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

Peptide Mimicrying Between SARS Coronavirus Spike Protein and Human Proteins Reacts with SARS Patient Serum

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K.-Y. Hwa

2008-01-01

Full Text Available Molecular mimicry, defined as similar structures shared by molecules from dissimilar genes or proteins, is a general strategy used by pathogens to infect host cells. Severe acute respiratory syndrome (SARS is a new human respiratory infectious disease caused by SARS coronavirus (SARS-CoV. The spike (S protein of SARS-CoV plays an important role in the virus entry into a cell. In this study, eleven synthetic peptides from the S protein were selected based on its sequence homology with human proteins. Two of the peptides D07 (residues 927–937 and D08 (residues 942–951 were recognized by the sera of SARS patients. Murine hyperimmune sera against these peptides bound to proteins of human lung epithelial cells A549. Another peptide D10 (residues 490–502 stimulated A549 to proliferate and secrete IL-8. The present results suggest that the selected S protein regions, which share sequence homology with human proteins, may play important roles in SARS-CoV infection.

Activation of mGluR5 induces spike afterdepolarization and enhanced excitability in medium spiny neurons of the nucleus accumbens by modulating persistent Na+ currents

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D’Ascenzo, Marcello; Podda, Maria Vittoria; Fellin, Tommaso; Azzena, Gian Battista; Haydon, Philip; Grassi, Claudio

2009-01-01

The involvement of metabotropic glutamate receptors type 5 (mGluR5) in drug-induced behaviours is well-established but limited information is available on their functional roles in addiction-relevant brain areas like the nucleus accumbens (NAc). This study demonstrates that pharmacological and synaptic activation of mGluR5 increases the spike discharge of medium spiny neurons (MSNs) in the NAc. This effect was associated with the appearance of a slow afterdepolarization (ADP) which, in voltage-clamp experiments, was recorded as a slowly inactivating inward current. Pharmacological studies showed that ADP was elicited by mGluR5 stimulation via G-protein-dependent activation of phospholipase C and elevation of intracellular Ca2+ levels. Both ADP and spike aftercurrents were significantly inhibited by the Na+ channel-blocker, tetrodotoxin (TTX). Moreover, the selective blockade of persistent Na+ currents (INaP), achieved by NAc slice pre-incubation with 20 nm TTX or 10 μm riluzole, significantly reduced the ADP amplitude, indicating that this type of Na+ current is responsible for the mGluR5-dependent ADP. mGluR5 activation also produced significant increases in INaP, and the pharmacological blockade of this current prevented the mGluR5-induced enhancement of spike discharge. Collectively, these data suggest that mGluR5 activation upregulates INaP in MSNs of the NAc, thereby inducing an ADP that results in enhanced MSN excitability. Activation of mGluR5 will significantly alter spike firing in MSNs in vivo, and this effect could be an important mechanism by which these receptors mediate certain aspects of drug-induced behaviours. PMID:19433572

Mechanisms of Coronavirus Cell Entry Mediated by the Viral Spike Protein

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Gary R. Whittaker

2012-06-01

Full Text Available Coronaviruses are enveloped positive-stranded RNA viruses that replicate in the cytoplasm. To deliver their nucleocapsid into the host cell, they rely on the fusion of their envelope with the host cell membrane. The spike glycoprotein (S mediates virus entry and is a primary determinant of cell tropism and pathogenesis. It is classified as a class I fusion protein, and is responsible for binding to the receptor on the host cell as well as mediating the fusion of host and viral membranes—A process driven by major conformational changes of the S protein. This review discusses coronavirus entry mechanisms focusing on the different triggers used by coronaviruses to initiate the conformational change of the S protein: receptor binding, low pH exposure and proteolytic activation. We also highlight commonalities between coronavirus S proteins and other class I viral fusion proteins, as well as distinctive features that confer distinct tropism, pathogenicity and host interspecies transmission characteristics to coronaviruses.

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.

Investigation of Near-Surface Defects Induced by Spike Rapid Thermal Annealing in c-SILICON Solar Cells

Science.gov (United States)

Liu, Guodong; Ren, Pan; Zhang, Dayong; Wang, Weiping; Li, Jianfeng

2016-01-01

The defects induced by a spike rapid thermal annealing (RTA) process in crystalline silicon (c-Si) solar cells were investigated by the photoluminescence (PL) technique and the transmission electron microscopy (TEM), respectively. Dislocation defects were found to form in the near-surface junction region of the monocrystalline Si solar cell after a spike RTA process was performed at 1100∘C. Photo J-V characteristics were measured on the Si solar cell before and after the spike RTA treatments to reveal the effects of defects on the Si cell performances. In addition, the Silvaco device simulation program was used to study the effects of defects density on the cell performances by fitting the experimental data of RTA-treated cells. The results demonstrate that there was an obvious degradation in the Si solar cell performances when the defect density after the spike RTA treatment was above 1×1013cm-3.

Cortical plasticity induced by spike-triggered microstimulation in primate somatosensory cortex.

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Weiguo Song

Full Text Available Electrical stimulation of the nervous system for therapeutic purposes, such as deep brain stimulation in the treatment of Parkinson's disease, has been used for decades. Recently, increased attention has focused on using microstimulation to restore functions as diverse as somatosensation and memory. However, how microstimulation changes the neural substrate is still not fully understood. Microstimulation may cause cortical changes that could either compete with or complement natural neural processes, and could result in neuroplastic changes rendering the region dysfunctional or even epileptic. As part of our efforts to produce neuroprosthetic devices and to further study the effects of microstimulation on the cortex, we stimulated and recorded from microelectrode arrays in the hand area of the primary somatosensory cortex (area 1 in two awake macaque monkeys. We applied a simple neuroprosthetic microstimulation protocol to a pair of electrodes in the area 1 array, using either random pulses or pulses time-locked to the recorded spiking activity of a reference neuron. This setup was replicated using a computer model of the thalamocortical system, which consisted of 1980 spiking neurons distributed among six cortical layers and two thalamic nuclei. Experimentally, we found that spike-triggered microstimulation induced cortical plasticity, as shown by increased unit-pair mutual information, while random microstimulation did not. In addition, there was an increased response to touch following spike-triggered microstimulation, along with decreased neural variability. The computer model successfully reproduced both qualitative and quantitative aspects of the experimental findings. The physiological findings of this study suggest that even simple microstimulation protocols can be used to increase somatosensory information flow.

Replication of murine coronavirus requires multiple cysteines in the endodomain of spike protein

International Nuclear Information System (INIS)

Yang, Jinhua; Lv, Jun; Wang, Yuyan; Gao, Shuang; Yao, Qianqian; Qu, Di; Ye, Rong

2012-01-01

A conserved cysteine-rich motif located between the transmembrane domain and the endodomain is essential for membrane fusion and assembly of coronavirus spike (S) protein. Here, we proved that three cysteines within the motif, but not dependent on position, are minimally required for the survival of the recombinant mouse hepatitis virus. When the carboxy termini with these mutated motifs of S proteins were respectively introduced into a heterogeneous protein, both incorporation into lipid rafts and S-palmitoylation of these recombinant proteins showed a similar quantity requirement to cysteine residues. Meanwhile, the redistribution of these proteins on cellular surface indicated that the absence of the positively charged rather than cysteine residues in the motif might lead the dramatic reduction in syncytial formation of some mutants with the deleted motifs. These results suggest that multiple cysteine as well as charged residues concurrently improves the membrane-associated functions of S protein in viral replication and cytopathogenesis.

Replication of murine coronavirus requires multiple cysteines in the endodomain of spike protein

Energy Technology Data Exchange (ETDEWEB)

Yang, Jinhua; Lv, Jun; Wang, Yuyan; Gao, Shuang; Yao, Qianqian; Qu, Di; Ye, Rong, E-mail: yerong24@fudan.edu.cn

2012-06-05

A conserved cysteine-rich motif located between the transmembrane domain and the endodomain is essential for membrane fusion and assembly of coronavirus spike (S) protein. Here, we proved that three cysteines within the motif, but not dependent on position, are minimally required for the survival of the recombinant mouse hepatitis virus. When the carboxy termini with these mutated motifs of S proteins were respectively introduced into a heterogeneous protein, both incorporation into lipid rafts and S-palmitoylation of these recombinant proteins showed a similar quantity requirement to cysteine residues. Meanwhile, the redistribution of these proteins on cellular surface indicated that the absence of the positively charged rather than cysteine residues in the motif might lead the dramatic reduction in syncytial formation of some mutants with the deleted motifs. These results suggest that multiple cysteine as well as charged residues concurrently improves the membrane-associated functions of S protein in viral replication and cytopathogenesis.

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

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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

Detection of bursts in neuronal spike trains by the mean inter-spike interval method

Institute of Scientific and Technical Information of China (English)

Lin Chen; Yong Deng; Weihua Luo; Zhen Wang; Shaoqun Zeng

2009-01-01

Bursts are electrical spikes firing with a high frequency, which are the most important property in synaptic plasticity and information processing in the central nervous system. However, bursts are difficult to identify because bursting activities or patterns vary with phys-iological conditions or external stimuli. In this paper, a simple method automatically to detect bursts in spike trains is described. This method auto-adaptively sets a parameter (mean inter-spike interval) according to intrinsic properties of the detected burst spike trains, without any arbitrary choices or any operator judgrnent. When the mean value of several successive inter-spike intervals is not larger than the parameter, a burst is identified. By this method, bursts can be automatically extracted from different bursting patterns of cultured neurons on multi-electrode arrays, as accurately as by visual inspection. Furthermore, significant changes of burst variables caused by electrical stimulus have been found in spontaneous activity of neuronal network. These suggest that the mean inter-spike interval method is robust for detecting changes in burst patterns and characteristics induced by environmental alterations.

Synthesis of Salt Soluble Proteins in Barley. Pulse-Labeling Study of Grain Filling in Liquid-Cultured Detached Spikes

DEFF Research Database (Denmark)

Giese, Nanna Henriette; Hejgaard, Jørn

1984-01-01

The accumulation of salt-soluble proteins in the endosperm of developing barley (Hordeum vulgare L.) grains was examined. Detached spikes of barley were cultured at different levels of nitrogen nutrition and pulse-labeled with [14C] sucrose at specific times after anthesis. Proteins were extracted...... to increased nitrogen nutrition. Two major components, β-amylase and protein Z in particular, had a synthesis profile almost identical to that of the endosperm storage protein, hordein....

A truncated receptor-binding domain of MERS-CoV spike protein potently inhibits MERS-CoV infection and induces strong neutralizing antibody responses: implication for developing therapeutics and vaccines.

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Lanying Du

Full Text Available An emerging respiratory infectious disease with high mortality, Middle East respiratory syndrome (MERS, is caused by a novel coronavirus (MERS-CoV. It was first reported in 2012 in Saudi Arabia and has now spread to eight countries. Development of effective therapeutics and vaccines is crucial to save lives and halt the spread of MERS-CoV. Here, we show that a recombinant protein containing a 212-amino acid fragment (residues 377-588 in the truncated receptor-binding domain (RBD: residues 367-606 of MERS-CoV spike (S protein fused with human IgG Fc fragment (S377-588-Fc is highly expressed in the culture supernatant of transfected 293T cells. The purified S377-588-Fc protein efficiently binds to dipeptidyl peptidase 4 (DPP4, the receptor of MERS-CoV, and potently inhibited MERS-CoV infection, suggesting its potential to be further developed as a therapeutic modality for treating MERS-CoV infection and saving the patients' lives. The recombinant S377-588-Fc is able to induce in the vaccinated mice strong MERS-CoV S-specific antibodies, which blocks the binding of RBD to DPP4 receptor and effectively neutralizes MERS-CoV infection. These findings indicate that this truncated RBD protein shows promise for further development as an effective and safe vaccine for the prevention of MERS-CoV infection.

Spike Protein Fusion Peptide and Feline Coronavirus Virulence

Science.gov (United States)

Chang, Hui-Wen; Egberink, Herman F.; Halpin, Rebecca; Spiro, David J.

2012-01-01

Coronaviruses are well known for their potential to change their host or tissue tropism, resulting in unpredictable new diseases and changes in pathogenicity; severe acute respiratory syndrome and feline coronaviruses, respectively, are the most recognized examples. Feline coronaviruses occur as 2 pathotypes: nonvirulent feline enteric coronaviruses (FECVs), which replicate in intestinal epithelium cells, and lethal feline infectious peritonitis viruses (FIPVs), which replicate in macrophages. Evidence indicates that FIPV originates from FECV by mutation, but consistent distinguishing differences have not been established. We sequenced the full genome of 11 viruses of each pathotype and then focused on the single most distinctive site by additionally sequencing hundreds of viruses in that region. As a result, we identified 2 alternative amino acid differences in the putative fusion peptide of the spike protein that together distinguish FIPV from FECV in >95% of cases. By these and perhaps other mutations, the virus apparently acquires its macrophage tropism and spreads systemically. PMID:22709821

A camel-derived MERS-CoV with a variant spike protein cleavage site and distinct fusion activation properties

Science.gov (United States)

Millet, Jean Kaoru; Goldstein, Monty E; Labitt, Rachael N; Hsu, Hung-Lun; Daniel, Susan; Whittaker, Gary R

2016-01-01

Middle East respiratory syndrome coronavirus (MERS-CoV) continues to circulate in both humans and camels, and the origin and evolution of the virus remain unclear. Here we characterize the spike protein of a camel-derived MERS-CoV (NRCE-HKU205) identified in 2013, early in the MERS outbreak. NRCE-HKU205 spike protein has a variant cleavage motif with regard to the S2′ fusion activation site—notably, a novel substitution of isoleucine for the otherwise invariant serine at the critical P1′ cleavage site position. The substitutions resulted in a loss of furin-mediated cleavage, as shown by fluorogenic peptide cleavage and western blot assays. Cell–cell fusion and pseudotyped virus infectivity assays demonstrated that the S2′ substitutions decreased spike-mediated fusion and viral entry. However, cathepsin and trypsin-like protease activation were retained, albeit with much reduced efficiency compared with the prototypical EMC/2012 human strain. We show that NRCE-HKU205 has more limited fusion activation properties possibly resulting in more restricted viral tropism and may represent an intermediate in the complex pattern of MERS-CoV ecology and evolution. PMID:27999426

Orthobunyavirus ultrastructure and the curious tripodal glycoprotein spike.

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Thomas A Bowden

Full Text Available The genus Orthobunyavirus within the family Bunyaviridae constitutes an expanding group of emerging viruses, which threaten human and animal health. Despite the medical importance, little is known about orthobunyavirus structure, a prerequisite for understanding virus assembly and entry. Here, using electron cryo-tomography, we report the ultrastructure of Bunyamwera virus, the prototypic member of this genus. Whilst Bunyamwera virions are pleomorphic in shape, they display a locally ordered lattice of glycoprotein spikes. Each spike protrudes 18 nm from the viral membrane and becomes disordered upon introduction to an acidic environment. Using sub-tomogram averaging, we derived a three-dimensional model of the trimeric pre-fusion glycoprotein spike to 3-nm resolution. The glycoprotein spike consists mainly of the putative class-II fusion glycoprotein and exhibits a unique tripod-like arrangement. Protein-protein contacts between neighbouring spikes occur at membrane-proximal regions and intra-spike contacts at membrane-distal regions. This trimeric assembly deviates from previously observed fusion glycoprotein arrangements, suggesting a greater than anticipated repertoire of viral fusion glycoprotein oligomerization. Our study provides evidence of a pH-dependent conformational change that occurs during orthobunyaviral entry into host cells and a blueprint for the structure of this group of emerging pathogens.

pH-induced conformational change of the rotavirus VP4 spike: implications for cell entry and antibody neutralization.

Science.gov (United States)

Pesavento, Joseph B; Crawford, Sue E; Roberts, Ed; Estes, Mary K; Prasad, B V Venkataram

2005-07-01

The rotavirus spike protein, VP4, is a major determinant of infectivity and neutralization. Previously, we have shown that trypsin-enhanced infectivity of rotavirus involves a transformation of the VP4 spike from a flexible to a rigid bilobed structure. Here we show that at elevated pH the spike undergoes a drastic, irreversible conformational change and becomes stunted, with a pronounced trilobed appearance. These particles with altered spikes, at a normal pH of 7.5, despite the loss of infectivity and the ability to hemagglutinate, surprisingly exhibit sialic acid (SA)-independent cell binding in contrast to the SA-dependent cell binding exhibited by native virions. Remarkably, a neutralizing monoclonal antibody that remains bound to spikes throughout the pH changes (pH 7 to 11 and back to pH 7) completely prevents this conformational change, preserving the SA-dependent cell binding and hemagglutinating functions of the virion. A hypothesis that emerges from the present study is that high-pH treatment triggers a conformational change that mimics a post-SA-attachment step to expose an epitope recognized by a downstream receptor in the rotavirus cell entry process. This process involves sequential interactions with multiple receptors, and the mechanism by which the antibody neutralizes is by preventing this conformational change.

Small heat-shock proteins and leaf cooling capacity account for the unusual heat tolerance of the central spike leaves in Agave tequilana var. Weber.

Science.gov (United States)

Luján, Rosario; Lledías, Fernando; Martínez, Luz María; Barreto, Rita; Cassab, Gladys I; Nieto-Sotelo, Jorge

2009-12-01

Agaves are perennial crassulacean acid metabolism (CAM) plants distributed in tropical and subtropical arid environments, features that are attractive for studying the heat-shock response. In agaves, the stress response can be analysed easily during leaf development, as they form a spirally shaped rosette, having the meristem surrounded by folded leaves in the centre (spike) and the unfolded and more mature leaves in the periphery. Here, we report that the spike of Agave tequilana is the most thermotolerant part of the rosette withstanding shocks of up to 55 degrees C. This finding was inconsistent with the patterns of heat-shock protein (Hsp) gene expression, as maximal accumulation of Hsp transcripts was at 44 degrees C in all sectors (spike, inner, middle and outer). However, levels of small HSP (sHSP)-CI and sHSP-CII proteins were conspicuously higher in spike leaves at all temperatures correlating with their thermotolerance. In addition, spike leaves showed a higher stomatal density and abated more efficiently their temperature several degrees below that of air. We propose that the greater capacity for leaf cooling during the day in response to heat stress, and the elevated levels of sHSPs, constitute part of a set of strategies that protect the SAM and folded leaves of A. tequilana from high temperatures.

Mutations of 3c and spike protein genes correlate with the occurrence of feline infectious peritonitis.

Science.gov (United States)

Bank-Wolf, Barbara Regina; Stallkamp, Iris; Wiese, Svenja; Moritz, Andreas; Tekes, Gergely; Thiel, Heinz-Jürgen

2014-10-10

The genes encoding accessory proteins 3a, 3b, 3c, 7a and 7b, the S2 domain of the spike (S) protein gene and the membrane (M) protein gene of feline infectious peritonitis virus (FIPV) and feline enteric coronavirus (FECV) samples were amplified, cloned and sequenced. For this faeces and/or ascites samples from 19 cats suffering from feline infectious peritonitis (FIP) as well as from 20 FECV-infected healthy cats were used. Sequence comparisons revealed that 3c genes of animals with FIP were heavily affected by nucleotide deletions and point mutations compared to animals infected with FECV; these alterations resulted either in early termination or destruction of the translation initiation codon. Two ascites-derived samples of cats with FIP which displayed no alterations of ORF3c harboured mutations in the S2 domain of the S protein gene which resulted in amino acid exchanges or deletions. Moreover, changes in 3c were often accompanied by mutations in S2. In contrast, in samples obtained from faeces of healthy cats, the ORF3c was never affected by such mutations. Similarly ORF3c from faecal samples of the cats with FIP was mostly intact and showed only in a few cases the same mutations found in the respective ascites samples. The genes encoding 3a, 3b, 7a and 7b displayed no mutations linked to the feline coronavirus (FCoV) biotype. The M protein gene was found to be conserved between FECV and FIPV samples. Our findings suggest that mutations of 3c and spike protein genes correlate with the occurrence of FIP. Copyright © 2014 Elsevier B.V. All rights reserved.

Determination of (187)Os in molybdenite by ICP-MS with neutron-induced (186)Os and (188)Os spikes.

Science.gov (United States)

Qu, W; Du, A; Zhao, D

2001-10-31

The article describes a method for the determination of (187)Os in molybdenite by isotope dilution inductively coupled plasma-mass spectrometry (ID-ICP-MS) with neutron-induced (186)Os and (188)Os spike. The spike used in the present work was prepared in line with the principle by which artificial nuclides are produced in a nuclear reaction. The concentration and isotopic composition of osmium in the prepared spike were evaluated accurately with the isotope dilution method, using negative thermal ion mass spectrometry (N-TIMS). The advantage of this method is that using (186)Os and (188)Os double spikes can effectively compensate for the mass discrimination effects of ICP-MS. Thus, the common correction practice for mass bias in the isotope dilution method with a single spike is unnecessary. In addition, the method enables one to reduce the determined error arising from instrumental instability. The precision for the (187)Os/((186)Os+(188)Os) ratio was approximately 2% (2sigma, RSD), but in the case of (187)Os/(186)Os, (187)Os/(188)Os and (186)Os/(188)Os, precision ranged from 2.0 to 8% (2sigma, RSD). The results for (187)Os concentration in a molybdenite sample determined with this method showed good agreement with reference values.

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.

Statistical properties of superimposed stationary spike trains.

Science.gov (United States)

Deger, Moritz; Helias, Moritz; Boucsein, Clemens; Rotter, Stefan

2012-06-01

The Poisson process is an often employed model for the activity of neuronal populations. It is known, though, that superpositions of realistic, non- Poisson spike trains are not in general Poisson processes, not even for large numbers of superimposed processes. Here we construct superimposed spike trains from intracellular in vivo recordings from rat neocortex neurons and compare their statistics to specific point process models. The constructed superimposed spike trains reveal strong deviations from the Poisson model. We find that superpositions of model spike trains that take the effective refractoriness of the neurons into account yield a much better description. A minimal model of this kind is the Poisson process with dead-time (PPD). For this process, and for superpositions thereof, we obtain analytical expressions for some second-order statistical quantities-like the count variability, inter-spike interval (ISI) variability and ISI correlations-and demonstrate the match with the in vivo data. We conclude that effective refractoriness is the key property that shapes the statistical properties of the superposition spike trains. We present new, efficient algorithms to generate superpositions of PPDs and of gamma processes that can be used to provide more realistic background input in simulations of networks of spiking neurons. Using these generators, we show in simulations that neurons which receive superimposed spike trains as input are highly sensitive for the statistical effects induced by neuronal refractoriness.

Remifentanil-induced spike activity as a diagnostic tool in epilepsy surgery

DEFF Research Database (Denmark)

Gronlykke, L.; Knudsen, M.L.; Hogenhaven, H.

2008-01-01

. Electrocorticography (ECoG) recordings were performed on the intraventricular hippocampus and from the anterior inferior temporal and lateral neocortex before and after a 300 microg intravenous bolus of remifentanil. Spike activity was quantified as spike-count per minute. RESULTS: A significant increase (P

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)....

Cleavage of spike protein of SARS coronavirus by protease factor Xa is associated with viral infectivity

International Nuclear Information System (INIS)

Du, Lanying; Kao, Richard Y.; Zhou, Yusen; He, Yuxian; Zhao, Guangyu; Wong, Charlotte; Jiang, Shibo; Yuen, Kwok-Yung; Jin, Dong-Yan; Zheng, Bo-Jian

2007-01-01

The spike (S) protein of SARS coronavirus (SARS-CoV) has been known to recognize and bind to host receptors, whose conformational changes then facilitate fusion between the viral envelope and host cell membrane, leading to viral entry into target cells. However, other functions of SARS-CoV S protein such as proteolytic cleavage and its implications to viral infection are incompletely understood. In this study, we demonstrated that the infection of SARS-CoV and a pseudovirus bearing the S protein of SARS-CoV was inhibited by a protease inhibitor Ben-HCl. Also, the protease Factor Xa, a target of Ben-HCl abundantly expressed in infected cells, was able to cleave the recombinant and pseudoviral S protein into S1 and S2 subunits, and the cleavage was inhibited by Ben-HCl. Furthermore, this cleavage correlated with the infectivity of the pseudovirus. Taken together, our study suggests a plausible mechanism by which SARS-CoV cleaves its S protein to facilitate viral infection

HLA-A*0201 T-cell epitopes in severe acute respiratory syndrome (SARS) coronavirus nucleocapsid and spike proteins

International Nuclear Information System (INIS)

Tsao, Y.-P.; Lin, J.-Y.; Jan, J.-T.; Leng, C.-H.; Chu, C.-C.; Yang, Y.-C.; Chen, S.-L.

2006-01-01

The immunogenicity of HLA-A*0201-restricted cytotoxic T lymphocyte (CTL) peptide in severe acute respiratory syndrome coronavirus (SARS-CoV) nuclear capsid (N) and spike (S) proteins was determined by testing the proteins' ability to elicit a specific cellular immune response after immunization of HLA-A2.1 transgenic mice and in vitro vaccination of HLA-A2.1 positive human peripheral blood mononuclearcytes (PBMCs). First, we screened SARS N and S amino acid sequences for allele-specific motif matching those in human HLA-A2.1 MHC-I molecules. From HLA peptide binding predictions (http://thr.cit.nih.gov/molbio/hla_bind/), ten each potential N- and S-specific HLA-A2.1-binding peptides were synthesized. The high affinity HLA-A2.1 peptides were validated by T2-cell stabilization assays, with immunogenicity assays revealing peptides N223-231, N227-235, and N317-325 to be First identified HLA-A*0201-restricted CTL epitopes of SARS-CoV N protein. In addition, previous reports identified three HLA-A*0201-restricted CTL epitopes of S protein (S978-986, S1203-1211, and S1167-1175), here we found two novel peptides S787-795 and S1042-1050 as S-specific CTL epitopes. Moreover, our identified N317-325 and S1042-1050 CTL epitopes could induce recall responses when IFN-γ stimulation of blood CD8 + T-cells revealed significant difference between normal healthy donors and SARS-recovered patients after those PBMCs were in vitro vaccinated with their cognate antigen. Our results would provide a new insight into the development of therapeutic vaccine in SARS

SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks.

Science.gov (United States)

Zenke, Friedemann; Ganguli, Surya

2018-04-13

A vast majority of computation in the brain is performed by spiking neural networks. Despite the ubiquity of such spiking, we currently lack an understanding of how biological spiking neural circuits learn and compute in vivo, as well as how we can instantiate such capabilities in artificial spiking circuits in silico. Here we revisit the problem of supervised learning in temporally coding multilayer spiking neural networks. First, by using a surrogate gradient approach, we derive SuperSpike, a nonlinear voltage-based three-factor learning rule capable of training multilayer networks of deterministic integrate-and-fire neurons to perform nonlinear computations on spatiotemporal spike patterns. Second, inspired by recent results on feedback alignment, we compare the performance of our learning rule under different credit assignment strategies for propagating output errors to hidden units. Specifically, we test uniform, symmetric, and random feedback, finding that simpler tasks can be solved with any type of feedback, while more complex tasks require symmetric feedback. In summary, our results open the door to obtaining a better scientific understanding of learning and computation in spiking neural networks by advancing our ability to train them to solve nonlinear problems involving transformations between different spatiotemporal spike time patterns.

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

Immune responses against SARS-coronavirus nucleocapsid protein induced by DNA vaccine

International Nuclear Information System (INIS)

Zhao Ping; Cao Jie; Zhao Lanjuan; Qin Zhaolin; Ke Jinshan; Pan Wei; Ren Hao; Yu Jianguo; Qi Zhongtian

2005-01-01

The nucleocapsid (N) protein of SARS-coronavirus (SARS-CoV) is the key protein for the formation of the helical nucleocapsid during virion assembly. This protein is believed to be more conserved than other proteins of the virus, such as spike and membrane glycoprotein. In this study, the N protein of SARS-CoV was expressed in Escherichia coli DH5α and identified with pooled sera from patients in the convalescence phase of SARS. A plasmid pCI-N, encoding the full-length N gene of SARS-CoV, was constructed. Expression of the N protein was observed in COS1 cells following transfection with pCI-N. The immune responses induced by intramuscular immunization with pCI-N were evaluated in a murine model. Serum anti-N immunoglobulins and splenocytes proliferative responses against N protein were observed in immunized BALB/c mice. The major immunoglobulin G subclass recognizing N protein was immunoglobulin G2a, and stimulated splenocytes secreted high levels of gamma interferon and IL-2 in response to N protein. More importantly, the immunized mice produced strong delayed-type hypersensitivity (DTH) and CD8 + CTL responses to N protein. The study shows that N protein of SARS-CoV not only is an important B cell immunogen, but also can elicit broad-based cellular immune responses. The results indicate that the N protein may be of potential value in vaccine development for specific prophylaxis and treatment against SARS

Residue analysis of a CTL epitope of SARS-CoV spike protein by IFN-gamma production and bioinformatics prediction

Directory of Open Access Journals (Sweden)

Huang Jun

2012-09-01

Full Text Available Abstract Background Severe acute respiratory syndrome (SARS is an emerging infectious disease caused by the novel coronavirus SARS-CoV. The T cell epitopes of the SARS CoV spike protein are well known, but no systematic evaluation of the functional and structural roles of each residue has been reported for these antigenic epitopes. Analysis of the functional importance of side-chains by mutational study may exaggerate the effect by imposing a structural disturbance or an unusual steric, electrostatic or hydrophobic interaction. Results We demonstrated that N50 could induce significant IFN-gamma response from SARS-CoV S DNA immunized mice splenocytes by the means of ELISA, ELISPOT and FACS. Moreover, S366-374 was predicted to be an optimal epitope by bioinformatics tools: ANN, SMM, ARB and BIMAS, and confirmed by IFN-gamma response induced by a series of S358-374-derived peptides. Furthermore, each of S366-374 was replaced by alanine (A, lysine (K or aspartic acid (D, respectively. ANN was used to estimate the binding affinity of single S366-374 mutants to H-2 Kd. Y367 and L374 were predicated to possess the most important role in peptide binding. Additionally, these one residue mutated peptides were synthesized, and IFN-gamma production induced by G368, V369, A371, T372 and K373 mutated S366-374 were decreased obviously. Conclusions We demonstrated that S366-374 is an optimal H-2 Kd CTL epitope in the SARS CoV S protein. Moreover, Y367, S370, and L374 are anchors in the epitope, while C366, G368, V369, A371, T372, and K373 may directly interact with TCR on the surface of CD8-T cells.

Pharmacodynamics of remifentanil. Induced intracranial spike activity in mesial temporal lobe epilepsy

DEFF Research Database (Denmark)

Kjær, Troels Wesenberg; Hogenhaven, Hans; Lee, Andrea P

2017-01-01

that remifentanil potentiates spike activity is in agreement with previous findings from smaller studies. Furthermore, we were able to describe the pharmacodynamics of the remifentanil effect on spike activity. Peri-operative provocation with remifentanil may play a future role in guiding neurosurgical intervention...

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.

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)

Peptide-Based Membrane Fusion Inhibitors Targeting HCoV-229E Spike Protein HR1 and HR2 Domains

Directory of Open Access Journals (Sweden)

Shuai Xia

2018-02-01

Full Text Available Human coronavirus 229E (HCoV-229E infection in infants, elderly people, and immunocompromised patients can cause severe disease, thus calling for the development of effective and safe therapeutics to treat it. Here we reported the design, synthesis and characterization of two peptide-based membrane fusion inhibitors targeting HCoV-229E spike protein heptad repeat 1 (HR1 and heptad repeat 2 (HR2 domains, 229E-HR1P and 229E-HR2P, respectively. We found that 229E-HR1P and 229E-HR2P could interact to form a stable six-helix bundle and inhibit HCoV-229E spike protein-mediated cell-cell fusion with IC50 of 5.7 and 0.3 µM, respectively. 229E-HR2P effectively inhibited pseudotyped and live HCoV-229E infection with IC50 of 0.5 and 1.7 µM, respectively. In a mouse model, 229E-HR2P administered intranasally could widely distribute in the upper and lower respiratory tracts and maintain its fusion-inhibitory activity. Therefore, 229E-HR2P is a promising candidate for further development as an antiviral agent for the treatment and prevention of HCoV-229E infection.

Contamination spike simulation and measurement in a clean metal vapor laser

International Nuclear Information System (INIS)

Lin, C.E.; Yang, C.Y.

1990-01-01

This paper describes a new method for the generation of contamination-induced voltage spikes in a clean metal vapor laser. The method facilitates the study of the characteristics of this troublesome phenomenon in laser systems. Analysis of these artificially generated dirt spikes shows that the breakdown time of the laser tube is increased when these spike appear. The concept of a Townsend discharge is used to identify the parameter which changes the breakdown time of the discharges. The residual ionization control method is proposed to generate dirt spikes in a clean laser. Experimental results show that a wide range of dirt spike magnitudes can be obtained by using the proposed method. The method provides easy and accurate control of the magnitude of the dirt spike, and the laser tube does not become polluted. Results based on the measurements can be used in actual laser systems to monitor the appearance of dirt spikes and thus avoid the danger of thyratron failure

The influence of single bursts vs. single spikes at excitatory dendrodendritic synapses

Science.gov (United States)

Masurkar, Arjun V.; Chen, Wei R.

2015-01-01

The synchronization of neuronal activity is thought to enhance information processing. There is much evidence supporting rhythmically bursting external tufted cells (ETCs) of the rodent olfactory bulb glomeruli coordinating the activation of glomerular interneurons and mitral cells via dendrodendritic excitation. However, as bursting has variable significance at axodendritic cortical synapses, it is not clear if ETC bursting imparts a specific functional advantage over the preliminary spike in dendrodendritic synaptic networks. To answer this question, we investigated the influence of single ETC bursts and spikes with the in-vitro rat olfactory bulb preparation at different levels of processing, via calcium imaging of presynaptic ETC dendrites, dual electrical recording of ETC–interneuron synaptic pairs, and multicellular calcium imaging of ETC-induced population activity. Our findings supported single ETC bursts, vs. single spikes, driving robust presynaptic calcium signaling, which in turn was associated with profound extension of the initial monosynaptic spike-driven dendrodendritic excitatory postsynaptic potential. This extension could be driven by either the spike-dependent or spike-independent components of the burst. At the population level, burst-induced excitation was more widespread and reliable compared with single spikes. This further supports the ETC network, in part due to a functional advantage of bursting at excitatory dendrodendritic synapses, coordinating synchronous activity at behaviorally relevant frequencies related to odor processing in vivo. PMID:22277089

Deletion of a 197-Amino-Acid Region in the N-Terminal Domain of Spike Protein Attenuates Porcine Epidemic Diarrhea Virus in Piglets.

Science.gov (United States)

Hou, Yixuan; Lin, Chun-Ming; Yokoyama, Masaru; Yount, Boyd L; Marthaler, Douglas; Douglas, Arianna L; Ghimire, Shristi; Qin, Yibin; Baric, Ralph S; Saif, Linda J; Wang, Qiuhong

2017-07-15

We previously isolated a porcine epidemic diarrhea virus (PEDV) strain, PC177, by blind serial passaging of the intestinal contents of a diarrheic piglet in Vero cell culture. Compared with the highly virulent U.S. PEDV strain PC21A, the tissue culture-adapted PC177 (TC-PC177) contains a 197-amino-acid (aa) deletion in the N-terminal domain of the spike (S) protein. We orally inoculated neonatal, conventional suckling piglets with TC-PC177 or PC21A to compare their pathogenicities. Within 7 days postinoculation, TC-PC177 caused mild diarrhea and lower fecal viral RNA shedding, with no mortality, whereas PC21A caused severe clinical signs and 55% mortality. To investigate whether infection with TC-PC177 can induce cross-protection against challenge with a highly virulent PEDV strain, all the surviving piglets were challenged with PC21A at 3 weeks postinoculation. Compared with 100% protection in piglets initially inoculated with PC21A, 88% and 100% TC-PC177- and mock-inoculated piglets had diarrhea following challenge, respectively, indicating incomplete cross-protection. To investigate whether this 197-aa deletion was the determinant for the attenuation of TC-PC177, we generated a mutant (icPC22A-S1Δ197) bearing the 197-aa deletion from an infectious cDNA clone of the highly virulent PEDV PC22A strain (infectious clone PC22A, icPC22A). In neonatal gnotobiotic pigs, the icPC22A-S1Δ197 virus caused mild to moderate diarrhea, lower titers of viral shedding, and no mortality, whereas the icPC22A virus caused severe diarrhea and 100% mortality. Our data indicate that deletion of this 197-aa fragment in the spike protein can attenuate a highly virulent PEDV, but the virus may lose important epitopes for inducing robust protective immunity. IMPORTANCE The emerging, highly virulent PEDV strains have caused substantial economic losses worldwide. However, the virulence determinants are not established. In this study, we found that a 197-aa deletion in the N-terminal region

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...

Spike persistence and normalization in benign epilepsy with centrotemporal spikes - Implications for management.

Science.gov (United States)

Kim, Hunmin; Kim, Soo Yeon; Lim, Byung Chan; Hwang, Hee; Chae, Jong-Hee; Choi, Jieun; Kim, Ki Joong; Dlugos, Dennis J

2018-05-10

This study was performed 1) to determine the timing of spike normalization in patients with benign epilepsy with centrotemporal spikes (BECTS); 2) to identify relationships between age of seizure onset, age of spike normalization, years of spike persistence and treatment; and 3) to assess final outcomes between groups of patients with or without spikes at the time of medication tapering. Retrospective analysis of BECTS patients confirmed by clinical data, including age of onset, seizure semiology and serial electroencephalography (EEG) from diagnosis to remission. Age at spike normalization, years of spike persistence, and time of treatment onset to spike normalization were assessed. Final seizure and EEG outcome were compared between the groups with or without spikes at the time of AED tapering. One hundred and thirty-four patients were included. Mean age at seizure onset was 7.52 ± 2.11 years. Mean age at spike normalization was 11.89 ± 2.11 (range: 6.3-16.8) years. Mean time of treatment onset to spike normalization was 4.11 ± 2.13 (range: 0.24-10.08) years. Younger age of seizure onset was correlated with longer duration of spike persistence (r = -0.41, p < 0.001). In treated patients, spikes persisted for 4.1 ± 1.95 years, compared with 2.9 ± 1.97 years in untreated patients. No patients had recurrent seizures after AED was discontinued, regardless of the presence/absence of spikes at time of AED tapering. Years of spike persistence was longer in early onset BECTS patients. Treatment with AEDs did not shorten years of spike persistence. Persistence of spikes at time of treatment withdrawal was not associated with seizure recurrence. Copyright © 2018 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

The influence of single bursts versus single spikes at excitatory dendrodendritic synapses.

Science.gov (United States)

Masurkar, Arjun V; Chen, Wei R

2012-02-01

The synchronization of neuronal activity is thought to enhance information processing. There is much evidence supporting rhythmically bursting external tufted cells (ETCs) of the rodent olfactory bulb glomeruli coordinating the activation of glomerular interneurons and mitral cells via dendrodendritic excitation. However, as bursting has variable significance at axodendritic cortical synapses, it is not clear if ETC bursting imparts a specific functional advantage over the preliminary spike in dendrodendritic synaptic networks. To answer this question, we investigated the influence of single ETC bursts and spikes with the in vitro rat olfactory bulb preparation at different levels of processing, via calcium imaging of presynaptic ETC dendrites, dual electrical recording of ETC -interneuron synaptic pairs, and multicellular calcium imaging of ETC-induced population activity. Our findings supported single ETC bursts, versus single spikes, driving robust presynaptic calcium signaling, which in turn was associated with profound extension of the initial monosynaptic spike-driven dendrodendritic excitatory postsynaptic potential. This extension could be driven by either the spike-dependent or spike-independent components of the burst. At the population level, burst-induced excitation was more widespread and reliable compared with single spikes. This further supports the ETC network, in part due to a functional advantage of bursting at excitatory dendrodendritic synapses, coordinating synchronous activity at behaviorally relevant frequencies related to odor processing in vivo. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Production and immunogenicity of chimeric virus-like particles containing the spike glycoprotein of infectious bronchitis virus.

Science.gov (United States)

Lv, Lishan; Li, Xiaoming; Liu, Genmei; Li, Ran; Liu, Qiliang; Shen, Huifang; Wang, Wei; Xue, Chunyi; Cao, Yongchang

2014-01-01

Infectious bronchitis virus (IBV) poses a severe threat to the poultry industry and causes heavy economic losses worldwide. Vaccination is the most effective method of preventing infection and controlling the spread of IBV, but currently available inactivated and attenuated virus vaccines have some disadvantages. We developed a chimeric virus-like particle (VLP)-based candidate vaccine for IBV protection. The chimeric VLP was composed of matrix 1 protein from avian influenza H5N1 virus and a fusion protein neuraminidase (NA)/spike 1 (S1) that was generated by fusing IBV S1 protein to the cytoplasmic and transmembrane domains of NA protein of avian influenza H5N1 virus. The chimeric VLPs elicited significantly higher S1-specific antibody responses in intramuscularly immunized mice and chickens than inactivated IBV viruses. Furthermore, the chimeric VLPs induced significantly higher neutralization antibody levels than inactivated H120 virus in SPF chickens. Finally, the chimeric VLPs induced significantly higher IL-4 production in mice. These results demonstrate that chimeric VLPs have the potential for use in vaccines against IBV infection.

A study on antigenicity and receptor-binding ability of fragment 450-650 of the spike protein of SARS coronavirus

International Nuclear Information System (INIS)

Zhao Jincun; Wang Wei; Yuan Zhihong; Jia Rujing; Zhao Zhendong; Xu Xiaojun; Lv Ping; Zhang Yan; Jiang Chengyu; Gao Xiaoming

2007-01-01

The spike (S) protein of SARS coronavirus (SARS-CoV) is responsible for viral binding with ACE2 molecules. Its receptor-binding motif (S-RBM) is located between residues 424 and 494, which folds into 2 anti-parallel β-sheets, β5 and β6. We have previously demonstrated that fragment 450-650 of the S protein (S450-650) is predominantly recognized by convalescent sera of SARS patients. The N-terminal 60 residues (450-510) of the S450-650 fragment covers the entire β6 strand of S-RBM. In the present study, we demonstrate that patient sera predominantly recognized 2 linear epitopes outside the β6 fragment, while the mouse antisera, induced by immunization of BALB/c mice with recombinant S450-650, mainly recognized the β6 strand-containing region. Unlike patient sera, however, the mouse antisera were unable to inhibit the infectivity of S protein-expressing (SARS-CoV-S) pseudovirus. Fusion protein between green fluorescence protein (GFP) and S450-650 (S450-650-GFP) was able to stain Vero E6 cells and deletion of the β6 fragment rendered the fusion product (S511-650-GFP) unable to do so. Similarly, recombinant S450-650, but not S511-650, was able to block the infection of Vero E6 cells by the SARS-CoV-S pseudovirus. Co-precipitation experiments confirmed that S450-650 was able to specifically bind with ACE2 molecules in lysate of Vero E6 cells. However, the ability of S450-510, either alone or in fusion with GFP, to bind with ACE2 was significantly poorer compared with S450-650. Our data suggest a possibility that, although the β6 strand alone is able to bind with ACE2 with relatively high affinity, residues outside the S-RBM could also assist the receptor binding of SARS-CoV-S protein

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

and moving visual stimuli from the spontaneous ongoing spiking state, in all layers and zones of areas 17 and 18 indicating that the second threshold is a property of the network. Spontaneous and evoked spiking, thus can easily be distinguished. In addition, the trajectories of spontaneous ongoing states......Most neurons have a threshold separating the silent non-spiking state and the state of producing temporal sequences of spikes. But neurons in vivo also have a second threshold, found recently in granular layer neurons of the primary visual cortex, separating spontaneous ongoing spiking from...... 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...

Thermal spike analysis of highly charged ion tracks

International Nuclear Information System (INIS)

Karlušić, M.; Jakšić, M.

2012-01-01

The irradiation of material using swift heavy ion or highly charged ion causes excitation of the electron subsystem at nanometer scale along the ion trajectory. According to the thermal spike model, energy deposited into the electron subsystem leads to temperature increase due to electron–phonon coupling. If ion-induced excitation is sufficiently intensive, then melting of the material can occur, and permanent damage (i.e., ion track) can be formed upon rapid cooling. We present an extension of the analytical thermal spike model of Szenes for the analysis of surface ion track produced after the impact of highly charged ion. By applying the model to existing experimental data, more than 60% of the potential energy of the highly charged ion was shown to be retained in the material during the impact and transformed into the energy of the thermal spike. This value is much higher than 20–40% of the transferred energy into the thermal spike by swift heavy ion. Thresholds for formation of highly charged ion track in different materials show uniform behavior depending only on few material parameters.

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.

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

Impacts of clustering on noise-induced spiking regularity in the excitatory neuronal networks of subnetworks.

Science.gov (United States)

Li, Huiyan; Sun, Xiaojuan; Xiao, Jinghua

2015-01-01

In this paper, we investigate how clustering factors influent spiking regularity of the neuronal network of subnetworks. In order to do so, we fix the averaged coupling probability and the averaged coupling strength, and take the cluster number M, the ratio of intra-connection probability and inter-connection probability R, the ratio of intra-coupling strength and inter-coupling strength S as controlled parameters. With the obtained simulation results, we find that spiking regularity of the neuronal networks has little variations with changing of R and S when M is fixed. However, cluster number M could reduce the spiking regularity to low level when the uniform neuronal network's spiking regularity is at high level. Combined the obtained results, we can see that clustering factors have little influences on the spiking regularity when the entire energy is fixed, which could be controlled by the averaged coupling strength and the averaged connection probability.

Fluid-thermal analysis of aerodynamic heating over spiked blunt body configurations

Science.gov (United States)

Qin, Qihao; Xu, Jinglei; Guo, Shuai

2017-03-01

When flying at hypersonic speeds, the spiked blunt body is constantly subjected to severe aerodynamic heating. To illustrate the thermal response of different configurations and the relevant flow field variation, a loosely-coupled fluid-thermal analysis is performed in this paper. The Mesh-based parallel Code Coupling Interface (MpCCI) is adopted to implement the data exchange between the fluid solver and the thermal solver. The results indicate that increases in spike diameter and length will result in a sharp decline of the wall temperature along the spike, and the overall heat flux is remarkably reduced to less than 300 W/cm2 with the aerodome mounted at the spike tip. Moreover, the presence and evolution of small vortices within the recirculation zone are observed and proved to be induced by the stagnation effect of reattachment points on the spike. In addition, the drag coefficient of the configuration with a doubled spike length presents a maximum drop of 4.59% due to the elevated wall temperature. And the growing difference of the drag coefficient is further increased during the accelerating process.

Decoding spikes in a spiking neuronal network

Energy Technology Data Exchange (ETDEWEB)

Feng Jianfeng [Department of Informatics, University of Sussex, Brighton BN1 9QH (United Kingdom); Ding, Mingzhou [Department of Mathematics, Florida Atlantic University, Boca Raton, FL 33431 (United States)

2004-06-04

We investigate how to reliably decode the input information from the output of a spiking neuronal network. A maximum likelihood estimator of the input signal, together with its Fisher information, is rigorously calculated. The advantage of the maximum likelihood estimation over the 'brute-force rate coding' estimate is clearly demonstrated. It is pointed out that the ergodic assumption in neuroscience, i.e. a temporal average is equivalent to an ensemble average, is in general not true. Averaging over an ensemble of neurons usually gives a biased estimate of the input information. A method on how to compensate for the bias is proposed. Reconstruction of dynamical input signals with a group of spiking neurons is extensively studied and our results show that less than a spike is sufficient to accurately decode dynamical inputs.

Decoding spikes in a spiking neuronal network

International Nuclear Information System (INIS)

Feng Jianfeng; Ding, Mingzhou

2004-01-01

We investigate how to reliably decode the input information from the output of a spiking neuronal network. A maximum likelihood estimator of the input signal, together with its Fisher information, is rigorously calculated. The advantage of the maximum likelihood estimation over the 'brute-force rate coding' estimate is clearly demonstrated. It is pointed out that the ergodic assumption in neuroscience, i.e. a temporal average is equivalent to an ensemble average, is in general not true. Averaging over an ensemble of neurons usually gives a biased estimate of the input information. A method on how to compensate for the bias is proposed. Reconstruction of dynamical input signals with a group of spiking neurons is extensively studied and our results show that less than a spike is sufficient to accurately decode dynamical inputs

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.

An amino-terminal segment of hantavirus nucleocapsid protein presented on hepatitis B virus core particles induces a strong and highly cross-reactive antibody response in mice

International Nuclear Information System (INIS)

Geldmacher, Astrid; Skrastina, Dace; Petrovskis, Ivars; Borisova, Galina; Berriman, John A.; Roseman, Alan M.; Crowther, R. Anthony; Fischer, Jan; Musema, Shamil; Gelderblom, Hans R.; Lundkvist, Aake; Renhofa, Regina; Ose, Velta; Krueger, Detlev H.; Pumpens, Paul; Ulrich, Rainer

2004-01-01

Previously, we have demonstrated that hepatitis B virus (HBV) core particles tolerate the insertion of the amino-terminal 120 amino acids (aa) of the Puumala hantavirus nucleocapsid (N) protein. Here, we demonstrate that the insertion of 120 amino-terminal aa of N proteins from highly virulent Dobrava and Hantaan hantaviruses allows the formation of chimeric core particles. These particles expose the inserted foreign protein segments, at least in part, on their surface. Analysis by electron cryomicroscopy of chimeric particles harbouring the Puumala virus (PUUV) N segment revealed 90% T = 3 and 10% T = 4 shells. A map computed from T = 3 shells shows additional density splaying out from the tips of the spikes producing the effect of an extra shell of density at an outer radius compared with wild-type shells. The inserted Puumala virus N protein segment is flexibly linked to the core spikes and only partially icosahedrally ordered. Immunisation of mice of two different haplotypes (BALB/c and C57BL/6) with chimeric core particles induces a high-titered and highly cross-reactive N-specific antibody response in both mice strains

Rebound spiking in layer II medial entorhinal cortex stellate cells: Possible mechanism of grid cell function

Science.gov (United States)

Shay, Christopher F.; Ferrante, Michele; Chapman, G. William; Hasselmo, Michael E.

2015-01-01

Rebound spiking properties of medial entorhinal cortex (mEC) stellate cells induced by inhibition may underlie their functional properties in awake behaving rats, including the temporal phase separation of distinct grid cells and differences in grid cell firing properties. We investigated rebound spiking properties using whole cell patch recording in entorhinal slices, holding cells near spiking threshold and delivering sinusoidal inputs, superimposed with realistic inhibitory synaptic inputs to test the capacity of cells to selectively respond to specific phases of inhibitory input. Stellate cells showed a specific phase range of hyperpolarizing inputs that elicited spiking, but non-stellate cells did not show phase specificity. In both cell types, the phase range of spiking output occurred between the peak and subsequent descending zero crossing of the sinusoid. The phases of inhibitory inputs that induced spikes shifted earlier as the baseline sinusoid frequency increased, while spiking output shifted to later phases. Increases in magnitude of the inhibitory inputs shifted the spiking output to earlier phases. Pharmacological blockade of h-current abolished the phase selectivity of hyperpolarizing inputs eliciting spikes. A network computational model using cells possessing similar rebound properties as found in vitro produces spatially periodic firing properties resembling grid cell firing when a simulated animal moves along a linear track. These results suggest that the ability of mEC stellate cells to fire rebound spikes in response to a specific range of phases of inhibition could support complex attractor dynamics that provide completion and separation to maintain spiking activity of specific grid cell populations. PMID:26385258

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

Spiking sychronization regulated by noise in three types of Hodgkin—Huxley neuronal networks

International Nuclear Information System (INIS)

Zhang Zheng-Zhen; Zeng Shang-You; Tang Wen-Yan; Hu Jin-Lin; Zeng Shao-Wen; Ning Wei-Lian; Qiu Yi; Wu Hui-Si

2012-01-01

In this paper, we study spiking synchronization in three different types of Hodgkin—Huxley neuronal networks, which are the small-world, regular, and random neuronal networks. All the neurons are subjected to subthreshold stimulus and external noise. It is found that in each of all the neuronal networks there is an optimal strength of noise to induce the maximal spiking synchronization. We further demonstrate that in each of the neuronal networks there is a range of synaptic conductance to induce the effect that an optimal strength of noise maximizes the spiking synchronization. Only when the magnitude of the synaptic conductance is moderate, will the effect be considerable. However, if the synaptic conductance is small or large, the effect vanishes. As the connections between neurons increase, the synaptic conductance to maximize the effect decreases. Therefore, we show quantitatively that the noise-induced maximal synchronization in the Hodgkin—Huxley neuronal network is a general effect, regardless of the specific type of neuronal network

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

Science.gov (United States)

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

2016-01-01

Most neurons have a threshold separating the silent non-spiking state and the state of producing temporal sequences of spikes. But neurons in vivo also have a second threshold, found recently in granular layer neurons of the primary visual cortex, separating spontaneous ongoing spiking from 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 and moving visual stimuli from the spontaneous ongoing spiking state, in all layers and zones of areas 17 and 18 indicating that the second threshold is a property of the network. Spontaneous and evoked spiking, thus can easily be distinguished. In addition, the trajectories of spontaneous ongoing states were slow, frequently changing direction. In single trials, sharp as well as smooth and slow transients transform the trajectories to be outward directed, fast and crossing the threshold to become evoked. Although the speeds of the evolution of the evoked states differ, the same domain of the state space is explored indicating uniformity of the evoked states. All evoked states return to the spontaneous evoked spiking state as in a typical mono-stable dynamical system. In single trials, neither the original spiking rates, nor the temporal evolution in state space could distinguish simple visual scenes. PMID:27582693

Fast Na+ spike generation in dendrites of guinea-pig substantia nigra pars compacta neurons

DEFF Research Database (Denmark)

Nedergaard, S; Hounsgaard, Jørn Dybkjær

1996-01-01

were not inhibited in the presence of glutamate receptor antagonists or during Ca2+ channel blockade. Blockers of gap junctional conductance (sodium propionate, octanol and halothane) did not affect the field-induced spikes. The spike generation was highly sensitive to changes in membrane conductance...

Amino acid changes in the spike protein of feline coronavirus correlate with systemic spread of virus from the intestine and not with feline infectious peritonitis.

Science.gov (United States)

Porter, Emily; Tasker, Séverine; Day, Michael J; Harley, Ross; Kipar, Anja; Siddell, Stuart G; Helps, Christopher R

2014-04-25

Recent evidence suggests that a mutation in the spike protein gene of feline coronavirus (FCoV), which results in an amino acid change from methionine to leucine at position 1058, may be associated with feline infectious peritonitis (FIP). Tissue and faecal samples collected post mortem from cats diagnosed with or without FIP were subjected to RNA extraction and quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR) to detect FCoV RNA. In cats with FIP, 95% of tissue, and 81% of faecal samples were PCR-positive, as opposed to 22% of tissue, and 60% of faecal samples in cats without FIP. Relative FCoV copy numbers were significantly higher in the cats with FIP, both in tissues (P < 0.001) and faeces (P = 0.02). PCR-positive samples underwent pyrosequencing encompassing position 1058 of the FCoV spike protein. This identified a methionine codon at position 1058, consistent with the shedding of an enteric form of FCoV, in 77% of the faecal samples from cats with FIP, and in 100% of the samples from cats without FIP. In contrast, 91% of the tissue samples from cats with FIP and 89% from cats without FIP had a leucine codon at position 1058, consistent with a systemic form of FCoV. These results suggest that the methionine to leucine substitution at position 1058 in the FCoV spike protein is indicative of systemic spread of FCoV from the intestine, rather than a virus with the potential to cause FIP.

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)

Modulation of the spike activity of neocortex neurons during a conditioned reflex.

Science.gov (United States)

Storozhuk, V M; Sanzharovskii, A V; Sachenko, V V; Busel, B I

2000-01-01

Experiments were conducted on cats to study the effects of iontophoretic application of glutamate and a number of modulators on the spike activity of neurons in the sensorimotor cortex during a conditioned reflex. These studies showed that glutamate, as well as exerting a direct influence on neuron spike activity, also had a delayed facilitatory action lasting 10-20 min after iontophoresis was finished. Adrenomimetics were found to have a double modulatory effect on intracortical glutamate connections: inhibitory and facilitatory effects were mediated by beta1 and beta2 adrenoceptors respectively. Although dopamine, like glutamate, facilitated neuron spike activity during the period of application, the simultaneous facilitatory actions of glutamate and L-DOPA were accompanied by occlusion of spike activity, and simultaneous application of glutamate and haloperidol suppressed spike activity associated with the conditioned reflex response. Facilitation thus appears to show a significant level of dependence on metabotropic glutamate receptors which, like dopamine receptors, are linked to the intracellular medium via Gi proteins.

Automatic EEG spike detection.

Science.gov (United States)

Harner, Richard

2009-10-01

Since the 1970s advances in science and technology during each succeeding decade have renewed the expectation of efficient, reliable automatic epileptiform spike detection (AESD). But even when reinforced with better, faster tools, clinically reliable unsupervised spike detection remains beyond our reach. Expert-selected spike parameters were the first and still most widely used for AESD. Thresholds for amplitude, duration, sharpness, rise-time, fall-time, after-coming slow waves, background frequency, and more have been used. It is still unclear which of these wave parameters are essential, beyond peak-peak amplitude and duration. Wavelet parameters are very appropriate to AESD but need to be combined with other parameters to achieve desired levels of spike detection efficiency. Artificial Neural Network (ANN) and expert-system methods may have reached peak efficiency. Support Vector Machine (SVM) technology focuses on outliers rather than centroids of spike and nonspike data clusters and should improve AESD efficiency. An exemplary spike/nonspike database is suggested as a tool for assessing parameters and methods for AESD and is available in CSV or Matlab formats from the author at brainvue@gmail.com. Exploratory Data Analysis (EDA) is presented as a graphic method for finding better spike parameters and for the step-wise evaluation of the spike detection process.

SpikeTemp: An Enhanced Rank-Order-Based Learning Approach for Spiking Neural Networks With Adaptive Structure.

Science.gov (United States)

Wang, Jinling; Belatreche, Ammar; Maguire, Liam P; McGinnity, Thomas Martin

2017-01-01

This paper presents an enhanced rank-order-based learning algorithm, called SpikeTemp, for spiking neural networks (SNNs) with a dynamically adaptive structure. The trained feed-forward SNN consists of two layers of spiking neurons: 1) an encoding layer which temporally encodes real-valued features into spatio-temporal spike patterns and 2) an output layer of dynamically grown neurons which perform spatio-temporal classification. Both Gaussian receptive fields and square cosine population encoding schemes are employed to encode real-valued features into spatio-temporal spike patterns. Unlike the rank-order-based learning approach, SpikeTemp uses the precise times of the incoming spikes for adjusting the synaptic weights such that early spikes result in a large weight change and late spikes lead to a smaller weight change. This removes the need to rank all the incoming spikes and, thus, reduces the computational cost of SpikeTemp. The proposed SpikeTemp algorithm is demonstrated on several benchmark data sets and on an image recognition task. The results show that SpikeTemp can achieve better classification performance and is much faster than the existing rank-order-based learning approach. In addition, the number of output neurons is much smaller when the square cosine encoding scheme is employed. Furthermore, SpikeTemp is benchmarked against a selection of existing machine learning algorithms, and the results demonstrate the ability of SpikeTemp to classify different data sets after just one presentation of the training samples with comparable classification performance.

Spiking Neural Networks Based on OxRAM Synapses for Real-Time Unsupervised Spike Sorting.

Science.gov (United States)

Werner, Thilo; Vianello, Elisa; Bichler, Olivier; Garbin, Daniele; Cattaert, Daniel; Yvert, Blaise; De Salvo, Barbara; Perniola, Luca

2016-01-01

In this paper, we present an alternative approach to perform spike sorting of complex brain signals based on spiking neural networks (SNN). The proposed architecture is suitable for hardware implementation by using resistive random access memory (RRAM) technology for the implementation of synapses whose low latency (spike sorting. This offers promising advantages to conventional spike sorting techniques for brain-computer interfaces (BCI) and neural prosthesis applications. Moreover, the ultra-low power consumption of the RRAM synapses of the spiking neural network (nW range) may enable the design of autonomous implantable devices for rehabilitation purposes. We demonstrate an original methodology to use Oxide based RRAM (OxRAM) as easy to program and low energy (Spike Timing Dependent Plasticity. Real spiking data have been recorded both intra- and extracellularly from an in-vitro preparation of the Crayfish sensory-motor system and used for validation of the proposed OxRAM based SNN. This artificial SNN is able to identify, learn, recognize and distinguish between different spike shapes in the input signal with a recognition rate about 90% without any supervision.

Dynamics and spike trains statistics in conductance-based integrate-and-fire neural networks with chemical and electric synapses

International Nuclear Information System (INIS)

Cofré, Rodrigo; Cessac, Bruno

2013-01-01

We investigate the effect of electric synapses (gap junctions) on collective neuronal dynamics and spike statistics in a conductance-based integrate-and-fire neural network, driven by Brownian noise, where conductances depend upon spike history. We compute explicitly the time evolution operator and show that, given the spike-history of the network and the membrane potentials at a given time, the further dynamical evolution can be written in a closed form. We show that spike train statistics is described by a Gibbs distribution whose potential can be approximated with an explicit formula, when the noise is weak. This potential form encompasses existing models for spike trains statistics analysis such as maximum entropy models or generalized linear models (GLM). We also discuss the different types of correlations: those induced by a shared stimulus and those induced by neurons interactions

Space-filling, multifractal, localized thermal spikes in Si, Ge and ZnO

Science.gov (United States)

Ahmad, Shoaib; Abbas, Muhammad Sabtain; Yousuf, Muhammad; Javeed, Sumera; Zeeshan, Sumaira; Yaqub, Kashif

2018-04-01

The mechanism responsible for the emission of clusters from heavy ion irradiated solids is proposed to be thermal spikes. Collision cascade-based theories describe atomic sputtering but cannot explain the consistently observed experimental evidence for significant cluster emission. Statistical thermodynamic arguments for thermal spikes are employed here for qualitative and quantitative estimation of the thermal spike-induced cluster emission from Si, Ge and ZnO. The evolving cascades and spikes in elemental and molecular semiconducting solids are shown to have fractal characteristics. Power law potential is used to calculate the fractal dimension. With the loss of recoiling particles' energy the successive branching ratios get smaller. The fractal dimension is shown to be dependent upon the exponent of the power law interatomic potential D = 1/2m. Each irradiating ion has the probability of initiating a space-filling, multifractal thermal spike that may sublime a localized region near the surface by emitting clusters in relative ratios that depend upon the energies of formation of respective surface vacancies.

Automatic spike sorting using tuning information.

Science.gov (United States)

Ventura, Valérie

2009-09-01

Current spike sorting methods focus on clustering neurons' characteristic spike waveforms. The resulting spike-sorted data are typically used to estimate how covariates of interest modulate the firing rates of neurons. However, when these covariates do modulate the firing rates, they provide information about spikes' identities, which thus far have been ignored for the purpose of spike sorting. This letter describes a novel approach to spike sorting, which incorporates both waveform information and tuning information obtained from the modulation of firing rates. Because it efficiently uses all the available information, this spike sorter yields lower spike misclassification rates than traditional automatic spike sorters. This theoretical result is verified empirically on several examples. The proposed method does not require additional assumptions; only its implementation is different. It essentially consists of performing spike sorting and tuning estimation simultaneously rather than sequentially, as is currently done. We used an expectation-maximization maximum likelihood algorithm to implement the new spike sorter. We present the general form of this algorithm and provide a detailed implementable version under the assumptions that neurons are independent and spike according to Poisson processes. Finally, we uncover a systematic flaw of spike sorting based on waveform information only.

Identification of warm day and cool night conditions induced flowering-related genes in a Phalaenopsis orchid hybrid by suppression subtractive hybridization.

Science.gov (United States)

Li, D M; Lü, F B; Zhu, G F; Sun, Y B; Xu, Y C; Jiang, M D; Liu, J W; Wang, Z

2014-02-14

The influence of warm day and cool night conditions on induction of spikes in Phalaenopsis orchids has been studied with respect to photosynthetic efficiency, metabolic cycles and physiology. However, molecular events involved in spike emergence induced by warm day and cool night conditions are not clearly understood. We examined gene expression induced by warm day and cool night conditions in the Phalaenopsis hybrid Fortune Saltzman through suppression subtractive hybridization, which allowed identification of flowering-related genes in warm day and cool night conditions in spikes and leaves at vegetative phase grown under warm daily temperatures. In total, 450 presumably regulated expressed sequence tags (ESTs) were identified and classified into functional categories, including metabolism, development, transcription factor, signal transduction, transportation, cell defense, and stress. Furthermore, database comparisons revealed a notable number of Phalaenopsis hybrid Fortune Saltzman ESTs that matched genes with unknown function. The expression profiles of 24 genes (from different functional categories) have been confirmed by quantitative real-time PCR in induced spikes and juvenile apical leaves. The results of the real-time PCR showed that, compared to the vegetative apical leaves, the transcripts of genes encoding flowering locus T, AP1, AP2, KNOX1, knotted1-like homeobox protein, R2R3-like MYB, adenosine kinase 2, S-adenosylmethionine synthetase, dihydroflavonol 4-reductase, and naringenin 3-dioxygenase accumulated significantly higher levels, and genes encoding FCA, retrotransposon protein Ty3 and C3HC4-type RING finger protein accumulated remarkably lower levels in spikes of early developmental stages. These results suggested that the genes of two expression changing trends may play positive and negative roles in the early floral transition of Phalaenopsis orchids. In conclusion, spikes induced by warm day and cool night conditions were complex in

Reliability of MEG source imaging of anterior temporal spikes: analysis of an intracranially characterized spike focus.

Science.gov (United States)

Wennberg, Richard; Cheyne, Douglas

2014-05-01

To assess the reliability of MEG source imaging (MSI) of anterior temporal spikes through detailed analysis of the localization and orientation of source solutions obtained for a large number of spikes that were separately confirmed by intracranial EEG to be focally generated within a single, well-characterized spike focus. MSI was performed on 64 identical right anterior temporal spikes from an anterolateral temporal neocortical spike focus. The effects of different volume conductors (sphere and realistic head model), removal of noise with low frequency filters (LFFs) and averaging multiple spikes were assessed in terms of the reliability of the source solutions. MSI of single spikes resulted in scattered dipole source solutions that showed reasonable reliability for localization at the lobar level, but only for solutions with a goodness-of-fit exceeding 80% using a LFF of 3 Hz. Reliability at a finer level of intralobar localization was limited. Spike averaging significantly improved the reliability of source solutions and averaging 8 or more spikes reduced dependency on goodness-of-fit and data filtering. MSI performed on topographically identical individual spikes from an intracranially defined classical anterior temporal lobe spike focus was limited by low reliability (i.e., scattered source solutions) in terms of fine, sublobar localization within the ipsilateral temporal lobe. Spike averaging significantly improved reliability. MSI performed on individual anterior temporal spikes is limited by low reliability. Reduction of background noise through spike averaging significantly improves the reliability of MSI solutions. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Decoding spatiotemporal spike sequences via the finite state automata dynamics of spiking neural networks

International Nuclear Information System (INIS)

Jin, Dezhe Z

2008-01-01

Temporally complex stimuli are encoded into spatiotemporal spike sequences of neurons in many sensory areas. Here, we describe how downstream neurons with dendritic bistable plateau potentials can be connected to decode such spike sequences. Driven by feedforward inputs from the sensory neurons and controlled by feedforward inhibition and lateral excitation, the neurons transit between UP and DOWN states of the membrane potentials. The neurons spike only in the UP states. A decoding neuron spikes at the end of an input to signal the recognition of specific spike sequences. The transition dynamics is equivalent to that of a finite state automaton. A connection rule for the networks guarantees that any finite state automaton can be mapped into the transition dynamics, demonstrating the equivalence in computational power between the networks and finite state automata. The decoding mechanism is capable of recognizing an arbitrary number of spatiotemporal spike sequences, and is insensitive to the variations of the spike timings in the sequences

Revisiting the thermal-spike concept in ion-surface interactions

Science.gov (United States)

Miotello, Antonio; Kelly, Roger

1997-02-01

In recent years many groups have advocated a thermal-spike model to explain a variety of experimental results in ion-irradiation of solids, as for example sputtering, mixing, compositional change, structural change, and track formation. The latter include crystal-to-amorphous transitions as well as track formation due to MeV/u particles. In this paper we reconsider the phenomena occurring during ion impact of solids looking at the time scale generally indicated as relevant for thermal-spike effects, namely a picosecond scale as shown by molecular dynamics. Sputtering, mixing, and track formation, however, will be analyzed in more detail. We consider first ion-beam sputtering and reiterate (as is already well-known) that yields which increase with the bulk temperature most often indicate merely the onset of normal vaporization. Indeed, only simulations appear to be capable of giving insight even if the information is sometimes tentative. In mixing, ballistic transport is important but not dominant. It is often argued that the additional transport is provided by thermal spikes but it is noted that such an assumption is normally not required by the experimental results. What is more relevant is a role for residual defects such that the total diffusion flux includes (if the defects are chemically guided) a modified Darken factor, or (if the defects are not chemically guided) simply an increased diffusivity. The time scale (min), distances (well beyond the collision cascade), temperature sensitivity (changes of as little as 75 K are relevant), and correlation with vacancy properties (thence with the solid rather than liquid state) which are relevant to these residual defects are not understandable in terms of thermal spikes. We finally consider track formation. Recent work claiming that track formation in solids, irradiated with heavy ions, may be understood in terms of thermal spikes is reconsidered to show that the thermal-spike model is utilized without considering

Network evolution induced by asynchronous stimuli through spike-timing-dependent plasticity.

Directory of Open Access Journals (Sweden)

Wu-Jie Yuan

Full Text Available In sensory neural system, external asynchronous stimuli play an important role in perceptual learning, associative memory and map development. However, the organization of structure and dynamics of neural networks induced by external asynchronous stimuli are not well understood. Spike-timing-dependent plasticity (STDP is a typical synaptic plasticity that has been extensively found in the sensory systems and that has received much theoretical attention. This synaptic plasticity is highly sensitive to correlations between pre- and postsynaptic firings. Thus, STDP is expected to play an important role in response to external asynchronous stimuli, which can induce segregative pre- and postsynaptic firings. In this paper, we study the impact of external asynchronous stimuli on the organization of structure and dynamics of neural networks through STDP. We construct a two-dimensional spatial neural network model with local connectivity and sparseness, and use external currents to stimulate alternately on different spatial layers. The adopted external currents imposed alternately on spatial layers can be here regarded as external asynchronous stimuli. Through extensive numerical simulations, we focus on the effects of stimulus number and inter-stimulus timing on synaptic connecting weights and the property of propagation dynamics in the resulting network structure. Interestingly, the resulting feedforward structure induced by stimulus-dependent asynchronous firings and its propagation dynamics reflect both the underlying property of STDP. The results imply a possible important role of STDP in generating feedforward structure and collective propagation activity required for experience-dependent map plasticity in developing in vivo sensory pathways and cortices. The relevance of the results to cue-triggered recall of learned temporal sequences, an important cognitive function, is briefly discussed as well. Furthermore, this finding suggests a potential

Application of cross-correlated delay shift rule in spiking neural networks for interictal spike detection.

Science.gov (United States)

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

2016-08-01

This study proposes a Cross-Correlated Delay Shift (CCDS) supervised learning rule to train neurons with associated spatiotemporal patterns to classify spike patterns. The objective of this study was to evaluate the feasibility of using the CCDS rule to automate the detection of interictal spikes in electroencephalogram (EEG) data on patients with epilepsy. Encoding is the initial yet essential step for spiking neurons to process EEG patterns. A new encoding method is utilized to convert the EEG signal into spike patterns. The simulation results show that the proposed algorithm identified 69 spikes out of 82 spikes, or 84% detection rate, which is quite high considering the subtleties of interictal spikes and the tediousness of monitoring long EEG records. This CCDS rule is also benchmarked by ReSuMe on the same task.

Induced proteins in human melanomas by γ-ray

International Nuclear Information System (INIS)

Ohnishi, T.; Ihara, M.; Utsumi, H.

1992-01-01

When cells are exposed to environmental stresses such as heat, chemicals, radiation, the cells respond to them by synthesizing a characteristic group of proteins, called stress proteins. There are many famous stress proteins: heat shock proteins and metallothionein. Treated cells have a protective mechanism against these environmental stresses. SOS responses in Escherichia coli are most famous. As the mechanisms, when cells are exposed by many kinds of DNA damage agents, various enzymes are induced after the cleavage of repressor protein LexA by activated RecA enzyme. Thereafter, induced proteins act for DNA repair and mutagenesis. In mammalian cells there are many reports about inducible genes such as O 6 -methylguanine methyltransferase gene. This gene was also inducible by alkylating agents. The difference of radiation sensitivities may be reflected by the contents of repair enzymes(s) or the induced proteins. Therefore, this study aims on the differences in inducible proteins between radiosensitive cells and control cells. Since it was hypothesized that induced proteins concerning to DNA damage repair or the proteins to recognize the damage may exist in the nuclei, induced proteins in nuclei of γ-ray irradiated cells were analyzed. (author). 5 refs., 1 tab

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.

Spike rate and spike timing contributions to coding taste quality information in rat periphery

Directory of Open Access Journals (Sweden)

Vernon eLawhern

2011-05-01

Full Text Available There is emerging evidence that individual sensory neurons in the rodent brain rely on temporal features of the discharge pattern to code differences in taste quality information. In contrast, in-vestigations of individual sensory neurons in the periphery have focused on analysis of spike rate and mostly disregarded spike timing as a taste quality coding mechanism. The purpose of this work was to determine the contribution of spike timing to taste quality coding by rat geniculate ganglion neurons using computational methods that have been applied successfully in other sys-tems. We recorded the discharge patterns of narrowly-tuned and broadly-tuned neurons in the rat geniculate ganglion to representatives of the five basic taste qualities. We used mutual in-formation to determine significant responses and the van Rossum metric to characterize their temporal features. While our findings show that spike timing contributes a significant part of the message, spike rate contributes the largest portion of the message relayed by afferent neurons from rat fungiform taste buds to the brain. Thus, spike rate and spike timing together are more effective than spike rate alone in coding stimulus quality information to a single basic taste in the periphery for both narrowly-tuned specialist and broadly-tuned generalist neurons.

Relationship between focal penicillin spikes and cortical spindles in the cerveau isolé cat.

Science.gov (United States)

McLachlan, R S; Kaibara, M; Girvin, J P

1983-01-01

Using the unanesthetized, cerveau isolé preparation in the cat, the association between artificially induced penicillin (PCN) spikes and spontaneously occurring electrocorticographic (ECoG) spindles was investigated. Spikes were elicited by surface application of small pledgets of PCN. After the application of PCN, there was a decrease in spindle amplitude but no change in frequency, duration, or spindle wave frequency in the area of the focus. Examination of the times of occurrence of the spikes and spindles disclosed that in the majority of cases, within a few minutes of the initiation of the foci, there was very high simultaneity, usually 100% between the occurrences of these two events. Examination of the times of occurrence of the spikes within the ECoG spindles failed to disclose any compelling evidence which would favor either the hypothesis that spikes "trigger" spindles or the hypothesis that spindles predispose to focal spikes. Thus, whether spikes trigger spindles, or spikes simply occur in a nonspecific manner during the occurrence of the spindle, or whether it is a combination of both these explanations, must remain an open question on the basis of the data available.

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.

Spike-timing-based computation in sound localization.

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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.

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

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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.

The structure of the bacteriophage PRD1 spike sheds light on the evolution of viral capsid architecture.

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Merckel, Michael C; Huiskonen, Juha T; Bamford, Dennis H; Goldman, Adrian; Tuma, Roman

2005-04-15

Comparisons of bacteriophage PRD1 and adenovirus protein structures and virion architectures have been instrumental in unraveling an evolutionary relationship and have led to a proposal of a phylogeny-based virus classification. The structure of the PRD1 spike protein P5 provides further insight into the evolution of viral proteins. The crystallized P5 fragment comprises two structural domains: a globular knob and a fibrous shaft. The head folds into a ten-stranded jelly roll beta barrel, which is structurally related to the tumor necrosis factor (TNF) and the PRD1 coat protein domains. The shaft domain is a structural counterpart to the adenovirus spike shaft. The structural relationships between PRD1, TNF, and adenovirus proteins suggest that the vertex proteins may have originated from an ancestral TNF-like jelly roll coat protein via a combination of gene duplication and deletion.

Preparation of monoclonal antibodies against radiation-induced protein

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Nozawa, R.; Tanaka, A.; Watanabe, H.; Kitayama, S.

1992-01-01

We obtained the 6 monoclonal antibodies against gamma-induced proteins of Deinococcus radiodurans, and these antibodies were designated as Mab-3F, 4B, 4D, 4F, 4G and 12G. Using these antibodies, we investigated the relations between gamma-induced proteins and other stress protein in strain R1, and the induction of proteins were compared among strain R1, resistant mutant (rec1) and radiosensitive mutant (rec30). We found new 6 proteins recognized by these monoclonal antibodies which were induced after gamma-irradiation especially in strain R1 and rec 1, but not induced in strain rec30. We suppose that these proteins participate in repair of DNA damages including double strand breaks caused by gamma-irradiation. One of them was around 46kDa protein band recognized by Mab-12G, and this protein was so induced in a large quantity after irradiation that the protein could detect by gold staining. In addition to this observation, we found some proteins which were induced in R1 and rec 1 by gamma-irradiation and other stress, but not in strain rec30, such as 31kDa protein band recognized by Mab-3F, 4B and 4G, and other 11 proteins which were especially induced in irradiated strain R1. The latter proteins might be reinforcement factor to radioresistance such as GroE and DnaK, or participant in repair of damage by gamma-irradiation in strain R1. (author)

Origins of pressure-induced protein transitions.

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Chalikian, Tigran V; Macgregor, Robert B

2009-12-18

The molecular mechanisms underlying pressure-induced protein denaturation can be analyzed based on the pressure-dependent differences in the apparent volume occupied by amino acids inside the protein and when they are exposed to water in an unfolded conformation. We present here an analysis for the peptide group and the 20 naturally occurring amino acid side chains based on volumetric parameters for the amino acids in the interior of the native state, the micelle-like interior of the pressure-induced denatured state, and the unfolded conformation modeled by N-acetyl amino acid amides. The transfer of peptide groups from the protein interior to water becomes increasingly favorable as pressure increases. Thus, solvation of peptide groups represents a major driving force in pressure-induced protein denaturation. Polar side chains do not appear to exhibit significant pressure-dependent changes in their preference for the protein interior or solvent. The transfer of nonpolar side chains from the protein interior to water becomes more unfavorable as pressure increases. We conclude that a sizeable population of nonpolar side chains remains buried inside a solvent-inaccessible core of the pressure-induced denatured state. At elevated pressures, this core may become packed almost as tightly as the interior of the native state. The presence and partial disappearance of large intraglobular voids is another driving force facilitating pressure-induced denaturation of individual proteins. Our data also have implications for the kinetics of protein folding and shed light on the nature of the folding transition state ensemble.

GABAergic activities control spike timing- and frequency-dependent long-term depression at hippocampal excitatory synapses

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Makoto Nishiyama

2010-06-01

Full Text Available GABAergic interneuronal network activities in the hippocampus control a variety of neural functions, including learning and memory, by regulating θ and γ oscillations. How these GABAergic activities at pre- and post-synaptic sites of hippocampal CA1 pyramidal cells differentially contribute to synaptic function and plasticity during their repetitive pre- and post-synaptic spiking at θ and γ oscillations is largely unknown. We show here that activities mediated by postsynaptic GABAARs and presynaptic GABABRs determine, respectively, the spike timing- and frequency-dependence of activity-induced synaptic modifications at Schaffer collateral-CA1 excitatory synapses. We demonstrate that both feedforward and feedback GABAAR-mediated inhibition in the postsynaptic cell controls the spike timing-dependent long-term depression of excitatory inputs (“e-LTD” at the θ frequency. We also show that feedback postsynaptic inhibition specifically causes e-LTD of inputs that induce small postsynaptic currents (<70 pA with LTP timing, thus enforcing the requirement of cooperativity for induction of long-term potentiation at excitatory inputs (“e-LTP”. Furthermore, under spike-timing protocols that induce e-LTP and e-LTD at excitatory synapses, we observed parallel induction of LTP and LTD at inhibitory inputs (“i-LTP” and “i-LTD” to the same postsynaptic cells. Finally, we show that presynaptic GABABR-mediated inhibition plays a major role in the induction of frequency-dependent e-LTD at α and β frequencies. These observations demonstrate the critical influence of GABAergic interneuronal network activities in regulating the spike timing and frequency dependences of long-term synaptic modifications in the hippocampus.

Synaptic convergence regulates synchronization-dependent spike transfer in feedforward neural networks.

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Sailamul, Pachaya; Jang, Jaeson; Paik, Se-Bum

2017-12-01

Correlated neural activities such as synchronizations can significantly alter the characteristics of spike transfer between neural layers. However, it is not clear how this synchronization-dependent spike transfer can be affected by the structure of convergent feedforward wiring. To address this question, we implemented computer simulations of model neural networks: a source and a target layer connected with different types of convergent wiring rules. In the Gaussian-Gaussian (GG) model, both the connection probability and the strength are given as Gaussian distribution as a function of spatial distance. In the Uniform-Constant (UC) and Uniform-Exponential (UE) models, the connection probability density is a uniform constant within a certain range, but the connection strength is set as a constant value or an exponentially decaying function, respectively. Then we examined how the spike transfer function is modulated under these conditions, while static or synchronized input patterns were introduced to simulate different levels of feedforward spike synchronization. We observed that the synchronization-dependent modulation of the transfer function appeared noticeably different for each convergence condition. The modulation of the spike transfer function was largest in the UC model, and smallest in the UE model. Our analysis showed that this difference was induced by the different spike weight distributions that was generated from convergent synapses in each model. Our results suggest that, the structure of the feedforward convergence is a crucial factor for correlation-dependent spike control, thus must be considered important to understand the mechanism of information transfer in the brain.

Information transmission with spiking Bayesian neurons

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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

Proteolytic activation of the SARS-coronavirus spike protein: cutting enzymes at the cutting edge of antiviral research.

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Simmons, Graham; Zmora, Pawel; Gierer, Stefanie; Heurich, Adeline; Pöhlmann, Stefan

2013-12-01

The severe acute respiratory syndrome (SARS) pandemic revealed that zoonotic transmission of animal coronaviruses (CoV) to humans poses a significant threat to public health and warrants surveillance and the development of countermeasures. The activity of host cell proteases, which cleave and activate the SARS-CoV spike (S) protein, is essential for viral infectivity and constitutes a target for intervention. However, the identities of the proteases involved have been unclear. Pioneer studies identified cathepsins and type II transmembrane serine proteases as cellular activators of SARS-CoV and demonstrated that several emerging viruses might exploit these enzymes to promote their spread. Here, we will review the proteolytic systems hijacked by SARS-CoV for S protein activation, we will discuss their contribution to viral spread in the host and we will outline antiviral strategies targeting these enzymes. This paper forms part of a series of invited articles in Antiviral Research on "From SARS to MERS: 10years of research on highly pathogenic human coronaviruses.'' Copyright © 2013 Elsevier B.V. All rights reserved.

Adrenalectomy eliminates the extinction spike in autoshaping with rats.

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Thomas, B L; Papini, M R

2001-03-01

Experiment 1, using rats, investigated the effect of adrenalectomy (ADX) on the invigoration of lever-contact performance that occurs in the autoshaping situation after a shift from acquisition to extinction (called the extinction spike). Groups of rats with ADX or sham operations were trained under spaced and massed conditions [average intertrial intervals (ITI) of either 15 or 90 s] for 10 sessions and then shifted to extinction. ADX did not affect acquisition training but it eliminated the extinction spike. Plasma corticosterone levels during acquisition were shown in Experiment 2 to be similar in rats trained under spaced or massed conditions. Adrenal participation in the emotional arousal induced by conditions of surprising nonreward (e.g., extinction) is discussed.

Barbed micro-spikes for micro-scale biopsy

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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.

Kinetic Modeling of Methionine Oxidation in Monoclonal Antibodies from Hydrogen Peroxide Spiking Studies.

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Hui, Ada; Lam, Xanthe M; Kuehl, Christopher; Grauschopf, Ulla; Wang, Y John

2015-01-01

When isolator technology is applied to biotechnology drug product fill-finish process, hydrogen peroxide (H2O2) spiking studies for the determination of the sensitivity of protein to residual peroxide in the isolator can be useful for assessing a maximum vapor phase hydrogen peroxide (VPHP) level. When monoclonal antibody (mAb) drug products were spiked with H2O2, an increase in methionine (Met 252 and Met 428) oxidation in the Fc region of the mAbs with a decrease in H2O2 concentration was observed for various levels of spiked-in peroxide. The reaction between Fc-Met and H2O2 was stoichiometric (i.e., 1:1 molar ratio), and the reaction rate was dependent on the concentrations of mAb and H2O2. The consumption of H2O2 by Fc-Met oxidation in the mAb followed pseudo first-order kinetics, and the rate was proportional to mAb concentration. The extent of Met 428 oxidation was half of that of Met 252, supporting that Met 252 is twice as reactive as Met 428. Similar results were observed for free L-methionine when spiked with H2O2. However, mAb formulation excipients may affect the rate of H2O2 consumption. mAb formulations containing trehalose or sucrose had faster H2O2 consumption rates than formulations without the sugars, which could be the result of impurities (e.g., metal ions) present in the excipients that may act as catalysts. Based on the H2O2 spiking study results, we can predict the amount Fc-Met oxidation for a given protein concentration and H2O2 level. Our kinetic modeling of the reaction between Fc-Met oxidation and H2O2 provides an outline to design a H2O2 spiking study to support the use of VPHP isolator for antibody drug product manufacture. Isolator technology is increasing used in drug product manufacturing of biotherapeutics. In order to understand the impact of residual vapor phase hydrogen peroxide (VPHP) levels on protein product quality, hydrogen peroxide (H2O2) spiking studies may be performed to determine the sensitivity of monoclonal antibody

Forskolin suppresses delayed-rectifier K+ currents and enhances spike frequency-dependent adaptation of sympathetic neurons.

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Angel-Chavez, Luis I; Acosta-Gómez, Eduardo I; Morales-Avalos, Mario; Castro, Elena; Cruzblanca, Humberto

2015-01-01

In signal transduction research natural or synthetic molecules are commonly used to target a great variety of signaling proteins. For instance, forskolin, a diterpene activator of adenylate cyclase, has been widely used in cellular preparations to increase the intracellular cAMP level. However, it has been shown that forskolin directly inhibits some cloned K+ channels, which in excitable cells set up the resting membrane potential, the shape of action potential and regulate repetitive firing. Despite the growing evidence indicating that K+ channels are blocked by forskolin, there are no studies yet assessing the impact of this mechanism of action on neuron excitability and firing patterns. In sympathetic neurons, we find that forskolin and its derivative 1,9-Dideoxyforskolin, reversibly suppress the delayed rectifier K+ current (IKV). Besides, forskolin reduced the spike afterhyperpolarization and enhanced the spike frequency-dependent adaptation. Given that IKV is mostly generated by Kv2.1 channels, HEK-293 cells were transfected with cDNA encoding for the Kv2.1 α subunit, to characterize the mechanism of forskolin action. Both drugs reversible suppressed the Kv2.1-mediated K+ currents. Forskolin inhibited Kv2.1 currents and IKV with an IC50 of ~32 μM and ~24 µM, respectively. Besides, the drug induced an apparent current inactivation and slowed-down current deactivation. We suggest that forskolin reduces the excitability of sympathetic neurons by enhancing the spike frequency-dependent adaptation, partially through a direct block of their native Kv2.1 channels.

Deficient incorporation of spike protein into virions contributes to the lack of infectivity following establishment of a persistent, non-productive infection in oligodendroglial cell culture by murine coronavirus

International Nuclear Information System (INIS)

Liu Yin; Herbst, Werner; Cao Jianzhong; Zhang Xuming

2011-01-01

Infection of mouse oligodendrocytes with a recombinant mouse hepatitis virus (MHV) expressing a green fluorescence protein facilitated specific selection of virus-infected cells and subsequent establishment of persistence. Interestingly, while viral genomic RNAs persisted in infected cells over 14 subsequent passages with concomitant synthesis of viral subgenomic mRNAs and structural proteins, no infectious virus was isolated beyond passage 2. Further biochemical and electron microscopic analyses revealed that virions, while assembled, contained little spike in the envelope, indicating that lack of infectivity during persistence was likely due to deficiency in spike incorporation. This type of non-lytic, non-productive persistence in oligodendrocytes is unique among animal viruses and resembles MHV persistence previously observed in the mouse central nervous system. Thus, establishment of such a culture system that can recapitulate the in vivo phenomenon will provide a powerful approach for elucidating the mechanisms of coronavirus persistence in glial cells at the cellular and molecular levels.

Bayesian population decoding of spiking neurons.

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Gerwinn, Sebastian; Macke, Jakob; Bethge, Matthias

2009-01-01

The timing of action potentials in spiking neurons depends on the temporal dynamics of their inputs and contains information about temporal fluctuations in the stimulus. Leaky integrate-and-fire neurons constitute a popular class of encoding models, in which spike times depend directly on the temporal structure of the inputs. However, optimal decoding rules for these models have only been studied explicitly in the noiseless case. Here, we study decoding rules for probabilistic inference of a continuous stimulus from the spike times of a population of leaky integrate-and-fire neurons with threshold noise. We derive three algorithms for approximating the posterior distribution over stimuli as a function of the observed spike trains. In addition to a reconstruction of the stimulus we thus obtain an estimate of the uncertainty as well. Furthermore, we derive a 'spike-by-spike' online decoding scheme that recursively updates the posterior with the arrival of each new spike. We use these decoding rules to reconstruct time-varying stimuli represented by a Gaussian process from spike trains of single neurons as well as neural populations.

Bayesian population decoding of spiking neurons

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Sebastian Gerwinn

2009-10-01

Full Text Available The timing of action potentials in spiking neurons depends on the temporal dynamics of their inputs and contains information about temporal fluctuations in the stimulus. Leaky integrate-and-fire neurons constitute a popular class of encoding models, in which spike times depend directly on the temporal structure of the inputs. However, optimal decoding rules for these models have only been studied explicitly in the noiseless case. Here, we study decoding rules for probabilistic inference of a continuous stimulus from the spike times of a population of leaky integrate-and-fire neurons with threshold noise. We derive three algorithms for approximating the posterior distribution over stimuli as a function of the observed spike trains. In addition to a reconstruction of the stimulus we thus obtain an estimate of the uncertainty as well. Furthermore, we derive a `spike-by-spike' online decoding scheme that recursively updates the posterior with the arrival of each new spike. We use these decoding rules to reconstruct time-varying stimuli represented by a Gaussian process from spike trains of single neurons as well as neural populations.

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

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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

The host-binding domain of the P2 phage tail spike reveals a trimeric iron-binding structure

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Yamashita, Eiki; Nakagawa, Atsushi; Takahashi, Junichi; Tsunoda, Kin-ichi; Yamada, Seiko; Takeda, Shigeki

2011-01-01

The C-terminal domain of a bacteriophage P2 tail-spike protein, gpV, was crystallized and its structure was solved at 1.27 Å resolution. The refined model showed a triple β-helix structure and the presence of iron, calcium and chloride ions. The adsorption and infection of bacteriophage P2 is mediated by tail fibres and tail spikes. The tail spikes on the tail baseplate are used to irreversibly adsorb to the host cells. Recently, a P2 phage tail-spike protein, gpV, was purified and it was shown that a C-terminal domain, Ser87–Leu211, is sufficient for the binding of gpV to host Escherichia coli membranes [Kageyama et al. (2009 ▶), Biochemistry, 48, 10129–10135]. In this paper, the crystal structure of the C-terminal domain of P2 gpV is reported. The structure is a triangular pyramid and looks like a spearhead composed of an intertwined β-sheet, a triple β-helix and a metal-binding region containing iron, calcium and chloride ions

Human coronavirus 229E encodes a single ORF4 protein between the spike and the envelope genes

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Berkhout Ben

2006-12-01

Full Text Available Abstract Background The genome of coronaviruses contains structural and non-structural genes, including several so-called accessory genes. All group 1b coronaviruses encode a single accessory protein between the spike and envelope genes, except for human coronavirus (HCoV 229E. The prototype virus has a split gene, encoding the putative ORF4a and ORF4b proteins. To determine whether primary HCoV-229E isolates exhibit this unusual genome organization, we analyzed the ORF4a/b region of five current clinical isolates from The Netherlands and three early isolates collected at the Common Cold Unit (CCU in Salisbury, UK. Results All Dutch isolates were identical in the ORF4a/b region at amino acid level. All CCU isolates are only 98% identical to the Dutch isolates at the nucleotide level, but more closely related to the prototype HCoV-229E (>98%. Remarkably, our analyses revealed that the laboratory adapted, prototype HCoV-229E has a 2-nucleotide deletion in the ORF4a/b region, whereas all clinical isolates carry a single ORF, 660 nt in size, encoding a single protein of 219 amino acids, which is a homologue of the ORF3 proteins encoded by HCoV-NL63 and PEDV. Conclusion Thus, the genome organization of the group 1b coronaviruses HCoV-NL63, PEDV and HCoV-229E is identical. It is possible that extensive culturing of the HCoV-229E laboratory strain resulted in truncation of ORF4. This may indicate that the protein is not essential in cell culture, but the highly conserved amino acid sequence of the ORF4 protein among clinical isolates suggests that the protein plays an important role in vivo.

Improved SpikeProp for Using Particle Swarm Optimization

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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.

Characterization of radiation-induced proteins in Deinococcus radiodurans

International Nuclear Information System (INIS)

Tanaka, A.; Watanabe, H.; Nozawa, R.; Hu, Q.; Kitayama, S.

1992-01-01

Induction of proteins after gamma-irradiation in Deinococcus radiodurans were investigated. 10 proteins were induced and about 15 proteins were reduced after irradiation with 6kGy. These proteins were classified to four groups by responses to gamma-rays, UV light, mitomycin C(MMC) treatment and heating. Additional studies were carried out for the characterization of two induced proteins. One protein was induced by gamma-rays, UV light as well as heating. This protein appeared to be a glycoprotein from its reaction with lectin. From the amino acid sequences of N-terminal and internal region, it was found that this protein is homologous to EF-Tu protein of E. coli. Meanwhile the other protein was induced not only by gamma-rays but also by UV light and MMC treatment. This protein seems to be a new enzyme as it has no homology to the known proteins which have ever been analyzed. No accumulations of these two proteins were observed in radiation sensitive strain of D. radiodurans and in both of E. coli and Bacillus pumilus, suggesting that induction of these two proteins would be specific for high resistant strain. (author)

Reflex reading epilepsy: effect of linguistic characteristics on spike frequency.

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Safi, Dima; Lassonde, Maryse; Nguyen, Dang Khoa; Denault, Carole; Macoir, Joël; Rouleau, Isabelle; Béland, Renée

2011-04-01

Reading epilepsy is a rare reflex epilepsy in which seizures are provoked by reading. Several cases have been described in the literature, but the pathophysiological processes vary widely and remain unclear. We describe a 42-year-old male patient with reading epilepsy evaluated using clinical assessments and continuous video/EEG recordings. We administered verbal, nonverbal, and reading tasks to determine factors precipitating seizures. Linguistic characteristics of the words were manipulated. Results indicated that reading-induced seizures were significantly more numerous than those observed during verbal and nonverbal tasks. In reading tasks, spike frequency significantly increased with involvement of the phonological reading route. Spikes were recorded predominantly in left parasagittal regions. Future cerebral imaging studies will enable us to visualize the spatial localization and temporal course of reading-induced seizures and brain activity involved in reading. A better understanding of reading epilepsy is crucial for reading rehabilitation in these patients. Copyright © 2011 Elsevier Inc. All rights reserved.

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

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

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Claire Ramus

2016-03-01

Full Text Available 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 http://www.ebi.ac.uk/pride/archive/projects/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.

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

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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.

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.

Effects of Spike Anticipation on the Spiking Dynamics of Neural Networks

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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.

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

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de Santos-Sierra, Daniel; Sanchez-Jimenez, Abel; Garcia-Vellisca, Mariano A; Navas, Adrian; Villacorta-Atienza, Jose A

2015-01-01

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 (Pyragiene and Pyragas, 2013), where the slave neuron is able to anticipate in time the behavior 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 with 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.

Modeling thermal spike driven reactions at low temperature and application to zirconium carbide radiation damage

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Ulmer, Christopher J.; Motta, Arthur T.

2017-11-01

The development of TEM-visible damage in materials under irradiation at cryogenic temperatures cannot be explained using classical rate theory modeling with thermally activated reactions since at low temperatures thermal reaction rates are too low. Although point defect mobility approaches zero at low temperature, the thermal spikes induced by displacement cascades enable some atom mobility as it cools. In this work a model is developed to calculate "athermal" reaction rates from the atomic mobility within the irradiation-induced thermal spikes, including both displacement cascades and electronic stopping. The athermal reaction rates are added to a simple rate theory cluster dynamics model to allow for the simulation of microstructure evolution during irradiation at cryogenic temperatures. The rate theory model is applied to in-situ irradiation of ZrC and compares well at cryogenic temperatures. The results show that the addition of the thermal spike model makes it possible to rationalize microstructure evolution in the low temperature regime.

Simulation studies of protein-induced bilayer deformations, and lipid-induced protein tilting, on a mesoscopic model for lipid bilayers with embedded proteins

DEFF Research Database (Denmark)

Venturoli, M.; Smit, B.; Sperotto, Maria Maddalena

2005-01-01

membranes. Here we present a mesoscopic model for lipid bilayers with embedded proteins, which we have studied with the help of the dissipative particle dynamics simulation technique. Because hydrophobic matching is believed to be one of the main physical mechanisms regulating lipid-protein interactions......-induced protein tilt, with the hydrophobic mismatch ( positive and negative) between the protein hydrophobic length and the pure lipid bilayer hydrophobic thickness. The protein-induced bilayer perturbation was quantified in terms of a coherence length, xi(P), of the lipid bilayer hydrophobic thickness pro. le...... for positive values of mismatch; a dependence on the protein size appears as well. In the case of large model proteins experiencing extreme mismatch conditions, in the region next to the so-called lipid annulus, there appears an undershooting ( or overshooting) region where the bilayer hydrophobic thickness...

Spike-based population coding and working memory.

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Martin Boerlin

2011-02-01

Full Text Available Compelling behavioral evidence suggests that humans can make optimal decisions despite the uncertainty inherent in perceptual or motor tasks. A key question in neuroscience is how populations of spiking neurons can implement such probabilistic computations. In this article, we develop a comprehensive framework for optimal, spike-based sensory integration and working memory in a dynamic environment. We propose that probability distributions are inferred spike-per-spike in recurrently connected networks of integrate-and-fire neurons. As a result, these networks can combine sensory cues optimally, track the state of a time-varying stimulus and memorize accumulated evidence over periods much longer than the time constant of single neurons. Importantly, we propose that population responses and persistent working memory states represent entire probability distributions and not only single stimulus values. These memories are reflected by sustained, asynchronous patterns of activity which make relevant information available to downstream neurons within their short time window of integration. Model neurons act as predictive encoders, only firing spikes which account for new information that has not yet been signaled. Thus, spike times signal deterministically a prediction error, contrary to rate codes in which spike times are considered to be random samples of an underlying firing rate. As a consequence of this coding scheme, a multitude of spike patterns can reliably encode the same information. This results in weakly correlated, Poisson-like spike trains that are sensitive to initial conditions but robust to even high levels of external neural noise. This spike train variability reproduces the one observed in cortical sensory spike trains, but cannot be equated to noise. On the contrary, it is a consequence of optimal spike-based inference. In contrast, we show that rate-based models perform poorly when implemented with stochastically spiking neurons.

Consensus-Based Sorting of Neuronal Spike Waveforms.

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Fournier, Julien; Mueller, Christian M; Shein-Idelson, Mark; Hemberger, Mike; Laurent, Gilles

2016-01-01

Optimizing spike-sorting algorithms is difficult because sorted clusters can rarely be checked against independently obtained "ground truth" data. In most spike-sorting algorithms in use today, the optimality of a clustering solution is assessed relative to some assumption on the distribution of the spike shapes associated with a particular single unit (e.g., Gaussianity) and by visual inspection of the clustering solution followed by manual validation. When the spatiotemporal waveforms of spikes from different cells overlap, the decision as to whether two spikes should be assigned to the same source can be quite subjective, if it is not based on reliable quantitative measures. We propose a new approach, whereby spike clusters are identified from the most consensual partition across an ensemble of clustering solutions. Using the variability of the clustering solutions across successive iterations of the same clustering algorithm (template matching based on K-means clusters), we estimate the probability of spikes being clustered together and identify groups of spikes that are not statistically distinguishable from one another. Thus, we identify spikes that are most likely to be clustered together and therefore correspond to consistent spike clusters. This method has the potential advantage that it does not rely on any model of the spike shapes. It also provides estimates of the proportion of misclassified spikes for each of the identified clusters. We tested our algorithm on several datasets for which there exists a ground truth (simultaneous intracellular data), and show that it performs close to the optimum reached by a support vector machine trained on the ground truth. We also show that the estimated rate of misclassification matches the proportion of misclassified spikes measured from the ground truth data.

Status Epilepticus Induced Spontaneous Dentate Gyrus Spikes: In Vivo Current Source Density Analysis.

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Sean P Flynn

Full Text Available The dentate gyrus is considered to function as an inhibitory gate limiting excitatory input to the hippocampus. Following status epilepticus (SE, this gating function is reduced and granule cells become hyper-excitable. Dentate spikes (DS are large amplitude potentials observed in the dentate gyrus (DG of normal animals. DS are associated with membrane depolarization of granule cells, increased activity of hilar interneurons and suppression of CA3 and CA1 pyramidal cell firing. Therefore, DS could act as an anti-excitatory mechanism. Because of the altered gating function of the dentate gyrus following SE, we sought to investigate how DS are affected following pilocarpine-induced SE. Two weeks following lithium-pilocarpine SE induction, hippocampal EEG was recorded in male Sprague-Dawley rats with 16-channel silicon probes under urethane anesthesia. Probes were placed dorso-ventrally to encompass either CA1-CA3 or CA1-DG layers. Large amplitude spikes were detected from EEG recordings and subject to current source density analysis. Probe placement was verified histologically to evaluate the anatomical localization of current sinks and the origin of DS. In 9 of 11 pilocarpine-treated animals and two controls, DS were confirmed with large current sinks in the molecular layer of the dentate gyrus. DS frequency was significantly increased in pilocarpine-treated animals compared to controls. Additionally, in pilocarpine-treated animals, DS displayed current sinks in the outer, middle and/or inner molecular layers. However, there was no difference in the frequency of events when comparing between layers. This suggests that following SE, DS can be generated by input from medial and lateral entorhinal cortex, or within the dentate gyrus. DS were associated with an increase in multiunit activity in the granule cell layer, but no change in CA1. These results suggest that following SE there is an increase in DS activity, potentially arising from

Visually Evoked Spiking Evolves While Spontaneous Ongoing Dynamics Persist

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Huys, Raoul; Jirsa, Viktor K.; Darokhan, Ziauddin; Valentiniene, Sonata; Roland, Per E.

2016-01-01

Neurons in the primary visual cortex spontaneously spike even when there are no visual stimuli. It is unknown whether the spiking evoked by visual stimuli is just a modification of the spontaneous ongoing cortical spiking dynamics or whether the spontaneous spiking state disappears and is replaced 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 attractor. Its existence guarantees that evoked spiking return to the spontaneous state. However, the spontaneous ongoing spiking state and the visual evoked spiking states are qualitatively different and are separated by a threshold (separatrix). The functional advantage of this organization is that it avoids the need for a system reorganization following visual stimulation, and impedes the transition of spontaneous spiking to evoked spiking and the propagation of spontaneous spiking from layer 4 to layers 2–3. PMID:26778982

Distinct retrosplenial cortex cell populations and their spike dynamics during ketamine-induced unconscious state.

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Grace E Fox

Full Text Available Ketamine is known to induce psychotic-like symptoms, including delirium and visual hallucinations. It also causes neuronal damage and cell death in the retrosplenial cortex (RSC, an area that is thought to be a part of high visual cortical pathways and at least partially responsible for ketamine's psychotomimetic activities. However, the basic physiological properties of RSC cells as well as their response to ketamine in vivo remained largely unexplored. Here, we combine a computational method, the Inter-Spike Interval Classification Analysis (ISICA, and in vivo recordings to uncover and profile excitatory cell subtypes within layers 2&3 and 5&6 of the RSC in mice within both conscious, sleep, and ketamine-induced unconscious states. We demonstrate two distinct excitatory principal cell sub-populations, namely, high-bursting excitatory principal cells and low-bursting excitatory principal cells, within layers 2&3, and show that this classification is robust over the conscious states, namely quiet awake, and natural unconscious sleep periods. Similarly, we provide evidence of high-bursting and low-bursting excitatory principal cell sub-populations within layers 5&6 that remained distinct during quiet awake and sleep states. We further examined how these subtypes are dynamically altered by ketamine. During ketamine-induced unconscious state, these distinct excitatory principal cell subtypes in both layer 2&3 and layer 5&6 exhibited distinct dynamics. We also uncovered different dynamics of local field potential under various brain states in layer 2&3 and layer 5&6. Interestingly, ketamine administration induced high gamma oscillations in layer 2&3 of the RSC, but not layer 5&6. Our results show that excitatory principal cells within RSC layers 2&3 and 5&6 contain multiple physiologically distinct sub-populations, and they are differentially affected by ketamine.

Forskolin suppresses delayed-rectifier K+ currents and enhances spike frequency-dependent adaptation of sympathetic neurons.

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Luis I Angel-Chavez

Full Text Available In signal transduction research natural or synthetic molecules are commonly used to target a great variety of signaling proteins. For instance, forskolin, a diterpene activator of adenylate cyclase, has been widely used in cellular preparations to increase the intracellular cAMP level. However, it has been shown that forskolin directly inhibits some cloned K+ channels, which in excitable cells set up the resting membrane potential, the shape of action potential and regulate repetitive firing. Despite the growing evidence indicating that K+ channels are blocked by forskolin, there are no studies yet assessing the impact of this mechanism of action on neuron excitability and firing patterns. In sympathetic neurons, we find that forskolin and its derivative 1,9-Dideoxyforskolin, reversibly suppress the delayed rectifier K+ current (IKV. Besides, forskolin reduced the spike afterhyperpolarization and enhanced the spike frequency-dependent adaptation. Given that IKV is mostly generated by Kv2.1 channels, HEK-293 cells were transfected with cDNA encoding for the Kv2.1 α subunit, to characterize the mechanism of forskolin action. Both drugs reversible suppressed the Kv2.1-mediated K+ currents. Forskolin inhibited Kv2.1 currents and IKV with an IC50 of ~32 μM and ~24 µM, respectively. Besides, the drug induced an apparent current inactivation and slowed-down current deactivation. We suggest that forskolin reduces the excitability of sympathetic neurons by enhancing the spike frequency-dependent adaptation, partially through a direct block of their native Kv2.1 channels.

Spike voltage topography in temporal lobe epilepsy.

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Asadi-Pooya, Ali A; Asadollahi, Marjan; Shimamoto, Shoichi; Lorenzo, Matthew; Sperling, Michael R

2016-07-15

We investigated the voltage topography of interictal spikes in patients with temporal lobe epilepsy (TLE) to see whether topography was related to etiology for TLE. Adults with TLE, who had epilepsy surgery for drug-resistant seizures from 2011 until 2014 at Jefferson Comprehensive Epilepsy Center were selected. Two groups of patients were studied: patients with mesial temporal sclerosis (MTS) on MRI and those with other MRI findings. The voltage topography maps of the interictal spikes at the peak were created using BESA software. We classified the interictal spikes as polar, basal, lateral, or others. Thirty-four patients were studied, from which the characteristics of 340 spikes were investigated. The most common type of spike orientation was others (186 spikes; 54.7%), followed by lateral (146; 42.9%), polar (5; 1.5%), and basal (3; 0.9%). Characteristics of the voltage topography maps of the spikes between the two groups of patients were somewhat different. Five spikes in patients with MTS had polar orientation, but none of the spikes in patients with other MRI findings had polar orientation (odds ratio=6.98, 95% confidence interval=0.38 to 127.38; p=0.07). Scalp topographic mapping of interictal spikes has the potential to offer different information than visual inspection alone. The present results do not allow an immediate clinical application of our findings; however, detecting a polar spike in a patient with TLE may increase the possibility of mesial temporal sclerosis as the underlying etiology. Copyright © 2016 Elsevier B.V. All rights reserved.

Mitigation of starch-induced postprandial glycemic spikes in rats by antioxidants-rich extract of Cicer arietinum Linn. seeds and sprouts

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Ashok Kumar Tiwari

2013-01-01

Full Text Available Introduction: Consumption of highly processed calories dense diet leads abrupt increase in postprandial blood glucose level, which in turn induces immediate oxidative stress. Postprandial hyperglycemia (PPHG and resultant oxidative stress is one of the earliest detectable abnormalities in diabetes prone individuals, independent risk factor for development of cardiovascular disorders (CVD, a major pathophysiological link between diabetes and CVD and an important contributing factor in atherogenesis even in non-diabetic individuals. Therefore, dietary supplements mitigating PPHG spikes along with potent antioxidant activities may help decrease development of PPHG and oxidative stress induced pathogenesis. Objectives: The study evaluated free radicals scavenging, antioxidant properties and intestinal α-glucosidase inhibitory activity in methanol extract of two varieties of Cicer arietinum Linn viz. Bengal gram and Kabuli chana and green gram (Vigna radiata Linn. Wilczek raw grains and their sprouts and studied their influence on starch-induced postprandial glycemic excursion in rats. Materials and Methods: Healthy grains were procured from local markets. Free radicals scavenging antioxidant and glucose-induced hemoglobin (Hb-glycation inhibition activities were analyzed using standard in vitro procedures. In vitro antihyperglycemic activity was evaluated by assessing rat intestinal α-glucosidase inhibitory activity. Influence on starch-induced postprandial glycemic excursion in rats was studied by pre-treatment of rats with extracts. Results: Compared with raw seeds increase in total polyphenol and flavonoids concentration in green gram sprouts and Kabuli chana sprouts (KCs were observed. Total protein concentrations in sprouts did not differ from non-sprouted grains. 2,2′- Azinobis (3-ethyl benzthiazoline-6-sulphonic acid cation scavenging activity was more than twice in Bengal gram sprouts of (BGs and KCs than their raw seeds. 2,2-diphenyl-1

Multineuronal Spike Sequences Repeat with Millisecond Precision

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Koki eMatsumoto

2013-06-01

Full Text Available Cortical microcircuits are nonrandomly wired by neurons. As a natural consequence, spikes emitted by microcircuits are also nonrandomly patterned in time and space. One of the prominent spike organizations is a repetition of fixed patterns of spike series across multiple neurons. However, several questions remain unsolved, including how precisely spike sequences repeat, how the sequences are spatially organized, how many neurons participate in sequences, and how different sequences are functionally linked. To address these questions, we monitored spontaneous spikes of hippocampal CA3 neurons ex vivo using a high-speed functional multineuron calcium imaging technique that allowed us to monitor spikes with millisecond resolution and to record the location of spiking and nonspiking neurons. Multineuronal spike sequences were overrepresented in spontaneous activity compared to the statistical chance level. Approximately 75% of neurons participated in at least one sequence during our observation period. The participants were sparsely dispersed and did not show specific spatial organization. The number of sequences relative to the chance level decreased when larger time frames were used to detect sequences. Thus, sequences were precise at the millisecond level. Sequences often shared common spikes with other sequences; parts of sequences were subsequently relayed by following sequences, generating complex chains of multiple sequences.

Emergence of Slow Collective Oscillations in Neural Networks with Spike-Timing Dependent Plasticity

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Mikkelsen, Kaare; Imparato, Alberto; Torcini, Alessandro

2013-05-01

The collective dynamics of excitatory pulse coupled neurons with spike-timing dependent plasticity is studied. The introduction of spike-timing dependent plasticity induces persistent irregular oscillations between strongly and weakly synchronized states, reminiscent of brain activity during slow-wave sleep. We explain the oscillations by a mechanism, the Sisyphus Effect, caused by a continuous feedback between the synaptic adjustments and the coherence in the neural firing. Due to this effect, the synaptic weights have oscillating equilibrium values, and this prevents the system from relaxing into a stationary macroscopic state.

Spiking Neural P Systems with Communication on Request.

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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.

Self-control with spiking and non-spiking neural networks playing games.

Science.gov (United States)

Christodoulou, Chris; Banfield, Gaye; Cleanthous, Aristodemos

2010-01-01

Self-control can be defined as choosing a large delayed reward over a small immediate reward, while precommitment is the making of a choice with the specific aim of denying oneself future choices. Humans recognise that they have self-control problems and attempt to overcome them by applying precommitment. Problems in exercising self-control, suggest a conflict between cognition and motivation, which has been linked to competition between higher and lower brain functions (representing the frontal lobes and the limbic system respectively). This premise of an internal process conflict, lead to a behavioural model being proposed, based on which, we implemented a computational model for studying and explaining self-control through precommitment behaviour. Our model consists of two neural networks, initially non-spiking and then spiking ones, representing the higher and lower brain systems viewed as cooperating for the benefit of the organism. The non-spiking neural networks are of simple feed forward multilayer type with reinforcement learning, one with selective bootstrap weight update rule, which is seen as myopic, representing the lower brain and the other with the temporal difference weight update rule, which is seen as far-sighted, representing the higher brain. The spiking neural networks are implemented with leaky integrate-and-fire neurons with learning based on stochastic synaptic transmission. The differentiating element between the two brain centres in this implementation is based on the memory of past actions determined by an eligibility trace time constant. As the structure of the self-control problem can be likened to the Iterated Prisoner's Dilemma (IPD) game in that cooperation is to defection what self-control is to impulsiveness or what compromising is to insisting, we implemented the neural networks as two players, learning simultaneously but independently, competing in the IPD game. With a technique resembling the precommitment effect, whereby the

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.

Non-orthogonally transitive G2 spike solution

International Nuclear Information System (INIS)

Lim, Woei Chet

2015-01-01

We generalize the orthogonally transitive (OT) G 2 spike solution to the non-OT G 2 case. This is achieved by applying Geroch’s transformation on a Kasner seed. The new solution contains two more parameters than the OT G 2 spike solution. Unlike the OT G 2 spike solution, the new solution always resolves its spike. (fast track communication)

Wavelet analysis of epileptic spikes

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

2003-05-01

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.

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.

Decimetric type III radio bursts and associated hard X-ray spikes

Science.gov (United States)

Dennis, B. R.; Benz, A. O.; Ranieri, M.; Simnett, G. M.

1984-01-01

For a relatively weak solar flare on August 6, 1981, at 10:32 UT, a detailed comparison is made between hard X-ray spikes and decimetric type III radio bursts. The hard X-ray observations are made at energies above 30 keV, and the radio data are obtained in the frequency range from 100 to 1000 MHz. The time resolution for all the data sets is approximately 0.1 s or better. The dynamic radio spectrum exhibits many fast drift type III radio bursts with both normal and reverse slope, whereas the X-ray time profile contains many well resolved short spikes with durations less than or equal to 1 s. Some of the X-ray spikes are seen to be associated in time with reverse-slope bursts, indicating either that the electron beams producing the radio burst contain two or three orders of magnitude more fast electrons than has previously been assumed or that the electron beams can induce the acceleration of additional electrons or occur in coincidence with this acceleration. A case is presented in which a normal slope radio burst at approximately 600 MHz occurs in coincidence with the peak of an X-ray spike to within 0.1 s.

Characterization of novel monoclonal antibodies against the MERS-coronavirus spike protein and their application in species-independent antibody detection by competitive ELISA.

Science.gov (United States)

Fukushi, Shuetsu; Fukuma, Aiko; Kurosu, Takeshi; Watanabe, Shumpei; Shimojima, Masayuki; Shirato, Kazuya; Iwata-Yoshikawa, Naoko; Nagata, Noriyo; Ohnishi, Kazuo; Ato, Manabu; Melaku, Simenew Keskes; Sentsui, Hiroshi; Saijo, Masayuki

2018-01-01

Since discovering the Middle East respiratory syndrome coronavirus (MERS-CoV) as a causative agent of severe respiratory illness in the Middle East in 2012, serological testing has been conducted to assess antibody responses in patients and to investigate the zoonotic reservoir of the virus. Although the virus neutralization test is the gold standard assay for MERS diagnosis and for investigating the zoonotic reservoir, it uses live virus and so must be performed in high containment laboratories. Competitive ELISA (cELISA), in which a labeled monoclonal antibody (MAb) competes with test serum antibodies for target epitopes, may be a suitable alternative because it detects antibodies in a species-independent manner. In this study, novel MAbs against the spike protein of MERS-CoV were produced and characterized. One of these MAbs was used to develop a cELISA. The cELISA detected MERS-CoV-specific antibodies in sera from MERS-CoV-infected rats and rabbits immunized with the spike protein of MERS-CoV. The MAb-based cELISA was validated using sera from Ethiopian dromedary camels. Relative to the neutralization test, the cELISA detected MERS-CoV-specific antibodies in 66 Ethiopian dromedary camels with a sensitivity and specificity of 98% and 100%, respectively. The cELISA and neutralization test results correlated well (Pearson's correlation coefficients=0.71-0.76, depending on the cELISA serum dilution). This cELISA may be useful for MERS epidemiological investigations on MERS-CoV infection. Copyright © 2017 Elsevier B.V. All rights reserved.

Vented spikes improve delivery from intravenous bags with no air headspace.

Science.gov (United States)

Galush, William J; Horst, Travis A

2015-07-01

Flexible plastic bags are the container of choice for most intravenous (i.v.) infusions. Under certain circumstances, however, the air-liquid interface present in these i.v. bags can lead to physical instability of protein biopharmaceuticals, resulting in product aggregation. In principle, the air headspace present in the bags can be removed to increase drug stability, but experiments described here show that this can result in incomplete draining of solution from the bag using gravity delivery, or generation of negative pressure in the bag when an infusion pump is used. It is expected that these issues could lead to incomplete delivery of medication to patients or pump-related problems, respectively. However, here it is shown that contrary to the standard pharmacy practice of using nonvented spikes with i.v. bags, the use of vented spikes with i.v. bags that lack air headspace allows complete delivery of the dose solution without impacting the physical stability of a protein-based drug. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

Motor control by precisely timed spike patterns

DEFF Research Database (Denmark)

Srivastava, Kyle H; Holmes, Caroline M; Vellema, Michiel

2017-01-01

whether the information in spike timing actually plays a role in brain function. By examining the activity of individual motor units (the muscle fibers innervated by a single motor neuron) and manipulating patterns of activation of these neurons, we provide both correlative and causal evidence......A fundamental problem in neuroscience is understanding how sequences of action potentials ("spikes") encode information about sensory signals and motor outputs. Although traditional theories assume that this information is conveyed by the total number of spikes fired within a specified time...... interval (spike rate), recent studies have shown that additional information is carried by the millisecond-scale timing patterns of action potentials (spike timing). However, it is unknown whether or how subtle differences in spike timing drive differences in perception or behavior, leaving it unclear...

Generalized activity equations for spiking neural network dynamics

Directory of Open Access Journals (Sweden)

Michael A Buice

2013-11-01

Full Text Available Much progress has been made in uncovering the computational capabilities of spiking neural networks. However, spiking neurons will always be more expensive to simulate compared to rate neurons because of the inherent disparity in time scales - the spike duration time is much shorter than the inter-spike time, which is much shorter than any learning time scale. In numerical analysis, this is a classic stiff problem. Spiking neurons are also much more difficult to study analytically. One possible approach to making spiking networks more tractable is to augment mean field activity models with some information about spiking correlations. For example, such a generalized activity model could carry information about spiking rates and correlations between spikes self-consistently. Here, we will show how this can be accomplished by constructing a complete formal probabilistic description of the network and then expanding around a small parameter such as the inverse of the number of neurons in the network. The mean field theory of the system gives a rate-like description. The first order terms in the perturbation expansion keep track of covariances.

Spike-timing computation properties of a feed-forward neural network model

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Drew Benjamin Sinha

2014-01-01

Full Text Available Brain function is characterized by dynamical interactions among networks of neurons. These interactions are mediated by network topology at many scales ranging from microcircuits to brain areas. Understanding how networks operate can be aided by understanding how the transformation of inputs depends upon network connectivity patterns, e.g. serial and parallel pathways. To tractably determine how single synapses or groups of synapses in such pathways shape transformations, we modeled feed-forward networks of 7-22 neurons in which synaptic strength changed according to a spike-timing dependent plasticity rule. We investigated how activity varied when dynamics were perturbed by an activity-dependent electrical stimulation protocol (spike-triggered stimulation; STS in networks of different topologies and background input correlations. STS can successfully reorganize functional brain networks in vivo, but with a variability in effectiveness that may derive partially from the underlying network topology. In a simulated network with a single disynaptic pathway driven by uncorrelated background activity, structured spike-timing relationships between polysynaptically connected neurons were not observed. When background activity was correlated or parallel disynaptic pathways were added, however, robust polysynaptic spike timing relationships were observed, and application of STS yielded predictable changes in synaptic strengths and spike-timing relationships. These observations suggest that precise input-related or topologically induced temporal relationships in network activity are necessary for polysynaptic signal propagation. Such constraints for polysynaptic computation suggest potential roles for higher-order topological structure in network organization, such as maintaining polysynaptic correlation in the face of relatively weak synapses.

Protein Self-Assembly and Protein-Induced DNA Morphologies

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Mawhinney, Matthew T.

The ability of biomolecules to associate into various structural configurations has a substantial impact on human physiology. The synthesis of protein polypeptide chains using the information encoded by DNA is mediated through the use of regulatory proteins, known as transcription factors. Some transcription factors perform function by inducing local curvature in deoxyribonucleic acid (DNA) strands, the mechanisms of which are not entirely known. An important architectural protein, eleven zinc finger CTCF (11 ZF CTCF) is involved in genome organization and hypothesized to mediate DNA loop formation. Direct evidence for these CTCF-induced DNA loops has yet to be observed. In this thesis, the effect of 11 ZF CTCF on DNA morphology is examined using atomic force microscopy, a powerful technique for visualizing biomolecules with nanometer resolution. The presence of CTCF is revealed to induce a variety of morphologies deviating from the relaxed state of control DNA samples, including compact circular complexes, meshes, and networks. Images reveal quasi-circular DNA/CTCF complexes consistent with a single DNA molecule twice wrapped around the protein. The structures of DNA and proteins are highly important for operations in the cell. Structural irregularities may lead to a variety of issues, including more than twenty human pathologies resulting from aberrant protein misfolding into amyloid aggregates of elongated fibrils. Insulin deficiency and resistance characterizing type 2 diabetes often requires administration of insulin. Injectable and inhalable delivery methods have been documented to result in the deposition of amyloid fibrils. Oligomers, soluble multiprotein assemblies, are believed to play an important role in this process. Insulin aggregation under physiological conditions is not well understood and oligomers have not yet been fully characterized. In this thesis, in vitro insulin aggregation at acidic and neutral pH is explored using a variety of techniques

Proteomic analysis of rutin-induced secreted proteins from Aspergillus flavus.

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Medina, Martha L; Kiernan, Urban A; Francisco, Wilson A

2004-03-01

Few studies have been conducted to identify the extracellular proteins and enzymes secreted by filamentous fungi, particularly with respect to dispensable metabolic pathways. Proteomic analysis has proven to be the most powerful method for identification of proteins in complex mixtures and is suitable for the study of the alteration of protein expression under different environmental conditions. The filamentous fungus Aspergillus flavus can degrade the flavonoid rutin as the only source of carbon via an extracellular enzyme system. In this study, a proteomic analysis was used to differentiate and identify the extracellular rutin-induced and non-induced proteins secreted by A. flavus. The secreted proteins were analyzed by two-dimensional electrophoresis and MALDI-TOF mass spectrometry. While 15 rutin-induced proteins and 7 non-induced proteins were identified, more than 90 protein spots remain unidentified, indicating that these proteins are either novel proteins or proteins that have not yet been sequenced.

Emergence of slow collective oscillations in neural networks with spike-timing dependent plasticity

DEFF Research Database (Denmark)

Mikkelsen, Kaare; Imparato, Alberto; Torcini, Alessandro

2013-01-01

The collective dynamics of excitatory pulse coupled neurons with spike timing dependent plasticity (STDP) is studied. The introduction of STDP induces persistent irregular oscillations between strongly and weakly synchronized states, reminiscent of brain activity during slow-wave sleep. We explain...

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...

Hypoxic-induced stress protein expression in rat cardiac myocytes

International Nuclear Information System (INIS)

Howard, G.; Geoghegan, T.E.

1986-01-01

Mammalian stress proteins can be induced in cells and tissues exposed to a variety of conditions including hyperthermia and diminished O 2 supply. The authors have previously shown that the expression of three stress proteins (71, 85, and 95 kDa) was induced in cardiac tissue from mice exposed to hypoxic conditions. The expression of mRNAs coding for the 85 and 95 kDa proteins increase with time of exposure to hypoxia, while the mRNA coding for the 71 kDa protein is transiently induced. The authors extended these studies to investigate the expression of stress proteins in isolated rat cardiac myocytes. Freshly prepared myocytes were exposed to control, hypoxic, anoxic, or heat-shock environments for up to 16 h. The proteins were then labeled for 6 hours with [ 35 S]methionine. Analysis of the solubilized proteins by SDS-PAGE and autoradiography showed that there was a 6-fold increase in synthesis of the 85 kDa protein upon exposure to hypoxia but not heat-shock conditions. The 71 kDa protein was present at high levels in both control and treated myocyte protein preparations, and presumably had been induced during the isolation procedure. Total RNA isolated from intact rat heart and isolated myocytes was compared by cell-free translation analysis and showed induction of RNAs coding for several stress proteins in the myocyte preparation. The induced proteins at 85 and 95 kDa have molecular weights similar to reported cell stress and/or glucose-regulated proteins

Layer-specific high-frequency spiking in the prefrontal cortex of awake rats

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Zimbo Saroeni Raymond Maria Boudewijns

2013-06-01

Full Text Available Cortical pyramidal neurons show irregular in vivo action potential (AP spiking with high frequency bursts occurring on sparse background activity. Somatic APs can backpropagate from soma into basal and apical dendrites and locally generate dendritic calcium spikes. The critical AP frequency for generation of such dendritic calcium spikes can be very different depending on cell-type or brain area involved. Previously, it was shown in vitro that calcium electrogenesis can also be induced in L(ayer 5 pyramidal neurons of prefrontal cortex (PFC. It remains an open question whether somatic burst spiking and resulting dendritic calcium electrogenesis also occur in morphologically more compact L2/3 pyramidal neurons. Furthermore, it is not known whether critical frequencies that trigger dendritic calcium electrogenesis occur in PFC under awake conditions in vivo. Here, we addressed these issues and found that pyramidal neurons in both PFC L2/3 and L5 in awake rats spike APs in short bursts, but with different probabilities. The critical frequency for calcium electrogenesis in vitro was layer-specific and lower in L5 neurons compared to L2/3. Taking the in vitro critical frequency as predictive measure for dendritic electrogenesis during in vivo spontaneous activity, supracritical bursts in vivo were observed in a larger fraction of L5 neurons compared to L2/3 neurons but with similar incidence within these subpopulations. Together, these results show that in PFC of awake rats, AP spiking occurs at frequencies that are relevant for dendritic calcium electrogenesis and suggest that in awake rat PFC, dendritic calcium electrogenesis may be involved in neuronal computation.

Nonlinear Magnus-induced dynamics and Shapiro spikes for ac and dc driven skyrmions on periodic quasi-one-dimensional substrates

Science.gov (United States)

Reichhardt, Charles; Reichhardt, Cynthia J. Olson

We numerically examine skyrmions interacting with a periodic quasi-one-dimensional substrate. When we drive the skyrmions perpendicular to the substrate periodicity direction, a rich variety of nonlinear Magnus-induced effects arise, in contrast to an overdamped system that shows only a linear velocity-force curve for this geometry. The skyrmion velocity-force curve is strongly nonlinear and we observe a Magnus-induced speed-up effect when the pinning causes the Magnus velocity response to align with the dissipative response. At higher applied drives these components decouple, resulting in strong negative differential conductivity. For skyrmions under combined ac and dc driving, we find a new class of phase locking phenomena in which the velocity-force curves contain a series of what we call Shapiro spikes, distinct from the Shapiro steps observed in overdamped systems. There are also regimes in which the skyrmion moves in the direction opposite to the applied dc drive to give negative mobility.

Learning Universal Computations with Spikes

Science.gov (United States)

Thalmeier, Dominik; Uhlmann, Marvin; Kappen, Hilbert J.; Memmesheimer, Raoul-Martin

2016-01-01

Providing the neurobiological basis of information processing in higher animals, spiking neural networks must be able to learn a variety of complicated computations, including the generation of appropriate, possibly delayed reactions to inputs and the self-sustained generation of complex activity patterns, e.g. for locomotion. Many such computations require previous building of intrinsic world models. Here we show how spiking neural networks may solve these different tasks. Firstly, we derive constraints under which classes of spiking neural networks lend themselves to substrates of powerful general purpose computing. The networks contain dendritic or synaptic nonlinearities and have a constrained connectivity. We then combine such networks with learning rules for outputs or recurrent connections. We show that this allows to learn even difficult benchmark tasks such as the self-sustained generation of desired low-dimensional chaotic dynamics or memory-dependent computations. Furthermore, we show how spiking networks can build models of external world systems and use the acquired knowledge to control them. PMID:27309381

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

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.

Spikes and matter inhomogeneities in massless scalar field models

International Nuclear Information System (INIS)

Coley, A A; Lim, W C

2016-01-01

We shall discuss the general relativistic generation of spikes in a massless scalar field or stiff perfect fluid model. We first investigate orthogonally transitive (OT) G 2 stiff fluid spike models both heuristically and numerically, and give a new exact OT G 2 stiff fluid spike solution. We then present a new two-parameter family of non-OT G 2 stiff fluid spike solutions, obtained by the generalization of non-OT G 2 vacuum spike solutions to the stiff fluid case by applying Geroch’s transformation on a Jacobs seed. The dynamics of these new stiff fluid spike solutions is qualitatively different from that of the vacuum spike solutions in that the matter (stiff fluid) feels the spike directly and the stiff fluid spike solution can end up with a permanent spike. We then derive the evolution equations of non-OT G 2 stiff fluid models, including a second perfect fluid, in full generality, and briefly discuss some of their qualitative properties and their potential numerical analysis. Finally, we discuss how a fluid, and especially a stiff fluid or massless scalar field, affects the physics of the generation of spikes. (paper)

Propagation of spiking regularity and double coherence resonance in feedforward networks.

Science.gov (United States)

Men, Cong; Wang, Jiang; Qin, Ying-Mei; Deng, Bin; Tsang, Kai-Ming; Chan, Wai-Lok

2012-03-01

We investigate the propagation of spiking regularity in noisy feedforward networks (FFNs) based on FitzHugh-Nagumo neuron model systematically. It is found that noise could modulate the transmission of firing rate and spiking regularity. Noise-induced synchronization and synfire-enhanced coherence resonance are also observed when signals propagate in noisy multilayer networks. It is interesting that double coherence resonance (DCR) with the combination of synaptic input correlation and noise intensity is finally attained after the processing layer by layer in FFNs. Furthermore, inhibitory connections also play essential roles in shaping DCR phenomena. Several properties of the neuronal network such as noise intensity, correlation of synaptic inputs, and inhibitory connections can serve as control parameters in modulating both rate coding and the order of temporal coding.

Spiking neural P systems with multiple channels.

Science.gov (United States)

Peng, Hong; Yang, Jinyu; Wang, Jun; Wang, Tao; Sun, Zhang; Song, Xiaoxiao; Luo, Xiaohui; Huang, Xiangnian

2017-11-01

Spiking neural P systems (SNP systems, in short) are a class of distributed parallel computing systems inspired from the neurophysiological behavior of biological spiking neurons. In this paper, we investigate a new variant of SNP systems in which each neuron has one or more synaptic channels, called spiking neural P systems with multiple channels (SNP-MC systems, in short). The spiking rules with channel label are introduced to handle the firing mechanism of neurons, where the channel labels indicate synaptic channels of transmitting the generated spikes. The computation power of SNP-MC systems is investigated. Specifically, we prove that SNP-MC systems are Turing universal as both number generating and number accepting devices. Copyright © 2017 Elsevier Ltd. All rights reserved.

Transcriptome analysis of trichothecene-induced gene expression in barley.

Science.gov (United States)

Boddu, Jayanand; Cho, Seungho; Muehlbauer, Gary J

2007-11-01

Fusarium head blight, caused primarily by Fusarium graminearum, is a major disease problem on barley (Hordeum vulgare L.). Trichothecene mycotoxins produced by the fungus during infection increase the aggressiveness of the fungus and promote infection in wheat (Triticum aestivum L.). Loss-of-function mutations in the TRI5 gene in F. graminearum result in the inability to synthesize trichothecenes and in reduced virulence on wheat. We examined the impact of pathogen-derived trichothecenes on virulence and the transcriptional differences in barley spikes infected with a trichothecene-producing wild-type strain and a loss-of-function tri5 trichothecene nonproducing mutant. Disease severity, fungal biomass, and floret necrosis and bleaching were reduced in spikes inoculated with the tri5 mutant strain compared with the wild-type strain, indicating that the inability to synthesize trichothecenes results in reduced virulence in barley. We detected 63 transcripts that were induced during trichothecene accumulation, including genes encoding putative trichothecene detoxification and transport proteins, ubiquitination-related proteins, programmed cell death-related proteins, transcription factors, and cytochrome P450s. We also detected 414 gene transcripts that were designated as basal defense response genes largely independent of trichothecene accumulation. Our results show that barley exhibits a specific response to trichothecene accumulation that can be separated from the basal defense response. We propose that barley responds to trichothecene accumulation by inducing at least two general responses. One response is the induction of genes encoding trichothecene detoxification and transport activities that may reduce the impact of trichothecenes. The other response is to induce genes encoding proteins associated with ubiquitination and cell death which may promote successful establishment of the disease.

Geomagnetic spikes on the core-mantle boundary

Science.gov (United States)

Davies, C. J.; Constable, C.

2017-12-01

Extreme variations of Earth's magnetic field occurred in the Levantine region around 1000 BC, where the field intensity rose and fell by a factor of 2-3 over a short time and confined spatial region. There is presently no coherent link between this intensity spike and the generating processes in Earth's liquid core. Here we test the attribution of a surface spike to a flux patch visible on the core-mantle boundary (CMB), calculating geometric and energetic bounds on resulting surface geomagnetic features. We show that the Levantine intensity high must span at least 60 degrees in longitude. Models providing the best trade-off between matching surface spike intensity, minimizing L1 and L2 misfit to the available data and satisfying core energy constraints produce CMB spikes 8-22 degrees wide with peak values of O(100) mT. We propose that the Levantine spike grew in place before migrating northward and westward, contributing to the growth of the axial dipole field seen in Holocene field models. Estimates of Ohmic dissipation suggest that diffusive processes, which are often neglected, likely govern the ultimate decay of geomagnetic spikes. Using these results, we search for the presence of spike-like features in geodynamo simulations.

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.

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.

Stochastic variational learning in recurrent spiking networks.

Science.gov (United States)

Jimenez Rezende, Danilo; Gerstner, Wulfram

2014-01-01

The ability to learn and perform statistical inference with biologically plausible recurrent networks of spiking neurons is an important step toward 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 both stationary 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.

Distribution, transition and thermodynamic stability of protein conformations in the denaturant-induced unfolding of proteins.

Science.gov (United States)

Bian, Liujiao; Ji, Xu

2014-01-01

Extensive and intensive studies on the unfolding of proteins require appropriate theoretical model and parameter to clearly illustrate the feature and characteristic of the unfolding system. Over the past several decades, four approaches have been proposed to describe the interaction between proteins and denaturants, but some ambiguity and deviations usually occur in the explanation of the experimental data. In this work, a theoretical model was presented to show the dependency of the residual activity ratio of the proteins on the molar denaturant concentration. Through the characteristic unfolding parameters ki and Δmi in this model, the distribution, transition and thermodynamic stability of protein conformations during the unfolding process can be quantitatively described. This model was tested with the two-state unfolding of bovine heart cytochrome c and the three-state unfolding of hen egg white lysozyme induced by both guanidine hydrochloride and urea, the four-state unfolding of bovine carbonic anhydrase b induced by guanidine hydrochloride and the unfolding of some other proteins induced by denaturants. The results illustrated that this model could be used accurately to reveal the distribution and transition of protein conformations in the presence of different concentrations of denaturants and to evaluate the unfolding tendency and thermodynamic stability of different conformations. In most denaturant-induced unfolding of proteins, the unfolding became increasingly hard in next transition step and the proteins became more unstable as they attained next successive stable conformation. This work presents a useful method for people to study the unfolding of proteins and may be used to describe the unfolding and refolding of other biopolymers induced by denaturants, inducers, etc.

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.

Catching the PEG-induced attractive interaction between proteins.

Science.gov (United States)

Vivarès, D; Belloni, L; Tardieu, A; Bonneté, F

2002-09-01

We present the experimental and theoretical background of a method to characterize the protein-protein attractive potential induced by one of the mostly used crystallizing agents in the protein-field, the poly(ethylene glycol) (PEG). This attractive interaction is commonly called, in colloid physics, the depletion interaction. Small-Angle X-ray Scattering experiments and numerical treatments based on liquid-state theories were performed on urate oxidase-PEG mixtures with two different PEGs (3350 Da and 8000 Da). A "two-component" approach was used in which the polymer-polymer, the protein-polymer and the protein-protein pair potentials were determined. The resulting effective protein-protein potential was characterized. This potential is the sum of the free-polymer protein-protein potential and of the PEG-induced depletion potential. The depletion potential was found to be hardly dependent upon the protein concentration but strongly function of the polymer size and concentration. Our results were also compared with two models, which give an analytic expression for the depletion potential.

Resonance spiking by periodic loss in the double-sided liquid cooling disk oscillator

Science.gov (United States)

Nie, Rongzhi; She, Jiangbo; Li, Dongdong; Li, Fuli; Peng, Bo

2017-03-01

A double-sided liquid cooling Nd:YAG disk oscillator working at a pump repetition rate of 20 Hz is demonstrated. The output energy of 376 mJ is realized, corresponding to the optical-optical efficiency of 12.8% and the slope efficiency of 14%. The pump pulse width is 300 µs and the laser pulse width is 260 µs. Instead of being a damped signal, the output of laser comprises undamped spikes. A periodic intra-cavity loss was found by numerical analysis, which has a frequency component near the eigen frequency of the relaxation oscillation. Resonance effect will induce amplified spikes even though the loss fluctuates in a small range. The Shark-Hartmann sensor was used to investigate the wavefront aberration induced by turbulent flow and temperature gradient. According to the wavefront and fluid mechanics analysis, it is considered that the periodic intra-cavity loss can be attributed to turbulent flow and temperature gradient.

UV-induced DNA-binding proteins in human cells

International Nuclear Information System (INIS)

Glazer, P.M.; Greggio, N.A.; Metherall, J.E.; Summers, W.C.

1989-01-01

To investigate the response of human cells to DNA-damaging agents such as UV irradiation, the authors examined nuclear protein extracts of UV-irradiated HeLa cells for the presence of DNA-binding proteins. Electrophoretically separated proteins were transferred to a nitrocellulose filter that was subsequently immersed in a binding solution containing radioactively labeled DNA probes. Several DNA-binding proteins were induced in HeLa cells after UV irradiation. These included proteins that bind predominantly double-stranded DNA and proteins that bind both double-stranded and single-stranded DNA. The binding proteins were induced in a dose-dependent manner by UV light. Following a dose of 12 J/m 2 , the binding proteins in the nuclear extracts increased over time to a peak in the range of 18 hr after irradiation. Experiments with metabolic inhibitors (cycloheximide and actinomycin D) revealed that de novo synthesis of these proteins is not required for induction of the binding activities, suggesting that the induction is mediated by protein modification

The local field potential reflects surplus spike synchrony

DEFF Research Database (Denmark)

Denker, Michael; Roux, Sébastien; Lindén, Henrik

2011-01-01

While oscillations of the local field potential (LFP) are commonly attributed to the synchronization of neuronal firing rate on the same time scale, their relationship to coincident spiking in the millisecond range is unknown. Here, we present experimental evidence to reconcile the notions...... of synchrony at the level of spiking and at the mesoscopic scale. We demonstrate that only in time intervals of significant spike synchrony that cannot be explained on the basis of firing rates, coincident spikes are better phase locked to the LFP than predicted by the locking of the individual spikes....... This effect is enhanced in periods of large LFP amplitudes. A quantitative model explains the LFP dynamics by the orchestrated spiking activity in neuronal groups that contribute the observed surplus synchrony. From the correlation analysis, we infer that neurons participate in different constellations...

Validation of double-spike electrograms as markers of conduction delay or block in atrial flutter.

Science.gov (United States)

Cosio, F G; Arribas, F; Barbero, J M; Kallmeyer, C; Goicolea, A

1988-04-01

Recent mapping studies of atrial flutter have shown that fragmented electrograms can be found in most cases from the posterior, posteroseptal and posterolateral walls of the right atrium. The fragmentation pattern most often consists of a double spike. To further assess double-spike electrograms as a possible marker of conduction delay, bipolar electrograms were continuously recorded during atrial overdrive pacing of common flutter from the right atrium (7 patients) and from the proximal coronary sinus (5). Baseline double-spike separation of 50 to 130 ms was unchanged in 1 patient and slightly increased (5 to 25 ms) in 4 by coronary sinus pacing. The electrogram sequence was unchanged and the surface morphology was similar to that of basal flutter. Right atrial pacing decreased double-spike separation by 25 to 85 ms from basal values of 45 to 175 ms (23 to 83%), suggesting fusion in the area of fragmented electrograms. These findings suggest that double-spike electrograms represent activation on both sides of a conduction delay zone. The changes induced in these electrograms by pacing from the anterior right atrium and the coronary sinus are consistent with flutter circuits rotating counterclockwise (frontal plane) in the posterior right atrial wall in common atrial flutter.

Supervised Learning Based on Temporal Coding in Spiking Neural Networks.

Science.gov (United States)

Mostafa, Hesham

2017-08-01

Gradient descent training techniques are remarkably successful in training analog-valued artificial neural networks (ANNs). Such training techniques, however, do not transfer easily to spiking networks due to the spike generation hard nonlinearity and the discrete nature of spike communication. We show that in a feedforward spiking network that uses a temporal coding scheme where information is encoded in spike times instead of spike rates, the network input-output relation is differentiable almost everywhere. Moreover, this relation is piecewise linear after a transformation of variables. Methods for training ANNs thus carry directly to the training of such spiking networks as we show when training on the permutation invariant MNIST task. In contrast to rate-based spiking networks that are often used to approximate the behavior of ANNs, the networks we present spike much more sparsely and their behavior cannot be directly approximated by conventional ANNs. Our results highlight a new approach for controlling the behavior of spiking networks with realistic temporal dynamics, opening up the potential for using these networks to process spike patterns with complex temporal information.

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

Rapamycin-induced oligomer formation system of FRB-FKBP fusion proteins.

Science.gov (United States)

Inobe, Tomonao; Nukina, Nobuyuki

2016-07-01

Most proteins form larger protein complexes and perform multiple functions in the cell. Thus, artificial regulation of protein complex formation controls the cellular functions that involve protein complexes. Although several artificial dimerization systems have already been used for numerous applications in biomedical research, cellular protein complexes form not only simple dimers but also larger oligomers. In this study, we showed that fusion proteins comprising the induced heterodimer formation proteins FRB and FKBP formed various oligomers upon addition of rapamycin. By adjusting the configuration of fusion proteins, we succeeded in generating an inducible tetramer formation system. Proteins of interest also formed tetramers by fusing to the inducible tetramer formation system, which exhibits its utility in a broad range of biological applications. Copyright © 2015 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

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.

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.

Surfing a spike wave down the ventral stream.

Science.gov (United States)

VanRullen, Rufin; Thorpe, Simon J

2002-10-01

Numerous theories of neural processing, often motivated by experimental observations, have explored the computational properties of neural codes based on the absolute or relative timing of spikes in spike trains. Spiking neuron models and theories however, as well as their experimental counterparts, have generally been limited to the simulation or observation of isolated neurons, isolated spike trains, or reduced neural populations. Such theories would therefore seem inappropriate to capture the properties of a neural code relying on temporal spike patterns distributed across large neuronal populations. Here we report a range of computer simulations and theoretical considerations that were designed to explore the possibilities of one such code and its relevance for visual processing. In a unified framework where the relation between stimulus saliency and spike relative timing plays the central role, we describe how the ventral stream of the visual system could process natural input scenes and extract meaningful information, both rapidly and reliably. The first wave of spikes generated in the retina in response to a visual stimulation carries information explicitly in its spatio-temporal structure: the most salient information is represented by the first spikes over the population. This spike wave, propagating through a hierarchy of visual areas, is regenerated at each processing stage, where its temporal structure can be modified by (i). the selectivity of the cortical neurons, (ii). lateral interactions and (iii). top-down attentional influences from higher order cortical areas. The resulting model could account for the remarkable efficiency and rapidity of processing observed in the primate visual system.

Phorbol ester tumor promoter induced the synthesis of two major cytoplasmic proteins: identity with two proteins induced under heat-shocked and glucose-starved conditions

International Nuclear Information System (INIS)

Zhang, H.; Chen, K.Y.; Liu, A.Y.C.

1987-01-01

The regulation of specific protein synthesis by the phorbol ester tumor promoter, 12-O-tetradecanoyl-phorbol-13-acetate (TPA), was evaluated using the L-8 and C-2 myoblast and the 3T3-L1 fibroblast cell cultures. TPA increased, by 2-4 fold, the synthesis rates of two cytoplasmic proteins with apparent molecular weights of 89,000 and 74,000 as determined by SDS-polyacrylamide gel electrophoresis and autoradiography. The concentration of TPA and the time of incubation needed to elicit this induction was determined to be 10 μg/ml and 20 hrs, respectively. Increasing the concentration of TPA to 100, 200, and 500 ng/ml did not result in a greater magnitude of induction. The possibility that these two TPA-induced proteins may be identical to proteins with similar molecular weights induced under heat-shocked or glucose-starved conditions was evaluated by 1-D and 2-D gel electrophoresis and autoradiography. Results provided evidence that the TPA-induced 89,000- and 74,000-dalton proteins were identical to hsp 89 and hsp 74, 2 out of a set of 8-9 proteins induced under heat shocked conditions. Furthermore, they are identical to two of the set of glucose-regulated proteins induced under a glucose-starved condition

Role of LAMP1 Binding and pH Sensing by the Spike Complex of Lassa Virus.

Science.gov (United States)

Cohen-Dvashi, Hadas; Israeli, Hadar; Shani, Orly; Katz, Aliza; Diskin, Ron

2016-11-15

To effectively infect cells, Lassa virus needs to switch in an endosomal compartment from its primary receptor, α-dystroglycan, to a protein termed LAMP1. A unique histidine triad on the surface of the receptor-binding domain from the glycoprotein spike complex of Lassa virus is important for LAMP1 binding. Here we investigate mutated spikes that have an impaired ability to interact with LAMP1 and show that although LAMP1 is important for efficient infectivity, it is not required for spike-mediated membrane fusion per se Our studies reveal important regulatory roles for histidines from the triad in sensing acidic pH and preventing premature spike triggering. We further show that LAMP1 requires a positively charged His230 residue to engage with the spike complex and that LAMP1 binding promotes membrane fusion. These results elucidate the molecular role of LAMP1 binding during Lassa virus cell entry and provide new insights into how pH is sensed by the spike. Lassa virus is a devastating disease-causing agent in West Africa, with a significant yearly death toll and severe long-term complications associated with its infection in survivors. In recent years, we learned that Lassa virus needs to switch receptors in a pH-dependent manner to efficiently infect cells, but neither the molecular mechanisms that allow switching nor the actual effects of switching were known. Here we investigate the activity of the viral spike complex after abrogation of its ability to switch receptors. These studies inform us about the role of switching receptors and provide new insights into how the spike senses acidic pH. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Spike timing precision of neuronal circuits.

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Kilinc, Deniz; Demir, Alper

2018-04-17

Spike timing is believed to be a key factor in sensory information encoding and computations performed by the neurons and neuronal circuits. However, the considerable noise and variability, arising from the inherently stochastic mechanisms that exist in the neurons and the synapses, degrade spike timing precision. Computational modeling can help decipher the mechanisms utilized by the neuronal circuits in order to regulate timing precision. In this paper, we utilize semi-analytical techniques, which were adapted from previously developed methods for electronic circuits, for the stochastic characterization of neuronal circuits. These techniques, which are orders of magnitude faster than traditional Monte Carlo type simulations, can be used to directly compute the spike timing jitter variance, power spectral densities, correlation functions, and other stochastic characterizations of neuronal circuit operation. We consider three distinct neuronal circuit motifs: Feedback inhibition, synaptic integration, and synaptic coupling. First, we show that both the spike timing precision and the energy efficiency of a spiking neuron are improved with feedback inhibition. We unveil the underlying mechanism through which this is achieved. Then, we demonstrate that a neuron can improve on the timing precision of its synaptic inputs, coming from multiple sources, via synaptic integration: The phase of the output spikes of the integrator neuron has the same variance as that of the sample average of the phases of its inputs. Finally, we reveal that weak synaptic coupling among neurons, in a fully connected network, enables them to behave like a single neuron with a larger membrane area, resulting in an improvement in the timing precision through cooperation.

Causal Inference and Explaining Away in a Spiking Network

Science.gov (United States)

Moreno-Bote, Rubén; Drugowitsch, Jan

2015-01-01

While the brain uses spiking neurons for communication, theoretical research on brain computations has mostly focused on non-spiking networks. The nature of spike-based algorithms that achieve complex computations, such as object probabilistic inference, is largely unknown. Here we demonstrate that a family of high-dimensional quadratic optimization problems with non-negativity constraints can be solved exactly and efficiently by a network of spiking neurons. The network naturally imposes the non-negativity of causal contributions that is fundamental to causal inference, and uses simple operations, such as linear synapses with realistic time constants, and neural spike generation and reset non-linearities. The network infers the set of most likely causes from an observation using explaining away, which is dynamically implemented by spike-based, tuned inhibition. The algorithm performs remarkably well even when the network intrinsically generates variable spike trains, the timing of spikes is scrambled by external sources of noise, or the network is mistuned. This type of network might underlie tasks such as odor identification and classification. PMID:26621426

Degradation of protein translation machinery by amino acid starvation-induced macroautophagy

DEFF Research Database (Denmark)

Gretzmeier, Christine; Eiselein, Sven; Johnson, Gregory R.

2017-01-01

, unbiased approaches relying on quantitative mass spectrometry-based proteomics. Macroautophagy is induced by rapamycin treatment, and by amino acid and glucose starvation in differentially, metabolically labeled cells. Protein dynamics are linked to image-based models of autophagosome turnover. Depending...... on the inducing stimulus, protein as well as organelle turnover differ. Amino acid starvation-induced macroautophagy leads to selective degradation of proteins important for protein translation. Thus, protein dynamics reflect cellular conditions in the respective treatment indicating stimulus-specific pathways...

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.

Neuro-Inspired Spike-Based Motion: From Dynamic Vision Sensor to Robot Motor Open-Loop Control through Spike-VITE

Science.gov (United States)

Perez-Peña, Fernando; Morgado-Estevez, Arturo; Linares-Barranco, Alejandro; Jimenez-Fernandez, Angel; Gomez-Rodriguez, Francisco; Jimenez-Moreno, Gabriel; Lopez-Coronado, Juan

2013-01-01

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. PMID:24264330

Analysis of the noise-induced bursting-spiking transition in a pancreatic beta-cell model

DEFF Research Database (Denmark)

Aguirre, J.; Mosekilde, Erik; Sanjuan, M.A.F.

2004-01-01

potential signals, such as their periodic or chaotic nature, and their bursting or spiking behavior. We present effective computational tools to obtain as much information as possible from these signals, and we suggest that the methods could be applied to real time series. Finally, a universal dependence...

Silencing of SARS-CoV spike gene by small interfering RNA in HEK 293T cells

International Nuclear Information System (INIS)

Qin Zhaoling; Zhao Ping; Zhang Xiaolian; Yu Jianguo; Cao Mingmei; Zhao Lanjuan; Luan Jie; Qi Zhongtian

2004-01-01

Two candidate small interfering RNAs (siRNAs) corresponding to severe acute respiratory syndrome-associated coronavirus (SARS-CoV) spike gene were designed and in vitro transcribed to explore the possibility of silencing SARS-CoV S gene. The plasmid pEGFP-optS, which contains the codon-optimized SARS-CoV S gene and expresses spike-EGFP fusion protein (S-EGFP) as silencing target and expressing reporter, was transfected with siRNAs into HEK 293T cells. At various time points of posttransfection, the levels of S-EGFP expression and amounts of spike mRNA transcript were detected by fluorescence microscopy, flow cytometry, Western blot, and real-time quantitative PCR, respectively. The results showed that the cells transfected with pEGFP-optS expressed S-EGFP fusion protein at a higher level compared with those transfected with pEGFP-S, which contains wildtype SARS-CoV spike gene sequence. The green fluorescence, mean fluorescence intensity, and SARS-CoV S RNA transcripts were found significantly reduced, and the expression of SARS-CoV S glycoprotein was strongly inhibited in those cells co-transfected with either EGFP- or S-specific siRNAs. Our findings demonstrated that the S-specific siRNAs used in this study were able to specifically and effectively inhibit SARS-CoV S glycoprotein expression in cultured cells through blocking the accumulation of S mRNA, which may provide an approach for studies on the functions of SARS-CoV S gene and development of novel prophylactic or therapeutic agents for SARS-CoV

Spiking in auditory cortex following thalamic stimulation is dominated by cortical network activity

Science.gov (United States)

Krause, Bryan M.; Raz, Aeyal; Uhlrich, Daniel J.; Smith, Philip H.; Banks, Matthew I.

2014-01-01

The state of the sensory cortical network can have a profound impact on neural responses and perception. In rodent auditory cortex, sensory responses are reported to occur in the context of network events, similar to brief UP states, that produce “packets” of spikes and are associated with synchronized synaptic input (Bathellier et al., 2012; Hromadka et al., 2013; Luczak et al., 2013). However, traditional models based on data from visual and somatosensory cortex predict that ascending sensory thalamocortical (TC) pathways sequentially activate cells in layers 4 (L4), L2/3, and L5. The relationship between these two spatio-temporal activity patterns is unclear. Here, we used calcium imaging and electrophysiological recordings in murine auditory TC brain slices to investigate the laminar response pattern to stimulation of TC afferents. We show that although monosynaptically driven spiking in response to TC afferents occurs, the vast majority of spikes fired following TC stimulation occurs during brief UP states and outside the context of the L4>L2/3>L5 activation sequence. Specifically, monosynaptic subthreshold TC responses with similar latencies were observed throughout layers 2–6, presumably via synapses onto dendritic processes located in L3 and L4. However, monosynaptic spiking was rare, and occurred primarily in L4 and L5 non-pyramidal cells. By contrast, during brief, TC-induced UP states, spiking was dense and occurred primarily in pyramidal cells. These network events always involved infragranular layers, whereas involvement of supragranular layers was variable. During UP states, spike latencies were comparable between infragranular and supragranular cells. These data are consistent with a model in which activation of auditory cortex, especially supragranular layers, depends on internally generated network events that represent a non-linear amplification process, are initiated by infragranular cells and tightly regulated by feed-forward inhibitory

Automated analysis of calcium spiking profiles with CaSA software: two case studies from root-microbe symbioses.

Science.gov (United States)

Russo, Giulia; Spinella, Salvatore; Sciacca, Eva; Bonfante, Paola; Genre, Andrea

2013-12-26

Repeated oscillations in intracellular calcium (Ca2+) concentration, known as Ca2+ spiking signals, have been described in plants for a limited number of cellular responses to biotic or abiotic stimuli and most notably the common symbiotic signaling pathway (CSSP) which mediates the recognition by their plant hosts of two endosymbiotic microbes, arbuscular mycorrhizal (AM) fungi and nitrogen fixing rhizobia. The detailed analysis of the complexity and variability of the Ca2+ spiking patterns which have been revealed in recent studies requires both extensive datasets and sophisticated statistical tools. As a contribution, we have developed automated Ca2+ spiking analysis (CaSA) software that performs i) automated peak detection, ii) statistical analyses based on the detected peaks, iii) autocorrelation analysis of peak-to-peak intervals to highlight major traits in the spiking pattern.We have evaluated CaSA in two experimental studies. In the first, CaSA highlighted unpredicted differences in the spiking patterns induced in Medicago truncatula root epidermal cells by exudates of the AM fungus Gigaspora margarita as a function of the phosphate concentration in the growth medium of both host and fungus. In the second study we compared the spiking patterns triggered by either AM fungal or rhizobial symbiotic signals. CaSA revealed the existence of different patterns in signal periodicity, which are thought to contribute to the so-called Ca2+ signature. We therefore propose CaSA as a useful tool for characterizing oscillatory biological phenomena such as Ca2+ spiking.

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

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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.

Anti-correlations in the degree distribution increase stimulus detection performance in noisy spiking neural networks

NARCIS (Netherlands)

Martens, M.B. (Marijn B.); A.R. Houweling (Arthur); E. Tiesinga, P.H. (Paul H.)

2017-01-01

textabstractNeuronal circuits in the rodent barrel cortex are characterized by stable low firing rates. However, recent experiments show that short spike trains elicited by electrical stimulation in single neurons can induce behavioral responses. Hence, the underlying neural networks provide

Al cation induces aggregation of serum proteins.

Science.gov (United States)

Chanphai, P; Kreplak, L; Tajmir-Riahi, H A

2017-07-15

Al cation is known to induce protein fibrillation and causes several neurodegenerative disorders. We report the spectroscopic, thermodynamic analysis and AFM imaging for the Al cation binding process with human serum albumin (HSA), bovine serum albumin (BSA) and milk beta-lactoglobulin (b-LG) in aqueous solution at physiological pH. Hydrophobicity played a major role in Al-protein interactions with more hydrophobic b-LG forming stronger Al-protein complexes. Thermodynamic parameters ΔS, ΔH and ΔG showed Al-protein bindings occur via hydrophobic and H-bonding contacts for b-LG, while van der Waals and H-bonding interactions prevail in HSA and BSA adducts. AFM clearly indicated that aluminum cations are able to force BSA and b-LG into larger or more robust aggregates than HSA, with HSA 4±0.2 (SE, n=801) proteins per aggregate, for BSA 17±2 (SE, n=148), and for b-LG 12±3 (SE, n=151). Thioflavin T test showed no major protein fibrillation in the presence of Al cation. Al complexation induced major alterations of protein conformations with the order of perturbations b-LG>BSA>HSA. Copyright © 2017 Elsevier B.V. All rights reserved.

Joint Probability-Based Neuronal Spike Train Classification

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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.

Fitting neuron models to spike trains

Directory of Open Access Journals (Sweden)

Cyrille eRossant

2011-02-01

Full Text Available Computational modeling is increasingly used to understand the function of neural circuitsin systems neuroscience.These studies require models of individual neurons with realisticinput-output properties.Recently, it was found that spiking models can accurately predict theprecisely timed spike trains produced by cortical neurons in response tosomatically injected currents,if properly fitted. This requires fitting techniques that are efficientand flexible enough to easily test different candidate models.We present a generic solution, based on the Brian simulator(a neural network simulator in Python, which allowsthe user to define and fit arbitrary neuron models to electrophysiological recordings.It relies on vectorization and parallel computing techniques toachieve efficiency.We demonstrate its use on neural recordings in the barrel cortex andin the auditory brainstem, and confirm that simple adaptive spiking modelscan accurately predict the response of cortical neurons. Finally, we show how a complexmulticompartmental model can be reduced to a simple effective spiking model.

Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE

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Pietro Quaglio

2017-05-01

Full Text Available Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs. STPs are hypothesized to play a role in the communication of information in the computational process operated by the cerebral cortex. A variety of statistical methods for the detection of STPs have been developed and applied to electrophysiological recordings, but such methods scale poorly with the current size of available parallel spike train recordings (more than 100 neurons. In this work, we introduce a novel method capable of overcoming the computational and statistical limits of existing analysis techniques in detecting repeating STPs within massively parallel spike trains (MPST. We employ advanced data mining techniques to efficiently extract repeating sequences of spikes from the data. Then, we introduce and compare two alternative approaches to distinguish statistically significant patterns from chance sequences. The first approach uses a measure known as conceptual stability, of which we investigate a computationally cheap approximation for applications to such large data sets. The second approach is based on the evaluation of pattern statistical significance. In particular, we provide an extension to STPs of a method we recently introduced for the evaluation of statistical significance of synchronous spike patterns. The performance of the two approaches is evaluated in terms of computational load and statistical power on a variety of artificial data sets that replicate specific features of experimental data. Both methods provide an effective and robust procedure for detection of STPs in MPST data. The method based on significance evaluation shows the best overall performance, although at a higher computational cost. We name the novel procedure the spatio-temporal Spike PAttern Detection and Evaluation (SPADE analysis.

Constructing Precisely Computing Networks with Biophysical Spiking Neurons.

Science.gov (United States)

Schwemmer, Michael A; Fairhall, Adrienne L; Denéve, Sophie; Shea-Brown, Eric T

2015-07-15

While spike timing has been shown to carry detailed stimulus information at the sensory periphery, its possible role in network computation is less clear. Most models of computation by neural networks are based on population firing rates. In equivalent spiking implementations, firing is assumed to be random such that averaging across populations of neurons recovers the rate-based approach. Recently, however, Denéve and colleagues have suggested that the spiking behavior of neurons may be fundamental to how neuronal networks compute, with precise spike timing determined by each neuron's contribution to producing the desired output (Boerlin and Denéve, 2011; Boerlin et al., 2013). By postulating that each neuron fires to reduce the error in the network's output, it was demonstrated that linear computations can be performed by networks of integrate-and-fire neurons that communicate through instantaneous synapses. This left open, however, the possibility that realistic networks, with conductance-based neurons with subthreshold nonlinearity and the slower timescales of biophysical synapses, may not fit into this framework. Here, we show how the spike-based approach can be extended to biophysically plausible networks. We then show that our network reproduces a number of key features of cortical networks including irregular and Poisson-like spike times and a tight balance between excitation and inhibition. Lastly, we discuss how the behavior of our model scales with network size or with the number of neurons "recorded" from a larger computing network. These results significantly increase the biological plausibility of the spike-based approach to network computation. We derive a network of neurons with standard spike-generating currents and synapses with realistic timescales that computes based upon the principle that the precise timing of each spike is important for the computation. We then show that our network reproduces a number of key features of cortical networks

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.

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.

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

Predictive features of persistent activity emergence in regular spiking and intrinsic bursting model neurons.

Directory of Open Access Journals (Sweden)

Kyriaki Sidiropoulou

Full Text Available Proper functioning of working memory involves the expression of stimulus-selective persistent activity in pyramidal neurons of the prefrontal cortex (PFC, which refers to neural activity that persists for seconds beyond the end of the stimulus. The mechanisms which PFC pyramidal neurons use to discriminate between preferred vs. neutral inputs at the cellular level are largely unknown. Moreover, the presence of pyramidal cell subtypes with different firing patterns, such as regular spiking and intrinsic bursting, raises the question as to what their distinct role might be in persistent firing in the PFC. Here, we use a compartmental modeling approach to search for discriminatory features in the properties of incoming stimuli to a PFC pyramidal neuron and/or its response that signal which of these stimuli will result in persistent activity emergence. Furthermore, we use our modeling approach to study cell-type specific differences in persistent activity properties, via implementing a regular spiking (RS and an intrinsic bursting (IB model neuron. We identify synaptic location within the basal dendrites as a feature of stimulus selectivity. Specifically, persistent activity-inducing stimuli consist of activated synapses that are located more distally from the soma compared to non-inducing stimuli, in both model cells. In addition, the action potential (AP latency and the first few inter-spike-intervals of the neuronal response can be used to reliably detect inducing vs. non-inducing inputs, suggesting a potential mechanism by which downstream neurons can rapidly decode the upcoming emergence of persistent activity. While the two model neurons did not differ in the coding features of persistent activity emergence, the properties of persistent activity, such as the firing pattern and the duration of temporally-restricted persistent activity were distinct. Collectively, our results pinpoint to specific features of the neuronal response to a given

Effectiveness of ketogenic diet in pentylenetetrazol-induced and kindling rats as well as its potential mechanisms.

Science.gov (United States)

Wang, Shan; Ding, Yao; Ding, Xiao-Yan; Liu, Zhi-Rong; Shen, Chun-Hong; Jin, Bo; Guo, Yi; Wang, Shuang; Ding, Mei-Ping

2016-02-12

The effects and mechanisms of ketogenic diets (KD) are unclear. In this study, we aimed to reveal electrographic and behavioral thresholds in responses to the KD in pentylenetetrazol (PTZ)-induced seizures, as well as its antiepileptogenic effects on PTZ-kindling rats. Additionally, we investigated the potential link between KD and expression levels of two cation chloride co-transporters: K(+)-Cl(-) co-transporter 2 (KCC2) and Na(+)-K(+)-Cl(-) co-transporter 1 (NKCC1). The KD group had significantly higher electrographic thresholds than the control (ND) group for the first spike-and-wave, subcontinuous spike-and-wave, high amplitude spike-and-wave, and polyspikes both in the cortex and hippocampus. Compared to the ND group, the KD group had higher behavioral thresholds for behavioral absence, first jerk, first overt myoclonia, and generalized seizures. In the PTZ-kindling model, KD not only prolonged the latency of myoclonic and clonic convulsions, but shortened clonic and generalized duration. In addition, KD rats had higher KCC2 protein expression before kindling, during myoclonic jerks, and GTCS compared with ND rats. There were no significant differences in NKCC1 protein levels between both groups following the four-week dietary intervention without PTZ exposure (before kindling). Moreover, KD inhibited the upregulation of NKCC1 expression induced by kindling in myoclonic jerks and GTCS. Therefore, our findings demonstrated that KD had antiepileptic features in elevating thresholds to most electrographic and behavioral seizure patterns in PTZ-induced rats, as well as delaying the progression and alleviating the severity of seizure in PTZ-kindling model. The antiepileptogenic effects of KD may be attributed to its regulatory properties on KCC2 and NKCC1 protein expression. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Induced mutants for cereal grain protein improvement

International Nuclear Information System (INIS)

1982-01-01

Out of 17 papers and one summary presented, six dealing with the genetic improvement of seed protein using ionizing radiations fall within the INIS subject scope. Other topics discussed were non-radiation induced mutants used for cereal grain protein improvement

Solving Constraint Satisfaction Problems with Networks of Spiking Neurons.

Science.gov (United States)

Jonke, Zeno; Habenschuss, Stefan; Maass, Wolfgang

2016-01-01

Network of neurons in the brain apply-unlike processors in our current generation of computer hardware-an event-based processing strategy, where short pulses (spikes) are emitted sparsely by neurons to signal the occurrence of an event at a particular point in time. Such spike-based computations promise to be substantially more power-efficient than traditional clocked processing schemes. However, it turns out to be surprisingly difficult to design networks of spiking neurons that can solve difficult computational problems on the level of single spikes, rather than rates of spikes. We present here a new method for designing networks of spiking neurons via an energy function. Furthermore, we show how the energy function of a network of stochastically firing neurons can be shaped in a transparent manner by composing the networks of simple stereotypical network motifs. We show that this design approach enables networks of spiking neurons to produce approximate solutions to difficult (NP-hard) constraint satisfaction problems from the domains of planning/optimization and verification/logical inference. The resulting networks employ noise as a computational resource. Nevertheless, the timing of spikes plays an essential role in 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.

Recent progress in multi-electrode spike sorting methods.

Science.gov (United States)

Lefebvre, Baptiste; Yger, Pierre; Marre, Olivier

2016-11-01

In recent years, arrays of extracellular electrodes have been developed and manufactured to record simultaneously from hundreds of electrodes packed with a high density. These recordings should allow neuroscientists to reconstruct the individual activity of the neurons spiking in the vicinity of these electrodes, with the help of signal processing algorithms. Algorithms need to solve a source separation problem, also known as spike sorting. However, these new devices challenge the classical way to do spike sorting. Here we review different methods that have been developed to sort spikes from these large-scale recordings. We describe the common properties of these algorithms, as well as their main differences. Finally, we outline the issues that remain to be solved by future spike sorting algorithms. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Low dose radiation induced protein and its experimental and ophthalmic clinical research

International Nuclear Information System (INIS)

Shen Wei; Su Liaoyuan; Liu Fenju; Ding Jie; Li Longbiao; Pan Chengsi

2001-01-01

The protective effects of low dose radiation (LDR) induced protein on cellular impairments caused by some harmful chemical and physical factors were studied. Male Kunming mice were irradiated with LDR, then the spleen cells of the mice were broken with ultrasonic energy and then ultracentrifugalized. The supernatant solution contained with LDR induced protein. The newly emerging protein was detected by gel filtration and its molecular weight was determined by gel electrophoresis. The content of newly emerging protein (LDR induced protein) was determined by Lowry's method. The method of isotope incorporation was used to observe the biological activity and its influence factors, the protective effects of LDR induced protein on the cells impaired by irradiating with ultraviolet (UV), high doses of 60 Co γ-rays and exposed to heat respectively, and the stimulative effects of LDR induced protein on human peripheral blood lymphocytes. Newly emerging protein has been observed in the experiment. The molecular weight of the protein is in the region 76.9 KD+- - 110.0 KD+-, the yield of the protein was 613.33 +- 213.42 μg per 3 x 10 7 spleen cells. DPM values (isotope were incorporated) of normal and injured mice spleen cells increased significantly after stimulating with the solution contained LDR induced protein. It is concluded that LDR induced protein could be obtained from mice spleen cells exposed to 5 - 15 cGy radiation for 2 - 16 h. The protein had biological activity and was able to stimulate the transformation of the spleen cells in vitro. It had obvious protective effects on some impaired cells caused by high dose radiation, UV radiation, heat and so on. It also had stimulative effects on the transformation of peripheral blood T and B lymphocytes of healthy individual and patients with eye diseases. It indicates that LDR induced protein increased immune function of human

Induced variability for protein content in bread wheat

International Nuclear Information System (INIS)

Singhal, N.C.; Jain, H.K.; Austin, A.

1978-01-01

The negative correlation observed between seed weight and percentage of protein in the seeds of bread wheat is a function of the fact that increase in seed size is commonly associated with a disproportionately large deposition of starch relative to the protein. The present study, as well as our earlier analysis, shows that exceptional genotypes of bread wheat do exist in which increase in seed weight is associated with a relatively larger synthesis of protein. In the course of the present investigation on radiation-induced variability, genotypes showing more efficient synthesis of storage proteins in their seeds have been identified in the M 2 and M 3 generations. The induced variability, thus, makes it possible to break the negative correlation between seed weight and percentage of protein in the seed. Based on these findings, it has been suggested that in a protein improvement programme on bread wheat it should be useful to select in the segregating generation plants showing increase in seed size, some of which can be expected to be relatively more efficient in protein synthesis and give higher protein yields. (author)

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...

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/.

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.

Visually Evoked Spiking Evolves While Spontaneous Ongoing Dynamics Persist

DEFF Research Database (Denmark)

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

2016-01-01

attractor. Its existence guarantees that evoked spiking return to the spontaneous state. However, the spontaneous ongoing spiking state and the visual evoked spiking states are qualitatively different and are separated by a threshold (separatrix). The functional advantage of this organization...

Multichannel interictal spike activity detection using time-frequency entropy measure.

Science.gov (United States)

Thanaraj, Palani; Parvathavarthini, B

2017-06-01

Localization of interictal spikes is an important clinical step in the pre-surgical assessment of pharmacoresistant epileptic patients. The manual selection of interictal spike periods is cumbersome and involves a considerable amount of analysis workload for the physician. The primary focus of this paper is to automate the detection of interictal spikes for clinical applications in epilepsy localization. The epilepsy localization procedure involves detection of spikes in a multichannel EEG epoch. Therefore, a multichannel Time-Frequency (T-F) entropy measure is proposed to extract features related to the interictal spike activity. Least squares support vector machine is used to train the proposed feature to classify the EEG epochs as either normal or interictal spike period. The proposed T-F entropy measure, when validated with epilepsy dataset of 15 patients, shows an interictal spike classification accuracy of 91.20%, sensitivity of 100% and specificity of 84.23%. Moreover, the area under the curve of Receiver Operating Characteristics plot of 0.9339 shows the superior classification performance of the proposed T-F entropy measure. The results of this paper show a good spike detection accuracy without any prior information about the spike morphology.

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.

Determination and application of immunodominant regions of SARS coronavirus spike and nucleocapsid proteins recognized by sera from different animal species.

Science.gov (United States)

Yu, Meng; Stevens, Vicky; Berry, Jody D; Crameri, Gary; McEachern, Jennifer; Tu, Changchun; Shi, Zhengli; Liang, Guodong; Weingartl, Hana; Cardosa, Jane; Eaton, Bryan T; Wang, Lin-Fa

2008-02-29

Knowledge of immunodominant regions in major viral antigens is important for rational design of effective vaccines and diagnostic tests. Although there have been many reports of such work done for SARS-CoV, these were mainly focused on the immune responses of humans and mice. In this study, we aim to search for and compare immunodominant regions of the spike (S) and nucleocapsid (N) proteins which are recognized by sera from different animal species, including mouse, rat, rabbit, civet, pig and horse. Twelve overlapping recombinant protein fragments were produced in Escherichia coli, six each for the S and N proteins, which covered the entire coding region of the two proteins. Using a membrane-strip based Western blot approach, the reactivity of each antigen fragment against a panel of animal sera was determined. Immunodominant regions containing linear epitopes, which reacted with sera from all the species tested, were identified for both proteins. The S3 fragment (aa 402-622) and the N4 fragment (aa 220-336) were the most immunodominant among the six S and N fragments, respectively. Antibodies raised against the S3 fragment were able to block the binding of a panel of S-specific monoclonal antibodies (mAb) to SARS-CoV in ELISA, further demonstrating the immunodominance of this region. Based on these findings, one-step competition ELISAs were established which were able to detect SARS-CoV antibodies from human and at least seven different animal species. Considering that a large number of animal species are known to be susceptible to SARS-CoV, these assays will be a useful tool to trace the origin and transmission of SARS-CoV and to minimise the risk of animal-to-human transmission.

Spike Code Flow in Cultured Neuronal Networks.

Science.gov (United States)

Tamura, Shinichi; Nishitani, Yoshi; Hosokawa, Chie; Miyoshi, Tomomitsu; Sawai, Hajime; Kamimura, Takuya; Yagi, Yasushi; Mizuno-Matsumoto, Yuko; Chen, Yen-Wei

2016-01-01

We observed spike trains produced by one-shot electrical stimulation with 8 × 8 multielectrodes in cultured neuronal networks. Each electrode accepted spikes from several neurons. We extracted the short codes from spike trains and obtained a code spectrum with a nominal time accuracy of 1%. We then constructed code flow maps as movies of the electrode array to observe the code flow of "1101" and "1011," which are typical pseudorandom sequence such as that we often encountered in a literature and our experiments. They seemed to flow from one electrode to the neighboring one and maintained their shape to some extent. To quantify the flow, we calculated the "maximum cross-correlations" among neighboring electrodes, to find the direction of maximum flow of the codes with lengths less than 8. Normalized maximum cross-correlations were almost constant irrespective of code. Furthermore, if the spike trains were shuffled in interval orders or in electrodes, they became significantly small. Thus, the analysis suggested that local codes of approximately constant shape propagated and conveyed information across the network. Hence, the codes can serve as visible and trackable marks of propagating spike waves as well as evaluating information flow in the neuronal network.

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...

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.

Host cell entry of Middle East respiratory syndrome coronavirus after two-step, furin-mediated activation of the spike protein

Science.gov (United States)

Millet, Jean Kaoru; Whittaker, Gary R.

2014-01-01

Middle East respiratory syndrome coronavirus (MERS-CoV) is a newly identified betacoronavirus causing high morbidity and mortality in humans. The coronavirus spike (S) protein is the main determinant of viral entry, and although it was previously shown that MERS-CoV S can be activated by various proteases, the details of the mechanisms of proteolytic activation of fusion are still incompletely characterized. Here, we have uncovered distinctive characteristics of MERS-CoV S. We identify, by bioinformatics and peptide cleavage assays, two cleavage sites for furin, a ubiquitously expressed protease, which are located at the S1/S2 interface and at the S2′ position of the S protein. We show that although the S1/S2 site is proteolytically processed by furin during protein biosynthesis, the S2′ site is cleaved upon viral entry. MERS-CoV pseudovirion infection was shown to be enhanced by elevated levels of furin expression, and entry could be decreased by furin siRNA silencing. Enhanced furin activity appeared to partially override the low pH-dependent nature of MERS-CoV entry. Inhibition of furin activity was shown to decrease MERS-CoV S-mediated entry, as well as infection by the virus. Overall, we show that MERS-CoV has evolved an unusual two-step furin activation for fusion, suggestive of a role during the process of emergence into the human population. The ability of MERS-CoV to use furin in this manner, along with other proteases, may explain the polytropic nature of the virus. PMID:25288733

Introduction to spiking neural networks: Information processing, learning and applications.

Science.gov (United States)

Ponulak, Filip; Kasinski, Andrzej

2011-01-01

The concept that neural information is encoded in the firing rate of neurons has been the dominant paradigm in neurobiology for many years. This paradigm has also been adopted by the theory of artificial neural networks. Recent physiological experiments demonstrate, however, that in many parts of the nervous system, neural code is founded on the timing of individual action potentials. This finding has given rise to the emergence of a new class of neural models, called spiking neural networks. In this paper we summarize basic properties of spiking neurons and spiking networks. Our focus is, specifically, on models of spike-based information coding, synaptic plasticity and learning. We also survey real-life applications of spiking models. The paper is meant to be an introduction to spiking neural networks for scientists from various disciplines interested in spike-based neural processing.

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.

Prospective Identification of Oligoclonal/Abnormal Band of the Same Immunoglobulin Type as the Malignant Clone by Differential Location of M-Spike and Oligoclonal Band.

Science.gov (United States)

Vyas, Shikhar G; Singh, Gurmukh

2017-10-01

Serum and urine protein electrophoreses and immunofixation electrophoreses are the gold standards in diagnosing monoclonal gammopathy. Identification of oligoclonal bands in post-treatment patients has emerged as an important issue and recording the location of the malignant monoclonal peak may facilitate prospective identification of a new "monoclonal" spike as being distinct from the malignant peak. We recorded the locations of monoclonal spikes in descriptive terms, such as being in the cathodal region, mid-gamma region, anodal region, and beta region. The location of monoclonal or restricted heterogeneity bands in subsequent protein electrophoreses was compared to the location of the original malignant spike. In a patient with plasma cell myeloma, the original monoclonal IgG kappa band was located at the anodal end of gamma region. Post-treatment, an IgG kappa band was noted in mid-gamma region and the primary malignant clone was not detectable by serum protein immunofixation electrophoresis (SIFE) in post-treatment sample. Even though the κ/λ ratio remained abnormal, we were able to recognize stringent complete response by noting the different location of the new IgG kappa band as a benign regenerative process. Recording the location of the malignant monoclonal spike facilitates the identification of post-treatment oligoclonal bands, prospectively. Recognizing the regenerative, benign, bands in post-transplant patients facilitates the determination of stringent complete response despite an abnormal κ/λ ratio.

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.

Error-backpropagation in temporally encoded networks of spiking neurons

NARCIS (Netherlands)

S.M. Bohte (Sander); J.A. La Poutré (Han); J.N. Kok (Joost)

2000-01-01

textabstractFor a network of spiking neurons that encodes information in the timing of individual spike-times, we derive a supervised learning rule, emph{SpikeProp, akin to traditional error-backpropagation and show how to overcome the discontinuities introduced by thresholding. With this algorithm,

Mimickers of generalized spike and wave discharges.

Science.gov (United States)

Azzam, Raed; Bhatt, Amar B

2014-06-01

Overinterpretation of benign EEG variants is a common problem that can lead to the misdiagnosis of epilepsy. We review four normal patterns that mimic generalized spike and wave discharges: phantom spike-and-wave, hyperventilation hypersynchrony, hypnagogic/ hypnopompic hypersynchrony, and mitten patterns.

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.

Quinone-induced protein handling changes: Implications for major protein handling systems in quinone-mediated toxicity

International Nuclear Information System (INIS)

Xiong, Rui; Siegel, David; Ross, David

2014-01-01

Para-quinones such as 1,4-Benzoquinone (BQ) and menadione (MD) and ortho-quinones including the oxidation products of catecholamines, are derived from xenobiotics as well as endogenous molecules. The effects of quinones on major protein handling systems in cells; the 20/26S proteasome, the ER stress response, autophagy, chaperone proteins and aggresome formation, have not been investigated in a systematic manner. Both BQ and aminochrome (AC) inhibited proteasomal activity and activated the ER stress response and autophagy in rat dopaminergic N27 cells. AC also induced aggresome formation while MD had little effect on any protein handling systems in N27 cells. The effect of NQO1 on quinone induced protein handling changes and toxicity was examined using N27 cells stably transfected with NQO1 to generate an isogenic NQO1-overexpressing line. NQO1 protected against BQ–induced apoptosis but led to a potentiation of AC- and MD-induced apoptosis. Modulation of quinone-induced apoptosis in N27 and NQO1-overexpressing cells correlated only with changes in the ER stress response and not with changes in other protein handling systems. These data suggested that NQO1 modulated the ER stress response to potentiate toxicity of AC and MD, but protected against BQ toxicity. We further demonstrated that NQO1 mediated reduction to unstable hydroquinones and subsequent redox cycling was important for the activation of the ER stress response and toxicity for both AC and MD. In summary, our data demonstrate that quinone-specific changes in protein handling are evident in N27 cells and the induction of the ER stress response is associated with quinone-mediated toxicity. - Highlights: • Unstable hydroquinones contributed to quinone-induced ER stress and toxicity

Quinone-induced protein handling changes: Implications for major protein handling systems in quinone-mediated toxicity

Energy Technology Data Exchange (ETDEWEB)

Xiong, Rui; Siegel, David; Ross, David, E-mail: david.ross@ucdenver.edu

2014-10-15

Para-quinones such as 1,4-Benzoquinone (BQ) and menadione (MD) and ortho-quinones including the oxidation products of catecholamines, are derived from xenobiotics as well as endogenous molecules. The effects of quinones on major protein handling systems in cells; the 20/26S proteasome, the ER stress response, autophagy, chaperone proteins and aggresome formation, have not been investigated in a systematic manner. Both BQ and aminochrome (AC) inhibited proteasomal activity and activated the ER stress response and autophagy in rat dopaminergic N27 cells. AC also induced aggresome formation while MD had little effect on any protein handling systems in N27 cells. The effect of NQO1 on quinone induced protein handling changes and toxicity was examined using N27 cells stably transfected with NQO1 to generate an isogenic NQO1-overexpressing line. NQO1 protected against BQ–induced apoptosis but led to a potentiation of AC- and MD-induced apoptosis. Modulation of quinone-induced apoptosis in N27 and NQO1-overexpressing cells correlated only with changes in the ER stress response and not with changes in other protein handling systems. These data suggested that NQO1 modulated the ER stress response to potentiate toxicity of AC and MD, but protected against BQ toxicity. We further demonstrated that NQO1 mediated reduction to unstable hydroquinones and subsequent redox cycling was important for the activation of the ER stress response and toxicity for both AC and MD. In summary, our data demonstrate that quinone-specific changes in protein handling are evident in N27 cells and the induction of the ER stress response is associated with quinone-mediated toxicity. - Highlights: • Unstable hydroquinones contributed to quinone-induced ER stress and toxicity.

Unsupervised spike sorting based on discriminative subspace learning.

Science.gov (United States)

Keshtkaran, Mohammad Reza; Yang, Zhi

2014-01-01

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. In this paper, we present two unsupervised spike sorting algorithms based on discriminative subspace learning. The first algorithm simultaneously learns the discriminative feature subspace and performs clustering. It uses histogram of features in the most discriminative projection to detect the number of neurons. The second algorithm performs hierarchical divisive clustering that learns a discriminative 1-dimensional subspace for clustering in each level of the hierarchy until achieving almost unimodal distribution in the subspace. The algorithms are tested on synthetic and in-vivo data, and are compared against two widely used spike sorting methods. The comparative results demonstrate that our spike sorting methods can achieve substantially higher accuracy in lower dimensional feature space, and they are highly robust to noise. Moreover, they provide significantly better cluster separability in the learned subspace than in the subspace obtained by principal component analysis or wavelet transform.

Multiplexed Spike Coding and Adaptation in the Thalamus

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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.

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

A single amino acid substitution in the S1 and S2 Spike protein domains determines the neutralization escape phenotype of SARS-CoV.

Science.gov (United States)

Mitsuki, Yu-ya; Ohnishi, Kazuo; Takagi, Hirotaka; Oshima, Masamichi; Yamamoto, Takuya; Mizukoshi, Fuminori; Terahara, Kazutaka; Kobayashi, Kazuo; Yamamoto, Naoki; Yamaoka, Shoji; Tsunetsugu-Yokota, Yasuko

2008-07-01

In response to SARS-CoV infection, neutralizing antibodies are generated against the Spike (S) protein. Determination of the active regions that allow viral escape from neutralization would enable the use of these antibodies for future passive immunotherapy. We immunized mice with UV-inactivated SARS-CoV to generate three anti-S monoclonal antibodies, and established several neutralization escape mutants with S protein. We identified several amino acid substitutions, including Y442F and V601G in the S1 domain and D757N and A834V in the S2 region. In the presence of each neutralizing antibody, double mutants with substitutions in both domains exhibited a greater growth advantage than those with only one substitution. Importantly, combining two monoclonal antibodies that target different epitopes effected almost complete suppression of wild type virus replication. Thus, for effective passive immunotherapy, it is important to use neutralizing antibodies that recognize both the S1 and S2 regions.

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.

Fuel Saving on Diesel Genset using PV/Battery Spike Cutting in Remote Area Microgrid

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Dwi Atmaja Tinton

2018-01-01

Full Text Available Diesel Generator set was found to be a favorite power generator in a remote area. In this area, diesel genset usually consumes a significant amount of diesel fuel with higher fuel price than an urban area. Diesel Generator capacity conventionally prepared twice bigger or more than the existing load to prevent any load spike from designated equipment. This work implements an Energy Management System to cut the spike with the support from battery storage unit and photovoltaic module. Once the Energy Management System cut the load spike using battery/photovoltaics, Diesel Generator loads no longer need to be irrelevantly bigger than the existing load. The current experiment in the remote island at Raja Ampat archipelago indicates that the using of 80 kVA Diesel Generator can be reduced to 42 kVA Diesel Generator. This Diesel Generator replacement induces fuel consumption up to 50 %. With this designed work, a smart microgrid with PV-Battery-Diesel can be installed in a designated remote area with lower fuel consumption.

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...

Porcine circovirus-2 capsid protein induces cell death in PK15 cells

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Walia, Rupali; Dardari, Rkia, E-mail: rdardari@ucalgary.ca; Chaiyakul, Mark; Czub, Markus

2014-11-15

Studies have shown that Porcine circovirus (PCV)-2 induces apoptosis in PK15 cells. Here we report that cell death is induced in PCV2b-infected PK15 cells that express Capsid (Cap) protein and this effect is enhanced in interferon gamma (IFN-γ)-treated cells. We further show that transient PCV2a and 2b-Cap protein expression induces cell death in PK15 cells at rate similar to PCV2 infection, regardless of Cap protein localization. These data suggest that Cap protein may have the capacity to trigger different signaling pathways involved in cell death. Although further investigation is needed to gain deeper insights into the nature of the pathways involved in Cap-induced cell death, this study provides evidence that PCV2-induced cell death in kidney epithelial PK15 cells can be mapped to the Cap protein and establishes the need for future research regarding the role of Cap-induced cell death in PCV2 pathogenesis. - Highlights: • IFN-γ enhances PCV2 replication that leads to cell death in PK15 cells. • IFN-γ enhances nuclear localization of the PCV2 Capsid protein. • Transient PCV2a and 2b-Capsid protein expression induces cell death. • Cell death is not dictated by specific Capsid protein sub-localization.

DNA-protein complexes induced by chromate and other carcinogens

International Nuclear Information System (INIS)

Costa, M.

1991-01-01

DNA-protein complexes induced in intact Chinese hamster ovary cells by chromate have been isolated, analyzed, and compared with those induced by cis-platinum, ultraviolet light, and formaldehyde. Actin has been identified as one of the major proteins complexed to DNA by chromate based upon its molecular weight, isoelectric point, positive reaction with an actin polyclonal antibody, and proteolytic mapping. Chromate and cis-platinum both complex proteins of similar molecular weight and isoelectric point, positive reaction with an actin polyclonal antibody, and proteolytic mapping. Chromate and cis-platinum both complex proteins of similar molecular weight and isoelectric points, and these complexes can be disrupted by chelating agents and sulfhydryl reducing agents, suggesting that the metal itself is participating in binding rather than having a catalytic or indirect role (i.e., oxygen radicals). In contrast, formaldehyde complexed histones to the DNA, and these complexes were not disrupted by chelating or reducing agents. An antiserum raised to chromate-induced DNA-protein complexes reacted primarily with 97,000 kDa protein that did not silver stain. Slot blots, as well as Western blots, were used to detect formation of p97 DNA crosslinks. This protein was complexed to the DNA by all four agents studied

Temperature-induced transitions in disordered proteins probed by NMR spectroscopy

DEFF Research Database (Denmark)

Kjærgaard, Magnus; Poulsen, Flemming Martin; Kragelund, Birthe Brandt

2012-01-01

Intrinsically disordered proteins are abundant in nature and perform many important physiological functions. Multidimensional NMR spectroscopy has been crucial for the understanding of the conformational properties of disordered proteins and is increasingly used to probe their conformational...... ensembles. Compared to folded proteins, disordered proteins are more malleable and more easily perturbed by environmental factors. Accordingly, the experimental conditions and especially the temperature modify the structural and functional properties of disordered proteins. NMR spectroscopy allows analysis...... of temperature-induced structural changes at residue resolution using secondary chemical shift analysis, paramagnetic relaxation enhancement, and residual dipolar couplings. This chapter discusses practical aspects of NMR studies of temperature-induced structural changes in disordered proteins....

Model for Stress-induced Protein Degradation in Lemna minor1

Science.gov (United States)

Cooke, Robert J.; Roberts, Keith; Davies, David D.

1980-01-01

Transfer of Lemna minor fronds to adverse or stress conditions produces a large increase in the rate of protein degradation. Cycloheximide partially inhibits stress-induced protein degradation and also partially inhibits the protein degradation which occurs in the absence of stress. The increased protein degradation does not appear to be due to an increase in activity of soluble proteolytic enzymes. Biochemical evidence indicates that stress, perhaps acting via hormones, affects the permeability of certain membranes, particularly the tonoplast. A general model for stress-induced protein degradation is presented in which changes in membrane properties allow vacuolar proteolytic enzymes increased access to cytoplasmic proteins. PMID:16661588

Independent component analysis separates spikes of different origin in the EEG.

Science.gov (United States)

Urrestarazu, Elena; Iriarte, Jorge; Artieda, Julio; Alegre, Manuel; Valencia, Miguel; Viteri, César

2006-02-01

Independent component analysis (ICA) is a novel system that finds independent sources in recorded signals. Its usefulness in separating epileptiform activity of different origin has not been determined. The goal of this study was to demonstrate that ICA is useful for separating different spikes using samples of EEG of patients with focal epilepsy. Digital EEG samples from four patients with focal epilepsy were included. The patients had temporal (n = 2), centrotemporal (n = 1) or frontal spikes (n = 1). Twenty-six samples with two (or more) spikes from two different patients were created. The selection of the two spikes for each mixed EEG was performed randomly, trying to have all the different combinations and rejecting the mixture of two spikes from the same patient. Two different examiners studied the EEGs using ICA with JADE paradigm in Matlab platform, trying to separate and to identify the spikes. They agreed in the correct separation of the spikes in 24 of the 26 samples, classifying the spikes as frontal, temporal or centrotemporal, left or right sided. The demonstration of the possibility of detecting different artificially mixed spikes confirms that ICA may be useful in separating spikes or other elements in real EEGs.

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

excitatory synaptic input. Subsequent inhibition of action potential propagation and neurotransmission by blocking voltage-gated Na+-channels eliminated the increases in CMRO2 due to PF stimulation and increased PC spiking, but left a large fraction of CMRO2, i.e., basal CMRO2, intact. In conclusion, whereas......) of postsynaptic excitation and PC spiking during evoked and ongoing neuronal activity in the rat. By inhibiting excitatory synaptic input using ionotropic glutamate receptor blockers, we found that the increase in CMRO2 evoked by parallel fiber (PF) stimulation depended entirely on postsynaptic excitation...... basal CMRO2 in anesthetized animals did not seem to be related to neurosignaling, increases in CMRO2 could be induced by all aspects of neurosignaling. Our findings imply that CMRO2 responses cannot a priori be assigned to specific neuronal activities....

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.

Hypochlorous and peracetic acid induced oxidation of dairy proteins.

Science.gov (United States)

Kerkaert, Barbara; Mestdagh, Frédéric; Cucu, Tatiana; Aedo, Philip Roger; Ling, Shen Yan; De Meulenaer, Bruno

2011-02-09

Hypochlorous and peracetic acids, both known disinfectants in the food industry, were compared for their oxidative capacity toward dairy proteins. Whey proteins and caseins were oxidized under well controlled conditions at pH 8 as a function of the sanitizing concentration. Different markers for protein oxidation were monitored. The results established that the protein carbonyl content was a rather unspecific marker for protein oxidation, which did not allow one to differentiate the oxidant used especially at the lower concentrations. Cysteine, tryptophan, and methionine were proven to be the most vulnerable amino acids for degradation upon hypochlorous and peracetic acid treatment, while tyrosine was only prone to degradation in the presence of hypochlorous acid. Hypochlorous acid induced oxidation gave rise to protein aggregation, while during peracetic acid induced oxidation, no high molecular weight aggregates were observed. Protein aggregation upon hypochlorous acid oxidation could primarily be linked to tryptophan and tyrosine degradation.

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.

Measurement of isotope abundance variations in nature by gravimetric spiking isotope dilution analysis (GS-IDA).

Science.gov (United States)

Chew, Gina; Walczyk, Thomas

2013-04-02

Subtle variations in the isotopic composition of elements carry unique information about physical and chemical processes in nature and are now exploited widely in diverse areas of research. Reliable measurement of natural isotope abundance variations is among the biggest challenges in inorganic mass spectrometry as they are highly sensitive to methodological bias. For decades, double spiking of the sample with a mix of two stable isotopes has been considered the reference technique for measuring such variations both by multicollector-inductively coupled plasma mass spectrometry (MC-ICPMS) and multicollector-thermal ionization mass spectrometry (MC-TIMS). However, this technique can only be applied to elements having at least four stable isotopes. Here we present a novel approach that requires measurement of three isotope signals only and which is more robust than the conventional double spiking technique. This became possible by gravimetric mixing of the sample with an isotopic spike in different proportions and by applying principles of isotope dilution for data analysis (GS-IDA). The potential and principle use of the technique is demonstrated for Mg in human urine using MC-TIMS for isotopic analysis. Mg is an element inaccessible to double spiking methods as it consists of three stable isotopes only and shows great potential for metabolically induced isotope effects waiting to be explored.

Spike Code Flow in Cultured Neuronal Networks

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Shinichi Tamura

2016-01-01

Full Text Available We observed spike trains produced by one-shot electrical stimulation with 8 × 8 multielectrodes in cultured neuronal networks. Each electrode accepted spikes from several neurons. We extracted the short codes from spike trains and obtained a code spectrum with a nominal time accuracy of 1%. We then constructed code flow maps as movies of the electrode array to observe the code flow of “1101” and “1011,” which are typical pseudorandom sequence such as that we often encountered in a literature and our experiments. They seemed to flow from one electrode to the neighboring one and maintained their shape to some extent. To quantify the flow, we calculated the “maximum cross-correlations” among neighboring electrodes, to find the direction of maximum flow of the codes with lengths less than 8. Normalized maximum cross-correlations were almost constant irrespective of code. Furthermore, if the spike trains were shuffled in interval orders or in electrodes, they became significantly small. Thus, the analysis suggested that local codes of approximately constant shape propagated and conveyed information across the network. Hence, the codes can serve as visible and trackable marks of propagating spike waves as well as evaluating information flow in the neuronal network.

Computational modeling of distinct neocortical oscillations driven by cell-type selective optogenetic drive: Separable resonant circuits controlled by low-threshold spiking and fast-spiking interneurons

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Dorea Vierling-Claassen

2010-11-01

Full Text Available Selective optogenetic drive of fast spiking interneurons (FS leads to enhanced local field potential (LFP power across the traditional gamma frequency band (20-80Hz; Cardin et al., 2009. In contrast, drive to regular-spiking pyramidal cells (RS enhances power at lower frequencies, with a peak at 8 Hz. The first result is consistent with previous computational studies emphasizing the role of FS and the time constant of GABAA synaptic inhibition in gamma rhythmicity. However, the same theoretical models do not typically predict low-frequency LFP enhancement with RS drive. To develop hypotheses as to how the same network can support these contrasting behaviors, we constructed a biophysically principled network model of primary somatosensory neocortex containing FS, RS and low-threshold-spiking (LTS interneurons. Cells were modeled with detailed cell anatomy and physiology, multiple dendritic compartments, and included active somatic and dendritic ionic currents. Consistent with prior studies, the model demonstrated gamma resonance during FS drive, dependent on the time-constant of GABAA inhibition induced by synchronous FS activity. Lower frequency enhancement during RS drive was replicated only on inclusion of an inhibitory LTS population, whose activation was critically dependent on RS synchrony and evoked longer-lasting inhibition. Our results predict that differential recruitment of FS and LTS inhibitory populations is essential to the observed cortical dynamics and may provide a means for amplifying the natural expression of distinct oscillations in normal cortical processing.

Attention Induced Gain Stabilization in Broad and Narrow-Spiking Cells in the Frontal Eye-Field of Macaque Monkeys

Science.gov (United States)

Brandt, Christian; Dasilva, Miguel; Gotthardt, Sascha; Chicharro, Daniel; Panzeri, Stefano; Distler, Claudia

2016-01-01

Top-down attention increases coding abilities by altering firing rates and rate variability. In the frontal eye field (FEF), a key area enabling top-down attention, attention induced firing rate changes are profound, but its effect on different cell types is unknown. Moreover, FEF is the only cortical area investigated in which attention does not affect rate variability, as assessed by the Fano factor, suggesting that task engagement affects cortical state nonuniformly. We show that putative interneurons in FEF of Macaca mulatta show stronger attentional rate modulation than putative pyramidal cells. Partitioning rate variability reveals that both cell types reduce rate variability with attention, but more strongly so in narrow-spiking cells. The effects are captured by a model in which attention stabilizes neuronal excitability, thereby reducing the expansive nonlinearity that links firing rate and variance. These results show that the effect of attention on different cell classes and different coding properties are consistent across the cortical hierarchy, acting through increased and stabilized neuronal excitability. SIGNIFICANCE STATEMENT Cortical processing is critically modulated by attention. A key feature of this influence is a modulation of “cortical state,” resulting in increased neuronal excitability and resilience of the network against perturbations, lower rate variability, and an increased signal-to-noise ratio. In the frontal eye field (FEF), an area assumed to control spatial attention in human and nonhuman primates, firing rate changes with attention occur, but rate variability, quantified by the Fano factor, appears to be unaffected by attention. Using recently developed analysis tools and models to quantify attention effects on narrow- and broad-spiking cell activity, we show that attention alters cortical state strongly in the FEF, demonstrating that its effect on the neuronal network is consistent across the cortical hierarchy. PMID

Structure of Simian Immunodeficiency Virus Envelope Spikes Bound with CD4 and Monoclonal Antibody 36D5.

Science.gov (United States)

Hu, Guiqing; Liu, Jun; Roux, Kenneth H; Taylor, Kenneth A

2017-08-15

The human immunodeficiency virus type 1 (HIV-1)/simian immunodeficiency virus (SIV) envelope spike (Env) mediates viral entry into host cells. The V3 loop of the gp120 component of the Env trimer contributes to the coreceptor binding site and is a target for neutralizing antibodies. We used cryo-electron tomography to visualize the binding of CD4 and the V3 loop monoclonal antibody (MAb) 36D5 to gp120 of the SIV Env trimer. Our results show that 36D5 binds gp120 at the base of the V3 loop and suggest that the antibody exerts its neutralization effect by blocking the coreceptor binding site. The antibody does this without altering the dynamics of the spike motion between closed and open states when CD4 is bound. The interaction between 36D5 and SIV gp120 is similar to the interaction between some broadly neutralizing anti-V3 loop antibodies and HIV-1 gp120. Two conformations of gp120 bound with CD4 are revealed, suggesting an intrinsic dynamic nature of the liganded Env trimer. CD4 binding substantially increases the binding of 36D5 to gp120 in the intact Env trimer, consistent with CD4-induced changes in the conformation of gp120 and the antibody binding site. Binding by MAb 36D5 does not substantially alter the proportions of the two CD4-bound conformations. The position of MAb 36D5 at the V3 base changes little between conformations, indicating that the V3 base serves as a pivot point during the transition between these two states. IMPORTANCE Glycoprotein spikes on the surfaces of SIV and HIV are the sole targets available to the immune system for antibody neutralization. Spikes evade the immune system by a combination of a thick layer of polysaccharide on the surface (the glycan shield) and movement between spike domains that masks the epitope conformation. Using SIV virions whose spikes were "decorated" with the primary cellular receptor (CD4) and an antibody (36D5) at part of the coreceptor binding site, we visualized multiple conformations trapped by the

Comparison of Classifier Architectures for Online Neural Spike Sorting.

Science.gov (United States)

Saeed, Maryam; Khan, Amir Ali; Kamboh, Awais Mehmood

2017-04-01

High-density, intracranial recordings from micro-electrode arrays need to undergo Spike Sorting in order to associate the recorded neuronal spikes to particular neurons. This involves spike detection, feature extraction, and classification. To reduce the data transmission and power requirements, on-chip real-time processing is becoming very popular. However, high computational resources are required for classifiers in on-chip spike-sorters, making scalability a great challenge. In this review paper, we analyze several popular classifiers to propose five new hardware architectures using the off-chip training with on-chip classification approach. These include support vector classification, fuzzy C-means classification, self-organizing maps classification, moving-centroid K-means classification, and Cosine distance classification. The performance of these architectures is analyzed in terms of accuracy and resource requirement. We establish that the neural networks based Self-Organizing Maps classifier offers the most viable solution. A spike sorter based on the Self-Organizing Maps classifier, requires only 7.83% of computational resources of the best-reported spike sorter, hierarchical adaptive means, while offering a 3% better accuracy at 7 dB SNR.

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.

Oral Uncaria rhynchophylla (UR) reduces kainic acid-induced epileptic seizures and neuronal death accompanied by attenuating glial cell proliferation and S100B proteins in rats.

Science.gov (United States)

Lin, Yi-Wen; Hsieh, Ching-Liang

2011-05-17

Epilepsy is a common clinical syndrome with recurrent neuronal discharges in cerebral cortex and hippocampus. Here we aim to determine the protective role of Uncaria rhynchophylla (UR), an herbal drug belong to Traditional Chinese Medicine (TCM), on epileptic rats. To address this issue, we tested the effect of UR on kainic acid (KA)-induced epileptic seizures and further investigate the underlying mechanisms. Oral UR successfully decreased neuronal death and discharges in hippocampal CA1 pyramidal neurons. The population spikes (PSs) were decreased from 4.1 ± 0.4 mV to 2.1 ± 0.3 mV in KA-induced epileptic seizures and UR-treated groups, respectively. Oral UR protected animals from neuronal death induced by KA treatment (from 34 ± 4.6 to 191.7 ± 48.6 neurons/field) through attenuating glial cell proliferation and S100B protein expression but not GABAA and TRPV1 receptors. The above results provide detail mechanisms underlying the neuroprotective action of UR on KA-induced epileptic seizure in hippocampal CA1 neurons. Crown Copyright © 2011. Published by Elsevier Ireland Ltd. All rights reserved.

Scaling of spiking and humping in keyhole welding

Energy Technology Data Exchange (ETDEWEB)

Wei, P S; Chuang, K C [Department of Mechanical and Electro-Mechanical Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan (China); DebRoy, T [Department of Materials Science and Engineering, The Pennsylvania State University, University Park, PA 16802 (United States); Ku, J S, E-mail: pswei@mail.nsysu.edu.tw, E-mail: cielo.zhuang@gmail.com, E-mail: rtd1@psu.edu, E-mail: jsku@mail.nsysu.edu.tw [Institute of Materials Science and Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan (China)

2011-06-22

Spiking, rippling and humping seriously reduce the strength of welds. The effects of beam focusing, volatile alloying element concentration and welding velocity on spiking, coarse rippling and humping in keyhole mode electron-beam welding are examined through scale analysis. Although these defects have been studied in the past, the mechanisms for their formation are not fully understood. This work relates the average amplitudes of spikes to fusion zone depth for the welding of Al 6061, SS 304 and carbon steel, and Al 5083. The scale analysis introduces welding and melting efficiencies and an appropriate power distribution to account for the focusing effects, and the energy which is reflected and escapes through the keyhole opening to the surroundings. The frequency of humping and spiking can also be predicted from the scale analysis. The analysis also reveals the interrelation between coarse rippling and humping. The data and the mechanistic findings reported in this study are useful for understanding and preventing spiking and humping during keyhole mode electron and laser beam welding.

A metric space approach to the information capacity of spike trains

OpenAIRE

HOUGHTON, CONOR JAMES; GILLESPIE, JAMES

2010-01-01

PUBLISHED Classical information theory can be either discrete or continuous, corresponding to discrete or continuous random variables. However, although spike times in a spike train are described by continuous variables, the information content is usually calculated using discrete information theory. This is because the number of spikes, and hence, the number of variables, varies from spike train to spike train, making the continuous theory difficult to apply.It is possible to avoid ...

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.

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.

In-reactor creep of zirconium alloys by thermal spikes

International Nuclear Information System (INIS)

Ibrahim, E.F.

1975-01-01

The size and duration of thermal spikes from fast neutrons have been calculated for zirconium alloys, showing that spikes up to 1.8 nm radius may exist for 2 x 10 -11 s at greater than melting point, at 570K ambient temperature. Creep rates have been calculated assuming that the elastic strain from the applied stress relaxes in the volume of the spikes (by preferential loop alignment or modification of an existing dislocation network). The calculated rates are consistent with strain rates observed in long term tests-in-reactor, if spike lifetimes are 2 to 2.5 x 10 -11 s. (Auth.)

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

Spike-threshold adaptation predicted by membrane potential dynamics in vivo.

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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.

An Overview of Bayesian Methods for Neural Spike Train Analysis

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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.

Palmitoylation of SARS-CoV S protein is necessary for partitioning into detergent-resistant membranes and cell-cell fusion but not interaction with M protein

International Nuclear Information System (INIS)

McBride, Corrin E.; Machamer, Carolyn E.

2010-01-01

Coronaviruses are enveloped RNA viruses that generally cause mild disease in humans. However, the recently emerged coronavirus that caused severe acute respiratory syndrome (SARS-CoV) is the most pathogenic human coronavirus discovered to date. The SARS-CoV spike (S) protein mediates virus entry by binding cellular receptors and inducing fusion between the viral envelope and the host cell membrane. Coronavirus S proteins are palmitoylated, which may affect function. Here, we created a non-palmitoylated SARS-CoV S protein by mutating all nine cytoplasmic cysteine residues. Palmitoylation of SARS-CoV S was required for partitioning into detergent-resistant membranes and for cell-cell fusion. Surprisingly, however, palmitoylation of S was not required for interaction with SARS-CoV M protein. This contrasts with the requirement for palmitoylation of mouse hepatitis virus S protein for interaction with M protein and may point to important differences in assembly and infectivity of these two coronaviruses.

An Unsupervised Online Spike-Sorting Framework.

Science.gov (United States)

Knieling, Simeon; Sridharan, Kousik S; Belardinelli, Paolo; Naros, Georgios; Weiss, Daniel; Mormann, Florian; Gharabaghi, Alireza

2016-08-01

Extracellular neuronal microelectrode recordings can include action potentials from multiple neurons. To separate spikes from different neurons, they can be sorted according to their shape, a procedure referred to as spike-sorting. Several algorithms have been reported to solve this task. However, when clustering outcomes are unsatisfactory, most of them are difficult to adjust to achieve the desired results. We present an online spike-sorting framework that uses feature normalization and weighting to maximize the distinctiveness between different spike shapes. Furthermore, multiple criteria are applied to either facilitate or prevent cluster fusion, thereby enabling experimenters to fine-tune the sorting process. We compare our method to established unsupervised offline (Wave_Clus (WC)) and online (OSort (OS)) algorithms by examining their performance in sorting various test datasets using two different scoring systems (AMI and the Adamos metric). Furthermore, we evaluate sorting capabilities on intra-operative recordings using established quality metrics. Compared to WC and OS, our algorithm achieved comparable or higher scores on average and produced more convincing sorting results for intra-operative datasets. Thus, the presented framework is suitable for both online and offline analysis and could substantially improve the quality of microelectrode-based data evaluation for research and clinical application.

The roles of phosphorylation and SHAGGY-like protein kinases in geminivirus C4 protein induced hyperplasia.

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Katherine Mills-Lujan

Full Text Available Even though plant cells are highly plastic, plants only develop hyperplasia under very specific abiotic and biotic stresses, such as when exposed to pathogens like Beet curly top virus (BCTV. The C4 protein of BCTV is sufficient to induce hyperplasia and alter Arabidopsis development. It was previously shown that C4 interacts with two Arabidopsis Shaggy-like protein kinases, AtSK21 and 23, which are negative regulators of brassinosteroid (BR hormone signaling. Here we show that the C4 protein interacts with five additional AtSK family members. Bikinin, a competitive inhibitor of the seven AtSK family members that interact with C4, induced hyperplasia similar to that induced by the C4 protein. The Ser49 residue of C4 was found to be critical for C4 function, since: 1 mutagenesis of Ser49 to Ala abolished the C4-induced phenotype, abolished C4/AtSK interactions, and resulted in a mutant protein that failed to induce changes in the BR signaling pathway; 2 Ser49 is phosphorylated in planta; and 3 plant-encoded AtSKs must be catalytically active to interact with C4. A C4 N-myristoylation site mutant that does not localize to the plasma membrane and does not induce a phenotype, retained the ability to bind AtSKs. Taken together, these results suggest that plasma membrane associated C4 interacts with and co-opts multiple AtSKs to promote its own phosphorylation and activation to subsequently compromise cell cycle control.

Emergent dynamics of spiking neurons with fluctuating threshold

Science.gov (United States)

Bhattacharjee, Anindita; Das, M. K.

2017-05-01

Role of fluctuating threshold on neuronal dynamics is investigated. The threshold function is assumed to follow a normal probability distribution. Standard deviation of inter-spike interval of the response is computed as an indicator of irregularity in spike emission. It has been observed that, the irregularity in spiking is more if the threshold variation is more. A significant change in modal characteristics of Inter Spike Intervals (ISI) is seen to occur as a function of fluctuation parameter. Investigation is further carried out for coupled system of neurons. Cooperative dynamics of coupled neurons are discussed in view of synchronization. Total and partial synchronization regimes are depicted with the help of contour plots of synchrony measure under various conditions. Results of this investigation may provide a basis for exploring the complexities of neural communication and brain functioning.

Lipid-protein interaction induced domains: Kinetics and conformational changes in multicomponent vesicles

Science.gov (United States)

Sreeja, K. K.; Sunil Kumar, P. B.

2018-04-01

The spatio-temporal organization of proteins and the associated morphological changes in membranes are of importance in cell signaling. Several mechanisms that promote the aggregation of proteins at low cell surface concentrations have been investigated in the past. We show, using Monte Carlo simulations, that the affinity of proteins for specific lipids can hasten their aggregation kinetics. The lipid membrane is modeled as a dynamically triangulated surface with the proteins defined as in-plane fields at the vertices. We show that, even at low protein concentrations, strong lipid-protein interactions can result in large protein clusters indicating a route to lipid mediated signal amplification. At high protein concentrations, the domains form buds similar to that seen in lipid-lipid interaction induced phase separation. Protein interaction induced domain budding is suppressed when proteins act as anisotropic inclusions and exhibit nematic orientational order. The kinetics of protein clustering and resulting conformational changes are shown to be significantly different for the isotropic and anisotropic curvature inducing proteins.

Central ions and lateral asparagine/glutamine zippers stabilize the post-fusion hairpin conformation of the SARS coronavirus spike glycoprotein

International Nuclear Information System (INIS)

Duquerroy, Stephane; Vigouroux, Armelle; Rottier, Peter J.M.; Rey, Felix A.; Jan Bosch, Berend

2005-01-01

The coronavirus spike glycoprotein is a class I membrane fusion protein with two characteristic heptad repeat regions (HR1 and HR2) in its ectodomain. Here, we report the X-ray structure of a previously characterized HR1/HR2 complex of the severe acute respiratory syndrome coronavirus spike protein. As expected, the HR1 and HR2 segments are organized in antiparallel orientations within a rod-like molecule. The HR1 helices form an exceptionally long (120 A) internal coiled coil stabilized by hydrophobic and polar interactions. A striking arrangement of conserved asparagine and glutamine residues of HR1 propagates from two central chloride ions, providing hydrogen-bonding 'zippers' that strongly constrain the path of the HR2 main chain, forcing it to adopt an extended conformation at either end of a short HR2 α-helix

Single-trial estimation of stimulus and spike-history effects on time-varying ensemble spiking activity of multiple neurons: a simulation study

International Nuclear Information System (INIS)

Shimazaki, Hideaki

2013-01-01

Neurons in cortical circuits exhibit coordinated spiking activity, and can produce correlated synchronous spikes during behavior and cognition. We recently developed a method for estimating the dynamics of correlated ensemble activity by combining a model of simultaneous neuronal interactions (e.g., a spin-glass model) with a state-space method (Shimazaki et al. 2012 PLoS Comput Biol 8 e1002385). This method allows us to estimate stimulus-evoked dynamics of neuronal interactions which is reproducible in repeated trials under identical experimental conditions. However, the method may not be suitable for detecting stimulus responses if the neuronal dynamics exhibits significant variability across trials. In addition, the previous model does not include effects of past spiking activity of the neurons on the current state of ensemble activity. In this study, we develop a parametric method for simultaneously estimating the stimulus and spike-history effects on the ensemble activity from single-trial data even if the neurons exhibit dynamics that is largely unrelated to these effects. For this goal, we model ensemble neuronal activity as a latent process and include the stimulus and spike-history effects as exogenous inputs to the latent process. We develop an expectation-maximization algorithm that simultaneously achieves estimation of the latent process, stimulus responses, and spike-history effects. The proposed method is useful to analyze an interaction of internal cortical states and sensory evoked activity

Proteins induced by salt stress in tomato germinating seeds

International Nuclear Information System (INIS)

Torres-Shumann, S.; Godoy, J.A.; del Pozo, O.; Pintor-Toro, J.A.

1989-01-01

Salt effects on protein synthesis in tomato germinating seeds were investigated by two-dimensional polyacrilamide gel electrophoresis of proteins labeled in vivo with ( 35 S)-Methionine. Seeds germinating in NaCl were analyzed at three germination stages (4mm long radicals, 15mm long radicles and expanding cotyledons) and compared to those germinating in water. At the first germination stage several basic proteins of M.W. 13Kd, 16Kd, 17Kd and 18Kd were detected in only salt germinating seeds. Other basic proteins of M.W. 12Kd, 50Kd and 54Kd were salt-induced at the second and third stage of germination. One 14Kd acid protein is observed in every assayed stage and shows several phosphorylated forms. The levels of expression of these proteins are directly correlated to assayed NaCl concentrations. All of these proteins, except 17Kd, are also induced by abscisic acid (ABA) in the same germination stages. A cooperative effect on the synthesis of these proteins is observed when both ABA and NaCl are present

The electric potential of tripolar spikes

Energy Technology Data Exchange (ETDEWEB)

Nocera, L. [Theoretical Plasma Physics, IPCF-CNR, Via Moruzzi 1, I-56124 Pisa (Italy)

2010-02-22

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.

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.

Mouse neuroblastoma cell-based model and the effect of epileptic events on calcium oscillations and neural spikes

Science.gov (United States)

Kim, Suhwan; Jung, Unsang; Baek, Juyoung; Lee, Sangwon; Jung, Woonggyu; Kim, Jeehyun; Kang, Shinwon

2013-01-01

Recently, mouse neuroblastoma cells have been considered as an attractive model for the study of human neurological and prion diseases, and they have been intensively used as a model system in different areas. For example, the differentiation of neuro2a (N2A) cells, receptor-mediated ion current, and glutamate-induced physiological responses have been actively investigated with these cells. These mouse neuroblastoma N2A cells are of interest because they grow faster than other cells of neural origin and have a number of other advantages. The calcium oscillations and neural spikes of mouse neuroblastoma N2A cells in epileptic conditions are evaluated. Based on our observations of neural spikes in these cells with our proposed imaging modality, we reported that they can be an important model in epileptic activity studies. We concluded that mouse neuroblastoma N2A cells produce epileptic spikes in vitro in the same way as those produced by neurons or astrocytes. This evidence suggests that increased levels of neurotransmitter release due to the enhancement of free calcium from 4-aminopyridine causes the mouse neuroblastoma N2A cells to produce epileptic spikes and calcium oscillations.

Noisy Spiking in Visual Area V2 of Amblyopic Monkeys.

Science.gov (United States)

Wang, Ye; Zhang, Bin; Tao, Xiaofeng; Wensveen, Janice M; Smith, Earl L; Chino, Yuzo M

2017-01-25

Interocular decorrelation of input signals in developing visual cortex can cause impaired binocular vision and amblyopia. Although increased intrinsic noise is thought to be responsible for a range of perceptual deficits in amblyopic humans, the neural basis for the elevated perceptual noise in amblyopic primates is not known. Here, we tested the idea that perceptual noise is linked to the neuronal spiking noise (variability) resulting from developmental alterations in cortical circuitry. To assess spiking noise, we analyzed the contrast-dependent dynamics of spike counts and spiking irregularity by calculating the square of the coefficient of variation in interspike intervals (CV 2 ) and the trial-to-trial fluctuations in spiking, or mean matched Fano factor (m-FF) in visual area V2 of monkeys reared with chronic monocular defocus. In amblyopic neurons, the contrast versus response functions and the spike count dynamics exhibited significant deviations from comparable data for normal monkeys. The CV 2 was pronounced in amblyopic neurons for high-contrast stimuli and the m-FF was abnormally high in amblyopic neurons for low-contrast gratings. The spike count, CV 2 , and m-FF of spontaneous activity were also elevated in amblyopic neurons. These contrast-dependent spiking irregularities were correlated with the level of binocular suppression in these V2 neurons and with the severity of perceptual loss for individual monkeys. Our results suggest that the developmental alterations in normalization mechanisms resulting from early binocular suppression can explain much of these contrast-dependent spiking abnormalities in V2 neurons and the perceptual performance of our amblyopic monkeys. Amblyopia is a common developmental vision disorder in humans. Despite the extensive animal studies on how amblyopia emerges, we know surprisingly little about the neural basis of amblyopia in humans and nonhuman primates. Although the vision of amblyopic humans is often described as

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.

Protein-induced satiation and the calcium-sensing receptor

Directory of Open Access Journals (Sweden)

Ojha U

2018-03-01

Full Text Available Utkarsh Ojha Faculty of Medicine, Imperial College School of Medicine, Imperial College London, London, UK Abstract: Obesity is a major global health issue. High-protein diets have been shown to be associated with weight loss and satiety. The precise mechanism by which protein-rich diets promote weight loss remains unclear. Evidence suggests amino acids, formed as a consequence of protein digestion, are sensed by specific receptors on L-cells in the gastrointestinal (GI tract. These L-cells respond by secreting gut hormones that subsequently induce satiety. In recent years, the calcium-sensing receptor has been identified in several cells of the GI tract, including L-cells, and suggested to sense specific amino acids. This review evaluates the evidence for protein-rich diets in inducing weight loss and how the calcium-sensing receptor may be implicated in this phenomenon. Commandeering the mechanisms by which elements of a protein-rich diet suppress appetite may provide another successful avenue for developing anti-obesity drugs. Keywords: amino acids, energy regulation, obesity therapy, glucagon-like-peptide-1, peptide YY

Voltage spikes in Nb3Sn and NbTi strands

International Nuclear Information System (INIS)

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, A.V.; Fermilab

2005-01-01

As part of the High Field Magnet program at Fermilab several NbTi and Nb 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

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.

A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'.

Science.gov (United States)

Swindale, Nicholas V; Mitelut, Catalin; Murphy, Timothy H; Spacek, Martin A

2017-02-10

Few stand-alone software applications are available for sorting spikes from recordings made with multi-electrode arrays. Ideally, an application should be user friendly with a graphical user interface, able to read data files in a variety of formats, and provide users with a flexible set of tools giving them the ability to detect and sort extracellular voltage waveforms from different units with some degree of reliability. Previously published spike sorting methods are now available in a software program, SpikeSorter, intended to provide electrophysiologists with a complete set of tools for sorting, starting from raw recorded data file and ending with the export of sorted spikes times. Procedures are automated to the extent this is currently possible. The article explains and illustrates the use of the program. A representative data file is opened, extracellular traces are filtered, events are detected and then clustered. A number of problems that commonly occur during sorting are illustrated, including the artefactual over-splitting of units due to the tendency of some units to fire spikes in pairs where the second spike is significantly smaller than the first, and over-splitting caused by slow variation in spike height over time encountered in some units. The accuracy of SpikeSorter's performance has been tested with surrogate ground truth data and found to be comparable to that of other algorithms in current development.

A Markovian event-based framework for stochastic spiking neural networks.

Science.gov (United States)

Touboul, Jonathan D; Faugeras, Olivier D

2011-11-01

In spiking neural networks, the information is conveyed by the spike times, that depend on the intrinsic dynamics of each neuron, the input they receive and on the connections between neurons. In this article we study the Markovian nature of the sequence of spike times in stochastic neural networks, and in particular the ability to deduce from a spike train the next spike time, and therefore produce a description of the network activity only based on the spike times regardless of the membrane potential process. To study this question in a rigorous manner, we introduce and study an event-based description of networks of noisy integrate-and-fire neurons, i.e. that is based on the computation of the spike times. We show that the firing times of the neurons in the networks constitute a Markov chain, whose transition probability is related to the probability distribution of the interspike interval of the neurons in the network. In the cases where the Markovian model can be developed, the transition probability is explicitly derived in such classical cases of neural networks as the linear integrate-and-fire neuron models with excitatory and inhibitory interactions, for different types of synapses, possibly featuring noisy synaptic integration, transmission delays and absolute and relative refractory period. This covers most of the cases that have been investigated in the event-based description of spiking deterministic neural networks.

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

Noise-enhanced coding in phasic neuron spike trains.

Science.gov (United States)

Ly, Cheng; Doiron, Brent

2017-01-01

The stochastic nature of neuronal response has lead to conjectures about the impact of input fluctuations on the neural coding. For the most part, low pass membrane integration and spike threshold dynamics have been the primary features assumed in the transfer from synaptic input to output spiking. Phasic neurons are a common, but understudied, neuron class that are characterized by a subthreshold negative feedback that suppresses spike train responses to low frequency signals. Past work has shown that when a low frequency signal is accompanied by moderate intensity broadband noise, phasic neurons spike trains are well locked to the signal. We extend these results with a simple, reduced model of phasic activity that demonstrates that a non-Markovian spike train structure caused by the negative feedback produces a noise-enhanced coding. Further, this enhancement is sensitive to the timescales, as opposed to the intensity, of a driving signal. Reduced hazard function models show that noise-enhanced phasic codes are both novel and separate from classical stochastic resonance reported in non-phasic neurons. The general features of our theory suggest that noise-enhanced codes in excitable systems with subthreshold negative feedback are a particularly rich framework to study.

Financial time series prediction using spiking neural networks.

Science.gov (United States)

Reid, David; Hussain, Abir Jaafar; Tawfik, Hissam

2014-01-01

In this paper a novel application of a particular type of spiking neural network, a Polychronous Spiking Network, was used for financial time series prediction. It is argued that the inherent temporal capabilities of this type of network are suited to non-stationary data such as this. The performance of the spiking neural network was benchmarked against three systems: two "traditional", rate-encoded, neural networks; a Multi-Layer Perceptron neural network and a Dynamic Ridge Polynomial neural network, and a standard Linear Predictor Coefficients model. For this comparison three non-stationary and noisy time series were used: IBM stock data; US/Euro exchange rate data, and the price of Brent crude oil. The experiments demonstrated favourable prediction results for the Spiking Neural Network in terms of Annualised Return and prediction error for 5-Step ahead predictions. These results were also supported by other relevant metrics such as Maximum Drawdown and Signal-To-Noise ratio. This work demonstrated the applicability of the Polychronous Spiking Network to financial data forecasting and this in turn indicates the potential of using such networks over traditional systems in difficult to manage non-stationary environments.

Genes with a spike expression are clustered in chromosome (sub)bands and spike (sub)bands have a powerful prognostic value in patients with multiple myeloma

Science.gov (United States)

Kassambara, Alboukadel; Hose, Dirk; Moreaux, Jérôme; Walker, Brian A.; Protopopov, Alexei; Reme, Thierry; Pellestor, Franck; Pantesco, Véronique; Jauch, Anna; Morgan, Gareth; Goldschmidt, Hartmut; Klein, Bernard

2012-01-01

Background Genetic abnormalities are common in patients with multiple myeloma, and may deregulate gene products involved in tumor survival, proliferation, metabolism and drug resistance. In particular, translocations may result in a high expression of targeted genes (termed spike expression) in tumor cells. We identified spike genes in multiple myeloma cells of patients with newly-diagnosed myeloma and investigated their prognostic value. Design and Methods Genes with a spike expression in multiple myeloma cells were picked up using box plot probe set signal distribution and two selection filters. Results In a cohort of 206 newly diagnosed patients with multiple myeloma, 2587 genes/expressed sequence tags with a spike expression were identified. Some spike genes were associated with some transcription factors such as MAF or MMSET and with known recurrent translocations as expected. Spike genes were not associated with increased DNA copy number and for a majority of them, involved unknown mechanisms. Of spiked genes, 36.7% clustered significantly in 149 out of 862 documented chromosome (sub)bands, of which 53 had prognostic value (35 bad, 18 good). Their prognostic value was summarized with a spike band score that delineated 23.8% of patients with a poor median overall survival (27.4 months versus not reached, Pband score was independent of other gene expression profiling-based risk scores, t(4;14), or del17p in an independent validation cohort of 345 patients. Conclusions We present a new approach to identify spike genes and their relationship to patients’ survival. PMID:22102711

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.

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.

Ligand Binding Domain Protein in Tetracycline-Inducible Expression

African Journals Online (AJOL)

Purpose: To investigate tetracycline-inducible expression system for producing clinically usable, highquality liver X receptor ligand-binding domain recombinant protein. Methods: In this study, we have expressed and purified the recombinant liver X receptor β-ligand binding domain proteins in E. coli using a tetracycline ...

A spiking neuron circuit based on a carbon nanotube transistor

International Nuclear Information System (INIS)

Chen, C-L; Kim, K; Truong, Q; Shen, A; Li, Z; Chen, Y

2012-01-01

A spiking neuron circuit based on a carbon nanotube (CNT) transistor is presented in this paper. The spiking neuron circuit has a crossbar architecture in which the transistor gates are connected to its row electrodes and the transistor sources are connected to its column electrodes. An electrochemical cell is incorporated in the gate of the transistor by sandwiching a hydrogen-doped poly(ethylene glycol)methyl ether (PEG) electrolyte between the CNT channel and the top gate electrode. An input spike applied to the gate triggers a dynamic drift of the hydrogen ions in the PEG electrolyte, resulting in a post-synaptic current (PSC) through the CNT channel. Spikes input into the rows trigger PSCs through multiple CNT transistors, and PSCs cumulate in the columns and integrate into a ‘soma’ circuit to trigger output spikes based on an integrate-and-fire mechanism. The spiking neuron circuit can potentially emulate biological neuron networks and their intelligent functions. (paper)

Training-induced changes in membrane transport proteins of human skeletal muscle

DEFF Research Database (Denmark)

Juel, C.

2006-01-01

Training improves human physical performance by inducing structural and cardiovascular changes, metabolic changes, and changes in the density of membrane transport proteins. This review focuses on the training-induced changes in proteins involved in sarcolemmal membrane transport. It is concluded...

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.

Gamma-ray-induced changes in the synthesis of tomato pericarp protein

International Nuclear Information System (INIS)

Ferullo, J.M.; Nespoulous, L.; Triantaphylides, C.

1994-01-01

The application of massive doses of gamma rays (1–8 kGy) to mature green cherry-tomato fruits led to a transient fall in pericarp tissue protein metabolism within 6h. A separate 3 kGy treatment resulted in the appearance of certain transcripts and proteins, and a reduction in the abundance of others. At the same dose, protein synthesis regained the control level within 24 h, and in addition a new set of proteins was induced. Gamma-induced proteins (referred to as GIPs) were divided into three groups, depending on the time-course of their induction. Group 1 GIPs were synthesized only during the first few hours following treatment, whereas group 2 GIPs were synthesized for at least 48 h. Group 3 GIPs were progressively induced when the control level of synthesis was restored. These results demonstrated that, despite its deleterious effects on DNA and cell structures, irradiation induced an active response in plant tissue. Comparative experiments suggest that the majority of group 1 GIPs might belong to the heat shock protein family. GIPs might play a role in the protection and repair of cellular structures, or may be implicated in physiological disorders triggered by irradiation. (author)

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.

Pressurized water reactor iodine spiking behavior under power transient conditions

International Nuclear Information System (INIS)

Ho, J.C.

1992-01-01

The most accepted theory explaining the cause of pressurized water reactor iodine spiking is steam formation and condensation in damaged fuel rods. The phase transformation of the primary coolant from water to steam and back again is believed to cause the iodine spiking phenomenon. But due to the complex nature of the phenomenon, a comprehensive model of the behavior has not yet been successfully developed. This paper presents a new model based on an empirical approach, which gives a first-order estimation of the peak iodine spiking magnitude. Based on the proposed iodine spiking model, it is apparent that it is feasible to derive a correlation using the plant operating data base to monitor and control the peak iodine spiking magnitude

Ethylene-induced senescence-related gene expression requires protein synthesis

International Nuclear Information System (INIS)

Lawton, K.A.; Raghothama, K.G.; Woodson, W.R.

1990-01-01

We have investigated the effects of inhibiting protein synthesis on the ethylene-induced expression of 3 carnation senescence-related genes, pSR5, pSR8, and pSR12. Treatment of preclimacteric carnation petal discs with 1μg/ml of cycloheximide, a cytoplasmic protein synthesis inhibitor, for 3h inhibited protein synthesis by >80% as quantitated by the incorporation of [35S]methionine into protein. Pre-treatment of petal discs with cycloheximide prevented ethylene-induced SR transcript accumulation. Cycloheximide treatment of petal discs held in air did not result in increased levels of SR mRNA. These results indicate that ethylene does not interact with pre-formed factors but rather that the activation of SR gene expression by ethylene is mediated by labile protein factor(s) synthesized on cytoplasmic ribosomes. Experiments are currently underway to determine if cycloheximide exerts its effect at the transcriptional or post-transcriptional level

Spike and burst coding in thalamocortical relay cells.

Directory of Open Access Journals (Sweden)

Fleur Zeldenrust

2018-02-01

Full Text Available Mammalian thalamocortical relay (TCR neurons switch their firing activity between a tonic spiking and a bursting regime. In a combined experimental and computational study, we investigated the features in the input signal that single spikes and bursts in the output spike train represent and how this code is influenced by the membrane voltage state of the neuron. Identical frozen Gaussian noise current traces were injected into TCR neurons in rat brain slices as well as in a validated three-compartment TCR model cell. The resulting membrane voltage traces and spike trains were analyzed by calculating the coherence and impedance. Reverse correlation techniques gave the Event-Triggered Average (ETA and the Event-Triggered Covariance (ETC. This demonstrated that the feature selectivity started relatively long before the events (up to 300 ms and showed a clear distinction between spikes (selective for fluctuations and bursts (selective for integration. The model cell was fine-tuned to mimic the frozen noise initiated spike and burst responses to within experimental accuracy, especially for the mixed mode regimes. The information content carried by the various types of events in the signal as well as by the whole signal was calculated. Bursts phase-lock to and transfer information at lower frequencies than single spikes. On depolarization the neuron transits smoothly from the predominantly bursting regime to a spiking regime, in which it is more sensitive to high-frequency fluctuations. The model was then used to elucidate properties that could not be assessed experimentally, in particular the role of two important subthreshold voltage-dependent currents: the low threshold activated calcium current (IT and the cyclic nucleotide modulated h current (Ih. The ETAs of those currents and their underlying activation/inactivation states not only explained the state dependence of the firing regime but also the long-lasting concerted dynamic action of the two

Inducible immune proteins in the dampwood termite Zootermopsis angusticollis

Science.gov (United States)

Rosengaus, Rebeca B.; Cornelisse, Tara; Guschanski, Katerina; Traniello, James F. A.

2007-01-01

Dampwood termites, Zootermopsis angusticollis (Isoptera: Termopsidae), mount an immune response to resist microbial infection. Here we report on results of a novel analysis that allowed us to electrophoretically assess changes in hemolymph proteins in the same individual before and after exposure to a pathogen. We demonstrate that contact with a sublethal concentration of the entomopathogenic fungus Metarhizium anisopliae (Deuteromycotina:Hypomycetes) induces the production of protective proteins in nymphs, pseudergates (false workers), and soldiers. Termites exposed to an immunizing dosage of fungal conidia consistently showed an enhancement of constitutive proteins (62-85 kDa) in the hemolymph as well as an induction of novel proteins (28-48 kDa) relative to preimmunization levels. No significant differences in protein banding patterns relative to baseline levels in control and naïve termites were observed. Incubating excised and eluted induced proteins produced by immunized pseudergates or immunized soldiers with conidia significantly reduced the germination of the fungus. The fungistatic effect of eluted proteins differed significantly among five colonies examined. Our results show that the upregulation of protective proteins in the hemolymph underscores the in vivo immune response we previously recorded in Z. angusticollis.

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

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...... origin. In particular, we allow for the noise to be of arbitrary intensity. The optimal control problem is solved using dynamic programming when the controller has access to the voltage (closed-loop control), and using a maximum principle for the transition density when the controller only has access...... 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...

Anticipating Activity in Social Media Spikes

OpenAIRE

Higham, Desmond J.; Grindrod, Peter; Mantzaris, Alexander V.; Otley, Amanda; Laflin, Peter

2014-01-01

We propose a novel mathematical model for the activity of microbloggers during an external, event-driven spike. The model leads to a testable prediction of who would become most active if a spike were to take place. This type of information is of great interest to commercial organisations, governments and charities, as it identifies key players who can be targeted with information in real time when the network is most receptive. The model takes account of the fact that dynamic interactions ev...

Mutation in Spike Protein Cleavage Site and Pathogenesis of Feline Coronavirus

Science.gov (United States)

Licitra, Beth N.; Millet, Jean K.; Regan, Andrew D.; Hamilton, Brian S.; Rinaldi, Vera D.; Duhamel, Gerald E.

2013-01-01

Feline coronaviruses (FCoV) exist as 2 biotypes: feline enteric coronavirus (FECV) and feline infectious peritonitis virus (FIPV). FECV causes subclinical infections; FIPV causes feline infectious peritonitis (FIP), a systemic and fatal disease. It is thought that mutations in FECV enable infection of macrophages, causing FIP. However, the molecular basis for this biotype switch is unknown. We examined a furin cleavage site in the region between receptor-binding (S1) and fusion (S2) domains of the spike of serotype 1 FCoV. FECV sequences were compared with FIPV sequences. All FECVs had a conserved furin cleavage motif. For FIPV, there was a correlation with the disease and >1 substitution in the S1/S2 motif. Fluorogenic peptide assays confirmed that the substitutions modulate furin cleavage. We document a functionally relevant S1/S2 mutation that arises when FIP develops in a cat. These insights into FIP pathogenesis may be useful in development of diagnostic, prevention, and treatment measures against coronaviruses. PMID:23763835

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.

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

Noradrenaline decreases spike voltage threshold and induces electrographic sharp waves in turtle medial cortex in vitro.

Science.gov (United States)

Lorenzo, Daniel; Velluti, Julio C

2004-01-01

The noradrenergic modulation of neuronal properties has been described at different levels of the mammalian brain. Although the anatomical characteristics of the noradrenergic system are well known in reptiles, functional data are scarce. In our study the noradrenergic modulation of cortical electrogenesis in the turtle medial cortex was studied in vitro using a combination of field and intracellular recordings. Turtle EEG consists of a low voltage background interspersed by spontaneous large sharp waves (LSWs). Noradrenaline (NA, 5-40 microM) induced (or enhanced) the generation of LSWs in a dose-dependent manner. Pharmacological experiments suggest the participation of alpha and beta receptors in this effect. In medial cortex neurons NA induced a hyperpolarization of the resting potential and a decrease of input resistance. Both effects were observed also after TTX treatment. Noradrenaline increased the response of the cells to depolarizing pulses, resulting in an upward shift of the frequency/current relation. In most cells the excitability change was mediated by a decrease of the spike voltage threshold resulting in the reduction of the amount of depolarization needed to fire the cell (voltage threshold minus resting potential). As opposed to the mechanisms reported in mammalian neurons, no changes in the frequency adaptation or the post-train afterhyperpolarization were observed. The NA effects at the cellular level were not reproduced by noradrenergic agonists. Age- and species-dependent properties in the pharmacology of adrenergic receptors could be involved in this result. Cellular effects of NA in turtle cortex are similar to those described in mammals, although the increase in cellular excitability seems to be mediated by a different mechanism. Copyright 2004 S. Karger AG, Basel

Fusion proteins of HIV-1 envelope glycoprotein gp120 with CD4-induced antibodies showed enhanced binding to CD4 and CD4 binding site antibodies

Energy Technology Data Exchange (ETDEWEB)

Chen, Weizao, E-mail: chenw3@mail.nih.gov [Protein Interactions Group, Frederick National Laboratory for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, MD 21702 (United States); Feng, Yang [Protein Interactions Group, Frederick National Laboratory for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, MD 21702 (United States); Wang, Yanping [Protein Interactions Group, Frederick National Laboratory for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, MD 21702 (United States); The Basic Research Program, Science Applications International Corporation-Frederick, Inc., National Cancer Institute, National Institutes of Health, Frederick, MD 21702 (United States); Zhu, Zhongyu; Dimitrov, Dimiter S. [Protein Interactions Group, Frederick National Laboratory for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, MD 21702 (United States)

2012-09-07

Highlights: Black-Right-Pointing-Pointer Some recombinant HIV-1 gp120s do not preserve their conformations on gp140s. Black-Right-Pointing-Pointer We hypothesize that CD4i antibodies could induce conformational changes in gp120. Black-Right-Pointing-Pointer CD4i antibodies enhance binding of CD4 and CD4bs antibodies to gp120. Black-Right-Pointing-Pointer CD4i antibody-gp120 fusion proteins could have potential as vaccine immunogens. -- Abstract: Development of successful AIDS vaccine immunogens continues to be a major challenge. One of the mechanisms by which HIV-1 evades antibody-mediated neutralizing responses is the remarkable conformational flexibility of its envelope glycoprotein (Env) gp120. Some recombinant gp120s do not preserve their conformations on gp140s and functional viral spikes, and exhibit decreased recognition by CD4 and neutralizing antibodies. CD4 binding induces conformational changes in gp120 leading to exposure of the coreceptor-binding site (CoRbs). In this study, we test our hypothesis that CD4-induced (CD4i) antibodies, which target the CoRbs, could also induce conformational changes in gp120 leading to better exposed conserved neutralizing antibody epitopes including the CD4-binding site (CD4bs). We found that a mixture of CD4i antibodies with gp120 only weakly enhanced CD4 binding. However, such interactions in single-chain fusion proteins resulted in gp120 conformations which bound to CD4 and CD4bs antibodies better than the original or mutagenically stabilized gp120s. Moreover, the two molecules in the fusion proteins synergized with each other in neutralizing HIV-1. Therefore, fusion proteins of gp120 with CD4i antibodies could have potential as components of HIV-1 vaccines and inhibitors of HIV-1 entry, and could be used as reagents to explore the conformational flexibility of gp120 and mechanisms of entry and immune evasion.

A novel automated spike sorting algorithm with adaptable feature extraction.

Science.gov (United States)

Bestel, Robert; Daus, Andreas W; Thielemann, Christiane

2012-10-15

To study the electrophysiological properties of neuronal networks, in vitro studies based on microelectrode arrays have become a viable tool for analysis. Although in constant progress, a challenging task still remains in this area: the development of an efficient spike sorting algorithm that allows an accurate signal analysis at the single-cell level. Most sorting algorithms currently available only extract a specific feature type, such as the principal components or Wavelet coefficients of the measured spike signals in order to separate different spike shapes generated by different neurons. However, due to the great variety in the obtained spike shapes, the derivation of an optimal feature set is still a very complex issue that current algorithms struggle with. To address this problem, we propose a novel algorithm that (i) extracts a variety of geometric, Wavelet and principal component-based features and (ii) automatically derives a feature subset, most suitable for sorting an individual set of spike signals. Thus, there is a new approach that evaluates the probability distribution of the obtained spike features and consequently determines the candidates most suitable for the actual spike sorting. These candidates can be formed into an individually adjusted set of spike features, allowing a separation of the various shapes present in the obtained neuronal signal by a subsequent expectation maximisation clustering algorithm. Test results with simulated data files and data obtained from chick embryonic neurons cultured on microelectrode arrays showed an excellent classification result, indicating the superior performance of the described algorithm approach. Copyright © 2012 Elsevier B.V. All rights reserved.

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

Science.gov (United States)

Kreuz, Thomas; Mulansky, Mario; Bozanic, Nebojsa

2015-05-01

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. Copyright © 2015 the American Physiological Society.

Femtosecond laser fabricated spike structures for selective control of cellular behavior.

Science.gov (United States)

Schlie, Sabrina; Fadeeva, Elena; Koch, Jürgen; Ngezahayo, Anaclet; Chichkov, Boris N

2010-09-01

In this study we investigate the potential of femtosecond laser generated micrometer sized spike structures as functional surfaces for selective cell controlling. The spike dimensions as well as the average spike to spike distance can be easily tuned by varying the process parameters. Moreover, negative replications in soft materials such as silicone elastomer can be produced. This allows tailoring of wetting properties of the spike structures and their negative replicas representing a reduced surface contact area. Furthermore, we investigated material effects on cellular behavior. By comparing human fibroblasts and SH-SY5Y neuroblastoma cells we found that the influence of the material was cell specific. The cells not only changed their morphology, but also the cell growth was affected. Whereas, neuroblastoma cells proliferated at the same rate on the spike structures as on the control surfaces, the proliferation of fibroblasts was reduced by the spike structures. These effects can result from the cell specific adhesion patterns as shown in this work. These findings show a possibility to design defined surface microstructures, which could control cellular behavior in a cell specific manner.

Mouse neuroblastoma cell based model and the effect of epileptic events on calcium oscillations and neural spikes

Science.gov (United States)

Kim, Suhwan; Baek, Juyeong; Jung, Unsang; Lee, Sangwon; Jung, Woonggyu; Kim, Jeehyun; Kang, Shinwon

2013-05-01

Recently, Mouse neuroblastoma cells are considered as an attractive model for the study of human neurological and prion diseases, and intensively used as a model system in different areas. Among those areas, differentiation of neuro2a (N2A) cells, receptor mediated ion current, and glutamate induced physiological response are actively investigated. The reason for the interest to mouse neuroblastoma N2A cells is that they have a fast growing rate than other cells in neural origin with a few another advantages. This study evaluated the calcium oscillations and neural spikes recording of mouse neuroblastoma N2A cells in an epileptic condition. Based on our observation of neural spikes in mouse N2A cell with our proposed imaging modality, we report that mouse neuroblastoma N2A cells can be an important model related to epileptic activity studies. It is concluded that the mouse neuroblastoma N2A cells produce the epileptic spikes in vitro in the same way as produced by the neurons or the astrocytes. This evidence advocates the increased and strong level of neurotransmitters release by enhancement in free calcium using the 4-aminopyridine which causes the mouse neuroblastoma N2A cells to produce the epileptic spikes and calcium oscillation.

Understanding curcumin-induced modulation of protein aggregation.

Science.gov (United States)

Ahmad, Basir; Borana, Mohanish S; Chaudhary, Ankur P

2017-07-01

Curcumin, a diarylheptanoid compound, found in spice turmeric is known to alter the aggregation of proteins and reduce the toxicity of the aggregates. This review looks at the molecular basis of modulating protein aggregation and toxicity of the aggregates. Foremost, we identify the interaction of curcumin and its derivatives with proteins/peptides and the effect of their interaction on the conformational stability and unfolding/folding pathway(s). The unfolding/folding processes generate partially folded/unfolded intermediate, which serve as aggregation precursor state. Secondly, we discuss the effect of curcumin binding on the kinetics parameters of the aggregation process, which give information about the mechanism of the aggregation inhibition. We describe, in addition, that curcumin can accelerate/promote fibril formation by binding to oligomeric intermediate(s) accumulated in the aggregation pathway. Finally, we discuss the correlation of curcumin-induced monomeric and/or oligomeric precursor states with aggregate structure and toxicity. On the basis of these discussions, we propose a model describing curcumin-induced inhibition/promotion of formation of amyloid-like fibrils. Copyright © 2016 Elsevier B.V. All rights reserved.

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

2018-05-03

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 power • Contributes 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.

Limitations of polyethylene glycol-induced precipitation as predictive tool for protein solubility during formulation development.

Science.gov (United States)

Hofmann, Melanie; Winzer, Matthias; Weber, Christian; Gieseler, Henning

2018-05-01

Polyethylene glycol (PEG)-induced protein precipitation is often used to extrapolate apparent protein solubility at specific formulation compositions. The procedure was used for several fields of application such as protein crystal growth but also protein formulation development. Nevertheless, most studies focused on applicability in protein crystal growth. In contrast, this study focuses on applicability of PEG-induced precipitation during high-concentration protein formulation development. In this study, solubility of three different model proteins was investigated over a broad range of pH. Solubility values predicted by PEG-induced precipitation were compared to real solubility behaviour determined by either turbidity or content measurements. Predicted solubility by PEG-induced precipitation was confirmed for an Fc fusion protein and a monoclonal antibody. In contrast, PEG-induced precipitation failed to predict solubility of a single-domain antibody construct. Applicability of PEG-induced precipitation as indicator of protein solubility during formulation development was found to be not valid for one of three model molecules. Under certain conditions, PEG-induced protein precipitation is not valid for prediction of real protein solubility behaviour. The procedure should be used carefully as tool for formulation development, and the results obtained should be validated by additional investigations. © 2017 Royal Pharmaceutical Society.

Spike-timing theory of working memory.

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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.

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

Dual roles for spike signaling in cortical neural populations

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Dana eBallard

2011-06-01

Full Text Available A prominent feature of signaling in cortical neurons is that of randomness in the action potential. The output of a typical pyramidal cell can be well fit with a Poisson model, and variations in the Poisson rate repeatedly have been shown to be correlated with stimuli. However while the rate provides a very useful characterization of neural spike data, it may not be the most fundamental description of the signaling code. Recent data showing γ frequency range multi-cell action potential correlations, together with spike timing dependent plasticity, are spurring a re-examination of the classical model, since precise timing codes imply that the generation of spikes is essentially deterministic. Could the observed Poisson randomness and timing determinism reflect two separate modes of communication, or do they somehow derive from a single process? We investigate in a timing-based model whether the apparent incompatibility between these probabilistic and deterministic observations may be resolved by examining how spikes could be used in the underlying neural circuits. The crucial component of this model draws on dual roles for spike signaling. In learning receptive fields from ensembles of inputs, spikes need to behave probabilistically, whereas for fast signaling of individual stimuli, the spikes need to behave deterministically. Our simulations show that this combination is possible if deterministic signals using γ latency coding are probabilistically routed through different members of a cortical cell population at different times. This model exhibits standard features characteristic of Poisson models such as orientation tuning post-stimulus histograms and exponential interval histograms. In addition it makes testable predictions that follow from the γ latency coding.

Heat Shock Protein 70 Neutralizes Apoptosis-Inducing Factor

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Guido Kroemer

2001-01-01

Full Text Available Programmed cell death (apoptosis is the physiological process responsible for the demise of superfluous, aged, damaged, mutated, and ectopic cells. Its normal function is essential both for embryonic development and for maintenance of adult tissue homeostasis. Deficient apoptosis participates in cancerogenesis, whereas excessive apoptosis leads to unwarranted cell loss accounting for disparate diseases including neurodegeneration and AIDS. One critical step in the process of apoptosis consists in the permeabilization of mitochondrial membranes, leading to the release of proteins which normally are secluded behind the outer mitochondrial membrane[1]. For example, cytochrome c, which is normally confined to the mitochondrial intermembrane space, is liberated from mitochondria and interacts with a cytosolic protein, Apaf-1, causing its oligomerization and constitution of the so-called apoptosome, a protein complex which activates a specific class of cysteine proteases, the caspases[2]. Another example concerns the so-called apoptosis-inducing factor (AIF, another mitochondrial intermembrane protein which can translocate to the nucleus where it induces chromatin condensation and DNA fragmentation[3].

Chimeric Feline Coronaviruses That Encode Type II Spike Protein on Type I Genetic Background Display Accelerated Viral Growth and Altered Receptor Usage▿

Science.gov (United States)

Tekes, Gergely; Hofmann-Lehmann, Regina; Bank-Wolf, Barbara; Maier, Reinhard; Thiel, Heinz-Jürgen; Thiel, Volker

2010-01-01

Persistent infection of domestic cats with feline coronaviruses (FCoVs) can lead to a highly lethal, immunopathological disease termed feline infectious peritonitis (FIP). Interestingly, there are two serotypes, type I and type II FCoVs, that can cause both persistent infection and FIP, even though their main determinant of host cell tropism, the spike (S) protein, is of different phylogeny and displays limited sequence identity. In cell culture, however, there are apparent differences. Type II FCoVs can be propagated to high titers by employing feline aminopeptidase N (fAPN) as a cellular receptor, whereas the propagation of type I FCoVs is usually difficult, and the involvement of fAPN as a receptor is controversial. In this study we have analyzed the phenotypes of recombinant FCoVs that are based on the genetic background of type I FCoV strain Black but encode the type II FCoV strain 79-1146 S protein. Our data demonstrate that recombinant FCoVs expressing a type II FCoV S protein acquire the ability to efficiently use fAPN for host cell entry and corroborate the notion that type I FCoVs use another main host cell receptor. We also observed that recombinant FCoVs display a large-plaque phenotype and, unexpectedly, accelerated growth kinetics indistinguishable from that of type II FCoV strain 79-1146. Thus, the main phenotypic differences for type I and type II FCoVs in cell culture, namely, the growth kinetics and the efficient usage of fAPN as a cellular receptor, can be attributed solely to the FCoV S protein. PMID:19906918

Measures of spike train synchrony for data with multiple time scales

NARCIS (Netherlands)

Satuvuori, Eero; Mulansky, Mario; Bozanic, Nebojsa; Malvestio, Irene; Zeldenrust, Fleur; Lenk, Kerstin; Kreuz, Thomas

2017-01-01

Background Measures of spike train synchrony are widely used in both experimental and computational neuroscience. Time-scale independent and parameter-free measures, such as the ISI-distance, the SPIKE-distance and SPIKE-synchronization, are preferable to time scale parametric measures, since by

A novel unsupervised spike sorting algorithm for intracranial EEG.

Science.gov (United States)

Yadav, R; Shah, A K; Loeb, J A; Swamy, M N S; Agarwal, R

2011-01-01

This paper presents a novel, unsupervised spike classification algorithm for intracranial EEG. The method combines template matching and principal component analysis (PCA) for building a dynamic patient-specific codebook without a priori knowledge of the spike waveforms. The problem of misclassification due to overlapping classes is resolved by identifying similar classes in the codebook using hierarchical clustering. Cluster quality is visually assessed by projecting inter- and intra-clusters onto a 3D plot. Intracranial EEG from 5 patients was utilized to optimize the algorithm. The resulting codebook retains 82.1% of the detected spikes in non-overlapping and disjoint clusters. Initial results suggest a definite role of this method for both rapid review and quantitation of interictal spikes that could enhance both clinical treatment and research studies on epileptic patients.

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

The Mechanisms of Repetitive Spike Generation in an Axonless Retinal Interneuron

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Mark S. Cembrowski

2012-02-01

Full Text Available Several types of retinal interneurons exhibit spikes but lack axons. One such neuron is the AII amacrine cell, in which spikes recorded at the soma exhibit small amplitudes (5 ms. Here, we used electrophysiological recordings and computational analysis to examine the mechanisms underlying this atypical spiking. We found that somatic spikes likely represent large, brief action potential-like events initiated in a single, electrotonically distal dendritic compartment. In this same compartment, spiking undergoes slow modulation, likely by an M-type K conductance. The structural correlate of this compartment is a thin neurite that extends from the primary dendritic tree: local application of TTX to this neurite, or excision of it, eliminates spiking. Thus, the physiology of the axonless AII is much more complex than would be anticipated from morphological descriptions and somatic recordings; in particular, the AII possesses a single dendritic structure that controls its firing pattern.

Clusterin: an IR-inducible protein determining life and death

Energy Technology Data Exchange (ETDEWEB)

DAVID A. BOOTHMAN, Ph.D.

2006-07-11

The roles of ionizing radiation (IR)-inducible genes/proteins are now being elucidated and the research team will focus on the functions of the clusterin (CLU) proteins after low dose IR exposures. With funding from the DOE, we discovered that x-ray-inducible transcript/protein #8 (xip8) bound to the Ku70 DNA double strand break repair protein using various molecular biology techniques. We showed that translation of the CLU/xip8 transcript was complicated, leading to two classes of proteins separated by their intracellular processing. One set of CLU proteins (a secreted and precursor protein, sCLU and psCLU, respectively) were induced by very low doses of IR (>2.0 cGy) and subsequently secreted from the cell. The functions of sCLU, particularly in bystander effects, are not known; sCLU does not bind Ku70, but can interact with the TGF-ß II receptor. Another intracellular class of CLU proteins was targeted to the cytoplasm and existed in a dormant precursor nuclear form (pnCLU). After higher IR doses (>1.0 Gy), pnCLU was activated via post-translational modification, and translocated to the nucleus, where nuclear CLU (nCLU) interacted with Ku70/Ku80, and signaled cell death. The mechanism(s) of how cells die following nCLU accumulation are unknown. Recent data from our lab indicate that CLU gene transcription is also complicated. Thus far, the data suggest that: (a) p53 is a negative regulator of CLU transcription, however, the mechanisms by which it exerts this negative pressure are not known; and (b) IR induces transcription of the CLU promoter, independent of p53, at regulatory elements that lie between -1403 and -325 bps 5'-from the TATAA box. In this renewal, the research team will investigate three separate, but interrelated hypotheses: (1) p53 negatively regulates the CLU promoter via distinct head to tail p53 half sites, and induction is mediated by the combination of retinoblatoma control elements (RCEs) and NF-∫B sites; (2) sCLU is cytoprotective

Clusterin: an IR-inducible protein determining life and death

International Nuclear Information System (INIS)

DAVID A. BOOTHMAN

2006-01-01

The roles of ionizing radiation (IR)-inducible genes/proteins are now being elucidated and the research team will focus on the functions of the clusterin (CLU) proteins after low dose IR exposures. With funding from the DOE, we discovered that x-ray-inducible transcript/protein No.8 (xip8) bound to the Ku70 DNA double strand break repair protein using various molecular biology techniques. We showed that translation of the CLU/xip8 transcript was complicated, leading to two classes of proteins separated by their intracellular processing. One set of CLU proteins (a secreted and precursor protein, sCLU and psCLU, respectively) were induced by very low doses of IR (>2.0 cGy) and subsequently secreted from the cell. The functions of sCLU, particularly in bystander effects, are not known; sCLU does not bind Ku70, but can interact with the TGF-? II receptor. Another intracellular class of CLU proteins was targeted to the cytoplasm and existed in a dormant precursor nuclear form (pnCLU). After higher IR doses (>1.0 Gy), pnCLU was activated via post-translational modification, and translocated to the nucleus, where nuclear CLU (nCLU) interacted with Ku70/Ku80, and signaled cell death. The mechanism(s) of how cells die following nCLU accumulation are unknown. Recent data from our lab indicate that CLU gene transcription is also complicated. Thus far, the data suggest that: (a) p53 is a negative regulator of CLU transcription, however, the mechanisms by which it exerts this negative pressure are not known; and (b) IR induces transcription of the CLU promoter, independent of p53, at regulatory elements that lie between -1403 and -325 bps 5'-from the TATAA box. In this renewal, the research team will investigate three separate, but interrelated hypotheses: (1) p53 negatively regulates the CLU promoter via distinct head to tail p53 half sites, and induction is mediated by the combination of retinoblatoma control elements (RCEs) and NF-?B sites; (2) sCLU is cytoprotective and

Building functional networks of spiking model neurons.

Science.gov (United States)

Abbott, L F; DePasquale, Brian; Memmesheimer, Raoul-Martin

2016-03-01

Most of the networks used by computer scientists and many of those studied by modelers in neuroscience represent unit activities as continuous variables. Neurons, however, communicate primarily through discontinuous spiking. We review methods for transferring our ability to construct interesting networks that perform relevant tasks from the artificial continuous domain to more realistic spiking network models. These methods raise a number of issues that warrant further theoretical and experimental study.

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.

Enzyme-induced aggregation of whey proteins with Bacillus licheniformis protease

NARCIS (Netherlands)

Creusot, N.P.

2006-01-01

Whey proteins are commonly used as ingredient in food. In relation with the gelation properties of whey proteins, this thesis deals with understanding the mechanism of peptide-induced aggregation of whey protein hydrolysates made with Bacillus licheniformis protease (BLP). The results show that BLP

Fast and Efficient Asynchronous Neural Computation with Adapting Spiking Neural Networks

NARCIS (Netherlands)

D. Zambrano (Davide); S.M. Bohte (Sander)

2016-01-01

textabstractBiological neurons communicate with a sparing exchange of pulses - spikes. It is an open question how real spiking neurons produce the kind of powerful neural computation that is possible with deep artificial neural networks, using only so very few spikes to communicate. Building on

Coincidence Detection Using Spiking Neurons with Application to Face Recognition

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Fadhlan Kamaruzaman

2015-01-01

Full Text Available We elucidate the practical implementation of Spiking Neural Network (SNN as local ensembles of classifiers. Synaptic time constant τs is used as learning parameter in representing the variations learned from a set of training data at classifier level. This classifier uses coincidence detection (CD strategy trained in supervised manner using a novel supervised learning method called τs Prediction which adjusts the precise timing of output spikes towards the desired spike timing through iterative adaptation of τs. This paper also discusses the approximation of spike timing in Spike Response Model (SRM for the purpose of coincidence detection. This process significantly speeds up the whole process of learning and classification. Performance evaluations with face datasets such as AR, FERET, JAFFE, and CK+ datasets show that the proposed method delivers better face classification performance than the network trained with Supervised Synaptic-Time Dependent Plasticity (STDP. We also found that the proposed method delivers better classification accuracy than k nearest neighbor, ensembles of kNN, and Support Vector Machines. Evaluation on several types of spike codings also reveals that latency coding delivers the best result for face classification as well as for classification of other multivariate datasets.

Adaptive coupling optimized spiking coherence and synchronization in Newman-Watts neuronal networks.

Science.gov (United States)

Gong, Yubing; Xu, Bo; Wu, Ya'nan

2013-09-01

In this paper, we have numerically studied the effect of adaptive coupling on the temporal coherence and synchronization of spiking activity in Newman-Watts Hodgkin-Huxley neuronal networks. It is found that random shortcuts can enhance the spiking synchronization more rapidly when the increment speed of adaptive coupling is increased and can optimize the temporal coherence of spikes only when the increment speed of adaptive coupling is appropriate. It is also found that adaptive coupling strength can enhance the synchronization of spikes and can optimize the temporal coherence of spikes when random shortcuts are appropriate. These results show that adaptive coupling has a big influence on random shortcuts related spiking activity and can enhance and optimize the temporal coherence and synchronization of spiking activity of the network. These findings can help better understand the roles of adaptive coupling for improving the information processing and transmission in neural systems.

Effect of fullerenol surface chemistry on nanoparticle binding-induced protein misfolding

Science.gov (United States)

Radic, Slaven; Nedumpully-Govindan, Praveen; Chen, Ran; Salonen, Emppu; Brown, Jared M.; Ke, Pu Chun; Ding, Feng

2014-06-01

Fullerene and its derivatives with different surface chemistry have great potential in biomedical applications. Accordingly, it is important to delineate the impact of these carbon-based nanoparticles on protein structure, dynamics, and subsequently function. Here, we focused on the effect of hydroxylation -- a common strategy for solubilizing and functionalizing fullerene -- on protein-nanoparticle interactions using a model protein, ubiquitin. We applied a set of complementary computational modeling methods, including docking and molecular dynamics simulations with both explicit and implicit solvent, to illustrate the impact of hydroxylated fullerenes on the structure and dynamics of ubiquitin. We found that all derivatives bound to the model protein. Specifically, the more hydrophilic nanoparticles with a higher number of hydroxyl groups bound to the surface of the protein via hydrogen bonds, which stabilized the protein without inducing large conformational changes in the protein structure. In contrast, fullerene derivatives with a smaller number of hydroxyl groups buried their hydrophobic surface inside the protein, thereby causing protein denaturation. Overall, our results revealed a distinct role of surface chemistry on nanoparticle-protein binding and binding-induced protein misfolding.Fullerene and its derivatives with different surface chemistry have great potential in biomedical applications. Accordingly, it is important to delineate the impact of these carbon-based nanoparticles on protein structure, dynamics, and subsequently function. Here, we focused on the effect of hydroxylation -- a common strategy for solubilizing and functionalizing fullerene -- on protein-nanoparticle interactions using a model protein, ubiquitin. We applied a set of complementary computational modeling methods, including docking and molecular dynamics simulations with both explicit and implicit solvent, to illustrate the impact of hydroxylated fullerenes on the structure and

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.

Prolactin-inducible proteins in human breast cancer cells

International Nuclear Information System (INIS)

Shiu, R.P.; Iwasiow, B.M.

1985-01-01

The mechanism of action of prolactin in target cells and the role of prolactin in human breast cancer are poorly understood phenomena. The present study examines the effect of human prolactin (hPRL) on the synthesis of unique proteins by a human breast cancer cell line, T-47D, in serum-free medium containing bovine serum albumin. [ 35 S]Methionine-labeled proteins were analysed by sodium dodecyl sulfate-polyacrylamide slab gel electrophoresis and fluorography. Treatment of cells with hPRL (1-1000 ng/ml) and hydrocortisone (1 microgram/ml) for 36 h or longer resulted in the synthesis and secretion of three proteins having molecular weights of 11,000, 14,000, and 16,000. Neither hPRL nor hydrocortisone alone induced these proteins. Of several other peptide hormones tested, only human growth hormone, a hormone structurally and functionally similar to hPRL, could replace hPRL in causing protein induction. These three proteins were, therefore, referred to as prolactin-inducible proteins (PIP). Each of the three PIPs was purified to homogeneity by preparative sodium dodecyl sulfate-polyacrylamide gel electrophoresis, and specific antibodies were generated to them in rabbits. By immunoprecipitation and immunoblotting (Western blot) of proteins secreted by T-47D cells, it was demonstrated that the three PIPs were immunologically identical to one another. In addition, the 16-kDa and 14-kDa proteins (PIP-16 and PIP-14), and not the 11-kDa protein (PIP-11), incorporated [ 3 H]glycosamine. Furthermore, 2-deoxyglucose (2 mM) and tunicamycin (0.5 micrograms/ml), two compounds known to inhibit glycosylation, blocked the production of PIP-16 and PIP-14, with a concomitant increase in the accumulation of PIP-11

Spike sorting based upon machine learning algorithms (SOMA).

Science.gov (United States)

Horton, P M; Nicol, A U; Kendrick, K M; Feng, J F

2007-02-15

We have developed a spike sorting method, using a combination of various machine learning algorithms, to analyse electrophysiological data and automatically determine the number of sampled neurons from an individual electrode, and discriminate their activities. We discuss extensions to a standard unsupervised learning algorithm (Kohonen), as using a simple application of this technique would only identify a known number of clusters. Our extra techniques automatically identify the number of clusters within the dataset, and their sizes, thereby reducing the chance of misclassification. We also discuss a new pre-processing technique, which transforms the data into a higher dimensional feature space revealing separable clusters. Using principal component analysis (PCA) alone may not achieve this. Our new approach appends the features acquired using PCA with features describing the geometric shapes that constitute a spike waveform. To validate our new spike sorting approach, we have applied it to multi-electrode array datasets acquired from the rat olfactory bulb, and from the sheep infero-temporal cortex, and using simulated data. The SOMA sofware is available at http://www.sussex.ac.uk/Users/pmh20/spikes.

A model-based spike sorting algorithm for removing correlation artifacts in multi-neuron recordings.

Science.gov (United States)

Pillow, Jonathan W; Shlens, Jonathon; Chichilnisky, E J; Simoncelli, Eero P

2013-01-01

We examine the problem of estimating the spike trains of multiple neurons from voltage traces recorded on one or more extracellular electrodes. Traditional spike-sorting methods rely on thresholding or clustering of recorded signals to identify spikes. While these methods can detect a large fraction of the spikes from a recording, they generally fail to identify synchronous or near-synchronous spikes: cases in which multiple spikes overlap. Here we investigate the geometry of failures in traditional sorting algorithms, and document the prevalence of such errors in multi-electrode recordings from primate retina. We then develop a method for multi-neuron spike sorting using a model that explicitly accounts for the superposition of spike waveforms. We model the recorded voltage traces as a linear combination of spike waveforms plus a stochastic background component of correlated Gaussian noise. Combining this measurement model with a Bernoulli prior over binary spike trains yields a posterior distribution for spikes given the recorded data. We introduce a greedy algorithm to maximize this posterior that we call "binary pursuit". The algorithm allows modest variability in spike waveforms and recovers spike times with higher precision than the voltage sampling rate. This method substantially corrects cross-correlation artifacts that arise with conventional methods, and substantially outperforms clustering methods on both real and simulated data. Finally, we develop diagnostic tools that can be used to assess errors in spike sorting in the absence of ground truth.

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.

Development of new iraqi wheat varieties induced by gamma rays

International Nuclear Information System (INIS)

Ibrahim, I.F.; Al-Janabi, K.K.; Al-Maaroof, E.M.; Al-Aubaidi, M.O.; Mahmoud, A.H.; Al-Janabi, A.A.

1991-01-01

The aim of the present investigation is to study agronomic traits of three wheat mutants induced by gamma rays and compared with their origin 'Saber Beg' during M 8 - M 11 generations. These mutants showed a moderate resistance to leaf rust and lodging, while the origin was susceptible. Also, these mutants surpassed their origin in seed weight of 100 spikes, weight of 1000 kernels and protein yield per unit area. Chemical and physical analyses of mutant flours indicated that it could be used for bread making successfully.2 fig.,4 tab

Two endogenous proteins that induce cell wall extension in plants

Science.gov (United States)

McQueen-Mason, S.; Durachko, D. M.; Cosgrove, D. J.

1992-01-01

Plant cell enlargement is regulated by wall relaxation and yielding, which is thought to be catalyzed by elusive "wall-loosening" enzymes. By employing a reconstitution approach, we found that a crude protein extract from the cell walls of growing cucumber seedlings possessed the ability to induce the extension of isolated cell walls. This activity was restricted to the growing region of the stem and could induce the extension of isolated cell walls from various dicot stems and the leaves of amaryllidaceous monocots, but was less effective on grass coleoptile walls. Endogenous and reconstituted wall extension activities showed similar sensitivities to pH, metal ions, thiol reducing agents, proteases, and boiling in methanol or water. Sequential HPLC fractionation of the active wall extract revealed two proteins with molecular masses of 29 and 30 kD associated with the activity. Each protein, by itself, could induce wall extension without detectable hydrolytic breakdown of the wall. These proteins appear to mediate "acid growth" responses of isolated walls and may catalyze plant cell wall extension by a novel biochemical mechanism.

Amino acid substitutions within the heptad repeat domain 1 of murine coronavirus spike protein restrict viral antigen spread in the central nervous system

International Nuclear Information System (INIS)

Tsai, Jean C.; Groot, Linda de; Pinon, Josefina D.; Iacono, Kathryn T.; Phillips, Joanna J.; Seo, Suhun; Lavi, Ehud; Weiss, Susan R.

2003-01-01

Targeted recombination was carried out to select mouse hepatitis viruses (MHVs) in a defined genetic background, containing an MHV-JHM spike gene encoding either three heptad repeat 1 (HR1) substitutions (Q1067H, Q1094H, and L1114R) or L1114R alone. The recombinant virus, which expresses spike with the three substitutions, was nonfusogenic at neutral pH. Its replication was significantly inhibited by lysosomotropic agents, and it was highly neuroattenuated in vivo. In contrast, the recombinant expressing spike with L1114R alone mediated cell-to-cell fusion at neutral pH and replicated efficiently despite the presence of lysosomotropic agents; however, it still caused only subclinical morbidity and no mortality in animals. Thus, both recombinant viruses were highly attenuated and expressed viral antigen which was restricted to the olfactory bulbs and was markedly absent from other regions of the brains at 5 days postinfection. These data demonstrate that amino acid substitutions, in particular L1114R, within HR1 of the JHM spike reduced the ability of MHV to spread in the central nervous system. Furthermore, the requirements for low pH for fusion and viral entry are not prerequisites for the highly attenuated phenotype

Conditionally controlling nuclear trafficking in yeast by chemical-induced protein dimerization.

Science.gov (United States)

Xu, Tao; Johnson, Cole A; Gestwicki, Jason E; Kumar, Anuj

2010-11-01

We present here a protocol to conditionally control the nuclear trafficking of target proteins in yeast. In this system, rapamycin is used to heterodimerize two chimeric proteins. One chimera consists of a FK506-binding protein (FKBP12) fused to a cellular 'address' (nuclear localization signal or nuclear export sequence). The second chimera consists of a target protein fused to a fluorescent protein and the FKBP12-rapamycin-binding (FRB) domain from FKBP-12-rapamycin associated protein 1 (FRAP1, also known as mTor). Rapamycin induces dimerization of the FKBP12- and FRB-containing chimeras; these interactions selectively place the target protein under control of the cell address, thereby directing the protein into or out of the nucleus. By chemical-induced dimerization, protein mislocalization is reversible and enables the identification of conditional loss-of-function and gain-of-function phenotypes, in contrast to other systems that require permanent modification of the targeted protein. Yeast strains for this analysis can be constructed in 1 week, and the technique allows protein mislocalization within 15 min after drug treatment.

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.

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.

A titanium surface with nano-ordered spikes and pores enhances human dermal fibroblastic extracellular matrix production and integration of collagen fibers

International Nuclear Information System (INIS)

Yamada, Masahiro; Kato, Eiji; Sakurai, Kaoru; Yamamoto, Akiko

2016-01-01

The acquisition of substantial dermal sealing determines the prognosis of percutaneous titanium-based medical devices or prostheses. A nano-topographic titanium surface with ordered nano-spikes and pores has been shown to induce periodontal-like connective tissue attachment and activate gingival fibroblastic functions. This in vitro study aimed to determine whether an alkali-heat (AH) treatment-created nano-topographic titanium surface could enhance human dermal fibroblastic functions and binding strength to the deposited collagen on the titanium surface. The surface topographies of commercially pure titanium machined discs exposed to two different AH treatments were evaluated. Human dermal fibroblastic cultures grown on the discs were evaluated in terms of cellular morphology, proliferation, extracellular matrix (ECM) and proinflammatory cytokine synthesis, and physicochemical binding strength of surface-deposited collagen. An isotropically-patterned, shaggy nano-topography with a sponge-like inner network and numerous well-organized, anisotropically-patterned fine nano-spikes and pores were observed on each nano-topographic surface type via scanning electron microscopy. In contrast to the typical spindle-shaped cells on the machined surfaces, the isotropically- and anisotropically-patterned nano-topographic titanium surfaces had small circular/angular cells containing contractile ring-like structures and elongated, multi-shaped cells with a developed cytoskeletal network and multiple filopodia and lamellipodia, respectively. These nano-topographic surfaces enhanced dermal-related ECM synthesis at both the protein and gene levels, without proinflammatory cytokine synthesis or reduced proliferative activity. Deposited collagen fibers were included in these surfaces and sufficiently bound to the nano-topographies to resist the physical, enzymatic and chemical detachment treatments, in contrast to machined surfaces. Well-organized, isotropically

Prion protein inhibits microtubule assembly by inducing tubulin oligomerization

International Nuclear Information System (INIS)

Nieznanski, Krzysztof; Podlubnaya, Zoya A.; Nieznanska, Hanna

2006-01-01

A growing body of evidence points to an association of prion protein (PrP) with microtubular cytoskeleton. Recently, direct binding of PrP to tubulin has also been found. In this work, using standard light scattering measurements, sedimentation experiments, and electron microscopy, we show for First time the effect of a direct interaction between these proteins on tubulin polymerization. We demonstrate that full-length recombinant PrP induces a rapid increase in the turbidity of tubulin diluted below the critical concentration for microtubule assembly. This effect requires magnesium ions and is weakened by NaCl. Moreover, the PrP-induced light scattering structures of tubulin are cold-stable. In preparations of diluted tubulin incubated with PrP, electron microscopy revealed the presence of ∼50 nm disc-shaped structures not reported so far. These unique tubulin oligomers may form large aggregates. The effect of PrP is more pronounced under the conditions promoting microtubule formation. In these tubulin samples, PrP induces formation of the above oligomers associated with short protofilaments and sheets of protofilaments into aggregates. Noticeably, this is accompanied by a significant reduction of the number and length of microtubules. Hence, we postulate that prion protein may act as an inhibitor of microtubule assembly by inducing formation of stable tubulin oligomers

Correlations decrease with propagation of spiking activity in the mouse barrel cortex

Directory of Open Access Journals (Sweden)

Gayathri Nattar Ranganathan

2011-05-01

Full Text Available Propagation of suprathreshold spiking activity through neuronal populations is important for the function of the central nervous system. Neural correlations have an impact on cortical function particularly on the signaling of information and propagation of spiking activity. Therefore we measured the change in correlations as suprathreshold spiking activity propagated between recurrent neuronal networks of the mammalian cerebral cortex. Using optical methods we recorded spiking activity from large samples of neurons from two neural populations simultaneously. The results indicate that correlations decreased as spiking activity propagated from layer 4 to layer 2/3 in the rodent barrel cortex.

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.

Memory-induced resonancelike suppression of spike generation in a resonate-and-fire neuron model

Science.gov (United States)

Mankin, Romi; Paekivi, Sander

2018-01-01

The behavior of a stochastic resonate-and-fire neuron model based on a reduction of a fractional noise-driven generalized Langevin equation (GLE) with a power-law memory kernel is considered. The effect of temporally correlated random activity of synaptic inputs, which arise from other neurons forming local and distant networks, is modeled as an additive fractional Gaussian noise in the GLE. Using a first-passage-time formulation, in certain system parameter domains exact expressions for the output interspike interval (ISI) density and for the survival probability (the probability that a spike is not generated) are derived and their dependence on input parameters, especially on the memory exponent, is analyzed. In the case of external white noise, it is shown that at intermediate values of the memory exponent the survival probability is significantly enhanced in comparison with the cases of strong and weak memory, which causes a resonancelike suppression of the probability of spike generation as a function of the memory exponent. Moreover, an examination of the dependence of multimodality in the ISI distribution on input parameters shows that there exists a critical memory exponent αc≈0.402 , which marks a dynamical transition in the behavior of the system. That phenomenon is illustrated by a phase diagram describing the emergence of three qualitatively different structures of the ISI distribution. Similarities and differences between the behavior of the model at internal and external noises are also discussed.

The Nature of Power Spikes: a regime-switch approach

NARCIS (Netherlands)

C.M. de Jong (Cyriel)

2005-01-01

textabstractDue to its non-storable nature, electricity is a commodity with probably the most volatile spot prices, exemplified by occasional spikes. Appropriate pricing, portfolio, and risk management models have to incorporate these characteristics, and the spikes in particular. We investigate the

Dopamine D4 receptor activation increases hippocampal gamma oscillations by enhancing synchronization of fast-spiking interneurons.

Directory of Open Access Journals (Sweden)

Richard Andersson

Full Text Available BACKGROUND: Gamma oscillations are electric activity patterns of the mammalian brain hypothesized to serve attention, sensory perception, working memory and memory encoding. They are disrupted or altered in schizophrenic patients with associated cognitive deficits, which persist in spite of treatment with antipsychotics. Because cognitive symptoms are a core feature of schizophrenia it is relevant to explore signaling pathways that potentially regulate gamma oscillations. Dopamine has been reported to decrease gamma oscillation power via D1-like receptors. Based on the expression pattern of D4 receptors (D4R in hippocampus, and pharmacological effects of D4R ligands in animals, we hypothesize that they are in a position to regulate gamma oscillations as well. METHODOLOGY/PRINCIPAL FINDINGS: To address this hypothesis we use rat hippocampal slices and kainate-induced gamma oscillations. Local field potential recordings as well as intracellular recordings of pyramidal cells, fast-spiking and non-fast-spiking interneurons were carried out. We show that D4R activation with the selective ligand PD168077 increases gamma oscillation power, which can be blocked by the D4R-specific antagonist L745,870 as well as by the antipsychotic drug Clozapine. Pyramidal cells did not exhibit changes in excitatory or inhibitory synaptic current amplitudes, but inhibitory currents became more coherent with the oscillations after application of PD168077. Fast-spiking, but not non-fast spiking, interneurons, increase their action potential phase-coupling and coherence with regard to ongoing gamma oscillations in response to D4R activation. Among several possible mechanisms we found that the NMDA receptor antagonist AP5 also blocks the D4R mediated increase in gamma oscillation power. CONCLUSIONS/SIGNIFICANCE: We conclude that D4R activation affects fast-spiking interneuron synchronization and thereby increases gamma power by an NMDA receptor-dependent mechanism. This

Transcriptome Analysis for Abnormal Spike Development of the Wheat Mutant dms.

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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.

Cytoplasmic tail of Coronavirus spike protein has intracellular ...

Indian Academy of Sciences (India)

58

1Department of Biological Sciences, Indian Institute of Science Education and ... Introduction .... A major effort is underway to understand the interplay of .... For protein analysis, cells were plated on 100 mm tissue culture dishes and transfected.

Axonal propagation of simple and complex spikes in cerebellar Purkinje neurons.

Science.gov (United States)

Khaliq, Zayd M; Raman, Indira M

2005-01-12

In cerebellar Purkinje neurons, the reliability of propagation of high-frequency simple spikes and spikelets of complex spikes is likely to regulate inhibition of Purkinje target neurons. To test the extent to which a one-to-one correspondence exists between somatic and axonal spikes, we made dual somatic and axonal recordings from Purkinje neurons in mouse cerebellar slices. Somatic action potentials were recorded with a whole-cell pipette, and the corresponding axonal signals were recorded extracellularly with a loose-patch pipette. Propagation of spontaneous and evoked simple spikes was highly reliable. At somatic firing rates of approximately 200 spikes/sec, 375 Hz during somatic hyperpolarizations that silenced spontaneous firing to approximately 150 Hz during spontaneous activity. The probability of propagation of individual spikelets could be described quantitatively as a saturating function of spikelet amplitude, rate of rise, or preceding interspike interval. The results suggest that ion channels of Purkinje axons are adapted to produce extremely short refractory periods and that brief bursts of forward-propagating action potentials generated by complex spikes may contribute transiently to inhibition of postsynaptic neurons.

Hg stable isotope analysis by the double-spike method.

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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.

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.

Regulation of spike timing-dependent plasticity of olfactory inputs in mitral cells in the rat olfactory bulb.

Directory of Open Access Journals (Sweden)

Teng-Fei Ma

Full Text Available The recent history of activity input onto granule cells (GCs in the main olfactory bulb can affect the strength of lateral inhibition, which functions to generate contrast enhancement. However, at the plasticity level, it is unknown whether and how the prior modification of lateral inhibition modulates the subsequent induction of long-lasting changes of the excitatory olfactory nerve (ON inputs to mitral cells (MCs. Here we found that the repetitive stimulation of two distinct excitatory inputs to the GCs induced a persistent modification of lateral inhibition in MCs in opposing directions. This bidirectional modification of inhibitory inputs differentially regulated the subsequent synaptic plasticity of the excitatory ON inputs to the MCs, which was induced by the repetitive pairing of excitatory postsynaptic potentials (EPSPs with postsynaptic bursts. The regulation of spike timing-dependent plasticity (STDP was achieved by the regulation of the inter-spike-interval (ISI of the postsynaptic bursts. This novel form of inhibition-dependent regulation of plasticity may contribute to the encoding or processing of olfactory information in the olfactory bulb.

Accelerated spike resampling for accurate multiple testing controls.

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Harrison, Matthew T

2013-02-01

Controlling for multiple hypothesis tests using standard spike resampling techniques often requires prohibitive amounts of computation. Importance sampling techniques can be used to accelerate the computation. The general theory is presented, along with specific examples for testing differences across conditions using permutation tests and for testing pairwise synchrony and precise lagged-correlation between many simultaneously recorded spike trains using interval jitter.

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

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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.

The thermal-spike model description of the ion-irradiated polyimide

International Nuclear Information System (INIS)

Sun Youmei; Zhang Chonghong; Zhu Zhiyong; Wang Zhiguang; Jin Yunfan; Liu Jie; Wang Ying

2004-01-01

To describe the role of electronic energy loss (dE/dX) e for chemical modification of polyimide (PI), multi-layer stacks (corresponding to different dE/dX) were irradiated by different swift heavy ions (1.158 GeV Fe 56 and 1.755 GeV Xe 136 ) under vacuum and at room temperature. Chemical changes of modified PI films were studied by Fourier transform infrared (FTIR) spectroscopy. The chain disruption rate of PI was investigated in the fluence range from 1 x 10 11 to 6 x 10 12 ions/cm 2 and a wider energy stopping power range (2.2-5.1 keV/nm for Fe 56 ions and 8.6-11.5 keV/nm for Xe 136 ions). Alkyne formation was observed over the electronic energy loss range of interest. By applying the saturated track model assumption (the damage process only occur in a cylinder of area σ), the mean degradation and alkyne formation radii in tracks were induced for Fe and Xe ion irradiation, respectively. The results were validated by the thermal-spike model. The analysis of the irradiated PI films shows that the predictions of the thermal-spike model of Szenes are in qualitative agreement with the curve shape of experimental results

Real-time computing platform for spiking neurons (RT-spike).

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Ros, Eduardo; Ortigosa, Eva M; Agís, Rodrigo; Carrillo, Richard; Arnold, Michael

2006-07-01

A computing platform is described for simulating arbitrary networks of spiking neurons in real time. A hybrid computing scheme is adopted that uses both software and hardware components to manage the tradeoff between flexibility and computational power; the neuron model is implemented in hardware and the network model and the learning are implemented in software. The incremental transition of the software components into hardware is supported. We focus on a spike response model (SRM) for a neuron where the synapses are modeled as input-driven conductances. The temporal dynamics of the synaptic integration process are modeled with a synaptic time constant that results in a gradual injection of charge. This type of model is computationally expensive and is not easily amenable to existing software-based event-driven approaches. As an alternative we have designed an efficient time-based computing architecture in hardware, where the different stages of the neuron model are processed in parallel. Further improvements occur by computing multiple neurons in parallel using multiple processing units. This design is tested using reconfigurable hardware and its scalability and performance evaluated. Our overall goal is to investigate biologically realistic models for the real-time control of robots operating within closed action-perception loops, and so we evaluate the performance of the system on simulating a model of the cerebellum where the emulation of the temporal dynamics of the synaptic integration process is important.

Delayed brain ischemia tolerance induced by electroacupuncture pretreatment is mediated via MCP-induced protein 1

Science.gov (United States)

2013-01-01

Background Emerging studies have demonstrated that pretreatment with electroacupuncture (EA) induces significant tolerance to focal cerebral ischemia. The present study seeks to determine the involvement of monocyte chemotactic protein-induced protein 1 (MCPIP1), a recently identified novel modulator of inflammatory reactions, in the cerebral neuroprotection conferred by EA pretreatment in the animal model of focal cerebral ischemia and to elucidate the mechanisms of EA pretreatment-induced ischemic brain tolerance. Methods Twenty-four hours after the end of the last EA pretreatment, focal cerebral ischemia was induced by middle cerebral artery occlusion (MCAO) for 90 minutes in male C57BL/6 mice and MCPIP1 knockout mice. Transcription and expression of MCPIP1 gene was monitored by qRT-PCR, Western blot and immunohistochemistry. The neurobehavioral scores, infarction volumes, proinflammatory cytokines and leukocyte infiltration in brain and NF-κB signaling were evaluated after ischemia/reperfusion. Results MCPIP1 protein and mRNA levels significantly increased specifically in mouse brain undergoing EA pretreatment. EA pretreatment significantly attenuated the infarct volume, neurological deficits, upregulation of proinflammatory cytokines and leukocyte infiltration in the brain of wild-type mice after MCAO compared with that of the non-EA group. MCPIP1-deficient mice failed to evoke EA pretreatment-induced tolerance compared with that of the control MCPIP1 knockout group without EA treatment. Furthermore, the activation of NF-κB signaling was significantly reduced in EA-pretreated wild-type mice after MCAO compared to that of the non-EA control group and MCPIP1-deficient mice failed to confer the EA pretreatment-induced inhibition of NF-κB signaling after MCAO. Conclusions Our data demonstrated that MCPIP1 deficiency caused significant lack of EA pretreatment-induced cerebral protective effects after MCAO compared with the control group and that MCPIP1 is

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...

Involvement of MAPK proteins in bystander effects induced by chemicals and ionizing radiation

International Nuclear Information System (INIS)

Asur, Rajalakshmi; Balasubramaniam, Mamtha; Marples, Brian; Thomas, Robert A.; Tucker, James D.

2010-01-01

Many studies have examined bystander effects induced by ionizing radiation, however few have evaluated the ability of chemicals to induce similar effects. We previously reported the ability of two chemicals, mitomycin C (MMC) and phleomycin (PHL) to induce bystander effects in normal human lymphoblastoid cell lines. The focus of the current study was to determine the involvement of the MAPK proteins in bystander effects induced by physical and chemical DNA damaging agents and to evaluate the effects of MAPK inhibition on bystander-induced caspase 3/7 activation. The phosphorylation levels of the MAPK proteins ERK1/2, JNK, and p38, were measured from 1 to 24 h following direct or bystander exposure to MMC, PHL or radiation. We observed transient phosphorylation, at early time points, of all 3 proteins in bystander cells. We also evaluated the effect of MAPK inhibition on bystander-induced caspase 3/7 activity to determine the role of MAPK proteins in bystander-induced apoptosis. We observed bystander-induced activation of caspase 3/7 in bystander cells. Inhibition of MAPK proteins resulted in a decrease in caspase 3/7 activity at the early time points, and the caspase activity increased (in the case of ERK inhibition) or returned to basal levels (in the case of JNK or p38 inhibition) between 12 and 24 h. PHL is considered to be a radiomimetic agent, however in the present study PHL behaved more like a chemical and not like radiation in terms of MAPK phosphorylation. These results point to the involvement of MAPK proteins in the bystander effect induced by radiation and chemicals and provide additional evidence that this response is not limited to radiation but is a generalized stress response in cells.

Robust spike sorting of retinal ganglion cells tuned to spot stimuli.

Science.gov (United States)

Ghahari, Alireza; Badea, Tudor C

2016-08-01

We propose an automatic spike sorting approach for the data recorded from a microelectrode array during visual stimulation of wild type retinas with tiled spot stimuli. The approach first detects individual spikes per electrode by their signature local minima. With the mixture probability distribution of the local minima estimated afterwards, it applies a minimum-squared-error clustering algorithm to sort the spikes into different clusters. A template waveform for each cluster per electrode is defined, and a number of reliability tests are performed on it and its corresponding spikes. Finally, a divisive hierarchical clustering algorithm is used to deal with the correlated templates per cluster type across all the electrodes. According to the measures of performance of the spike sorting approach, it is robust even in the cases of recordings with low signal-to-noise ratio.

The transfer function of neuron spike.

Science.gov (United States)

Palmieri, Igor; Monteiro, Luiz H A; Miranda, Maria D

2015-08-01

The mathematical modeling of neuronal signals is a relevant problem in neuroscience. The complexity of the neuron behavior, however, makes this problem a particularly difficult task. Here, we propose a discrete-time linear time-invariant (LTI) model with a rational function in order to represent the neuronal spike detected by an electrode located in the surroundings of the nerve cell. The model is presented as a cascade association of two subsystems: one that generates an action potential from an input stimulus, and one that represents the medium between the cell and the electrode. The suggested approach employs system identification and signal processing concepts, and is dissociated from any considerations about the biophysical processes of the neuronal cell, providing a low-complexity alternative to model the neuronal spike. The model is validated by using in vivo experimental readings of intracellular and extracellular signals. A computational simulation of the model is presented in order to assess its proximity to the neuronal signal and to observe the variability of the estimated parameters. The implications of the results are discussed in the context of spike sorting. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

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)

Trace element ink spiking for signature authentication

International Nuclear Information System (INIS)

Hatzistavros, V.S.; Kallithrakas-Kontos, N.G.

2008-01-01

Signature authentication is a critical question in forensic document examination. Last years the evolution of personal computers made signature copying a quite easy task, so the development of new ways for signature authentication is crucial. In the present work a commercial ink was spiked with many trace elements in various concentrations. Inorganic and organometallic ink soluble compounds were used as spiking agents, whilst ink retained its initial properties. The spiked inks were used for paper writing and the documents were analyzed by a non destructive method, the energy dispersive X-ray fluorescence. The thin target model was proved right for quantitative analysis and a very good linear relationship of the intensity (X-ray signal) against concentration was estimated for all used elements. Intensity ratios between different elements in the same ink gave very stable results, independent on the writing alterations. The impact of time both to written document and prepared inks was also investigated. (author)

A Novel and Simple Spike Sorting Implementation.

Science.gov (United States)

Petrantonakis, Panagiotis C; Poirazi, Panayiota

2017-04-01

Monitoring the activity of multiple, individual neurons that fire spikes in the vicinity of an electrode, namely perform a Spike Sorting (SS) procedure, comprises one of the most important tools for contemporary neuroscience in order to reverse-engineer the brain. As recording electrodes' technology rabidly evolves by integrating thousands of electrodes in a confined spatial setting, the algorithms that are used to monitor individual neurons from recorded signals have to become even more reliable and computationally efficient. In this work, we propose a novel framework of the SS approach in which a single-step processing of the raw (unfiltered) extracellular signal is sufficient for both the detection and sorting of the activity of individual neurons. Despite its simplicity, the proposed approach exhibits comparable performance with state-of-the-art approaches, especially for spike detection in noisy signals, and paves the way for a new family of SS algorithms with the potential for multi-recording, fast, on-chip implementations.

A Fully Automated Approach to Spike Sorting.

Science.gov (United States)

Chung, Jason E; Magland, Jeremy F; Barnett, Alex H; Tolosa, Vanessa M; Tooker, Angela C; Lee, Kye Y; Shah, Kedar G; Felix, Sarah H; Frank, Loren M; Greengard, Leslie F

2017-09-13

Understanding the detailed dynamics of neuronal networks will require the simultaneous measurement of spike trains from hundreds of neurons (or more). Currently, approaches to extracting spike times and labels from raw data are time consuming, lack standardization, and involve manual intervention, making it difficult to maintain data provenance and assess the quality of scientific results. Here, we describe an automated clustering approach and associated software package that addresses these problems and provides novel cluster quality metrics. We show that our approach has accuracy comparable to or exceeding that achieved using manual or semi-manual techniques with desktop central processing unit (CPU) runtimes faster than acquisition time for up to hundreds of electrodes. Moreover, a single choice of parameters in the algorithm is effective for a variety of electrode geometries and across multiple brain regions. This algorithm has the potential to enable reproducible and automated spike sorting of larger scale recordings than is currently possible. Copyright © 2017 Elsevier Inc. All rights reserved.

A case-control study of wicket spikes using video-EEG monitoring.

Science.gov (United States)

Vallabhaneni, Maya; Baldassari, Laura E; Scribner, James T; Cho, Yong Won; Motamedi, Gholam K

2013-01-01

To investigate clinical characteristics associated with wicket spikes in patients undergoing long-term video-EEG monitoring. A case-control study was performed in 479 patients undergoing video-EEG monitoring, with 3 age- (±3 years) and gender-matched controls per patient with wicket spikes. Logistic regression was utilized to investigate the association between wicket spikes and other factors, including conditions that have been previously associated with wicket spikes. Wicket spikes were recorded in 48 patients. There was a significantly higher prevalence of dizziness/vertigo (p=0.002), headaches (p=0.005), migraine (p=0.015), and seizures (p=0.016) in patients with wickets. The majority of patients with wicket spikes did not exhibit epileptiform activity on EEG; however, patients with history of seizures were more likely to have wickets (p=0.017). There was no significant difference in the prevalence of psychogenic non-epileptic seizures between the groups. Wickets were more common on the left, during sleep, and more likely to be first recorded on day 1-2 of monitoring. Patients with wicket spikes are more likely to have dizziness/vertigo, headaches, migraine, and seizures. Patients with history of seizures are more likely to have wickets. The prevalence of psychogenic non-epileptic seizures is not significantly higher in patients with wickets. Copyright © 2012 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

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

Glycan shield and fusion activation of a deltacoronavirus spike glycoprotein fine-tuned for enteric infections.

Science.gov (United States)

Xiong, Xiaoli; Tortorici, M Alejandra; Snijder, Joost; Yoshioka, Craig; Walls, Alexandra C; Li, Wentao; McGuire, Andrew T; Rey, Félix A; Bosch, Berend-Jan; Veesler, David

2017-11-01

Coronaviruses recently emerged as major human pathogens causing outbreaks of severe acute respiratory syndrome and Middle-East respiratory syndrome. They utilize the spike (S) glycoprotein anchored in the viral envelope to mediate host attachment and fusion of the viral and cellular membranes to initiate infection. The S protein is a major determinant of the zoonotic potential of coronaviruses and is also the main target of the host humoral immune response. We report here the 3.5 Å resolution cryo-electron microscopy structure of the S glycoprotein trimer from the pathogenic porcine deltacoronavirus (PDCoV), which belongs to the recently identified delta genus. Structural and glycoproteomics data indicate that the glycans of PDCoV S are topologically conserved when compared with the human respiratory coronavirus HCoV-NL63 S, resulting in similar surface areas being shielded from neutralizing antibodies and implying that both viruses are under comparable immune pressure in their respective hosts. The structure further reveals a shortened S 2 ' activation loop, containing a reduced number of basic amino acids, which participates to rendering the spike largely protease-resistant. This property distinguishes PDCoV S from recently characterized betacoronavirus S proteins and suggests that the S protein of enterotropic PDCoV has evolved to tolerate the protease-rich environment of the small intestine and to fine-tune its fusion activation to avoid premature triggering and reduction of infectivity. IMPORTANCE Coronaviruses use transmembrane spike (S) glycoprotein trimers to promote host attachment and fusion of the viral and cellular membranes. We determined a near-atomic resolution cryo-electron microscopy structure of the S ectodomain trimer from the pathogenic porcine deltacoronavirus (PDCoV), which is responsible for diarrhea in piglets and has had devastating consequences for the swine industry worldwide. Structural and glycoproteomics data reveal that PDCoV S is

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.

Peptides corresponding to the predicted heptad repeat 2 domain of the feline coronavirus spike protein are potent inhibitors of viral infection.

Directory of Open Access Journals (Sweden)

I-Jung Liu

Full Text Available BACKGROUND: Feline infectious peritonitis (FIP is a lethal immune-mediated disease caused by feline coronavirus (FCoV. Currently, no therapy with proven efficacy is available. In searching for agents that may prove clinically effective against FCoV infection, five analogous overlapping peptides were designed and synthesized based on the putative heptad repeat 2 (HR2 sequence of the spike protein of FCoV, and the antiviral efficacy was evaluated. METHODS: Plaque reduction assay and MTT (3-(4,5-dimethylthiazol-2-yl-2,5-diphenyltetrazolium bromide cytotoxicity assay were performed in this study. Peptides were selected using a plaque reduction assay to inhibit Feline coronavirus infection. RESULTS: The results demonstrated that peptide (FP5 at concentrations below 20 μM inhibited viral replication by up to 97%. The peptide (FP5 exhibiting the most effective antiviral effect was further combined with a known anti-viral agent, human interferon-α (IFN-α, and a significant synergistic antiviral effect was observed. CONCLUSION: Our data suggest that the synthetic peptide FP5 could serve as a valuable addition to the current FIP prevention methods.

Predicting Spike Occurrence and Neuronal Responsiveness from LFPs in Primary Somatosensory Cortex

Science.gov (United States)

Storchi, Riccardo; Zippo, Antonio G.; Caramenti, Gian Carlo; Valente, Maurizio; Biella, Gabriele E. M.

2012-01-01

Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role. PMID:22586452

An Efficient Supervised Training Algorithm for Multilayer Spiking Neural Networks.

Science.gov (United States)

Xie, Xiurui; Qu, Hong; Liu, Guisong; Zhang, Malu; Kurths, Jürgen

2016-01-01

The spiking neural networks (SNNs) are the third generation of neural networks and perform remarkably well in cognitive tasks such as pattern recognition. The spike emitting and information processing mechanisms found in biological cognitive systems motivate the application of the hierarchical structure and temporal encoding mechanism in spiking neural networks, which have exhibited strong computational capability. However, the hierarchical structure and temporal encoding approach require neurons to process information serially in space and time respectively, which reduce the training efficiency significantly. For training the hierarchical SNNs, most existing methods are based on the traditional back-propagation algorithm, inheriting its drawbacks of the gradient diffusion and the sensitivity on parameters. To keep the powerful computation capability of the hierarchical structure and temporal encoding mechanism, but to overcome the low efficiency of the existing algorithms, a new training algorithm, the Normalized Spiking Error Back Propagation (NSEBP) is proposed in this paper. In the feedforward calculation, the output spike times are calculated by solving the quadratic function in the spike response model instead of detecting postsynaptic voltage states at all time points in traditional algorithms. Besides, in the feedback weight modification, the computational error is propagated to previous layers by the presynaptic spike jitter instead of the gradient decent rule, which realizes the layer-wised training. Furthermore, our algorithm investigates the mathematical relation between the weight variation and voltage error change, which makes the normalization in the weight modification applicable. Adopting these strategies, our algorithm outperforms the traditional SNN multi-layer algorithms in terms of learning efficiency and parameter sensitivity, that are also demonstrated by the comprehensive experimental results in this paper.

Isotope and Patient Age Predict for PSA Spikes After Permanent Prostate Brachytherapy

International Nuclear Information System (INIS)

Bostancic, Chelsea; Merrick, Gregory S.; Butler, Wayne M.; Wallner, Kent E.; Allen, Zachariah; Galbreath, Robert; Lief, Jonathan; Gutman, Sarah E.

2007-01-01

Purpose: To evaluate prostate-specific antigen (PSA) spikes after permanent prostate brachytherapy in low-risk patients. Methods and Materials: The study population consisted of 164 prostate cancer patients who were part of a prospective randomized trial comparing 103 Pd and 125 I for low-risk disease. Of the 164 patients, 61 (37.2%) received short-course androgen deprivation therapy. The median follow-up was 5.4 years. On average, 11.1 post-treatment PSA measurements were obtained per patient. Biochemical disease-free survival was defined as a PSA level of ≤0.40 ng/mL after nadir. A PSA spike was defined as an increase of ≥0.2 ng/mL, followed by a durable decline to prespike levels. Multiple parameters were evaluated as predictors for a PSA spike. Results: Of the 164 patients, 44 (26.9%) developed a PSA spike. Of the 46 hormone-naive 125 I patients and 57 hormone-naive 103 Pd patients, 21 (45.7%) and 8 (14.0%) developed a PSA spike. In the hormone-naive patients, the mean time between implantation and the spike was 22.6 months and 18.7 months for 125 I and 103 Pd, respectively. In patients receiving neoadjuvant androgen deprivation therapy, the incidence of spikes was comparable between isotopes ( 125 I 28.1% and 103 Pd 20.7%). The incidence of spikes was substantially different in patients 125 I and/or <65 years of age. Differences in isotope-related spikes are most pronounced in hormone-naive patients

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 ...

Numerical simulation on current spike behaviour of JT-60U disruptive plasmas

International Nuclear Information System (INIS)

Takei, N; Nakamura, Y; Tsutsui, H; Yoshino, R; Kawano, Y; Ozeki, T; Tobita, K; Tsuji-Iio, S; Shimada, R; Jardin, S C

2004-01-01

Characteristics and underlying mechanisms for plasma current spikes, which have been frequently observed during the thermal quench of JT-60U disruptions, were investigated through tokamak simulation code simulations including the passive shell effects of the vacuum vessel. Positive shear and reversed shear (PS and RS) plasmas were shown to have various current spike features in the experiments, e.g. an impulsive increase in the plasma current (positive spike) in the majority of thermal quenches, and a sudden decrease (negative spike), that has been excluded from past consideration, as an exception. It was first clarified that the shell effects, which become significant especially at a strong pressure drop due to the thermal quench of high β p plasmas, play an important role in the current spike in accordance with the initial relation of the radial location between the plasma equilibria and the vacuum vessel. As a consequence, a negative current spike may appear at thermal quench when the plasma is positioned further out from the geometric centre of the vacuum vessel. It was also pointed out that a further lowering in the internal inductance, in contradiction to previous interpretation in the past, is a plausible candidate for the mechanism for positive current spikes observed even in RS plasmas. The new interpretation enables us to reason out the whole character of current spikes of JT-60U disruptions

Statistical characteristics of climbing fiber spikes necessary for efficient cerebellar learning.

Science.gov (United States)

Kuroda, S; Yamamoto, K; Miyamoto, H; Doya, K; Kawat, M

2001-03-01

Mean firing rates (MFRs), with analogue values, have thus far been used as information carriers of neurons in most brain theories of learning. However, the neurons transmit the signal by spikes, which are discrete events. The climbing fibers (CFs), which are known to be essential for cerebellar motor learning, fire at the ultra-low firing rates (around 1 Hz), and it is not yet understood theoretically how high-frequency information can be conveyed and how learning of smooth and fast movements can be achieved. Here we address whether cerebellar learning can be achieved by CF spikes instead of conventional MFR in an eye movement task, such as the ocular following response (OFR), and an arm movement task. There are two major afferents into cerebellar Purkinje cells: parallel fiber (PF) and CF, and the synaptic weights between PFs and Purkinje cells have been shown to be modulated by the stimulation of both types of fiber. The modulation of the synaptic weights is regulated by the cerebellar synaptic plasticity. In this study we simulated cerebellar learning using CF signals as spikes instead of conventional MFR. To generate the spikes we used the following four spike generation models: (1) a Poisson model in which the spike interval probability follows a Poisson distribution, (2) a gamma model in which the spike interval probability follows the gamma distribution, (3) a max model in which a spike is generated when a synaptic input reaches maximum, and (4) a threshold model in which a spike is generated when the input crosses a certain small threshold. We found that, in an OFR task with a constant visual velocity, learning was successful with stochastic models, such as Poisson and gamma models, but not in the deterministic models, such as max and threshold models. In an OFR with a stepwise velocity change and an arm movement task, learning could be achieved only in the Poisson model. In addition, for efficient cerebellar learning, the distribution of CF spike

Membrane alterations induced by nonstructural proteins of human norovirus.

Directory of Open Access Journals (Sweden)

Sylvie Y Doerflinger

2017-10-01

Full Text Available Human noroviruses (huNoV are the most frequent cause of non-bacterial acute gastroenteritis worldwide, particularly genogroup II genotype 4 (GII.4 variants. The viral nonstructural (NS proteins encoded by the ORF1 polyprotein induce vesical clusters harboring the viral replication sites. Little is known so far about the ultrastructure of these replication organelles or the contribution of individual NS proteins to their biogenesis. We compared the ultrastructural changes induced by expression of norovirus ORF1 polyproteins with those induced upon infection with murine norovirus (MNV. Characteristic membrane alterations induced by ORF1 expression resembled those found in MNV infected cells, consisting of vesicle accumulations likely built from the endoplasmic reticulum (ER which included single membrane vesicles (SMVs, double membrane vesicles (DMVs and multi membrane vesicles (MMVs. In-depth analysis using electron tomography suggested that MMVs originate through the enwrapping of SMVs with tubular structures similar to mechanisms reported for picornaviruses. Expression of GII.4 NS1-2, NS3 and NS4 fused to GFP revealed distinct membrane alterations when analyzed by correlative light and electron microscopy. Expression of NS1-2 induced proliferation of smooth ER membranes forming long tubular structures that were affected by mutations in the active center of the putative NS1-2 hydrolase domain. NS3 was associated with ER membranes around lipid droplets (LDs and induced the formation of convoluted membranes, which were even more pronounced in case of NS4. Interestingly, NS4 was the only GII.4 protein capable of inducing SMV and DMV formation when expressed individually. Our work provides the first ultrastructural analysis of norovirus GII.4 induced vesicle clusters and suggests that their morphology and biogenesis is most similar to picornaviruses. We further identified NS4 as a key factor in the formation of membrane alterations of huNoV and

Asprosin, a fasting-induced glucogenic protein hormone

Science.gov (United States)

Hepatic glucose release into the circulation is vital for brain function and survival during periods of fasting and is modulated by an array of hormones that precisely regulate plasma glucose levels. We have identified a fasting-induced protein hormone that modulates hepatic glucose release. It is t...

Computational investigations of blunt body drag-reduction spikes in hypersonic flows

International Nuclear Information System (INIS)

Kamran, N.; Zahir, S.; Khan, M.A.

2003-01-01

Drag is an important parameter in the designing of high-speed vehicles. Such vehicles include hypervelocity projectiles, reentry modules, and hypersonic aircrafts. Therefore, there exists an active or passive technique to reduce drag due to the high pressures at nosetip region of the vehicle. Drag can be reduced by attaching a forward facing spike on the nose of the vehicle. The present study reviews and deals with the CFD analysis made on a standard blunt body to reduce aerodynamic drag due to the attachment of forward facing spikes for High-Speed vehicles. Different spike lengths have been examined to study the forebody flowfield. The investigation concludes that spikes are an effective way to reduce the aerodynamic drag due to reduced dynamic pressure on the nose caused by the separated flow on the spikes. With the accomplishment of confidence on computational data, study was extended in hypersonic Mach range with a drag prediction accuracy of ± 10%. In the present work, viscous fluid dynamics studies were performed for a complete freestream Mach number range of 5.0, 6.0, 7.0 and 8.0 for different spike lengths and zero degree angle of attack. (author)

Ligand Binding Domain Protein in Tetracycline-Inducible Expression ...

African Journals Online (AJOL)

binding domain proteins in E. coli using a tetracycline inducible system. To allow for ... development of molecular ligands with improved therapeutic windows. Keywords: Nuclear receptor ..... functional recombinant cannabinoid receptor CB2 in ...

Transient reduction in theta power caused by interictal spikes in human temporal lobe epilepsy.

Science.gov (United States)

Manling Ge; Jundan Guo; Yangyang Xing; Zhiguo Feng; Weide Lu; Xinxin Ma; Yuehua Geng; Xin Zhang

2017-07-01

The inhibitory impacts of spikes on LFP theta rhythms(4-8Hz) are investigated around sporadic spikes(SSs) based on intracerebral EEG of 4 REM sleep patients with temporal lobe epilepsy(TLE) under the pre-surgical monitoring. Sequential interictal spikes in both genesis area and extended propagation pathway are collected, that, SSs genesis only in anterior hippocampus(aH)(possible propagation pathway in Entorhinal cortex(EC)), only in EC(possible propagation pathway in aH), and in both aH and EC synchronously. Instantaneous theta power was estimated by using Gabor wavelet transform, and theta power level was estimated by averaged over time and frequency before SSs(350ms pre-spike) and after SSs(350ms post-spike). The inhibitory effect around spikes was evaluated by the ratio of theta power level difference between pre-spike and post-spike to pre-spike theta power level. The findings were that theta power level was reduced across SSs, and the effects were more sever in the case of SSs in both aH and EC synchronously than either SSs only in EC or SSs only in aH. It is concluded that interictal spikes impair LFP theta rhythms transiently and directly. The work suggests that the reduction of theta power after the interictal spike might be an evaluation indicator of damage of epilepsy to human cognitive rhythms.

Multi-scale approach to radiation damage induced by ion beams: complex DNA damage and effects of thermal spikes

International Nuclear Information System (INIS)

Surdutovich, E.; Yakubovich, A.V.; Solov'yov, A.V.; Surdutovich, E.; Yakubovich, A.V.; Solov'yov, A.V.

2010-01-01

We present the latest advances of the multi-scale approach to radiation damage caused by irradiation of a tissue with energetic ions and report the calculations of complex DNA damage and the effects of thermal spikes on biomolecules. The multi-scale approach aims to quantify the most important physical, chemical, and biological phenomena taking place during and following irradiation with ions and provide a better means for clinically-necessary calculations with adequate accuracy. We suggest a way of quantifying the complex clustered damage, one of the most important features of the radiation damage caused by ions. This quantification allows the studying of how the clusterization of DNA lesions affects the lethality of damage. We discuss the first results of molecular dynamics simulations of ubiquitin in the environment of thermal spikes, predicted to occur in tissue for a short time after an ion's passage in the vicinity of the ions' tracks. (authors)

Spectral components of cytosolic [Ca2+] spiking in neurons

DEFF Research Database (Denmark)

Kardos, J; Szilágyi, N; Juhász, G

1998-01-01

. Delayed complex responses of large [Ca2+]c spiking observed in cells from a different set of cultures were synthesized by a set of frequencies within the range 0.018-0.117 Hz. Differential frequency patterns are suggested as characteristics of the [Ca2+]c spiking responses of neurons under different...

Unsupervised clustering with spiking neurons by sparse temporal coding and multi-layer RBF networks

NARCIS (Netherlands)

S.M. Bohte (Sander); J.A. La Poutré (Han); J.N. Kok (Joost)

2000-01-01

textabstractWe demonstrate that spiking neural networks encoding information in spike times are capable of computing and learning clusters from realistic data. We show how a spiking neural network based on spike-time coding and Hebbian learning can successfully perform unsupervised clustering on

Neural Spike Train Synchronisation Indices: Definitions, Interpretations and Applications.

Science.gov (United States)

Halliday, D M; Rosenberg, J R

2017-04-24

A comparison of previously defined spike train syncrhonization indices is undertaken within a stochastic point process framework. The second order cumulant density (covariance density) is shown to be common to all the indices. Simulation studies were used to investigate the sampling variability of a single index based on the second order cumulant. The simulations used a paired motoneurone model and a paired regular spiking cortical neurone model. The sampling variability of spike trains generated under identical conditions from the paired motoneurone model varied from 50% { 160% of the estimated value. On theoretical grounds, and on the basis of simulated data a rate dependence is present in all synchronization indices. The application of coherence and pooled coherence estimates to the issue of synchronization indices is considered. This alternative frequency domain approach allows an arbitrary number of spike train pairs to be evaluated for statistically significant differences, and combined into a single population measure. The pooled coherence framework allows pooled time domain measures to be derived, application of this to the simulated data is illustrated. Data from the cortical neurone model is generated over a wide range of firing rates (1 - 250 spikes/sec). The pooled coherence framework correctly characterizes the sampling variability as not significant over this wide operating range. The broader applicability of this approach to multi electrode array data is briefly discussed.

Visualizing spikes in source-space

DEFF Research Database (Denmark)

Beniczky, Sándor; Duez, Lene; Scherg, Michael

2016-01-01

OBJECTIVE: Reviewing magnetoencephalography (MEG) recordings is time-consuming: signals from the 306 MEG-sensors are typically reviewed divided into six arrays of 51 sensors each, thus browsing each recording six times in order to evaluate all signals. A novel method of reconstructing the MEG...... signals in source-space was developed using a source-montage of 29 brain-regions and two spatial components to remove magnetocardiographic (MKG) artefacts. Our objective was to evaluate the accuracy of reviewing MEG in source-space. METHODS: In 60 consecutive patients with epilepsy, we prospectively...... evaluated the accuracy of reviewing the MEG signals in source-space as compared to the classical method of reviewing them in sensor-space. RESULTS: All 46 spike-clusters identified in sensor-space were also identified in source-space. Two additional spike-clusters were identified in source-space. As 29...

Rac1 modulates G-protein-coupled receptor-induced bronchial smooth muscle contraction.

Science.gov (United States)

Sakai, Hiroyasu; Kai, Yuki; Sato, Ken; Ikebe, Mitsuo; Chiba, Yohihiko

2018-01-05

Increasing evidence suggests a functional role of RhoA/Rho-kinase signalling as a mechanism for smooth muscle contraction; however, little is known regarding the roles of Rac1 and other members of the Rho protein family. This study aimed to examine whether Rac1 modulates bronchial smooth muscle contraction. Ring preparations of bronchi isolated from rats were suspended in an organ bath, and isometric contraction of circular smooth muscle was measured. Immunoblotting was used to examine myosin light chain phosphorylation in bronchial smooth muscle. Our results demonstrated that muscle contractions induced by carbachol (CCh) and endothelin-1 (ET-1) were inhibited by EHT1864, a selective Rac1 inhibitor, and NSC23766, a selective inhibitor of Rac1-specific guanine nucleotide exchange factors. Similarly, myosin light chain and myosin phosphatase target subunit 1 (MYPT1) at Thr853 phosphorylation induced by contractile agonist were inhibited with Rac1 inhibition. However, contractions induced by high K + , calyculin A (a potent protein phosphatase inhibitor) and K + /PDBu were not inhibited by these Rac1 inhibitors. Interestingly, NaF (a G-protein activator)-induced contractions were inhibited by EHT1864 but not by NSC23766. We next examined the effects of a trans-acting activator of transcription protein transduction domain (PTD) fusion protein with Rac1 (PTD-Rac1) on muscle contraction. The constitutively active form of PTD-Rac1 directly induced force development and contractions were abolished by EHT1864. These results suggest that Rac1, activated by G protein-coupled receptor agonists, such as CCh and ET-1, may induce myosin light chain and MYPT phosphorylation and modulate the contraction of bronchial smooth muscle. Copyright © 2017 Elsevier B.V. All rights reserved.

Tumor-associated proteins in rat submandibular gland induced by DMBA and irradiation

International Nuclear Information System (INIS)

Oh, Sung Ook; Choi, Soon Chul; Park, Tae Won; You, Dong Soo

1997-01-01

This study was performed in order to identify changes of the plasma membrane proteins in rat submandibular gland tumors induced by 7,12-dimethylbenz[a]anthracene [DMBA] and X-irradiation. Two kinds of tumor associated membrane proteins (protein A and B) were isolated with 3 M KCl extraction from rat submandibular gland tumors induced by DMBA and X-irradiation. To identify their antigenicities, immunoelectrophoresis and double immunodiffusion was carried out with various proteins extracted from liver, heart, skin and pancreas of adult rats and from embryonic liver, heart and skin. The rabbit antisera against the protein A did not cross-react with any of the proteins extracted from the above mentioned tissues, suggesting that protein A might be tumor specific antigen. However, the rabbit antisera against protein B was precipitated with proteins extracted from the liver of adult and embryonic rats. Polyacrylamide gel electrophoresis of these two proteins (A and B) showed that protein A was a dimer with molecular weights of 69,000 and 35,000 dalton, whereas protein B was a monomer with molecular weight of 50,000 dalton.

Temporal Correlations and Neural Spike Train Entropy

International Nuclear Information System (INIS)

Schultz, Simon R.; Panzeri, Stefano

2001-01-01

Sampling considerations limit the experimental conditions under which information theoretic analyses of neurophysiological data yield reliable results. We develop a procedure for computing the full temporal entropy and information of ensembles of neural spike trains, which performs reliably for limited samples of data. This approach also yields insight to the role of correlations between spikes in temporal coding mechanisms. The method, when applied to recordings from complex cells of the monkey primary visual cortex, results in lower rms error information estimates in comparison to a 'brute force' approach

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.

Transformation-invariant visual representations in self-organizing spiking neural networks.

Science.gov (United States)

Evans, Benjamin D; Stringer, Simon M

2012-01-01

The ventral visual pathway achieves object and face recognition by building transformation-invariant representations from elementary visual features. In previous computer simulation studies with rate-coded neural networks, the development of transformation-invariant representations has been demonstrated using either of two biologically plausible learning mechanisms, Trace learning and Continuous Transformation (CT) learning. However, it has not previously been investigated how transformation-invariant representations may be learned in a more biologically accurate spiking neural network. A key issue is how the synaptic connection strengths in such a spiking network might self-organize through Spike-Time Dependent Plasticity (STDP) where the change in synaptic strength is dependent on the relative times of the spikes emitted by the presynaptic and postsynaptic neurons rather than simply correlated activity driving changes in synaptic efficacy. Here we present simulations with conductance-based integrate-and-fire (IF) neurons using a STDP learning rule to address these gaps in our understanding. It is demonstrated that with the appropriate selection of model parameters and training regime, the spiking network model can utilize either Trace-like or CT-like learning mechanisms to achieve transform-invariant representations.

Transform-invariant visual representations in self-organizing spiking neural networks

Directory of Open Access Journals (Sweden)

Benjamin eEvans

2012-07-01

Full Text Available The ventral visual pathway achieves object and face recognition by building transform-invariant representations from elementary visual features. In previous computer simulation studies with rate-coded neural networks, the development of transform invariant representations has been demonstrated using either of two biologically plausible learning mechanisms, Trace learning and Continuous Transformation (CT learning. However, it has not previously been investigated how transform invariant representations may be learned in a more biologically accurate spiking neural network. A key issue is how the synaptic connection strengths in such a spiking network might self-organize through Spike-Time Dependent Plasticity (STDP where the change in synaptic strength is dependent on the relative times of the spikes emitted by the pre- and postsynaptic neurons rather than simply correlated activity driving changes in synaptic efficacy. Here we present simulations with conductance-based integrate-and-fire (IF neurons using a STDP learning rule to address these gaps in our understanding. It is demonstrated that with the appropriate selection of model pa- rameters and training regime, the spiking network model can utilize either Trace-like or CT-like learning mechanisms to achieve transform-invariant representations.

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.

Cyanobacterial high-light-inducible proteins - Protectors of chlorophyll-protein synthesis and assembly

Czech Academy of Sciences Publication Activity Database

Komenda, Josef; Sobotka, R.

2016-01-01

Roč. 1857, č. 3 (2016), s. 288-295 ISSN 0005-2728 R&D Projects: GA MŠk LO1416; GA ČR(CZ) GAP501/11/0377 Institutional support: RVO:61388971 Keywords : Chlorophyll * Cyanobacteria * High-light-inducible protein Subject RIV: CE - Biochemistry Impact factor: 4.932, year: 2016

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.

Spatiotemporal Spike Coding of Behavioral Adaptation in the Dorsal Anterior Cingulate Cortex.

Science.gov (United States)

Logiaco, Laureline; Quilodran, René; Procyk, Emmanuel; Arleo, Angelo

2015-08-01

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.

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.

Spike Neural Models Part II: Abstract Neural Models

Directory of Open Access Journals (Sweden)

Johnson, Melissa G.

2018-02-01

Full Text Available 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 which is not biologically realistic but does quickly and easily integrate input to produce spikes. Izhikevich's model is based on Hodgkin-Huxley's model but simplified such that it uses only two differentiation equations and four parameters to produce various realistic spike patterns. LIF is based on a standard electrical circuit and contains one equation. Either of these two models, or any of the many other models in literature can be used in a SNN. Choosing a neural model is an important task that depends on the goal of the research and the resources available. Once a model is chosen, network decisions such as connectivity, delay, and sparseness, need to be made. Understanding neural models and how they are incorporated into the network is the first step in creating a SNN.

Dietary Protein in the Prevention of Diet-Induced Obesity and Co-Morbidities

DEFF Research Database (Denmark)

Tastesen, Hanne Sørup

mice were fed obesity‐promoting diets with protein from different sources, in different forms and at different levels to evaluate the affect on development of obesity, glucose intolerance and dyslipidemia. Results: In the present study the dietary level of protein, 16 versus 32 percent energy from...... protein, was found to be negligible in development of obesity and co‐morbidities in mice. Seafood protein with high endogenous taurine and glycine contents was found to prevent diet‐induced adiposity and dyslipidemia, both in ad libitum and pair‐fed settings. The ability of seafood proteins to prevent...... that the source and form of protein has great impact on development and prevention of diet‐induced adiposity, dyslipidemia, hyperinsulinemia and impairment of glucose tolerance through modulations of voluntary locomotor activity, energy expenditure and energy substrate metabolism in mice...

Interspike Interval Based Filtering of Directional Selective Retinal Ganglion Cells Spike Trains

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Aurel Vasile Martiniuc

2012-01-01

Full Text Available The information regarding visual stimulus is encoded in spike trains at the output of retina by retinal ganglion cells (RGCs. Among these, the directional selective cells (DSRGC are signaling the direction of stimulus motion. DSRGCs' spike trains show accentuated periods of short interspike intervals (ISIs framed by periods of isolated spikes. Here we use two types of visual stimulus, white noise and drifting bars, and show that short ISI spikes of DSRGCs spike trains are more often correlated to their preferred stimulus feature (that is, the direction of stimulus motion and carry more information than longer ISI spikes. Firstly, our results show that correlation between stimulus and recorded neuronal response is best at short ISI spiking activity and decrease as ISI becomes larger. We then used grating bars stimulus and found that as ISI becomes shorter the directional selectivity is better and information rates are higher. Interestingly, for the less encountered type of DSRGC, known as ON-DSRGC, short ISI distribution and information rates revealed consistent differences when compared with the other directional selective cell type, the ON-OFF DSRGC. However, these findings suggest that ISI-based temporal filtering integrates a mechanism for visual information processing at the output of retina toward higher stages within early visual system.

Depletion-induced instability in protein-DNA mixtures: Influence of protein charge and size

NARCIS (Netherlands)

Vries, de R.J.

2006-01-01

While there is abundant experimental and theoretical work on polymer-induced DNA condensation, it is still unclear whether globular proteins can condense linear DNA or not. We develop a simple analytical approximation for the depletion attraction between rodlike segments of semiflexible

Low dose radiation induced protein and its effect on expression of CD25 molecule in lymphocytes

International Nuclear Information System (INIS)

Lu Duicai; Su Liaoyuan

2001-01-01

Objective: To find the substantial basis for effects of low dose radiation, on development, extraction, and the biogical activity of the low-dose radiation-induced proteins, and the effects of LDR induced proteins on CD25 molecule expression of human lymphocytes. Methods: 1. Healthy Kumning male mice exposed to radiation of 226 Ra γ-rays at 5, 10 and 15 cGy respectively. The mice were killed 2 hours after exposure, the spleen cells were broken with ultrasonic energy and then ultra-centrifugalized at low temperature (4 degree C). The LDR-induced proteins were obtained in the supernatant solution. Then the changes of CD25 molecule was measured by flow cytometry (FCM) with immunofluorescence technique, which was used to reflect the effect of LDR induced proteins on CD25 molecule expression of human lymphocytes. Results: LDR induced proteins were obtained from spleen cells in mice exposed to 5-15 cGy whole body radiation. Conclusion: The expression of CD25 molecule of lymphocytes was increased significantly after use of LDR induced proteins. LDR induced proteins can enhance expression of CD25 molecule of lymphocytes slightly

TPA-inducible proteins may account for sensitivity to promotion of transformation

International Nuclear Information System (INIS)

Hirano, K.; Smith, B.; Colburn, N.H.

1986-01-01

The preneoplastic JB6 mouse epidermal cell system includes cell lines sensitive (P + ) or resistant (P - ) to tumor promoter induced neoplastic transformation. The authors investigated whether a difference in TPA-inducible proteins may explain this differential sensitivity. The synthesis of a 39 Kd cytoplasmic protein (Major Excreted Protein) was TPA-inducible, but to a similar extent in both P + and P - cells. TPA stimulated phosphorylation but not synthesis of the previously described stress protein pp80 in both P + and P - cells from 1 to 5 hr after treatment. Pulse labelling of P + and P - cells with 35 S-methionine revealed a TPA dependent P + specific transient increase in the synthesis of 58Kd protein. Induction was observed at 1 hr, and returned to basal levels by 4 hr and 20 hr, in nuclear and cytoplasmic fractions, respectively. This protein is not phosphorylated in response to TPA treatment. P + cells differ from P - cells in one or more genes that specify sensitivity to promotion of transformation, designated pro genes. Antibodies to three peptides representing the pro-1 open reading frame were used in immunoprecipitation and Western blotting to isolate the pro-1 gene product. A 43 Kd protein was immunologically responsive to the pro-1 peptide antibodies, and showed an increased signal 40 min after TPA treatment. Since the predicted molecular weight of a pro-1 gene product is only 7 Kd, the possibility of a modification of the protein by poly(ADP-ribosylation) or glycosylation is being investigated

Production of a monoclonal antibody directed against an interferon-induced 56,000-dalton protein and its use in the study of this protein

International Nuclear Information System (INIS)

Rubin, B.Y.; Anderson, S.L.; Lunn, R.M.; Hellermann, G.R.; Richardson, N.K.; Smith, L.J.

1988-01-01

Interferon (IFN) treatment of cells induces the synthesis of several new proteins. A hybridoma cell line producing monoclonal antibody to the IFN-induced 56,000-dalton protein has been developed. The IFN-induced 56,000-dalton protein is synthesized by a variety of different cells and in response to IFN-α, IFN-β, and IFN-γ. The induction of this protein is dependent on de novo RNA synthesis, since its induction is inhibited if actinomycin D and the IFNs are added to the cells simultaneously. [ 35 S]-labeling of IFN-treated cells at 4-h intervals at various times after the addition of the IFNs reveals that the synthesis of the 56,000-dalton protein in IFN-α-treated cells peaks within 12 h after the addition of the IFN and is no longer enhanced 20 h after exposure to the IFN. In contrast, IFN-γ-treated cells continue to show an enhanced synthesis of this IFN-induced protein even after 20 h of exposure to the IFN. Thus, the synthesis of the IFN-induced 56,000-dalton protein is regulated differently by the different IFNs. When cells are treated with IFN-α or IFN-γ in the presence of cycloheximide, and actinomycin D is added prior to the removal of the cycloheximide, the cells produce the IFN-induced 56,000-dalton protein and develop an antiviral state in response to both IFN-α and IFN-γ. These results demonstrate that the synthesis of the 56,000-dalton protein is not dependent on the synthesis of an intermediary protein and that the establishment of an antiviral state occurs in the absence of multiple transcriptional events

Structured chaos shapes spike-response noise entropy in balanced neural networks

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Guillaume eLajoie

2014-10-01

Full Text Available Large networks of sparsely coupled, excitatory and inhibitory cells occur throughout the brain. For many models of these networks, a striking feature is that their dynamics are chaotic and thus, are sensitive to small perturbations. How does this chaos manifest in the neural code? Specifically, how variable are the spike patterns that such a network produces in response to an input signal? To answer this, we derive a bound for a general measure of variability -- spike-train entropy. This leads to important insights on the variability of multi-cell spike pattern distributions in large recurrent networks of spiking neurons responding to fluctuating inputs. The analysis is based on results from random dynamical systems theory and is complemented by detailed numerical simulations. We find that the spike pattern entropy is an order of magnitude lower than what would be extrapolated from single cells. This holds despite the fact that network coupling becomes vanishingly sparse as network size grows -- a phenomenon that depends on ``extensive chaos, as previously discovered for balanced networks without stimulus drive. Moreover, we show how spike pattern entropy is controlled by temporal features of the inputs. Our findings provide insight into how neural networks may encode stimuli in the presence of inherently chaotic dynamics.

Induced protein polymorphisms and nutritional quality of gamma irradiation mutants of sorghum

Energy Technology Data Exchange (ETDEWEB)

Mehlo, Luke, E-mail: LMehlo@csir.co.za [CSIR Biosciences, Meiring Naude Road, P.O. Box 395, Pretoria 0001 (South Africa); Mbambo, Zodwa [CSIR Biosciences, Meiring Naude Road, P.O. Box 395, Pretoria 0001 (South Africa); Microbiology Discipline, School of Life Sciences, University of KwaZulu-Natal (Westville Campus), Private Bag X54001, Durban 4000 (South Africa); Bado, Souleymane [Plant Breeding and Genetics Laboratory – Joint FAO/IAEA Agriculture and Biotechnology Laboratory, International Atomic Energy Agency Laboratories, A-2444 Seibersdorf (Austria); Lin, Johnson [Microbiology Discipline, School of Life Sciences, University of KwaZulu-Natal (Westville Campus), Private Bag X54001, Durban 4000 (South Africa); Moagi, Sydwell M.; Buthelezi, Sindisiwe; Stoychev, Stoyan; Chikwamba, Rachel [CSIR Biosciences, Meiring Naude Road, P.O. Box 395, Pretoria 0001 (South Africa)

2013-09-15

Highlights: • We analyse kafirin protein polymorphisms induced by gamma irradiation in sorghum. • One mutant with suppressed kafirins in the endosperm accumulated them in the germ. • Kafirin polymorphisms were associated with high levels of free amino acids. • Nutritional value of sorghum can be improved significantly by induced mutations. - Abstract: Physical and biochemical analysis of protein polymorphisms in seed storage proteins of a mutant population of sorghum revealed a mutant with redirected accumulation of kafirin proteins in the germ. The change in storage proteins was accompanied by an unusually high level accumulation of free lysine and other essential amino acids in the endosperm. This mutant further displayed a significant suppression in the synthesis and accumulation of the 27 kDa γ-, 24 kDa α-A1 and the 22 kDa α-A2 kafirins in the endosperm. The suppression of kafirins was counteracted by an upsurge in the synthesis and accumulation of albumins, globulins and other proteins. The data collectively suggest that sorghum has huge genetic potential for nutritional biofortification and that induced mutations can be used as an effective tool in achieving premium nutrition in staple cereals.

Induced protein polymorphisms and nutritional quality of gamma irradiation mutants of sorghum

International Nuclear Information System (INIS)

Mehlo, Luke; Mbambo, Zodwa; Bado, Souleymane; Lin, Johnson; Moagi, Sydwell M.; Buthelezi, Sindisiwe; Stoychev, Stoyan; Chikwamba, Rachel

2013-01-01

Highlights: • We analyse kafirin protein polymorphisms induced by gamma irradiation in sorghum. • One mutant with suppressed kafirins in the endosperm accumulated them in the germ. • Kafirin polymorphisms were associated with high levels of free amino acids. • Nutritional value of sorghum can be improved significantly by induced mutations. - Abstract: Physical and biochemical analysis of protein polymorphisms in seed storage proteins of a mutant population of sorghum revealed a mutant with redirected accumulation of kafirin proteins in the germ. The change in storage proteins was accompanied by an unusually high level accumulation of free lysine and other essential amino acids in the endosperm. This mutant further displayed a significant suppression in the synthesis and accumulation of the 27 kDa γ-, 24 kDa α-A1 and the 22 kDa α-A2 kafirins in the endosperm. The suppression of kafirins was counteracted by an upsurge in the synthesis and accumulation of albumins, globulins and other proteins. The data collectively suggest that sorghum has huge genetic potential for nutritional biofortification and that induced mutations can be used as an effective tool in achieving premium nutrition in staple cereals

Radiation-induced DNA-protein cross-links: Mechanisms and biological significance.

Science.gov (United States)

Nakano, Toshiaki; Xu, Xu; Salem, Amir M H; Shoulkamy, Mahmoud I; Ide, Hiroshi

2017-06-01

Ionizing radiation produces various DNA lesions such as base damage, DNA single-strand breaks (SSBs), DNA double-strand breaks (DSBs), and DNA-protein cross-links (DPCs). Of these, the biological significance of DPCs remains elusive. In this article, we focus on radiation-induced DPCs and review the current understanding of their induction, properties, repair, and biological consequences. When cells are irradiated, the formation of base damage, SSBs, and DSBs are promoted in the presence of oxygen. Conversely, that of DPCs is promoted in the absence of oxygen, suggesting their importance in hypoxic cells, such as those present in tumors. DNA and protein radicals generated by hydroxyl radicals (i.e., indirect effect) are responsible for DPC formation. In addition, DPCs can also be formed from guanine radical cations generated by the direct effect. Actin, histones, and other proteins have been identified as cross-linked proteins. Also, covalent linkages between DNA and protein constituents such as thymine-lysine and guanine-lysine have been identified and their structures are proposed. In irradiated cells and tissues, DPCs are repaired in a biphasic manner, consisting of fast and slow components. The half-time for the fast component is 20min-2h and that for the slow component is 2-70h. Notably, radiation-induced DPCs are repaired more slowly than DSBs. Homologous recombination plays a pivotal role in the repair of radiation-induced DPCs as well as DSBs. Recently, a novel mechanism of DPC repair mediated by a DPC protease was reported, wherein the resulting DNA-peptide cross-links were bypassed by translesion synthesis. The replication and transcription of DPC-bearing reporter plasmids are inhibited in cells, suggesting that DPCs are potentially lethal lesions. However, whether DPCs are mutagenic and induce gross chromosomal alterations remains to be determined. Copyright © 2017 Elsevier Inc. All rights reserved.

Glutamate Induced Thermal Equilibrium Intermediate and Counteracting Effect on Chemical Denaturation of Proteins.

Science.gov (United States)

Anumalla, Bramhini; Prabhu, N Prakash

2018-01-25

When organisms are subjected to stress conditions, one of their adaptive responses is accumulation of small organic molecules called osmolytes. These osmolytes affect the structure and stability of the biological macromolecules including proteins. The present study examines the effect of a negatively charged amino acid osmolyte, glutamate (Glu), on two model proteins, ribonuclease A (RNase A) and α-lactalbumin (α-LA), which have positive and negative surface charges at pH 7, respectively. These proteins follow two-state unfolding transitions during both heat and chemical induced denaturation processes. The addition of Glu stabilizes the proteins against temperature and induces an early equilibrium intermediate during unfolding. The stability is found to be enthalpy-driven, and the free energy of stabilization is more for α-LA compared to RNase A. The decrease in the partial molar volume and compressibility of both of the proteins in the presence of Glu suggests that the proteins attain a more compact state through surface hydration which could provide a more stable conformation. This is also supported by molecule dynamic simulation studies which demonstrate that the water density around the proteins is increased upon the addition of Glu. Further, the intermediates could be completely destabilized by lower concentrations (∼0.5 M) of guanidinium chloride and salt. However, urea subverts the Glu-induced intermediate formed by α-LA, whereas it only slightly destabilizes in the case of RNase A which has a positive surface charge and could possess charge-charge interactions with Glu. This suggests that, apart from hydration, columbic interactions might also contribute to the stability of the intermediate. Gdm-induced denaturation of RNase A and α-LA in the absence and the presence of Glu at different temperatures was carried out. These results also show the Glu-induced stabilization of both of the proteins; however, all of the unfolding transitions followed two

Identification of proteins whose synthesis in Saccharomyces cerevisiae is induced by DNA damage and heat shock

International Nuclear Information System (INIS)

Gailit, James

1990-01-01

Protein synthesis in Saccharomyces cerevisiae after exposure to ultraviolet light (UV) was examined by two-dimensional gel electrophoresis of pulse-labelled proteins. The synthesis of 12 distinct proteins was induced by treatment with UV doses of 10-200 J/m 2 . The induced proteins differed in minimum dose necessary for induction, maximum dose at which induction still occurred and constitutive level present in unirradiated cells. A chemical mutagen, 4-nitroquinoline-1-oxide, induced synthesis of the same proteins. Induction after UV treatment was observed in seven different yeast strains, including three mutants deficient in DNA repair. Synthesis of five of the proteins was also induced by brief heat shock treatment. These five may be members of a family of proteins whose synthesis is regulated by two different pathways responding to different types of stress. (author)

Fragile X Mental Retardation Protein Is Required to Maintain Visual Conditioning-Induced Behavioral Plasticity by Limiting Local Protein Synthesis.

Science.gov (United States)

Liu, Han-Hsuan; Cline, Hollis T

2016-07-06

Fragile X mental retardation protein (FMRP) is thought to regulate neuronal plasticity by limiting dendritic protein synthesis, but direct demonstration of a requirement for FMRP control of local protein synthesis during behavioral plasticity is lacking. Here we tested whether FMRP knockdown in Xenopus optic tectum affects local protein synthesis in vivo and whether FMRP knockdown affects protein synthesis-dependent visual avoidance behavioral plasticity. We tagged newly synthesized proteins by incorporation of the noncanonical amino acid azidohomoalanine and visualized them with fluorescent noncanonical amino acid tagging (FUNCAT). Visual conditioning and FMRP knockdown produce similar increases in FUNCAT in tectal neuropil. Induction of visual conditioning-dependent behavioral plasticity occurs normally in FMRP knockdown animals, but plasticity degrades over 24 h. These results indicate that FMRP affects visual conditioning-induced local protein synthesis and is required to maintain the visual conditioning-induced behavioral plasticity. Fragile X syndrome (FXS) is the most common form of inherited intellectual disability. Exaggerated dendritic protein synthesis resulting from loss of fragile X mental retardation protein (FMRP) is thought to underlie cognitive deficits in FXS, but no direct evidence has demonstrated that FMRP-regulated dendritic protein synthesis affects behavioral plasticity in intact animals. Xenopus tadpoles exhibit a visual avoidance behavior that improves with visual conditioning in a protein synthesis-dependent manner. We showed that FMRP knockdown and visual conditioning dramatically increase protein synthesis in neuronal processes. Furthermore, induction of visual conditioning-dependent behavioral plasticity occurs normally after FMRP knockdown, but performance rapidly deteriorated in the absence of FMRP. These studies show that FMRP negatively regulates local protein synthesis and is required to maintain visual conditioning-induced

Should spikes on post-resection ECoG guide pediatric epilepsy surgery?

Science.gov (United States)

Greiner, Hansel M; Horn, Paul S; Tenney, Jeffrey R; Arya, Ravindra; Jain, Sejal V; Holland, Katherine D; Leach, James L; Miles, Lili; Rose, Douglas F; Fujiwara, Hisako; Mangano, Francesco T

2016-05-01

There is wide variation in clinical practice regarding the role of electrocorticography immediately after resection (post-resection ECoG) for pediatric epilepsy surgery. Results can guide further resection of potentially epileptogenic tissue. We hypothesized that post-resection ECoG spiking represents a biomarker of the epileptogenic zone and predicts seizure outcome in children undergoing epilepsy surgery. We retrospectively identified 124 children with post-resection ECoG performed on the margins of resection. ECoG records were scored in a blinded fashion based on presence of frequent spiking. For patients identified as having additional resection based on clinical post-resection ECoG interpretation, these "second-look" ECoG results were re-reviewed for ongoing discharges or completeness of resection. Frequent spike populations were grouped using a standard scoring system into three ranges: 0.1-0.5Hz, 0.5-1Hz, >1Hz. Seizure outcomes were determined at minimum 12-month followup. Of 124 patients who met inclusion criteria, 60 (48%) had an identified spike population on post-resection ECoG. Thirty (50%) of these had further resection based on clinical interpretation. Overall, good outcome (ILAE 1) was seen in 56/124 (45%). Completeness of resection of spiking (absence of spiking on initial post-resection ECoG or resolution of spiking after further resection) showed a trend toward good outcome (OR 2.03, p=0.099). Patients with completeness of resection had good outcome in 41/80 (51%) of cases; patients with continued spikes had good outcome in 15/44 (35%) of cases. Post-resection ECoG identifies residual epileptogenic tissue in a significant number of children. Lower frequency or absence of discharges on initial recording showed a trend toward good outcome. Completeness of resection demonstrated on final ECoG recording did not show a significant difference in outcome. This suggests that post-resection discharges represent a prognostic marker rather than a remediable

Evoking prescribed spike times in stochastic neurons