methods on a Blue Gene/P supercomputer

    Directory of Open Access Journals (Sweden)

    Michael eHines

    2011-11-01

    Full Text Available The performance of several spike exchange methods using a Blue Gene/P supercomputerhas been tested with 8K to 128K cores using randomly connected networks of up to 32M cells with 1k connections per cell and 4M cells with 10k connections per cell. The spike exchange methods used are the standard Message Passing Interface collective, MPI_Allgather, and several variants of the non-blocking multisend method either implemented via non-blocking MPI_Isend, or exploiting the possibility of very low overhead direct memory access communication available on the Blue Gene/P. In all cases the worst performing method was that using MPI_Isend due to the high overhead of initiating a spike communication. The two best performing methods --- the persistent multisend method using the Record-Replay feature of the Deep Computing Messaging Framework DCMF_Multicast;and a two phase multisend in which a DCMF_Multicast is used to first send to a subset of phase 1 destination cores which then pass it on to their subset of phase 2 destination cores --- had similar performance with very low overhead for the initiation of spike communication. Departure from ideal scaling for the multisend methods is almost completely due to load imbalance caused by the largevariation in number of cells that fire on each processor in the interval between synchronization. Spike exchange time itself is negligible since transmission overlaps with computation and is handled by a direct memory access controller. We conclude that ideal performance scaling will be ultimately limited by imbalance between incoming processor spikes between synchronization intervals. Thus, counterintuitively, maximization of load balance requires that the distribution of cells on processors should not reflect neural net architecture but be randomly distributed so that sets of cells which are burst firing together should be on different processors with their targets on as large a set of processors as possible.

  5. Attention deficit associated with early life interictal spikes in a rat model is improved with ACTH.

    Directory of Open Access Journals (Sweden)

    Amanda E Hernan

    Full Text Available Children with epilepsy often present with pervasive cognitive and behavioral comorbidities including working memory impairments, attention deficit hyperactivity disorder (ADHD and autism spectrum disorder. These non-seizure characteristics are severely detrimental to overall quality of life. Some of these children, particularly those with epilepsies classified as Landau-Kleffner Syndrome or continuous spike and wave during sleep, have infrequent seizure activity but frequent focal epileptiform activity. This frequent epileptiform activity is thought to be detrimental to cognitive development; however, it is also possible that these IIS events initiate pathophysiological pathways in the developing brain that may be independently associated with cognitive deficits. These hypotheses are difficult to address due to the previous lack of an appropriate animal model. To this end, we have recently developed a rat model to test the role of frequent focal epileptiform activity in the prefrontal cortex. Using microinjections of a GABA(A antagonist (bicuculline methiodine delivered multiple times per day from postnatal day (p 21 to p25, we showed that rat pups experiencing frequent, focal, recurrent epileptiform activity in the form of interictal spikes during neurodevelopment have significant long-term deficits in attention and sociability that persist into adulthood. To determine if treatment with ACTH, a drug widely used to treat early-life seizures, altered outcome we administered ACTH once per day subcutaneously during the time of the induced interictal spike activity. We show a modest amelioration of the attention deficit seen in animals with a history of early life interictal spikes with ACTH, in the absence of alteration of interictal spike activity. These results suggest that pharmacological intervention that is not targeted to the interictal spike activity is worthy of future study as it may be beneficial for preventing or ameliorating adverse

  6. Interlaboratory comparison of PCR-based identification of Candida and Aspergillus DNA in spiked blood samples.

    Science.gov (United States)

    Reichard, Utz; Buchheidt, Dieter; Lass-Flörl, Cornelia; Loeffler, Juergen; Lugert, Raimond; Ruhnke, Markus; Tintelnot, Kathrin; Weig, Michael; Groß, Uwe

    2012-09-01

    Despite PCR per se being a powerful and sensitive technique, regarding the detection of fungi in patients' blood, no consensus for a standardised PCR protocol yet exists. To complement other ongoing or accomplished studies which tackle this problem, the German Reference Center for Systemic Mycoses conducted an interlaboratory comparison starting with blood samples spiked with fungal cell elements. Altogether, six laboratories using in-house PCR-protocols from Germany and Austria participated in the trial. Blood samples were spiked with vital cells of Candida albicans or Aspergillus fumigatus. Candida was used in the yeast form, whereas Aspergillus cells were either spiked as conidia or as very young germlings, also known as smoo cells. Spiked blood samples contained between 10 and 10 000 cells ml(-1). Depending on the techniques used for fungal cell disruption and DNA-amplification, detection quality was variable between laboratories, but also differed within single laboratories in different trials particularly for samples spiked with less than 100 cells ml(-1). Altogether, at least regarding the detection of A. fumigatus, two of six laboratories showed constant reliable test results also with low fungal cell number spiked samples. Protocols used by these labs do not differ substantially from others. However, as particularities, one protocol included a conventional phenol chloroform extraction during the DNA preparation process and the other included a real time PCR-protocol based on FRET probes. Other laboratory comparisons on the basis of clinical samples should follow to further evaluate the procedures. The difficulties and problems of such trials in general are discussed. © 2012 Blackwell Verlag GmbH.

  7. Spike Pattern Structure Influences Synaptic Efficacy Variability under STDP and Synaptic Homeostasis. I: Spike Generating Models on Converging Motifs

    OpenAIRE

    Bi, Zedong; Zhou, Changsong

    2016-01-01

    In neural systems, synaptic plasticity is usually driven by spike trains. Due to the inherent noises of neurons and synapses as well as the randomness of connection details, spike trains typically exhibit variability such as spatial randomness and temporal stochasticity, resulting in variability of synaptic changes under plasticity, which we call efficacy variability. How the variability of spike trains influences the efficacy variability of synapses remains unclear. In this paper, we try to...

  8. [Wide QRS tachycardia preceded by pacemaker spikes].

    Science.gov (United States)

    Romero, M; Aranda, A; Gómez, F J; Jurado, A

    2014-04-01

    The differential diagnosis and therapeutic management of wide QRS tachycardia preceded by pacemaker spike is presented. The pacemaker-mediated tachycardia, tachycardia fibrillo-flutter in patients with pacemakers, and runaway pacemakers, have a similar surface electrocardiogram, but respond to different therapeutic measures. The tachycardia response to the application of a magnet over the pacemaker could help in the differential diagnosis, and in some cases will be therapeutic, as in the case of a tachycardia-mediated pacemaker. Although these conditions are diagnosed and treated in hospitals with catheterization laboratories using the application programmer over the pacemaker, patients presenting in primary care clinic and emergency forced us to make a diagnosis and treat the haemodynamically unstable patient prior to referral. Copyright © 2012 Sociedad Española de Médicos de Atención Primaria (SEMERGEN). Publicado por Elsevier España. All rights reserved.

  9. Neuronal spike sorting based on radial basis function neural networks

    Directory of Open Access Journals (Sweden)

    Taghavi Kani M

    2011-02-01

    Full Text Available "nBackground: Studying the behavior of a society of neurons, extracting the communication mechanisms of brain with other tissues, finding treatment for some nervous system diseases and designing neuroprosthetic devices, require an algorithm to sort neuralspikes automatically. However, sorting neural spikes is a challenging task because of the low signal to noise ratio (SNR of the spikes. The main purpose of this study was to design an automatic algorithm for classifying neuronal spikes that are emitted from a specific region of the nervous system."n "nMethods: The spike sorting process usually consists of three stages: detection, feature extraction and sorting. We initially used signal statistics to detect neural spikes. Then, we chose a limited number of typical spikes as features and finally used them to train a radial basis function (RBF neural network to sort the spikes. In most spike sorting devices, these signals are not linearly discriminative. In order to solve this problem, the aforesaid RBF neural network was used."n "nResults: After the learning process, our proposed algorithm classified any arbitrary spike. The obtained results showed that even though the proposed Radial Basis Spike Sorter (RBSS reached to the same error as the previous methods, however, the computational costs were much lower compared to other algorithms. Moreover, the competitive points of the proposed algorithm were its good speed and low computational complexity."n "nConclusion: Regarding the results of this study, the proposed algorithm seems to serve the purpose of procedures that require real-time processing and spike sorting.

  10. Clustering predicts memory performance in networks of spiking and non-spiking neurons

    Directory of Open Access Journals (Sweden)

    Weiliang eChen

    2011-03-01

    Full Text Available The problem we address in this paper is that of finding effective and parsimonious patterns of connectivity in sparse associative memories. This problem must be addressed in real neuronal systems, so that results in artificial systems could throw light on real systems. We show that there are efficient patterns of connectivity and that these patterns are effective in models with either spiking or non-spiking neurons. This suggests that there may be some underlying general principles governing good connectivity in such networks. We also show that the clustering of the network, measured by Clustering Coefficient, has a strong linear correlation to the performance of associative memory. This result is important since a purely static measure of network connectivity appears to determine an important dynamic property of the network.

  11. SAWYER ASTEROID SPECTRA

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains 94 optical asteroid spectra obtained by Scott Sawyer as part of his Ph.D. dissertation at the University of Texas at Austin. Observational...

  12. Self-consistent determination of the spike-train power spectrum in a neural network with sparse connectivity.

    Science.gov (United States)

    Dummer, Benjamin; Wieland, Stefan; Lindner, Benjamin

    2014-01-01

    A major source of random variability in cortical networks is the quasi-random arrival of presynaptic action potentials from many other cells. In network studies as well as in the study of the response properties of single cells embedded in a network, synaptic background input is often approximated by Poissonian spike trains. However, the output statistics of the cells is in most cases far from being Poisson. This is inconsistent with the assumption of similar spike-train statistics for pre- and postsynaptic cells in a recurrent network. Here we tackle this problem for the popular class of integrate-and-fire neurons and study a self-consistent statistics of input and output spectra of neural spike trains. Instead of actually using a large network, we use an iterative scheme, in which we simulate a single neuron over several generations. In each of these generations, the neuron is stimulated with surrogate stochastic input that has a similar statistics as the output of the previous generation. For the surrogate input, we employ two distinct approximations: (i) a superposition of renewal spike trains with the same interspike interval density as observed in the previous generation and (ii) a Gaussian current with a power spectrum proportional to that observed in the previous generation. For input parameters that correspond to balanced input in the network, both the renewal and the Gaussian iteration procedure converge quickly and yield comparable results for the self-consistent spike-train power spectrum. We compare our results to large-scale simulations of a random sparsely connected network of leaky integrate-and-fire neurons (Brunel, 2000) and show that in the asynchronous regime close to a state of balanced synaptic input from the network, our iterative schemes provide an excellent approximations to the autocorrelation of spike trains in the recurrent network.

  13. No WIMP mini-spikes in dwarf spheroidal galaxies

    NARCIS (Netherlands)

    Wanders, M.; Bertone, G.; Volonteri, M.; Weniger, C.

    2015-01-01

    The formation of black holes inevitably affects the distribution of dark and baryonic matter in their vicinity, leading to an enhancement of the dark matter density, called spike, and if dark matter is made of WIMPs, to a strong enhancement of the dark matter annihilation rate. Spikes at the center

  14. Grain price spikes and beggar-thy-neighbor policy responses

    DEFF Research Database (Denmark)

    Boysen, Ole; Jensen, Hans Grinsted

    Upward spikes in the international price of food in recent years led some countries to raise export barriers, thereby exacerbating both the price spike and reducing the terms of trade for food-importing countries (beggaring their neighbors). At the same time, and for similar political...

  15. Spiking and bursting patterns of fractional-order Izhikevich model

    Science.gov (United States)

    Teka, Wondimu W.; Upadhyay, Ranjit Kumar; Mondal, Argha

    2018-03-01

    Bursting and spiking oscillations play major roles in processing and transmitting information in the brain through cortical neurons that respond differently to the same signal. These oscillations display complex dynamics that might be produced by using neuronal models and varying many model parameters. Recent studies have shown that models with fractional order can produce several types of history-dependent neuronal activities without the adjustment of several parameters. We studied the fractional-order Izhikevich model and analyzed different kinds of oscillations that emerge from the fractional dynamics. The model produces a wide range of neuronal spike responses, including regular spiking, fast spiking, intrinsic bursting, mixed mode oscillations, regular bursting and chattering, by adjusting only the fractional order. Both the active and silent phase of the burst increase when the fractional-order model further deviates from the classical model. For smaller fractional order, the model produces memory dependent spiking activity after the pulse signal turned off. This special spiking activity and other properties of the fractional-order model are caused by the memory trace that emerges from the fractional-order dynamics and integrates all the past activities of the neuron. On the network level, the response of the neuronal network shifts from random to scale-free spiking. Our results suggest that the complex dynamics of spiking and bursting can be the result of the long-term dependence and interaction of intracellular and extracellular ionic currents.

  16. Interictal spike EEG source analysis in hypothalamic hamartoma epilepsy.

    Science.gov (United States)

    Leal, Alberto J R; Passão, Vitorina; Calado, Eulália; Vieira, José P; Silva Cunha, João P

    2002-12-01

    The epilepsy associated with the hypothalamic hamartomas constitutes a syndrome with peculiar seizures, usually refractory to medical therapy, mild cognitive delay, behavioural problems and multifocal spike activity in the scalp electroencephalogram (EEG). The cortical origin of spikes has been widely assumed but not specifically demonstrated. We present results of a source analysis of interictal spikes from 4 patients (age 2-25 years) with epilepsy and hypothalamic hamartoma, using EEG scalp recordings (32 electrodes) and realistic boundary element models constructed from volumetric magnetic resonance imaging (MRIs). Multifocal spike activity was the most common finding, distributed mainly over the frontal and temporal lobes. A spike classification based on scalp topography was done and averaging within each class performed to improve the signal to noise ratio. Single moving dipole models were used, as well as the Rap-MUSIC algorithm. All spikes with good signal to noise ratio were best explained by initial deep sources in the neighbourhood of the hamartoma, with late sources located in the cortex. Not a single patient could have his spike activity explained by a combination of cortical sources. Overall, the results demonstrate a consistent origin of spike activity in the subcortical region in the neighbourhood of the hamartoma, with late spread to cortical areas.

  17. Spike protection device for electronics and communication appliances

    African Journals Online (AJOL)

    Experience shows that most failures of electronic and communication equipment result from damage caused by external electrical disturbances in the form of overvoltage, undervoltage, surge, sag, spike, or voltage dropout (blackout), the status of which is determined by the amplitude and duration of the disturbance. Spikes ...

  18. Diagrammatic scale for the assessment of blast on wheat spikes

    Directory of Open Access Journals (Sweden)

    João Leodato Nunes Maciel

    2013-09-01

    Full Text Available The correct quantification of blast caused by the fungus Magnaporthe oryzae on wheat (Triticum aestivum spikes is an important component to understand the development of this disease aimed at its control. Visual quantification based on a diagrammatic scale can be a practical and efficient strategy that has already proven to be useful against several plant pathosystems, including diseases affecting wheat spikes like glume blotch and fusarium head blight. Spikes showing different disease severity values were collected from a wheat field with the aim of elaborating a diagrammatic scale to quantify blast severity on wheat spikes. The spikes were photographed and blast severity was determined by using resources of the software ImageJ. A diagrammatic scale was developed with the following disease severity values: 3.7, 7.5, 21.4, 30.5, 43.8, 57.3, 68.1, 86.0, and 100.0%. An asymptomatic spike was added to the scale. Scale validation was performed by eight people who estimated blast severity by using digitalized images of 40 wheat spikes. The precision and the accuracy of the evaluations varied according to the rater (0.82spikes.

  19. SPIKY: a graphical user interface for monitoring spike train synchrony

    Science.gov (United States)

    Mulansky, Mario; Bozanic, Nebojsa

    2015-01-01

    Techniques for recording large-scale neuronal spiking activity are developing very fast. This leads to an increasing demand for algorithms capable of analyzing large amounts of experimental spike train data. One of the most crucial and demanding tasks is the identification of similarity patterns with a very high temporal resolution and across different spatial scales. To address this task, in recent years three time-resolved measures of spike train synchrony have been proposed, the ISI-distance, the SPIKE-distance, and event synchronization. The Matlab source codes for calculating and visualizing these measures have been made publicly available. However, due to the many different possible representations of the results the use of these codes is rather complicated and their application requires some basic knowledge of Matlab. Thus it became desirable to provide a more user-friendly and interactive interface. Here we address this need and present SPIKY, a graphical user interface that facilitates the application of time-resolved measures of spike train synchrony to both simulated and real data. SPIKY includes implementations of the ISI-distance, the SPIKE-distance, and the SPIKE-synchronization (an improved and simplified extension of event synchronization) that have been optimized with respect to computation speed and memory demand. It also comprises a spike train generator and an event detector that makes it capable of analyzing continuous data. Finally, the SPIKY package includes additional complementary programs aimed at the analysis of large numbers of datasets and the estimation of significance levels. PMID:25744888

  20. Cytoplasmic tail of coronavirus spike protein has intracellular

    Indian Academy of Sciences (India)

    Intracellular trafficking and localization studies of spike protein from SARS and OC43 showed that SARS spikeprotein is localized in the ER or ERGIC compartment and OC43 spike protein is predominantly localized in thelysosome. Differential localization can be explained by signal sequence. The sequence alignment ...

  1. Adaptive robotic control driven by a versatile spiking cerebellar network.

    Directory of Open Access Journals (Sweden)

    Claudia Casellato

    Full Text Available The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning, a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions.

  2. A supervised learning rule for classification of spatiotemporal spike patterns.

    Science.gov (United States)

    Lilin Guo; Zhenzhong Wang; Adjouadi, Malek

    2016-08-01

    This study introduces a novel supervised algorithm for spiking neurons that take into consideration synapse delays and axonal delays associated with weights. It can be utilized for both classification and association and uses several biologically influenced properties, such as axonal and synaptic delays. This algorithm also takes into consideration spike-timing-dependent plasticity as in Remote Supervised Method (ReSuMe). This paper focuses on the classification aspect alone. Spiked neurons trained according to this proposed learning rule are capable of classifying different categories by the associated sequences of precisely timed spikes. Simulation results have shown that the proposed learning method greatly improves classification accuracy when compared to the Spike Pattern Association Neuron (SPAN) and the Tempotron learning rule.

  3. Computer programs for locating and fitting full energie peak in γ-ray spectra. Test and rules for an estimation of the main results

    International Nuclear Information System (INIS)

    1980-12-01

    After the different interlaboratory tests on gamma spectrum analysis organised by the 'Laboratoire de Metrologie des Rayonnements Ionisants' and by the International Atomic Energy Agency, it looked useful to manage a same type of intercomparison with the different supplies of Data acquisition and Analysis systems including mini-ordinator or microprocessor. Four spectrum have been chosen between those of the interlaboratory tests. The test dealt with the investigation of total absorption peaks of different levels in a complex spectrum and the calculation of their main parameters. Four supplies participed in the intercomparison with their own logicial. The result allow to suggest a few tests in order to try a new logicial, or to compare results with standards [fr

  4. Uroguanylin induces electroencephalographic spikes in rats

    OpenAIRE

    Teixeira, MDA.; Nascimento, NRF.; Fonteles, MC.; Vale, OC.

    2013-01-01

    Uroguanylin (UGN) is an endogenous peptide that acts on membrane-bound guanylate cyclase receptors of intestinal and renal cells increasing cGMP production and regulating electrolyte and water epithelial transport. Recent research works demonstrate the expression of this peptide and its receptor in the central nervous system. The current work was undertaken in order to evaluate modifications of electroencephalographic spectra (EEG) in anesthetized Wistar rats, submitted to intracisternal infu...

  5. Diffraction of sonic booms around buildings resulting in the building spiking effect.

    Science.gov (United States)

    Cho, Sang-Ik T; Sparrow, Victor W

    2011-03-01

    The diffraction of a sonic boom around a building of finite dimensions yields amplification of the front shock and a positive spike that follows the tail shock in the pressure waveform recorded at the incident side of the building's exterior surface. This physical phenomenon is consistently found both in the data obtained from a 2006 NASA flight test and field experiment, and in the finite-difference time-domain simulation that models this particular experiment, and the authors call it the "building spiking" effect. This paper presents an analysis of the numerical and the accompanying experimental results used to investigate the cause of this effect. The simulation assumes linear acoustics only, which sufficiently describes the physics of interest. Separating the low and high frequency components of boom recordings using optimal finite impulse response filters with complementary magnitude responses shows that the building spiking effect can be attributed to the frequency dependent nature of diffraction. A comparison of the building spiking effect of a conventional N-wave and a low-amplitude sonic boom shows that a longer shock rise time leads to less pronounced amplification of the exterior pressure loading on buildings, and thus reveals an advantage of shaping a boom to elongate its rise time. © 2011 Acoustical Society of America

  6. Automated spike sorting using density grid contour clustering and subtractive waveform decomposition.

    Science.gov (United States)

    Vargas-Irwin, Carlos; Donoghue, John P

    2007-08-15

    In multiple cell recordings identifying the number of neurons and assigning each action potential to a particular source, commonly referred to as 'spike sorting', is a highly non-trivial problem. Density grid contour clustering provides a computationally efficient way of locating high-density regions of arbitrary shape in low-dimensional space. When applied to waveforms projected onto their first two principal components, the algorithm allows the extraction of templates that provide high-dimensional reference points that can be used to perform accurate spike sorting. Template matching using subtractive waveform decomposition can locate these templates in waveform samples despite the influence of noise, spurious threshold crossing and waveform overlap. Tests with a large synthetic dataset incorporating realistic challenges faced during spike sorting (including overlapping and phase-shifted spikes) reveal that this strategy can consistently yield results with less than 6% false positives and false negatives (and less than 2% for high signal-to-noise ratios) at processing speeds exceeding those previously reported for similar algorithms by more than an order of magnitude.

  7. Peptide de novo sequencing of mixture tandem mass spectra

    DEFF Research Database (Denmark)

    Gorshkov, Vladimir; Hotta, Stéphanie Yuki Kolbeck; Braga, Thiago Verano

    2016-01-01

    The impact of mixture spectra deconvolution on the performance of four popular de novo sequencing programs was tested using artificially constructed mixture spectra as well as experimental proteomics data. Mixture fragmentation spectra are recognized as a limitation in proteomics because they dec...

  8. Solar Energetic Particle Spectra

    Science.gov (United States)

    Ryan, J. M.; Boezio, M.; Bravar, U.; Bruno, A.; Christian, E. R.; de Nolfo, G. A.; Martucci, M.; Mergè, M.; Munini, R.; Ricci, M.; Sparvoli, R.; Stochaj, S.

    2017-12-01

    We report updated event-integrated spectra from several SEP events measured with PAMELA. The measurements were made from 2006 to 2014 in the energy range starting at 80 MeV and extending well above the neutron monitor threshold. The PAMELA instrument is in a high inclination, low Earth orbit and has access to SEPs when at high latitudes. Spectra have been assembled from these high-latitude measurements. The field of view of PAMELA is small and during the high-latitude passes it scans a wide range of asymptotic directions as the spacecraft orbits. Correcting for data gaps, solid angle effects and improved background corrections, we have compiled event-integrated intensity spectra for twenty-eight SEP events. Where statistics permit, the spectra exhibit power law shapes in energy with a high-energy exponential roll over. The events analyzed include two genuine ground level enhancements (GLE). In those cases the roll-over energy lies above the neutron monitor threshold ( 1 GV) while the others are lower. We see no qualitative difference between the spectra of GLE vs. non-GLE events, i.e., all roll over in an exponential fashion with rapidly decreasing intensity at high energies.

  9. Spiking irregularity and frequency modulate the behavioral report of single-neuron stimulation.

    Science.gov (United States)

    Doron, Guy; von Heimendahl, Moritz; Schlattmann, Peter; Houweling, Arthur R; Brecht, Michael

    2014-02-05

    The action potential activity of single cortical neurons can evoke measurable sensory effects, but it is not known how spiking parameters and neuronal subtypes affect the evoked sensations. Here, we examined the effects of spike train irregularity, spike frequency, and spike number on the detectability of single-neuron stimulation in rat somatosensory cortex. For regular-spiking, putative excitatory neurons, detectability increased with spike train irregularity and decreasing spike frequencies but was not affected by spike number. Stimulation of single, fast-spiking, putative inhibitory neurons led to a larger sensory effect compared to regular-spiking neurons, and the effect size depended only on spike irregularity. An ideal-observer analysis suggests that, under our experimental conditions, rats were using integration windows of a few hundred milliseconds or more. Our data imply that the behaving animal is sensitive to single neurons' spikes and even to their temporal patterning. Copyright © 2014 Elsevier Inc. All rights reserved.

  10. Generalized analog thresholding for spike acquisition at ultralow sampling rates.

    Science.gov (United States)

    He, Bryan D; Wein, Alex; Varshney, Lav R; Kusuma, Julius; Richardson, Andrew G; Srinivasan, Lakshminarayan

    2015-07-01

    Efficient spike acquisition techniques are needed to bridge the divide from creating large multielectrode arrays (MEA) to achieving whole-cortex electrophysiology. In this paper, we introduce generalized analog thresholding (gAT), which achieves millisecond temporal resolution with sampling rates as low as 10 Hz. Consider the torrent of data from a single 1,000-channel MEA, which would generate more than 3 GB/min using standard 30-kHz Nyquist sampling. Recent neural signal processing methods based on compressive sensing still require Nyquist sampling as a first step and use iterative methods to reconstruct spikes. Analog thresholding (AT) remains the best existing alternative, where spike waveforms are passed through an analog comparator and sampled at 1 kHz, with instant spike reconstruction. By generalizing AT, the new method reduces sampling rates another order of magnitude, detects more than one spike per interval, and reconstructs spike width. Unlike compressive sensing, the new method reveals a simple closed-form solution to achieve instant (noniterative) spike reconstruction. The base method is already robust to hardware nonidealities, including realistic quantization error and integration noise. Because it achieves these considerable specifications using hardware-friendly components like integrators and comparators, generalized AT could translate large-scale MEAs into implantable devices for scientific investigation and medical technology. Copyright © 2015 the American Physiological Society.

  11. Predictive coding of dynamical variables in balanced spiking networks.

    Science.gov (United States)

    Boerlin, Martin; Machens, Christian K; Denève, Sophie

    2013-01-01

    Two observations about the cortex have puzzled neuroscientists for a long time. First, neural responses are highly variable. Second, the level of excitation and inhibition received by each neuron is tightly balanced at all times. Here, we demonstrate that both properties are necessary consequences of neural networks that represent information efficiently in their spikes. We illustrate this insight with spiking networks that represent dynamical variables. Our approach is based on two assumptions: We assume that information about dynamical variables can be read out linearly from neural spike trains, and we assume that neurons only fire a spike if that improves the representation of the dynamical variables. Based on these assumptions, we derive a network of leaky integrate-and-fire neurons that is able to implement arbitrary linear dynamical systems. We show that the membrane voltage of the neurons is equivalent to a prediction error about a common population-level signal. Among other things, our approach allows us to construct an integrator network of spiking neurons that is robust against many perturbations. Most importantly, neural variability in our networks cannot be equated to noise. Despite exhibiting the same single unit properties as widely used population code models (e.g. tuning curves, Poisson distributed spike trains), balanced networks are orders of magnitudes more reliable. Our approach suggests that spikes do matter when considering how the brain computes, and that the reliability of cortical representations could have been strongly underestimated.

  12. A method for decoding the neurophysiological spike-response transform.

    Science.gov (United States)

    Stern, Estee; García-Crescioni, Keyla; Miller, Mark W; Peskin, Charles S; Brezina, Vladimir

    2009-11-15

    Many physiological responses elicited by neuronal spikes-intracellular calcium transients, synaptic potentials, muscle contractions-are built up of discrete, elementary responses to each spike. However, the spikes occur in trains of arbitrary temporal complexity, and each elementary response not only sums with previous ones, but can itself be modified by the previous history of the activity. A basic goal in system identification is to characterize the spike-response transform in terms of a small number of functions-the elementary response kernel and additional kernels or functions that describe the dependence on previous history-that will predict the response to any arbitrary spike train. Here we do this by developing further and generalizing the "synaptic decoding" approach of Sen et al. (1996). Given the spike times in a train and the observed overall response, we use least-squares minimization to construct the best estimated response and at the same time best estimates of the elementary response kernel and the other functions that characterize the spike-response transform. We avoid the need for any specific initial assumptions about these functions by using techniques of mathematical analysis and linear algebra that allow us to solve simultaneously for all of the numerical function values treated as independent parameters. The functions are such that they may be interpreted mechanistically. We examine the performance of the method as applied to synthetic data. We then use the method to decode real synaptic and muscle contraction transforms.

  13. Bursts generate a non-reducible spike-pattern code

    Directory of Open Access Journals (Sweden)

    Hugo G Eyherabide

    2009-05-01

    Full Text Available On the single-neuron level, precisely timed spikes can either constitute firing-rate codes or spike-pattern codes that utilize the relative timing between consecutive spikes. There has been little experimental support for the hypothesis that such temporal patterns contribute substantially to information transmission. Using grasshopper auditory receptors as a model system, we show that correlations between spikes can be used to represent behaviorally relevant stimuli. The correlations reflect the inner structure of the spike train: a succession of burst-like patterns. We demonstrate that bursts with different spike counts encode different stimulus features, such that about 20% of the transmitted information corresponds to discriminating between different features, and the remaining 80% is used to allocate these features in time. In this spike-pattern code, the "what" and the "when" of the stimuli are encoded in the duration of each burst and the time of burst onset, respectively. Given the ubiquity of burst firing, we expect similar findings also for other neural systems.

  14. A Simple Deep Learning Method for Neuronal Spike Sorting

    Science.gov (United States)

    Yang, Kai; Wu, Haifeng; Zeng, Yu

    2017-10-01

    Spike sorting is one of key technique to understand brain activity. With the development of modern electrophysiology technology, some recent multi-electrode technologies have been able to record the activity of thousands of neuronal spikes simultaneously. The spike sorting in this case will increase the computational complexity of conventional sorting algorithms. In this paper, we will focus spike sorting on how to reduce the complexity, and introduce a deep learning algorithm, principal component analysis network (PCANet) to spike sorting. The introduced method starts from a conventional model and establish a Toeplitz matrix. Through the column vectors in the matrix, we trains a PCANet, where some eigenvalue vectors of spikes could be extracted. Finally, support vector machine (SVM) is used to sort spikes. In experiments, we choose two groups of simulated data from public databases availably and compare this introduced method with conventional methods. The results indicate that the introduced method indeed has lower complexity with the same sorting errors as the conventional methods.

  15. Automated spike preparation system for Isotope Dilution Mass Spectrometry (IDMS)

    International Nuclear Information System (INIS)

    Maxwell, S.L. III; Clark, J.P.

    1990-01-01

    Isotope Dilution Mass Spectrometry (IDMS) is a method frequently employed to measure dissolved, irradiated nuclear materials. A known quantity of a unique isotope of the element to be measured (referred to as the ''spike'') is added to the solution containing the analyte. The resulting solution is chemically purified then analyzed by mass spectrometry. By measuring the magnitude of the response for each isotope and the response for the ''unique spike'' then relating this to the known quantity of the ''spike'', the quantity of the nuclear material can be determined. An automated spike preparation system was developed at the Savannah River Site (SRS) to dispense spikes for use in IDMS analytical methods. Prior to this development, technicians weighed each individual spike manually to achieve the accuracy required. This procedure was time-consuming and subjected the master stock solution to evaporation. The new system employs a high precision SMI Model 300 Unipump dispenser interfaced with an electronic balance and a portable Epson HX-20 notebook computer to automate spike preparation

  16. Grain price spikes and beggar-thy-neighbor policy responses

    DEFF Research Database (Denmark)

    Boysen, Ole; Jensen, Hans Grinsted

    Upward spikes in the international price of food in recent years led some countries to raise export barriers, thereby exacerbating both the price spike and reducing the terms of trade for food-importing countries (beggaring their neighbors). At the same time, and for similar political......-economy reasons, numerous food-importing countries reduced or suspended their import tariffs, and some even provided food import subsidies -- which also exacerbated the international price spike, thus turning the terms of trade even further against food-importing countries. This issue became a major item...

  17. Boobs, Boxing, and Bombs: Problematizing the Entertainment of Spike TV

    OpenAIRE

    Walton, Gerald; Potvin, L.

    2009-01-01

    Spike is the only television network in North America “for men.” Its motto, “Get more action,” is suggestive of pursuits of various forms of violence. We conceptualize Spike not as trivial entertainment, but rather as a form of pop culture that erodes the gains of feminists who have challenged the prevalence of normalized hegemonic masculinity (HM). Our paper highlights themes of Spike content, and connects those themes to the literature on HM. Moreover, we validate the identities and lives ...

  18. ACCELERATED FITTING OF STELLAR SPECTRA

    International Nuclear Information System (INIS)

    Ting, Yuan-Sen; Conroy, Charlie; Rix, Hans-Walter

    2016-01-01

    Stellar spectra are often modeled and fitted by interpolating within a rectilinear grid of synthetic spectra to derive the stars’ labels: stellar parameters and elemental abundances. However, the number of synthetic spectra needed for a rectilinear grid grows exponentially with the label space dimensions, precluding the simultaneous and self-consistent fitting of more than a few elemental abundances. Shortcuts such as fitting subsets of labels separately can introduce unknown systematics and do not produce correct error covariances in the derived labels. In this paper we present a new approach—Convex Hull Adaptive Tessellation (chat)—which includes several new ideas for inexpensively generating a sufficient stellar synthetic library, using linear algebra and the concept of an adaptive, data-driven grid. A convex hull approximates the region where the data lie in the label space. A variety of tests with mock data sets demonstrate that chat can reduce the number of required synthetic model calculations by three orders of magnitude in an eight-dimensional label space. The reduction will be even larger for higher dimensional label spaces. In chat the computational effort increases only linearly with the number of labels that are fit simultaneously. Around each of these grid points in the label space an approximate synthetic spectrum can be generated through linear expansion using a set of “gradient spectra” that represent flux derivatives at every wavelength point with respect to all labels. These techniques provide new opportunities to fit the full stellar spectra from large surveys with 15–30 labels simultaneously.

  19. Power-Law Dynamics of Membrane Conductances Increase Spiking Diversity in a Hodgkin-Huxley Model.

    Science.gov (United States)

    Teka, Wondimu; Stockton, David; Santamaria, Fidel

    2016-03-01

    We studied the effects of non-Markovian power-law voltage dependent conductances on the generation of action potentials and spiking patterns in a Hodgkin-Huxley model. To implement slow-adapting power-law dynamics of the gating variables of the potassium, n, and sodium, m and h, conductances we used fractional derivatives of order η≤1. The fractional derivatives were used to solve the kinetic equations of each gate. We systematically classified the properties of each gate as a function of η. We then tested if the full model could generate action potentials with the different power-law behaving gates. Finally, we studied the patterns of action potential that emerged in each case. Our results show the model produces a wide range of action potential shapes and spiking patterns in response to constant current stimulation as a function of η. In comparison with the classical model, the action potential shapes for power-law behaving potassium conductance (n gate) showed a longer peak and shallow hyperpolarization; for power-law activation of the sodium conductance (m gate), the action potentials had a sharp rise time; and for power-law inactivation of the sodium conductance (h gate) the spikes had wider peak that for low values of η replicated pituitary- and cardiac-type action potentials. With all physiological parameters fixed a wide range of spiking patterns emerged as a function of the value of the constant input current and η, such as square wave bursting, mixed mode oscillations, and pseudo-plateau potentials. Our analyses show that the intrinsic memory trace of the fractional derivative provides a negative feedback mechanism between the voltage trace and the activity of the power-law behaving gate variable. As a consequence, power-law behaving conductances result in an increase in the number of spiking patterns a neuron can generate and, we propose, expand the computational capacity of the neuron.

  20. Transgenerational isotopic marking of carp Cyprinus carpio, L. using a 86Sr /84Sr double spike

    Science.gov (United States)

    Zitek, Andreas; Cervicek, Magdalena; Irrgeher, Johanna; Horsky, Monika; Kletzl, Manfred; Weismann, Thomas; Prohaska, Thomas

    2013-04-01

    Transgenerational isotopic marking has been recognized recently as an effective tool for mass marking and tracking of individual fish to their original source. Compared to other conventional marking techniques, transgenerational marking offers several advantages. Most importantly, it is possible to mark all offspring of one individual female without the necessity of handling eggs or larval fish. Furthermore it is possible to vary the concentrations of individual isotopes to obtain specific marks for individual female fish. An enriched isotopic spike solution is usually applied to gravid female spawners by injection into the body cavity for transgenerational marking. The isotope is then incorporated into the central otolith region of the offspring which is known to be built up by maternally derived material. Within this study transgenerational marking of a typical cyprinid fish species, Cyprinus carpio, L., was tested using a 86Sr /84Sr double spike. Buffered solutions with different isotopic composition and concentrations were administered to 4 female individuals by intraperitoneal injection 5 days before spawning, while one female was injected a blank solution. After spawning, otoliths (Lapilli) from juvenile fish were sampled at the age of about 5 months at fish sizes between 3 and 4 cm and analyzed for their isotopic composition by LA-ICPMS applying cross sectional line scans. Central otolith regions of the progeny showed a shift in the natural isotope ratios for the administered isotopes. Deconvolution of the blank corrected measurement data of the Sr isotopes was done to trace back the original spike ratio. The different spike ratios could be well distinguished reflecting the original composition of the spike solution. This study proved that it is possible to create batch-specific unique transgenerational marks in otolith cores by varying the concentrations of two naturally occurring Sr isotopes. This method has high potential to reduce the marking effort for

  1. Parameterization of rotational spectra

    International Nuclear Information System (INIS)

    Zhou Chunmei; Liu Tong

    1992-01-01

    The rotational spectra of the strongly deformed nuclei with low rotational frequencies and weak band mixture are analyzed. The strongly deformed nuclei are commonly encountered in the rare-earth region (e. g., 150 220). A lot of rotational band knowledge are presented

  2. Atomic Spectra Database (ASD)

    Science.gov (United States)

    SRD 78 NIST Atomic Spectra Database (ASD) (Web, free access)   This database provides access and search capability for NIST critically evaluated data on atomic energy levels, wavelengths, and transition probabilities that are reasonably up-to-date. The NIST Atomic Spectroscopy Data Center has carried out these critical compilations.

  3. Effects of mercury on visible/near-infrared reflectance spectra of mustard spinach plants (Brassica rapa P.)

    Energy Technology Data Exchange (ETDEWEB)

    Dunagan, Sarah C. [Department of Earth and Environmental Sciences, Wesleyan University, 265 Church Street, Middletown, CT 06459 (United States)]. E-mail: sdunagan@wesleyan.edu; Gilmore, Martha S. [Department of Earth and Environmental Sciences, Wesleyan University, 265 Church Street, Middletown, CT 06459 (United States)]. E-mail: mgilmore@wesleyan.edu; Varekamp, Johan C. [Department of Earth and Environmental Sciences, Wesleyan University, 265 Church Street, Middletown, CT 06459 (United States)]. E-mail: jvarekamp@wesleyan.edu

    2007-07-15

    Mustard spinach plants were grown in mercury-spiked and contaminated soils collected in the field under controlled laboratory conditions over a full growth cycle to test if vegetation grown in these soils has discernible characteristics in visible/near-infrared (VNIR) spectra. Foliar Hg concentrations (0.174-3.993 ppm) of the Mustard spinach plants were positively correlated with Hg concentration of soils and varied throughout the growing season. Equations relating foliar Hg concentration to spectral reflectance, its first derivative, and selected vegetation indices were generated using stepwise multiple linear regression. Significant correlations are found for limited wavelengths for specific treatments and dates. Ratio Vegetation Index (RVI) and Red Edge Position (REP) values of plants in Hg-spiked and field-contaminated soils are significantly lower relative to control plants during the early and middle portions of the growth cycle which may be related to lower chlorophyll abundance or functioning in Hg-contaminated plants. - Some spectral characteristics of leaves of Brassica rapa P. may be associated with foliar mercury content.

  4. Heterogeneity of Purkinje cell simple spike-complex spike interactions: zebrin- and non-zebrin-related variations.

    Science.gov (United States)

    Tang, Tianyu; Xiao, Jianqiang; Suh, Colleen Y; Burroughs, Amelia; Cerminara, Nadia L; Jia, Linjia; Marshall, Sarah P; Wise, Andrew K; Apps, Richard; Sugihara, Izumi; Lang, Eric J

    2017-08-01

    Cerebellar Purkinje cells (PCs) generate two types of action potentials, simple and complex spikes. Although they are generated by distinct mechanisms, interactions between the two spike types exist. Zebrin staining produces alternating positive and negative stripes of PCs across most of the cerebellar cortex. Thus, here we compared simple spike-complex spike interactions both within and across zebrin populations. Simple spike activity undergoes a complex modulation preceding and following a complex spike. The amplitudes of the pre- and post-complex spike modulation phases were correlated across PCs. On average, the modulation was larger for PCs in zebrin positive regions. Correlations between aspects of the complex spike waveform and simple spike activity were found, some of which varied between zebrin positive and negative PCs. The implications of the results are discussed with regard to hypotheses that complex spikes are triggered by rises in simple spike activity for either motor learning or homeostatic functions. Purkinje cells (PCs) generate two types of action potentials, called simple and complex spikes (SSs and CSs). We first investigated the CS-associated modulation of SS activity and its relationship to the zebrin status of the PC. The modulation pattern consisted of a pre-CS rise in SS activity, and then, following the CS, a pause, a rebound, and finally a late inhibition of SS activity for both zebrin positive (Z+) and negative (Z-) cells, though the amplitudes of the phases were larger in Z+ cells. Moreover, the amplitudes of the pre-CS rise with the late inhibitory phase of the modulation were correlated across PCs. In contrast, correlations between modulation phases across CSs of individual PCs were generally weak. Next, the relationship between CS spikelets and SS activity was investigated. The number of spikelets/CS correlated with the average SS firing rate only for Z+ cells. In contrast, correlations across CSs between spikelet numbers and the

  5. Perceptron learning rule derived from spike-frequency adaptation and spike-time-dependent plasticity.

    Science.gov (United States)

    D'Souza, Prashanth; Liu, Shih-Chii; Hahnloser, Richard H R

    2010-03-09

    It is widely believed that sensory and motor processing in the brain is based on simple computational primitives rooted in cellular and synaptic physiology. However, many gaps remain in our understanding of the connections between neural computations and biophysical properties of neurons. Here, we show that synaptic spike-time-dependent plasticity (STDP) combined with spike-frequency adaptation (SFA) in a single neuron together approximate the well-known perceptron learning rule. Our calculations and integrate-and-fire simulations reveal that delayed inputs to a neuron endowed with STDP and SFA precisely instruct neural responses to earlier arriving inputs. We demonstrate this mechanism on a developmental example of auditory map formation guided by visual inputs, as observed in the external nucleus of the inferior colliculus (ICX) of barn owls. The interplay of SFA and STDP in model ICX neurons precisely transfers the tuning curve from the visual modality onto the auditory modality, demonstrating a useful computation for multimodal and sensory-guided processing.

  6. Stochastic optimal control of single neuron spike trains

    DEFF Research Database (Denmark)

    Iolov, Alexandre; Ditlevsen, Susanne; Longtin, Andrë

    2014-01-01

    stimulation of a neuron to achieve a target spike train under the physiological constraint to not damage tissue. Approach. We pose a stochastic optimal control problem to precisely specify the spike times in a leaky integrate-and-fire (LIF) model of a neuron with noise assumed to be of intrinsic or synaptic...... to the spike times (open-loop control). Main results. We have developed a stochastic optimal control algorithm to obtain precise spike times. It is applicable in both the supra-threshold and sub-threshold regimes, under open-loop and closed-loop conditions and with an arbitrary noise intensity; the accuracy...... into account physiological constraints on the control. A precise and robust targeting of neural activity based on stochastic optimal control has great potential for regulating neural activity in e.g. prosthetic applications and to improve our understanding of the basic mechanisms by which neuronal firing...

  7. Higher Order Spike Synchrony in Prefrontal Cortex during visual memory

    Directory of Open Access Journals (Sweden)

    Gordon ePipa

    2011-06-01

    Full Text Available Precise temporal synchrony of spike firing has been postulated as an important neuronal mechanism for signal integration and the induction of plasticity in neocortex. As prefrontal cortex plays an important role in organizing memory and executive functions, the convergence of multiple visual pathways onto PFC predicts that neurons should preferentially synchronize their spiking when stimulus information is processed. Furthermore, synchronous spike firing should intensify if memory processes require the induction of neuronal plasticity, even if this is only for short-term. Here we show with multiple simultaneously recorded units in ventral prefrontal cortex that neurons participate in 3 ms precise synchronous discharges distributed across multiple sites separated by at least 500 µm. The frequency of synchronous firing is modulated by behavioral performance and is specific for the memorized visual stimuli. In particular, during the memory period in which activity is not stimulus driven, larger groups of up to 7 sites exhibit performance dependent modulation of their spike synchronization.

  8. Sonar target localization based on spike coded spectrograms

    Directory of Open Access Journals (Sweden)

    Bertrand FONTAINE

    2006-12-01

    Full Text Available Target location is coded into the pattern of spikes that run up the auditory nerve to the bat's brain. Realistic scenes containing multiple, closely spaced, reflectors give rise to complex echo signals consisting of multiple filtered copies of the bat's own vocalisation. Some of this filtering is due to the directivity of the bat’s reception system i.e., the outer ears, and some of it is due to sound absorption and the reflection process. The analysis below concentrates on the conspicuous ridges (notches these filter operations give rise to in the time-frequency representation of the echo as produced by the bat's inner ear. Assuming multiple threshold detecting neurons for each frequency channel it is shown how the distribution of spike times within the generated spike bursts is linked to the presence and characteristics of these notches. A neural network decoding the spike bursts in terms of target location is described.

  9. Spatiotemporal Dynamics and Reliable Computations in Recurrent Spiking Neural Networks

    Science.gov (United States)

    Pyle, Ryan; Rosenbaum, Robert

    2017-01-01

    Randomly connected networks of excitatory and inhibitory spiking neurons provide a parsimonious model of neural variability, but are notoriously unreliable for performing computations. We show that this difficulty is overcome by incorporating the well-documented dependence of connection probability on distance. Spatially extended spiking networks exhibit symmetry-breaking bifurcations and generate spatiotemporal patterns that can be trained to perform dynamical computations under a reservoir computing framework.

  10. Spike Neural Models Part II: Abstract Neural Models

    OpenAIRE

    Johnson, Melissa G.; Chartier, Sylvain

    2018-01-01

    Neurons are complex cells that require a lot of time and resources to model completely. In spiking neural networks (SNN) though, not all that complexity is required. Therefore simple, abstract models are often used. These models save time, use less computer resources, and are easier to understand. This tutorial presents two such models: Izhikevich's model, which is biologically realistic in the resulting spike trains but not in the parameters, and the Leaky Integrate and Fire (LIF) model whic...

  11. Characteristics of Spike motion in World top lever volleyball players

    OpenAIRE

    黒川, 貞生; 森田, 恭光; 亀ヶ谷, 純一; 加藤, 浩人; 松井, 泰二; 鈴木, 陽一; 矢島, 忠明

    2008-01-01

    The purpose of this study was to investigate the characteristics of spike motion in world top level volleyball players. Front- and back-spike motions were recorded by high-speed video camera system operating at 250Hz to obtain three dimensional coordinates of the body segments and the center of the ball. The velocity of the ball, wrist, shoulder and trunk twist angle was calculated using motion analyzer. There is no significant relationship between the initial ball velocity and the velocity o...

  12. EPILEPTIC ENCEPHALOPATHY WITH CONTINUOUS SPIKES-WAVES ACTIVITY DURING SLEEP

    OpenAIRE

    E. D. Belousova

    2012-01-01

    The author represents the review and discussion of current scientific literature devoted to epileptic encephalopathy with continuous spikes-waves activity during sleep — the special form of partly reversible age-dependent epileptic encephalopathy, characterized by triad of symptoms: continuous prolonged epileptiform (spike-wave) activity on EEG in sleep, epileptic seizures and cognitive disorders. The author describes the aspects of classification, pathogenesis and etiology, prevalence, clini...

  13. Nonlinear evolution of single spike in Richtmyer-Meshkov instability

    International Nuclear Information System (INIS)

    Fukuda, Y.; Nishihara, K.; Wouchuk, J.G.

    2000-01-01

    Nonlinear evolution of single spike structure and vortex in the Richtmyer-Meshkov instability is investigated with the use of a two-dimensional hydrodynamic code. It is shown that singularity appears in the vorticity left by transmitted and reflected shocks at a corrugated interface. This singularity results in opposite sign of vorticity along the interface that causes double spiral structure of the spike. (authors)

  14. Automatic fitting of spiking neuron models to electrophysiological recordings

    Directory of Open Access Journals (Sweden)

    Cyrille Rossant

    2010-03-01

    Full Text Available Spiking models can accurately predict the spike trains produced by cortical neurons in response to somatically injected currents. Since the specific characteristics of the model depend on the neuron, a computational method is required to fit models to electrophysiological recordings. The fitting procedure can be very time consuming both in terms of computer simulations and in terms of code writing. We present algorithms to fit spiking models to electrophysiological data (time-varying input and spike trains that can run in parallel on graphics processing units (GPUs. The model fitting library is interfaced with Brian, a neural network simulator in Python. If a GPU is present it uses just-in-time compilation to translate model equations into optimized code. Arbitrary models can then be defined at script level and run on the graphics card. This tool can be used to obtain empirically validated spiking models of neurons in various systems. We demonstrate its use on public data from the INCF Quantitative Single-Neuron Modeling 2009 competition by comparing the performance of a number of neuron spiking models.

  15. Absolute Ca Isotopic Measurement Using an Improved Double Spike Technique

    Directory of Open Access Journals (Sweden)

    Jason Jiun-San Shen

    2009-01-01

    Full Text Available A new vector analytical method has been developed in order to obtain the true isotopic composition of the 42Ca-48Ca double spike. This is achieved by using two different sample-spike mixtures combined with the double spike and natural Ca data. Be cause the natural sample (two mixtures and the spike should all lie on a single mixing line, we are able to con strain the true isotopic composition of our double spike using this new approach. Once the isotopic composition of the Ca double spike is established, we are able to obtain the true Ca isotopic composition of the NIST Ca standard SRM915a, 40Ca/44Ca = 46.537 ± 2 (2sm, n = 55, 42Ca/44Ca = 0.31031 ± 1, 43Ca/44Ca = 0.06474 ± 1, and 48Ca/44Ca = 0.08956 ± 1. De spite an off set of 1.3% in 40Ca/44Ca between our result and the previously re ported value (Russell et al. 1978, our data indicate an off set of 1.89__in 40Ca/44Ca between SRM915a and seawater, entirely consistent with the published results.

  16. X-ray absorption spectra and emission spectra of plasmas

    International Nuclear Information System (INIS)

    Peng Yonglun; Yang Li; Wang Minsheng; Li Jiaming

    2002-01-01

    The author reports a theoretical method to calculate the resolved absorption spectra and emission spectra (optically thin) of hot dense plasmas. Due to its fully relativistic treatment incorporated with the quantum defect theory, it calculates the absorption spectra and emission spectra for single element or multi-element plasmas with little computational efforts. The calculated absorption spectra of LTE gold plasmas agree well with the experimental ones. It also calculates the optical thin emission spectra of LTE gold plasmas, which is helpful to diagnose the plasmas of relevant ICF plasmas. It can also provide the relevant parameters such as population density of various ionic stages, precise radiative properties for ICF studies

  17. Weighted spiking neural P systems with structural plasticity working in sequential mode based on maximum spike number

    Science.gov (United States)

    Sun, Mingming; Qu, Jianhua

    2017-10-01

    Spiking neural P systems (SNP systems, in short) are a group of parallel and distributed computing devices inspired by the function and structure of spiking neurons. Recently, a new variant of SNP systems, called SNP systems with structural plasticity (SNPSP systems, in short) was proposed. In SNPSP systems, neuron can use plasticity ru les to create and delete synapses. In this work, we consider many restrictions sequentiality on SNPSP systems: (1) neuron with the maximum number of spikes is chosen to fire; (2) we use the weighted synapses. Specifically, we investigate the computational power of weighted SNPSP systems working in the sequential mode based on maximum spike number (WSNPSPM systems, in short) and we proved that SNPSP systems with these new restrictions are universal as generating devices.

  18. NE-213-scintillator-based neutron detection system for diagnostic measurements of energy spectra for neutrons having energies greater than or equal to 0.8 MeV created during plasma operations at the Princeton Tokamak Fusion Test Reactor

    International Nuclear Information System (INIS)

    Dickens, J.K.; Hill, N.W.; Hou, F.S.; McConnell, J.W.; Spencer, R.R.; Tsang, F.Y.

    1985-08-01

    A system for making diagnostic measurements of the energy spectra of greater than or equal to 0.8-MeV neutrons produced during plasma operations of the Princeton Tokamak Fusion Test Reactor (TFTR) has been fabricated and tested and is presently in operation in the TFTR Test Cell Basement. The system consists of two separate detectors, each made up of cells containing liquid NE-213 scintillator attached permanently to RCA-8850 photomultiplier tubes. Pulses obtained from each photomultiplier system are amplified and electronically analyzed to identify and separate those pulses due to neutron-induced events in the detector from those due to photon-induced events in the detector. Signals from each detector are routed to two separate Analog-to-Digital Converters, and the resulting digitized information, representing: (1) the raw neutron-spectrum data; and (2) the raw photon-spectrum data, are transmited to the CICADA data-acquisition computer system of the TFTR. Software programs have been installed on the CICADA system to analyze the raw data to provide moderate-resolution recreations of the energy spectrum of the neutron and photon fluences incident on the detector during the operation of the TFTR. A complete description of, as well as the operation of, the hardware and software is given in this report

  19. NE-213-scintillator-based neutron detection system for diagnostic measurements of energy spectra for neutrons having energies greater than or equal to 0. 8 MeV created during plasma operations at the Princeton Tokamak Fusion Test Reactor

    Energy Technology Data Exchange (ETDEWEB)

    Dickens, J.K.; Hill, N.W.; Hou, F.S.; McConnell, J.W.; Spencer, R.R.; Tsang, F.Y.

    1985-08-01

    A system for making diagnostic measurements of the energy spectra of greater than or equal to 0.8-MeV neutrons produced during plasma operations of the Princeton Tokamak Fusion Test Reactor (TFTR) has been fabricated and tested and is presently in operation in the TFTR Test Cell Basement. The system consists of two separate detectors, each made up of cells containing liquid NE-213 scintillator attached permanently to RCA-8850 photomultiplier tubes. Pulses obtained from each photomultiplier system are amplified and electronically analyzed to identify and separate those pulses due to neutron-induced events in the detector from those due to photon-induced events in the detector. Signals from each detector are routed to two separate Analog-to-Digital Converters, and the resulting digitized information, representing: (1) the raw neutron-spectrum data; and (2) the raw photon-spectrum data, are transmited to the CICADA data-acquisition computer system of the TFTR. Software programs have been installed on the CICADA system to analyze the raw data to provide moderate-resolution recreations of the energy spectrum of the neutron and photon fluences incident on the detector during the operation of the TFTR. A complete description of, as well as the operation of, the hardware and software is given in this report.

  20. Thermoluminescence spectra of amethyst

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Q. [Suzhou Railway Teachers College (China). Dept. of Physics; Yang, B. [Beijing Normal University (China). Dept. of Physics; Wood, R.A.; White, D.R.R.; Townsend, P.D.; Luff, B.J. [Sussex Univ., Brighton (United Kingdom). School of Mathematical and Physical Sciences

    1994-04-01

    Thermoluminescence and cathodoluminescence data from natural and synthetic amethyst and synthetic quartz samples are compared. The spectra include features from the quartz host lattice and from impurity-generated recombination sites. Emission features exist throughout the wavelength range studied, 250-800 nm. The near infrared emission at 740-750 nm appears to be characteristic of the amethyst and is proposed to be due to Fe ion impurity. (Author).

  1. Spike Pattern Structure Influences Synaptic Efficacy Variability under STDP and Synaptic Homeostasis. II: Spike Shuffling Methods on LIF Networks

    Science.gov (United States)

    Bi, Zedong; Zhou, Changsong

    2016-01-01

    Synapses may undergo variable changes during plasticity because of the variability of spike patterns such as temporal stochasticity and spatial randomness. Here, we call the variability of synaptic weight changes during plasticity to be efficacy variability. In this paper, we investigate how four aspects of spike pattern statistics (i.e., synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations) influence the efficacy variability under pair-wise additive spike-timing dependent plasticity (STDP) and synaptic homeostasis (the mean strength of plastic synapses into a neuron is bounded), by implementing spike shuffling methods onto spike patterns self-organized by a network of excitatory and inhibitory leaky integrate-and-fire (LIF) neurons. With the increase of the decay time scale of the inhibitory synaptic currents, the LIF network undergoes a transition from asynchronous state to weak synchronous state and then to synchronous bursting state. We first shuffle these spike patterns using a variety of methods, each designed to evidently change a specific pattern statistics; and then investigate the change of efficacy variability of the synapses under STDP and synaptic homeostasis, when the neurons in the network fire according to the spike patterns before and after being treated by a shuffling method. In this way, we can understand how the change of pattern statistics may cause the change of efficacy variability. Our results are consistent with those of our previous study which implements spike-generating models on converging motifs. We also find that burstiness/regularity is important to determine the efficacy variability under asynchronous states, while heterogeneity of cross-correlations is the main factor to cause efficacy variability when the network moves into synchronous bursting states (the states observed in epilepsy). PMID:27555816

  2. Spike Pattern Structure Influences Synaptic Efficacy Variability Under STDP and Synaptic Homeostasis. II: Spike Shuffling Methods on LIF Networks

    Directory of Open Access Journals (Sweden)

    Zedong Bi

    2016-08-01

    Full Text Available Synapses may undergo variable changes during plasticity because of the variability of spike patterns such as temporal stochasticity and spatial randomness. Here, we call the variability of synaptic weight changes during plasticity to be efficacy variability. In this paper, we investigate how four aspects of spike pattern statistics (i.e., synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations influence the efficacy variability under pair-wise additive spike-timing dependent plasticity (STDP and synaptic homeostasis (the mean strength of plastic synapses into a neuron is bounded, by implementing spike shuffling methods onto spike patterns self-organized by a network of excitatory and inhibitory leaky integrate-and-fire (LIF neurons. With the increase of the decay time scale of the inhibitory synaptic currents, the LIF network undergoes a transition from asynchronous state to weak synchronous state and then to synchronous bursting state. We first shuffle these spike patterns using a variety of methods, each designed to evidently change a specific pattern statistics; and then investigate the change of efficacy variability of the synapses under STDP and synaptic homeostasis, when the neurons in the network fire according to the spike patterns before and after being treated by a shuffling method. In this way, we can understand how the change of pattern statistics may cause the change of efficacy variability. Our results are consistent with those of our previous study which implements spike-generating models on converging motifs. We also find that burstiness/regularity is important to determine the efficacy variability under asynchronous states, while heterogeneity of cross-correlations is the main factor to cause efficacy variability when the network moves into synchronous bursting states (the states observed in epilepsy.

  3. Spike Pattern Structure Influences Synaptic Efficacy Variability under STDP and Synaptic Homeostasis. II: Spike Shuffling Methods on LIF Networks

    OpenAIRE

    Bi, Zedong; Zhou, Changsong

    2016-01-01

    Synapses may undergo variable changes during plasticity because of the variability of spike patterns such as temporal stochasticity and spatial randomness. Here, we call the variability of synaptic weight changes during plasticity to be efficacy variability. In this paper, we investigate how four aspects of spike pattern statistics (i.e., synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations) influence the efficacy variability under pair-wis...

  4. Stress-Induced Impairment of a Working Memory Task: Role of Spiking Rate and Spiking History Predicted Discharge

    Science.gov (United States)

    Devilbiss, David M.; Jenison, Rick L.; Berridge, Craig W.

    2012-01-01

    Stress, pervasive in society, contributes to over half of all work place accidents a year and over time can contribute to a variety of psychiatric disorders including depression, schizophrenia, and post-traumatic stress disorder. Stress impairs higher cognitive processes, dependent on the prefrontal cortex (PFC) and that involve maintenance and integration of information over extended periods, including working memory and attention. Substantial evidence has demonstrated a relationship between patterns of PFC neuron spiking activity (action-potential discharge) and components of delayed-response tasks used to probe PFC-dependent cognitive function in rats and monkeys. During delay periods of these tasks, persistent spiking activity is posited to be essential for the maintenance of information for working memory and attention. However, the degree to which stress-induced impairment in PFC-dependent cognition involves changes in task-related spiking rates or the ability for PFC neurons to retain information over time remains unknown. In the current study, spiking activity was recorded from the medial PFC of rats performing a delayed-response task of working memory during acute noise stress (93 db). Spike history-predicted discharge (SHPD) for PFC neurons was quantified as a measure of the degree to which ongoing neuronal discharge can be predicted by past spiking activity and reflects the degree to which past information is retained by these neurons over time. We found that PFC neuron discharge is predicted by their past spiking patterns for nearly one second. Acute stress impaired SHPD, selectively during delay intervals of the task, and simultaneously impaired task performance. Despite the reduction in delay-related SHPD, stress increased delay-related spiking rates. These findings suggest that neural codes utilizing SHPD within PFC networks likely reflects an additional important neurophysiological mechanism for maintenance of past information over time. Stress

  5. Pattern recognition in spectra

    Science.gov (United States)

    Gebran, M.; Paletou, F.

    2017-06-01

    We present a new automated procedure that simultaneously derives the effective temperature Teff, surface gravity log g, metallicity [Fe/H], and equatorial projected rotational velocity ve sin i for stars. The procedure is inspired by the well-known PCA-based inversion of spectropolarimetric full-Stokes solar data, which was used both for Zeeman and Hanle effects. The efficiency and accuracy of this procedure have been proven for FGK, A, and late type dwarf stars of K and M spectral types. Learning databases are generated from the Elodie stellar spectra library using observed spectra for which fundamental parameters were already evaluated or with synthetic data. The synthetic spectra are calculated using ATLAS9 model atmospheres. This technique helped us to detect many peculiar stars such as Am, Ap, HgMn, SiEuCr and binaries. This fast and efficient technique could be used every time a pattern recognition is needed. One important application is the understanding of the physical properties of planetary surfaces by comparing aboard instrument data to synthetic ones.

  6. Estimating Spectra from Photometry

    Science.gov (United States)

    Kalmbach, J. Bryce; Connolly, Andrew J.

    2017-12-01

    Measuring the physical properties of galaxies such as redshift frequently requires the use of spectral energy distributions (SEDs). SED template sets are, however, often small in number and cover limited portions of photometric color space. Here we present a new method to estimate SEDs as a function of color from a small training set of template SEDs. We first cover the mathematical background behind the technique before demonstrating our ability to reconstruct spectra based upon colors and then compare our results to other common interpolation and extrapolation methods. When the photometric filters and spectra overlap, we show that the error in the estimated spectra is reduced by more than 65% compared to the more commonly used techniques. We also show an expansion of the method to wavelengths beyond the range of the photometric filters. Finally, we demonstrate the usefulness of our technique by generating 50 additional SED templates from an original set of 10 and by applying the new set to photometric redshift estimation. We are able to reduce the photometric redshifts standard deviation by at least 22.0% and the outlier rejected bias by over 86.2% compared to original set for z ≤ 3.

  7. Pattern recognition in spectra

    International Nuclear Information System (INIS)

    Gebran, M; Paletou, F

    2017-01-01

    We present a new automated procedure that simultaneously derives the effective temperature T eff , surface gravity log g , metallicity [ Fe/H ], and equatorial projected rotational velocity v e sin i for stars. The procedure is inspired by the well-known PCA-based inversion of spectropolarimetric full-Stokes solar data, which was used both for Zeeman and Hanle effects. The efficiency and accuracy of this procedure have been proven for FGK, A, and late type dwarf stars of K and M spectral types. Learning databases are generated from the Elodie stellar spectra library using observed spectra for which fundamental parameters were already evaluated or with synthetic data. The synthetic spectra are calculated using ATLAS9 model atmospheres. This technique helped us to detect many peculiar stars such as Am, Ap, HgMn, SiEuCr and binaries. This fast and efficient technique could be used every time a pattern recognition is needed. One important application is the understanding of the physical properties of planetary surfaces by comparing aboard instrument data to synthetic ones. (paper)

  8. Temporally coordinated spiking activity of human induced pluripotent stem cell-derived neurons co-cultured with astrocytes.

    Science.gov (United States)

    Kayama, Tasuku; Suzuki, Ikuro; Odawara, Aoi; Sasaki, Takuya; Ikegaya, Yuji

    2018-01-01

    In culture conditions, human induced-pluripotent stem cells (hiPSC)-derived neurons form synaptic connections with other cells and establish neuronal networks, which are expected to be an in vitro model system for drug discovery screening and toxicity testing. While early studies demonstrated effects of co-culture of hiPSC-derived neurons with astroglial cells on survival and maturation of hiPSC-derived neurons, the population spiking patterns of such hiPSC-derived neurons have not been fully characterized. In this study, we analyzed temporal spiking patterns of hiPSC-derived neurons recorded by a multi-electrode array system. We discovered that specific sets of hiPSC-derived neurons co-cultured with astrocytes showed more frequent and highly coherent non-random synchronized spike trains and more dynamic changes in overall spike patterns over time. These temporally coordinated spiking patterns are physiological signs of organized circuits of hiPSC-derived neurons and suggest benefits of co-culture of hiPSC-derived neurons with astrocytes. Copyright © 2017 Elsevier Inc. All rights reserved.

  9. Starburst amacrine cells change from spiking to nonspiking neurons during retinal development.

    Science.gov (United States)

    Zhou, Z J; Fain, G L

    1996-01-01

    The membrane excitability of cholinergic (starburst) amacrine cells was studied in the rabbit retina during postnatal development. Whole-cell patch-clamp recordings were made from 110 displaced starburst cells in a thin retina] slice preparation of rabbits between postnatal days P1 and P56 old. We report that displaced starburst cells undergo a dramatic transition from spiking to nonspiking, caused by a loss of voltage-gated Na currents. This change in membrane excitability occurred just after eye opening (P10), such that all of the starburst cells tested before eye opening had conspicuous tetrodotoxin-sensitive Na currents and action potentials, but none tested after the first 3 postnatal weeks had detectable Na currents or spikes. Our results suggest that starburst cells use action potentials transiently during development and probably play a functional role in visual development. These cells then cease to spike as the retina matures, presumably consistent with their role in visual processing in the mature retina. Images Fig. 1 PMID:8755602

  10. Removal of polycyclic aromatic hydrocarbons in soil spiked with model mixtures of petroleum hydrocarbons and heterocycles using biosurfactants from Rhodococcus ruber IEGM 231.

    Science.gov (United States)

    Ivshina, Irina; Kostina, Ludmila; Krivoruchko, Anastasiya; Kuyukina, Maria; Peshkur, Tatyana; Anderson, Peter; Cunningham, Colin

    2016-07-15

    Removal of polycyclic aromatic hydrocarbons (PAHs) in soil using biosurfactants (BS) produced by Rhodococcus ruber IEGM 231 was studied in soil columns spiked with model mixtures of major petroleum constituents. A crystalline mixture of single PAHs (0.63g/kg), a crystalline mixture of PAHs (0.63g/kg) and polycyclic aromatic sulfur heterocycles (PASHs), and an artificially synthesized non-aqueous phase liquid (NAPL) containing PAHs (3.00g/kg) dissolved in alkanes C10-C19 were used for spiking. Percentage of PAH removal with BS varied from 16 to 69%. Washing activities of BS were 2.5 times greater than those of synthetic surfactant Tween 60 in NAPL-spiked soil and similar to Tween 60 in crystalline-spiked soil. At the same time, amounts of removed PAHs were equal and consisted of 0.3-0.5g/kg dry soil regardless the chemical pattern of a model mixture of petroleum hydrocarbons and heterocycles used for spiking. UV spectra for soil before and after BS treatment were obtained and their applicability for differentiated analysis of PAH and PASH concentration changes in remediated soil was shown. The ratios A254nm/A288nm revealed that BS increased biotreatability of PAH-contaminated soils. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Epileptic Negative Myoclonus as the First and Only Symptom in a Challenging Diagnosis of Benign Epilepsy With Centrotemporal Spikes

    Directory of Open Access Journals (Sweden)

    Jing Chen MD

    2017-07-01

    Full Text Available Objective: To investigate the clinical and neurophysiological characteristics of epileptic negative myoclonus as the first and only ictal symptom of benign epilepsy with centrotemporal spikes. Methods: Electrophysiological evaluations included polygraphic recordings with simultaneous video electroencephalogram monitoring and tests performed with patient’s upper limb outstretched in standing posture. Epileptic negative myoclonus manifestations, electrophysiological features, and responses to antiepileptic drugs were analyzed. Results: The authors report 2 patients with benign epilepsy with centrotemporal spikes, who had epileptic negative myoclonus as the first and only seizure type. Video electroencephalogram monitoring results showed that their negative myoclonus seizures were emanating from the contralateral central and the parietal regions. Epileptic negative myoclonus was controlled by administration of valproate and levetiracetam. Conclusion: Epileptic negative myoclonus can be the first and only seizure type of benign epilepsy with centrotemporal spikes, and long-term follow-up monitoring should be the care for the recurrence and/or presence of other types of seizures.

  12. Taped Random Spectra for Reliability Demonstration Testing

    Science.gov (United States)

    1981-04-01

    power switch. The outputs of all the gener- ators are the input to a single Operational Amplifier ( OpAmp ). The output of the OpAmp is adjusted to...approximately 0. 250 Vrms using the 100K potentiometer. The variable capacitor, on the input side of the OpAmp is adjusted to minimize K harmonic...mechanical "On" resistance < 200 ohms Physical dimensions 16.42 in. x 6.30 in. max. (417 x 160 mm max) (outline dim.) Ra1-0639-059(3/4)W 2-75 Table 2

  13. Severe acute respiratory syndrome coronavirus (SARS-CoV) infection inhibition using spike protein heptad repeat-derived peptides.

    NARCIS (Netherlands)

    B.J. Bosch (Berend Jan); B.E.E. Martina (Byron); R. van der Zee (Ruurd); J. Lepault (Jean); B.J. Haijema; C. Versluis (Cees); A.J.R. Heck (Albert); R. de Groot (Ronald); A.D.M.E. Osterhaus (Albert); P.J.M. Rottier (Peter)

    2004-01-01

    textabstractThe coronavirus SARS-CoV is the primary cause of the life-threatening severe acute respiratory syndrome (SARS). With the aim of developing therapeutic agents, we have tested peptides derived from the membrane-proximal (HR2) and membrane-distal (HR1) heptad repeat region of the spike

  14. Label-free capture of breast cancer cells spiked in buffy coats using carbon nanotube antibody micro-arrays

    Science.gov (United States)

    Khosravi, Farhad; Trainor, Patrick; Rai, Shesh N.; Kloecker, Goetz; Wickstrom, Eric; Panchapakesan, Balaji

    2016-04-01

    We demonstrate the rapid and label-free capture of breast cancer cells spiked in buffy coats using nanotube-antibody micro-arrays. Single wall carbon nanotube arrays were manufactured using photo-lithography, metal deposition, and etching techniques. Anti-epithelial cell adhesion molecule (EpCAM) antibodies were functionalized to the surface of the nanotube devices using 1-pyrene-butanoic acid succinimidyl ester functionalization method. Following functionalization, plain buffy coat and MCF7 cell spiked buffy coats were adsorbed on to the nanotube device and electrical signatures were recorded for differences in interaction between samples. A statistical classifier for the ‘liquid biopsy’ was developed to create a predictive model based on dynamic time warping to classify device electrical signals that corresponded to plain (control) or spiked buffy coats (case). In training test, the device electrical signals originating from buffy versus spiked buffy samples were classified with ˜100% sensitivity, ˜91% specificity and ˜96% accuracy. In the blinded test, the signals were classified with ˜91% sensitivity, ˜82% specificity and ˜86% accuracy. A heatmap was generated to visually capture the relationship between electrical signatures and the sample condition. Confocal microscopic analysis of devices that were classified as spiked buffy coats based on their electrical signatures confirmed the presence of cancer cells, their attachment to the device and overexpression of EpCAM receptors. The cell numbers were counted to be ˜1-17 cells per 5 μl per device suggesting single cell sensitivity in spiked buffy coats that is scalable to higher volumes using the micro-arrays.

  15. Deconvolution of Positrons' Lifetime spectra

    International Nuclear Information System (INIS)

    Calderin Hidalgo, L.; Ortega Villafuerte, Y.

    1996-01-01

    In this paper, we explain the iterative method previously develop for the deconvolution of Doppler broadening spectra using the mathematical optimization theory. Also, we start the adaptation and application of this method to the deconvolution of positrons' lifetime annihilation spectra

  16. Nuclear Spectra from Skyrmions

    International Nuclear Information System (INIS)

    Manton, N.

    2009-01-01

    For some time now, the Skyrme model has been studied as an effective nonlinear field theory in nuclear physics. Its classical, stable soliton solutions, called Skyrmions, have a conserved topological charge which is identified with baryon number. A quantized Skyrmion models a nucleus. Skyrmions with baryon number a multiple of four are structurally similar to the cluster structures well-known in the a-particle model. The most convenient quantization scheme treats a Skyrmion as a rigid body in space and isospin space, and quantizes just the collective rotational motion. Some selected vibrational modes of Skyrmions may be included too. This approach has been applied previously to Skyrmions up to baryon number about 6, by Braaten and Carson, Kopeliovich, Walhout, and others. Recently, Battye, Manton, Sutcliffe and Wood have calculated the moment of inertia tensors in space and isospace for Skyrmions up to baryon number 12. The allowed spin and isospin states have been found, and the energy spectra calculated. These spectra agree quite well with experimental spectra of several light nuclei, including 6 L i, 8 B e, 1 2C , and their various isotopes. However, for this to work, the length scale needs to be set rather larger than the traditional value determined by Adkins and Nappi using the nucleon and delta resonance masses. The most interesting theoretical feature of these calculations is that isospin and spin excitations are treated in a uniform way. There are quite subtle constraints on the possible spin and isospin values, because of the classical symmetries of each Skyrmion. Manton and his students, and Battye and Sutcliffe, have published a number of papers on classical and quantized Skyrmions in journals and on the arXiv. They are also jointly contributing an invited chapter on Skyrmions and Nuclei to the book The Multifaceted Skyrmion, currently being edited by G. Brown and M. Rho.(author)

  17. Benchmarking Spike-Based Visual Recognition: A Dataset and Evaluation

    Science.gov (United States)

    Liu, Qian; Pineda-García, Garibaldi; Stromatias, Evangelos; Serrano-Gotarredona, Teresa; Furber, Steve B.

    2016-01-01

    Today, increasing attention is being paid to research into spike-based neural computation both to gain a better understanding of the brain and to explore biologically-inspired computation. Within this field, the primate visual pathway and its hierarchical organization have been extensively studied. Spiking Neural Networks (SNNs), inspired by the understanding of observed biological structure and function, have been successfully applied to visual recognition and classification tasks. In addition, implementations on neuromorphic hardware have enabled large-scale networks to run in (or even faster than) real time, making spike-based neural vision processing accessible on mobile robots. Neuromorphic sensors such as silicon retinas are able to feed such mobile systems with real-time visual stimuli. A new set of vision benchmarks for spike-based neural processing are now needed to measure progress quantitatively within this rapidly advancing field. We propose that a large dataset of spike-based visual stimuli is needed to provide meaningful comparisons between different systems, and a corresponding evaluation methodology is also required to measure the performance of SNN models and their hardware implementations. In this paper we first propose an initial NE (Neuromorphic Engineering) dataset based on standard computer vision benchmarksand that uses digits from the MNIST database. This dataset is compatible with the state of current research on spike-based image recognition. The corresponding spike trains are produced using a range of techniques: rate-based Poisson spike generation, rank order encoding, and recorded output from a silicon retina with both flashing and oscillating input stimuli. In addition, a complementary evaluation methodology is presented to assess both model-level and hardware-level performance. Finally, we demonstrate the use of the dataset and the evaluation methodology using two SNN models to validate the performance of the models and their hardware

  18. Spike morphology in blast-wave-driven instability experiments

    International Nuclear Information System (INIS)

    Kuranz, C. C.; Drake, R. P.; Grosskopf, M. J.; Fryxell, B.; Budde, A.; Hansen, J. F.; Miles, A. R.; Plewa, T.; Hearn, N.; Knauer, J.

    2010-01-01

    The laboratory experiments described in the present paper observe the blast-wave-driven Rayleigh-Taylor instability with three-dimensional (3D) initial conditions. About 5 kJ of energy from the Omega laser creates conditions similar to those of the He-H interface during the explosion phase of a supernova. The experimental target is a 150 μm thick plastic disk followed by a low-density foam. The plastic piece has an embedded, 3D perturbation. The basic structure of the pattern is two orthogonal sine waves where each sine wave has an amplitude of 2.5 μm and a wavelength of 71 μm. In some experiments, an additional wavelength is added to explore the interaction of modes. In experiments with 3D initial conditions the spike morphology differs from what has been observed in other Rayleigh-Taylor experiments and simulations. Under certain conditions, experimental radiographs show some mass extending from the interface to the shock front. Current simulations show neither the spike morphology nor the spike penetration observed in the experiments. The amount of mass reaching the shock front is analyzed and potential causes for the spike morphology and the spikes reaching the shock are discussed. One such hypothesis is that these phenomena may be caused by magnetic pressure, generated by an azimuthal magnetic field produced by the plasma dynamics.

  19. A proteomic study of spike development inhibition in bread wheat.

    Science.gov (United States)

    Zheng, Yong-Sheng; Guo, Jun-Xian; Zhang, Jin-Peng; Gao, Ai-Nong; Yang, Xin-Ming; Li, Xiu-Quan; Liu, Wei-Hua; Li, Li-Hui

    2013-09-01

    Spike development in wheat is a complicated development process and determines the wheat propagation and survival. We report herein a proteomic study on the bread wheat mutant strain 5660M underlying spike development inhibition. A total of 121 differentially expressed proteins, which were involved in cold stress response, protein folding and assembly, cell-cycle regulation, scavenging of ROS, and the autonomous pathway were identified using MS/MS and database searching. We found that cold responsive proteins were highly expressed in the mutant in contrast to those expressed in the wild-type line. Particularly, the autonomous pathway protein FVE, which modulates flowering, was dramatically downregulated and closely related to the spike development inhibition phenotype of 5660M. A quantitative RT-PCR study demonstrated that the transcription of the FVE and other six genes in the autonomous pathway and downstream flowering regulators were all markedly downregulated. The results indicate that spike development of 5660M cannot complete the floral transition. FVE might play an important role in the spikes development of the wheat. Our results provide the theory basis for studying floral development and transition in the reproductive growth period, and further analysis of wheat yield formation. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Multiplexed Spike Coding and Adaptation in the Thalamus

    Directory of Open Access Journals (Sweden)

    Rebecca A. Mease

    2017-05-01

    Full Text Available High-frequency “burst” clusters of spikes are a generic output pattern of many neurons. While bursting is a ubiquitous computational feature of different nervous systems across animal species, the encoding of synaptic inputs by bursts is not well understood. We find that bursting neurons in the rodent thalamus employ “multiplexing” to differentially encode low- and high-frequency stimulus features associated with either T-type calcium “low-threshold” or fast sodium spiking events, respectively, and these events adapt differently. Thus, thalamic bursts encode disparate information in three channels: (1 burst size, (2 burst onset time, and (3 precise spike timing within bursts. Strikingly, this latter “intraburst” encoding channel shows millisecond-level feature selectivity and adapts across statistical contexts to maintain stable information encoded per spike. Consequently, calcium events both encode low-frequency stimuli and, in parallel, gate a transient window for high-frequency, adaptive stimulus encoding by sodium spike timing, allowing bursts to efficiently convey fine-scale temporal information.

  1. ViSAPy: A Python tool for biophysics-based generation of virtual spiking activity for evaluation of spike-sorting algorithms

    OpenAIRE

    Hagen, Espen; Ness, Torbjørn V.; Khosrowshahi, Amir; Sørensen, Christina; Fyhn, Marianne; Hafting, Torkel; Franke, Felix; Einevoll, Gaute T.

    2015-01-01

    Background: New, silicon-based multielectrodes comprising hundreds or more electrode contacts offer the possibility to record spike trains from thousands of neurons simultaneously. This potential cannot be realized unless accurate, reliable automated methods for spike sorting are developed, in turn requiring benchmarking data sets with known ground-truth spike times.New method: We here present a general simulation tool for computing benchmarking data for evaluation of spike-sorting algorithms...

  2. Spike Pattern Structure Influences Synaptic Efficacy Variability Under STDP and Synaptic Homeostasis. I: Spike Generating Models on Converging Motifs

    Directory of Open Access Journals (Sweden)

    Zedong eBi

    2016-02-01

    Full Text Available In neural systems, synaptic plasticity is usually driven by spike trains. Due to the inherent noises of neurons and synapses as well as the randomness of connection details, spike trains typically exhibit variability such as spatial randomness and temporal stochasticity, resulting in variability of synaptic changes under plasticity, which we call efficacy variability. How the variability of spike trains influences the efficacy variability of synapses remains unclear. In this paper, we try to understand this influence under pair-wise additive spike-timing dependent plasticity (STDP when the mean strength of plastic synapses into a neuron is bounded (synaptic homeostasis. Specifically, we systematically study, analytically and numerically, how four aspects of statistical features, i.e. synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations, as well as their interactions influence the efficacy variability in converging motifs (simple networks in which one neuron receives from many other neurons. Neurons (including the post-synaptic neuron in a converging motif generate spikes according to statistical models with tunable parameters. In this way, we can explicitly control the statistics of the spike patterns, and investigate their influence onto the efficacy variability, without worrying about the feedback from synaptic changes onto the dynamics of the post-synaptic neuron. We separate efficacy variability into two parts: the drift part (DriftV induced by the heterogeneity of change rates of different synapses, and the diffusion part (DiffV induced by weight diffusion caused by stochasticity of spike trains. Our main findings are: (1 synchronous firing and burstiness tend to increase DiffV, (2 heterogeneity of rates induces DriftV when potentiation and depression in STDP are not balanced, and (3 heterogeneity of cross-correlations induces DriftV together with heterogeneity of rates. We anticipate our

  3. Energetic Proton Spectra Measured by the Van Allen Probes

    Science.gov (United States)

    Summers, Danny; Shi, Run; Engebretson, Mark J.; Oksavik, Kjellmar; Manweiler, Jerry W.; Mitchell, Donald G.

    2017-10-01

    We test the hypothesis that pitch angle scattering by electromagnetic ion cyclotron (EMIC) waves can limit ring current proton fluxes. For two chosen magnetic storms, during 17-20 March 2013 and 17-20 March 2015, we measure proton energy spectra in the region 3 ≤ L ≤ 6 using the RBSPICE-B instrument on the Van Allen Probes. The most intense proton spectra are observed to occur during the recovery periods of the respective storms. Using proton precipitation data from the POES (NOAA and MetOp) spacecraft, we deduce that EMIC wave action was prevalent at the times and L-shell locations of the most intense proton spectra. We calculate limiting ring current proton energy spectra from recently developed theory. Comparisons between the observed proton energy spectra and the theoretical limiting spectra show reasonable agreement. We conclude that the measurements of the most intense proton spectra are consistent with self-limiting by EMIC wave scattering.

  4. Seizmic response spectra

    Directory of Open Access Journals (Sweden)

    Igor Leššo

    2005-12-01

    Full Text Available A computation of 1D and 3D seismic motion parameters was made and the influence of input parameters on these parameters were analysed. A modelling was realised on the examples of sedimentary structures geotechnical models. This comparison provides different spectral and frequencial values and spectral accelerations. The differences in seismic response spectra are influenced not only by properties of geological structures but also by the methodics of the soil structure interaction modeling and input time history spectral composition. However, the influence of geotechnical properties of geological structures on the output results are apparent. The modelling results of different input time history spectral composition, the Ricker impuls and the Gabor function were compared. In the area of cement factory in Rohožník, the new rotary kiln furnance is planned to be build. In the sense of STN 73 0036 the expert seismic judgment has been claimed. The standard and local seismic response spectra is computed for the place where the rotary kiln will be situated. The application of the local spectral acceleration in seismic load computations enables to save costs in comparing with the standard acceleration.

  5. Spiking Neural Network With Distributed Plasticity Reproduces Cerebellar Learning in Eye Blink Conditioning Paradigms.

    Science.gov (United States)

    Antonietti, Alberto; Casellato, Claudia; Garrido, Jesús A; Luque, Niceto R; Naveros, Francisco; Ros, Eduardo; D' Angelo, Egidio; Pedrocchi, Alessandra

    2016-01-01

    In this study, we defined a realistic cerebellar model through the use of artificial spiking neural networks, testing it in computational simulations that reproduce associative motor tasks in multiple sessions of acquisition and extinction. By evolutionary algorithms, we tuned the cerebellar microcircuit to find out the near-optimal plasticity mechanism parameters that better reproduced human-like behavior in eye blink classical conditioning, one of the most extensively studied paradigms related to the cerebellum. We used two models: one with only the cortical plasticity and another including two additional plasticity sites at nuclear level. First, both spiking cerebellar models were able to well reproduce the real human behaviors, in terms of both "timing" and "amplitude", expressing rapid acquisition, stable late acquisition, rapid extinction, and faster reacquisition of an associative motor task. Even though the model with only the cortical plasticity site showed good learning capabilities, the model with distributed plasticity produced faster and more stable acquisition of conditioned responses in the reacquisition phase. This behavior is explained by the effect of the nuclear plasticities, which have slow dynamics and can express memory consolidation and saving. We showed how the spiking dynamics of multiple interactive neural mechanisms implicitly drive multiple essential components of complex learning processes.  This study presents a very advanced computational model, developed together by biomedical engineers, computer scientists, and neuroscientists. Since its realistic features, the proposed model can provide confirmations and suggestions about neurophysiological and pathological hypotheses and can be used in challenging clinical applications.

  6. Artificial intelligence analysis of paraspinal power spectra.

    Science.gov (United States)

    Oliver, C W; Atsma, W J

    1996-10-01

    OBJECTIVE: As an aid to discrimination of sufferers with back pain an artificial intelligence neural network was constructed to differentiate paraspinal power spectra. DESIGN: Clinical investigation using surface electromyography. METHOD: The surface electromyogram power spectra from 60 subjects, 33 non-back-pain sufferers and 27 chronic back pain sufferers were used to construct a back propagation neural network that was then tested. Subjects were placed on a test frame in 30 degrees of lumbar forward flexion. An isometric load of two-thirds maximum voluntary contraction was held constant for 30 s whilst surface electromyograms were recorded at the level of the L(4-5). Paraspinal power spectra were calculated and loaded into the input layer of a three-layer back propagation network. The neural network classified the spectra into normal or back pain type. RESULTS: The back propagation neural was shown to have satisfactory convergence with a specificity of 79% and a sensitivity of 80%. CONCLUSIONS: Artificial intelligence neural networks appear to be a useful method of differentiating paraspinal power spectra in back-pain sufferers.

  7. Probabilistic Decision Making with Spikes: From ISI Distributions to Behaviour via Information Gain.

    Directory of Open Access Journals (Sweden)

    Javier A Caballero

    Full Text Available Computational theories of decision making in the brain usually assume that sensory 'evidence' is accumulated supporting a number of hypotheses, and that the first accumulator to reach threshold triggers a decision in favour of its associated hypothesis. However, the evidence is often assumed to occur as a continuous process whose origins are somewhat abstract, with no direct link to the neural signals - action potentials or 'spikes' - that must ultimately form the substrate for decision making in the brain. Here we introduce a new variant of the well-known multi-hypothesis sequential probability ratio test (MSPRT for decision making whose evidence observations consist of the basic unit of neural signalling - the inter-spike interval (ISI - and which is based on a new form of the likelihood function. We dub this mechanism s-MSPRT and show its precise form for a range of realistic ISI distributions with positive support. In this way we show that, at the level of spikes, the refractory period may actually facilitate shorter decision times, and that the mechanism is robust against poor choice of the hypothesized data distribution. We show that s-MSPRT performance is related to the Kullback-Leibler divergence (KLD or information gain between ISI distributions, through which we are able to link neural signalling to psychophysical observation at the behavioural level. Thus, we find the mean information needed for a decision is constant, thereby offering an account of Hick's law (relating decision time to the number of choices. Further, the mean decision time of s-MSPRT shows a power law dependence on the KLD offering an account of Piéron's law (relating reaction time to stimulus intensity. These results show the foundations for a research programme in which spike train analysis can be made the basis for predictions about behavior in multi-alternative choice tasks.

  8. The race to learn: spike timing and STDP can coordinate learning and recall in CA3.

    Science.gov (United States)

    Nolan, Christopher R; Wyeth, Gordon; Milford, Michael; Wiles, Janet

    2011-06-01

    The CA3 region of the hippocampus has long been proposed as an autoassociative network performing pattern completion on known inputs. The dentate gyrus (DG) region is often proposed as a network performing the complementary function of pattern separation. Neural models of pattern completion and separation generally designate explicit learning phases to encode new information and assume an ideal fixed threshold at which to stop learning new patterns and begin recalling known patterns. Memory systems are significantly more complex in practice, with the degree of memory recall depending on context-specific goals. Here, we present our spike-timing separation and completion (STSC) model of the entorhinal cortex (EC), DG, and CA3 network, ascribing to each region a role similar to that in existing models but adding a temporal dimension by using a spiking neural network. Simulation results demonstrate that (a) spike-timing dependent plasticity in the EC-CA3 synapses provides a pattern completion ability without recurrent CA3 connections, (b) the race between activation of CA3 cells via EC-CA3 synapses and activation of the same cells via DG-CA3 synapses distinguishes novel from known inputs, and (c) modulation of the EC-CA3 synapses adjusts the learned versus test input similarity required to evoke a direct CA3 response prior to any DG activity, thereby adjusting the pattern completion threshold. These mechanisms suggest that spike timing can arbitrate between learning and recall based on the novelty of each individual input, ensuring control of the learn-recall decision resides in the same subsystem as the learned memories themselves. The proposed modulatory signal does not override this decision but biases the system toward either learning or recall. The model provides an explanation for empirical observations that a reduction in novelty produces a corresponding reduction in the latency of responses in CA3 and CA1. Copyright © 2010 Wiley-Liss, Inc.

  9. Grain price spikes and beggar-thy-neighbor policy responses

    DEFF Research Database (Denmark)

    Jensen, Hans Grinsted; Anderson, Kym

    2017-01-01

    When prices spike in international grain markets, national governments often reduce the extent to which that spike affects their domestic food markets. Those actions exacerbate the price spike and international welfare transfer associated with that terms of trade change. Several recent analyses...... have assessed the extent to which those policies contributed to the 2006–08 international price rises but only by focusing on one commodity or by using a back-of-the envelope (BOTE) method. The present more comprehensive analysis uses a global, economy-wide model that is able to take account...... of the interactions between markets for farm products that are closely related in production and/or consumption and able to estimate the impacts of those insulating policies on grain prices and on the grain trade and economic welfare of the world's various countries. Our results support the conclusion from earlier...

  10. Grain price spikes and beggar-thy-neighbor policy responses

    DEFF Research Database (Denmark)

    Jensen, Hans Grinsted; Anderson, Kym

    When prices spike in international grain markets, national governments often reduce the extent to which that spike affects their domestic food markets. Those actions exacerbate the price spike and international welfare transfer associated with that terms of trade change. Several recent analyses...... have assessed the extent to which those policies contributed to the 2006-08 international price rise, but only by focusing on one commodity or using a back-of-the envelope (BOTE) method. This paper provides a more-comprehensive analysis using a global economy-wide model that is able to take account...... of the interactions between markets for farm products that are closely related in production and/or consumption, and able to estimate the impacts of those insulating policies on grain prices and on the grain trade and economic welfare of the world’s various countries. Our results support the conclusion from earlier...

  11. Spikes and memory in (Nord Pool) electricity price spot prices

    DEFF Research Database (Denmark)

    Proietti, Tomasso; Haldrup, Niels; Knapik, Oskar

    from the normal price, where the latter is defined as the expectation arising from a model accounting for long memory at the zero and at the weekly seasonal frequencies, given the knowledge of the past realizations. Hence, a spike is associated to a time series innovation with size larger than......Electricity spot prices are subject to transitory sharp movements commonly referred to as spikes. The paper aims at assessing their effects on model based inferences and predictions, with reference to the Nord Pool power exchange. We identify a spike as a price value which deviates substantially...... a specified threshold. The latter regulates the robustness of the estimates of the underlying price level and it is chosen by a data driven procedure that focuses on the ability to predict future prices. The normal price is computed by a modified Kalman filter, which robustifies the inferences by cleaning...

  12. Inherently stochastic spiking neurons for probabilistic neural computation

    KAUST Repository

    Al-Shedivat, Maruan

    2015-04-01

    Neuromorphic engineering aims to design hardware that efficiently mimics neural circuitry and provides the means for emulating and studying neural systems. In this paper, we propose a new memristor-based neuron circuit that uniquely complements the scope of neuron implementations and follows the stochastic spike response model (SRM), which plays a cornerstone role in spike-based probabilistic algorithms. We demonstrate that the switching of the memristor is akin to the stochastic firing of the SRM. Our analysis and simulations show that the proposed neuron circuit satisfies a neural computability condition that enables probabilistic neural sampling and spike-based Bayesian learning and inference. Our findings constitute an important step towards memristive, scalable and efficient stochastic neuromorphic platforms. © 2015 IEEE.

  13. Evaluation of the uranium double spike technique for environmental monitoring

    International Nuclear Information System (INIS)

    Hemberger, P.H.; Rokop, D.J.; Efurd, D.W.; Roensch, F.R.; Smith, D.H.; Turner, M.L.; Barshick, C.M.; Bayne, C.K.

    1998-01-01

    Use of a uranium double spike in analysis of environmental samples showed that a 235 U enrichment of 1% ( 235 U/ 238 U = 0.00732) can be distinguished from natural ( 235 U/ 238 U = 0.00725). Experiments performed jointly at Los Alamos National Laboratory (LANL) and Oak Ridge National Laboratory (ORNL) used a carefully calibrated double spike of 233 U and 236 U to obtain much better precision than is possible using conventional analytical techniques. A variety of different sampling media (vegetation and swipes) showed that, provided sufficient care is exercised in choice of sample type, relative standard deviations of less than ± 0.5% can be routinely obtained. This ability, unavailable without use of the double spike, has enormous potential significance in the detection of undeclared nuclear facilities

  14. A Cross-Correlated Delay Shift Supervised Learning Method for Spiking Neurons with Application to Interictal Spike Detection in Epilepsy.

    Science.gov (United States)

    Guo, Lilin; Wang, Zhenzhong; Cabrerizo, Mercedes; Adjouadi, Malek

    2017-05-01

    This study introduces a novel learning algorithm for spiking neurons, called CCDS, which is able to learn and reproduce arbitrary spike patterns in a supervised fashion allowing the processing of spatiotemporal information encoded in the precise timing of spikes. Unlike the Remote Supervised Method (ReSuMe), synapse delays and axonal delays in CCDS are variants which are modulated together with weights during learning. The CCDS rule is both biologically plausible and computationally efficient. The properties of this learning rule are investigated extensively through experimental evaluations in terms of reliability, adaptive learning performance, generality to different neuron models, learning in the presence of noise, effects of its learning parameters and classification performance. Results presented show that the CCDS learning method achieves learning accuracy and learning speed comparable with ReSuMe, but improves classification accuracy when compared to both the Spike Pattern Association Neuron (SPAN) learning rule and the Tempotron learning rule. The merit of CCDS rule is further validated on a practical example involving the automated detection of interictal spikes in EEG records of patients with epilepsy. Results again show that with proper encoding, the CCDS rule achieves good recognition performance.

  15. Continuum Fitting HST QSO Spectra

    Science.gov (United States)

    Tytler, David; Oliversen, Ronald J. (Technical Monitor)

    2002-01-01

    The Principal Component Analysis (PCA) method which we are using to fit and describe QSO spectra relies upon the fact that QSO continuum are generally very smooth and simple except for emission and absorption lines. To see this we need high signal-to-noise (S/N) spectra of QSOs at low redshift which have relatively few absorption lines in the Lyman-a forest. We need a large number of such spectra to use as the basis set for the PCA analysis which will find the set of principal component spectra which describe the QSO family as a whole. We have found that too few HST spectra have the required S/N and hence we need to supplement them with ground based spectra of QSOs at higher redshift. We have many such spectra and we have been working to make them suitable for this analysis. We have concentrated on this topic since 12/15/01.

  16. An Event-Driven Classifier for Spiking Neural Networks Fed with Synthetic or Dynamic Vision Sensor Data

    Directory of Open Access Journals (Sweden)

    Evangelos Stromatias

    2017-06-01

    Full Text Available This paper introduces a novel methodology for training an event-driven classifier within a Spiking Neural Network (SNN System capable of yielding good classification results when using both synthetic input data and real data captured from Dynamic Vision Sensor (DVS chips. The proposed supervised method uses the spiking activity provided by an arbitrary topology of prior SNN layers to build histograms and train the classifier in the frame domain using the stochastic gradient descent algorithm. In addition, this approach can cope with leaky integrate-and-fire neuron models within the SNN, a desirable feature for real-world SNN applications, where neural activation must fade away after some time in the absence of inputs. Consequently, this way of building histograms captures the dynamics of spikes immediately before the classifier. We tested our method on the MNIST data set using different synthetic encodings and real DVS sensory data sets such as N-MNIST, MNIST-DVS, and Poker-DVS using the same network topology and feature maps. We demonstrate the effectiveness of our approach by achieving the highest classification accuracy reported on the N-MNIST (97.77% and Poker-DVS (100% real DVS data sets to date with a spiking convolutional network. Moreover, by using the proposed method we were able to retrain the output layer of a previously reported spiking neural network and increase its performance by 2%, suggesting that the proposed classifier can be used as the output layer in works where features are extracted using unsupervised spike-based learning methods. In addition, we also analyze SNN performance figures such as total event activity and network latencies, which are relevant for eventual hardware implementations. In summary, the paper aggregates unsupervised-trained SNNs with a supervised-trained SNN classifier, combining and applying them to heterogeneous sets of benchmarks, both synthetic and from real DVS chips.

  17. Stochastic hybrid model of spontaneous dendritic NMDA spikes

    International Nuclear Information System (INIS)

    Bressloff, Paul C; Newby, Jay M

    2014-01-01

    Following recent advances in imaging techniques and methods of dendritic stimulation, active voltage spikes have been observed in thin dendritic branches of excitatory pyramidal neurons, where the majority of synapses occur. The generation of these dendritic spikes involves both Na + ion channels and M-methyl-D-aspartate receptor (NMDAR) channels. During strong stimulation of a thin dendrite, the resulting high levels of glutamate, the main excitatory neurotransmitter in the central nervous system and an NMDA agonist, modify the current-voltage (I–V) characteristics of an NMDAR so that it behaves like a voltage-gated Na + channel. Hence, the NMDARs can fire a regenerative dendritic spike, just as Na + channels support the initiation of an action potential following membrane depolarization. However, the duration of the dendritic spike is of the order 100 ms rather than 1 ms, since it involves slow unbinding of glutamate from NMDARs rather than activation of hyperpolarizing K + channels. It has been suggested that dendritic NMDA spikes may play an important role in dendritic computations and provide a cellular substrate for short-term memory. In this paper, we consider a stochastic, conductance-based model of dendritic NMDA spikes, in which the noise originates from the stochastic opening and closing of a finite number of Na + and NMDA receptor ion channels. The resulting model takes the form of a stochastic hybrid system, in which membrane voltage evolves according to a piecewise deterministic dynamics that is coupled to a jump Markov process describing the opening and closing of the ion channels. We formulate the noise-induced initiation and termination of a dendritic spike in terms of a first-passage time problem, under the assumption that glutamate unbinding is negligible, which we then solve using a combination of WKB methods and singular perturbation theory. Using a stochastic phase-plane analysis we then extend our analysis to take proper account of the

  18. Bayesian Inference for Structured Spike and Slab Priors

    DEFF Research Database (Denmark)

    Andersen, Michael Riis; Winther, Ole; Hansen, Lars Kai

    2014-01-01

    Sparse signal recovery addresses the problem of solving underdetermined linear inverse problems subject to a sparsity constraint. We propose a novel prior formulation, the structured spike and slab prior, which allows to incorporate a priori knowledge of the sparsity pattern by imposing a spatial...... Gaussian process on the spike and slab probabilities. Thus, prior information on the structure of the sparsity pattern can be encoded using generic covariance functions. Furthermore, we provide a Bayesian inference scheme for the proposed model based on the expectation propagation framework. Using...

  19. Spike propagation in driven chain networks with dominant global inhibition

    International Nuclear Information System (INIS)

    Chang Wonil; Jin, Dezhe Z.

    2009-01-01

    Spike propagation in chain networks is usually studied in the synfire regime, in which successive groups of neurons are synaptically activated sequentially through the unidirectional excitatory connections. Here we study the dynamics of chain networks with dominant global feedback inhibition that prevents the synfire activity. Neural activity is driven by suprathreshold external inputs. We analytically and numerically demonstrate that spike propagation along the chain is a unique dynamical attractor in a wide parameter regime. The strong inhibition permits a robust winner-take-all propagation in the case of multiple chains competing via the inhibition.

  20. Method for spiking soil samples with organic compounds

    DEFF Research Database (Denmark)

    Brinch, Ulla C; Ekelund, Flemming; Jacobsen, Carsten S

    2002-01-01

    We examined the harmful side effects on indigenous soil microorganisms of two organic solvents, acetone and dichloromethane, that are normally used for spiking of soil with polycyclic aromatic hydrocarbons for experimental purposes. The solvents were applied in two contamination protocols to either...... higher than in control soil, probably due mainly to release of predation from indigenous protozoa. In order to minimize solvent effects on indigenous soil microorganisms when spiking native soil samples with compounds having a low water solubility, we propose a common protocol in which the contaminant...

  1. Identification of spikes associated with local sources in continuous time series of atmospheric CO, CO2 and CH4

    Science.gov (United States)

    El Yazidi, Abdelhadi; Ramonet, Michel; Ciais, Philippe; Broquet, Gregoire; Pison, Isabelle; Abbaris, Amara; Brunner, Dominik; Conil, Sebastien; Delmotte, Marc; Gheusi, Francois; Guerin, Frederic; Hazan, Lynn; Kachroudi, Nesrine; Kouvarakis, Giorgos; Mihalopoulos, Nikolaos; Rivier, Leonard; Serça, Dominique

    2018-03-01

    This study deals with the problem of identifying atmospheric data influenced by local emissions that can result in spikes in time series of greenhouse gases and long-lived tracer measurements. We considered three spike detection methods known as coefficient of variation (COV), robust extraction of baseline signal (REBS) and standard deviation of the background (SD) to detect and filter positive spikes in continuous greenhouse gas time series from four monitoring stations representative of the European ICOS (Integrated Carbon Observation System) Research Infrastructure network. The results of the different methods are compared to each other and against a manual detection performed by station managers. Four stations were selected as test cases to apply the spike detection methods: a continental rural tower of 100 m height in eastern France (OPE), a high-mountain observatory in the south-west of France (PDM), a regional marine background site in Crete (FKL) and a marine clean-air background site in the Southern Hemisphere on Amsterdam Island (AMS). This selection allows us to address spike detection problems in time series with different variability. Two years of continuous measurements of CO2, CH4 and CO were analysed. All methods were found to be able to detect short-term spikes (lasting from a few seconds to a few minutes) in the time series. Analysis of the results of each method leads us to exclude the COV method due to the requirement to arbitrarily specify an a priori percentage of rejected data in the time series, which may over- or underestimate the actual number of spikes. The two other methods freely determine the number of spikes for a given set of parameters, and the values of these parameters were calibrated to provide the best match with spikes known to reflect local emissions episodes that are well documented by the station managers. More than 96 % of the spikes manually identified by station managers were successfully detected both in the SD and the

  2. Using a spike-in experiment to evaluate analysis of LC-MS data

    Directory of Open Access Journals (Sweden)

    Tuli Leepika

    2012-02-01

    Full Text Available Abstract Background Recent advances in liquid chromatography-mass spectrometry (LC-MS technology have led to more effective approaches for measuring changes in peptide/protein abundances in biological samples. Label-free LC-MS methods have been used for extraction of quantitative information and for detection of differentially abundant peptides/proteins. However, difference detection by analysis of data derived from label-free LC-MS methods requires various preprocessing steps including filtering, baseline correction, peak detection, alignment, and normalization. Although several specialized tools have been developed to analyze LC-MS data, determining the most appropriate computational pipeline remains challenging partly due to lack of established gold standards. Results The work in this paper is an initial study to develop a simple model with "presence" or "absence" condition using spike-in experiments and to be able to identify these "true differences" using available software tools. In addition to the preprocessing pipelines, choosing appropriate statistical tests and determining critical values are important. We observe that individual statistical tests could lead to different results due to different assumptions and employed metrics. It is therefore preferable to incorporate several statistical tests for either exploration or confirmation purpose. Conclusions The LC-MS data from our spike-in experiment can be used for developing and optimizing LC-MS data preprocessing algorithms and to evaluate workflows implemented in existing software tools. Our current work is a stepping stone towards optimizing LC-MS data acquisition and testing the accuracy and validity of computational tools for difference detection in future studies that will be focused on spiking peptides of diverse physicochemical properties in different concentrations to better represent biomarker discovery of differentially abundant peptides/proteins.

  3. Fractal dimension analysis for spike detection in low SNR extracellular signals.

    Science.gov (United States)

    Salmasi, Mehrdad; Büttner, Ulrich; Glasauer, Stefan

    2016-06-01

    Many algorithms have been suggested for detection and sorting of spikes in extracellular recording. Nevertheless, it is still challenging to detect spikes in low signal-to-noise ratios (SNR). We propose a spike detection algorithm that is based on the fractal properties of extracellular signals and can detect spikes in low SNR regimes. Semi-intact spikes are low-amplitude spikes whose shapes are almost preserved. The detection of these spikes can significantly enhance the performance of multi-electrode recording systems. Semi-intact spikes are simulated by adding three noise components to a spike train: thermal noise, inter-spike noise, and spike-level noise. We show that simulated signals have fractal properties which make them proper candidates for fractal analysis. Then we use fractal dimension as the main core of our spike detection algorithm and call it fractal detector. The performance of the fractal detector is compared with three frequently used spike detectors. We demonstrate that in low SNR, the fractal detector has the best performance and results in the highest detection probability. It is shown that, in contrast to the other three detectors, the performance of the fractal detector is independent of inter-spike noise power and that variations in spike shape do not alter its performance. Finally, we use the fractal detector for spike detection in experimental data and similar to simulations, it is shown that the fractal detector has the best performance in low SNR regimes. The detection of low-amplitude spikes provides more information about the neural activity in the vicinity of the recording electrodes. Our results suggest using the fractal detector as a reliable and robust method for detecting semi-intact spikes in low SNR extracellular signals.

  4. Seismic spectra of events at regional distances

    International Nuclear Information System (INIS)

    Springer, D.L.; Denny, M.D.

    1976-01-01

    About 40 underground nuclear explosions detonated at the Nevada Test Site (NTS) were chosen for analysis of their spectra and any relationships they might have to source parameters such as yield, depth of burial, etc. The sample covered a large yield range (less than 20 kt to greater than 1 Mt). Broadband (0.05 to 20 Hz) data recorded by the four-station seismic network operated by Lawrence Livermore Laboratory were analyzed in a search for unusual explosion signatures in their spectra. Long time windows (total wave train) as well as shorter windows (for instance, P/sub n/) were used as input to calculate the spectra. Much variation in the spectra of the long windows is typical although some gross features are similar, such as a dominant peak in the microseismic window. The variation is such that selection of corner frequencies is impractical and yield scaling could not be determined. Spectra for one NTS earthquake showed more energy in the short periods (less than 1 sec) as well as in the long periods (greater than 8 sec) compared to those for NTS explosions

  5. Spiking Activity of a LIF Neuron in Distributed Delay Framework

    Directory of Open Access Journals (Sweden)

    Saket Kumar Choudhary

    2016-06-01

    Full Text Available Evolution of membrane potential and spiking activity for a single leaky integrate-and-fire (LIF neuron in distributed delay framework (DDF is investigated. DDF provides a mechanism to incorporate memory element in terms of delay (kernel function into a single neuron models. This investigation includes LIF neuron model with two different kinds of delay kernel functions, namely, gamma distributed delay kernel function and hypo-exponential distributed delay kernel function. Evolution of membrane potential for considered models is studied in terms of stationary state probability distribution (SPD. Stationary state probability distribution of membrane potential (SPDV for considered neuron models are found asymptotically similar which is Gaussian distributed. In order to investigate the effect of membrane potential delay, rate code scheme for neuronal information processing is applied. Firing rate and Fano-factor for considered neuron models are calculated and standard LIF model is used for comparative study. It is noticed that distributed delay increases the spiking activity of a neuron. Increase in spiking activity of neuron in DDF is larger for hypo-exponential distributed delay function than gamma distributed delay function. Moreover, in case of hypo-exponential delay function, a LIF neuron generates spikes with Fano-factor less than 1.

  6. Bayesian Inference for Structured Spike and Slab Priors

    DEFF Research Database (Denmark)

    Andersen, Michael Riis; Winther, Ole; Hansen, Lars Kai

    2014-01-01

    Sparse signal recovery addresses the problem of solving underdetermined linear inverse problems subject to a sparsity constraint. We propose a novel prior formulation, the structured spike and slab prior, which allows to incorporate a priori knowledge of the sparsity pattern by imposing a spatial...

  7. Cochlear spike synchronization and neuron coincidence detection model

    Science.gov (United States)

    Bader, Rolf

    2018-02-01

    Coincidence detection of a spike pattern fed from the cochlea into a single neuron is investigated using a physical Finite-Difference model of the cochlea and a physiologically motivated neuron model. Previous studies have shown experimental evidence of increased spike synchronization in the nucleus cochlearis and the trapezoid body [Joris et al., J. Neurophysiol. 71(3), 1022-1036 and 1037-1051 (1994)] and models show tone partial phase synchronization at the transition from mechanical waves on the basilar membrane into spike patterns [Ch. F. Babbs, J. Biophys. 2011, 435135]. Still the traveling speed of waves on the basilar membrane cause a frequency-dependent time delay of simultaneously incoming sound wavefronts up to 10 ms. The present model shows nearly perfect synchronization of multiple spike inputs as neuron outputs with interspike intervals (ISI) at the periodicity of the incoming sound for frequencies from about 30 to 300 Hz for two different amounts of afferent nerve fiber neuron inputs. Coincidence detection serves here as a fusion of multiple inputs into one single event enhancing pitch periodicity detection for low frequencies, impulse detection, or increased sound or speech intelligibility due to dereverberation.

  8. A memristive spiking neuron with firing rate coding

    Directory of Open Access Journals (Sweden)

    Marina eIgnatov

    2015-10-01

    Full Text Available Perception, decisions, and sensations are all encoded into trains of action potentials in the brain. The relation between stimulus strength and all-or-nothing spiking of neurons is widely believed to be the basis of this coding. This initiated the development of spiking neuron models; one of today's most powerful conceptual tool for the analysis and emulation of neural dynamics. The success of electronic circuit models and their physical realization within silicon field-effect transistor circuits lead to elegant technical approaches. Recently, the spectrum of electronic devices for neural computing has been extended by memristive devices, mainly used to emulate static synaptic functionality. Their capabilities for emulations of neural activity were recently demonstrated using a memristive neuristor circuit, while a memristive neuron circuit has so far been elusive. Here, a spiking neuron model is experimentally realized in a compact circuit comprising memristive and memcapacitive devices based on the strongly correlated electron material vanadium dioxide (VO2 and on the chemical electromigration cell Ag/TiO2-x/Al. The circuit can emulate dynamical spiking patterns in response to an external stimulus including adaptation, which is at the heart of firing rate coding as first observed by E.D. Adrian in 1926.

  9. Spike-timing-based computation in sound localization.

    Directory of Open Access Journals (Sweden)

    Dan F M Goodman

    2010-11-01

    Full Text Available Spike timing is precise in the auditory system and it has been argued that it conveys information about auditory stimuli, in particular about the location of a sound source. However, beyond simple time differences, the way in which neurons might extract this information is unclear and the potential computational advantages are unknown. The computational difficulty of this task for an animal is to locate the source of an unexpected sound from two monaural signals that are highly dependent on the unknown source signal. In neuron models consisting of spectro-temporal filtering and spiking nonlinearity, we found that the binaural structure induced by spatialized sounds is mapped to synchrony patterns that depend on source location rather than on source signal. Location-specific synchrony patterns would then result in the activation of location-specific assemblies of postsynaptic neurons. We designed a spiking neuron model which exploited this principle to locate a variety of sound sources in a virtual acoustic environment using measured human head-related transfer functions. The model was able to accurately estimate the location of previously unknown sounds in both azimuth and elevation (including front/back discrimination in a known acoustic environment. We found that multiple representations of different acoustic environments could coexist as sets of overlapping neural assemblies which could be associated with spatial locations by Hebbian learning. The model demonstrates the computational relevance of relative spike timing to extract spatial information about sources independently of the source signal.

  10. Sleep deprivation and spike-wave discharges in epileptic rats

    NARCIS (Netherlands)

    Drinkenburg, W.H.I.M.; Coenen, A.M.L.; Vossen, J.M.H.; Luijtelaar, E.L.J.M. van

    1995-01-01

    The effects of sleep deprivation were studied on the occurrence of spike-wave discharges in the electroencephalogram of rats of the epileptic WAG/Rij strain, a model for absence epilepsy. This was done before, during and after a period of 12 hours of near total sleep deprivation. A substantial

  11. Thermal impact on spiking properties in Hodgkin-Huxley neuron ...

    Indian Academy of Sciences (India)

    Thermal impact on spiking properties in Hodgkin-Huxley neuron with synaptic stimulus. Shenbing ... Department of Physical Science and Technology, Wuhan University of Technology, Wuhan, 430070, China; State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan, 430070, China ...

  12. Fast computation with spikes in a recurrent neural network

    International Nuclear Information System (INIS)

    Jin, Dezhe Z.; Seung, H. Sebastian

    2002-01-01

    Neural networks with recurrent connections are sometimes regarded as too slow at computation to serve as models of the brain. Here we analytically study a counterexample, a network consisting of N integrate-and-fire neurons with self excitation, all-to-all inhibition, instantaneous synaptic coupling, and constant external driving inputs. When the inhibition and/or excitation are large enough, the network performs a winner-take-all computation for all possible external inputs and initial states of the network. The computation is done very quickly: As soon as the winner spikes once, the computation is completed since no other neurons will spike. For some initial states, the winner is the first neuron to spike, and the computation is done at the first spike of the network. In general, there are M potential winners, corresponding to the top M external inputs. When the external inputs are close in magnitude, M tends to be larger. If M>1, the selection of the actual winner is strongly influenced by the initial states. If a special relation between the excitation and inhibition is satisfied, the network always selects the neuron with the maximum external input as the winner

  13. A memristive spiking neuron with firing rate coding.

    Science.gov (United States)

    Ignatov, Marina; Ziegler, Martin; Hansen, Mirko; Petraru, Adrian; Kohlstedt, Hermann

    2015-01-01

    Perception, decisions, and sensations are all encoded into trains of action potentials in the brain. The relation between stimulus strength and all-or-nothing spiking of neurons is widely believed to be the basis of this coding. This initiated the development of spiking neuron models; one of today's most powerful conceptual tool for the analysis and emulation of neural dynamics. The success of electronic circuit models and their physical realization within silicon field-effect transistor circuits lead to elegant technical approaches. Recently, the spectrum of electronic devices for neural computing has been extended by memristive devices, mainly used to emulate static synaptic functionality. Their capabilities for emulations of neural activity were recently demonstrated using a memristive neuristor circuit, while a memristive neuron circuit has so far been elusive. Here, a spiking neuron model is experimentally realized in a compact circuit comprising memristive and memcapacitive devices based on the strongly correlated electron material vanadium dioxide (VO2) and on the chemical electromigration cell Ag/TiO2-x /Al. The circuit can emulate dynamical spiking patterns in response to an external stimulus including adaptation, which is at the heart of firing rate coding as first observed by E.D. Adrian in 1926.

  14. Stochastic resonance in noisy spiking retinal and sensory neuron models.

    Science.gov (United States)

    Patel, Ashok; Kosko, Bart

    2005-01-01

    Two new theorems show that small amounts of additive white noise can improve the bit count or mutual information of several popular models of spiking retinal neurons and spiking sensory neurons. The first theorem gives necessary and sufficient conditions for this noise benefit or stochastic resonance (SR) effect for subthreshold signals in a standard family of Poisson spiking models of retinal neurons. The result holds for all types of finite-variance noise and for all types of infinite-variance stable noise: SR occurs if and only if a sum of noise means or location parameters falls outside a 'forbidden interval' of values. The second theorem gives a similar forbidden-interval sufficient condition for the SR effect for several types of spiking sensory neurons that include the Fitzhugh-Nagumo neuron, the leaky integrate-and-fire neuron, and the reduced Type I neuron model if the additive noise is Gaussian white noise. Simulations show that neither the forbidden-interval condition nor Gaussianity is necessary for the SR effect.

  15. Effect of Rolandic Spikes on ADHD Impulsive Behavior

    Directory of Open Access Journals (Sweden)

    J Gordon Millichap

    2007-01-01

    Full Text Available The association of Rolandic spikes with the neuropsychological profile of children with attention deficit hyperactivity disorder (ADHD was studied in a total of 48 patients at JW Goethe-University, Frankfurt/Main; and Central Institute of Mental Health, Mannheim, Germany.

  16. Design energy spectra for Turkey

    OpenAIRE

    López Almansa, Francisco; Yazgan, Ahmet Utku; Benavent Climent, Amadeo

    2012-01-01

    This work proposes design energy spectra in terms of velocity, derived through linear dynamic analyses on Turkish registers and intended for regions with design peak acceleration 0.3 g or higher. In the long and mid period ranges the analyses are linear, taking profit of the rather insensitivity of the spectra to the structural parameters other than the fundamental period; in the short period range, the spectra are more sensitive to the structural parameters and nonlinear analyses would be re...

  17. Critical slowing down governs the transition to neuron spiking.

    Directory of Open Access Journals (Sweden)

    Christian Meisel

    2015-02-01

    Full Text Available Many complex systems have been found to exhibit critical transitions, or so-called tipping points, which are sudden changes to a qualitatively different system state. These changes can profoundly impact the functioning of a system ranging from controlled state switching to a catastrophic break-down; signals that predict critical transitions are therefore highly desirable. To this end, research efforts have focused on utilizing qualitative changes in markers related to a system's tendency to recover more slowly from a perturbation the closer it gets to the transition--a phenomenon called critical slowing down. The recently studied scaling of critical slowing down offers a refined path to understand critical transitions: to identify the transition mechanism and improve transition prediction using scaling laws. Here, we outline and apply this strategy for the first time in a real-world system by studying the transition to spiking in neurons of the mammalian cortex. The dynamical system approach has identified two robust mechanisms for the transition from subthreshold activity to spiking, saddle-node and Hopf bifurcation. Although theory provides precise predictions on signatures of critical slowing down near the bifurcation to spiking, quantitative experimental evidence has been lacking. Using whole-cell patch-clamp recordings from pyramidal neurons and fast-spiking interneurons, we show that 1 the transition to spiking dynamically corresponds to a critical transition exhibiting slowing down, 2 the scaling laws suggest a saddle-node bifurcation governing slowing down, and 3 these precise scaling laws can be used to predict the bifurcation point from a limited window of observation. To our knowledge this is the first report of scaling laws of critical slowing down in an experiment. They present a missing link for a broad class of neuroscience modeling and suggest improved estimation of tipping points by incorporating scaling laws of critical slowing

  18. The Severe Acute Respiratory Syndrome (SARS-coronavirus 3a protein may function as a modulator of the trafficking properties of the spike protein

    Directory of Open Access Journals (Sweden)

    Tan Yee-Joo

    2005-02-01

    Full Text Available Abstract Background A recent publication reported that a tyrosine-dependent sorting signal, present in cytoplasmic tail of the spike protein of most coronaviruses, mediates the intracellular retention of the spike protein. This motif is missing from the spike protein of the severe acute respiratory syndrome-coronavirus (SARS-CoV, resulting in high level of surface expression of the spike protein when it is expressed on its own in vitro. Presentation of the hypothesis It has been shown that the severe acute respiratory syndrome-coronavirus genome contains open reading frames that encode for proteins with no homologue in other coronaviruses. One of them is the 3a protein, which is expressed during infection in vitro and in vivo. The 3a protein, which contains a tyrosine-dependent sorting signal in its cytoplasmic domain, is expressed on the cell surface and can undergo internalization. In addition, 3a can bind to the spike protein and through this interaction, it may be able to cause the spike protein to become internalized, resulting in a decrease in its surface expression. Testing the hypothesis The effects of 3a on the internalization of cell surface spike protein can be examined biochemically and the significance of the interplay between these two viral proteins during viral infection can be studied using reverse genetics methodology. Implication of the hypothesis If this hypothesis is proven, it will indicate that the severe acute respiratory syndrome-coronavirus modulates the surface expression of the spike protein via a different mechanism from other coronaviruses. The interaction between 3a and S, which are expressed from separate subgenomic RNA, would be important for controlling the trafficking properties of S. The cell surface expression of S in infected cells significantly impacts viral assembly, viral spread and viral pathogenesis. Modulation by this unique pathway could confer certain advantages during the replication of the severe

  19. Sequencing BPS spectra

    Energy Technology Data Exchange (ETDEWEB)

    Gukov, Sergei [Walter Burke Institute for Theoretical Physics, California Institute of Technology,1200 E California Blvd, Pasadena, CA 91125 (United States); Max-Planck-Institut für Mathematik,Vivatsgasse 7, D-53111 Bonn (Germany); Nawata, Satoshi [Walter Burke Institute for Theoretical Physics, California Institute of Technology,1200 E California Blvd, Pasadena, CA 91125 (United States); Centre for Quantum Geometry of Moduli Spaces, University of Aarhus,Nordre Ringgade 1, DK-8000 (Denmark); Saberi, Ingmar [Walter Burke Institute for Theoretical Physics, California Institute of Technology,1200 E California Blvd, Pasadena, CA 91125 (United States); Stošić, Marko [CAMGSD, Departamento de Matemática, Instituto Superior Técnico,Av. Rovisco Pais, 1049-001 Lisbon (Portugal); Mathematical Institute SANU,Knez Mihajlova 36, 11000 Belgrade (Serbia); Sułkowski, Piotr [Walter Burke Institute for Theoretical Physics, California Institute of Technology,1200 E California Blvd, Pasadena, CA 91125 (United States); Faculty of Physics, University of Warsaw,ul. Pasteura 5, 02-093 Warsaw (Poland)

    2016-03-02

    This paper provides both a detailed study of color-dependence of link homologies, as realized in physics as certain spaces of BPS states, and a broad study of the behavior of BPS states in general. We consider how the spectrum of BPS states varies as continuous parameters of a theory are perturbed. This question can be posed in a wide variety of physical contexts, and we answer it by proposing that the relationship between unperturbed and perturbed BPS spectra is described by a spectral sequence. These general considerations unify previous applications of spectral sequence techniques to physics, and explain from a physical standpoint the appearance of many spectral sequences relating various link homology theories to one another. We also study structural properties of colored HOMFLY homology for links and evaluate Poincaré polynomials in numerous examples. Among these structural properties is a novel “sliding” property, which can be explained by using (refined) modular S-matrix. This leads to the identification of modular transformations in Chern-Simons theory and 3d N=2 theory via the 3d/3d correspondence. Lastly, we introduce the notion of associated varieties as classical limits of recursion relations of colored superpolynomials of links, and study their properties.

  20. Assembly of spikes into coronavirus particles is mediated by the carboxy-terminal domain of the spike protein

    NARCIS (Netherlands)

    Godeke, G J; de Haan, Cornelis A M; Rossen, J W; Vennema, H; Rottier, P J

    The type I glycoprotein S of coronavirus, trimers of which constitute the typical viral spikes, is assembled into virions through noncovalent interactions with the M protein. Here we demonstrate that incorporation is mediated by the short carboxy-terminal segment comprising the transmembrane and

  1. Methodology for analyzing weak spectra

    International Nuclear Information System (INIS)

    Yankovich, T.L.; Swainson, I.P.

    2000-02-01

    There is considerable interest in quantifying radionuclide transfer between environmental compartments. However, in many cases, it can be a challenge to detect concentrations of gamma-emitting radionuclides due to their low levels in environmental samples. As a result, it is valuable to develop analytical protocols to ensure consistent analysis of the areas under weak peaks. The current study has focused on testing how reproducibly peak areas and baselines can be determined using two analytical approaches. The first approach, which can be carried out using Maestro software, involves extracting net counts under a curve without fitting a functional form to the peak, whereas the second approach, which is used by most other peak fitting programs, determines net counts from spectra by fitting a Gaussian form to the data. It was found that the second approach produces more consistent peak area and baseline measurements, with the ability to de-convolute multiple, overlapping peaks. In addition, programs, such as Peak Fit, which can be used to fit a form to spectral data, often provide goodness of fit analyses, since the Gaussian form can be described using a characteristic equation against which peak data can be tested for their statistical significance. (author)

  2. A Hardware-Efficient Scalable Spike Sorting Neural Signal Processor Module for Implantable High-Channel-Count Brain Machine Interfaces.

    Science.gov (United States)

    Yang, Yuning; Boling, Sam; Mason, Andrew J

    2017-08-01

    Next-generation brain machine interfaces demand a high-channel-count neural recording system to wirelessly monitor activities of thousands of neurons. A hardware efficient neural signal processor (NSP) is greatly desirable to ease the data bandwidth bottleneck for a fully implantable wireless neural recording system. This paper demonstrates a complete multichannel spike sorting NSP module that incorporates all of the necessary spike detector, feature extractor, and spike classifier blocks. To meet high-channel-count and implantability demands, each block was designed to be highly hardware efficient and scalable while sharing resources efficiently among multiple channels. To process multiple channels in parallel, scalability analysis was performed, and the utilization of each block was optimized according to its input data statistics and the power, area and/or speed of each block. Based on this analysis, a prototype 32-channel spike sorting NSP scalable module was designed and tested on an FPGA using synthesized datasets over a wide range of signal to noise ratios. The design was mapped to 130 nm CMOS to achieve 0.75 μW power and 0.023 mm 2 area consumptions per channel based on post synthesis simulation results, which permits scalability of digital processing to 690 channels on a 4×4 mm 2 electrode array.

  3. Accuracy evaluation of numerical methods used in state-of-the-art simulators for spiking neural networks.

    Science.gov (United States)

    Henker, Stephan; Partzsch, Johannes; Schüffny, René

    2012-04-01

    With the various simulators for spiking neural networks developed in recent years, a variety of numerical solution methods for the underlying differential equations are available. In this article, we introduce an approach to systematically assess the accuracy of these methods. In contrast to previous investigations, our approach focuses on a completely deterministic comparison and uses an analytically solved model as a reference. This enables the identification of typical sources of numerical inaccuracies in state-of-the-art simulation methods. In particular, with our approach we can separate the error of the numerical integration from the timing error of spike detection and propagation, the latter being prominent in simulations with fixed timestep. To verify the correctness of the testing procedure, we relate the numerical deviations to theoretical predictions for the employed numerical methods. Finally, we give an example of the influence of simulation artefacts on network behaviour and spike-timing-dependent plasticity (STDP), underlining the importance of spike-time accuracy for the simulation of STDP.

  4. Investigation of Current Spike Phenomena During Heavy Ion Irradiation of NAND Flash Memories

    Science.gov (United States)

    Oldham, Timothy R.; Berg, Melanie; Friendlich, Mark; Wilcox, Ted; Seidleck, Christina; LaBel, Kenneth A.; Irom, Farokh; Buchner, Steven P.; McMorrow, Dale; Mavis, David G.; hide

    2011-01-01

    A series of heavy ion and laser irradiations were performed to investigate previously reported current spikes in flash memories. High current events were observed, however, none matches the previously reported spikes. Plausible mechanisms are discussed.

  5. Fluorescence Spectra of Blowfly Metaxanthopsins

    NARCIS (Netherlands)

    Kruizinga, B.; Stavenga, D.G.

    The main visual pigment of blowflies (xanthopsin) photoconverts into two thermostable metaxanthopsin states M and M’. The fluorescence spectra of the two photoproducts were studied by microspectrofluorometry in vivo. The emission spectra of M and M’ are very similar and peak at 660 nm. The

  6. Fluorescence Spectra of Highlighter Inks

    Science.gov (United States)

    Birriel, Jennifer J.; King, Damon

    2018-01-01

    Fluorescence spectra excited by laser pointers have been the subject of several papers in TPT. These papers all describe a fluorescence phenomenon in which the reflected laser light undergoes a change in color: this color change results from the combination of some partially reflected laser light and additional colors generated by fluorescent emission. Here we examine the fluorescence spectra of highlighter inks using green and violet laser pointers. We use an RSpec Explorer spectrometer to obtain spectra and compare the emission spectra of blue, green, yellow, orange, pink, and purple highlighters. The website Compound Interest details the chemical composition of highlighter inks; in addition, the site discusses how some base dye colors can be combined to produce the variety commercially available colors. Spectra obtained in this study were qualitatively consistent with the Compound Interest site. We discuss similarities and differences between various highlighter colors and conclude with the relevance of such studies to physics students.

  7. Static vs dynamic DFT prediction of IR spectra of flexible molecules in the condensed phase: The (ClCF2CF(CF3)OCF2CH3) liquid as a test case

    Science.gov (United States)

    Galimberti, Daria Ruth; Milani, Alberto; Gaigeot, Marie-Pierre; Radice, Stefano; Tonelli, Claudio; Picozzi, Rosaldo; Castiglioni, Chiara

    2017-08-01

    First-principles molecular dynamics (FPMD) simulations in the framework of Density Functional Theory (DFT) are carried out for the prediction of the infrared spectrum of the fluorinated molecule ClCF2CF(CF3)OCF2CH3 in liquid and gas phase. This molecule is characterized by a flexible structure, allowing the co-existence of several stable conformers, that differ by values of the torsional angles. FPMD computed spectra are compared to the experimental ones, and to Boltzmann weighted IR spectra based on gas phase calculations.

  8. A 41 μW real-time adaptive neural spike classifier

    NARCIS (Netherlands)

    Zjajo, A.; van Leuken, T.G.R.M.

    2016-01-01

    Robust, power- and area-efficient spike classifier, capable of accurate identification of the neural spikes even for low SNR, is a prerequisite for the real-time, implantable, closed-loop brain-machine interface. In this paper, we propose an easily-scalable, 128-channel, programmable, neural spike

  9. Intracellular transport of recombinant coronavirus spike proteins: implications for virus assembly

    NARCIS (Netherlands)

    Horzinek, M.C.; Vennema, H.; Heijnen, L.; Zijderveld, A.; Spaan, W.J.M.

    1990-01-01

    Coronavirus spike protein genes were expressed in vitro by using the recombinant vaccinia virus expression system. Recombinant spike proteins were expressed at the cell surface and induced cell fusion in a host-cell-dependent fashion. The intracellular transport of recombinant spike proteins was

  10. The Ripple Pond: Enabling Spiking Networks to See

    Directory of Open Access Journals (Sweden)

    Saeed eAfshar

    2013-11-01

    Full Text Available We present the biologically inspired Ripple Pond Network (RPN, a simply connected spiking neural network which performs a transformation converting two dimensional images to one dimensional temporal patterns suitable for recognition by temporal coding learning and memory networks. The RPN has been developed as a hardware solution linking previously implemented neuromorphic vision and memory structures such as frameless vision sensors and neuromorphic temporal coding spiking neural networks. Working together such systems are potentially capable of delivering end-to-end high-speed, low-power and low-resolution recognition for mobile and autonomous applications where slow, highly sophisticated and power hungry signal processing solutions are ineffective. Key aspects in the proposed approach include utilising the spatial properties of physically embedded neural networks and propagating waves of activity therein for information processing, using dimensional collapse of imagery information into amenable temporal patterns and the use of asynchronous frames for information binding.

  11. Prolonging the postcomplex spike pause speeds eyeblink conditioning.

    Science.gov (United States)

    Maiz, Jaione; Karakossian, Movses H; Pakaprot, Narawut; Robleto, Karla; Thompson, Richard F; Otis, Thomas S

    2012-10-09

    Climbing fiber input to the cerebellum is believed to serve as a teaching signal during associative, cerebellum-dependent forms of motor learning. However, it is not understood how this neural pathway coordinates changes in cerebellar circuitry during learning. Here, we use pharmacological manipulations to prolong the postcomplex spike pause, a component of the climbing fiber signal in Purkinje neurons, and show that these manipulations enhance the rate of learning in classical eyelid conditioning. Our findings elucidate an unappreciated aspect of the climbing fiber teaching signal, and are consistent with a model in which convergent postcomplex spike pauses drive learning-related plasticity in the deep cerebellar nucleus. They also suggest a physiological mechanism that could modulate motor learning rates.

  12. EPILEPTIC ENCEPHALOPATHY WITH CONTINUOUS SPIKES-WAVES ACTIVITY DURING SLEEP

    Directory of Open Access Journals (Sweden)

    E. D. Belousova

    2012-01-01

    Full Text Available The author represents the review and discussion of current scientific literature devoted to epileptic encephalopathy with continuous spikes-waves activity during sleep — the special form of partly reversible age-dependent epileptic encephalopathy, characterized by triad of symptoms: continuous prolonged epileptiform (spike-wave activity on EEG in sleep, epileptic seizures and cognitive disorders. The author describes the aspects of classification, pathogenesis and etiology, prevalence, clinical picture and diagnostics of this disorder, including the peculiar anomalies on EEG. The especial attention is given to approaches to the treatment of epileptic encephalopathy with continuous spikeswaves activity during sleep. Efficacy of valproates, corticosteroid hormones and antiepileptic drugs of other groups is considered. The author represents own experience of treatment this disorder with corticosteroids, scheme of therapy and assessment of efficacy.

  13. Harmonics of Solar Radio Spikes at Metric Wavelengths

    Science.gov (United States)

    Feng, S. W.; Chen, Y.; Li, C. Y.; Wang, B.; Wu, Z.; Kong, X. L.; Du, Q. F.; Zhang, J. R.; Zhao, G. Q.

    2018-03-01

    This paper presents the latest observations from the newly built solar radio spectrograph at the Chashan Solar Observatory. On July 18, 2016, the spectrograph records a solar spike burst event, which has several episodes showing harmonic structures, with the second, third, and fourth harmonics. The lower harmonic radio spike emissions are observed later than the higher harmonic bands, and the temporal delay of the second (third) harmonic relative to the fourth harmonic is about 30 - 40 (10) ms. Based on the electron cyclotron maser emission mechanism, we analyze possible causes of the temporal delay and further infer relevant coronal parameters, such as the magnetic field strength and the electron density at the radio source.

  14. Supervised learning with decision margins in pools of spiking neurons.

    Science.gov (United States)

    Le Mouel, Charlotte; Harris, Kenneth D; Yger, Pierre

    2014-10-01

    Learning to categorise sensory inputs by generalising from a few examples whose category is precisely known is a crucial step for the brain to produce appropriate behavioural responses. At the neuronal level, this may be performed by adaptation of synaptic weights under the influence of a training signal, in order to group spiking patterns impinging on the neuron. Here we describe a framework that allows spiking neurons to perform such "supervised learning", using principles similar to the Support Vector Machine, a well-established and robust classifier. Using a hinge-loss error function, we show that requesting a margin similar to that of the SVM improves performance on linearly non-separable problems. Moreover, we show that using pools of neurons to discriminate categories can also increase the performance by sharing the load among neurons.

  15. A Theory of Material Spike Formation in Flow Separation

    Science.gov (United States)

    Serra, Mattia; Haller, George

    2017-11-01

    We develop a frame-invariant theory of material spike formation during flow separation over a no-slip boundary in two-dimensional flows with arbitrary time dependence. This theory identifies both fixed and moving separation, is effective also over short-time intervals, and admits a rigorous instantaneous limit. Our theory is based on topological properties of material lines, combining objectively stretching- and rotation-based kinematic quantities. The separation profile identified here serves as the theoretical backbone for the material spike from its birth to its fully developed shape, and remains hidden to existing approaches. Finally, our theory can be used to rigorously explain the perception of off-wall separation in unsteady flows, and more importantly, provide the conditions under which such a perception is justified. We illustrate our results in several examples including steady, time-periodic and unsteady analytic velocity fields with flat and curved boundaries, and an experimental dataset.

  16. Origin of the spike-timing-dependent plasticity rule

    Science.gov (United States)

    Cho, Myoung Won; Choi, M. Y.

    2016-08-01

    A biological synapse changes its efficacy depending on the difference between pre- and post-synaptic spike timings. Formulating spike-timing-dependent interactions in terms of the path integral, we establish a neural-network model, which makes it possible to predict relevant quantities rigorously by means of standard methods in statistical mechanics and field theory. In particular, the biological synaptic plasticity rule is shown to emerge as the optimal form for minimizing the free energy. It is further revealed that maximization of the entropy of neural activities gives rise to the competitive behavior of biological learning. This demonstrates that statistical mechanics helps to understand rigorously key characteristic behaviors of a neural network, thus providing the possibility of physics serving as a useful and relevant framework for probing life.

  17. Spin-orbit torque induced spike-timing dependent plasticity

    Energy Technology Data Exchange (ETDEWEB)

    Sengupta, Abhronil, E-mail: asengup@purdue.edu; Al Azim, Zubair; Fong, Xuanyao; Roy, Kaushik [School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana 47907 (United States)

    2015-03-02

    Nanoelectronic devices that mimic the functionality of synapses are a crucial requirement for performing cortical simulations of the brain. In this work, we propose a ferromagnet-heavy metal heterostructure that employs spin-orbit torque to implement spike-timing dependent plasticity. The proposed device offers the advantage of decoupled spike transmission and programming current paths, thereby leading to reliable operation during online learning. Possible arrangement of such devices in a crosspoint architecture can pave the way for ultra-dense neural networks. Simulation studies indicate that the device has the potential of achieving pico-Joule level energy consumption (maximum 2 pJ per synaptic event) which is comparable to the energy consumption for synaptic events in biological synapses.

  18. Strategies for Interpreting Two Dimensional Microwave Spectra

    Science.gov (United States)

    Martin-Drumel, Marie-Aline; Crabtree, Kyle N.; Buchanan, Zachary

    2017-06-01

    Microwave spectroscopy can uniquely identify molecules because their rotational energy levels are sensitive to the three principal moments of inertia. However, a priori predictions of a molecule's structure have traditionally been required to enable efficient assignment of the rotational spectrum. Recently, automated microwave double resonance spectroscopy (AMDOR) has been employed to rapidly generate two dimensional spectra based on transitions that share a common rotational level, which may enable automated extraction of rotational constants without any prior estimates of molecular structure. Algorithms used to date for AMDOR have relied on making several initial assumptions about the nature of a subset of the linked transitions, followed by testing possible assignments by "brute force." In this talk, we will discuss new strategies for interpreting AMDOR spectra, using eugenol as a test case, as well as prospects for library-free, automated identification of the molecules in a volatile mixture.

  19. Simulating large-scale spiking neuronal networks with NEST

    OpenAIRE

    Senk, Johanna; Diesmann, Markus

    2014-01-01

    The Neural Simulation Tool NEST [1, www.nest-simulator.org] is the simulator for spiking neural networkmodels of the HBP that focuses on the dynamics, size and structure of neural systems rather than on theexact morphology of individual neurons. Its simulation kernel is written in C++ and it runs on computinghardware ranging from simple laptops to clusters and supercomputers with thousands of processor cores.The development of NEST is coordinated by the NEST Initiative [www.nest-initiative.or...

  20. Stiff fluid spike solutions from Bianchi type V seed solutions

    Science.gov (United States)

    Gregoris, D.; Lim, W. C.; Coley, A. A.

    2017-12-01

    In this paper we expand upon our previous work Coley et al (2016 Class. Quantum Grav. 33 215010) by using the entire family of Bianchi type V stiff fluid solutions as seed solutions of the Stephani transformation. Among the new exact solutions generated, we observe a number of important physical phenomena. The most interesting phenomenon is exact solutions with intersecting spikes. Other interesting phenomena are solutions with saddle states and a close-to-FL epoch.

  1. Spike: Artificial intelligence scheduling for Hubble space telescope

    Science.gov (United States)

    Johnston, Mark; Miller, Glenn; Sponsler, Jeff; Vick, Shon; Jackson, Robert

    1990-01-01

    Efficient utilization of spacecraft resources is essential, but the accompanying scheduling problems are often computationally intractable and are difficult to approximate because of the presence of numerous interacting constraints. Artificial intelligence techniques were applied to the scheduling of the NASA/ESA Hubble Space Telescope (HST). This presents a particularly challenging problem since a yearlong observing program can contain some tens of thousands of exposures which are subject to a large number of scientific, operational, spacecraft, and environmental constraints. New techniques were developed for machine reasoning about scheduling constraints and goals, especially in cases where uncertainty is an important scheduling consideration and where resolving conflicts among conflicting preferences is essential. These technique were utilized in a set of workstation based scheduling tools (Spike) for HST. Graphical displays of activities, constraints, and schedules are an important feature of the system. High level scheduling strategies using both rule based and neural network approaches were developed. While the specific constraints implemented are those most relevant to HST, the framework developed is far more general and could easily handle other kinds of scheduling problems. The concept and implementation of the Spike system are described along with some experiments in adapting Spike to other spacecraft scheduling domains.

  2. Stochastic models for spike trains of single neurons

    CERN Document Server

    Sampath, G

    1977-01-01

    1 Some basic neurophysiology 4 The neuron 1. 1 4 1. 1. 1 The axon 7 1. 1. 2 The synapse 9 12 1. 1. 3 The soma 1. 1. 4 The dendrites 13 13 1. 2 Types of neurons 2 Signals in the nervous system 14 2. 1 Action potentials as point events - point processes in the nervous system 15 18 2. 2 Spontaneous activi~ in neurons 3 Stochastic modelling of single neuron spike trains 19 3. 1 Characteristics of a neuron spike train 19 3. 2 The mathematical neuron 23 4 Superposition models 26 4. 1 superposition of renewal processes 26 4. 2 Superposition of stationary point processe- limiting behaviour 34 4. 2. 1 Palm functions 35 4. 2. 2 Asymptotic behaviour of n stationary point processes superposed 36 4. 3 Superposition models of neuron spike trains 37 4. 3. 1 Model 4. 1 39 4. 3. 2 Model 4. 2 - A superposition model with 40 two input channels 40 4. 3. 3 Model 4. 3 4. 4 Discussion 41 43 5 Deletion models 5. 1 Deletion models with 1nd~endent interaction of excitatory and inhibitory sequences 44 VI 5. 1. 1 Model 5. 1 The basic de...

  3. Spiking neural network-based control chart pattern recognition

    Directory of Open Access Journals (Sweden)

    Medhat H.A. Awadalla

    2012-03-01

    Full Text Available Due to an increasing competition in products, consumers have become more critical in choosing products. The quality of products has become more important. Statistical Process Control (SPC is usually used to improve the quality of products. Control charting plays the most important role in SPC. Control charts help to monitor the behavior of the process to determine whether it is stable or not. Unnatural patterns in control charts mean that there are some unnatural causes for variations in SPC. Spiking neural networks (SNNs are the third generation of artificial neural networks that consider time as an important feature for information representation and processing. In this paper, a spiking neural network architecture is proposed to be used for control charts pattern recognition (CCPR. Furthermore, enhancements to the SpikeProp learning algorithm are proposed. These enhancements provide additional learning rules for the synaptic delays, time constants and for the neurons thresholds. Simulated experiments have been conducted and the achieved results show a remarkable improvement in the overall performance compared with artificial neural networks.

  4. Poisson-Like Spiking in Circuits with Probabilistic Synapses

    Science.gov (United States)

    Moreno-Bote, Rubén

    2014-01-01

    Neuronal activity in cortex is variable both spontaneously and during stimulation, and it has the remarkable property that it is Poisson-like over broad ranges of firing rates covering from virtually zero to hundreds of spikes per second. The mechanisms underlying cortical-like spiking variability over such a broad continuum of rates are currently unknown. We show that neuronal networks endowed with probabilistic synaptic transmission, a well-documented source of variability in cortex, robustly generate Poisson-like variability over several orders of magnitude in their firing rate without fine-tuning of the network parameters. Other sources of variability, such as random synaptic delays or spike generation jittering, do not lead to Poisson-like variability at high rates because they cannot be sufficiently amplified by recurrent neuronal networks. We also show that probabilistic synapses predict Fano factor constancy of synaptic conductances. Our results suggest that synaptic noise is a robust and sufficient mechanism for the type of variability found in cortex. PMID:25032705

  5. The Use Of Spikes Protocol In Cancer: An Integrative Review

    Directory of Open Access Journals (Sweden)

    Fernando Henrique de Sousa

    2017-03-01

    Full Text Available This is an integrative review which aimed to evaluate the use of the SPIKES protocol in Oncology. We selected articles published in Medline and CINAHL databases between 2005-2015, in English, with the descriptors defined by the Medical Subject Headings (MeSH:cancer, neoplasms, plus the uncontrolled descriptor: protocol spikes.  Six articles met the inclusion criteria and were analyzed in full, three thematic categories were established: aspects inherent to the health care professional; Aspects related to the patient and aspects related to the protocol. The main effects of the steps of SPIKES protocol can provide the strengthening of ties between health professionals and patients, and ensure the maintenance and quality of this relationship.  The results indicate an important limiting factor for effective doctor-patient relationship, the little training provided to medical professionals communication of bad news, verified by the difficulty reported in this moment through interviews in the analyzed studies.

  6. Economic impact on the Florida economy of energy price spikes

    International Nuclear Information System (INIS)

    Mory, J.F.

    1992-01-01

    A substantial disturbance in oil supplies is likely to generate a large price upsurge and a downturn in the level of economic activity. Each of these two effects diminishes demand by a certain amount. The specific price surge required to reduce demand to the lower level of supply can be calculated with an oil demand function and with empirical estimations of the association between price spikes and declines in economic activity. The first section presents an energy demand model for Florida, which provides the price and income elasticities needed. The second section includes theoretical explanations and empirical estimations of the relationship between price spikes and recessions. Based on historical evidence, it seems that Florida's and the nation's economic systems are very sensitive to oil price surges. As price spikes appear damaging to the economy, it could be expected that reductions in the price of oil are beneficial to the system. That is likely to be the case in the long run, but no empirical evidence of favorable short-term effects of oil price decreases was found. Several possible explanations and theoretical reasons are offered to explain this lack of association. The final section presents estimates of the effect of oil disruptions upon specific industries in Florida and the nation

  7. Efficient Architecture for Spike Sorting in Reconfigurable Hardware

    Science.gov (United States)

    Hwang, Wen-Jyi; Lee, Wei-Hao; Lin, Shiow-Jyu; Lai, Sheng-Ying

    2013-01-01

    This paper presents a novel hardware architecture for fast spike sorting. The architecture is able to perform both the feature extraction and clustering in hardware. The generalized Hebbian algorithm (GHA) and fuzzy C-means (FCM) algorithm are used for feature extraction and clustering, respectively. The employment of GHA allows efficient computation of principal components for subsequent clustering operations. The FCM is able to achieve near optimal clustering for spike sorting. Its performance is insensitive to the selection of initial cluster centers. The hardware implementations of GHA and FCM feature low area costs and high throughput. In the GHA architecture, the computation of different weight vectors share the same circuit for lowering the area costs. Moreover, in the FCM hardware implementation, the usual iterative operations for updating the membership matrix and cluster centroid are merged into one single updating process to evade the large storage requirement. To show the effectiveness of the circuit, the proposed architecture is physically implemented by field programmable gate array (FPGA). It is embedded in a System-on-Chip (SOC) platform for performance measurement. Experimental results show that the proposed architecture is an efficient spike sorting design for attaining high classification correct rate and high speed computation. PMID:24189331

  8. Enhanced polychronisation in a spiking network with metaplasticity

    Directory of Open Access Journals (Sweden)

    Mira eGuise

    2015-02-01

    Full Text Available Computational models of metaplasticity have usually focused on the modeling of single synapses (Shouval et al., 2002. In this paper we study the effect of metaplasticity on network behavior. Our guiding assumption is that the primary purpose of metaplasticity is to regulate synaptic plasticity, by increasing it when input is low and decreasing it when input is high. For our experiments we adopt a model of metaplasticity that demonstrably has this effect for a single synapse; our primary interest is in how metaplasticity thus defined affects network-level phenomena. We focus on a network-level phenomenon called polychronicity, that has a potential role in representation and memory. A network with polychronicity has the ability to produce non-synchronous but precisely timed sequences of neural firing events that can arise from strongly connected groups of neurons called polychronous neural groups (Izhikevich et al., 2004; Izhikevich, 2006a. Polychronous groups (PNGs develop readily when spiking networks are exposed to repeated spatio-temporal stimuli under the influence of spike-timing-dependent plasticity (STDP, but are sensitive to changes in synaptic weight distribution. We use a technique we have recently developed called Response Fingerprinting to show that PNGs formed in the presence of metaplasticity are significantly larger than those with no metaplasticity. A potential mechanism for this enhancement is proposed that links an inherent property of integrator type neurons called spike latency to an increase in the tolerance of PNG neurons to jitter in their inputs.

  9. Efficient Architecture for Spike Sorting in Reconfigurable Hardware

    Directory of Open Access Journals (Sweden)

    Sheng-Ying Lai

    2013-11-01

    Full Text Available This paper presents a novel hardware architecture for fast spike sorting. The architecture is able to perform both the feature extraction and clustering in hardware. The generalized Hebbian algorithm (GHA and fuzzy C-means (FCM algorithm are used for feature extraction and clustering, respectively. The employment of GHA allows efficient computation of principal components for subsequent clustering operations. The FCM is able to achieve near optimal clustering for spike sorting. Its performance is insensitive to the selection of initial cluster centers. The hardware implementations of GHA and FCM feature low area costs and high throughput. In the GHA architecture, the computation of different weight vectors share the same circuit for lowering the area costs. Moreover, in the FCM hardware implementation, the usual iterative operations for updating the membership matrix and cluster centroid are merged into one single updating process to evade the large storage requirement. To show the effectiveness of the circuit, the proposed architecture is physically implemented by field programmable gate array (FPGA. It is embedded in a System-on-Chip (SOC platform for performance measurement. Experimental results show that the proposed architecture is an efficient spike sorting design for attaining high classification correct rate and high speed computation.

  10. Linking structure and activity in nonlinear spiking networks.

    Directory of Open Access Journals (Sweden)

    Gabriel Koch Ocker

    2017-06-01

    Full Text Available Recent experimental advances are producing an avalanche of data on both neural connectivity and neural activity. To take full advantage of these two emerging datasets we need a framework that links them, revealing how collective neural activity arises from the structure of neural connectivity and intrinsic neural dynamics. This problem of structure-driven activity has drawn major interest in computational neuroscience. Existing methods for relating activity and architecture in spiking networks rely on linearizing activity around a central operating point and thus fail to capture the nonlinear responses of individual neurons that are the hallmark of neural information processing. Here, we overcome this limitation and present a new relationship between connectivity and activity in networks of nonlinear spiking neurons by developing a diagrammatic fluctuation expansion based on statistical field theory. We explicitly show how recurrent network structure produces pairwise and higher-order correlated activity, and how nonlinearities impact the networks' spiking activity. Our findings open new avenues to investigating how single-neuron nonlinearities-including those of different cell types-combine with connectivity to shape population activity and function.

  11. How adaptation shapes spike rate oscillations in recurrent neuronal networks

    Directory of Open Access Journals (Sweden)

    Moritz eAugustin

    2013-02-01

    Full Text Available Neural mass signals from in-vivo recordings often show oscillations with frequencies ranging from <1 Hz to 100 Hz. Fast rhythmic activity in the beta and gamma range can be generated by network based mechanisms such as recurrent synaptic excitation-inhibition loops. Slower oscillations might instead depend on neuronal adaptation currents whose timescales range from tens of milliseconds to seconds. Here we investigate how the dynamics of such adaptation currents contribute to spike rate oscillations and resonance properties in recurrent networks of excitatory and inhibitory neurons. Based on a network of sparsely coupled spiking model neurons with two types of adaptation current and conductance based synapses with heterogeneous strengths and delays we use a mean-field approach to analyze oscillatory network activity. For constant external input, we find that spike-triggered adaptation currents provide a mechanism to generate slow oscillations over a wide range of adaptation timescales as long as recurrent synaptic excitation is sufficiently strong. Faster rhythms occur when recurrent inhibition is slower than excitation and oscillation frequency increases with the strength of inhibition. Adaptation facilitates such network based oscillations for fast synaptic inhibition and leads to decreased frequencies. For oscillatory external input, adaptation currents amplify a narrow band of frequencies and cause phase advances for low frequencies in addition to phase delays at higher frequencies. Our results therefore identify the different key roles of neuronal adaptation dynamics for rhythmogenesis and selective signal propagation in recurrent networks.

  12. Spike latency and response properties of an excitable micropillar laser

    Science.gov (United States)

    Selmi, F.; Braive, R.; Beaudoin, G.; Sagnes, I.; Kuszelewicz, R.; Erneux, T.; Barbay, S.

    2016-10-01

    We present experimental measurements concerning the response of an excitable micropillar laser with saturable absorber to incoherent as well as coherent perturbations. The excitable response is similar to the behavior of spiking neurons but with much faster time scales. It is accompanied by a subnanosecond nonlinear delay that is measured for different bias pump values. This mechanism provides a natural scheme for encoding the strength of an ultrafast stimulus in the response delay of excitable spikes (temporal coding). Moreover, we demonstrate coherent and incoherent perturbations techniques applied to the micropillar with perturbation thresholds in the range of a few femtojoules. Responses to coherent perturbations assess the cascadability of the system. We discuss the physical origin of the responses to single and double perturbations with the help of numerical simulations of the Yamada model and, in particular, unveil possibilities to control the relative refractory period that we recently evidenced in this system. Experimental measurements are compared to both numerical simulations of the Yamada model and analytic expressions obtained in the framework of singular perturbation techniques. This system is thus a good candidate to perform photonic spike processing tasks in the framework of novel neuroinspired computing systems.

  13. Fractal characterization of acupuncture-induced spike trains of rat WDR neurons

    International Nuclear Information System (INIS)

    Chen, Yingyuan; Guo, Yi; Wang, Jiang; Hong, Shouhai; Wei, Xile; Yu, Haitao; Deng, Bin

    2015-01-01

    Highlights: •Fractal analysis is a valuable tool for measuring MA-induced neural activities. •In course of the experiments, the spike trains display different fractal properties. •The fractal properties reflect the long-term modulation of MA on WDR neurons. •The results may explain the long-lasting effects induced by acupuncture. -- Abstract: The experimental and the clinical studies have showed manual acupuncture (MA) could evoke multiple responses in various neural regions. Characterising the neuronal activities in these regions may provide more deep insights into acupuncture mechanisms. This paper used fractal analysis to investigate MA-induced spike trains of Wide Dynamic Range (WDR) neurons in rat spinal dorsal horn, an important relay station and integral component in processing acupuncture information. Allan factor and Fano factor were utilized to test whether the spike trains were fractal, and Allan factor were used to evaluate the scaling exponents and Hurst exponents. It was found that these two fractal exponents before and during MA were different significantly. During MA, the scaling exponents of WDR neurons were regulated in a small range, indicating a special fractal pattern. The neuronal activities were long-range correlated over multiple time scales. The scaling exponents during and after MA were similar, suggesting that the long-range correlations not only displayed during MA, but also extended to after withdrawing the needle. Our results showed that fractal analysis is a useful tool for measuring acupuncture effects. MA could modulate neuronal activities of which the fractal properties change as time proceeding. This evolution of fractal dynamics in course of MA experiments may explain at the level of neuron why the effect of MA observed in experiment and in clinic are complex, time-evolutionary, long-range even lasting for some time after stimulation

  14. Development of the SPIKE code for analysis of the sodium-water reaction

    Energy Technology Data Exchange (ETDEWEB)

    Hwang, Sung Tai; Park, Jin Ho; Choi, Jong Hyeun; Kim, Tae Joon [Korea Atomic Energy Research Institute, Taejon (Korea)

    1998-08-01

    In the secondary loop of liquid metal reactors, including SG, water leak into sodium causes the sudden increase of pressure by the H{sub 2} and heat generated from reaction. At few miliseconds after leak, a sharp and short-lived increase of pressure is generated and its propagation depends on the acoustic constraint characteristics of secondary loop. As increasing leak amount of water, another pressure increase is caused by H{sub 2} and its transients depends on the resistance of pressure opening system, such as rupture disc. For prediction of the transients of initial spike pressure, a code of SPIKE was developed. The code was based on the following simplifications and assumptions: combination of total and half release of H{sub 2} rate, spherical shape of H{sub 2} bubble, compressible and Newtonian fluid for sodium. The program was built in FOTRAN language and consisted of 5 modules. Several sample calculations were performed to test the code and to determine the scale down factor of experimental facilities for experimental verification of the code: parameter study of the variables in chemical reaction model, comparison study with results calculated by superposition methods for simple piping structures, comparison study with results calculated by previous researchers, and calculation for KALIMER models of various size. With these calculation results, the generally predicted phenomena of sodium water reaction can be explained and the calculated ones by SPIKE code were well agreed with the previous study. And the scale down factor can be determined. (author). 88 refs., 99 figs., 39 tabs.

  15. Raman spectra of lithium compounds

    Science.gov (United States)

    Gorelik, V. S.; Bi, Dongxue; Voinov, Y. P.; Vodchits, A. I.; Gorshunov, B. P.; Yurasov, N. I.; Yurasova, I. I.

    2017-11-01

    The paper is devoted to the results of investigating the spontaneous Raman scattering spectra in the lithium compounds crystals in a wide spectral range by the fibre-optic spectroscopy method. We also present the stimulated Raman scattering spectra in the lithium hydroxide and lithium deuteride crystals obtained with the use of powerful laser source. The symmetry properties of the lithium hydroxide, lithium hydroxide monohydrate and lithium deuteride crystals optical modes were analyzed by means of the irreducible representations of the point symmetry groups. We have established the selection rules in the Raman and infrared absorption spectra of LiOH, LiOH·H2O and LiD crystals.

  16. Detecting well casing leaks in Bangladesh using a salt spiking method

    Science.gov (United States)

    Stahl, M.O.; Ong, J.B.; Harvey, C.F.; Johnson, C.D.; Badruzzaman, A.B.M.; Tarek, M.H.; VanGeen, A.; Anderson, J.A.; Lane, J.W.

    2014-01-01

    We apply fluid-replacement logging in arsenic-contaminated regions of Bangladesh using a low-cost, down-well fluid conductivity logging tool to detect leaks in the cased section of wells. The fluid-conductivity tool is designed for the developing world: it is lightweight and easily transportable, operable by one person, and can be built for minimal cost. The fluid-replacement test identifies leaking casing by comparison of fluid conductivity logs collected before and after spiking the wellbore with a sodium chloride tracer. Here, we present results of fluid-replacement logging tests from both leaking and non-leaking casing from wells in Araihazar and Munshiganj, Bangladesh, and demonstrate that the low-cost tool produces measurements comparable to those obtained with a standard geophysical logging tool. Finally, we suggest well testing procedures and approaches for preventing casing leaks in Bangladesh and other developing countries.

  17. Fast convergence of spike sequences to periodic patterns in recurrent networks

    International Nuclear Information System (INIS)

    Jin, Dezhe Z.

    2002-01-01

    The dynamical attractors are thought to underlie many biological functions of recurrent neural networks. Here we show that stable periodic spike sequences with precise timings are the attractors of the spiking dynamics of recurrent neural networks with global inhibition. Almost all spike sequences converge within a finite number of transient spikes to these attractors. The convergence is fast, especially when the global inhibition is strong. These results support the possibility that precise spatiotemporal sequences of spikes are useful for information encoding and processing in biological neural networks

  18. Controllable spiking patterns in long-wavelength vertical cavity surface emitting lasers for neuromorphic photonics systems

    Energy Technology Data Exchange (ETDEWEB)

    Hurtado, Antonio, E-mail: antonio.hurtado@strath.ac.uk [Institute of Photonics, SUPA Department of Physics, University of Strathclyde, TIC Centre, 99 George Street, Glasgow G1 1RD (United Kingdom); Javaloyes, Julien [Departament de Fisica, Universitat de les Illes Balears, c/Valldemossa km 7.5, 07122 Mallorca (Spain)

    2015-12-14

    Multiple controllable spiking patterns are achieved in a 1310 nm Vertical-Cavity Surface Emitting Laser (VCSEL) in response to induced perturbations and for two different cases of polarized optical injection, namely, parallel and orthogonal. Furthermore, reproducible spiking responses are demonstrated experimentally at sub-nanosecond speed resolution and with a controlled number of spikes fired. This work opens therefore exciting research avenues for the use of VCSELs in ultrafast neuromorphic photonic systems for non-traditional computing applications, such as all-optical binary-to-spiking format conversion and spiking information encoding.

  19. Detecting spikes of wheat plants using neural networks with Laws texture energy.

    Science.gov (United States)

    Qiongyan, Li; Cai, Jinhai; Berger, Bettina; Okamoto, Mamoru; Miklavcic, Stanley J

    2017-01-01

    The spike of a cereal plant is the grain-bearing organ whose physical characteristics are proxy measures of grain yield. The ability to detect and characterise spikes from 2D images of cereal plants, such as wheat, therefore provides vital information on tiller number and yield potential. We have developed a novel spike detection method for wheat plants involving, firstly, an improved colour index method for plant segmentation and, secondly, a neural network-based method using Laws texture energy for spike detection. The spike detection step was further improved by removing noise using an area and height threshold. The evaluation results showed an accuracy of over 80% in identification of spikes. In the proposed method we also measure the area of individual spikes as well as all spikes of individual plants under different experimental conditions. The correlation between the final average grain yield and spike area is also discussed in this paper. Our highly accurate yield trait phenotyping method for spike number counting and spike area estimation, is useful and reliable not only for grain yield estimation but also for detecting and quantifying subtle phenotypic variations arising from genetic or environmental differences.

  20. Infrared spectra of mineral species

    CERN Document Server

    Chukanov, Nikita V

    2014-01-01

    This book details more than 3,000 IR spectra of more than 2,000 mineral species collected during last 30 years. It features full descriptions and analytical data of each sample for which IR spectrum was obtained.

  1. Exposure dose response relationships of the freshwater bivalve Hyridella australis to cadmium spiked sediments

    International Nuclear Information System (INIS)

    Marasinghe Wadige, Chamani P.M.; Maher, William A.; Taylor, Anne M.; Krikowa, Frank

    2014-01-01

    Highlights: • The exposure–dose–response approach was used to assess cadmium exposure and toxicity. • Accumulated cadmium in H. australis reflected the sediment cadmium exposure. • Spill over of cadmium into the biologically active pool was observed. • Increased cadmium resulted in measurable biological effects. • H. australis has the potential to be a cadmium biomonitor in freshwater environments. - Abstract: To understand how benthic biota may respond to the additive or antagonistic effects of metal mixtures in the environment it is first necessary to examine their responses to the individual metals. In this context, laboratory controlled single metal-spiked sediment toxicity tests are useful to assess this. The exposure–dose–response relationships of Hyridella australis to cadmium-spiked sediments were, therefore, investigated in laboratory microcosms. H. australis was exposed to individual cadmium spiked sediments (<0.05 (control), 4 ± 0.3 (low) and 15 ± 1 (high) μg/g dry mass) for 28 days. Dose was measured as cadmium accumulation in whole soft body and individual tissues at weekly intervals over the exposure period. Dose was further examined as sub-cellular localisation of cadmium in hepatopancreas tissues. The biological responses in terms of enzymatic and cellular biomarkers were measured in hepatopancreas tissues at day 28. H. australis accumulated cadmium from spiked sediments with an 8-fold (low exposure organisms) and 16-fold (high exposure organisms) increase at day 28 compared to control organisms. The accumulated tissue cadmium concentrations reflected the sediment cadmium exposure at day 28. Cadmium accumulation in high exposure organisms was inversely related to the tissue calcium concentrations. Gills of H. australis showed significantly higher cadmium accumulation than the other tissues. Accumulated cadmium in biologically active and biologically detoxified metal pools was not significantly different in cadmium exposed

  2. A Spiking Neural Network Model of the Lateral Geniculate Nucleus on the SpiNNaker Machine

    Directory of Open Access Journals (Sweden)

    Basabdatta Sen-Bhattacharya

    2017-08-01

    Full Text Available We present a spiking neural network model of the thalamic Lateral Geniculate Nucleus (LGN developed on SpiNNaker, which is a state-of-the-art digital neuromorphic hardware built with very-low-power ARM processors. The parallel, event-based data processing in SpiNNaker makes it viable for building massively parallel neuro-computational frameworks. The LGN model has 140 neurons representing a “basic building block” for larger modular architectures. The motivation of this work is to simulate biologically plausible LGN dynamics on SpiNNaker. Synaptic layout of the model is consistent with biology. The model response is validated with existing literature reporting entrainment in steady state visually evoked potentials (SSVEP—brain oscillations corresponding to periodic visual stimuli recorded via electroencephalography (EEG. Periodic stimulus to the model is provided by: a synthetic spike-train with inter-spike-intervals in the range 10–50 Hz at a resolution of 1 Hz; and spike-train output from a state-of-the-art electronic retina subjected to a light emitting diode flashing at 10, 20, and 40 Hz, simulating real-world visual stimulus to the model. The resolution of simulation is 0.1 ms to ensure solution accuracy for the underlying differential equations defining Izhikevichs neuron model. Under this constraint, 1 s of model simulation time is executed in 10 s real time on SpiNNaker; this is because simulations on SpiNNaker work in real time for time-steps dt ⩾ 1 ms. The model output shows entrainment with both sets of input and contains harmonic components of the fundamental frequency. However, suppressing the feed-forward inhibition in the circuit produces subharmonics within the gamma band (>30 Hz implying a reduced information transmission fidelity. These model predictions agree with recent lumped-parameter computational model-based predictions, using conventional computers. Scalability of the framework is demonstrated by a multi

  3. Exposure dose response relationships of the freshwater bivalve Hyridella australis to cadmium spiked sediments

    Energy Technology Data Exchange (ETDEWEB)

    Marasinghe Wadige, Chamani P.M., E-mail: chamani.marasinghe.wadige@canberra.edu.au; Maher, William A.; Taylor, Anne M.; Krikowa, Frank

    2014-07-01

    Highlights: • The exposure–dose–response approach was used to assess cadmium exposure and toxicity. • Accumulated cadmium in H. australis reflected the sediment cadmium exposure. • Spill over of cadmium into the biologically active pool was observed. • Increased cadmium resulted in measurable biological effects. • H. australis has the potential to be a cadmium biomonitor in freshwater environments. - Abstract: To understand how benthic biota may respond to the additive or antagonistic effects of metal mixtures in the environment it is first necessary to examine their responses to the individual metals. In this context, laboratory controlled single metal-spiked sediment toxicity tests are useful to assess this. The exposure–dose–response relationships of Hyridella australis to cadmium-spiked sediments were, therefore, investigated in laboratory microcosms. H. australis was exposed to individual cadmium spiked sediments (<0.05 (control), 4 ± 0.3 (low) and 15 ± 1 (high) μg/g dry mass) for 28 days. Dose was measured as cadmium accumulation in whole soft body and individual tissues at weekly intervals over the exposure period. Dose was further examined as sub-cellular localisation of cadmium in hepatopancreas tissues. The biological responses in terms of enzymatic and cellular biomarkers were measured in hepatopancreas tissues at day 28. H. australis accumulated cadmium from spiked sediments with an 8-fold (low exposure organisms) and 16-fold (high exposure organisms) increase at day 28 compared to control organisms. The accumulated tissue cadmium concentrations reflected the sediment cadmium exposure at day 28. Cadmium accumulation in high exposure organisms was inversely related to the tissue calcium concentrations. Gills of H. australis showed significantly higher cadmium accumulation than the other tissues. Accumulated cadmium in biologically active and biologically detoxified metal pools was not significantly different in cadmium exposed

  4. Sequential Analysis of Gamma Spectra

    International Nuclear Information System (INIS)

    Fayez-Hassan, M.; Hella, Kh.M.

    2009-01-01

    This work shows how easy one can deal with a huge number of gamma spectra. The method can be used for radiation monitoring. It is based on the macro feature of the windows XP connected to QBASIC software. The routine was used usefully in generating accurate results free from human errors. One hundred measured gamma spectra were fully analyzed in 10 minutes using our fast and automated method controlling the Genie 2000 gamma acquisition analysis software.

  5. Response spectra in alluvial soils

    International Nuclear Information System (INIS)

    Chandrasekharan, A.R.; Paul, D.K.

    1975-01-01

    For aseismic design of structures, the ground motion data is assumed either in the form of ground acceleration as a function of time or indirectly in the form of response spectra. Though the response spectra approach has limitations like not being applicable for nonlinear problems, it is usually used for structures like nuclear power plants. Fifty accelerograms recorded at alluvial sites have been processed. Since different empirical formulas relating acceleration with magnitude and distance give a wide scatter of values, peak ground acceleration alone cannot be the parameter as is assumed by a number of authors. The spectra corresponding to 5% damping have been normalised with respect to three parameters, namely, peak ground acceleration, peak ground velocity and a nondimensional quantity ad/v 2 . Envelopee of maxima and minima as well as average response spectra has been obtained. A comparison with the USAEC spectra has been made. A relation between ground acceleration, ground velocity and ad/v 2 has been obtained which would nearly give the same magnification of the response. A design response spectra for alluvial soils has been recommended. (author)

  6. A stimulus-dependent spike threshold is an optimal neural coder

    Directory of Open Access Journals (Sweden)

    Douglas L Jones

    2015-06-01

    Full Text Available A neural code based on sequences of spikes can consume a significant portion of the brain’s energy budget. Thus, energy considerations would dictate that spiking activity be kept as low as possible. However, a high spike-rate improves the coding and representation of signals in spike trains, particularly in sensory systems. These are competing demands, and selective pressure has presumably worked to optimize coding by apportioning a minimum number of spikes so as to maximize coding fidelity. The mechanisms by which a neuron generates spikes while maintaining a fidelity criterion are not known. Here, we show that a signal-dependent neural threshold, similar to a dynamic or adapting threshold, optimizes the trade-off between spike generation (encoding and fidelity (decoding. The threshold mimics a post-synaptic membrane (a low-pass filter and serves as an internal decoder. Further, it sets the average firing rate (the energy constraint. The decoding process provides an internal copy of the coding error to the spike-generator which emits a spike when the error equals or exceeds a spike threshold. When optimized, the trade-off leads to a deterministic spike firing-rule that generates optimally timed spikes so as to maximize fidelity. The optimal coder is derived in closed-form in the limit of high spike-rates, when the signal can be approximated as a piece-wise constant signal. The predicted spike-times are close to those obtained experimentally in the primary electrosensory afferent neurons of weakly electric fish (Apteronotus leptorhynchus and pyramidal neurons from the somatosensory cortex of the rat. We suggest that KCNQ/Kv7 channels (underlying the M-current are good candidates for the decoder. They are widely coupled to metabolic processes and do not inactivate. We conclude that the neural threshold is optimized to generate an energy-efficient and high-fidelity neural code.

  7. GABA(B) receptors inhibit backpropagating dendritic spikes in hippocampal CA1 pyramidal cells in vivo.

    Science.gov (United States)

    Leung, L Stan; Peloquin, Pascal

    2006-01-01

    Spike backpropagation has been proposed to enhance dendritic depolarization and synaptic plasticity. However, relatively little is known about the inhibitory control of spike backpropagation in vivo. In this study, the backpropagation of the antidromic spike into the dendrites of CA1 pyramidal cells was studied by extracellular recording in urethane-anesthetized rats. The population antidromic spike (pAS) in CA1 following stimulation of the alveus was recorded simultaneously with a 16-channel silicon probe and analyzed as current source density (CSD). The pAS current sink was shown to sequentially invade the soma and then the apical and basal dendrites. When the pAS was preceded sinks were reduced and delayed. Dendritic spike suppression was large after a high-intensity CA3 conditioning stimulus that evoked a population spike, small after a low-intensity CA3 conditioning stimulus, and weak after conditioning by another pAS. The late (150-400 ms latency) inhibition of the backpropagating pAS at the apical and basal dendrites was partially relieved by a GABA(B) receptor antagonist, CGP35348 or CGP56999A, given intracerebroventricularly (icv). CGP35348 icv also decreased the latency of the antidromic spike sinks at all depths. A compartment cable model of a CA1 pyramidal cell with excitable dendrites, combined with a model of extracellular potential generation, confirms that GABA(B) receptor activation delays a backpropagating spike and blocks distal dendritic spikes. GABA(B) receptor-mediated conductance increase and hyperpolarization, amplified by removing dendritic I(A) inactivation, contribute to conditioned dendritic spike suppression. In addition, the model shows that slow Na(+) channel inactivation also participates in conditioned spike suppression, which may partly explain the small dendritic spike suppression after conditioning with a weak orthodromic stimulus or another antidromic spike. Thus, both theory and experiment confirm an important role of the GABA

  8. Mercury spikes suggest volcanic driver of the Ordovician-Silurian mass extinction.

    Science.gov (United States)

    Gong, Qing; Wang, Xiangdong; Zhao, Laishi; Grasby, Stephen E; Chen, Zhong-Qiang; Zhang, Lei; Li, Yang; Cao, Ling; Li, Zhihong

    2017-07-13

    The second largest Phanerozoic mass extinction occurred at the Ordovician-Silurian (O-S) boundary. However, unlike the other major mass extinction events, the driver for the O-S extinction remains uncertain. The abundance of mercury (Hg) and total organic carbon (TOC) of Ordovician and early Silurian marine sediments were analyzed from four sections (Huanghuachang, Chenjiahe, Wangjiawan and Dingjiapo) in the Yichang area, South China, as a test for evidence of massive volcanism associated with the O-S event. Our results indicate the Hg concentrations generally vary in parallel with TOC, and that the Hg/TOC ratios remain low and steady state through the Early and Middle Ordovician. However, Hg concentrations and the Hg/TOC ratio increased rapidly in the Late Katian, and have a second peak during the Late Hirnantian (Late Ordovician) that was temporally coincident with two main pulses of mass extinction. Hg isotope data display little to no variation associated with the Hg spikes during the extinction intervals, indicating that the observed Hg spikes are from a volcanic source. These results suggest intense volcanism occurred during the Late Ordovician, and as in other Phanerozoic extinctions, likely played an important role in the O-S event.

  9. Does the thermal spike affect low energy ion-induced interfacial mixing?

    International Nuclear Information System (INIS)

    Suele, P.; Menyhard, M.; Nordlund, K.

    2003-01-01

    Molecular dynamics simulations have been used to obtain the three-dimensional distribution of interfacial mixing and cascade defects in Ti/Pt multilayer system due to single 1 keV Ar + impact at grazing angle of incidence. The Ti/Pt system was chosen because of its relatively high heat of mixing in the binary alloy and therefore a suitable candidate for testing the effect of heat of mixing on ion-beam mixing. However, the calculated mixing profile is not sensitive to the heat of mixing. Therefore the thermal spike model of mixing is not fully supported under these irradiation conditions. Instead we found that the majority of mixing occurs after the thermal spike during the relaxation process. These conclusions are supported by liquid, vacancy as well as adatom analysis. The interfacial mixing is in various aspects anomalous in this system: the time evolution of mixing is leading to a phase delay for Ti mixing, and Pt exhibits an unexpected double peaked mixing evolution. The reasons to these effects are discussed

  10. Component spectra extraction from terahertz measurements of unknown mixtures.

    Science.gov (United States)

    Li, Xian; Hou, D B; Huang, P J; Cai, J H; Zhang, G X

    2015-10-20

    The aim of this work is to extract component spectra from unknown mixtures in the terahertz region. To that end, a method, hard modeling factor analysis (HMFA), was applied to resolve terahertz spectral matrices collected from the unknown mixtures. This method does not require any expertise of the user and allows the consideration of nonlinear effects such as peak variations or peak shifts. It describes the spectra using a peak-based nonlinear mathematic model and builds the component spectra automatically by recombination of the resolved peaks through correlation analysis. Meanwhile, modifications on the method were made to take the features of terahertz spectra into account and to deal with the artificial baseline problem that troubles the extraction process of some terahertz spectra. In order to validate the proposed method, simulated wideband terahertz spectra of binary and ternary systems and experimental terahertz absorption spectra of amino acids mixtures were tested. In each test, not only the number of pure components could be correctly predicted but also the identified pure spectra had a good similarity with the true spectra. Moreover, the proposed method associated the molecular motions with the component extraction, making the identification process more physically meaningful and interpretable compared to other methods. The results indicate that the HMFA method with the modifications can be a practical tool for identifying component terahertz spectra in completely unknown mixtures. This work reports the solution to this kind of problem in the terahertz region for the first time, to the best of the authors' knowledge, and represents a significant advance toward exploring physical or chemical mechanisms of unknown complex systems by terahertz spectroscopy.

  11. In the Crosshair: Astrometric Exoplanet Detection with WFIRST's Diffraction Spikes

    Science.gov (United States)

    Melchior, Peter; Spergel, David; Lanz, Arianna

    2018-02-01

    WFIRST will conduct a coronagraphic program that characterizes the atmospheres of planets around bright nearby stars. When observed with the WFIRST Wide Field Camera, these stars will saturate the detector and produce very strong diffraction spikes. In this paper, we forecast the astrometric precision that WFIRST can achieve by centering on the diffraction spikes of highly saturated stars. This measurement principle is strongly facilitated by the WFIRST H4RG detectors, which confine excess charges within the potential well of saturated pixels. By adopting a simplified analytical model of the diffraction spike caused by a single support strut obscuring the telescope aperture, integrated over the WFIRST pixel size, we predict the performance of this approach with the Fisher-matrix formalism. We discuss the validity of the model and find that 10 μ {as} astrometric precision is achievable with a single 100 s exposure of an {R}{AB}=6 or a {J}{AB}=5 star. We discuss observational limitations from the optical distortion correction and pixel-level artifacts, which need to be calibrated at the level of 10{--}20 μ {as} so as to not dominate the error budget. To suppress those systematics, we suggest a series of short exposures, dithered by at least several hundred pixels, to reach an effective per-visit astrometric precision better than 10 μ {as}. If this can be achieved, a dedicated WFIRST GO program will be able to detect Earth-mass exoplanets with orbital periods of ≳ 1 {year} around stars within a few pc as well as Neptune-like planets with shorter periods or around more massive or distant stars. Such a program will also enable mass measurements of many anticipated direct-imaging exoplanet targets of the WFIRST coronagraph and a “starshade” occulter.

  12. Systematic regional variations in Purkinje cell spiking patterns.

    Directory of Open Access Journals (Sweden)

    Jianqiang Xiao

    Full Text Available In contrast to the uniform anatomy of the cerebellar cortex, molecular and physiological studies indicate that significant differences exist between cortical regions, suggesting that the spiking activity of Purkinje cells (PCs in different regions could also show distinct characteristics. To investigate this possibility we obtained extracellular recordings from PCs in different zebrin bands in crus IIa and vermis lobules VIII and IX in anesthetized rats in order to compare PC firing characteristics between zebrin positive (Z+ and negative (Z- bands. In addition, we analyzed recordings from PCs in the A2 and C1 zones of several lobules in the posterior lobe, which largely contain Z+ and Z- PCs, respectively. In both datasets significant differences in simple spike (SS activity were observed between cortical regions. Specifically, Z- and C1 PCs had higher SS firing rates than Z+ and A2 PCs, respectively. The irregularity of SS firing (as assessed by measures of interspike interval distribution was greater in Z+ bands in both absolute and relative terms. The results regarding systematic variations in complex spike (CS activity were less consistent, suggesting that while real differences can exist, they may be sensitive to other factors than the cortical location of the PC. However, differences in the interactions between SSs and CSs, including the post-CS pause in SSs and post-pause modulation of SSs, were also consistently observed between bands. Similar, though less strong trends were observed in the zonal recordings. These systematic variations in spontaneous firing characteristics of PCs between zebrin bands in vivo, raises the possibility that fundamental differences in information encoding exist between cerebellar cortical regions.

  13. Spike-timing dependent plasticity in the striatum

    Directory of Open Access Journals (Sweden)

    Elodie Fino

    2010-06-01

    Full Text Available The striatum is the major input nucleus of basal ganglia, an ensemble of interconnected sub-cortical nuclei associated with fundamental processes of action-selection and procedural learning and memory. The striatum receives afferents from the cerebral cortex and the thalamus. In turn, it relays the integrated information towards the basal ganglia output nuclei through which it operates a selected activation of behavioral effectors. The striatal output neurons, the GABAergic medium-sized spiny neurons (MSNs, are in charge of the detection and integration of behaviorally relevant information. This property confers to the striatum the ability to extract relevant information from the background noise and select cognitive-motor sequences adapted to environmental stimuli. As long-term synaptic efficacy changes are believed to underlie learning and memory, the corticostriatal long-term plasticity provides a fundamental mechanism for the function of the basal ganglia in procedural learning. Here, we reviewed the different forms of spike-timing dependent plasticity (STDP occurring at corticostriatal synapses. Most of the studies have focused on MSNs and their ability to develop long-term plasticity. Nevertheless, the striatal interneurons (the fast-spiking GABAergic, the NO synthase and cholinergic interneurons also receive monosynaptic afferents from the cortex and tightly regulated corticostriatal information processing. Therefore, it is important to take into account the variety of striatal neurons to fully understand the ability of striatum to develop long-term plasticity. Corticostriatal STDP with various spike-timing dependence have been observed depending on the neuronal sub-populations and experimental conditions. This complexity highlights the extraordinary potentiality in term of plasticity of the corticostriatal pathway.

  14. From spiking neuron models to linear-nonlinear models.

    Directory of Open Access Journals (Sweden)

    Srdjan Ostojic

    Full Text Available Neurons transform time-varying inputs into action potentials emitted stochastically at a time dependent rate. The mapping from current input to output firing rate is often represented with the help of phenomenological models such as the linear-nonlinear (LN cascade, in which the output firing rate is estimated by applying to the input successively a linear temporal filter and a static non-linear transformation. These simplified models leave out the biophysical details of action potential generation. It is not a priori clear to which extent the input-output mapping of biophysically more realistic, spiking neuron models can be reduced to a simple linear-nonlinear cascade. Here we investigate this question for the leaky integrate-and-fire (LIF, exponential integrate-and-fire (EIF and conductance-based Wang-Buzsáki models in presence of background synaptic activity. We exploit available analytic results for these models to determine the corresponding linear filter and static non-linearity in a parameter-free form. We show that the obtained functions are identical to the linear filter and static non-linearity determined using standard reverse correlation analysis. We then quantitatively compare the output of the corresponding linear-nonlinear cascade with numerical simulations of spiking neurons, systematically varying the parameters of input signal and background noise. We find that the LN cascade provides accurate estimates of the firing rates of spiking neurons in most of parameter space. For the EIF and Wang-Buzsáki models, we show that the LN cascade can be reduced to a firing rate model, the timescale of which we determine analytically. Finally we introduce an adaptive timescale rate model in which the timescale of the linear filter depends on the instantaneous firing rate. This model leads to highly accurate estimates of instantaneous firing rates.

  15. Codeine-spiked beer in a date rape case?

    Science.gov (United States)

    Havig, Stine Marie; Wiik, Elisabeth; Karinen, Ritva; Brochmann, Gerd Wenche; Vevelstad, Merete

    2016-11-01

    A case of suspected drug-facilitated sexual assault, involving codeine and acetaminophen, possibly mixed in beer, was recently addressed at the Norwegian Institute of Public Health. To examine the case, a small study was performed, spiking beer with preparations containing codeine and acetaminophen and observing the concentrations, appearance, and taste of the solutions. The study revealed the majority of the preparations to be quickly soluble in beer, achieving high concentrations, but at the expense of strong taste and drastic visible changes in the beer.

  16. Self-organization of spiking neurons using action potential timing.

    Science.gov (United States)

    Ruf, B; Schmitt, M

    1998-01-01

    We propose a mechanism for unsupervised learning in networks of spiking neurons which is based on the timing of single firing events. Our results show that a topology preserving behavior quite similar to that of Kohonen's self-organizing map can be achieved using temporal coding. In contrast to previous approaches, which use rate coding, the winner among competing neurons can be determined fast and locally. Our model is a further step toward a more realistic description of unsupervised learning in biological neural systems. Furthermore, it may provide a basis for fast implementations in pulsed VLSI (very large scale integration).

  17. First-spike latency in the presence of spontaneous activity

    Czech Academy of Sciences Publication Activity Database

    Pawlas, Z.; Klebanov, L. B.; Beneš, V.; Prokešová, M.; Popelář, Jiří; Lánský, Petr

    2010-01-01

    Roč. 22, č. 7 (2010), s. 1675-1693 ISSN 0899-7667 R&D Projects: GA ČR(CZ) GA309/07/1336; GA MŠk(CZ) LC554 Grant - others:GA AVCR(CZ) IAA101120604; GA ČR(CZ) GP201/08/P100 Program:IA Institutional research plan: CEZ:AV0Z50390703; CEZ:AV0Z50110509 Keywords : spike trans * inferior colliculus * response latency Subject RIV: FH - Neurology Impact factor: 2.290, year: 2010

  18. On the Non-Learnability of a Single Spiking Neuron

    Czech Academy of Sciences Publication Activity Database

    Šíma, Jiří; Sgall, Jiří

    2005-01-01

    Roč. 17, č. 12 (2005), s. 2635-2647 ISSN 0899-7667 R&D Projects: GA ČR GA201/02/1456; GA AV ČR 1ET100300517; GA MŠk LN00A056; GA MŠk(CZ) 1M0545 Institutional research plan: CEZ:AV0Z10300504; CEZ:AV0Z10190503 Keywords : spiking neuron * consistency problem * NP-completness * PAC model * robust learning * representation problem Subject RIV: BA - General Mathematics Impact factor: 2.591, year: 2005

  19. Propagation of epileptic spikes reconstructed from spatiotemporal magnetoencephalographic and electroencephalographic source analysis.

    Science.gov (United States)

    Tanaka, Naoaki; Hämäläinen, Matti S; Ahlfors, Seppo P; Liu, Hesheng; Madsen, Joseph R; Bourgeois, Blaise F; Lee, Jong Woo; Dworetzky, Barbara A; Belliveau, John W; Stufflebeam, Steven M

    2010-03-01

    The purpose of this study is to assess the accuracy of spatiotemporal source analysis of magnetoencephalography (MEG) and scalp electroencephalography (EEG) for representing the propagation of frontotemporal spikes in patients with partial epilepsy. This study focuses on frontotemporal spikes, which are typically characterized by a preceding anterior temporal peak followed by an ipsilateral inferior frontal peak. Ten patients with frontotemporal spikes on MEG/EEG were studied. We analyzed the propagation of temporal to frontal epileptic spikes on both MEG and EEG independently by using a cortically constrained minimum norm estimate (MNE). Spatiotemporal source distribution of each spike was obtained on the cortical surface derived from the patient's MRI. All patients underwent an extraoperative intracranial EEG (IEEG) recording covering temporal and frontal lobes after presurgical evaluation. We extracted source waveforms of MEG and EEG from the source distribution of interictal spikes at the sites corresponding to the location of intracranial electrodes. The time differences of the ipsilateral temporal and frontal peaks as obtained by MEG, EEG and IEEG were statistically compared in each patient. In all patients, MEG and IEEG showed similar time differences between temporal and frontal peaks. The time differences of EEG spikes were significantly smaller than those of IEEG in nine of ten patients. Spatiotemporal analysis of MEG spikes models the time course of frontotemporal spikes as observed on IEEG more adequately than EEG in our patients. Spatiotemporal source analysis may be useful for planning epilepsy surgery, by predicting the pattern of IEEG spikes. Copyright (c) 2009 Elsevier Inc. All rights reserved.

  20. Changes in Purkinje Cell Simple Spike Encoding of Reach Kinematics during Adaption to a Mechanical Perturbation

    Science.gov (United States)

    Hewitt, Angela L.; Popa, Laurentiu S.

    2015-01-01

    The cerebellum is essential in motor learning. At the cellular level, changes occur in both the simple spike and complex spike firing of Purkinje cells. Because simple spike discharge reflects the main output of the cerebellar cortex, changes in simple spike firing likely reflect the contribution of the cerebellum to the adapted behavior. Therefore, we investigated in Rhesus monkeys how the representation of arm kinematics in Purkinje cell simple spike discharge changed during adaptation to mechanical perturbations of reach movements. Monkeys rapidly adapted to a novel assistive or resistive perturbation along the direction of the reach. Adaptation consisted of matching the amplitude and timing of the perturbation to minimize its effect on the reach. In a majority of Purkinje cells, simple spike firing recorded before and during adaptation demonstrated significant changes in position, velocity, and acceleration sensitivity. The timing of the simple spike representations change within individual cells, including shifts in predictive versus feedback signals. At the population level, feedback-based encoding of position increases early in learning and velocity decreases. Both timing changes reverse later in learning. The complex spike discharge was only weakly modulated by the perturbations, demonstrating that the changes in simple spike firing can be independent of climbing fiber input. In summary, we observed extensive alterations in individual Purkinje cell encoding of reach kinematics, although the movements were nearly identical in the baseline and adapted states. Therefore, adaption to mechanical perturbation of a reaching movement is accompanied by widespread modifications in the simple spike encoding. PMID:25609626

  1. Routes to Chaos Induced by a Discontinuous Resetting Process in a Hybrid Spiking Neuron Model.

    Science.gov (United States)

    Nobukawa, Sou; Nishimura, Haruhiko; Yamanishi, Teruya

    2018-01-10

    Several hybrid spiking neuron models combining continuous spike generation mechanisms and discontinuous resetting processes following spiking have been proposed. The Izhikevich neuron model, for example, can reproduce many spiking patterns. This model clearly possesses various types of bifurcations and routes to chaos under the effect of a state-dependent jump in the resetting process. In this study, we focus further on the relation between chaotic behaviour and the state-dependent jump, approaching the subject by comparing spiking neuron model versions with and without the resetting process. We first adopt a continuous two-dimensional spiking neuron model in which the orbit in the spiking state does not exhibit divergent behaviour. We then insert the resetting process into the model. An evaluation using the Lyapunov exponent with a saltation matrix and a characteristic multiplier of the Poincar'e map reveals that two types of chaotic behaviour (i.e. bursting chaotic spikes and near-period-two chaotic spikes) are induced by the resetting process. In addition, we confirm that this chaotic bursting state is generated from the periodic spiking state because of the slow- and fast-scale dynamics that arise when jumping to the hyperpolarization and depolarization regions, respectively.

  2. Combining abilities for spike traits in a diallel cross of barley

    Directory of Open Access Journals (Sweden)

    Milomirka Madić

    2014-03-01

    Full Text Available Five two-row winter barley (Hordeum vulgare L. cultivars divergent in spike traits were crossed in all possible combinations excluding reciprocals to produce 10 F1 and F2 hybrids for analysis of combining abilities. The analysis of variance of combining abilities showed significant differences for GCA and SCA in F1 hybrids and F2 generation, suggesting additive and non-additive gene action. The GCA/SCA ratio in F1 and F2 indicated the prevalence of the additive component of genetic variance for spike length, grain weight per spike and spike harvest index. By contrast, the SCA variance for grain weight per spike was higher than the GCA variance, indicating the dominance of non-additive gene action. Good GCAs were found in parents having high values for spike length (Djerdap, NS-293, grain number per spike (Vada, Jagodinac, grain weight per spike (Vada, NS-293 and spike harvest index (Djerdap, Jagodinac. None of the parents had good GCA for all traits, suggesting a potential increase in combining abilities for spike traits. The best SCA were obtained mostly from crosses between parents having high x low, high x high or average x low GCA values. Parents having high GCA values may be used to produce improved lines in hybridisation programmes. Combinations with high SCA values may yield good segregating lines in further selection programmes.

  3. An online supervised learning method based on gradient descent for spiking neurons.

    Science.gov (United States)

    Xu, Yan; Yang, Jing; Zhong, Shuiming

    2017-09-01

    The purpose of supervised learning with temporal encoding for spiking neurons is to make the neurons emit a specific spike train encoded by precise firing times of spikes. The gradient-descent-based (GDB) learning methods are widely used and verified in the current research. Although the existing GDB multi-spike learning (or spike sequence learning) methods have good performance, they work in an offline manner and still have some limitations. This paper proposes an online GDB spike sequence learning method for spiking neurons that is based on the online adjustment mechanism of real biological neuron synapses. The method constructs error function and calculates the adjustment of synaptic weights as soon as the neurons emit a spike during their running process. We analyze and synthesize desired and actual output spikes to select appropriate input spikes in the calculation of weight adjustment in this paper. The experimental results show that our method obviously improves learning performance compared with the offline learning manner and has certain advantage on learning accuracy compared with other learning methods. Stronger learning ability determines that the method has large pattern storage capacity. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. A matched-filter algorithm to detect amperometric spikes resulting from quantal secretion.

    Science.gov (United States)

    Balaji Ramachandran, Supriya; Gillis, Kevin D

    2018-01-01

    Electrochemical microelectrodes located immediately adjacent to the cell surface can detect spikes of amperometric current during exocytosis as the transmitter released from a single vesicle is oxidized on the electrode surface. Automated techniques to detect spikes are needed in order to quantify the spike rate as a measure of the rate of exocytosis. We have developed a Matched Filter (MF) detection algorithm that scans the data set with a library of prototype spike templates while performing a least-squares fit to determine the amplitude and standard error. The ratio of the fit amplitude to the standard error constitutes a criterion score that is assigned for each time point and for each template. A spike is detected when the criterion score exceeds a threshold and the highest-scoring template and the time of peak score is identified. The search for the next spike commences only after the score falls below a second, lower threshold to reduce false positives. The approach was extended to detect spikes with double-exponential decays with the sum of two templates. Receiver Operating Characteristic plots (ROCs) demonstrate that the algorithm detects >95% of manually identified spikes with a false-positive rate of ∼2%. ROCs demonstrate that the MF algorithm performs better than algorithms that detect spikes based on a derivative-threshold approach. The MF approach performs well and leads into approaches to identify spike parameters. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Impact of substance P on the correlation of spike train evoked by electro acupuncture

    International Nuclear Information System (INIS)

    Jin, Chen; Zhang, Xuan; Wang, Jiang; Guo, Yi; Zhao, Xue; Guo, Yong-Ming

    2016-01-01

    Highlights: • We analyze spike trains induced by EA before and after inhibiting SP in PC6 area. • Inhibiting SP leads to an increase of spiking rate of median nerve. • SP may modulate membrane potential to affect the spiking rate. • SP has an influence on long-range correlation of spike train evoked by EA. • SP play an important role in EA-induced neural spiking and encoding. - Abstract: Substance P (SP) participates in the neural signal transmission evoked by electro-acupuncture (EA). This paper investigates the impact of SP on the correlation of spike train in the median nerve evoked by EA at 'Neiguan' acupoint (PC6). It shows that the spiking rate and interspike interval (ISI) distribution change obviously after inhibiting SP. This variation of spiking activity indicates that SP affects the temporal structure of spike train through modulating the action potential on median nerve filaments. Furtherly, the correlation coefficient and scaling exponent are considered to measure the correlation of spike train. Scaled Windowed Variance (SWV) method is applied to calculate scaling exponent which quantifies the long-range correlation of the neural electrical signals. It is found that the correlation coefficients of ISI increase after inhibiting SP released. In addition, the scaling exponents of neuronal spike train have significant differences between before and after inhibiting SP. These findings demonstrate that SP has an influence on the long-range correlation of spike train. Our results indicate that SP may play an important role in EA-induced neural spiking and encoding.

  6. Novel Spiked-Washer Repair Is Biomechanically Superior to Suture and Bone Tunnels for Arcuate Fracture Repair.

    Science.gov (United States)

    Vojdani, Saman; Fernandez, Laviel; Jiao, Jian; Enders, Tyler; Ortiz, Steven; Lin, Liangjun; Qin, Yi-Xian; Komatsu, David E; Penna, James; Ruotolo, Charles J

    2017-03-01

    Injuries to the posterolateral corner of the knee can lead to chronic degenerative changes, external rotation instability, and varus instability if not repaired adequately. A proximal fibula avulsion fracture, referred to as an arcuate fracture, has been described in the literature, but a definitive repair technique has yet to be described. The objective of this study was to present a novel arcuate fracture repair technique, using a spiked-washer with an intramedullary screw, and to compare its biomechanical integrity to a previously described suture and bone tunnel method. Ten fresh-frozen cadaveric knees underwent a proximal fibula osteotomy to simulate a proximal fibula avulsion fracture. The lateral knee capsule and posterior cruciate ligament were also sectioned to create maximal varus instability. Five fibulas were repaired using a novel spiked-washer technique and the other 5 were repaired using the suture and bone tunnel method. The repaired knees were subjected to a monotonic varus load using a mechanical testing system instrument until failure of the repair or associated posterolateral corner structures. Compared with the suture repair group, the spiked-washer repair group demonstrated a 100% increase in stiffness, 100% increase in yield, 110% increase in failure force, and 108% increase in energy to failure. The spiked-washer technique offers superior quasi-static biomechanical performance compared with suture repair with bone tunnels for arcuate fractures of the proximal fibula. Further clinical investigation of this technique is warranted and the results of this testing may lead to improved outcomes and patient satisfaction for proximal fibula avulsion fractures.

  7. The sodium channel activator Lu AE98134 normalizes the altered firing properties of fast spiking interneurons in Dlx5/6+/- mice

    DEFF Research Database (Denmark)

    von Schoubye, Nadia Lybøl; Frederiksen, Kristen; Kristiansen, Uffe

    2018-01-01

    Mental disorders such as schizophrenia are associated with impaired firing properties of fast spiking inhibitory interneurons (FSINs) causing reduced task-evoked gamma-oscillation in prefrontal cortex. The voltage-gated sodium channel NaV1.1 is highly expressed in PV-positive interneurons, but only...... facilitated the sodium current mediated by NaV1.1 expressed in HEK cells by shifting its activation to more negative values, decreasing its inactivation kinetics and promoting a persistent inward current. In a slice preparation from the brain of adult mice, Lu AE98134 promoted the excitability of fast spiking...... interneurons by decreasing the threshold for action potentials. We then tested if Lu AE98134 could normalize the altered firing properties of FSINs in Dlx5/6+/- mutant mice. FSINs of this model for schizophrenia are characterized by broader action potentials and higher spike threshold. We found...

  8. Effect of heavy metals on pH buffering capacity and solubility of Ca, Mg, K, and P in non-spiked and heavy metal-spiked soils.

    Science.gov (United States)

    Najafi, Sarvenaz; Jalali, Mohsen

    2016-06-01

    In many parts of the world, soil acidification and heavy metal contamination has become a serious concern due to the adverse effects on chemical properties of soil and crop yield. The aim of this study was to investigate the effect of pH (in the range of 1 to 3 units above and below the native pH of soils) on calcium (Ca), magnesium (Mg), potassium (K), and phosphorus (P) solubility in non-spiked and heavy metal-spiked soil samples. Spiked samples were prepared by cadmium (Cd), copper (Cu), nickel (Ni), and zinc (Zn) as chloride salts and incubating soils for 40 days. The pH buffering capacity (pHBC) of each sample was determined by plotting the amount of H(+) or OH(-) added (mmol kg(-1)) versus the related pH value. The pHBC of soils ranged from 47.1 to 1302.5 mmol kg(-1) for non-spiked samples and from 45.0 to 1187.4 mmol kg(-1) for spiked soil samples. The pHBC values were higher in soil 2 (non-spiked and spiked) which had higher calcium carbonate content. The results indicated the presence of heavy metals in soils generally decreased the solution pH and pHBC values in spiked samples. In general, solubility of Ca, Mg, and K decreased with increasing equilibrium pH of non-spiked and spiked soil samples. In the case of P, increasing the pH to about 7, decreased the solubility in all soils but further increase of pH from 7, enhanced P solubility. The solubility trends and values for Ca, Mg, and K did not differed significantly in non-spiked and spiked samples. But in the case of P, a reduction in solubility was observed in heavy metal-spiked soils. The information obtained in this study can be useful to make better estimation of the effects of soil pollutants on anion and cation solubility from agricultural and environmental viewpoints.

  9. Double photoionisation spectra of molecules

    CERN Document Server

    Eland, John

    2017-01-01

    This book contains spectra of the doubly charged positive ions (dications) of some 75 molecules, including the major constituents of terrestrial and planetary atmospheres and prototypes of major chemical groups. It is intended to be a new resource for research in all areas of molecular spectroscopy involving high energy environments, both terrestrial and extra-terrestrial. All the spectra have been produced by photoionisation using laboratory lamps or synchrotron radiation and have been measured using the magnetic bottle time-of-flight technique by coincidence detection of correlated electron pairs. Full references to published work on the same species are given, though for several molecules these are the first published spectra. Double ionisation energies are listed and discussed in relation to the molecular electronic structure of the molecules. A full introduction to the field of molecular double ionisation is included and the mechanisms by which double photoionisation can occur are examined in detail. A p...

  10. Theory of input spike auto- and cross-correlations and their effect on the response of spiking neurons.

    Science.gov (United States)

    Moreno-Bote, Rubén; Renart, Alfonso; Parga, Néstor

    2008-07-01

    Spike correlations between neurons are ubiquitous in the cortex, but their role is not understood. Here we describe the firing response of a leaky integrate-and-fire neuron (LIF) when it receives a temporarily correlated input generated by presynaptic correlated neuronal populations. Input correlations are characterized in terms of the firing rates, Fano factors, correlation coefficients, and correlation timescale of the neurons driving the target neuron. We show that the sum of the presynaptic spike trains cannot be well described by a Poisson process. In fact, the total input current has a nontrivial two-point correlation function described by two main parameters: the correlation timescale (how precise the input correlations are in time) and the correlation magnitude (how strong they are). Therefore, the total current generated by the input spike trains is not well described by a white noise gaussian process. Instead, we model the total current as a colored gaussian process with the same mean and two-point correlation function, leading to the formulation of the problem in terms of a Fokker-Planck equation. Solutions of the output firing rate are found in the limit of short and long correlation timescales. The solutions described here expand and improve on our previous results (Moreno, de la Rocha, Renart, & Parga, 2002) by presenting new analytical expressions for the output firing rate for general IF neurons, extending the validity of the results for arbitrarily large correlation magnitude, and by describing the differential effect of correlations on the mean-driven or noise-dominated firing regimes. Also the details of this novel formalism are given here for the first time. We employ numerical simulations to confirm the analytical solutions and study the firing response to sudden changes in the input correlations. We expect this formalism to be useful for the study of correlations in neuronal networks and their role in neural processing and information

  11. Spike timing analysis in neural networks with unsupervised synaptic plasticity

    Science.gov (United States)

    Mizusaki, B. E. P.; Agnes, E. J.; Brunnet, L. G.; Erichsen, R., Jr.

    2013-01-01

    The synaptic plasticity rules that sculpt a neural network architecture are key elements to understand cortical processing, as they may explain the emergence of stable, functional activity, while avoiding runaway excitation. For an associative memory framework, they should be built in a way as to enable the network to reproduce a robust spatio-temporal trajectory in response to an external stimulus. Still, how these rules may be implemented in recurrent networks and the way they relate to their capacity of pattern recognition remains unclear. We studied the effects of three phenomenological unsupervised rules in sparsely connected recurrent networks for associative memory: spike-timing-dependent-plasticity, short-term-plasticity and an homeostatic scaling. The system stability is monitored during the learning process of the network, as the mean firing rate converges to a value determined by the homeostatic scaling. Afterwards, it is possible to measure the recovery efficiency of the activity following each initial stimulus. This is evaluated by a measure of the correlation between spike fire timings, and we analysed the full memory separation capacity and limitations of this system.

  12. Approximate, computationally efficient online learning in Bayesian spiking neurons.

    Science.gov (United States)

    Kuhlmann, Levin; Hauser-Raspe, Michael; Manton, Jonathan H; Grayden, David B; Tapson, Jonathan; van Schaik, André

    2014-03-01

    Bayesian spiking neurons (BSNs) provide a probabilistic interpretation of how neurons perform inference and learning. Online learning in BSNs typically involves parameter estimation based on maximum-likelihood expectation-maximization (ML-EM) which is computationally slow and limits the potential of studying networks of BSNs. An online learning algorithm, fast learning (FL), is presented that is more computationally efficient than the benchmark ML-EM for a fixed number of time steps as the number of inputs to a BSN increases (e.g., 16.5 times faster run times for 20 inputs). Although ML-EM appears to converge 2.0 to 3.6 times faster than FL, the computational cost of ML-EM means that ML-EM takes longer to simulate to convergence than FL. FL also provides reasonable convergence performance that is robust to initialization of parameter estimates that are far from the true parameter values. However, parameter estimation depends on the range of true parameter values. Nevertheless, for a physiologically meaningful range of parameter values, FL gives very good average estimation accuracy, despite its approximate nature. The FL algorithm therefore provides an efficient tool, complementary to ML-EM, for exploring BSN networks in more detail in order to better understand their biological relevance. Moreover, the simplicity of the FL algorithm means it can be easily implemented in neuromorphic VLSI such that one can take advantage of the energy-efficient spike coding of BSNs.

  13. Spiked natural matrix materials as quality assessment samples

    International Nuclear Information System (INIS)

    Feiner, M.S.; Sanderson, C.G.

    1988-01-01

    The Environmental Measurements Laboratory has conducted the Quality Assessment Program since 1976 to evaluate the quality of the environmental radioactivity data, which is reported to the Department of Energy by as many as 42 commercial contractors involved in nuclear work. In this program, matrix materials of known radionuclide concentrations are distributed routinely to the contractors and the reported results are compared. The five matrices used are: soil, vegetation, animal tissue, water and filter paper. Environmental soil, vegetation and animal tissue are used, but the water and filter paper samples are prepared by spiking with known amounts of standard solutions traceable to the National Bureau of Standards. A summary of results is given to illustrate the successful operation of the program. Because of the difficulty and high cost of collecting large samples of natural matrix material and to increase the versatility of the program, an attempt was recently made to prepare the soil, vegetation and animal tissue samples with spiked solutions. A description of the preparation of these reference samples and the results of analyses are presented along with a discussion of the pitfalls and advantages of this approach. 19 refs.; 6 tabs

  14. Fuel switching? Demand destruction? Gas market responses to price spikes

    International Nuclear Information System (INIS)

    Lippe, D.

    2004-01-01

    This presentation defined fuel switching and addressed the issue regarding which consumers have the capability to switch fuels. In response to short term price aberrations, consumers with fuel switching capabilities reduce their use of one fuel and increase consumption of an alternative fuel. For example, natural gas consumption by some consumers declines in response to price spikes relative to prices of alternative fuels. This presentation also addressed the issue of differentiating between fuel switching and demand destruction. It also demonstrated how to compare gas prices versus alternative fuel prices and how to determine when consumers will likely switch fuels. Price spikes have implications for long term trends in natural gas demand, supply/demand balances and prices. The power generating sector represents a particular class of gas consumers that reduce operating rates of gas fired plants and increase operating rates of other plants. Some gas consumers even shut down plants until gas prices declines and relative economies improve. Some practical considerations for fuel switching include storage tank capacity, domestic refinery production, winter heating season, and decline in working gas storage. tabs., figs

  15. Macroscopic phase-resetting curves for spiking neural networks

    Science.gov (United States)

    Dumont, Grégory; Ermentrout, G. Bard; Gutkin, Boris

    2017-10-01

    The study of brain rhythms is an open-ended, and challenging, subject of interest in neuroscience. One of the best tools for the understanding of oscillations at the single neuron level is the phase-resetting curve (PRC). Synchronization in networks of neurons, effects of noise on the rhythms, effects of transient stimuli on the ongoing rhythmic activity, and many other features can be understood by the PRC. However, most macroscopic brain rhythms are generated by large populations of neurons, and so far it has been unclear how the PRC formulation can be extended to these more common rhythms. In this paper, we describe a framework to determine a macroscopic PRC (mPRC) for a network of spiking excitatory and inhibitory neurons that generate a macroscopic rhythm. We take advantage of a thermodynamic approach combined with a reduction method to simplify the network description to a small number of ordinary differential equations. From this simplified but exact reduction, we can compute the mPRC via the standard adjoint method. Our theoretical findings are illustrated with and supported by numerical simulations of the full spiking network. Notably our mPRC framework allows us to predict the difference between effects of transient inputs to the excitatory versus the inhibitory neurons in the network.

  16. Spike neural models (part I: The Hodgkin-Huxley model

    Directory of Open Access Journals (Sweden)

    Johnson, Melissa G.

    2017-05-01

    Full Text Available Artificial neural networks, or ANNs, have grown a lot since their inception back in the 1940s. But no matter the changes, one of the most important components of neural networks is still the node, which represents the neuron. Within spiking neural networks, the node is especially important because it contains the functions and properties of neurons that are necessary for their network. One important aspect of neurons is the ionic flow which produces action potentials, or spikes. Forces of diffusion and electrostatic pressure work together with the physical properties of the cell to move ions around changing the cell membrane potential which ultimately produces the action potential. This tutorial reviews the Hodkgin-Huxley model and shows how it simulates the ionic flow of the giant squid axon via four differential equations. The model is implemented in Matlab using Euler's Method to approximate the differential equations. By using Euler's method, an extra parameter is created, the time step. This new parameter needs to be carefully considered or the results of the node may be impaired.

  17. Information filtering by synchronous spikes in a neural population.

    Science.gov (United States)

    Sharafi, Nahal; Benda, Jan; Lindner, Benjamin

    2013-04-01

    Information about time-dependent sensory stimuli is encoded by the spike trains of neurons. Here we consider a population of uncoupled but noisy neurons (each subject to some intrinsic noise) that are driven by a common broadband signal. We ask specifically how much information is encoded in the synchronous activity of the population and how this information transfer is distributed with respect to frequency bands. In order to obtain some insight into the mechanism of information filtering effects found previously in the literature, we develop a mathematical framework to calculate the coherence of the synchronous output with the common stimulus for populations of simple neuron models. Within this frame, the synchronous activity is treated as the product of filtered versions of the spike trains of a subset of neurons. We compare our results for the simple cases of (1) a Poisson neuron with a rate modulation and (2) an LIF neuron with intrinsic white current noise and a current stimulus. For the Poisson neuron, formulas are particularly simple but show only a low-pass behavior of the coherence of synchronous activity. For the LIF model, in contrast, the coherence function of the synchronous activity shows a clear peak at high frequencies, comparable to recent experimental findings. We uncover the mechanism for this shift in the maximum of the coherence and discuss some biological implications of our findings.

  18. Dynamics of Monoterpene Formation in Spike Lavender Plants

    Science.gov (United States)

    Kutzner, Erika; Huber, Claudia; Segura, Juan; Arrillaga, Isabel

    2017-01-01

    The metabolic cross-talk between the mevalonate (MVA) and the methylerythritol phosphate (MEP) pathways was analyzed in spike lavender (Lavandula latifolia Med) on the basis of 13CO2-labelling experiments using wildtype and transgenic plants overexpressing the 3-hydroxy-3-methylglutaryl CoA reductase (HMGR), the first and key enzyme of the MVA pathway. The plants were labelled in the presence of 13CO2 in a gas chamber for controlled pulse and chase periods of time. GC/MS and NMR analysis of 1,8-cineole and camphor, the major monoterpenes present in their essential oil, indicated that the C5-precursors, isopentenyl diphosphate (IPP) and dimethylallyl diphosphate (DMAPP) of both monoterpenes are predominantly biosynthesized via the MEP pathway. Surprisingly, overexpression of HMGR did not have significant impact upon the crosstalk between the MVA and MEP pathways indicating that the MEP route is the preferred pathway for the synthesis of C5 monoterpene precursors in spike lavender. PMID:29257083

  19. Spike-Based Bayesian-Hebbian Learning of Temporal Sequences.

    Directory of Open Access Journals (Sweden)

    Philip J Tully

    2016-05-01

    Full Text Available Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN learning rule. We find that the formation of distributed memories, embodied by increased periods of firing in pools of excitatory neurons, together with asymmetrical associations between these distinct network states, can be acquired through plasticity. The model's feasibility is demonstrated using simulations of adaptive exponential integrate-and-fire model neurons (AdEx. We show that the learning and speed of sequence replay depends on a confluence of biophysically relevant parameters including stimulus duration, level of background noise, ratio of synaptic currents, and strengths of short-term depression and adaptation. Moreover, sequence elements are shown to flexibly participate multiple times in the sequence, suggesting that spiking attractor networks of this type can support an efficient combinatorial code. The model provides a principled approach towards understanding how multiple interacting plasticity mechanisms can coordinate hetero-associative learning in unison.

  20. Automatic detection of interictal spikes using data mining models.

    Science.gov (United States)

    Valenti, Pablo; Cazamajou, Enrique; Scarpettini, Marcelo; Aizemberg, Ariel; Silva, Walter; Kochen, Silvia

    2006-01-15

    A prospective candidate for epilepsy surgery is studied both the ictal and interictal spikes (IS) to determine the localization of the epileptogenic zone. In this work, data mining (DM) classification techniques were utilized to build an automatic detection model. The selected DM algorithms are: Decision Trees (J 4.8), and Statistical Bayesian Classifier (naïve model). The main objective was the detection of IS, isolating them from the EEG's base activity. On the other hand, DM has an attractive advantage in such applications, in that the recognition of epileptic discharges does not need a clear definition of spike morphology. Furthermore, previously 'unseen' patterns could be recognized by the DM with proper 'training'. The results obtained showed that the efficacy of the selected DM algorithms is comparable to the current visual analysis used by the experts. Moreover, DM is faster than the time required for the visual analysis of the EEG. So this tool can assist the experts by facilitating the analysis of a patient's information, and reducing the time and effort required in the process.

  1. Hg stable isotope analysis by the double-spike method.

    Science.gov (United States)

    Mead, Chris; Johnson, Thomas M

    2010-06-01

    Recent publications suggest great potential for analysis of Hg stable isotope abundances to elucidate sources and/or chemical processes that control the environmental impact of mercury. We have developed a new MC-ICP-MS method for analysis of mercury isotope ratios using the double-spike approach, in which a solution containing enriched (196)Hg and (204)Hg is mixed with samples and provides a means to correct for instrumental mass bias and most isotopic fractionation that may occur during sample preparation and introduction into the instrument. Large amounts of isotopic fractionation induced by sample preparation and introduction into the instrument (e.g., by batch reactors) are corrected for. This may greatly enhance various Hg pre-concentration methods by correcting for minor fractionation that may occur during preparation and removing the need to demonstrate 100% recovery. Current precision, when ratios are normalized to the daily average, is 0.06 per thousand, 0.06 per thousand, 0.05 per thousand, and 0.05 per thousand (2sigma) for (202)Hg/(198)Hg, (201)Hg/(198)Hg, (200)Hg/(198)Hg, and (199)Hg/(198)Hg, respectively. This is slightly better than previously published methods. Additionally, this precision was attained despite the presence of large amounts of other Hg isotopes (e.g., 5.0% atom percent (198)Hg) in the spike solution; substantially better precision could be achieved if purer (196)Hg were used.

  2. Correlation Functions and Power Spectra

    DEFF Research Database (Denmark)

    Larsen, Jan

    2006-01-01

    The present lecture note is a supplement to the textbook Digital Signal Processing by J. Proakis and D.G. Manolakis used in the IMM/DTU course 02451 Digital Signal Processing and provides an extended discussion of correlation functions and power spectra. The definitions of correlation functions....... It is possible to define correlation functions and associated spectra for aperiodic, periodic and random signals although the interpretation is different. Moreover, we will discuss correlation functions when mixing these basic signal types. In addition, the note include several examples for the purpose...

  3. Soil emissivity and reflectance spectra measurements

    International Nuclear Information System (INIS)

    Sobrino, Jose A.; Mattar, Cristian; Pardo, Pablo; Jimenez-Munoz, Juan C.; Hook, Simon J.; Baldridge, Alice; Ibanez, Rafael

    2009-01-01

    We present an analysis of the laboratory reflectance and emissivity spectra of 11 soil samples collected on different field campaigns carried out over a diverse suite of test sites in Europe, North Africa, and South America from 2002 to 2008. Hemispherical reflectance spectra were measured from 2.0 to 14 μm with a Fourier transform infrared spectrometer, and x-ray diffraction analysis (XRD) was used to determine the mineralogical phases of the soil samples. Emissivity spectra were obtained from the hemispherical reflectance measurements using Kirchhoff's law and compared with in situ radiance measurements obtained with a CIMEL Electronique CE312-2 thermal radiometer and converted to emissivity using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) temperature and emissivity separation algorithm. The CIMEL has five narrow bands at approximately the same positions as the ASTER. Results show a root mean square error typically below 0.015 between laboratory emissivity measurements and emissivity measurements derived from the field radiometer.

  4. Numerical analysis of alpha spectra using two different codes

    International Nuclear Information System (INIS)

    Hurtado, S.; Jimenez-Ramos, M.C.; Villa, M.; Vioque, I.; Manjon, G.; Garcia-Tenorio, R.

    2008-01-01

    This work presents an intercomparison between commercial software for alpha-particle spectrometry, Genie 2000, and the new free available software, Winalpha, developed by International Atomic Energy Agency (IAEA). In order to compare both codes, different environmental spectra containing plutonium, uranium, thorium and polonium have been analyzed, together with IAEA test alpha spectra. A statistical study was performed in order to evaluate the precision and accuracy in the analyses, and to enhance the confidence in using the software on alpha spectrometric studies

  5. Reduction of the fast electrons preheating by changing the spike launch time in shock ignition approach

    Science.gov (United States)

    Jafar Jafari, Mohammad; Farahbod, Amir Hossein; Rezaei, Somayeh

    2016-01-01

    Target characteristic parameters in shock ignition approach before launching the spike pulse are studied using a 1-D hydrodynamic simulation code. By delaying the spike launch time, the shell areal density, ρR, is increased. The enhanced shell areal density prevents the hot electrons preheating of main fuel which in turn is generated from the intense laser plasma interaction with corona. To consider the effect of the spike launch time on the target performance, the target gain for a wide range of spike powers and launch times are computed. It is noticed that for HiPER reference target, few tenth nanoseconds displacement of spike launch time increases the areal density, ρR, value up to 30-70 percent. Furthermore, by choosing an appropriate spike energy and peak power, the optimum target gain is achieved in which the total driver energy is reduced.

  6. Principal cell spiking, postsynaptic excitation, and oxygen consumption in the rat cerebellar cortex

    DEFF Research Database (Denmark)

    Thomsen, Kirsten; Piilgaard, Henning; Gjedde, Albert

    2009-01-01

    . In contrast, PC spiking was largely responsible for the increase in CMRO2 when ongoing neuronal activity was increased by gamma-aminobutyric acid type A receptor blockade. In this case, CMRO2 increased equally during PC spiking with excitatory synaptic activity as during PC pacemaker spiking without......One contention within the field of neuroimaging concerns the character of the depicted activity: Does it represent neuronal action potential generation (i.e., spiking) or postsynaptic excitation? This question is related to the metabolic costs of different aspects of neurosignaling. The cerebellar...... cortex is well suited for addressing this problem because synaptic input to and spiking of the principal cell, the Purkinje cell (PC), are spatially segregated. Also, PCs are pacemakers, able to generate spikes endogenously. We examined the contributions to cerebellar cortical oxygen consumption (CMRO2...

  7. On the Spike Train Variability Characterized by Variance-to-Mean Power Relationship.

    Science.gov (United States)

    Koyama, Shinsuke

    2015-07-01

    We propose a statistical method for modeling the non-Poisson variability of spike trains observed in a wide range of brain regions. Central to our approach is the assumption that the variance and the mean of interspike intervals are related by a power function characterized by two parameters: the scale factor and exponent. It is shown that this single assumption allows the variability of spike trains to have an arbitrary scale and various dependencies on the firing rate in the spike count statistics, as well as in the interval statistics, depending on the two parameters of the power function. We also propose a statistical model for spike trains that exhibits the variance-to-mean power relationship. Based on this, a maximum likelihood method is developed for inferring the parameters from rate-modulated spike trains. The proposed method is illustrated on simulated and experimental spike trains.

  8. Measurement of the MACS of {sup 181}Ta(n,γ) at kT=30 keV as a test of a method for Maxwellian neutron spectra generation

    Energy Technology Data Exchange (ETDEWEB)

    Praena, J., E-mail: jpraena@us.es [Universidad de Sevilla (Spain); Centro Nacional de Aceleradores, Sevilla (Spain); Mastinu, P.F. [Laboratori Nazionali di Legnaro, INFN, Padova (Italy); Pignatari, M. [Department of Physics, University of Basel, Klingelbergstrasse 82, CH-4056 Basel (Switzerland); Quesada, J.M. [Universidad de Sevilla (Spain); García-López, J. [Universidad de Sevilla (Spain); Centro Nacional de Aceleradores, Sevilla (Spain); Lozano, M. [Universidad de Sevilla (Spain); Dzysiuk, N. [International Nuclear Safety Center of Ukraine, Kyiv (Ukraine); Capote, R. [NAPC–Nuclear Data Section, International Atomic Energy Agency, Vienna (Austria); Martín-Hernández, G. [Centro de Aplicaciones Tecnólogicas y Desarrollo Nuclear, 5ta y 30, Playa, La Habana (Cuba)

    2013-11-01

    Measurement of the Maxwellian-Averaged Cross-Section (MACS) of the {sup 181}Ta(n,γ) reaction at kT=30 keV by the activation technique using an innovative method for the generation of Maxwellian neutron spectra is presented. The method is based on the shaping of the proton beam to produce a desired neutron spectrum using the {sup 7}Li(p,n) reaction as a neutron source. The characterization of neutron spectra has been performed by combining measured proton distributions, an analytical description of the differential neutron yield in angle and energy of the {sup 7}Li(p,n) reaction, and with Monte Carlo simulations of the neutron transport. A measured value equal to 815±73 mbarn is reported for the MACS of the reaction {sup 181}Ta(n,γ) at kT=30 keV. The MACS of the reaction {sup 197}Au(n,γ) provided by KADoNiS has been used as a reference. -- Author-Highlights: • Generation of Maxwellian neutron spectrum for astrophysics and nuclear data validation. • {sup 7}Li(p,n) reaction and proton distributions conformed by aluminum as a shaper foil. • Measurement of the proton distributions and simulation of the neutron transport. • MACS of {sup 181}Ta(n,γ) at kT=30 keV measured by the activation technique. • First accelerator-based neutron source in Spain.

  9. SPAN: spike pattern association neuron for learning spatio-temporal sequences

    OpenAIRE

    Mohemmed, A; Schliebs, S; Matsuda, S; Kasabov, N

    2012-01-01

    Spiking Neural Networks (SNN) were shown to be suitable tools for the processing of spatio-temporal information. However, due to their inherent complexity, the formulation of efficient supervised learning algorithms for SNN is difficult and remains an important problem in the research area. This article presents SPAN — a spiking neuron that is able to learn associations of arbitrary spike trains in a supervised fashion allowing the processing of spatio-temporal information encoded in the prec...

  10. Spike Pattern Structure Influences Efficacy Variability under STDP and Synaptic Homeostasis

    OpenAIRE

    Bi, Zedong; Zhou, Changsong; Zhou, Hai-Jun

    2015-01-01

    In neural systems, synaptic plasticity is usually driven by spike trains. Due to the inherent noises of neurons, synapses and networks, spike trains typically exhibit externally uncontrollable variability such as spatial heterogeneity and temporal stochasticity, resulting in variability of synapses, which we call efficacy variability. Spike patterns with the same population rate but inducing different efficacy variability may result in neuronal networks with sharply different structures and f...

  11. A COMPARISON OF GADRAS SIMULATED AND MEASURED GAMMA RAY SPECTRA

    Energy Technology Data Exchange (ETDEWEB)

    Jeffcoat, R.; Salaymeh, S.

    2010-06-28

    Gamma-ray radiation detection systems are continuously being developed and improved for detecting the presence of radioactive material and for identifying isotopes present. Gamma-ray spectra, from many different isotopes and in different types and thicknesses of attenuation material and matrixes, are needed to evaluate the performance of these devices. Recently, a test and evaluation exercise was performed by the Savannah River National Laboratory that required a large number of gamma-ray spectra. Simulated spectra were used for a major portion of the testing in order to provide a pool of data large enough for the results to be statistically significant. The test data set was comprised of two types of data, measured and simulated. The measured data were acquired with a hand-held Radioisotope Identification Device (RIID) and simulated spectra were created using Gamma Detector Response and Analysis Software (GADRAS, Mitchell and Mattingly, Sandia National Laboratory). GADRAS uses a one-dimensional discrete ordinate calculation to simulate gamma-ray spectra. The measured and simulated spectra have been analyzed and compared. This paper will discuss the results of the comparison and offer explanations for spectral differences.

  12. Average stopping powers and the use of non-analyte spiking for the determination of phosphorus and sodium by PIPPS

    International Nuclear Information System (INIS)

    Olivier, C.; Morland, H.J.

    1991-01-01

    By using particle induced prompt photon spectrometry, PIPPS, the ratios of the average stopping powers in samples and standards can be used to determine elemental compositions. Since the average stopping powers in the samples are in general unknown, this procedure poses a problem. It has been shown that by spiking the sample with a known amount of a compound with known stopping power and containing a non-analyte element, appropriate stopping powers in the samples can be determined by measuring the prompt gamma-ray yields induced in the spike. Using 5-MeV protons and lithium compounds as non-analyte spikes, sodium and phosphorus were determined in ivory, while sodium was determined in geological samples. For the stopping power determinations in the samples the 429-keV 7 Li n(1,0) and 478-keV 7 Li (1,0) gamma rays were measured, while for phosphorus and sodium determinations the high yield 1,266-keV 31 P (1,0), 440-keV 23 Na (1,0), 1,634-keV, Na 23 α(1,0) and 1,637-keV 23 Na (2,1) gamma rays were used. The method was tested by analyzing the standard reference materials SRM 91, 120c and 694

  13. Adenosine A2A Receptors Control Glutamatergic Synaptic Plasticity in Fast Spiking Interneurons of the Prefrontal Cortex

    Directory of Open Access Journals (Sweden)

    Amber Kerkhofs

    2018-03-01

    Full Text Available Adenosine A2A receptors (A2AR are activated upon increased synaptic activity to assist in the implementation of long-term plastic changes at synapses. While it is reported that A2AR are involved in the control of prefrontal cortex (PFC-dependent behavior such as working memory, reversal learning and effort-based decision making, it is not known whether A2AR control glutamatergic synapse plasticity within the medial PFC (mPFC. To elucidate that, we tested whether A2AR blockade affects long-term plasticity (LTP of excitatory post-synaptic potentials in pyramidal neurons and fast spiking (FS interneurons in layer 5 of the mPFC and of population spikes. Our results show that A2AR are enriched at mPFC synapses, where their blockade reversed the direction of plasticity at excitatory synapses onto layer 5 FS interneurons from LTP to long-term depression, while their blockade had no effect on the induction of LTP at excitatory synapses onto layer 5 pyramidal neurons. At the network level, extracellularly induced LTP of population spikes was reduced by A2AR blockade. The interneuron-specificity of A2AR in controlling glutamatergic synapse LTP may ensure that during periods of high synaptic activity, a proper excitation/inhibition balance is maintained within the mPFC.

  14. Clapping-surpressed focal spikes in EEG may be unique for the patients with rett syndrome : a case report.

    Science.gov (United States)

    Lv, Yudan; Liu, Chang; Shi, Mingchao; Cui, Li

    2016-06-13

    Rett syndrome is a severe neurodevelopmental disorder that primarily affects females. Typical features include a loss of purposeful hand skills, development of hand stereotypies, loss of spoken language, gait abnormalities, and acquired microcephaly. However, Rett syndrome hasn't been recognized by clinical doctors at the early stage. So we need to find some special characters. We reported a Chinese case of Rett syndrome, exhibiting continuous centrotemporal spikes in EEG with paroxysmal suppression by hand stereotypies (hand clapping). The child, female, 4 years old, presented with a significant regression in her spoken language skills, hand stereotypies (hand clapping and hand wringing), a wider based gait with difficulties in balance, repeated abnormal behaviors (bruxism and head banging). With her clinical-history, Rett syndrome was suspected and genetic testing with mutation in MECP2 confirmed the diagnosis. Her EEG showed slow acticity in background and revealed a specific feature that continuous centrotemporal spikes can be suppressed by the repeated hand clapping. And when the hand stopped, the spikes reoccured again. This unique EEG signature has rarely been reported, which will expand the spectrum of EEG abnormalities in Rett syndrome.

  15. Test

    DEFF Research Database (Denmark)

    Bendixen, Carsten

    2014-01-01

    Bidrag med en kortfattet, introducerende, perspektiverende og begrebsafklarende fremstilling af begrebet test i det pædagogiske univers.......Bidrag med en kortfattet, introducerende, perspektiverende og begrebsafklarende fremstilling af begrebet test i det pædagogiske univers....

  16. Population activity statistics dissect subthreshold and spiking variability in V1.

    Science.gov (United States)

    Bányai, Mihály; Koman, Zsombor; Orbán, Gergő

    2017-07-01

    Response variability, as measured by fluctuating responses upon repeated performance of trials, is a major component of neural responses, and its characterization is key to interpret high dimensional population recordings. Response variability and covariability display predictable changes upon changes in stimulus and cognitive or behavioral state, providing an opportunity to test the predictive power of models of neural variability. Still, there is little agreement on which model to use as a building block for population-level analyses, and models of variability are often treated as a subject of choice. We investigate two competing models, the doubly stochastic Poisson (DSP) model assuming stochasticity at spike generation, and the rectified Gaussian (RG) model tracing variability back to membrane potential variance, to analyze stimulus-dependent modulation of both single-neuron and pairwise response statistics. Using a pair of model neurons, we demonstrate that the two models predict similar single-cell statistics. However, DSP and RG models have contradicting predictions on the joint statistics of spiking responses. To test the models against data, we build a population model to simulate stimulus change-related modulations in pairwise response statistics. We use single-unit data from the primary visual cortex (V1) of monkeys to show that while model predictions for variance are qualitatively similar to experimental data, only the RG model's predictions are compatible with joint statistics. These results suggest that models using Poisson-like variability might fail to capture important properties of response statistics. We argue that membrane potential-level modeling of stochasticity provides an efficient strategy to model correlations. NEW & NOTEWORTHY Neural variability and covariability are puzzling aspects of cortical computations. For efficient decoding and prediction, models of information encoding in neural populations hinge on an appropriate model of

  17. A comparison of take-off dynamics during three different spikes, block and counter-movement jump in female volleyball players.

    Science.gov (United States)

    Kabacinski, Jaroslae; Dworak, Lecholslaw B; Murawa, Michal; Ostarello, John; Rzepnicka, Agata; Maczynski, Jacek

    2016-12-01

    The purpose of the study was to compare the take-off dynamics in counter-movement jump (CMJ), volleyball block and spikes. Twelve professional female players, representing the highest volleyball league in Poland, participated in the laboratory tests. A force platform was used to record ground reaction force (GRF) during take-off phase in CMJ test, block from a run-up and spikes: front row attack, slide attack, back row attack. Vertical (v) GRF (peak: Rmax and integral mean: ), impulse of vGRF (J) and mechanical power (peak: Pmax and integral mean: ) were analyzed. Significant differences (P, J, Pmax, and ) were found between CMJ, block from a run-up and three different technique spikes. The highest values were recorded during take-off in the back row attack: peak vGRF (2.93±0.05 BW), integral mean vGRF (1.90±0.08 BW), impulse of vGRF (354±40 Ns), peak power (5320±918 W) and integral mean power (3604±683 W). Peak power (2608±217 W) and integral mean power (1417±94 W) were determined in CMJ test to evaluate the force-velocity capabilities of the players. In terms of GRF and the mechanical power, high level of dynamics in take-off influences positively the jumping height and significantly increases the effectiveness of attacks during spike of the ball over the block of the opponent.

  18. Fluorescence Spectra of Highlighter Inks

    Science.gov (United States)

    Birriel, Jennifer J.; King, Damon

    2018-01-01

    Fluorescence spectra excited by laser pointers have been the subject of several papers in "TPT". These papers all describe a fluorescence phenomenon in which the reflected laser light undergoes a change in color: this color change results from the combination of some partially reflected laser light and additional colors generated by…

  19. Classical Trajectories and Quantum Spectra

    Science.gov (United States)

    Mielnik, Bogdan; Reyes, Marco A.

    1996-01-01

    A classical model of the Schrodinger's wave packet is considered. The problem of finding the energy levels corresponds to a classical manipulation game. It leads to an approximate but non-perturbative method of finding the eigenvalues, exploring the bifurcations of classical trajectories. The role of squeezing turns out decisive in the generation of the discrete spectra.

  20. Explanation of earthquake response spectra

    OpenAIRE

    Douglas, John

    2017-01-01

    This is a set of five slides explaining how earthquake response spectra are derived from strong-motion records and simple models of structures and their purpose within seismic design and assessment. It dates from about 2002 and I have used it in various introductory lectures on engineering seismology.

  1. Voltage-spike analysis for a free-running parallel inverter

    Science.gov (United States)

    Lee, F. C. Y.; Wilson, T. G.

    1974-01-01

    Unwanted and sometimes damaging high-amplitude voltage spikes occur during each half cycle in many transistor saturable-core inverters at the moment when the core saturates and the transistors switch. The analysis shows that spikes are an intrinsic characteristic of certain types of inverters even with negligible leakage inductance and purely resistive load. The small but unavoidable after-saturation inductance of the saturable-core transformer plays an essential role in creating these undesired thigh-voltage spikes. State-plane analysis provides insight into the complex interaction between core and transistors, and shows the circuit parameters upon which the magnitude of these spikes depends.

  2. Multineuron spike train analysis with R-convolution linear combination kernel.

    Science.gov (United States)

    Tezuka, Taro

    2018-06-01

    A spike train kernel provides an effective way of decoding information represented by a spike train. Some spike train kernels have been extended to multineuron spike trains, which are simultaneously recorded spike trains obtained from multiple neurons. However, most of these multineuron extensions were carried out in a kernel-specific manner. In this paper, a general framework is proposed for extending any single-neuron spike train kernel to multineuron spike trains, based on the R-convolution kernel. Special subclasses of the proposed R-convolution linear combination kernel are explored. These subclasses have a smaller number of parameters and make optimization tractable when the size of data is limited. The proposed kernel was evaluated using Gaussian process regression for multineuron spike trains recorded from an animal brain. It was compared with the sum kernel and the population Spikernel, which are existing ways of decoding multineuron spike trains using kernels. The results showed that the proposed approach performs better than these kernels and also other commonly used neural decoding methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

  3. Aspects of Quantitation in Mass Spectrometry Imaging Investigated on Cryo-Sections of Spiked Tissue Homogenates

    DEFF Research Database (Denmark)

    Hansen, Heidi Toft; Janfelt, Christian

    2016-01-01

    for differences in tissue types in, for example, whole-body imaging, a set of tissue homogenates of different tissue types (lung, liver, kidney, heart, and brain) from rabbit was spiked to the same concentration with the drug amitriptyline and imaged in the same experiment using isotope labeled amitriptyline......Internal standards have been introduced in quantitative mass spectrometry imaging in order to compensate for differences in intensities throughout an image caused by, for example, difference in ion suppression or analyte extraction efficiency. To test how well the internal standards compensate...... for these results range approximately within a factor of 3 (but for other compounds in other tissues could be higher), underscore the importance of preparing the standard curve in the same matrix as the unknown sample whenever possible. In, for example, whole-body imaging where a diversity of tissue types...

  4. FPGA IMPLEMENTATION OF ADAPTIVE INTEGRATED SPIKING NEURAL NETWORK FOR EFFICIENT IMAGE RECOGNITION SYSTEM

    Directory of Open Access Journals (Sweden)

    T. Pasupathi

    2014-05-01

    Full Text Available Image recognition is a technology which can be used in various applications such as medical image recognition systems, security, defense video tracking, and factory automation. In this paper we present a novel pipelined architecture of an adaptive integrated Artificial Neural Network for image recognition. In our proposed work we have combined the feature of spiking neuron concept with ANN to achieve the efficient architecture for image recognition. The set of training images are trained by ANN and target output has been identified. Real time videos are captured and then converted into frames for testing purpose and the image were recognized. The machine can operate at up to 40 frames/sec using images acquired from the camera. The system has been implemented on XC3S400 SPARTAN-3 Field Programmable Gate Arrays.

  5. Non-Euclidean properties of spike train metric spaces.

    Science.gov (United States)

    Aronov, Dmitriy; Victor, Jonathan D

    2004-06-01

    Quantifying the dissimilarity (or distance) between two sequences is essential to the study of action potential (spike) trains in neuroscience and genetic sequences in molecular biology. In neuroscience, traditional methods for sequence comparisons rely on techniques appropriate for multivariate data, which typically assume that the space of sequences is intrinsically Euclidean. More recently, metrics that do not make this assumption have been introduced for comparison of neural activity patterns. These metrics have a formal resemblance to those used in the comparison of genetic sequences. Yet the relationship between such metrics and the traditional Euclidean distances has remained unclear. We show, both analytically and computationally, that the geometries associated with metric spaces of event sequences are intrinsically non-Euclidean. Our results demonstrate that metric spaces enrich the study of neural activity patterns, since accounting for perceptual spaces requires a non-Euclidean geometry.

  6. Variational and perturbative schemes for a spiked harmonic oscillator

    International Nuclear Information System (INIS)

    Aguilera-Navarro, V.C.; Estevez, G.A.; Guardiola, R.

    1989-01-01

    A variational analysis of the spiked harmonic-oscillator Hamiltonian operator -d 2 /dx 2 + x 2 + l(l+1)/x 2 + λ |x| -α , where α is a real positive parameter, is reported in this work. The formalism makes use of the functional space spanned by the solutions of the Schroedinger equation for the linear harmonic-oscillator Hamiltonian supplemented by a Dirichlet boundary condition, and a standard procedure for diagonalizing symmetric matrices. The eigenvalues obtained by increasing the dimension of the basis set provides accurate approximations for the ground-state energy of the model system, valid for positive and relatively large values of the coupling parameter λ. Additionally, a large-coupling pertubative-expansion is carried out and the contributions up to fourth order to the ground-state energy are explicitly evaluated. Numerical results are compared for the special case α=5/2. (author) [pt

  7. A Model of Fast Hebbian Spike Latency Normalization

    Directory of Open Access Journals (Sweden)

    Hafsteinn Einarsson

    2017-05-01

    Full Text Available Hebbian changes of excitatory synapses are driven by and enhance correlations between pre- and postsynaptic neuronal activations, forming a positive feedback loop that can lead to instability in simulated neural networks. Because Hebbian learning may occur on time scales of seconds to minutes, it is conjectured that some form of fast stabilization of neural firing is necessary to avoid runaway of excitation, but both the theoretical underpinning and the biological implementation for such homeostatic mechanism are to be fully investigated. Supported by analytical and computational arguments, we show that a Hebbian spike-timing-dependent metaplasticity rule, accounts for inherently-stable, quick tuning of the total input weight of a single neuron in the general scenario of asynchronous neural firing characterized by UP and DOWN states of activity.

  8. Brian: a simulator for spiking neural networks in Python

    Directory of Open Access Journals (Sweden)

    Dan F M Goodman

    2008-11-01

    Full Text Available Brian is a new simulator for spiking neural networks, written in Python (http://brian.di.ens.fr. It is an intuitive and highly flexible tool for rapidly developing new models, especially networks of single-compartment neurons. In addition to using standard types of neuron models, users can define models by writing arbitrary differential equations in ordinary mathematical notation. Python scientific libraries can also be used for defining models and analysing data. Vectorisation techniques allow efficient simulations despite the overheads of an interpreted language. Brian will be especially valuable for working on non-standard neuron models not easily covered by existing software, and as an alternative to using Matlab or C for simulations. With its easy and intuitive syntax, Brian is also very well suited for teaching computational neuroscience.

  9. Spike-Based Bayesian-Hebbian Learning of Temporal Sequences

    DEFF Research Database (Denmark)

    Tully, Philip J; Lindén, Henrik; Hennig, Matthias H

    2016-01-01

    and speed of sequence replay depends on a confluence of biophysically relevant parameters including stimulus duration, level of background noise, ratio of synaptic currents, and strengths of short-term depression and adaptation. Moreover, sequence elements are shown to flexibly participate multiple times......Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed...... in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN) learning rule. We find that the formation of distributed memories, embodied by increased periods...

  10. A self-resetting spiking phase-change neuron.

    Science.gov (United States)

    Cobley, R A; Hayat, H; Wright, C D

    2018-05-11

    Neuromorphic, or brain-inspired, computing applications of phase-change devices have to date concentrated primarily on the implementation of phase-change synapses. However, the so-called accumulation mode of operation inherent in phase-change materials and devices can also be used to mimic the integrative properties of a biological neuron. Here we demonstrate, using physical modelling of nanoscale devices and SPICE modelling of associated circuits, that a single phase-change memory cell integrated into a comparator type circuit can deliver a basic hardware mimic of an integrate-and-fire spiking neuron with self-resetting capabilities. Such phase-change neurons, in combination with phase-change synapses, can potentially open a new route for the realisation of all-phase-change neuromorphic computing.

  11. Double spike with isotope pattern deconvolution for mercury speciation

    International Nuclear Information System (INIS)

    Castillo, A.; Rodriguez-Gonzalez, P.; Centineo, G.; Roig-Navarro, A.F.; Garcia Alonso, J.I.

    2009-01-01

    Full text: A double-spiking approach, based on an isotope pattern deconvolution numerical methodology, has been developed and applied for the accurate and simultaneous determination of inorganic mercury (IHg) and methylmercury (MeHg). Isotopically enriched mercury species ( 199 IHg and 201 MeHg) are added before sample preparation to quantify the extent of methylation and demethylation processes. Focused microwave digestion was evaluated to perform the quantitative extraction of such compounds from solid matrices of environmental interest. Satisfactory results were obtained in different certificated reference materials (dogfish liver DOLT-4 and tuna fish CRM-464) both by using GC-ICPMS and GC-MS, demonstrating the suitability of the proposed analytical method. (author)

  12. A simultaneous comparison of acupuncture needle and insulated needle sphenoidal electrodes for detection of anterior temporal spikes.

    Science.gov (United States)

    Chu, N S

    1992-01-01

    Uninsulated acupuncture needles have been used as sphenoidal electrodes, but the issue of insulation has not been adequately addressed. In this report, acupuncture needles and insulated needle sphenoidal electrodes were simultaneously used to compare the rate of spike detection, spike amplitude and distribution of maximal spikes from eight spike foci in seven patients with temporal lobe epilepsy. When compared to the insulated needle electrode, the acupuncture needle electrode was equally effective in spike detection, but spike amplitudes tended to be smaller and maximal spikes were less frequently encountered. Thus, insulation has an influence on the spikes recorded by the acupuncture needle sphenoidal electrode. However, the overall effect appears to be not sufficiently different from the insulated needle electrode for the purpose of detecting anterior temporal spikes in outpatient EEG recordings for the diagnosis of temporal lobe epilepsy.

  13. Spike-timing dependent plasticity and the cognitive map

    Directory of Open Access Journals (Sweden)

    Daniel eBush

    2010-10-01

    Full Text Available Since the discovery of place cells – single pyramidal neurons that encode spatial location – it has been hypothesised that the hippocampus may act as a cognitive map of known environments. This putative function has been extensively modelled using auto-associative networks, which utilise rate-coded synaptic plasticity rules in order to generate strong bi-directional connections between concurrently active place cells that encode for neighbouring place fields. However, empirical studies using hippocampal cultures have demonstrated that the magnitude and direction of changes in synaptic strength can also be dictated by the relative timing of pre- and post- synaptic firing according to a spike-timing dependent plasticity (STDP rule. Furthermore, electrophysiology studies have identified persistent ‘theta-coded’ temporal correlations in place cell activity in vivo, characterised by phase precession of firing as the corresponding place field is traversed. It is not yet clear if STDP and theta-coded neural dynamics are compatible with cognitive map theory and previous rate-coded models of spatial learning in the hippocampus. Here, we demonstrate that an STDP rule based on empirical data obtained from the hippocampus can mediate rate-coded Hebbian learning when pre- and post- synaptic activity is stochastic and has no persistent sequence bias. We subsequently demonstrate that a spiking recurrent neural network that utilises this STDP rule, alongside theta-coded neural activity, allows the rapid development of a cognitive map during directed or random exploration of an environment of overlapping place fields. Hence, we establish that STDP and phase precession are compatible with rate-coded models of cognitive map development.

  14. Analog Memristive Synapse in Spiking Networks Implementing Unsupervised Learning

    Science.gov (United States)

    Covi, Erika; Brivio, Stefano; Serb, Alexander; Prodromakis, Themis; Fanciulli, Marco; Spiga, Sabina

    2016-01-01

    Emerging brain-inspired architectures call for devices that can emulate the functionality of biological synapses in order to implement new efficient computational schemes able to solve ill-posed problems. Various devices and solutions are still under investigation and, in this respect, a challenge is opened to the researchers in the field. Indeed, the optimal candidate is a device able to reproduce the complete functionality of a synapse, i.e., the typical synaptic process underlying learning in biological systems (activity-dependent synaptic plasticity). This implies a device able to change its resistance (synaptic strength, or weight) upon proper electrical stimuli (synaptic activity) and showing several stable resistive states throughout its dynamic range (analog behavior). Moreover, it should be able to perform spike timing dependent plasticity (STDP), an associative homosynaptic plasticity learning rule based on the delay time between the two firing neurons the synapse is connected to. This rule is a fundamental learning protocol in state-of-art networks, because it allows unsupervised learning. Notwithstanding this fact, STDP-based unsupervised learning has been proposed several times mainly for binary synapses rather than multilevel synapses composed of many binary memristors. This paper proposes an HfO2-based analog memristor as a synaptic element which performs STDP within a small spiking neuromorphic network operating unsupervised learning for character recognition. The trained network is able to recognize five characters even in case incomplete or noisy images are displayed and it is robust to a device-to-device variability of up to ±30%. PMID:27826226

  15. Relationship of Sphincter of Oddi Spike Bursts to Gastrointestinal Myoelectric Activity in Conscious Opossums

    Science.gov (United States)

    Honda, Ryuichi; Toouli, James; Dodds, Wylie J.; Sarna, Sushil; Hogan, Walter J.; Itoh, Zen

    1982-01-01

    The oppossum sphincter of Oddi (SO) exhibits peristaltic spike bursts with accompanying contraction waves that originate proximally in the sphincter of Oddi and propagate toward the duodenum. In this study we recorded myoelectrical activity of the opossum SO and upper gastrointestinal tract in six conscious animals using chronically implanted electrodes. Biopolar electrodes were implanted in the gastric antrum, duodenum, SO segment, jejunum, and ileum. During fasting the frequency of SO spike bursts, scored as number per minute, showed a cyclic pattern consisting of four phases (A to D). Phase A had a low spike burst frequency of ∼2/min that lasted ∼20 min. In phase B, the spike burst frequency increased progressively during a 40-45 min interval culminating in a short interval of phase C activity characterized by a maximal spike burst frequency of ∼5/min. During phase D, the spike bursts decreased over 15 min to merge with the low frequency of phase A and the cycle repeated. Cycle length of the interdigestive SO cycle, 87±11 SD min, was virtually identical with that of the interdigestive migrating myoelectric complex (MMC) of the upper gastrointestinal tract. The onset of phase C activity in the SO began 1-2 min before phase III of the MMC activity in the duodenum. Feeding abolished the cyclic pattern of spike burst activity in the SO as well as in the upper gastrointestinal tract. After feeding the SO spike bursts occurred at a frequency of 5-6/min for at least 3 h. We conclude that: (a) During fasting, the oppossum SO exhibits cyclic changes in its spike burst frequency; (b) Maximal spike burst frequency of the SO occurs virtually concurrent with passage of phase III MMC activity through the duodenum and; (c) Feeding abolishes the interdigestive cyclic spike burst pattern of the SO as well as that of the gastrointestinal tract. PMID:7076847

  16. Extracting information in spike time patterns with wavelets and information theory.

    Science.gov (United States)

    Lopes-dos-Santos, Vítor; Panzeri, Stefano; Kayser, Christoph; Diamond, Mathew E; Quian Quiroga, Rodrigo

    2015-02-01

    We present a new method to assess the information carried by temporal patterns in spike trains. The method first performs a wavelet decomposition of the spike trains, then uses Shannon information to select a subset of coefficients carrying information, and finally assesses timing information in terms of decoding performance: the ability to identify the presented stimuli from spike train patterns. We show that the method allows: 1) a robust assessment of the information carried by spike time patterns even when this is distributed across multiple time scales and time points; 2) an effective denoising of the raster plots that improves the estimate of stimulus tuning of spike trains; and 3) an assessment of the information carried by temporally coordinated spikes across neurons. Using simulated data, we demonstrate that the Wavelet-Information (WI) method performs better and is more robust to spike time-jitter, background noise, and sample size than well-established approaches, such as principal component analysis, direct estimates of information from digitized spike trains, or a metric-based method. Furthermore, when applied to real spike trains from monkey auditory cortex and from rat barrel cortex, the WI method allows extracting larger amounts of spike timing information. Importantly, the fact that the WI method incorporates multiple time scales makes it robust to the choice of partly arbitrary parameters such as temporal resolution, response window length, number of response features considered, and the number of available trials. These results highlight the potential of the proposed method for accurate and objective assessments of how spike timing encodes information. Copyright © 2015 the American Physiological Society.

  17. Channel noise effects on first spike latency of a stochastic Hodgkin-Huxley neuron

    Science.gov (United States)

    Maisel, Brenton; Lindenberg, Katja

    2017-02-01

    While it is widely accepted that information is encoded in neurons via action potentials or spikes, it is far less understood what specific features of spiking contain encoded information. Experimental evidence has suggested that the timing of the first spike may be an energy-efficient coding mechanism that contains more neural information than subsequent spikes. Therefore, the biophysical features of neurons that underlie response latency are of considerable interest. Here we examine the effects of channel noise on the first spike latency of a Hodgkin-Huxley neuron receiving random input from many other neurons. Because the principal feature of a Hodgkin-Huxley neuron is the stochastic opening and closing of channels, the fluctuations in the number of open channels lead to fluctuations in the membrane voltage and modify the timing of the first spike. Our results show that when a neuron has a larger number of channels, (i) the occurrence of the first spike is delayed and (ii) the variation in the first spike timing is greater. We also show that the mean, median, and interquartile range of first spike latency can be accurately predicted from a simple linear regression by knowing only the number of channels in the neuron and the rate at which presynaptic neurons fire, but the standard deviation (i.e., neuronal jitter) cannot be predicted using only this information. We then compare our results to another commonly used stochastic Hodgkin-Huxley model and show that the more commonly used model overstates the first spike latency but can predict the standard deviation of first spike latencies accurately. We end by suggesting a more suitable definition for the neuronal jitter based upon our simulations and comparison of the two models.

  18. Learning of Precise Spike Times with Homeostatic Membrane Potential Dependent Synaptic Plasticity.

    Directory of Open Access Journals (Sweden)

    Christian Albers

    Full Text Available Precise spatio-temporal patterns of neuronal action potentials underly e.g. sensory representations and control of muscle activities. However, it is not known how the synaptic efficacies in the neuronal networks of the brain adapt such that they can reliably generate spikes at specific points in time. Existing activity-dependent plasticity rules like Spike-Timing-Dependent Plasticity are agnostic to the goal of learning spike times. On the other hand, the existing formal and supervised learning algorithms perform a temporally precise comparison of projected activity with the target, but there is no known biologically plausible implementation of this comparison. Here, we propose a simple and local unsupervised synaptic plasticity mechanism that is derived from the requirement of a balanced membrane potential. Since the relevant signal for synaptic change is the postsynaptic voltage rather than spike times, we call the plasticity rule Membrane Potential Dependent Plasticity (MPDP. Combining our plasticity mechanism with spike after-hyperpolarization causes a sensitivity of synaptic change to pre- and postsynaptic spike times which can reproduce Hebbian spike timing dependent plasticity for inhibitory synapses as was found in experiments. In addition, the sensitivity of MPDP to the time course of the voltage when generating a spike allows MPDP to distinguish between weak (spurious and strong (teacher spikes, which therefore provides a neuronal basis for the comparison of actual and target activity. For spatio-temporal input spike patterns our conceptually simple plasticity rule achieves a surprisingly high storage capacity for spike associations. The sensitivity of the MPDP to the subthreshold membrane potential during training allows robust memory retrieval after learning even in the presence of activity corrupted by noise. We propose that MPDP represents a biophysically plausible mechanism to learn temporal target activity patterns.

  19. Learning of Precise Spike Times with Homeostatic Membrane Potential Dependent Synaptic Plasticity.

    Science.gov (United States)

    Albers, Christian; Westkott, Maren; Pawelzik, Klaus

    2016-01-01

    Precise spatio-temporal patterns of neuronal action potentials underly e.g. sensory representations and control of muscle activities. However, it is not known how the synaptic efficacies in the neuronal networks of the brain adapt such that they can reliably generate spikes at specific points in time. Existing activity-dependent plasticity rules like Spike-Timing-Dependent Plasticity are agnostic to the goal of learning spike times. On the other hand, the existing formal and supervised learning algorithms perform a temporally precise comparison of projected activity with the target, but there is no known biologically plausible implementation of this comparison. Here, we propose a simple and local unsupervised synaptic plasticity mechanism that is derived from the requirement of a balanced membrane potential. Since the relevant signal for synaptic change is the postsynaptic voltage rather than spike times, we call the plasticity rule Membrane Potential Dependent Plasticity (MPDP). Combining our plasticity mechanism with spike after-hyperpolarization causes a sensitivity of synaptic change to pre- and postsynaptic spike times which can reproduce Hebbian spike timing dependent plasticity for inhibitory synapses as was found in experiments. In addition, the sensitivity of MPDP to the time course of the voltage when generating a spike allows MPDP to distinguish between weak (spurious) and strong (teacher) spikes, which therefore provides a neuronal basis for the comparison of actual and target activity. For spatio-temporal input spike patterns our conceptually simple plasticity rule achieves a surprisingly high storage capacity for spike associations. The sensitivity of the MPDP to the subthreshold membrane potential during training allows robust memory retrieval after learning even in the presence of activity corrupted by noise. We propose that MPDP represents a biophysically plausible mechanism to learn temporal target activity patterns.

  20. EFFECTS OF DIFFERENT GROWING CONDITIONS ON THE MORPHOLOGICAL FEATURES OF THE SPIKE OF HEXAPLOID TRITICALE

    Directory of Open Access Journals (Sweden)

    K. U. Kurkiev

    2016-01-01

    Full Text Available Aim. The aim is to study the effect of different environmental conditions on the morphological traits of the spike of hexaploid triticale varieties.Methods. We analyzed 507 samples of triticale of various eco-geographical origins, in different years of study and at different seeding times. To investigate the influence of environmental conditions on the phenotypic expression of the studied traits we held a comparative analysis of the spike of two years and, in addition, of spring triticale during winter and spring crops. Analysis on the features was carried out on the main spikes. We studied the following morphological characteristics of the spike: length, number of spikelets and density.Results and discussion. The study of differences in individual variety samples showed that more than 60% triticale samples had significant differences in the length of the spike, depending on the weather conditions of the year – with the winter crops number of spikelets per spike was significantly higher than with the spring crops. A comparative analysis of the impact of the weather conditions of the year on triticale showed that significant differences in the density of the spike were observed in less than 30%.Conclusion. Study of the influence of conditions of the year and sowing dates on the main features of the spike of triticale showed that the density of the spike is the least affected by the external environment. The length of the spikes and the number of spikelets per spike differed significantly when growing in a various conditions.

  1. Learning of Precise Spike Times with Homeostatic Membrane Potential Dependent Synaptic Plasticity

    Science.gov (United States)

    Albers, Christian; Westkott, Maren; Pawelzik, Klaus

    2016-01-01

    Precise spatio-temporal patterns of neuronal action potentials underly e.g. sensory representations and control of muscle activities. However, it is not known how the synaptic efficacies in the neuronal networks of the brain adapt such that they can reliably generate spikes at specific points in time. Existing activity-dependent plasticity rules like Spike-Timing-Dependent Plasticity are agnostic to the goal of learning spike times. On the other hand, the existing formal and supervised learning algorithms perform a temporally precise comparison of projected activity with the target, but there is no known biologically plausible implementation of this comparison. Here, we propose a simple and local unsupervised synaptic plasticity mechanism that is derived from the requirement of a balanced membrane potential. Since the relevant signal for synaptic change is the postsynaptic voltage rather than spike times, we call the plasticity rule Membrane Potential Dependent Plasticity (MPDP). Combining our plasticity mechanism with spike after-hyperpolarization causes a sensitivity of synaptic change to pre- and postsynaptic spike times which can reproduce Hebbian spike timing dependent plasticity for inhibitory synapses as was found in experiments. In addition, the sensitivity of MPDP to the time course of the voltage when generating a spike allows MPDP to distinguish between weak (spurious) and strong (teacher) spikes, which therefore provides a neuronal basis for the comparison of actual and target activity. For spatio-temporal input spike patterns our conceptually simple plasticity rule achieves a surprisingly high storage capacity for spike associations. The sensitivity of the MPDP to the subthreshold membrane potential during training allows robust memory retrieval after learning even in the presence of activity corrupted by noise. We propose that MPDP represents a biophysically plausible mechanism to learn temporal target activity patterns. PMID:26900845

  2. Far-infrared spectra of lateral quantum dot molecules

    Science.gov (United States)

    Helle, M.; Harju, A.; Nieminen, R. M.

    2006-02-01

    We study effects of electron electron interactions and confinement potential on the magneto-optical absorption spectrum in the far-infrared (FIR) range of lateral quantum dot molecules (QDMs). We calculate FIR spectra for three different QDM confinement potentials. We use an accurate exact diagonalization technique for two interacting electrons and calculate dipole transitions between two-body levels with perturbation theory. We conclude that the two-electron FIR spectra directly reflect the symmetry of the confinement potential and interactions cause only small shifts in the spectra. These predictions could be tested in experiments with non-parabolic quantum dots (QDs) by changing the number of confined electrons. We also calculate FIR spectra for up to six non-interacting electrons and observe some additional features in the spectrum.

  3. Cross-correlation analysis of Ge/Li/ spectra

    International Nuclear Information System (INIS)

    MacDonald, R.; Robertson, A.; Kennett, T.J.; Prestwich, W.V.

    1974-01-01

    A sensitive technique is proposed for activation analysis using cross-correlation and improved spectral orthogonality achieved through use of a rectangular zero area digital filter. To test the accuracy and reliability of the cross-correlation procedure five spectra obtained with a Ge/Li detector were combined in different proportions. Gaussian distributed statistics were then added to the composite spectra by means of a pseudo-random number generator. The basis spectra used were 76 As, 82 Br, 72 Ga, 77 Ge, and room background. In general, when the basis spectra were combined in roughly comparable proportions the accuracy of the techique proved to be excelent (>1%). However, of primary importance was the ability of the correlation technique to identify low intensity components in the presence of high intensity components. It was found that the detection threshold for Ge, for example, was not reached until the Ge content in the unfiltered spectrum was <0.16%. (T.G.)

  4. Reconstruction of neutron spectra through neural networks

    International Nuclear Information System (INIS)

    Vega C, H.R.; Hernandez D, V.M.; Manzanares A, E.

    2003-01-01

    A neural network has been used to reconstruct the neutron spectra starting from the counting rates of the detectors of the Bonner sphere spectrophotometric system. A group of 56 neutron spectra was selected to calculate the counting rates that would produce in a Bonner sphere system, with these data and the spectra it was trained the neural network. To prove the performance of the net, 12 spectra were used, 6 were taken of the group used for the training, 3 were obtained of mathematical functions and those other 3 correspond to real spectra. When comparing the original spectra of those reconstructed by the net we find that our net has a poor performance when reconstructing monoenergetic spectra, this attributes it to those characteristic of the spectra used for the training of the neural network, however for the other groups of spectra the results of the net are appropriate with the prospective ones. (Author)

  5. Neuro-Inspired Spike-Based Motion: From Dynamic Vision Sensor to Robot Motor Open-Loop Control through Spike-VITE

    Directory of Open Access Journals (Sweden)

    Fernando Perez-Peña

    2013-11-01

    Full Text Available In this paper we present a complete spike-based architecture: from a Dynamic Vision Sensor (retina to a stereo head robotic platform. The aim of this research is to reproduce intended movements performed by humans taking into account as many features as possible from the biological point of view. This paper fills the gap between current spike silicon sensors and robotic actuators by applying a spike processing strategy to the data flows in real time. The architecture is divided into layers: the retina, visual information processing, the trajectory generator layer which uses a neuroinspired algorithm (SVITE that can be replicated into as many times as DoF the robot has; and finally the actuation layer to supply the spikes to the robot (using PFM. All the layers do their tasks in a spike-processing mode, and they communicate each other through the neuro-inspired AER protocol. The open-loop controller is implemented on FPGA using AER interfaces developed by RTC Lab. Experimental results reveal the viability of this spike-based controller. Two main advantages are: low hardware resources (2% of a Xilinx Spartan 6 and power requirements (3.4 W to control a robot with a high number of DoF (up to 100 for a Xilinx Spartan 6. It also evidences the suitable use of AER as a communication protocol between processing and actuation.

  6. Inclusive spectra in hard processes

    International Nuclear Information System (INIS)

    Kiselev, A.V.; Petrov, V.A.

    1985-01-01

    It is shown that the unified mechanism of hadronization in hard processes results in universality of inclusive spectra of soft hadrons. Inclusive spectrum of hadrons in energy share in deep-inelastic lepton-hadron scattering is calculated. The spectrum obtained is calculated with analogous distribution in e + e - annihilation. It is noted that inclusive spectrum of soft hadrons in hard processes is described by a universal function

  7. Learning of spiking networks with different forms of long-term synaptic plasticity

    International Nuclear Information System (INIS)

    Vlasov, D.S.; Sboev, A.G.; Serenko, A.V.; Rybka, R.B.; Moloshnikov, I.A.

    2016-01-01

    The possibility of modeling the learning process based on different forms of spike timing-dependent plasticity (STDP) has been studied. It has been shown that the learnability depends on the choice of the spike pairing scheme in the STDP rule and the type of the input signal used during learning [ru

  8. The coronavirus spike protein : mechanisms of membrane fusion and virion incorporation

    NARCIS (Netherlands)

    Bosch, B.J.

    2004-01-01

    The coronavirus spike protein is a membrane-anchored glycoprotein responsible for virus-cell attachment and membrane fusion, prerequisites for a successful virus infection. In this thesis, two aspects are described regarding the molecular biology of the coronavirus spike protein: its membrane fusion

  9. Spatiotemporal Spike Coding of Behavioral Adaptation in the Dorsal Anterior Cingulate Cortex.

    Directory of Open Access Journals (Sweden)

    Laureline Logiaco

    2015-08-01

    Full Text Available The frontal cortex controls behavioral adaptation in environments governed by complex rules. Many studies have established the relevance of firing rate modulation after informative events signaling whether and how to update the behavioral policy. However, whether the spatiotemporal features of these neuronal activities contribute to encoding imminent behavioral updates remains unclear. We investigated this issue in the dorsal anterior cingulate cortex (dACC of monkeys while they adapted their behavior based on their memory of feedback from past choices. We analyzed spike trains of both single units and pairs of simultaneously recorded neurons using an algorithm that emulates different biologically plausible decoding circuits. This method permits the assessment of the performance of both spike-count and spike-timing sensitive decoders. In response to the feedback, single neurons emitted stereotypical spike trains whose temporal structure identified informative events with higher accuracy than mere spike count. The optimal decoding time scale was in the range of 70-200 ms, which is significantly shorter than the memory time scale required by the behavioral task. Importantly, the temporal spiking patterns of single units were predictive of the monkeys' behavioral response time. Furthermore, some features of these spiking patterns often varied between jointly recorded neurons. All together, our results suggest that dACC drives behavioral adaptation through complex spatiotemporal spike coding. They also indicate that downstream networks, which decode dACC feedback signals, are unlikely to act as mere neural integrators.

  10. Characterizing neural activities evoked by manual acupuncture through spiking irregularity measures

    International Nuclear Information System (INIS)

    Xue Ming; Wang Jiang; Deng Bin; Wei Xi-Le; Yu Hai-Tao; Chen Ying-Yuan

    2013-01-01

    The neural system characterizes information in external stimulations by different spiking patterns. In order to examine how neural spiking patterns are related to acupuncture manipulations, experiments are designed in such a way that different types of manual acupuncture (MA) manipulations are taken at the ‘Zusanli’ point of experimental rats, and the induced electrical signals in the spinal dorsal root ganglion are detected and recorded. The interspike interval (ISI) statistical histogram is fitted by the gamma distribution, which has two parameters: one is the time-dependent firing rate and the other is a shape parameter characterizing the spiking irregularities. The shape parameter is the measure of spiking irregularities and can be used to identify the type of MA manipulations. The coefficient of variation is mostly used to measure the spike time irregularity, but it overestimates the irregularity in the case of pronounced firing rate changes. However, experiments show that each acupuncture manipulation will lead to changes in the firing rate. So we combine four relatively rate-independent measures to study the irregularity of spike trains evoked by different types of MA manipulations. Results suggest that the MA manipulations possess unique spiking statistics and characteristics and can be distinguished according to the spiking irregularity measures. These studies have offered new insights into the coding processes and information transfer of acupuncture. (interdisciplinary physics and related areas of science and technology)

  11. Spike sorting of heterogeneous neuron types by multimodality-weighted PCA and explicit robust variational Bayes

    Directory of Open Access Journals (Sweden)

    Takashi eTakekawa

    2012-03-01

    Full Text Available This study introduces a new spike sorting method that classifies spike waveforms from multiunit recordings into spike trains of individual neurons. In particular, we develop a method to sort a spike mixture generated by a heterogeneous neural population. Such a spike sorting has a significant practical value, but was previously difficult. The method combines a feature extraction method, which we may term multimodality-weighted principal component analysis (mPCA, and a clustering method by variational Bayes for Student’s t mixture model (SVB. The performance of the proposed method was compared with that of other conventional methods for simulated and experimental data sets. We found that the mPCA efficiently extracts highly informative features as clusters clearly separable in a relatively low-dimensional feature space. The SVB was implemented explicitly without relying on Maximum-A-Posterior (MAP inference for the degree of freedom parameters. The explicit SVB is faster than the conventional SVB derived with MAP inference and works more reliably over various data sets that include spiking patterns difficult to sort. For instance, spikes of a single bursting neuron may be separated incorrectly into multiple clusters, whereas those of a sparsely firing neuron tend to be merged into clusters for other neurons. Our method showed significantly improved performance in spike sorting of these difficult neurons. A parallelized implementation of the proposed algorithm (EToS version 3 is available as open-source code at http://etos.sourceforge.net/.

  12. Mutations in GRIN2A cause idiopathic focal epilepsy with rolandic spikes

    DEFF Research Database (Denmark)

    Lemke, Johannes R; Lal, Dennis; Reinthaler, Eva M

    2013-01-01

    Idiopathic focal epilepsy (IFE) with rolandic spikes is the most common childhood epilepsy, comprising a phenotypic spectrum from rolandic epilepsy (also benign epilepsy with centrotemporal spikes, BECTS) to atypical benign partial epilepsy (ABPE), Landau-Kleffner syndrome (LKS) and epileptic enc...

  13. Conduction Delay Learning Model for Unsupervised and Supervised Classification of Spatio-Temporal Spike Patterns.

    Science.gov (United States)

    Matsubara, Takashi

    2017-01-01

    Precise spike timing is considered to play a fundamental role in communications and signal processing in biological neural networks. Understanding the mechanism of spike timing adjustment would deepen our understanding of biological systems and enable advanced engineering applications such as efficient computational architectures. However, the biological mechanisms that adjust and maintain spike timing remain unclear. Existing algorithms adopt a supervised approach, which adjusts the axonal conduction delay and synaptic efficacy until the spike timings approximate the desired timings. This study proposes a spike timing-dependent learning model that adjusts the axonal conduction delay and synaptic efficacy in both unsupervised and supervised manners. The proposed learning algorithm approximates the Expectation-Maximization algorithm, and classifies the input data encoded into spatio-temporal spike patterns. Even in the supervised classification, the algorithm requires no external spikes indicating the desired spike timings unlike existing algorithms. Furthermore, because the algorithm is consistent with biological models and hypotheses found in existing biological studies, it could capture the mechanism underlying biological delay learning.

  14. Ictal source imaging and electroclinical correlation in self-limited epilepsy with centrotemporal spikes

    DEFF Research Database (Denmark)

    Alving, Jørgen; Fabricius, Martin; Rosenzweig, Ivana

    2017-01-01

    PURPOSE: To elucidate the localization of ictal EEG activity, and correlate it to semiological features in self-limited epilepsy with centrotemporal spikes (formerly called "benign epilepsy with centrotemporal spikes"). METHODS: We have performed ictal electric source imaging, and we analysed...

  15. New explicit spike solution -- non-local component of the generalized Mixmaster attractor

    OpenAIRE

    Lim, Woei Chet

    2007-01-01

    By applying a standard solution-generating transformation to an arbitrary vacuum Bianchi type II solution, one generates a new solution with spikes commonly observed in numerical simulations. It is conjectured that the spike solution is part of the generalized Mixmaster attractor.

  16. Remifentanil-induced spike activity as a diagnostic tool in epilepsy surgery

    DEFF Research Database (Denmark)

    Grønlykke, L; Knudsen, M L; Høgenhaven, H

    2008-01-01

    To assess the value of remifentanil in intraoperative evaluation of spike activity in patients undergoing surgery for mesial temporal lobe epilepsy (MTLE).......To assess the value of remifentanil in intraoperative evaluation of spike activity in patients undergoing surgery for mesial temporal lobe epilepsy (MTLE)....

  17. Regulation of granule cell excitability by a low-threshold calcium spike in turtle olfactory bulb

    DEFF Research Database (Denmark)

    Pinato, Giulietta; Midtgaard, Jens

    2003-01-01

    Granule cells excitability in the turtle olfactory bulb was analyzed using whole cell recordings in current- and voltage-clamp mode. Low-threshold spikes (LTSs) were evoked at potentials that are subthreshold for Na spikes in normal medium. The LTSs were evoked from rest, but hyperpolarization...

  18. VARIABILITY OF NUMBER OF KERNELS PER SPIKE IN WHEAT CULTIVARS (Triticum aestivum L.

    Directory of Open Access Journals (Sweden)

    Desimir KNEZEVIC

    2012-09-01

    Full Text Available In this paper was analyzed number of kernels per spike in 20 genetically divergent wheat cultivars originated from different breeding centers in Serbia. Investigation conducted during two seasons which characterized different climatic condition. For analysis used samples of 60 wheat plants (20 plants in 3 replications which were harvested in full maturity stage. The differences in average values for number of kernels per spike in studied cultivars were determined. The variability of number of kernels per spike was established. In average, number of kernels per spike for all cultivars was higher in second year 72.22 than in first experimental year 68.73. The highest number of kernels/spike in both year expressed Tanjugovka cultivar and the lowest Yugoslavia cultivar. Average value of coefficientvariation for all cultivars varied from 14.19 in first year to 12.92 in second year. Average number of kernels per spike for both year of growing, varied from 54.56 in cultivar Yugoslavia to 77.83 in cultivar Tanjugovka. Significant differences for number of kernels/spike were found among cultivars in both years as well between years. Heritability in wide sense for number of kernels/spike was 79.13%.

  19. Spike detection from noisy neural data in linear-probe recordings.

    Science.gov (United States)

    Takekawa, Takashi; Ota, Keisuke; Murayama, Masanori; Fukai, Tomoki

    2014-06-01

    Simultaneous recordings of multiple neuron activities with multi-channel extracellular electrodes are widely used for studying information processing by the brain's neural circuits. In this method, the recorded signals containing the spike events of a number of adjacent or distant neurons must be correctly sorted into spike trains of individual neurons, and a variety of methods have been proposed for this spike sorting. However, spike sorting is computationally difficult because the recorded signals are often contaminated by biological noise. Here, we propose a novel method for spike detection, which is the first stage of spike sorting and hence crucially determines overall sorting performance. Our method utilizes a model of extracellular recording data that takes into account variations in spike waveforms, such as the widths and amplitudes of spikes, by detecting the peaks of band-pass-filtered data. We show that the new method significantly improves the cost-performance of multi-channel electrode recordings by increasing the number of cleanly sorted neurons. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  20. Conduction Delay Learning Model for Unsupervised and Supervised Classification of Spatio-Temporal Spike Patterns

    Directory of Open Access Journals (Sweden)

    Takashi Matsubara

    2017-11-01

    Full Text Available Precise spike timing is considered to play a fundamental role in communications and signal processing in biological neural networks. Understanding the mechanism of spike timing adjustment would deepen our understanding of biological systems and enable advanced engineering applications such as efficient computational architectures. However, the biological mechanisms that adjust and maintain spike timing remain unclear. Existing algorithms adopt a supervised approach, which adjusts the axonal conduction delay and synaptic efficacy until the spike timings approximate the desired timings. This study proposes a spike timing-dependent learning model that adjusts the axonal conduction delay and synaptic efficacy in both unsupervised and supervised manners. The proposed learning algorithm approximates the Expectation-Maximization algorithm, and classifies the input data encoded into spatio-temporal spike patterns. Even in the supervised classification, the algorithm requires no external spikes indicating the desired spike timings unlike existing algorithms. Furthermore, because the algorithm is consistent with biological models and hypotheses found in existing biological studies, it could capture the mechanism underlying biological delay learning.

  1. Neuronal Networks in Children with Continuous Spikes and Waves during Slow Sleep

    Science.gov (United States)

    Siniatchkin, Michael; Groening, Kristina; Moehring, Jan; Moeller, Friederike; Boor, Rainer; Brodbeck, Verena; Michel, Christoph M.; Rodionov, Roman; Lemieux, Louis; Stephani, Ulrich

    2010-01-01

    Epileptic encephalopathy with continuous spikes and waves during slow sleep is an age-related disorder characterized by the presence of interictal epileptiform discharges during at least greater than 85% of sleep and cognitive deficits associated with this electroencephalography pattern. The pathophysiological mechanisms of continuous spikes and…

  2. Calcium spikes and calcium plateaux evoked by differential polarization in dendrites of turtle motoneurones in vitro

    DEFF Research Database (Denmark)

    Hounsgaard, J; Kiehn, O

    1993-01-01

    The ability of dendrites in turtle motoneurones to support calcium spikes and calcium plateaux was investigated using differential polarization by applied electric fields. 2. Electric fields were generated by passing current through transverse slices of the turtle spinal cord between two plate......+ spikes and Ca2+ plateaux are present in dendrites of spinal motoneurones of the turtle....

  3. Immobilization of Cadmium in a Cd-Spiked Soil by Different Kinds of Amendments

    Directory of Open Access Journals (Sweden)

    Mahboub Saffari

    2015-07-01

    Full Text Available    Chemical stabilization of heavy metals is one of the soil remediation methods based on the application amendments to reduce mobility of heavy metals. A laboratory study was conducted to investigate the influence of different kinds of amendments on cadmium (Cd stabilization in a Cd-spiked soil. The amendments were municipal solid waste compost (MSWC, Coal fly ash (CFA, rice husk biochars prepared at 300°C (B300 and 600°C (B600, zero valent iron (Fe0 and zero valent manganese (Mn0. The Cd-spiked soils were separately incubated with selected amendments at the rates of 2 and 5% (W/W for 90 days at 25 °C. Soil samples were extracted by EDTA for periods of 5 to 975min. In addition, sequential extraction was used as a suitable method for identification of chemical forms of Cd and their plant availability. The addition of amendments to soil had significant effects on desorption and chemical forms of Cd. Changes in Cd fractions and their conversion into less soluble forms were clear in all treated soils. The addition of amendments resulted in a significant reduction in mobility factor of Cd compared to the control treatment. Among all amendments tested, Fe0 was the most effective treatment in decreasing dynamic of Cd. Biphasic pattern of Cd desorption kinetic was fitted well by the model of two first-order reactions. In general, from the practical point of view, Fe0, MSWC and Mn0 treatments are effective in Cd immobilization, while application of  Fe0 at 5% (W/W was the best treatment for stabilization of Cd. 

  4. Improved sensitivity to venom specific-immunoglobulin E by spiking with the allergen component in Japanese patients suspected of Hymenoptera venom allergy

    Directory of Open Access Journals (Sweden)

    Naruo Yoshida

    2015-07-01

    Conclusions: The measurement of sIgE following spiking of rVes v 5 and rPol d 5 by conventional testing in Japanese subjects with sIgE against hornet and paper wasp venom, respectively, improved the sensitivity for detecting Hymenoptera venom allergy. Improvement testing for measuring sIgE levels against hornet and paper wasp venom has potential for serologically elucidating Hymenoptera allergy in Japan.

  5. No bacterial growth found in spiked intravenous fluids over an 8-hour period.

    Science.gov (United States)

    Haas, Richard E; Beitz, Edwin; Reed, Amy; Burtnett, Howard; Lowe, Jason; Crist, Arthur E; Stierer, Kevin A; Birenberg, Allan M

    2017-04-01

    Protocol changes prompted by the Joint Commission mandating intravenous (IV) fluid bags to be used within 1 hour of spiking because of possible bacterial contamination have sparked clinical and economic concerns. This study investigated the degree of bacterial growth in which samples were obtained from spiked IV fluid bags at the time of spiking and 1, 2, 4, and 8 hours after spiking. No bacterial growth occurred in any of the 80 bags of Lactated Ringer's (LR) IV solutions sampled. This study demonstrated that LR IV bags do not support any bacterial growth for up to 8 hours after spiking. Copyright © 2017 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

  6. Approach for domestic preparation of standard material (LSD spike) for isotope dilution mass spectrometry

    International Nuclear Information System (INIS)

    Ishikawa, Fumitaka; Sumi, Mika; Chiba, Masahiko; Suzuki, Toru; Abe, Tomoyuki; Kuno, Yusuke

    2008-01-01

    The accountancy analysis of the nuclear fuel material at Plutonium Fuel Development Center of JAEA is performed by isotope dilution mass spectrometry (IDMS; Isotope Dilution Mass Spectrometry). IDMS requires the standard material called LSD spike (Large Size Dried spike) which is indispensable for the accountancy in the facilities where the nuclear fuel materials are handled. Although the LSD spike and Pu source material have been supplied from foreign countries, the transportation for such materials has been getting more difficult recently. This difficulty may affect the operation of nuclear facilities in the future. Therefore, research and development of the domestic LSD spike and base material has been performed at JAEA. Certification for such standard nuclear materials including spikes produced in Japan is being studied. This report presents the current status and the future plan for the technological development. (author)

  7. Hardware friendly probabilistic spiking neural network with long-term and short-term plasticity.

    Science.gov (United States)

    Hsieh, Hung-Yi; Tang, Kea-Tiong

    2013-12-01

    This paper proposes a probabilistic spiking neural network (PSNN) with unimodal weight distribution, possessing long- and short-term plasticity. The proposed algorithm is derived by both the arithmetic gradient decent calculation and bioinspired algorithms. The algorithm is benchmarked by the Iris and Wisconsin breast cancer (WBC) data sets. The network features fast convergence speed and high accuracy. In the experiment, the PSNN took not more than 40 epochs for convergence. The average testing accuracy for Iris and WBC data is 96.7% and 97.2%, respectively. To test the usefulness of the PSNN to real world application, the PSNN was also tested with the odor data, which was collected by our self-developed electronic nose (e-nose). Compared with the algorithm (K-nearest neighbor) that has the highest classification accuracy in the e-nose for the same odor data, the classification accuracy of the PSNN is only 1.3% less but the memory requirement can be reduced at least 40%. All the experiments suggest that the PSNN is hardware friendly. First, it requires only nine-bits weight resolution for training and testing. Second, the PSNN can learn complex data sets with a little number of neurons that in turn reduce the cost of VLSI implementation. In addition, the algorithm is insensitive to synaptic noise and the parameter variation induced by the VLSI fabrication. Therefore, the algorithm can be implemented by either software or hardware, making it suitable for wider application.

  8. Input-output relation and energy efficiency in the neuron with different spike threshold dynamics

    Directory of Open Access Journals (Sweden)

    Guo-Sheng eYi

    2015-05-01

    Full Text Available Neuron encodes and transmits information through generating sequences of output spikes, which is a high energy-consuming process. The spike is initiated when membrane depolarization reaches a threshold voltage. In many neurons, threshold is dynamic and depends on the rate of membrane depolarization (dV/dt preceding a spike. Identifying the metabolic energy involved in neural coding and their relationship to threshold dynamic is critical to understanding neuronal function and evolution. Here, we use a modified Morris-Lecar model to investigate neuronal input-output property and energy efficiency associated with different spike threshold dynamics. We find that the neurons with dynamic threshold sensitive to dV/dt generate discontinuous frequency-current curve and type II phase response curve (PRC through Hopf bifurcation, and weak noise could prohibit spiking when bifurcation just occurs. The threshold that is insensitive to dV/dt, instead, results in a continuous frequency-current curve, a type I PRC and a saddle-node on invariant circle bifurcation, and simultaneously weak noise cannot inhibit spiking. It is also shown that the bifurcation, frequency-current curve and PRC type associated with different threshold dynamics arise from the distinct subthreshold interactions of membrane currents. Further, we observe that the energy consumption of the neuron is related to its firing characteristics. The depolarization of spike threshold improves neuronal energy efficiency by reducing the overlap of Na+ and K+ currents during an action potential. The high energy efficiency is achieved at more depolarized spike threshold and high stimulus current. These results provide a fundamental biophysical connection that links spike threshold dynamics, input-output relation, energetics and spike initiation, which could contribute to uncover neural encoding mechanism.

  9. Intracellular calcium spikes in rat suprachiasmatic nucleus neurons induced by BAPTA-based calcium dyes.

    Directory of Open Access Journals (Sweden)

    Jin Hee Hong

    Full Text Available BACKGROUND: Circadian rhythms in spontaneous action potential (AP firing frequencies and in cytosolic free calcium concentrations have been reported for mammalian circadian pacemaker neurons located within the hypothalamic suprachiasmatic nucleus (SCN. Also reported is the existence of "Ca(2+ spikes" (i.e., [Ca(2+](c transients having a bandwidth of 10 approximately 100 seconds in SCN neurons, but it is unclear if these SCN Ca(2+ spikes are related to the slow circadian rhythms. METHODOLOGY/PRINCIPAL FINDINGS: We addressed this issue based on a Ca(2+ indicator dye (fluo-4 and a protein Ca(2+ sensor (yellow cameleon. Using fluo-4 AM dye, we found spontaneous Ca(2+ spikes in 18% of rat SCN cells in acute brain slices, but the Ca(2+ spiking frequencies showed no day/night variation. We repeated the same experiments with rat (and mouse SCN slice cultures that expressed yellow cameleon genes for a number of different circadian phases and, surprisingly, spontaneous Ca(2+ spike was barely observed (<3%. When fluo-4 AM or BAPTA-AM was loaded in addition to the cameleon-expressing SCN cultures, however, the number of cells exhibiting Ca(2+ spikes was increased to 13 approximately 14%. CONCLUSIONS/SIGNIFICANCE: Despite our extensive set of experiments, no evidence of a circadian rhythm was found in the spontaneous Ca(2+ spiking activity of SCN. Furthermore, our study strongly suggests that the spontaneous Ca(2+ spiking activity is caused by the Ca(2+ chelating effect of the BAPTA-based fluo-4 dye. Therefore, this induced activity seems irrelevant to the intrinsic circadian rhythm of [Ca(2+](c in SCN neurons. The problems with BAPTA based dyes are widely known and our study provides a clear case for concern, in particular, for SCN Ca(2+ spikes. On the other hand, our study neither invalidates the use of these dyes as a whole, nor undermines the potential role of SCN Ca(2+ spikes in the function of SCN.

  10. Comparison of degradation between indigenous and spiked bisphenol A and triclosan in a biosolids amended soil

    International Nuclear Information System (INIS)

    Langdon, Kate A.; Warne, Michael StJ.; Smernik, Ronald J.; Shareef, Ali; Kookana, Rai S.

    2013-01-01

    This study compared the degradation of indigenous bisphenol A (BPA) and triclosan (TCS) in a biosolids-amended soil, to the degradation of spiked labelled surrogates of the same compounds (BPA-d 16 and TCS- 13 C 12 ). The aim was to determine if spiking experiments accurately predict the degradation of compounds in biosolids-amended soils using two different types of biosolids, a centrifuge dried biosolids (CDB) and a lagoon dried biosolids (LDB). The rate of degradation of the compounds was examined and the results indicated that there were considerable differences between the indigenous and spiked compounds. These differences were more marked for BPA, for which the indigenous compound was detectable throughout the study, whereas the spiked compound decreased to below the detection limit prior to the study completion. The rate of degradation for the indigenous BPA was approximately 5-times slower than that of the spiked BPA-d 16 . The indigenous and spiked TCS were both detectable throughout the study, however, the shape of the degradation curves varied considerably, particularly in the CDB treatment. These findings show that spiking experiments may not be suitable to predict the degradation and persistence of organic compounds following land application of biosolids. - Highlights: ► Degradation of indigenous and spiked compounds from biosolids were compared. ► Differences were observed for both the rate and pattern of degradation. ► Spiked bisphenol A entirely degraded however the indigenous compound remained. ► TCS was detectable during the experiment however the degradation patterns varied. ► Spiking experiments may not be suitable to predict degradation of organic compounds

  11. Comparison of degradation between indigenous and spiked bisphenol A and triclosan in a biosolids amended soil

    Energy Technology Data Exchange (ETDEWEB)

    Langdon, Kate A., E-mail: Kate.Langdon@csiro.au [School of Agriculture, Food and Wine and Waite Research Institute, University of Adelaide, South Australia, 5005, Adelaide (Australia); Water for a Healthy Country Research Flagship, Commonwealth Scientific and Industrial Research Organisation (CSIRO), PMB 2, Glen Osmond, South Australia, 5064, Adelaide (Australia); Warne, Michael StJ. [Water for a Healthy Country Research Flagship, Commonwealth Scientific and Industrial Research Organisation (CSIRO), PMB 2, Glen Osmond, South Australia, 5064, Adelaide (Australia); Smernik, Ronald J. [School of Agriculture, Food and Wine and Waite Research Institute, University of Adelaide, South Australia, 5005, Adelaide (Australia); Shareef, Ali; Kookana, Rai S. [Water for a Healthy Country Research Flagship, Commonwealth Scientific and Industrial Research Organisation (CSIRO), PMB 2, Glen Osmond, South Australia, 5064, Adelaide (Australia)

    2013-03-01

    This study compared the degradation of indigenous bisphenol A (BPA) and triclosan (TCS) in a biosolids-amended soil, to the degradation of spiked labelled surrogates of the same compounds (BPA-d{sub 16} and TCS-{sup 13}C{sub 12}). The aim was to determine if spiking experiments accurately predict the degradation of compounds in biosolids-amended soils using two different types of biosolids, a centrifuge dried biosolids (CDB) and a lagoon dried biosolids (LDB). The rate of degradation of the compounds was examined and the results indicated that there were considerable differences between the indigenous and spiked compounds. These differences were more marked for BPA, for which the indigenous compound was detectable throughout the study, whereas the spiked compound decreased to below the detection limit prior to the study completion. The rate of degradation for the indigenous BPA was approximately 5-times slower than that of the spiked BPA-d{sub 16}. The indigenous and spiked TCS were both detectable throughout the study, however, the shape of the degradation curves varied considerably, particularly in the CDB treatment. These findings show that spiking experiments may not be suitable to predict the degradation and persistence of organic compounds following land application of biosolids. - Highlights: ► Degradation of indigenous and spiked compounds from biosolids were compared. ► Differences were observed for both the rate and pattern of degradation. ► Spiked bisphenol A entirely degraded however the indigenous compound remained. ► TCS was detectable during the experiment however the degradation patterns varied. ► Spiking experiments may not be suitable to predict degradation of organic compounds.

  12. Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains

    Science.gov (United States)

    Onken, Arno; Liu, Jian K.; Karunasekara, P. P. Chamanthi R.; Delis, Ioannis; Gollisch, Tim; Panzeri, Stefano

    2016-01-01

    Advances in neuronal recording techniques are leading to ever larger numbers of simultaneously monitored neurons. This poses the important analytical challenge of how to capture compactly all sensory information that neural population codes carry in their spatial dimension (differences in stimulus tuning across neurons at different locations), in their temporal dimension (temporal neural response variations), or in their combination (temporally coordinated neural population firing). Here we investigate the utility of tensor factorizations of population spike trains along space and time. These factorizations decompose a dataset of single-trial population spike trains into spatial firing patterns (combinations of neurons firing together), temporal firing patterns (temporal activation of these groups of neurons) and trial-dependent activation coefficients (strength of recruitment of such neural patterns on each trial). We validated various factorization methods on simulated data and on populations of ganglion cells simultaneously recorded in the salamander retina. We found that single-trial tensor space-by-time decompositions provided low-dimensional data-robust representations of spike trains that capture efficiently both their spatial and temporal information about sensory stimuli. Tensor decompositions with orthogonality constraints were the most efficient in extracting sensory information, whereas non-negative tensor decompositions worked well even on non-independent and overlapping spike patterns, and retrieved informative firing patterns expressed by the same population in response to novel stimuli. Our method showed that populations of retinal ganglion cells carried information in their spike timing on the ten-milliseconds-scale about spatial details of natural images. This information could not be recovered from the spike counts of these cells. First-spike latencies carried the majority of information provided by the whole spike train about fine-scale image

  13. Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains.

    Directory of Open Access Journals (Sweden)

    Arno Onken

    2016-11-01

    Full Text Available Advances in neuronal recording techniques are leading to ever larger numbers of simultaneously monitored neurons. This poses the important analytical challenge of how to capture compactly all sensory information that neural population codes carry in their spatial dimension (differences in stimulus tuning across neurons at different locations, in their temporal dimension (temporal neural response variations, or in their combination (temporally coordinated neural population firing. Here we investigate the utility of tensor factorizations of population spike trains along space and time. These factorizations decompose a dataset of single-trial population spike trains into spatial firing patterns (combinations of neurons firing together, temporal firing patterns (temporal activation of these groups of neurons and trial-dependent activation coefficients (strength of recruitment of such neural patterns on each trial. We validated various factorization methods on simulated data and on populations of ganglion cells simultaneously recorded in the salamander retina. We found that single-trial tensor space-by-time decompositions provided low-dimensional data-robust representations of spike trains that capture efficiently both their spatial and temporal information about sensory stimuli. Tensor decompositions with orthogonality constraints were the most efficient in extracting sensory information, whereas non-negative tensor decompositions worked well even on non-independent and overlapping spike patterns, and retrieved informative firing patterns expressed by the same population in response to novel stimuli. Our method showed that populations of retinal ganglion cells carried information in their spike timing on the ten-milliseconds-scale about spatial details of natural images. This information could not be recovered from the spike counts of these cells. First-spike latencies carried the majority of information provided by the whole spike train about fine

  14. The Chronotron: A Neuron That Learns to Fire Temporally Precise Spike Patterns

    Science.gov (United States)

    Florian, Răzvan V.

    2012-01-01

    In many cases, neurons process information carried by the precise timings of spikes. Here we show how neurons can learn to generate specific temporally precise output spikes in response to input patterns of spikes having precise timings, thus processing and memorizing information that is entirely temporally coded, both as input and as output. We introduce two new supervised learning rules for spiking neurons with temporal coding of information (chronotrons), one that provides high memory capacity (E-learning), and one that has a higher biological plausibility (I-learning). With I-learning, the neuron learns to fire the target spike trains through synaptic changes that are proportional to the synaptic currents at the timings of real and target output spikes. We study these learning rules in computer simulations where we train integrate-and-fire neurons. Both learning rules allow neurons to fire at the desired timings, with sub-millisecond precision. We show how chronotrons can learn to classify their inputs, by firing identical, temporally precise spike trains for different inputs belonging to the same class. When the input is noisy, the classification also leads to noise reduction. We compute lower bounds for the memory capacity of chronotrons and explore the influence of various parameters on chronotrons' performance. The chronotrons can model neurons that encode information in the time of the first spike relative to the onset of salient stimuli or neurons in oscillatory networks that encode information in the phases of spikes relative to the background oscillation. Our results show that firing one spike per cycle optimizes memory capacity in neurons encoding information in the phase of firing relative to a background rhythm. PMID:22879876

  15. iRaster: a novel information visualization tool to explore spatiotemporal patterns in multiple spike trains.

    Science.gov (United States)

    Somerville, J; Stuart, L; Sernagor, E; Borisyuk, R

    2010-12-15

    Over the last few years, simultaneous recordings of multiple spike trains have become widely used by neuroscientists. Therefore, it is important to develop new tools for analysing multiple spike trains in order to gain new insight into the function of neural systems. This paper describes how techniques from the field of visual analytics can be used to reveal specific patterns of neural activity. An interactive raster plot called iRaster has been developed. This software incorporates a selection of statistical procedures for visualization and flexible manipulations with multiple spike trains. For example, there are several procedures for the re-ordering of spike trains which can be used to unmask activity propagation, spiking synchronization, and many other important features of multiple spike train activity. Additionally, iRaster includes a rate representation of neural activity, a combined representation of rate and spikes, spike train removal and time interval removal. Furthermore, it provides multiple coordinated views, time and spike train zooming windows, a fisheye lens distortion, and dissemination facilities. iRaster is a user friendly, interactive, flexible tool which supports a broad range of visual representations. This tool has been successfully used to analyse both synthetic and experimentally recorded datasets. In this paper, the main features of iRaster are described and its performance and effectiveness are demonstrated using various types of data including experimental multi-electrode array recordings from the ganglion cell layer in mouse retina. iRaster is part of an ongoing research project called VISA (Visualization of Inter-Spike Associations) at the Visualization Lab in the University of Plymouth. The overall aim of the VISA project is to provide neuroscientists with the ability to freely explore and analyse their data. The software is freely available from the Visualization Lab website (see www.plymouth.ac.uk/infovis). Copyright © 2010

  16. The chronotron: a neuron that learns to fire temporally precise spike patterns.

    Directory of Open Access Journals (Sweden)

    Răzvan V Florian

    Full Text Available In many cases, neurons process information carried by the precise timings of spikes. Here we show how neurons can learn to generate specific temporally precise output spikes in response to input patterns of spikes having precise timings, thus processing and memorizing information that is entirely temporally coded, both as input and as output. We introduce two new supervised learning rules for spiking neurons with temporal coding of information (chronotrons, one that provides high memory capacity (E-learning, and one that has a higher biological plausibility (I-learning. With I-learning, the neuron learns to fire the target spike trains through synaptic changes that are proportional to the synaptic currents at the timings of real and target output spikes. We study these learning rules in computer simulations where we train integrate-and-fire neurons. Both learning rules allow neurons to fire at the desired timings, with sub-millisecond precision. We show how chronotrons can learn to classify their inputs, by firing identical, temporally precise spike trains for different inputs belonging to the same class. When the input is noisy, the classification also leads to noise reduction. We compute lower bounds for the memory capacity of chronotrons and explore the influence of various parameters on chronotrons' performance. The chronotrons can model neurons that encode information in the time of the first spike relative to the onset of salient stimuli or neurons in oscillatory networks that encode information in the phases of spikes relative to the background oscillation. Our results show that firing one spike per cycle optimizes memory capacity in neurons encoding information in the phase of firing relative to a background rhythm.

  17. Input-output relation and energy efficiency in the neuron with different spike threshold dynamics.

    Science.gov (United States)

    Yi, Guo-Sheng; Wang, Jiang; Tsang, Kai-Ming; Wei, Xi-Le; Deng, Bin

    2015-01-01

    Neuron encodes and transmits information through generating sequences of output spikes, which is a high energy-consuming process. The spike is initiated when membrane depolarization reaches a threshold voltage. In many neurons, threshold is dynamic and depends on the rate of membrane depolarization (dV/dt) preceding a spike. Identifying the metabolic energy involved in neural coding and their relationship to threshold dynamic is critical to understanding neuronal function and evolution. Here, we use a modified Morris-Lecar model to investigate neuronal input-output property and energy efficiency associated with different spike threshold dynamics. We find that the neurons with dynamic threshold sensitive to dV/dt generate discontinuous frequency-current curve and type II phase response curve (PRC) through Hopf bifurcation, and weak noise could prohibit spiking when bifurcation just occurs. The threshold that is insensitive to dV/dt, instead, results in a continuous frequency-current curve, a type I PRC and a saddle-node on invariant circle bifurcation, and simultaneously weak noise cannot inhibit spiking. It is also shown that the bifurcation, frequency-current curve and PRC type associated with different threshold dynamics arise from the distinct subthreshold interactions of membrane currents. Further, we observe that the energy consumption of the neuron is related to its firing characteristics. The depolarization of spike threshold improves neuronal energy efficiency by reducing the overlap of Na(+) and K(+) currents during an action potential. The high energy efficiency is achieved at more depolarized spike threshold and high stimulus current. These results provide a fundamental biophysical connection that links spike threshold dynamics, input-output relation, energetics and spike initiation, which could contribute to uncover neural encoding mechanism.

  18. Tritium uptake in rainbow trout (Oncorhynchus mykiss): HTO and OBT-spiked feed exposures simultaneously

    International Nuclear Information System (INIS)

    Kim, S.B.; Shultz, C.; Stuart, M.; Festarini, A.

    2015-01-01

    There is currently considerable interest in organically bound tritium (OBT) formation in edible fish. The major questions revolve around whether or not tritium can accumulate in fish after being released into aquatic environments. Since OBT formation rates in large, edible fish are poorly understood, rainbow trout (Oncorhynchus mykiss) studies, where fish were simultaneously exposed to tritiated water (HTO) and OBT-spiked feed over 130 days, were conducted to evaluate tritium uptake. The measured HTO activity concentrations in fish tissue confirmed that HTO in fish tissue equilibrates quickly with HTO in tank water. The data obtained also confirmed that OBT uptake is faster when fish are ingesting OBT-spiked feed compared to when fish are living in tritiated water (and consuming non-OBT-spiked feed). The difference between the two exposure types is such that the groups exposed to tritiated water and OBT-spiked feed simultaneously were showing the same uptake rates as OBT-spiked feed only exposures. Contrary to what was expected, the rate of OBT uptake (from OBT-spiked feed) seemed to be higher in slow growing fish compared to fast growing fish. Another observation from these studies was that OBT activity concentrations in all organs (viscera) had a tendency to be higher than OBT activity concentrations measured in fish flesh. - Highlights: • Edible size of rainbow trout (Oncorhynchus mykiss) were simultaneously exposed to tritiated water (HTO) and OBT-spiked feed over 130 days. • OBT uptake is faster when fish are ingesting OBT-spiked feed compared to when fish are living in tritiated water (and consuming non-OBT-spiked feed). • The rate of OBT uptake (from OBT-spiked feed) seemed to be higher in slow growing fish compared to fast growing fish

  19. Design spectra development considering short time histories

    International Nuclear Information System (INIS)

    Weiner, E.O.

    1983-01-01

    The need for generation of seismic acceleration histories to prescribed response spectra arises several ways in structural dynamics. For example, one way of obtaining floor spectra is to generate a history from a foundation spectra and then solve for the floor motion from which a floor spectrum can be obtained. Two separate programs, MODQKE and MDOF, were written to provide a capability of obtaining equipment spectra from design spectra. MODQKE generates or modifies acceleration histories to conform with design spectra pertaining to, say, a foundation. MDOF is a simple linear modal superposition program that solves for equipment support histories using the design spectra conforming histories as input. Equipment spectra, then, are obtained from the support histories using MODQKE

  20. Modeling Spike-Train Processing in the Cerebellum Granular Layer and Changes in Plasticity Reveal Single Neuron Effects in Neural Ensembles

    Directory of Open Access Journals (Sweden)

    Chaitanya Medini

    2012-01-01

    Full Text Available The cerebellum input stage has been known to perform combinatorial operations on input signals. In this paper, two types of mathematical models were used to reproduce the role of feed-forward inhibition and computation in the granular layer microcircuitry to investigate spike train processing. A simple spiking model and a biophysically-detailed model of the network were used to study signal recoding in the granular layer and to test observations like center-surround organization and time-window hypothesis in addition to effects of induced plasticity. Simulations suggest that simple neuron models may be used to abstract timing phenomenon in large networks, however detailed models were needed to reconstruct population coding via evoked local field potentials (LFP and for simulating changes in synaptic plasticity. Our results also indicated that spatio-temporal code of the granular network is mainly controlled by the feed-forward inhibition from the Golgi cell synapses. Spike amplitude and total number of spikes were modulated by LTP and LTD. Reconstructing granular layer evoked-LFP suggests that granular layer propagates the nonlinearities of individual neurons. Simulations indicate that granular layer network operates a robust population code for a wide range of intervals, controlled by the Golgi cell inhibition and is regulated by the post-synaptic excitability.

  1. ViSAPy: a Python tool for biophysics-based generation of virtual spiking activity for evaluation of spike-sorting algorithms.

    Science.gov (United States)

    Hagen, Espen; Ness, Torbjørn V; Khosrowshahi, Amir; Sørensen, Christina; Fyhn, Marianne; Hafting, Torkel; Franke, Felix; Einevoll, Gaute T

    2015-04-30

    New, silicon-based multielectrodes comprising hundreds or more electrode contacts offer the possibility to record spike trains from thousands of neurons simultaneously. This potential cannot be realized unless accurate, reliable automated methods for spike sorting are developed, in turn requiring benchmarking data sets with known ground-truth spike times. We here present a general simulation tool for computing benchmarking data for evaluation of spike-sorting algorithms entitled ViSAPy (Virtual Spiking Activity in Python). The tool is based on a well-established biophysical forward-modeling scheme and is implemented as a Python package built on top of the neuronal simulator NEURON and the Python tool LFPy. ViSAPy allows for arbitrary combinations of multicompartmental neuron models and geometries of recording multielectrodes. Three example benchmarking data sets are generated, i.e., tetrode and polytrode data mimicking in vivo cortical recordings and microelectrode array (MEA) recordings of in vitro activity in salamander retinas. The synthesized example benchmarking data mimics salient features of typical experimental recordings, for example, spike waveforms depending on interspike interval. ViSAPy goes beyond existing methods as it includes biologically realistic model noise, synaptic activation by recurrent spiking networks, finite-sized electrode contacts, and allows for inhomogeneous electrical conductivities. ViSAPy is optimized to allow for generation of long time series of benchmarking data, spanning minutes of biological time, by parallel execution on multi-core computers. ViSAPy is an open-ended tool as it can be generalized to produce benchmarking data or arbitrary recording-electrode geometries and with various levels of complexity. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

  2. Operator functions and localization of spectra

    CERN Document Server

    Gil’, Michael I

    2003-01-01

    "Operator Functions and Localization of Spectra" is the first book that presents a systematic exposition of bounds for the spectra of various linear nonself-adjoint operators in a Hilbert space, having discrete and continuous spectra. In particular bounds for the spectra of integral, differential and integro-differential operators, as well as finite and infinite matrices are established. The volume also presents a systematic exposition of estimates for norms of operator-valued functions and their applications.

  3. Wavelet spectra of JACEE events

    International Nuclear Information System (INIS)

    Suzuki, Naomichi; Biyajima, Minoru; Ohsawa, Akinori.

    1995-01-01

    Pseudo-rapidity distributions of two high multiplicity events Ca-C and Si-AgBr observed by the JACEE are analyzed by a wavelet transform. Wavelet spectra of those events are calculated and compared with the simulation calculations. The wavelet spectrum of the Ca-C event somewhat resembles that simulated with the uniform random numbers. That of Si-AgBr event, however, is not reproduced by simulation calculations with Poisson random numbers, uniform random numbers, or a p-model. (author)

  4. Rotational spectra and molecular structure

    CERN Document Server

    Wollrab, James E

    1967-01-01

    Physical Chemistry, A Series of Monographs: Rotational Spectra and Molecular Structure covers the energy levels and rotational transitions. This book is divided into nine chapters that evaluate the rigid asymmetric top molecules and the nuclear spin statistics for asymmetric tops. Some of the topics covered in the book are the asymmetric rotor functions; rotational transition intensities; classes of molecules; nuclear spin statistics for linear molecules and symmetric tops; and classical appearance of centrifugal and coriolis forces. Other chapters deal with the energy levels and effects of ce

  5. The relevance of attention deficit hyperactivity disorder in self-limited childhood epilepsy with centrotemporal spikes.

    Science.gov (United States)

    Lima, Ellen Marise; Rzezak, Patricia; Dos Santos, Bernardo; Gentil, Letícia; Montenegro, Maria A; Guerreiro, Marilisa M; Valente, Kette D

    2018-04-09

    In this study, we aimed to evaluate the attentional and executive functions in patients with benign childhood epilepsy with centrotemporal spikes (BCECTS) with and without attention-deficit hyperactivity disorder (ADHD) compared with controls and compared with patients with ADHD without epilepsy. We evaluated 12 patients with BCECTS and ADHD (66.7% boys; mean age of 9.67years); 11 children with non-ADHD BCECTS (63.6% boys; mean age of 11.91years); 20 healthy children (75% boys; mean age of 10.15years); and 20 subjects with ADHD without epilepsy (60% boys; mean age of 10.9years). We used a comprehensive battery of neuropsychological tests to evaluate attentional and executive functions in their broad domains. Patients with BCECTS and ADHD had worse performance in Conners' Continuous Performance Test II (reaction time standard error [p=0.008], variability [p=0.033], perseverations [p=0.044] and in reaction time interstimuli interval [p=0.016]). Patients with ADHD showed worse performance in Trail Making Test B errors [p=0.012]. In conclusion, patients with BCECTS and ADHD had worse executive and attentional performance compared with controls than non-ADHD patients with BCECTS. Regardless of the presence of epilepsy, ADHD also negatively impacted executive and attentional functions but in different executive subdomains compared with patients with epilepsy. Copyright © 2018 Elsevier Inc. All rights reserved.

  6. Detection of hidden structures in nonstationary spike trains.

    Science.gov (United States)

    Takiyama, Ken; Okada, Masato

    2011-05-01

    We propose an algorithm for simultaneously estimating state transitions among neural states and nonstationary firing rates using a switching state-space model (SSSM). This algorithm enables us to detect state transitions on the basis of not only discontinuous changes in mean firing rates but also discontinuous changes in the temporal profiles of firing rates (e.g., temporal correlation). We construct estimation and learning algorithms for a nongaussian SSSM, whose nongaussian property is caused by binary spike events. Local variational methods can transform the binary observation process into a quadratic form. The transformed observation process enables us to construct a variational Bayes algorithm that can determine the number of neural states based on automatic relevance determination. Additionally, our algorithm can estimate model parameters from single-trial data using a priori knowledge about state transitions and firing rates. Synthetic data analysis reveals that our algorithm has higher performance for estimating nonstationary firing rates than previous methods. The analysis also confirms that our algorithm can detect state transitions on the basis of discontinuous changes in temporal correlation, which are transitions that previous hidden Markov models could not detect. We also analyze neural data recorded from the medial temporal area. The statistically detected neural states probably coincide with transient and sustained states that have been detected heuristically. Estimated parameters suggest that our algorithm detects the state transitions on the basis of discontinuous changes in the temporal correlation of firing rates. These results suggest that our algorithm is advantageous in real-data analysis.

  7. Dynamics of spiking neurons: between homogeneity and synchrony.

    Science.gov (United States)

    Rangan, Aaditya V; Young, Lai-Sang

    2013-06-01

    Randomly connected networks of neurons driven by Poisson inputs are often assumed to produce "homogeneous" dynamics, characterized by largely independent firing and approximable by diffusion processes. At the same time, it is well known that such networks can fire synchronously. Between these two much studied scenarios lies a vastly complex dynamical landscape that is relatively unexplored. In this paper, we discuss a phenomenon which commonly manifests in these intermediate regimes, namely brief spurts of spiking activity which we call multiple firing events (MFE). These events do not depend on structured network architecture nor on structured input; they are an emergent property of the system. We came upon them in an earlier modeling paper, in which we discovered, through a careful benchmarking process, that MFEs are the single most important dynamical mechanism behind many of the V1 phenomena we were able to replicate. In this paper we explain in a simpler setting how MFEs come about, as well as their potential dynamic consequences. Although the mechanism underlying MFEs cannot easily be captured by current population dynamics models, this phenomena should not be ignored during analysis; there is a growing body of evidence that such collaborative activity may be a key towards unlocking the possible functional properties of many neuronal networks.

  8. U.S. Virgin Islands Petroleum Price-Spike Preparation

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, C.

    2012-06-01

    This NREL technical report details a plan for the U.S. Virgin Islands (USVI) to minimize the economic damage caused by major petroleum price increases. The assumptions for this plan are that the USVI will have very little time and money to implement it and that the population will be highly motivated to follow it because of high fuel prices. The plan's success, therefore, is highly dependent on behavior change. This plan was derived largely from a review of the actions taken and behavior changes made by companies and commuters throughout the United States in response to the oil price spike of 2008. Many of these solutions were coordinated by or reported through the 88 local representatives of the U.S. Department of Energy's Clean Cities program. The National Renewable Energy Laboratory provides technical and communications support for the Clean Cities program and therefore serves as a de facto repository of these solutions. This plan is the first publication that has tapped this repository.

  9. Serotonin inhibits low-threshold spike interneurons in the striatum

    Science.gov (United States)

    Cains, Sarah; Blomeley, Craig P; Bracci, Enrico

    2012-01-01

    Low-threshold spike interneurons (LTSIs) are important elements of the striatal architecture and the only known source of nitric oxide in this nucleus, but their rarity has so far prevented systematic studies. Here, we used transgenic mice in which green fluorescent protein is expressed under control of the neuropeptide Y (NPY) promoter and striatal NPY-expressing LTSIs can be easily identified, to investigate the effects of serotonin on these neurons. In sharp contrast with its excitatory action on other striatal interneurons, serotonin (30 μm) strongly inhibited LTSIs, reducing or abolishing their spontaneous firing activity and causing membrane hyperpolarisations. These hyperpolarisations persisted in the presence of tetrodotoxin, were mimicked by 5-HT2C receptor agonists and reversed by 5-HT2C antagonists. Voltage-clamp slow-ramp experiments showed that serotonin caused a strong increase in an outward current activated by depolarisations that was blocked by the specific M current blocker XE 991. In current-clamp experiments, XE 991 per se caused membrane depolarisations in LTSIs and subsequent application of serotonin (in the presence of XE 991) failed to affect these neurons. We concluded that serotonin strongly inhibits striatal LTSIs acting through postsynaptic 5-HT2C receptors and increasing an M type current. PMID:22495583

  10. Learning Probabilistic Inference through Spike-Timing-Dependent Plasticity123

    Science.gov (United States)

    Pecevski, Dejan

    2016-01-01

    Abstract Numerous experimental data show that the brain is able to extract information from complex, uncertain, and often ambiguous experiences. Furthermore, it can use such learnt information for decision making through probabilistic inference. Several models have been proposed that aim at explaining how probabilistic inference could be performed by networks of neurons in the brain. We propose here a model that can also explain how such neural network could acquire the necessary information for that from examples. We show that spike-timing-dependent plasticity in combination with intrinsic plasticity generates in ensembles of pyramidal cells with lateral inhibition a fundamental building block for that: probabilistic associations between neurons that represent through their firing current values of random variables. Furthermore, by combining such adaptive network motifs in a recursive manner the resulting network is enabled to extract statistical information from complex input streams, and to build an internal model for the distribution p* that generates the examples it receives. This holds even if p* contains higher-order moments. The analysis of this learning process is supported by a rigorous theoretical foundation. Furthermore, we show that the network can use the learnt internal model immediately for prediction, decision making, and other types of probabilistic inference. PMID:27419214

  11. Learning Probabilistic Inference through Spike-Timing-Dependent Plasticity.

    Science.gov (United States)

    Pecevski, Dejan; Maass, Wolfgang

    2016-01-01

    Numerous experimental data show that the brain is able to extract information from complex, uncertain, and often ambiguous experiences. Furthermore, it can use such learnt information for decision making through probabilistic inference. Several models have been proposed that aim at explaining how probabilistic inference could be performed by networks of neurons in the brain. We propose here a model that can also explain how such neural network could acquire the necessary information for that from examples. We show that spike-timing-dependent plasticity in combination with intrinsic plasticity generates in ensembles of pyramidal cells with lateral inhibition a fundamental building block for that: probabilistic associations between neurons that represent through their firing current values of random variables. Furthermore, by combining such adaptive network motifs in a recursive manner the resulting network is enabled to extract statistical information from complex input streams, and to build an internal model for the distribution p (*) that generates the examples it receives. This holds even if p (*) contains higher-order moments. The analysis of this learning process is supported by a rigorous theoretical foundation. Furthermore, we show that the network can use the learnt internal model immediately for prediction, decision making, and other types of probabilistic inference.

  12. Symbol manipulation and rule learning in spiking neuronal networks.

    Science.gov (United States)

    Fernando, Chrisantha

    2011-04-21

    It has been claimed that the productivity, systematicity and compositionality of human language and thought necessitate the existence of a physical symbol system (PSS) in the brain. Recent discoveries about temporal coding suggest a novel type of neuronal implementation of a physical symbol system. Furthermore, learning classifier systems provide a plausible algorithmic basis by which symbol re-write rules could be trained to undertake behaviors exhibiting systematicity and compositionality, using a kind of natural selection of re-write rules in the brain, We show how the core operation of a learning classifier system, namely, the replication with variation of symbol re-write rules, can be implemented using spike-time dependent plasticity based supervised learning. As a whole, the aim of this paper is to integrate an algorithmic and an implementation level description of a neuronal symbol system capable of sustaining systematic and compositional behaviors. Previously proposed neuronal implementations of symbolic representations are compared with this new proposal. Copyright © 2011 Elsevier Ltd. All rights reserved.

  13. Recurrent coupling improves discrimination of temporal spike patterns

    Directory of Open Access Journals (Sweden)

    Chun-Wei eYuan

    2012-05-01

    Full Text Available Despite the ubiquitous presence of recurrent synaptic connections insensory neuronal systems, their general functional purpose is not wellunderstood. A recent conceptual advance has been achieved by theoriesof reservoir computing in which recurrent networks have been proposedto generate short-term memory as well as to improve neuronalrepresentation of the sensory input for subsequent computations.Here, we present a numerical study on the distinct effects ofinhibitory and excitatory recurrence in a canonical linearclassification task. It is found that both types of coupling improvethe ability to discriminate temporal spike patterns as compared to apurely feed-forward system, although in different ways. For a largeclass of inhibitory networks, the network's performance is optimal aslong as a fraction of roughly 50% of neurons per stimulus is activein the resulting population code. Thereby the contribution of inactiveneurons to the neural code is found to be even more informative thanthat of the active neurons, generating an inherent robustness ofclassification performance against temporal jitter of the inputspikes. Excitatory couplings are found to not only produce ashort-term memory buffer but also to improve linear separability ofthe population patterns by evoking more irregular firing as comparedto the purely inhibitory case. As the excitatory connectivity becomesmore sparse, firing becomes more variable and pattern separabilityimproves. We argue that the proposed paradigm is particularlywell-suited as a conceptual framework for processing of sensoryinformation in the auditory pathway.

  14. Dynamic finite size effects in spiking neural networks.

    Directory of Open Access Journals (Sweden)

    Michael A Buice

    Full Text Available We investigate the dynamics of a deterministic finite-sized network of synaptically coupled spiking neurons and present a formalism for computing the network statistics in a perturbative expansion. The small parameter for the expansion is the inverse number of neurons in the network. The network dynamics are fully characterized by a neuron population density that obeys a conservation law analogous to the Klimontovich equation in the kinetic theory of plasmas. The Klimontovich equation does not possess well-behaved solutions but can be recast in terms of a coupled system of well-behaved moment equations, known as a moment hierarchy. The moment hierarchy is impossible to solve but in the mean field limit of an infinite number of neurons, it reduces to a single well-behaved conservation law for the mean neuron density. For a large but finite system, the moment hierarchy can be truncated perturbatively with the inverse system size as a small parameter but the resulting set of reduced moment equations that are still very difficult to solve. However, the entire moment hierarchy can also be re-expressed in terms of a functional probability distribution of the neuron density. The moments can then be computed perturbatively using methods from statistical field theory. Here we derive the complete mean field theory and the lowest order second moment corrections for physiologically relevant quantities. Although we focus on finite-size corrections, our method can be used to compute perturbative expansions in any parameter.

  15. Population spikes in cortical networks during different functional states.

    Directory of Open Access Journals (Sweden)

    Shirley eMark

    2012-07-01

    Full Text Available Brain computational challenges vary between behavioral states. Engaged animals react according to incoming sensory information, while in relaxed and sleeping states consolidation of the learned information is believed to take place. Different states are characterized by different forms of cortical activity. We study a possible neuronal mechanism for generating these diverse dynamics and suggest their possible functional significance. Previous studies demonstrated that brief synchronized increase in a neural firing (Population Spikes can be generated in homogenous recurrent neural networks with short-term synaptic depression. Here we consider more realistic networks with clustered architecture. We show that the level of synchronization in neural activity can be controlled smoothly by network parameters. The network shifts from asynchronous activity to a regime in which clusters synchronized separately, then, the synchronization between the clusters increases gradually to fully synchronized state. We examine the effects of different synchrony levels on the transmission of information by the network. We find that the regime of intermediate synchronization is preferential for the flow of information between sparsely connected areas. Based on these results, we suggest that the regime of intermediate synchronization corresponds to engaged behavioral state of the animal, while global synchronization is exhibited during relaxed and sleeping states.

  16. Electrical source imaging of interictal spikes using multiple sparse volumetric priors for presurgical epileptogenic focus localization

    Directory of Open Access Journals (Sweden)

    Gregor Strobbe

    2016-01-01

    Full Text Available Electrical source imaging of interictal spikes observed in EEG recordings of patients with refractory epilepsy provides useful information to localize the epileptogenic focus during the presurgical evaluation. However, the selection of the time points or time epochs of the spikes in order to estimate the origin of the activity remains a challenge. In this study, we consider a Bayesian EEG source imaging technique for distributed sources, i.e. the multiple volumetric sparse priors (MSVP approach. The approach allows to estimate the time courses of the intensity of the sources corresponding with a specific time epoch of the spike. Based on presurgical averaged interictal spikes in six patients who were successfully treated with surgery, we estimated the time courses of the source intensities for three different time epochs: (i an epoch starting 50 ms before the spike peak and ending at 50% of the spike peak during the rising phase of the spike, (ii an epoch starting 50 ms before the spike peak and ending at the spike peak and (iii an epoch containing the full spike time period starting 50 ms before the spike peak and ending 230 ms after the spike peak. To identify the primary source of the spike activity, the source with the maximum energy from 50 ms before the spike peak till 50% of the spike peak was subsequently selected for each of the time windows. For comparison, the activity at the spike peaks and at 50% of the peaks was localized using the LORETA inversion technique and an ECD approach. Both patient-specific spherical forward models and patient-specific 5-layered finite difference models were considered to evaluate the influence of the forward model. Based on the resected zones in each of the patients, extracted from post-operative MR images, we compared the distances to the resection border of the estimated activity. Using the spherical models, the distances to the resection border for the MSVP approach and each of the different time

  17. The Analysis and Suppression of the spike noise in vibrator record

    Science.gov (United States)

    Jia, H.; Jiang, T.; Xu, X.; Ge, L.; Lin, J.; Yang, Z.

    2013-12-01

    During the seismic exploration with vibrator, seismic recording systems have often been affected by random spike noise in the background, which leads to strong data distortions as a result of the cross-correlation processing of the vibrator method. Partial or total loss of the desired seismic information is possible if no automatic spike reduction is available in the field prior to correlation of the field record. Generally speaking, original record of vibrator is uncorrelated data, in which the signal is non-wavelet form. In order to obtain the seismic record similar to explosive source, the signal of uncorrelated data needs to use the correlation algorithm to compress into wavelet form. The correlation process results in that the interference of spike in correlated data is not only being suppressed, but also being expanded. So the spike noise suppression of vibrator is indispensable. According to numerical simulation results, the effect of spike in the vibrator record is mainly affected by the amplitude and proportional points in the uncorrelated record. When the spike noise ratio in uncorrelated record reaches 1.5% and the average amplitude exceeds 200, it will make the SNR(signal-to-noise ratio) of the correlated record lower than 0dB, so that it is difficult to separate the signal. While the amplitude and ratio is determined by the intensity of background noise. Therefore, when the noise level is strong, in order to improve SNR of the seismic data, the uncorrelated record of vibrator need to take necessary steps to suppress spike noise. For the sake of reducing the influence of the spike noise, we need to make the detection and suppression of spike noise process for the uncorrelated record. Because vibrator works by inputting sweep signal into the underground long time, ideally, the peak and valley values of each trace have little change. On the basis of the peak and valley values, we can get a reference amplitude value. Then the spike can be detected and

  18. Comments on the variation of spike morphology in selected species of Elytrigia and Elymus (Triticeae

    Directory of Open Access Journals (Sweden)

    Romuald Kosina

    2014-01-01

    Full Text Available The structure of spikes of Elytrigia repens, E. intermedia and Elymus caninus was investigated. The number of spikelets per spike reveals the weakest correlations with other characters of the spike. The same concerns some character ratios. The correlations provide information about the segmented structure (metamers of the spike. There is a great difference between matrices of correlation coefficients for E. repens and E. intermedia related to the development and structure of spike. Characters important for the description of the spike were chosen - in five-character set these are among others: length of glume awn in median spikelet, length of lemma awn in the first floret of the median spikelet, number of spikelets per spike. Length of lemma awn and mean length of the rachis segment were recognized as the best discriminants for species. Ordination of forms along axes of canonical variates does not indicate the subunits within E. repens. Intermediate forms between E. repens and Elymus caninus have not been found. Between E. repens and E. intermedia there exists some proximity. Heteromorphic individuals were described by means of cluster analysis. They prove the mobility of the genome in ramets of a single genet.

  19. Energetics based spike generation of a single neuron: simulation results and analysis

    Directory of Open Access Journals (Sweden)

    Nagarajan eVenkateswaran

    2012-02-01

    Full Text Available Existing current based models that capture spike activity, though useful in studying information processing capabilities of neurons, fail to throw light on their internal functioning. It is imperative to develop a model that captures the spike train of a neuron as a function of its intra cellular parameters for non-invasive diagnosis of diseased neurons. This is the first ever article to present such an integrated model that quantifies the inter-dependency between spike activity and intra cellular energetics. The generated spike trains from our integrated model will throw greater light on the intra-cellular energetics than existing current models. Now, an abnormality in the spike of a diseased neuron can be linked and hence effectively analyzed at the energetics level. The spectral analysis of the generated spike trains in a time-frequency domain will help identify abnormalities in the internals of a neuron. As a case study, the parameters of our model are tuned for Alzheimer disease and its resultant spike trains are studied and presented.

  20. Biophysical properties and computational modeling of calcium spikes in serotonergic neurons of the dorsal raphe nucleus.

    Science.gov (United States)

    Tuckwell, Henry C

    2013-06-01

    Serotonergic neurons of the dorsal raphe nuclei, with their extensive innervation of nearly the whole brain have important modulatory effects on many cognitive and physiological processes. They play important roles in clinical depression and other psychiatric disorders. In order to quantify the effects of serotonergic transmission on target cells it is desirable to construct computational models and to this end these it is necessary to have details of the biophysical and spike properties of the serotonergic neurons. Here several basic properties are reviewed with data from several studies since the 1960s to the present. The quantities included are input resistance, resting membrane potential, membrane time constant, firing rate, spike duration, spike and afterhyperpolarization (AHP) amplitude, spike threshold, cell capacitance, soma and somadendritic areas. The action potentials of these cells are normally triggered by a combination of sodium and calcium currents which may result in autonomous pacemaker activity. We here analyse the mechanisms of high-threshold calcium spikes which have been demonstrated in these cells the presence of TTX (tetrodotoxin). The parameters for calcium dynamics required to give calcium spikes are quite different from those for regular spiking which suggests the involvement of restricted parts of the soma-dendritic surface as has been found, for example, in hippocampal neurons. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  1. Spike-threshold adaptation predicted by membrane potential dynamics in vivo.

    Directory of Open Access Journals (Sweden)

    Bertrand Fontaine

    2014-04-01

    Full Text Available Neurons encode information in sequences of spikes, which are triggered when their membrane potential crosses a threshold. In vivo, the spiking threshold displays large variability suggesting that threshold dynamics have a profound influence on how the combined input of a neuron is encoded in the spiking. Threshold variability could be explained by adaptation to the membrane potential. However, it could also be the case that most threshold variability reflects noise and processes other than threshold adaptation. Here, we investigated threshold variation in auditory neurons responses recorded in vivo in barn owls. We found that spike threshold is quantitatively predicted by a model in which the threshold adapts, tracking the membrane potential at a short timescale. As a result, in these neurons, slow voltage fluctuations do not contribute to spiking because they are filtered by threshold adaptation. More importantly, these neurons can only respond to input spikes arriving together on a millisecond timescale. These results demonstrate that fast adaptation to the membrane potential captures spike threshold variability in vivo.

  2. Comparison of degradation between indigenous and spiked bisphenol A and triclosan in a biosolids amended soil.

    Science.gov (United States)

    Langdon, Kate A; Warne, Michael Stj; Smernik, Ronald J; Shareef, Ali; Kookana, Rai S

    2013-03-01

    This study compared the degradation of indigenous bisphenol A (BPA) and triclosan (TCS) in a biosolids-amended soil, to the degradation of spiked labelled surrogates of the same compounds (BPA-d16 and TCS-(13)C12). The aim was to determine if spiking experiments accurately predict the degradation of compounds in biosolids-amended soils using two different types of biosolids, a centrifuge dried biosolids (CDB) and a lagoon dried biosolids (LDB). The rate of degradation of the compounds was examined and the results indicated that there were considerable differences between the indigenous and spiked compounds. These differences were more marked for BPA, for which the indigenous compound was detectable throughout the study, whereas the spiked compound decreased to below the detection limit prior to the study completion. The rate of degradation for the indigenous BPA was approximately 5-times slower than that of the spiked BPA-d16. The indigenous and spiked TCS were both detectable throughout the study, however, the shape of the degradation curves varied considerably, particularly in the CDB treatment. These findings show that spiking experiments may not be suitable to predict the degradation and persistence of organic compounds following land application of biosolids. Copyright © 2013 Elsevier B.V. All rights reserved.

  3. Electricity market price spike analysis by a hybrid data model and feature selection technique

    International Nuclear Information System (INIS)

    Amjady, Nima; Keynia, Farshid

    2010-01-01

    In a competitive electricity market, energy price forecasting is an important activity for both suppliers and consumers. For this reason, many techniques have been proposed to predict electricity market prices in the recent years. However, electricity price is a complex volatile signal owning many spikes. Most of electricity price forecast techniques focus on the normal price prediction, while price spike forecast is a different and more complex prediction process. Price spike forecasting has two main aspects: prediction of price spike occurrence and value. In this paper, a novel technique for price spike occurrence prediction is presented composed of a new hybrid data model, a novel feature selection technique and an efficient forecast engine. The hybrid data model includes both wavelet and time domain variables as well as calendar indicators, comprising a large candidate input set. The set is refined by the proposed feature selection technique evaluating both relevancy and redundancy of the candidate inputs. The forecast engine is a probabilistic neural network, which are fed by the selected candidate inputs of the feature selection technique and predict price spike occurrence. The efficiency of the whole proposed method for price spike occurrence forecasting is evaluated by means of real data from the Queensland and PJM electricity markets. (author)

  4. Neonatal NMDA receptor blockade disrupts spike timing and glutamatergic synapses in fast spiking interneurons in a NMDA receptor hypofunction model of schizophrenia.

    Directory of Open Access Journals (Sweden)

    Kevin S Jones

    Full Text Available The dysfunction of parvalbumin-positive, fast-spiking interneurons (FSI is considered a primary contributor to the pathophysiology of schizophrenia (SZ, but deficits in FSI physiology have not been explicitly characterized. We show for the first time, that a widely-employed model of schizophrenia minimizes first spike latency and increases GluN2B-mediated current in neocortical FSIs. The reduction in FSI first-spike latency coincides with reduced expression of the Kv1.1 potassium channel subunit which provides a biophysical explanation for the abnormal spiking behavior. Similarly, the increase in NMDA current coincides with enhanced expression of the GluN2B NMDA receptor subunit, specifically in FSIs. In this study mice were treated with the NMDA receptor antagonist, MK-801, during the first week of life. During adolescence, we detected reduced spike latency and increased GluN2B-mediated NMDA current in FSIs, which suggests transient disruption of NMDA signaling during neonatal development exerts lasting changes in the cellular and synaptic physiology of neocortical FSIs. Overall, we propose these physiological disturbances represent a general impairment to the physiological maturation of FSIs which may contribute to schizophrenia-like behaviors produced by this model.

  5. Transcriptome Analysis for Abnormal Spike Development of the Wheat Mutant dms.

    Directory of Open Access Journals (Sweden)

    Xin-Xin Zhu

    Full Text Available Wheat (Triticum aestivum L. spike development is the foundation for grain yield. We obtained a novel wheat mutant, dms, characterized as dwarf, multi-pistil and sterility. Although the genetic changes are not clear, the heredity of traits suggests that a recessive gene locus controls the two traits of multi-pistil and sterility in self-pollinating populations of the medium plants (M, such that the dwarf genotype (D and tall genotype (T in the progeny of the mutant are ideal lines for studies regarding wheat spike development. The objective of this study was to explore the molecular basis for spike abnormalities of dwarf genotype.Four unigene libraries were assembled by sequencing the mRNAs of the super-bulked differentiating spikes and stem tips of the D and T plants. Using integrative analysis, we identified 419 genes highly expressed in spikes, including nine typical homeotic genes of the MADS-box family and the genes TaAP2, TaFL and TaDL. We also identified 143 genes that were significantly different between young spikes of T and D, and 26 genes that were putatively involved in spike differentiation. The result showed that the expression levels of TaAP1-2, TaAP2, and other genes involved in the majority of biological processes such as transcription, translation, cell division, photosynthesis, carbohydrate transport and metabolism, and energy production and conversion were significantly lower in D than in T.We identified a set of genes related to wheat floral organ differentiation, including typical homeotic genes. Our results showed that the major causal factors resulting in the spike abnormalities of dms were the lower expression homeotic genes, hormonal imbalance, repressed biological processes, and deficiency of construction materials and energy. We performed a series of studies on the homeotic genes, however the other three causal factors for spike abnormal phenotype of dms need further study.

  6. Transcriptome Analysis for Abnormal Spike Development of the Wheat Mutant dms.

    Science.gov (United States)

    Zhu, Xin-Xin; Li, Qiao-Yun; Shen, Chun-Cai; Duan, Zong-Biao; Yu, Dong-Yan; Niu, Ji-Shan; Ni, Yong-Jing; Jiang, Yu-Mei

    2016-01-01

    Wheat (Triticum aestivum L.) spike development is the foundation for grain yield. We obtained a novel wheat mutant, dms, characterized as dwarf, multi-pistil and sterility. Although the genetic changes are not clear, the heredity of traits suggests that a recessive gene locus controls the two traits of multi-pistil and sterility in self-pollinating populations of the medium plants (M), such that the dwarf genotype (D) and tall genotype (T) in the progeny of the mutant are ideal lines for studies regarding wheat spike development. The objective of this study was to explore the molecular basis for spike abnormalities of dwarf genotype. Four unigene libraries were assembled by sequencing the mRNAs of the super-bulked differentiating spikes and stem tips of the D and T plants. Using integrative analysis, we identified 419 genes highly expressed in spikes, including nine typical homeotic genes of the MADS-box family and the genes TaAP2, TaFL and TaDL. We also identified 143 genes that were significantly different between young spikes of T and D, and 26 genes that were putatively involved in spike differentiation. The result showed that the expression levels of TaAP1-2, TaAP2, and other genes involved in the majority of biological processes such as transcription, translation, cell division, photosynthesis, carbohydrate transport and metabolism, and energy production and conversion were significantly lower in D than in T. We identified a set of genes related to wheat floral organ differentiation, including typical homeotic genes. Our results showed that the major causal factors resulting in the spike abnormalities of dms were the lower expression homeotic genes, hormonal imbalance, repressed biological processes, and deficiency of construction materials and energy. We performed a series of studies on the homeotic genes, however the other three causal factors for spike abnormal phenotype of dms need further study.

  7. Which spike train distance is most suitable for distinguishing rate and temporal coding?

    Science.gov (United States)

    Satuvuori, Eero; Kreuz, Thomas

    2018-04-01

    It is commonly assumed in neuronal coding that repeated presentations of a stimulus to a coding neuron elicit similar responses. One common way to assess similarity are spike train distances. These can be divided into spike-resolved, such as the Victor-Purpura and the van Rossum distance, and time-resolved, e.g. the ISI-, the SPIKE- and the RI-SPIKE-distance. We use independent steady-rate Poisson processes as surrogates for spike trains with fixed rate and no timing information to address two basic questions: How does the sensitivity of the different spike train distances to temporal coding depend on the rates of the two processes and how do the distances deal with very low rates? Spike-resolved distances always contain rate information even for parameters indicating time coding. This is an issue for reasonably high rates but beneficial for very low rates. In contrast, the operational range for detecting time coding of time-resolved distances is superior at normal rates, but these measures produce artefacts at very low rates. The RI-SPIKE-distance is the only measure that is sensitive to timing information only. While our results on rate-dependent expectation values for the spike-resolved distances agree with Chicharro et al. (2011), we here go one step further and specifically investigate applicability for very low rates. The most appropriate measure depends on the rates of the data being analysed. Accordingly, we summarize our results in one table that allows an easy selection of the preferred measure for any kind of data. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

  8. Scikit-spectra: Explorative Spectroscopy in Python

    Directory of Open Access Journals (Sweden)

    Adam Hughes

    2015-06-01

    Full Text Available Scikit-spectra is an intuitive framework for explorative spectroscopy in Python. Scikit-spectra leverages the Pandas library for powerful data processing to provide datastructures and an API designed for spectroscopy. Utilizing the new IPython Notebook widget system, scikit-spectra is headed towards a GUI when you want it, API when you need it approach to spectral analysis. As an application, analysis is presented of the surface-plasmon resonance shift in a solution of gold nanoparticles induced by proteins binding to the gold’s surface. Please refer to the scikit-spectra website for full documentation and support: http://hugadams.github.io/scikit-spectra/

  9. Polychlorinated biphenyl (PCB) recovery from spiked organic matrix using accelerated solvent extraction (ASE) and Soxhlet extraction.

    Science.gov (United States)

    Abrha, Y; Raghavan, D

    2000-12-30

    The recovery of five PCB congeners from PCB spiked organic matrices was studied using Accelerated solvent extraction (ASE) and Soxhlet extraction (SE). The chromatogram of ASE extract was found to be relatively clean and similar to that of SE extract. ASE extraction efficiency was dependent on the operation temperature and sample size loading. ASE showed extraction efficiency comparable or slightly higher to that of SE for the PCB spiked organic matrix. PCB recovery from spiked matrix was dependent on the type and molecular weight of congener, and nature of matrix. For some selected PCB congeners, ortho-substitution did influence the PCB recovery from graphite matrix.

  10. Immunogenic Display of Purified Chemically Cross-Linked HIV-1 Spikes

    Science.gov (United States)

    Leaman, Daniel P.; Lee, Jeong Hyun; Ward, Andrew B.

    2015-01-01

    ABSTRACT HIV-1 envelope glycoprotein (Env) spikes are prime vaccine candidates, at least in principle, but suffer from instability, molecular heterogeneity and a low copy number on virions. We anticipated that chemical cross-linking of HIV-1 would allow purification and molecular characterization of trimeric Env spikes, as well as high copy number immunization. Broadly neutralizing antibodies bound tightly to all major quaternary epitopes on cross-linked spikes. Covalent cross-linking of the trimer also stabilized broadly neutralizing epitopes, although surprisingly some individual epitopes were still somewhat sensitive to heat or reducing agent. Immunodepletion using non-neutralizing antibodies to gp120 and gp41 was an effective method for removing non-native-like Env. Cross-linked spikes, purified via an engineered C-terminal tag, were shown by negative stain EM to have well-ordered, trilobed structure. An immunization was performed comparing a boost with Env spikes on virions to spikes cross-linked and captured onto nanoparticles, each following a gp160 DNA prime. Although differences in neutralization did not reach statistical significance, cross-linked Env spikes elicited a more diverse and sporadically neutralizing antibody response against Tier 1b and 2 isolates when displayed on nanoparticles, despite attenuated binding titers to gp120 and V3 crown peptides. Our study demonstrates display of cross-linked trimeric Env spikes on nanoparticles, while showing a level of control over antigenicity, purity and density of virion-associated Env, which may have relevance for Env based vaccine strategies for HIV-1. IMPORTANCE The envelope spike (Env) is the target of HIV-1 neutralizing antibodies, which a successful vaccine will need to elicit. However, native Env on virions is innately labile, as well as heterogeneously and sparsely displayed. We therefore stabilized Env spikes using a chemical cross-linker and removed non-native Env by immunodepletion with non

  11. Modeling degradation in SOEC impedance spectra

    DEFF Research Database (Denmark)

    Jensen, Søren Højgaard; Hauch, Anne; Knibbe, Ruth

    2013-01-01

    Solid oxide cell (SOC) performance is limited by various processes. One way to investigate these processes is by electrochemical impedance spectroscopy. In order to quantify and characterize the processes, an equivalent circuit can be used to model the SOC impedance spectra (IS). Unfortunately......, the optimal equivalent circuit is often unknown and to complicate matters further, several processes contribute to the SOC impedance - making detailed process characterization difficult. In this work we analyze and model a series of IS measured during steam electrolysis operation of an SOC. During testing......, degradation is only observed in the Ni/YSZ electrode and not in the electrolyte or the LSM/YSZ electrode. A batch fit of the differences between the IS shows that a modified Gerischer element provides a better fit to the Ni/YSZ electrode impedance than the frequently used RQ element - albeit neither...

  12. Effects of potassium concentration on firing patterns of low-calcium epileptiform activity in anesthetized rat hippocampus: inducing of persistent spike activity.

    Science.gov (United States)

    Feng, Zhouyan; Durand, Dominique M

    2006-04-01

    It has been shown that a low-calcium high-potassium solution can generate ictal-like epileptiform activity in vitro and in vivo. Moreover, during status epileptiform activity, the concentration of [K+]o increases, and the concentration of [Ca2+]o decreases in brain tissue. Therefore we tested the hypothesis that long-lasting persistent spike activity, similar to one of the patterns of status epilepticus, could be generated by a high-potassium, low-calcium solution in the hippocampus in vivo. Artificial cerebrospinal fluid was perfused over the surface of the exposed left dorsal hippocampus of anesthetized rats. A stimulating electrode and a recording probe were placed in the CA1 region. By elevating K+ concentration from 6 to 12 mM in the perfusate solution, the typical firing pattern of low-calcium ictal bursts was transformed into persistent spike activity in the CA1 region with synaptic transmission being suppressed by calcium chelator EGTA. The activity was characterized by double spikes repeated at a frequency approximately 4 Hz that could last for >1 h. The analysis of multiple unit activity showed that both elevating [K+]o and lowering [Ca2+]o decreased the inhibition period after the response of paired-pulse stimulation, indicating a suppression of the after-hyperpolarization (AHP) activity. These results suggest that persistent status epilepticus-like spike activity can be induced by nonsynaptic mechanisms when synaptic transmission is blocked. The unique double-spike pattern of this activity is presumably caused by higher K+ concentration augmenting the frequency of typical low-calcium nonsynaptic burst activity.

  13. Different spectra with the same neutron source

    Energy Technology Data Exchange (ETDEWEB)

    Vega C, H. R.; Ortiz R, J. M.; Hernandez D, V. M.; Martinez B, M. R.; Hernandez A, B.; Ortiz H, A. A. [Universidad Autonoma de Zacatecas, Unidad Academica de Estudios Nucleares, Calle Cipres No. 10, Fracc. La Penuela, 98068 Zacatecas (Mexico); Mercado, G. A., E-mail: fermineutron@yahoo.co [Universidad Autonoma de Zacatecas, Unidad Academica de Matematicas, Jardin Juarez No. 147, 98000 Zacatecas (Mexico)

    2010-02-15

    Using as source term the spectrum of a {sup 239}Pu-Be source several neutron spectra have been calculated using Monte Carlo methods. The source term was located in the centre of spherical moderators made of light water, heavy water and polyethylene of different diameters. Also a {sup 239}Pu-Be source was used to measure its neutron spectrum, bare and moderated by water. The neutron spectra were measured at 100 cm with a Bonner spheres spectrometer. Monte Carlo calculations were used to calculate the neutron spectra of bare and water-moderated spectra that were compared with those measured with the spectrometer. Resulting spectra are similar to those found in power plants with PWR, BWR and Candu nuclear reactors. Beside the spectra the dosimetric features were determined. Using moderators and a single neutron source can be produced neutron spectra alike those found in workplaces, this neutron fields can be utilized to calibrate neutron dosimeters and area monitors. (Author)

  14. Different spectra with the same neutron source

    International Nuclear Information System (INIS)

    Vega C, H. R.; Ortiz R, J. M.; Hernandez D, V. M.; Martinez B, M. R.; Hernandez A, B.; Ortiz H, A. A.; Mercado, G. A.

    2010-01-01

    Using as source term the spectrum of a 239 Pu-Be source several neutron spectra have been calculated using Monte Carlo methods. The source term was located in the centre of spherical moderators made of light water, heavy water and polyethylene of different diameters. Also a 239 Pu-Be source was used to measure its neutron spectrum, bare and moderated by water. The neutron spectra were measured at 100 cm with a Bonner spheres spectrometer. Monte Carlo calculations were used to calculate the neutron spectra of bare and water-moderated spectra that were compared with those measured with the spectrometer. Resulting spectra are similar to those found in power plants with PWR, BWR and Candu nuclear reactors. Beside the spectra the dosimetric features were determined. Using moderators and a single neutron source can be produced neutron spectra alike those found in workplaces, this neutron fields can be utilized to calibrate neutron dosimeters and area monitors. (Author)

  15. Imaging Emission Spectra with Handheld and Cellphone Cameras

    Science.gov (United States)

    Sitar, David

    2012-01-01

    As point-and-shoot digital camera technology advances it is becoming easier to image spectra in a laboratory setting on a shoestring budget and get immediate results. With this in mind, I wanted to test three cameras to see how their results would differ. Two undergraduate physics students and I used one handheld 7.1 megapixel (MP) digital Cannon…

  16. Towards a full reference library of MS(n) spectra. II: A perspective from the library of pesticide spectra extracted from the literature/Internet.

    Science.gov (United States)

    Milman, Boris L; Zhurkovich, Inna K

    2011-12-30

    To gain perspective on building full transferable libraries of MS(n) spectra from their diverse/numerous collections, a new library was built from 1723 MS(>1) spectra (mainly MS² spectra) of 490 pesticides and related compounds. Spectra acquired on different types of tandem instruments in various experimental conditions were extracted from 168 literature articles and Internet sites. Testing of the library was based on searches where 'unknown' and reference spectra originated from different sources (mainly from different laboratories) were cross-compared. The NIST 05 MS² library was added to the reference spectra. The library searches were performed with all the test spectra or were divided into different subsamples containing (a) various numbers of replicate spectra of test compounds or (b) spectra acquired from different instrument types. Thus, the dependence of true/false search (identification) result rates on different factors was explored. The percentage of 1st rank correct identifications (true positives) for the only 'unknown' mass spectrum and two and more reference spectra and matching precursor ion m/z values was 89%. For qualified matches, above the cut-off match factor, that rate decreased to 80%. The corresponding rates based on the best match for two and more 'unknown' and reference spectral replicates were 89-94%. For quadrupole instruments, the rates were even higher: 91-95% (one 'unknown' spectrum) and 90-100% (two and more such spectra). This study shows that MS² spectral libraries generated from the numerous literature/Internet sources are not less efficient for the goal of identification of unknown compounds including pesticides than very common EI-MS¹ libraries and are almost as efficient as the most productive from current MS² spectral databases. Such libraries may be used as individual reference databases or supplements to large experimental spectral collections covering many groups of abundant compounds and different types of tandem

  17. Parameterization of MARVELS Spectra Using Deep Learning

    Science.gov (United States)

    Gilda, Sankalp; Ge, Jian; MARVELS

    2018-01-01

    Like many large-scale surveys, the Multi-Object APO Radial Velocity Exoplanet Large-area Survey (MARVELS) was designed to operate at a moderate spectral resolution ($\\sim$12,000) for efficiency in observing large samples, which makes the stellar parameterization difficult due to the high degree of blending of spectral features. Two extant solutions to deal with this issue are to utilize spectral synthesis, and to utilize spectral indices [Ghezzi et al. 2014]. While the former is a powerful and tested technique, it can often yield strongly coupled atmospheric parameters, and often requires high spectral resolution (Valenti & Piskunov 1996). The latter, though a promising technique utilizing measurements of equivalent widths of spectral indices, has only been employed with respect to FKG dwarfs and sub-giants and not red-giant branch stars, which constitute ~30% of MARVELS targets. In this work, we tackle this problem using a convolution neural network (CNN). In particular, we train a one-dimensional CNN on appropriately processed PHOENIX synthetic spectra using supervised training to automatically distinguish the features relevant for the determination of each of the three atmospheric parameters – T_eff, log(g), [Fe/H] – and use the knowledge thus gained by the network to parameterize 849 MARVELS giants. When tested on the synthetic spectra themselves, our estimates of the parameters were consistent to within 11 K, .02 dex, and .02 dex (in terms of mean absolute errors), respectively. For MARVELS dwarfs, the accuracies are 80K, .16 dex and .10 dex, respectively.

  18. Reversible electrokinetic adsorption barriers for the removal of atrazine and oxyfluorfen from spiked soils.

    Science.gov (United States)

    Vieira Dos Santos, E; Sáez, C; Cañizares, P; Martínez-Huitle, C A; Rodrigo, M A

    2017-01-15

    This study demonstrates the application of reversible electrokinetic adsorption barrier (REKAB) technology to soils spiked with low-solubility pollutants. A permeable reactive barrier (PRB) of granular activated carbon (GAC) was placed between the anode and cathode of an electrokinetic (EK) soil remediation bench-scale setup with the aim of enhancing the removal of two low-solubility herbicides (atrazine and oxyfluorfen) using a surfactant solution (sodium dodecyl sulfate) as the flushing fluid. This innovative study focused on evaluating the interaction between the EK system and the GAC-PRB, attempting to obtain insights into the primary mechanisms involved. The obtained results highlighted the successful treatment of atrazine and oxyfluorfen in contaminated soils. The results obtained from the tests after 15days of treatment were compared with those obtained using the more conventional electrokinetic soil flushing (EKSF) technology, and very important differences were observed. Although both technologies are efficient for removing the herbicides from soils, REKAB outperforms EKSF. After the 15-day treatment tests, only approximately 10% of atrazine and oxyfluorfen remained in the soil, and adsorption onto the GAC bed was an important removal mechanism (15-17% of herbicide retained). The evaporation loses in REKAB were lower than those obtained in EKSF (45-50% compared to 60-65%). Copyright © 2016 Elsevier B.V. All rights reserved.

  19. Graviton spectra in string cosmology

    Energy Technology Data Exchange (ETDEWEB)

    Galluccio, Massimo [Osservatorio Astronomico di Roma (Roma-IT); Litterio, Marco [Istituto Astronomico dell' Universita (Roma-IT); Occhionero, Franco [Osservatorio Astronomico di Roma (Roma-IT)

    1996-08-01

    We propose to uncover the signature of a stringy era in the primordial Universe by searching for a prominent peak in the relic graviton spectrum. This feature, which in our specific model terminates an ω³ increase and initiates an ω⁻⁷ decrease, is induced during the so far overlooked bounce of the scale factor between the collapsing deflationary era (or pre-Big Bang) and the expanding inflationary era (or post-Big Bang). We evaluate both analytically and numerically the frequency and the intensity of the peak and we show that they may likely fall in the realm of the new generation of interferometric detectors. The existence of a peak is at variance with ordinarily monotonic (either increasing or decreasing) graviton spectra of canonical cosmologies; its detection would therefore offer strong support to string cosmology.

  20. Just-in-time connectivity for large spiking networks.

    Science.gov (United States)

    Lytton, William W; Omurtag, Ahmet; Neymotin, Samuel A; Hines, Michael L

    2008-11-01

    The scale of large neuronal network simulations is memory limited due to the need to store connectivity information: connectivity storage grows as the square of neuron number up to anatomically relevant limits. Using the NEURON simulator as a discrete-event simulator (no integration), we explored the consequences of avoiding the space costs of connectivity through regenerating connectivity parameters when needed: just in time after a presynaptic cell fires. We explored various strategies for automated generation of one or more of the basic static connectivity parameters: delays, postsynaptic cell identities, and weights, as well as run-time connectivity state: the eve