Stochastic resonance of ensemble neurons for transient spike trains: Wavelet analysis

International Nuclear Information System (INIS)

Hasegawa, Hideo

2002-01-01

By using the wavelet transformation (WT), I have analyzed the response of an ensemble of N (=1, 10, 100, and 500) Hodgkin-Huxley neurons to transient M-pulse spike trains (M=1 to 3) with independent Gaussian noises. The cross correlation between the input and output signals is expressed in terms of the WT expansion coefficients. The signal-to-noise ratio (SNR) is evaluated by using the denoising method within the WT, by which the noise contribution is extracted from the output signals. Although the response of a single (N=1) neuron to subthreshold transient signals with noises is quite unreliable, the transmission fidelity assessed by the cross correlation and SNR is shown to be much improved by increasing the value of N: a population of neurons plays an indispensable role in the stochastic resonance (SR) for transient spike inputs. It is also shown that in a large-scale ensemble, the transmission fidelity for suprathreshold transient spikes is not significantly degraded by a weak noise which is responsible to SR for subthreshold inputs

Immune responses induced by recombinant Bacillus subtilis expressing the spike protein of transmissible gastroenteritis virus in pigs.

Science.gov (United States)

Mou, Chunxiao; Zhu, Liqi; Xing, Xianping; Lin, Jian; Yang, Qian

2016-07-01

Transmissible gastroenteritis (TGE) causes severe diarrhea in suckling piglets, results in enormous economic loss in swine-producing areas of the world. To develop an effective, safe, and convenient vaccine for the prevention of TGE, we have constructed a recombinant Bacillus subtilis strain (B. subtilis CotGSG) displaying the transmissible gastroenteritis virus (TGEV) spike (S) protein and discussed its immune function to intestinal submucosal dendritic cells (DCs). Our results showed that the recombinant B. subtilis had the ability to recruit more DCs to sample B. subtilis CotGSG, migrate to MLNs, and induce immune responses. Immunized piglets with B. subtilis CotGSG could significantly elevate the specific SIgA titers in feces, IgG titers and neutralizing antibodies in serum. Collectively, our results suggested that recombinant B. subtilis CotGSG expressing the TGEV S protein could effectively induce immune responses via DCs, and provided a perspective on potential novel strategy and approach that may be applicable to the development of the next generation of TGEV vaccines. Copyright © 2016 Elsevier B.V. All rights reserved.

Technetium-99m-Labeled Autologous Serum Albumin: A Personal-Exclusive Source of Serum Component

OpenAIRE

Wang, Yuh-Feng; Chen, Yi-Chun; Li, Dian-Kun; Chuang, Mei-Hua

2011-01-01

Technetium-99m human serum albumin (99mTc-HSA) is an important radiopharmaceutical required in nuclear medicine studies. However, the risk of transfusion-transmitted infection remains a major safety concern. Autopreparation of serum component acquired from patient provides a “personal-exclusive” source for radiolabeling. This paper is to evaluate the practicality of on-site elusion and subsequent radiolabeling efficacy for serum albumin. Results showed that the autologous elute contained more...

Serum levels of parathyroid hormone-M, magnesium and calcium and their inter-relationship in patients with acute pancreatitis

International Nuclear Information System (INIS)

Liu Qi; Zhou Li; Lu Yuanhan; Wang Yan; Wang Yan; Liu Huarong

2002-01-01

Objective: To study the changes of serum parathyroid hormone-M, magnesium, and calcium levels and their interrelationships in patients with mild acute pancreatitis (MAP) and severe acute pancreatitis (SAP). Methods: Serum level of PTH-M was measured by means of radioimmunoassay, serum magnesium and calcium levels were determines with automatic biochemical analytical apparatus. Results: 1) Serum levels of PTH-M in acute period and daring recovery in patients with MAP and SAP were not significant different from those in controls (p > 0.05); serum levels of magnesium and calcium in cute period of patients with SAP were significantly lower than those in controls (p<0.01); 2) There was a linear positive correlation between serum levels of PTH-M and serum magnesium in acute-phase of SAP patients, correlation coefficient r = 0.413 (p<0.05). Conclusion: That presence of hypocalcemia in patients with severe acute pancreatitis did not lead to parathyroid hormone-M responsive rise, that might be due to the presence of hypomagnesemia

Serum TSH and the response to radioiodine treatment of toxic multinodular goitre

DEFF Research Database (Denmark)

Pedersen-Bjergaard, U; Kirkegaard, B C

1997-01-01

A retrospective analysis of data from 73 consecutive patients with toxic multinodular goitre treated with iodine-131 (131I) during a 2-year period was performed to investigate if serum TSH at the time of 131I treatment influences the outcome. The dose of 131I was calculated according to a model...... compensating for thyroid size estimated by palpation and 24-h 131I uptake. Serum TSH was determined by a third-generation assay with a functional sensitivity of 0.03 mU/l. A significantly more pronounced response to 131I treatment was observed in patients with TSH > 0.0 mU/l than in patients with TSH = 0.0 m......U/l (P = 0.0006. This difference resulted in a threefold lower frequency of non-responders and a fivefold higher rate of early hypothyroidism in the group with detectable serum TSH. While the high frequency of hypothyroidism among patients with measurable serum TSH can be explained by destruction...

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.

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

Science.gov (United States)

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

2016-04-01

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

A Model of Electrically Stimulated Auditory Nerve Fiber Responses with Peripheral and Central Sites of Spike Generation

DEFF Research Database (Denmark)

Joshi, Suyash Narendra; Dau, Torsten; Epp, Bastian

2017-01-01

. A single ANF is modeled as a network of two exponential integrateand-fire point-neuron models, referred to as peripheral and central axons of the ANF. The peripheral axon is excited by the cathodic charge, inhibited by the anodic charge, and exhibits longer spike latencies than the central axon......A computational model of cat auditory nerve fiber (ANF) responses to electrical stimulation is presented. The model assumes that (1) there exist at least two sites of spike generation along the ANF and (2) both an anodic (positive) and a cathodic (negative) charge in isolation can evoke a spike......; the central axon is excited by the anodic charge, inhibited by the cathodic charge, and exhibits shorter spike latencies than the peripheral axon. The model also includes subthreshold and suprathreshold adaptive feedback loops which continuously modify the membrane potential and can account for effects...

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.

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.

Grain price spikes and beggar-thy-neighbor policy responses

DEFF Research Database (Denmark)

Boysen, Ole; Jensen, Hans Grinsted

on the agenda of various international policy fora, including the annual meetings of G20 countries in recent years. For that reason, recent studies have attempted to quantify the extent to which such policy actions contributed to the rise in food prices. A study by Jensen & Anderson (2014) uses the global AGE...... model GTAP and the corresponding database to quantify the global policy actions contributions to the raise in food prices by modeling the changes in distortions to agricultural incentives in the period 2006 to 2008. We link the results from this global model into a national AGE model, highlighting how...... global "Beggar-thy-Neighbor Policy Responses" impacted on poor households in Uganda. More specifically we examine the following research questions: What were the Ugandan economy-wide and poverty impacts of the price spikes? What was the impact of other countries "Beggar-thy-Neighbor Policy Responses...

Directionality of auditory nerve fiber responses to pure tone stimuli in the grassfrog, Rana temporaria. II. Spike timing

DEFF Research Database (Denmark)

Jørgensen, M B; Christensen-Dalsgaard, J

1997-01-01

We studied the directionality of spike timing in the responses of single auditory nerve fibers of the grass frog, Rana temporaria, to tone burst stimulation. Both the latency of the first spike after stimulus onset and the preferred firing phase during the stimulus were studied. In addition, the ...

Clinical value of serum anti-mullerian hormone and inhibin B in prediction of ovarian response in patients with polycystic ovary syndrome.

Science.gov (United States)

Zhang, Fan; Liu, Xiao-Ling; Rong, Nan; Huang, Xiao-Wen

2017-02-01

The present study aimed to investigate the clinical value of serum anti-mullerian hormone (AMH) and inhibin B (INHB) in predicting the ovarian response of patients with polycystic ovary syndrome (PCOS). A total of 120 PCOS patients were enrolled and divided into three groups in terms of the ovarian response: a low-response group (n=36), a normal-response group (n=44), and a high-response group (n=40). The serum AMH and INHB levels were measured by enzyme-linked immunosorbent assay (ELISA). The follicle stimulating hormone (FSH), luteinizing hormone (LH), and estradiol (E2) levels were determined by chemiluminescence microparticle immunoassay. The correlation of the serum AMH and INHB levels with other indicators was analyzed. A receiver operating characteristic (ROC) curve was established to analyze the prediction of ovarian response by AMH and INHB. The results showed that there were significant differences in age, body mass index (BMI), FSH, total gonadotropin-releasing hormone (GnRH), LH, E2, and antral follicle counts (AFCs) between the groups (Povarian response of PCOS patients increasing (Povarian response showed that the area under the ROC curve (AUC) value of the serum AMH level was 0.817, with a cut-off value of 1.29 ng/mL. The sensitivity and specificity were 71.2% and 79.6%, respectively. The AUC value of serum INHB was 0.674, with a cut-off value of 38.65 ng/mL, and the sensitivity and specificity were 50.7% and 74.5%, respectively. ROC curve analysis showed when the serum AMH and INHB levels were used to predict a high ovarian response, the AUC value of the serum AMH level was 0.742, with a cut-off value of 2.84 ng/mL, and the sensitivity and specificity were 72.7% and 65.9%, respectively; the AUC value of the serum INHB level was 0.551 with a cut-off of 45.76 ng/mL, and the sensitivity and specificity were 76.3% and 40.2%, respectively. It was suggested the serum AMH and INHB levels have high clinical value in predicting the ovarian response of PCOS

Grain price spikes and beggar-thy-neighbor policy responses

DEFF Research Database (Denmark)

Jensen, Hans Grinsted; Anderson, Kym

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

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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

Science.gov (United States)

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

2012-01-01

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

Headspace Solid Phase Micro Extraction Gas Chromatographic Determination of Fenthion in Human Serum

Directory of Open Access Journals (Sweden)

Kyriaki Machera

2008-05-01

Full Text Available A simple and effective analytical procedure was developed for the determination of fenthion residues in human serum samples. The sample treatment was performed using the headspace solid-phase micro extraction with polyacrylate fiber, which has the advantage to require low amount of serum (1 mL without tedious pre-treatment. The quantification of fenthion was carried out by gas chromatography-mass spectrometry and the recoveries ranged from 79 to 104% at two spiking levels for 6 replicates. Detection and quantification limits were calculated as 1.51 and 4.54 ng/mL of serum respectively. Two fenthion metabolites − fenoxon and fenthion–sulfoxide − were also identified.

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

Serum Adiponectin, Vitamin D, and Alpha-Fetoprotein in Children with Chronic Hepatitis C: Can They Predict Treatment Response?

Science.gov (United States)

Khedr, Mohamed Ahmed; Sira, Ahmad Mohamed; Saber, Magdy Anwar; Raia, Gamal Yousef

2015-01-01

Background & Aims. The currently available treatment for chronic hepatitis C (CHC) in children is costly and with much toxicity. So, predicting the likelihood of response before starting therapy is important. Methods. Serum adiponectin, vitamin D, and alpha-fetoprotein (AFP) were measured before starting pegylated-interferon/ribavirin therapy for 50 children with CHC. Another 21 healthy children were recruited as controls. Results. Serum adiponectin, vitamin D, and AFP were higher in the CHC group than healthy controls (p < 0.0001, p = 0.071, and p = 0.87, resp.). In univariate analysis, serum adiponectin was significantly higher in responders than nonresponders (p < 0.0001) and at a cutoff value ≥8.04 ng/mL it can predict treatment response by 77.8% sensitivity and 92.9% specificity, while both AFP and viremia were significantly lower in responders than nonresponders, p < 0.0001 and p = 0.0003, respectively, and at cutoff values ≤3.265 ng/mL and ≤235,384 IU/mL, respectively, they can predict treatment response with a sensitivity of 83.3% for both and specificity of 85.7% and 78.6%, respectively. In multivariate analysis, adiponectin was found to be the only independent predictor of treatment response (p = 0.044). Conclusions. The pretreatment serum level of adiponectin can predict the likelihood of treatment response, thus avoiding toxicities for those unlikely to respond to therapy.

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

Relationship between serum IV-C, β2-m levels and diabetic nephropathy

International Nuclear Information System (INIS)

Liu Lu; Zhang Mukun

2005-01-01

Objective: To investigate the relationship between the serum type IV collagen (IV-C), β 2 -micro globulin (β 2 -m) levels and diabetic nephropathy. Methods: Serum IV-C, β 2 -m levels were measured with RIA in 30 controls and 86 patients with type 2 diabetics mellitus (35 with diabetic nephropathy and 51 without nephropathy). Results: the serum levels of IV-C and β 2 -m in diabetic patients with nephropathy were significantly higher than those in controls (P 0.05). Conclusion: Serum IV-C and β 2 -m levels increased gradually as the diabetic nephropathy got more severe. They could be a sensitive marker for early diagnosis of development of diabetic nephropathy. (authors)

[Screening serum response special antibodies of U251 cell line from surface display phage antibody library].

Science.gov (United States)

Yu, Min; Tan, De-Yong; Qian, Wei; Lai, Jian-Hua; Sun, Gui-Lin

2004-05-01

U251 cell is a sensitive cell line to serum, which stops at G0 phase of cell cycle in no-serum medium, and recovers growth when the serum is added into no-serum medium. The cell can express corresponding proteins in different phase of cell cycle. Therefore it is very signification for the study of cell cycle regulation mechanism that explores these proteins. In this paper, the mouse antibody phage display library was added into the bottle in which the serum starvation U251 cells had been cultured, and the special antibody phages were absorbed. Then the absorbed antibody phages were amplified by adding E. coli TG1 and helper phage M13K07. Amplified antibody phages were added into bottle in which the serum cultured cell after serum starvation (follow named as serum recovered cells) were incubated, so that the cell absorbed the no-special antibody phages for the serum starvation cell and the special antibody phages were in supernatant. The remaining no-special antibody phages in the supernatant were discarded by repeating above program 3-4 times. The pure special antibody phages were gotten, and amplified by adding the host cell E. coli TG1 and helper phage M13K07. Then the host bacterium infected special antibody phage was spread on the plate medium with ampicillin, and the monoclonal antibody phages were gotten. Using same as above program, the monoclonal antibody phages absorbed specially for serum recovered U251 cells were obtained when the serum recovered cells instead of serum starvation cells and serum starvation cells instead of serum recovered cells. In this study, ninety-six positive monoclonal antibody phages that absorbed specially the serum starvation cells and eighty-two positive monoclonal antibody phages that absorbed specially the serum recovered cells were obtained. By using cell immunochemistry assay, two special signification antibodies were obtained. one (No.11) was the strong response in serum starvation cells, the other (No.2) was the strong

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...

Effects of Spike Anticipation on the Spiking Dynamics of Neural Networks

Directory of Open Access Journals (Sweden)

Daniel ede Santos-Sierra

2015-11-01

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

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

Science.gov (United States)

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.

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.

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.

The fifth leaf and spike organs of barley (Hordeum vulgare L.) display different physiological and metabolic responses to drought stress.

Science.gov (United States)

Hein, Jordan A; Sherrard, Mark E; Manfredi, Kirk P; Abebe, Tilahun

2016-11-09

Photosynthetic organs of the cereal spike (ear) provide assimilate for grain filling, but their response to drought is poorly understood. In this study, we characterized the drought response of individual organs of the barley spike (awn, lemma, and palea) and compared them with a vegetative organ (fifth leaf). Understanding differences in physiological and metabolic responses between the leaf and spike organs during drought can help us develop high yielding cultivars for environments where terminal drought is prevalent. We exposed barley plants to drought by withholding water for 4 days at the grain filling stage and compared changes in: (1) relative water content (RWC), (2) osmotic potential (Ψ s ), (3) osmotic adjustment (OA), (4) gas exchange, and (5) metabolite content between organs. Drought reduced RWC and Ψ s in all four organs, but the decrease in RWC was greater and there was a smaller change in Ψ s in the fifth leaf than the spike organs. We detected evidence of OA in the awn, lemma, and palea, but not in the fifth leaf. Rates of gas exchange declined more rapidly in the fifth leaf than awn during drought. We identified 18 metabolites but, only ten metabolites accumulated significantly during drought in one or more organs. Among these, proline accumulated in all organs during drought while accumulation of the other metabolites varied between organs. This may suggest that each organ in the same plant uses a different set of osmolytes for drought resistance. Our results suggest that photosynthetic organs of the barley spike maintain higher water content, greater osmotic adjustment, and higher rates of gas exchange than the leaf during drought.

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

Serum Adiponectin, Vitamin D, and Alpha-Fetoprotein in Children with Chronic Hepatitis C: Can They Predict Treatment Response?

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Mohamed Ahmed Khedr

2015-01-01

Full Text Available Background & Aims. The currently available treatment for chronic hepatitis C (CHC in children is costly and with much toxicity. So, predicting the likelihood of response before starting therapy is important. Methods. Serum adiponectin, vitamin D, and alpha-fetoprotein (AFP were measured before starting pegylated-interferon/ribavirin therapy for 50 children with CHC. Another 21 healthy children were recruited as controls. Results. Serum adiponectin, vitamin D, and AFP were higher in the CHC group than healthy controls (p<0.0001, p=0.071, and p=0.87, resp.. In univariate analysis, serum adiponectin was significantly higher in responders than nonresponders (p<0.0001 and at a cutoff value ≥8.04 ng/mL it can predict treatment response by 77.8% sensitivity and 92.9% specificity, while both AFP and viremia were significantly lower in responders than nonresponders, p<0.0001 and p=0.0003, respectively, and at cutoff values ≤3.265 ng/mL and ≤235,384 IU/mL, respectively, they can predict treatment response with a sensitivity of 83.3% for both and specificity of 85.7% and 78.6%, respectively. In multivariate analysis, adiponectin was found to be the only independent predictor of treatment response (p=0.044. Conclusions. The pretreatment serum level of adiponectin can predict the likelihood of treatment response, thus avoiding toxicities for those unlikely to respond to therapy.

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

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.

Serum deprivation induces glucose response and intercellular coupling in human pancreatic adenocarcinoma PANC-1 cells.

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Hiram-Bab, Sahar; Shapira, Yuval; Gershengorn, Marvin C; Oron, Yoram

2012-03-01

This study aimed to investigate whether the previously described differentiating islet-like aggregates of human pancreatic adenocarcinoma cells (PANC-1) develop glucose response and exhibit intercellular communication. Fura 2-loaded PANC-1 cells in serum-free medium were assayed for changes in cytosolic free calcium ([Ca]i) induced by depolarization, tolbutamide inhibition of K(ATP) channels, or glucose. Dye transfer, assayed by confocal microscopy or by FACS, was used to detect intercellular communication. Changes in messenger RNA (mRNA) expression of genes of interest were assessed by quantitative real-time polymerase chain reaction. Proliferation was assayed by the MTT method. Serum-deprived PANC-1 cell aggregates developed [Ca]i response to KCl, tolbutamide, or glucose. These responses were accompanied by 5-fold increase in glucokinase mRNA level and, to a lesser extent, of mRNAs for K(ATP) and L-type calcium channels, as well as increase in mRNA levels of glucagon and somatostatin. Trypsin, a proteinase-activated receptor 2 agonist previously shown to enhance aggregation, modestly improved [Ca]i response to glucose. Glucose-induced coordinated [Ca]i oscillations and dye transfer demonstrated the emergence of intercellular communication. These findings suggest that PANC-1 cells, a pancreatic adenocarcinoma cell line, can be induced to express a differentiated phenotype in which cells exhibit response to glucose and form a functional syncytium similar to those observed in pancreatic islets.

Clinical utility of serum folate measurement in tertiary care patients: Argument for revising reference range for serum folate from 3.0 ng/mL to 13.0 ng/mL

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Gurmukh Singh

2015-04-01

Full Text Available Objective: Assess the need for folate testing, frequency of corrective action, and determine reference level for serum folate. Methods: Serum folate levels in 5313 samples from 4448 patients, and clinical data were reviewed for patient characteristics and for (a evidence of corrective action in patients with serum folate values 25.7 ng/mL. Results: The prevalence of serum folate levels, in patients, 25.7 ng/mL the sample was collected after supplementation with folic acid. Of the 128 patients with serum folate 60% of the patients. Since serum folate levels ≥13.0 ng/mL are needed for optimal prevention of neural tube defects in the embryo/fetus, we propose that normal serum folate level should be designated to be ≥13.0 ng/mL. Keywords: Serum folate, Prevalence of folate deficiency, Neural tube defects, Optimum serum folate level, Utility of folate testing

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.

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.

Effect of HFE gene polymorphism on sustained virological response in patients with chronic hepatitis C and elevated serum ferritin.

Science.gov (United States)

Coelho-Borges, Silvia; Cheinquer, Hugo; Wolff, Fernando Herz; Cheinquer, Nelson; Krug, Luciano; Ashton-Prolla, Patricia

2012-01-01

Abnormal serum ferritin levels are found in approximately 20%-30% of the patients with chronic hepatitis C and are associated with a lower response rate to interferon therapy. To determine if the presence of HFE gene mutations had any effect on the sustained virological response rate to interferon based therapy in chronic hepatitis C patients with elevated serum ferritin. A total of 44 treatment naÏve patients with histologically demonstrated chronic hepatitis C, all infected with hepatitis C virus genotype non-1 (38 genotype 3; 6 genotype 2) and serum ferritin above 500 ng/mL were treated with interferon (3 MU, 3 times a week) and ribavirin (1.000 mg, daily) for 24 weeks. Sustained virological response was defined as negative qualitative HCV-RNA more than 24 weeks after the end of treatment. Serum HCV-RNA was measured by qualitative in house polymerase chain reaction with a limit of detection of 200 IU/mL. HFE gene mutation was detected using restriction-enzyme digestion with RsaI (C282Y mutation analysis) and BclI (H63D mutation analysis) in 16 (37%) patients, all heterozygous (11 H63D, 2 C282Y and 3 both). Sustained virological response was achieved in 0 of 16 patients with HFE gene mutations and 11 (41%) of 27 patients without HFE gene mutations (P = 0.002; exact Fisher test). Heterozigozity for H63D and/or C282Y HFE gene mutation predicts absence of sustained virological response to combination treatment with interferon and ribavirin in patients with chronic hepatitis C, non-1 genotype and serum ferritin levels above 500 ng/mL.

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)

Neuronal spike-train responses in the presence of threshold noise.

Science.gov (United States)

Coombes, S; Thul, R; Laudanski, J; Palmer, A R; Sumner, C J

2011-03-01

The variability of neuronal firing has been an intense topic of study for many years. From a modelling perspective it has often been studied in conductance based spiking models with the use of additive or multiplicative noise terms to represent channel fluctuations or the stochastic nature of neurotransmitter release. Here we propose an alternative approach using a simple leaky integrate-and-fire model with a noisy threshold. Initially, we develop a mathematical treatment of the neuronal response to periodic forcing using tools from linear response theory and use this to highlight how a noisy threshold can enhance downstream signal reconstruction. We further develop a more general framework for understanding the responses to large amplitude forcing based on a calculation of first passage times. This is ideally suited to understanding stochastic mode-locking, for which we numerically determine the Arnol'd tongue structure. An examination of data from regularly firing stellate neurons within the ventral cochlear nucleus, responding to sinusoidally amplitude modulated pure tones, shows tongue structures consistent with these predictions and highlights that stochastic, as opposed to deterministic, mode-locking is utilised at the level of the single stellate cell to faithfully encode periodic stimuli.

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

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.

Study of the binding of {sup 114m}In radiotracer to human serum components by ultrafiltration and chromatography

Energy Technology Data Exchange (ETDEWEB)

Hulle, M. van; De Cremer, K.; Cornelis, R. [Ghent Rijksuniversiteit (Belgium). Lab. for Analytical Chemistry

2000-10-01

The chemical speciation of indium in serum was studied. Ultrafiltration was used to investigate the influence of several buffer systems on the binding characteristics of indium in serum and to study the association of indium with transferrin and albumin. This was performed by means of batch incubation experiments with a {sup 114m}In tracer. Different buffer systems were investigated. A series of bicarbonate, Tris:HCl and HEPES buffers were found to fit for this purpose. Phosphate buffer was not suitable, as it is capable of disrupting the binding between indium and transferrin. Batch ultrafiltration experiments with {sup 114m}In incubated solutions of transferrin and albumin showed that both proteins are capable of binding indium to a high degree. Three chromatographic techniques (SEC, AEC, AC) were used to study the different chemically active species of indium in serum. It is concluded that next to transferrin, albumin is also responsible for the binding and transport of indium in serum. (orig.)

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.

A novel quantification strategy of transferrin and albumin in human serum by species-unspecific isotope dilution laser ablation inductively coupled plasma mass spectrometry (ICP-MS)

Energy Technology Data Exchange (ETDEWEB)

Feng, Liuxing, E-mail: fenglx@nim.ac.cn; Zhang, Dan; Wang, Jun; Shen, Dairui; Li, Hongmei

2015-07-16

Highlights: • Species-unspecific ID-PAGE-LA-ICP-MS was used to quantify Alb and Tf in human serum. • Addition methods of species-unspecific {sup 34}S spike were evaluated. • Isotope change conditions were investigated to reach satisfactory “isotope equilibration”. • Human serum CRM (ERM-DA470k/IFCC) was used to validate the new arrangements. • The developed method offers potential for accurate quantification of protein by ID-PAGE-LA-ICP-MS. - Abstract: Species-specific (SS) isotope dilution analysis with gel electrophoresis (GE)-laser ablation (LA)-ICP-MS is a promising technique for the quantification of particular metal-binding proteins in biological samples. However, unavailable isotopically enriched spike and metal losses in GE separation are main limitations for SS-isotope dilution PAGE-LA-ICP-MS. In this study, we report for the first time the absolute quantification of transferrin (Tf) and albumin (Alb) in human serum by non-denaturing (native) GE combined with species-unspecific isotope dilution mass spectrometry (IDMS). In order to achieve a homogeneous distribution of both protein and isotope-enriched spike (simulated isotope equilibration), immersing the protein strips with {sup 34}S spike solution after gel electrophoresis was demonstrated to be an effective way of spike addition. Furthermore, effects of immersion time and {sup 34}S spike concentration were investigated to obtain optimal conditions of the post-electrophoresis isotope dilution method. The relative mass of spike and ablated sample (m{sub sp}/m{sub sam}) in IDMS equation was calculated by standard Tf and Alb proteins, which could be applied to the quantification of Tf and Alb in ERM-DA470k/IFCC for method confirmation. The results were in agreement with the certified value with good precision and small uncertainty (1.5–3%). In this method, species-specific spike protein is not necessary and the integrity of the heteroatom-protein could be maintained in sample preparation

A novel quantification strategy of transferrin and albumin in human serum by species-unspecific isotope dilution laser ablation inductively coupled plasma mass spectrometry (ICP-MS)

International Nuclear Information System (INIS)

Feng, Liuxing; Zhang, Dan; Wang, Jun; Shen, Dairui; Li, Hongmei

2015-01-01

Highlights: • Species-unspecific ID-PAGE-LA-ICP-MS was used to quantify Alb and Tf in human serum. • Addition methods of species-unspecific 34 S spike were evaluated. • Isotope change conditions were investigated to reach satisfactory “isotope equilibration”. • Human serum CRM (ERM-DA470k/IFCC) was used to validate the new arrangements. • The developed method offers potential for accurate quantification of protein by ID-PAGE-LA-ICP-MS. - Abstract: Species-specific (SS) isotope dilution analysis with gel electrophoresis (GE)-laser ablation (LA)-ICP-MS is a promising technique for the quantification of particular metal-binding proteins in biological samples. However, unavailable isotopically enriched spike and metal losses in GE separation are main limitations for SS-isotope dilution PAGE-LA-ICP-MS. In this study, we report for the first time the absolute quantification of transferrin (Tf) and albumin (Alb) in human serum by non-denaturing (native) GE combined with species-unspecific isotope dilution mass spectrometry (IDMS). In order to achieve a homogeneous distribution of both protein and isotope-enriched spike (simulated isotope equilibration), immersing the protein strips with 34 S spike solution after gel electrophoresis was demonstrated to be an effective way of spike addition. Furthermore, effects of immersion time and 34 S spike concentration were investigated to obtain optimal conditions of the post-electrophoresis isotope dilution method. The relative mass of spike and ablated sample (m sp /m sam ) in IDMS equation was calculated by standard Tf and Alb proteins, which could be applied to the quantification of Tf and Alb in ERM-DA470k/IFCC for method confirmation. The results were in agreement with the certified value with good precision and small uncertainty (1.5–3%). In this method, species-specific spike protein is not necessary and the integrity of the heteroatom-protein could be maintained in sample preparation process. Moreover, the

Fast computation with spikes in a recurrent neural network

International Nuclear Information System (INIS)

Jin, Dezhe Z.; Seung, H. Sebastian

2002-01-01

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

Theta frequency background tunes transmission but not summation of spiking responses.

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Dhanya Parameshwaran

Full Text Available Hippocampal neurons are known to fire as a function of frequency and phase of spontaneous network rhythms, associated with the animal's behaviour. This dependence is believed to give rise to precise rate and temporal codes. However, it is not well understood how these periodic membrane potential fluctuations affect the integration of synaptic inputs. Here we used sinusoidal current injection to the soma of CA1 pyramidal neurons in the rat brain slice to simulate background oscillations in the physiologically relevant theta and gamma frequency range. We used a detailed compartmental model to show that somatic current injection gave comparable results to more physiological synaptically driven theta rhythms incorporating excitatory input in the dendrites, and inhibitory input near the soma. We systematically varied the phase of synaptic inputs with respect to this background, and recorded changes in response and summation properties of CA1 neurons using whole-cell patch recordings. The response of the cell was dependent on both the phase of synaptic inputs and frequency of the background input. The probability of the cell spiking for a given synaptic input was up to 40% greater during the depolarized phases between 30-135 degrees of theta frequency current injection. Summation gain on the other hand, was not affected either by the background frequency or the phasic afferent inputs. This flat summation gain, coupled with the enhanced spiking probability during depolarized phases of the theta cycle, resulted in enhanced transmission of summed inputs during the same phase window of 30-135 degrees. Overall, our study suggests that although oscillations provide windows of opportunity to selectively boost transmission and EPSP size, summation of synaptic inputs remains unaffected during membrane oscillations.

Effect of HFE gene polymorphism on sustained virological response in patients with chronic hepatitis C and elevated serum ferritin

Directory of Open Access Journals (Sweden)

Silvia Coelho-Borges

2012-03-01

Full Text Available CONTEXT: Abnormal serum ferritin levels are found in approximately 20%-30% of the patients with chronic hepatitis C and are associated with a lower response rate to interferon therapy. OBJECTIVE: To determine if the presence of HFE gene mutations had any effect on the sustained virological response rate to interferon based therapy in chronic hepatitis C patients with elevated serum ferritin. METHODS: A total of 44 treatment naÏve patients with histologically demonstrated chronic hepatitis C, all infected with hepatitis C virus genotype non-1 (38 genotype 3; 6 genotype 2 and serum ferritin above 500 ng/mL were treated with interferon (3 MU, 3 times a week and ribavirin (1.000 mg, daily for 24 weeks. RESULTS: Sustained virological response was defined as negative qualitative HCV-RNA more than 24 weeks after the end of treatment. Serum HCV-RNA was measured by qualitative in house polymerase chain reaction with a limit of detection of 200 IU/mL. HFE gene mutation was detected using restriction-enzyme digestion with RsaI (C282Y mutation analysis and BclI (H63D mutation analysis in 16 (37% patients, all heterozygous (11 H63D, 2 C282Y and 3 both. Sustained virological response was achieved in 0 of 16 patients with HFE gene mutations and 11 (41% of 27 patients without HFE gene mutations (P = 0.002; exact Fisher test. CONCLUSION: Heterozigozity for H63D and/or C282Y HFE gene mutation predicts absence of sustained virological response to combination treatment with interferon and ribavirin in patients with chronic hepatitis C, non-1 genotype and serum ferritin levels above 500 ng/mL.

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...

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...

Metabolic changes in serum metabolome in response to a meal.

Science.gov (United States)

Shrestha, Aahana; Müllner, Elisabeth; Poutanen, Kaisa; Mykkänen, Hannu; Moazzami, Ali A

2017-03-01

The change in serum metabolic response from fasting state to postprandial state provides novel insights into the impact of a single meal on human metabolism. Therefore, this study explored changes in serum metabolite profile after a single meal. Nineteen healthy postmenopausal women with normal glucose tolerance participated in the study. They received a meal consisting of refined wheat bread (50 g carbohydrates, 9 g protein, 4.2 g fat and 2.7 g dietary fibre), 40 g cucumber and 300 mL noncaloric orange drink. Blood samples were collected at fasting and five postprandial time points. Metabolic profile was measured by nuclear magnetic resonance and targeted liquid chromatography-mass spectrometry. Changes over time were assessed with multivariate models and ANOVA, with baseline as control. The metabolomic analyses demonstrated alterations in phospholipids, amino acids and their breakdown products, glycolytic products, acylcarnitines and ketone bodies after a single meal. More specifically, phosphatidylcholines, lysophosphatidylcholines and citrate displayed an overall declining pattern, while leucine, isoleucine, methionine and succinate increased initially but declined thereafter. A sharp decline in acylcarnitines and ketone bodies and increase in glycolytic products postprandially suggest a switch in the body's energy source from β-oxidation to glycolysis. Moreover, individuals with relatively high postprandial insulin responses generated a higher postprandial leucine responses compared to participants with lower insulin responses. The study demonstrated complex changes from catabolic to anabolic metabolism after a meal and indicated that the extent of postprandial responses is different between individuals with high and low insulin response.

Force sensor in simulated skin and neural model mimic tactile SAI afferent spiking response to ramp and hold stimuli.

Science.gov (United States)

Kim, Elmer K; Wellnitz, Scott A; Bourdon, Sarah M; Lumpkin, Ellen A; Gerling, Gregory J

2012-07-23

The next generation of prosthetic limbs will restore sensory feedback to the nervous system by mimicking how skin mechanoreceptors, innervated by afferents, produce trains of action potentials in response to compressive stimuli. Prior work has addressed building sensors within skin substitutes for robotics, modeling skin mechanics and neural dynamics of mechanotransduction, and predicting response timing of action potentials for vibration. The effort here is unique because it accounts for skin elasticity by measuring force within simulated skin, utilizes few free model parameters for parsimony, and separates parameter fitting and model validation. Additionally, the ramp-and-hold, sustained stimuli used in this work capture the essential features of the everyday task of contacting and holding an object. This systems integration effort computationally replicates the neural firing behavior for a slowly adapting type I (SAI) afferent in its temporally varying response to both intensity and rate of indentation force by combining a physical force sensor, housed in a skin-like substrate, with a mathematical model of neuronal spiking, the leaky integrate-and-fire. Comparison experiments were then conducted using ramp-and-hold stimuli on both the spiking-sensor model and mouse SAI afferents. The model parameters were iteratively fit against recorded SAI interspike intervals (ISI) before validating the model to assess its performance. Model-predicted spike firing compares favorably with that observed for single SAI afferents. As indentation magnitude increases (1.2, 1.3, to 1.4 mm), mean ISI decreases from 98.81 ± 24.73, 54.52 ± 6.94, to 41.11 ± 6.11 ms. Moreover, as rate of ramp-up increases, ISI during ramp-up decreases from 21.85 ± 5.33, 19.98 ± 3.10, to 15.42 ± 2.41 ms. Considering first spikes, the predicted latencies exhibited a decreasing trend as stimulus rate increased, as is observed in afferent recordings. Finally, the SAI afferent's characteristic response

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.

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.

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.

Sensitivity and specificity of a real-time reverse transcriptase polymerase chain reaction detecting feline coronavirus mutations in effusion and serum/plasma of cats to diagnose feline infectious peritonitis.

Science.gov (United States)

Felten, Sandra; Leutenegger, Christian M; Balzer, Hans-Joerg; Pantchev, Nikola; Matiasek, Kaspar; Wess, Gerhard; Egberink, Herman; Hartmann, Katrin

2017-08-02

Feline coronavirus (FCoV) exists as two pathotypes, and FCoV spike gene mutations are considered responsible for the pathotypic switch in feline infectious peritonitis (FIP) pathogenesis. The aim of this study was to evaluate sensitivity and specificity of a real-time reverse transcriptase polymerase chain reaction (RT-PCR) specifically designed to detect FCoV spike gene mutations at two nucleotide positions. It was hypothesized that this test would correctly discriminate feline infectious peritonitis virus (FIPV) and feline enteric coronavirus (FECV). The study included 63 cats with signs consistent with FIP. FIP was confirmed in 38 cats. Twenty-five control cats were definitively diagnosed with a disease other than FIP. Effusion and/or serum/plasma samples were examined by real-time RT-PCR targeting the two FCoV spike gene fusion peptide mutations M1058 L and S1060A using an allelic discrimination approach. Sensitivity, specificity, negative and positive predictive values including 95% confidence intervals (95% CI) were calculated. FIPV was detected in the effusion of 25/59 cats, one of them being a control cat with chronic kidney disease. A mixed population of FIPV/FECV was detected in the effusion of 2/59 cats; all of them had FIP. RT-PCR was negative or the pathotype could not be determined in 34/59 effusion samples. In effusion, sensitivity was 68.6% (95% CI 50.7-83.2), specificity was 95.8% (95% CI 78.9-99.9). No serum/plasma samples were positive for FIPV. Although specificity of the test in effusions was high, one false positive result occurred. The use of serum/plasma cannot be recommended due to a low viral load in blood.

Quantitative and temporal analyses of murine antibody response in serum and gut secretions to infection with Giardia muris.

Science.gov (United States)

Snider, D P; Underdown, B J

1986-04-01

We analyzed the appearance and level of Giardia muris-specific antibody of immunoglobulin A (IgA), IgG, and IgM isotypes, at weekly intervals, over the course of a 7-week infection in BALB/c and C57BL/6 mice. Using sensitive immunoradiometric assays, we observed that IgA antibody was the only detectable anti-G. muris antibody in intestinal secretions throughout the course of infection. No secreted IgG or IgM anti-G. muris antibody was detected even in concentrated intestinal secretions. The expulsion of G. muris by the mice was associated closely with the appearance and increasing levels of secreted anti-G. muris IgA antibody. Both IgG and IgA serum antibody to G. muris were detected, but no serum IgM antibody was detected. Serum IgA and IgG anti-G. muris antibody remained at high levels up to 10 weeks following clearance of the parasite. An interesting observation indicated that serum IgA antibody to G. muris developed more slowly in response to infection than secreted IgA antibody. An analysis of the molecular weight distribution of total serum IgA in infected mice determined that infection produced a transient but significant shift in serum IgA to high-molecular-weight (greater than or equal to dimeric IgA) forms. The results indicate that a substantial IgA antibody response occurs in sera and in gut secretions of G. muris-resistant mice and that IgA antibody is the dominant and possibly the only effector antibody active in intestinal secretions during G. muris infection in mice.

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...

Imaging diagnosis of protein-losing enteropathy by 99mTc-labeled serum albumin

International Nuclear Information System (INIS)

Kashiwagi, Toru; Fukui, Hiroyuki; Jyokou, Takeshi

1990-01-01

Abdominal scintigraphy with intravenous injection of 99m Tc-labeled serum albumin was performed in 6 patients with protein-losing enteropathy (PLE) and 3 patients with nongastrointestinal tract disorders. In 3 out of 6 patients with PLE, abnormal radioactivity was observed in the ileum region 3 hours after injection, and thereafter clear colon image was obtained. In the remaining 3 patients, the colon was visualized 24 hours after injection. On the other hand, in all patients with nongastrointestinal tract disorders, no abnormal radioactivity was observed in the abdomen until 24 hours after injection. These results indicate that gastrointestinal protein loss could be demonstrated by scintigraphy with intravenously administered 99m Tc-labeled serum albumin. In one healthy subject, 99m Tc-labeled serum albumin was administered orally and abdominal scintigraphy was performed. Gastrointestinal tract image was only observed and no other image was demonstrated until 24 hours after oral administration. This result suggests that 99m Tc excreted into the gastrointestinal tract is not reabsorbed. Therefore, abdominal scintigraphy with 99m Tc-labeled serum albumin appears to be a simple and useful method for diagnosis of PLE. (author)

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

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.

Ghrelin Serum Concentrations Are Associated with Treatment Response During Lithium Augmentation of Antidepressants.

Science.gov (United States)

Ricken, Roland; Bopp, Sandra; Schlattmann, Peter; Himmerich, Hubertus; Bschor, Tom; Richter, Christoph; Elstner, Samuel; Stamm, Thomas J; Schulz-Ratei, Brigitte; Lingesleben, Alexandra; Reischies, Friedel M; Sterzer, Philipp; Borgwardt, Stefan; Bauer, Michael; Heinz, Andreas; Hellweg, Rainer; Lang, Undine E; Adli, Mazda

2017-09-01

Lithium augmentation of antidepressants is an effective strategy in treatment-resistant depression. The proteohormone ghrelin is thought to be involved in the pathophysiology of depression. The purpose of this study was to investigate the association of treatment response with the course of ghrelin levels during lithium augmentation. Ghrelin serum concentrations and severity of depression were measured in 85 acute depressive patients before and after 4 weeks of lithium augmentation. In a linear mixed model analysis, we found a significant effect of response*time interaction (F1.81=9.48; P=.0028): under treatment, ghrelin levels increased in nonresponders and slightly decreased in responders to lithium augmentation. The covariate female gender had a significant positive effect (F1.83=4.69; P=.033), whereas time, response, appetite, and body mass index (kg/m2) did not show any significant effect on ghrelin levels (P>.05). This is the first study showing that the course of ghrelin levels separates responders and nonresponders to lithium augmentation. Present results support the hypothesis that ghrelin serum concentrations might be involved in response to pharmacological treatment of depression. © The Author 2017. Published by Oxford University Press on behalf of CINP.

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.

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

Directory of Open Access Journals (Sweden)

Bertrand Fontaine

2014-04-01

Full Text Available Neurons encode information in sequences of spikes, which are triggered when their membrane potential crosses a threshold. In vivo, the spiking threshold displays large variability suggesting that threshold dynamics have a profound influence on how the combined input of a neuron is encoded in the spiking. Threshold variability could be explained by adaptation to the membrane potential. However, it could also be the case that most threshold variability reflects noise and processes other than threshold adaptation. Here, we investigated threshold variation in auditory neurons responses recorded in vivo in barn owls. We found that spike threshold is quantitatively predicted by a model in which the threshold adapts, tracking the membrane potential at a short timescale. As a result, in these neurons, slow voltage fluctuations do not contribute to spiking because they are filtered by threshold adaptation. More importantly, these neurons can only respond to input spikes arriving together on a millisecond timescale. These results demonstrate that fast adaptation to the membrane potential captures spike threshold variability in vivo.

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

The coronavirus spike protein : mechanisms of membrane fusion and virion incorporation

NARCIS (Netherlands)

Bosch, B.J.

2004-01-01

The coronavirus spike protein is a membrane-anchored glycoprotein responsible for virus-cell attachment and membrane fusion, prerequisites for a successful virus infection. In this thesis, two aspects are described regarding the molecular biology of the coronavirus spike protein: its membrane fusion

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

Science.gov (United States)

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

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.

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

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

Biophysical Neural Spiking, Bursting, and Excitability Dynamics in Reconfigurable Analog VLSI.

Science.gov (United States)

Yu, T; Sejnowski, T J; Cauwenberghs, G

2011-10-01

We study a range of neural dynamics under variations in biophysical parameters underlying extended Morris-Lecar and Hodgkin-Huxley models in three gating variables. The extended models are implemented in NeuroDyn, a four neuron, twelve synapse continuous-time analog VLSI programmable neural emulation platform with generalized channel kinetics and biophysical membrane dynamics. The dynamics exhibit a wide range of time scales extending beyond 100 ms neglected in typical silicon models of tonic spiking neurons. Circuit simulations and measurements show transition from tonic spiking to tonic bursting dynamics through variation of a single conductance parameter governing calcium recovery. We similarly demonstrate transition from graded to all-or-none neural excitability in the onset of spiking dynamics through the variation of channel kinetic parameters governing the speed of potassium activation. Other combinations of variations in conductance and channel kinetic parameters give rise to phasic spiking and spike frequency adaptation dynamics. The NeuroDyn chip consumes 1.29 mW and occupies 3 mm × 3 mm in 0.5 μm CMOS, supporting emerging developments in neuromorphic silicon-neuron interfaces.

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.

Occult abnormal pregnancies after first post-embryo transfer serum beta-human chorionic gonadotropin levels of 1.0-5.0 mIU/mL.

Science.gov (United States)

Maslow, Bat-Sheva L; Bartolucci, Alison; Sueldo, Carolina; Engmann, Lawrence; Benadiva, Claudio; Nulsen, John C

2016-04-01

To assess the occult pregnancy rate after "negative" first post-embryo transfer (ET) serum β-hCG results. Two-part retrospective cohort study and nested case series. University-based fertility center. A total of 1,571 negative first post-ET serum β-hCG results were included in the study; 1,326 results (primary cohort, June 2009-December 2013) were initially reported as <5 mIU/mL and 245 results (secondary cohort, January 2014-March 2015) were reported as discrete values from 1.0 to 5.0 mIU/mL. None. Rates of occult pregnancy, ectopic pregnancy, and complications after negative first post-ET serum β-hCG results. A total of 88.8% (1,178/1,326) of the negative first post-ET results reported as <5 were actually <1.0 mIU/mL. Occult pregnancy was incidentally identified in 1.2% (12/1,041) of subjects with follow-up. Six had ectopic pregnancies, and seven experienced serious complications; 11 (91.7%) of the 12 occult pregnancies had a first post-ET serum β-hCG level of 1.0-5.0 mIU/mL and 1 (8.3%) <1.0 mIU/mL. All pregnancies with serious complications had initial β-hCG levels of 1.0-5.0 mIU/mL. Of the 245 results reported as discreet values, occult pregnancies were diagnosed in 5.5% (9/163) of subjects with follow-up. One had an ectopic pregnancy, which was treated with methotrexate. There were no serious complications in the secondary cohort. The majority of negative first post-ET serum β-hCG levels are <1.0 mIU/mL. Results from 1.0 to 5.0 mIU/mL may fail to exclude abnormal pregnancy and are associated with poor outcomes compared with β-hCG levels <1.0 mIU/mL. Serial serum β-hCG may be warranted in this population. Copyright © 2016 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Reproducibility of the serum lipid response to coffee oil in healthy volunteers

Directory of Open Access Journals (Sweden)

Katan Martijn B

2003-10-01

Full Text Available Abstract Background Humans and animals show a certain consistency in the response of their serum lipids to fat-modified diets. This may indicate a genetic basis underlying this response. Coffee oil might be used as a model substance to investigate which genes determine differences in the serum lipid response. Before carrying out such studies our objective was to investigate to what extent the effect of coffee oil on serum lipid concentrations is reproducible within subjects. Methods The serum lipid response of 32 healthy volunteers was measured twice in separate five-week periods in which coffee oil was administered (69 mg cafestol / day. Results Total cholesterol levels increased by 24% in period 1 (range:0;52% and 18% in period 2 (1;48%, LDL cholesterol by 29 % (-9;71% and 20% (-12;57%, triglycerides by 66% (16;175% and 58% (-13;202%, and HDL cholesterol did not change significantly: The range of the HDL response was -19;25% in period 1 and -20;33% in period 2. The correlation between the two responses was 0.20 (95%CI -0.16, 0.51 for total cholesterol, 0.16 (95%CI -0.20, 0.48 for LDL, 0.67 (95%CI 0.42, 0.83 for HDL, and 0.77 (95%CI 0.56, 0.88 for triglycerides. Conclusions The responses of total and LDL cholesterol to coffee oil were poorly reproducible within subjects. The responses of HDL and triglycerides, however, appeared to be highly reproducible. Therefore, investigating the genetic sources of the variation in the serum-lipid response to coffee oil is more promising for HDL and triglycerides.

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.

Egr-1 and serum response factor are involved in growth factors- and serum-mediated induction of E2-EPF UCP expression that regulates the VHL-HIF pathway.

Science.gov (United States)

Lim, Jung Hwa; Jung, Cho-Rok; Lee, Chan-Hee; Im, Dong-Soo

2008-11-01

E2-EPF ubiquitin carrier protein (UCP) has been shown to be highly expressed in common human cancers and target von Hippel-Lindau (VHL) for proteosomal degradation in cells, thereby stabilizing hypoxia-inducible factor (HIF)-1alpha. Here, we investigated cellular factors that regulate the expression of UCP gene. Promoter deletion assay identified binding sites for early growth response-1 (Egr-1) and serum response factor (SRF) in the UCP promoter. Hepatocyte or epidermal growth factor (EGF), or phorbol 12-myristate 13-acetate induced UCP expression following early induction of Egr-1 expression in HeLa cells. Serum increased mRNA and protein levels of SRF and UCP in the cell. By electrophoretic mobility shift and chromatin immunoprecipitation assays, sequence-specific DNA-binding of Egr-1 and SRF to the UCP promoter was detected in nuclear extracts from HeLa cells treated with EGF and serum, respectively. Overexpression of Egr-1 or SRF increased UCP expression. RNA interference-mediated depletion of endogenous Egr-1 or SRF impaired EGF- or serum-mediated induction of UCP expression, which was required for cancer cell proliferation. Systemic delivery of EGF into mice also increased UCP expression following early induction of Egr-1 expression in mouse liver. The induced UCP expression by the growth factors or serum increased HIF-1alpha protein level under non-hypoxic conditions, suggesting that the Egr-1/SRF-UCP-VHL pathway is in part responsible for the increased HIF-1alpha protein level in vitro and in vivo. Thus, growth factors and serum induce expression of Egr-1 and SRF, respectively, which in turn induces UCP expression that positively regulates cancer cell growth.

Soil fluoride spiking effects on olive trees (Olea europaea L. cv. Chemlali).

Science.gov (United States)

Zouari, M; Ben Ahmed, C; Fourati, R; Delmail, D; Ben Rouina, B; Labrousse, P; Ben Abdallah, F

2014-10-01

A pot experiment under open air conditions was carried out to investigate the uptake, accumulation and toxicity effects of fluoride in olive trees (Olea europaea L.) grown in a soil spiked with inorganic sodium fluoride (NaF). Six different levels (0, 20, 40, 60, 80 and 100mM NaF) of soil spiking were applied through NaF to irrigation water. At the end of the experiment, total fluoride content in soil was 20 and 1770mgFkg(-1) soil in control and 100mM NaF treatments, respectively. The comparative distribution of fluoride partitioning among the different olive tree parts showed that the roots accumulated the most fluoride and olive fruits were minimally affected by soil NaF spiking as they had the lowest fluoride content. In fact, total fluoride concentration varied between 12 and 1070µgFg(-1) in roots, between 9 and 570µgFg(-1) in shoots, between 12 and 290µgFg(-1) in leaves, and between 10 and 29µgFg(-1) in fruits, respectively for control and 100mM NaF treatments. Indeed, the fluoride accumulation pattern showed the following distribution: roots>shoots>leaves>fruits. On the other hand, fluoride toxicity symptoms such as leaf necrosis and leaf drop appeared only in highly spiked soils (60, 80 and 100mM NaF). Copyright © 2014 Elsevier Inc. All rights reserved.

Development of on-off spiking in superior paraolivary nucleus neurons of the mouse

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Felix, Richard A.; Vonderschen, Katrin; Berrebi, Albert S.

2013-01-01

The superior paraolivary nucleus (SPON) is a prominent cell group in the auditory brain stem that has been increasingly implicated in representing temporal sound structure. Although SPON neurons selectively respond to acoustic signals important for sound periodicity, the underlying physiological specializations enabling these responses are poorly understood. We used in vitro and in vivo recordings to investigate how SPON neurons develop intrinsic cellular properties that make them well suited for encoding temporal sound features. In addition to their hallmark rebound spiking at the stimulus offset, SPON neurons were characterized by spiking patterns termed onset, adapting, and burst in response to depolarizing stimuli in vitro. Cells with burst spiking had some morphological differences compared with other SPON neurons and were localized to the dorsolateral region of the nucleus. Both membrane and spiking properties underwent strong developmental regulation, becoming more temporally precise with age for both onset and offset spiking. Single-unit recordings obtained in young mice demonstrated that SPON neurons respond with temporally precise onset spiking upon tone stimulation in vivo, in addition to the typical offset spiking. Taken together, the results of the present study demonstrate that SPON neurons develop sharp on-off spiking, which may confer sensitivity to sound amplitude modulations or abrupt sound transients. These findings are consistent with the proposed involvement of the SPON in the processing of temporal sound structure, relevant for encoding communication cues. PMID:23515791

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

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

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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.

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

Science.gov (United States)

Zhu, Xin-Xin; Li, Qiao-Yun; Shen, Chun-Cai; Duan, Zong-Biao; Yu, Dong-Yan; Niu, Ji-Shan; Ni, Yong-Jing; Jiang, Yu-Mei

2016-01-01

Wheat (Triticum aestivum L.) spike development is the foundation for grain yield. We obtained a novel wheat mutant, dms, characterized as dwarf, multi-pistil and sterility. Although the genetic changes are not clear, the heredity of traits suggests that a recessive gene locus controls the two traits of multi-pistil and sterility in self-pollinating populations of the medium plants (M), such that the dwarf genotype (D) and tall genotype (T) in the progeny of the mutant are ideal lines for studies regarding wheat spike development. The objective of this study was to explore the molecular basis for spike abnormalities of dwarf genotype. Four unigene libraries were assembled by sequencing the mRNAs of the super-bulked differentiating spikes and stem tips of the D and T plants. Using integrative analysis, we identified 419 genes highly expressed in spikes, including nine typical homeotic genes of the MADS-box family and the genes TaAP2, TaFL and TaDL. We also identified 143 genes that were significantly different between young spikes of T and D, and 26 genes that were putatively involved in spike differentiation. The result showed that the expression levels of TaAP1-2, TaAP2, and other genes involved in the majority of biological processes such as transcription, translation, cell division, photosynthesis, carbohydrate transport and metabolism, and energy production and conversion were significantly lower in D than in T. We identified a set of genes related to wheat floral organ differentiation, including typical homeotic genes. Our results showed that the major causal factors resulting in the spike abnormalities of dms were the lower expression homeotic genes, hormonal imbalance, repressed biological processes, and deficiency of construction materials and energy. We performed a series of studies on the homeotic genes, however the other three causal factors for spike abnormal phenotype of dms need further study.

On-site preparation of technetium-99m labeled human serum albumin for clinical application

International Nuclear Information System (INIS)

Wang Yuhfeng; Chuang Meihua; Cham Thauming; Chung Meiing; Chiu Jainnshiun

2007-01-01

Technetium-99m labeled human serum albumin (Tc-99m HSA) is an important radiopharmaceutical for clinical applications, such as cardiac function tests or protein-losing gastroenteropathy assessment. However, because of transfusion-induced infectious diseases, the safety of serum products is a serious concern. In this context, serum products acquired from patients themselves are the most ideal tracer. However, the development of rapid separation and easy clinical labeling methods is not yet well established. Under such situation, products from the same ethnic group or country are now recommended by the World Health Organization as an alternative preparation. This article describes the on-site preparation of Tc-99m HSA from locally supplied serum products. Different formulations were prepared and the labeling efficiency and stability were examined. Radio-labeling efficiencies were more than 90% in all preparation protocols, except for one that omitted the stannous solution. The most cost-effective protocol contained HSA 0.1 mg, treated with stannous fluoride 0.2 mg, and mixed with Tc-99m pertechnetate 30 mCi. A biodistribution study was performed in rats using a gamma camera immediately after intravenous administration of radiolabeled HSA. Tissue/organ uptake was obtained by measuring the radioactivity in organs after sacrificing the rats at timed intervals. The biologic half-life was about 32 min, determined from sequential venous blood collections. These data indicate that our preparation of Tc-99m HSA is useful and potentially applicable clinically. In addition, this on-site preparation provides the possibility of labeling a patient's own serum for subsequent clinical application. (author)

A microculture system for the measurement of antigen-induced murine lymphocyte proliferation: advantages of 5% horse serum and 5 X 10(-5) M mercaptoethanol.

Science.gov (United States)

Brummer, E; Vris, T W; Lawrence, H S

1977-01-01

Short term microculture systems which measure murine lymphocyte proliferative responses to mitogens are well established. We demonstrate here that these microculture methods are not suitable for antigen-induced responses because of the high levels of murine lymphocyte proliferation in control cultures associated with the use of fetal calf serum or human serum. We also show that this problem can be eliminated with the use of a combination of 5% horse serum and 5 X 10(-5) M mercaptoethanol. We describe an antigen-induced murine lymphocyte proliferation microculture system in which good stimulation indices are achieved and the lymphocyte proliferation in control cultures remain at a low level throughout the 7 day culture period.

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.

The Mechanisms of Repetitive Spike Generation in an Axonless Retinal Interneuron

Directory of Open Access Journals (Sweden)

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.

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.

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.

Model-based decoding, information estimation, and change-point detection techniques for multineuron spike trains.

Science.gov (United States)

Pillow, Jonathan W; Ahmadian, Yashar; Paninski, Liam

2011-01-01

One of the central problems in systems neuroscience is to understand how neural spike trains convey sensory information. Decoding methods, which provide an explicit means for reading out the information contained in neural spike responses, offer a powerful set of tools for studying the neural coding problem. Here we develop several decoding methods based on point-process neural encoding models, or forward models that predict spike responses to stimuli. These models have concave log-likelihood functions, which allow efficient maximum-likelihood model fitting and stimulus decoding. We present several applications of the encoding model framework to the problem of decoding stimulus information from population spike responses: (1) a tractable algorithm for computing the maximum a posteriori (MAP) estimate of the stimulus, the most probable stimulus to have generated an observed single- or multiple-neuron spike train response, given some prior distribution over the stimulus; (2) a gaussian approximation to the posterior stimulus distribution that can be used to quantify the fidelity with which various stimulus features are encoded; (3) an efficient method for estimating the mutual information between the stimulus and the spike trains emitted by a neural population; and (4) a framework for the detection of change-point times (the time at which the stimulus undergoes a change in mean or variance) by marginalizing over the posterior stimulus distribution. We provide several examples illustrating the performance of these estimators with simulated and real neural data.

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

NARCIS (Netherlands)

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

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

DETERMINATION OF MUSHROOM TOXIN ALPHA-AMANITIN IN SERUM BY LIQUID CHROMATOGRAPHY-MASS SPECTROMETRY AFTER SOLID-PHASE EXTRACTION

Directory of Open Access Journals (Sweden)

Maja Vujović

2015-03-01

Full Text Available Alpha-amanitin is a cyclic peptide which belongs to a large group of mushroom toxins known as amatoxins. Being responsible for the majority of fatal mushroom poisonings, they require rapid detection and excretion from the body fluids. In accordance with these requirements, a simple and an accurate method was developed for successful identification and quantification of alpha-amanitin in serum with electrospray liquid chromatography–mass spectrometry (LC-ESI-MS after collision-induced dissociation. The method conforms to the established International Conference on Harmonization Q2A/Q2B 1996 guidelines on the validation of analytical methods. Linearity, precision, extraction recovery and stability test on blank serum spiked with alpha-amanitin and stored in different conditions met the acceptance criteria. The obtained calibration curve was linear over the concentration range 5-100 ng/mL with a lower limit of quantification (LOQ of 5 ng/mL and limit of detection (LOD of 2.5 ng/mL. The mean intra- and inter-day precision and accuracy were 6.05% and less than ±15% of nominal values, respectively. The neutral solid phase extraction with copolymer hydrophilic–lipophilic balance cartridges was found optimal for sample preparation with the mean recovery of 91.94%. The proposed method demonstrated high sensitivity and selectivity which can be useful both for clinical and forensic toxicology analysis of alpha-amanitin at low concentrations.

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.

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

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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

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

Quantification of NS1 dengue biomarker in serum via optomagnetic nanocluster detection

DEFF Research Database (Denmark)

Antunes, Paula Soares Martins; Watterson, Daniel; Parmvi, Mattias

2015-01-01

Dengue is a tropical vector-borne disease without cure or vaccine that progressively spreads into regions with temperate climates. Diagnostic tools amenable to resource-limited settings would be highly valuable for epidemiologic control and containment during outbreaks. Here, we present a novel low......-cost automated biosensing platform for detection of dengue fever biomarker NS1 and demonstrate it on NS1 spiked in human serum. Magnetic nanoparticles (MNPs) are coated with high-affinity monoclonal antibodies against NS1 via bio-orthogonal Cu-free 'click' chemistry on an anti-fouling surface molecular...... method. The resulting automated dengue fever assay takes just 8 minutes, requires 6 μL of serum sample and shows a limit of detection of 25 ng/mL with an upper detection range of 20000 ng/mL. The technology holds a great potential to be applied to NS1 detection in patient samples. As the assay...

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.

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.

A defined network of fast-spiking interneurons in orbitofrontal cortex: responses to behavioral contingencies and ketamine administration

Directory of Open Access Journals (Sweden)

Michael C Quirk

2009-11-01

Full Text Available Orbitofrontal cortex (OFC is a region of prefrontal cortex implicated in the motivational control of behavior and in related abnormalities seen in psychosis and depression. It has been hypothesized that a critical mechanism in these disorders is the dysfunction of GABAergic interneurons that normally regulate prefrontal information processing. Here, we studied a subclass of interneurons isolated in rat OFC using extracellular waveform and spike train analysis. During performance of a goal-directed behavioral task, the firing of this class of putative fast-spiking (FS interneurons showed robust temporal correlations indicative of a functionally coherent network. FS cell activity also co-varied with behavioral response latency, a key indicator of motivational state. Systemic administration of ketamine, a drug that can mimic psychosis, preferentially inhibited this cell class. Together, these results support the idea that OFC-FS interneurons form a critical link in the regulation of motivation by prefrontal circuits during normal and abnormal brain and behavioral states.

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.

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.

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

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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.

CCS mRNA transcripts and serum CCS protein as copper marker in adults suffering inflammatory processes.

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Araya, Magdalena; Gutiérrez, Ricardo; Arredondo, Miguel

2014-08-01

The chaperone to Zn-Cu superoxide dismutase (CCS) has been postulated as a candidate copper indicator, changing in a consistent manner in induced and recovered copper deficiency, in experimental cell and animal models. In real life people have various conditions that may modify molecules acting as acute phase proteins, such as serum ceruloplasmin and copper concentration and could alter CCS responses. With the hypothesis that CCS mRNA transcripts and protein would be different in individuals suffering inflammatory processes in comparison to healthy individuals, we assessed adult individuals who, although not ill had conditions known to induce variable degrees of inflammation. Screening of 600 adults resulted in two study groups, formed on the basis of their clinical history and levels of serum C reactive protein (CRP): Group 1 (n = 61, mean (range) CRP = 0.9 (0.3-2.0 mg/dL) and Group 2 (n = 150, mean (range) CRP = 6.1 (4.3-8.7 mg/dL). Results showed that mRNA transcripts relative abundance was not different for CCS, MTIIA, TNF-alpha and Cu-Zn-SOD by group (p > 0.05, one way Anova), nor between sexes (p > 0.05, one way Anova). Distribution of CCS mRNA transcripts and CCS protein in serum did not show any differences or trends. Results disproved our hypothesis that CCS abundance of transcripts and CCS protein would be different in individuals suffering inflammatory processes, adding further support to the idea that CCS may be a copper marker.

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

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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.

Serum proBDNF/BDNF and response to fluvoxamine in drug-naïve first-episode major depressive disorder patients.

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Yoshimura, Reiji; Kishi, Taro; Hori, Hikaru; Atake, Kiyokazu; Katsuki, Asuka; Nakano-Umene, Wakako; Ikenouchi-Sugita, Atsuko; Iwata, Nakao; Nakamura, Jun

2014-01-01

We investigated the association between serum proBDNF, a precursor of brain-derived neurotrophic factor (BDNF), and response to fluvoxamine in patients with major depressive disorder (MDD) using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR): physically healthy and free of current alcohol or drug abuse, comorbid anxiety, or personality disorders. Fifty-one patients with MDD (M/F, 19:32; age, 38 ± 19 years) and 51 healthy controls (M/F, 22:29; age, 34 ± 17 years) were studied using DSM-IV-TR: physically healthy and free of current alcohol or drug abuse, comorbid anxiety, or personality disorders. Serum levels of proBDNF and MDNF were measured by sandwich enzyme-linked immunosorbent assay (ELISA). Serum mature BDNF levels in the MDD patients were significantly lower than those in the healthy controls (t = 3.046, p = 0.0018). On the other hand, no difference was found in serum proBDNF between the MDD patients and the healthy controls (t = -0.979, p = 0.833). A trend of negative correlation was found between baseline serum BDNF and baseline scores of the 17 items of the Hamilton Rating Scale for Depression (HAMD17) (r = -0.183, p = 0.071). No correlation was however found between HAMD17 scores and proBDNF at baseline (r = 0.092, p = 0.421). Furthermore, no correlation was observed between baseline HAMD17 scores and baseline proBDNF/BDNF (r = -0.130, p = 0.190). No changes were observed in serum levels of proBDNF and BDNF during the treatment periods. These results suggest that there is no association between serum proBDNF/BDNF and fluvoxamine response in MDD patients at least within 4 weeks of the treatment.

Clinical significance of determination of serum and urine β2-microglobulin (β2-m) in patients with Graves' disease

International Nuclear Information System (INIS)

Wang Luhua; Mai Mang; Ouyang Xiaoqing; Wang Shuhua; Lin Cen; Fang Linli

2005-01-01

Objective: To explore the relationship between the serum, urine contents of β 2 -m and serum thyroid hormones levels in patients with Graves' disease. Methods: Serum, urine β 2 -m contents (with RIA), serum FT 3 , FT 4 levels (with CLIA), TGA, TMA positive rates (with RIA) were determined in 82 patients with Graves' disease both before and after treatment as well as in 40 controls. Results: The serum and urine β 2 -m contents as well as the serum FT 3 , FT 4 levels in the 82 hyperthyroid patients before treatment were significantly higher than those in the controls (P 2 -m, FT 3 , FT 4 levels dropped to approaching normal (vs controls, P>0.05). In the 13 treatment failures, the levels remained significantly higher than those in controls (P 2 -m contents after treatment paralleled those of FT 3 , FT 4 levels. β 2 -m could be used as a diagnostic indicator for hyperthyroidism. (authors)

Synthesis of peptide templated copper nanoclusters for fluorometric determination of Fe(III) in human serum

International Nuclear Information System (INIS)

Tang, Ting; Ouyang, Jiang; Hu, Lanshuang; Guo, Linyan; Yang, Minghui; Chen, Xiang

2016-01-01

Copper nanoclusters (Cu-NCs) were prepared by reducing CuCl 2 with ascorbic acid in the presence of the short peptide template Cys-Cys-Cys-Asp-Leu. They were characterized by UV-vis absorption and fluorescence spectroscopy, transmission electron microscopy and X-ray photoelectron spectroscopy. The Cu-NCs have a size of ∼2 nm, can be well dispersed in water and are photostable. Their fluorescence (peaking at 425 nm under 365-nm excitation) is quenched by Fe(III) ions. Based on this finding, a sensitive and selective fluorescence assay for the detection of Fe(III) was developed. Under optimized conditions and a pH value of 2.0, the assay displays a linear response in the 0.05 to 30 μM Fe(III) concentration range, with a detection limit of 20 nM based on an S/N ratio of 3. The assay was successfully applied to the determination of Fe(III) in spiked human serum where is gave recoveries that ranged from 96.2 % to 98.3 %. (author)

Serum antibody responses by male and female C57Bl/6 mice infected with Giardia muris.

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Daniels, C W; Belosevic, M

1994-09-01

We compared the levels of serum antibodies in male and female C57Bl/6 mice during the primary and after challenge infection with Giardia muris. Male mice began passing cysts in their faeces earlier than females, and were shedding cysts for over 60 days, while females stopped shedding cysts by day 20 after infection. In both males and females there were significant increases in parasite-specific IgM 10 and 20 days after infection. No differences in parasite-specific serum IgA were observed until 40 days after infection. Parasite-specific IgG (whole) levels were elevated on days 20 and 40 in females, while males showed no significant increases. In addition, females had a much stronger IgG2b and IgG3 response than males. After challenge with either cysts or soluble parasite protein only the females had significant increases in specific anti-parasite IgG2b. Our data show differential ability of males and females to control the infection with G. muris is paralleled by a difference in the anti-parasite serum IgG response of the mice.

The Effects of Context and Attention on Spiking Activity in Human Early Visual Cortex.

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Self, Matthew W; Peters, Judith C; Possel, Jessy K; Reithler, Joel; Goebel, Rainer; Ris, Peterjan; Jeurissen, Danique; Reddy, Leila; Claus, Steven; Baayen, Johannes C; Roelfsema, Pieter R

2016-03-01

Here we report the first quantitative analysis of spiking activity in human early visual cortex. We recorded multi-unit activity from two electrodes in area V2/V3 of a human patient implanted with depth electrodes as part of her treatment for epilepsy. We observed well-localized multi-unit receptive fields with tunings for contrast, orientation, spatial frequency, and size, similar to those reported in the macaque. We also observed pronounced gamma oscillations in the local-field potential that could be used to estimate the underlying spiking response properties. Spiking responses were modulated by visual context and attention. We observed orientation-tuned surround suppression: responses were suppressed by image regions with a uniform orientation and enhanced by orientation contrast. Additionally, responses were enhanced on regions that perceptually segregated from the background, indicating that neurons in the human visual cortex are sensitive to figure-ground structure. Spiking responses were also modulated by object-based attention. When the patient mentally traced a curve through the neurons' receptive fields, the accompanying shift of attention enhanced neuronal activity. These results demonstrate that the tuning properties of cells in the human early visual cortex are similar to those in the macaque and that responses can be modulated by both contextual factors and behavioral relevance. Our results, therefore, imply that the macaque visual system is an excellent model for the human visual cortex.

The Effects of Context and Attention on Spiking Activity in Human Early Visual Cortex.

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Matthew W Self

2016-03-01

Full Text Available Here we report the first quantitative analysis of spiking activity in human early visual cortex. We recorded multi-unit activity from two electrodes in area V2/V3 of a human patient implanted with depth electrodes as part of her treatment for epilepsy. We observed well-localized multi-unit receptive fields with tunings for contrast, orientation, spatial frequency, and size, similar to those reported in the macaque. We also observed pronounced gamma oscillations in the local-field potential that could be used to estimate the underlying spiking response properties. Spiking responses were modulated by visual context and attention. We observed orientation-tuned surround suppression: responses were suppressed by image regions with a uniform orientation and enhanced by orientation contrast. Additionally, responses were enhanced on regions that perceptually segregated from the background, indicating that neurons in the human visual cortex are sensitive to figure-ground structure. Spiking responses were also modulated by object-based attention. When the patient mentally traced a curve through the neurons' receptive fields, the accompanying shift of attention enhanced neuronal activity. These results demonstrate that the tuning properties of cells in the human early visual cortex are similar to those in the macaque and that responses can be modulated by both contextual factors and behavioral relevance. Our results, therefore, imply that the macaque visual system is an excellent model for the human visual cortex.

Serum levels of insulin-like growth factor binding protein-1 and ovulatory responses to clomiphene citrate in women with polycystic ovarian disease.

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Tiitinen, A E; Laatikainen, T J; Seppälä, M T

1993-07-01

To study the serum levels of insulin, insulin-like growth factor I (IGF-I), and insulin-like growth factor binding protein-1 (IGFBP-1) in relation to clomiphene citrate (CC) responsiveness in women with polycystic ovarian disease (PCOD). Prospective. PATIENTS, SETTING: Twenty-three women with PCOD admitted consecutively to the University Infertility Clinic, a tertiary referral center. Blood samples were taken at fasting state and during oral glucose tolerance test (OGTT) for the determination of insulin, IGF-I, and IGFBP-1. A dose of 50 to 200 mg/d CC was given for ovulation induction. With CC treatment, ovulation was achieved in 13 of 23 PCOD patients. The IGFBP-1 concentration was lower in CC nonresponders than in CC responders (20.5 +/- 4.0 ng/mL versus 41.0 +/- 8.5 ng/mL) (P PCOD patients. Lean CC nonresponders (n = 7) had almost threefold lower serum IGFBP-1 levels than lean CC responders (n = 6) (24.0 +/- 3.1 ng/mL versus 61.8 +/- 8.6 ng/mL) (P PCOD patients, the IGFBP-1 levels were low irrespective of CC responsiveness (14.8 +/- 8.0 ng/mL versus 16.7 +/- 7.2 ng/mL). The differences remained during OGTT. The concentrations of IGF-I, insulin, sex hormone-binding globulin, LH, FSH, and androgens showed no significant differences between CC responders and nonresponders. There was an inverse correlation between serum insulin and IGFBP-1 levels in obese PCOD patients, whereas this was not seen in lean patients. In lean PCOD patients, low serum IGFBP-1 concentration is related to CC unresponsiveness by a mechanism unrelated to insulin.

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.

Information transmission with spiking Bayesian neurons

International Nuclear Information System (INIS)

Lochmann, Timm; Deneve, Sophie

2008-01-01

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

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

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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.

Timing intervals using population synchrony and spike timing dependent plasticity

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Wei Xu

2016-12-01

Full Text Available We present a computational model by which ensembles of regularly spiking neurons can encode different time intervals through synchronous firing. We show that a neuron responding to a large population of convergent inputs has the potential to learn to produce an appropriately-timed output via spike-time dependent plasticity. We explain why temporal variability of this population synchrony increases with increasing time intervals. We also show that the scalar property of timing and its violation at short intervals can be explained by the spike-wise accumulation of jitter in the inter-spike intervals of timing neurons. We explore how the challenge of encoding longer time intervals can be overcome and conclude that this may involve a switch to a different population of neurons with lower firing rate, with the added effect of producing an earlier bias in response. Experimental data on human timing performance show features in agreement with the model’s output.

Determination of carbamazepine in serum and saliva samples by high performance liquid chromatography with ultraviolet detection.

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Dordević, Snezana; Kilibarda, Vesna; Stojanović, Tomislav

2009-05-01

Carbamazepine is antiepileptic drug widely used for the treatment of epilepsy. Due to low therapeutic index of carbamazepine there is a need for routine measuring its concentrations in biological fluids. The aim of the study was to describe a method for concomitant determination of carbamazepine in the serum and saliva. Separation of the drug from matrix is achieved by reversed-phase chromatography on a C18 column, with a mobile phase of methanol-water-acetic acid (65:34:1) at a flow-rate of 1.0 ml/min. Detection was effected by ultra-violet absorption at 285 nm. The total run time was 5 min. Samples were prepared by alkaline extraction (pH 10) using chlorophorm. Calibration curves were in the range 0.1-5 microg/mL for serum and saliva samples. Mean recoveries of spiked serum and saliva were 97.59 and 92.30%, respectively. Limits of detection (LOD) of carbamazepine in serum and saliva were 0.166 and 0.178 microg/mL, respectively. Limits of quantification (LOQ) in the serum and saliva were 0.237 and 0.226 microg/mL, respectively. The method precision was carried out with coefficient of variation of 2.10% and 4.03% for the serum and saliva, respectively. The obtained data showed that there was a strong correlation between saliva and serum concentrations (r = 0.9481, p < 0.001). The method described here is rapid, precise, accurate and simple, and can be used for quantitative determination of carbamazepine in human serum and saliva after therapy applying. Saliva samples could be used as an alternative matrix for therapeutic drug monitoring of this antiepileptic drug.

Barbed micro-spikes for micro-scale biopsy

Science.gov (United States)

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

2005-06-01

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

Development of an electrothermal atomization laser-excited atomic fluorescence spectrometry procedure for direct measurements of arsenic in diluted serum.

Science.gov (United States)

Swart, D J; Simeonsson, J B

1999-11-01

A procedure for the direct determination of arsenic in diluted serum by electrothermal atomization laser-excited atomic fluorescence spectrometry (ETA-LEAFS) is reported. Laser radiation needed to excite As at 193.696 and 197.197 nm is generated as the second anti-Stokes stimulated Raman scattering output of a frequency-doubled dye laser operating near 230.5 and 235.5 nm, respectively. Two different LEAFS schemes have been utilized and provide limits of detection of 200-300 fg for As in aqueous standards. When measurements of serum samples diluted 1:10 with deionized water are performed, a stable background signal is observed that can be accounted for by taking measurements with the laser tuned off-wavelength. No As is detected in any of the bovine or human serum samples analyzed. Measurements of 100 pg/mL standard additions of As to a diluted bovine serum sample utilizing either inorganic or organic As species demonstrate a linear relationship of the fluorescence signal to As spike concentration, but exhibit a sensitivity of approximately half that observed in pure aqueous standards. The limit of detection for As in 1:10 diluted serum samples is 65 pg/mL or 650 fg absolute mass, which corresponds to 0.65 ng/mL As in undiluted serum. To our knowledge, the ETA-LEAFS procedure is currently the only one capable of directly measuring As in diluted serum at these 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

Directory of Open Access Journals (Sweden)

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.

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.

Spike and burst coding in thalamocortical relay cells.

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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

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

Science.gov (United States)

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

2017-08-01

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

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.

A memristive spiking neuron with firing rate coding

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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.

Receptor-binding domain of SARS-CoV spike protein induces highly potent neutralizing antibodies: implication for developing subunit vaccine

International Nuclear Information System (INIS)

He Yuxian; Zhou Yusen; Liu Shuwen; Kou Zhihua; Li Wenhui; Farzan, Michael; Jiang Shibo

2004-01-01

The spike (S) protein of severe acute respiratory syndrome (SARS) coronavirus (CoV), a type I transmembrane envelope glycoprotein, consists of S1 and S2 domains responsible for virus binding and fusion, respectively. The S1 contains a receptor-binding domain (RBD) that can specifically bind to angiotensin-converting enzyme 2 (ACE2), the receptor on target cells. Here we show that a recombinant fusion protein (designated RBD-Fc) containing 193-amino acid RBD (residues 318-510) and a human IgG1 Fc fragment can induce highly potent antibody responses in the immunized rabbits. The antibodies recognized RBD on S1 domain and completely inhibited SARS-CoV infection at a serum dilution of 1:10,240. Rabbit antisera effectively blocked binding of S1, which contains RBD, to ACE2. This suggests that RBD can induce highly potent neutralizing antibody responses and has potential to be developed as an effective and safe subunit vaccine for prevention of SARS

Hardware implementation of stochastic spiking neural networks.

Science.gov (United States)

Rosselló, Josep L; Canals, Vincent; Morro, Antoni; Oliver, Antoni

2012-08-01

Spiking Neural Networks, the last generation of Artificial Neural Networks, are characterized by its bio-inspired nature and by a higher computational capacity with respect to other neural models. In real biological neurons, stochastic processes represent an important mechanism of neural behavior and are responsible of its special arithmetic capabilities. In this work we present a simple hardware implementation of spiking neurons that considers this probabilistic nature. The advantage of the proposed implementation is that it is fully digital and therefore can be massively implemented in Field Programmable Gate Arrays. The high computational capabilities of the proposed model are demonstrated by the study of both feed-forward and recurrent networks that are able to implement high-speed signal filtering and to solve complex systems of linear equations.

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.

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.

Quantitation of 14C-oxaliplatin concentrations in human serum samples by using accelerator mass spectrometry

International Nuclear Information System (INIS)

Kobayashi, Takeshi; Toyoguchi, Teiko; Kato, Kazuhiro; Tokanai, Fuyuki; Shiraishi, Tadashi

2013-01-01

The understanding of human pharmacokinetics is important for development of new drugs. Microdosing studies have been proposed as means of obtaining human pharmacokinetics information at early stages of drug development. Accelerator mass spectrometry (AMS) has high detection sensitivity and is expected to play an important role in microdose trials. In this study, we used the AMS microdosing facility at Yamagata University to measure the concentration of 14 C in 14 C-oxaliplatin-spiked serum samples. The calibration curve of 14 C concentration in serum was linear, and the correlation coefficient was 0.9994. The precision, accuracy, and stability values obtained (freeze and thaw cycles, and short- and long-term stability) satisfied the criteria. The mean background 14 C concentrations in samples of 6 healthy Japanese volunteers were 1.635dpm/mL in blood and 0.56dpm/mL in plasma. These results suggest the suitability of AMS-based quantitation for analyzing samples from microdosing studies. (author)

The chronotron: a neuron that learns to fire temporally precise spike patterns.

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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.

Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains.

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Arno Onken

2016-11-01

Full Text Available Advances in neuronal recording techniques are leading to ever larger numbers of simultaneously monitored neurons. This poses the important analytical challenge of how to capture compactly all sensory information that neural population codes carry in their spatial dimension (differences in stimulus tuning across neurons at different locations, in their temporal dimension (temporal neural response variations, or in their combination (temporally coordinated neural population firing. Here we investigate the utility of tensor factorizations of population spike trains along space and time. These factorizations decompose a dataset of single-trial population spike trains into spatial firing patterns (combinations of neurons firing together, temporal firing patterns (temporal activation of these groups of neurons and trial-dependent activation coefficients (strength of recruitment of such neural patterns on each trial. We validated various factorization methods on simulated data and on populations of ganglion cells simultaneously recorded in the salamander retina. We found that single-trial tensor space-by-time decompositions provided low-dimensional data-robust representations of spike trains that capture efficiently both their spatial and temporal information about sensory stimuli. Tensor decompositions with orthogonality constraints were the most efficient in extracting sensory information, whereas non-negative tensor decompositions worked well even on non-independent and overlapping spike patterns, and retrieved informative firing patterns expressed by the same population in response to novel stimuli. Our method showed that populations of retinal ganglion cells carried information in their spike timing on the ten-milliseconds-scale about spatial details of natural images. This information could not be recovered from the spike counts of these cells. First-spike latencies carried the majority of information provided by the whole spike train about fine

Des-Lys58-beta 2m and native beta 2m in rheumatoid arthritis serum and synovial fluid

DEFF Research Database (Denmark)

Williams, R C; Malone, C C; Nissen, Mogens Holst

1995-01-01

-Lys58-beta 2m were found in 80% of 21 SF from RA patients and in 43% of 41 SF from other subjects with various forms of inflammatory arthritis. In RA and other disorders such as gout or pseudogout, levels of Des-Lys58-beta 2m were higher in synovial fluid than in serum during an acute episode...

Analysis of human serum by liquid chromatography-mass spectrometry: improved sample preparation and data analysis.

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Govorukhina, N I; Reijmers, T H; Nyangoma, S O; van der Zee, A G J; Jansen, R C; Bischoff, R

2006-07-07

Discovery of biomarkers is a fast developing field in proteomics research. Liquid chromatography coupled on line to mass spectrometry (LC-MS) has become a powerful method for the sensitive detection, quantification and identification of proteins and peptides in biological fluids like serum. However, the presence of highly abundant proteins often masks those of lower abundance and thus generally prevents their detection and identification in proteomics studies. To perform future comparative analyses of samples from a serum bank of cervical cancer patients in a longitudinal and cross-sectional manner, methodology based on the depletion of high-abundance proteins followed by tryptic digestion and LC-MS has been developed. Two sample preparation methods were tested in terms of their efficiency to deplete high-abundance serum proteins and how they affect the repeatability of the LC-MS data sets. The first method comprised depletion of human serum albumin (HSA) on a dye ligand chromatographic and immunoglobulin G (IgG) on an immobilized Protein A support followed by tryptic digestion, fractionation by cation-exchange chromatography, trapping on a C18 column and reversed-phase LC-MS. The second method included depletion of the six most abundant serum proteins based on multiple immunoaffinity chromatography followed by tryptic digestion, trapping on a C18 column and reversed-phase LC-MS. Repeatability of the overall procedures was evaluated in terms of retention time and peak area for a selected number of endogenous peptides showing that the second method, besides being less time consuming, gave more repeatable results (retention time: <0.1% RSD; peak area: <30% RSD). Application of an LC-MS component detection algorithm followed by principal component analysis (PCA) enabled discrimination of serum samples that were spiked with horse heart cytochrome C from non-spiked serum and the detection of a concentration trend, which correlated to the amount of spiked horse heart

[A case of IgA2-lambda type M-protein that IgA concentration differs from the values of M-protein by serum protein electrophoresis].

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Fukushima, M; Sugano, M; Ichikawa, T; Honda, T; Totsuka, M; Katsuyama, T; Fujita, K

2001-07-01

We report an IgA-lambda type M-protein in which the IgA concentration differed from the values of M-protein by serum protein electrophoresis found in a 53-year-old man with multiple myeloma. The M-protein value as determined by serum protein electrophoresis was 6,170 mg/dl. However, the serum IgA concentration was 3,052 mg/dl by turbidimetric immunoassay. Immuno-fixation electrophoresis using IgA subclass antisera revealed that this M-protein was the IgA2-lambda type. Western blotting analysis showed that the IgA2 molecules were composed of two approximately 68 kDa alpha 2 chains and two 28 kDa lambda chains. In addition the free lambda chain band was detected at the position of 28 kDa without 2-mercaptoethanol(2-ME) even though the patient IgA was purified. Since it is known that IgA2m(1) allotype easily release light chains from the IgA molecules in SDS-PAGE without 2-ME, we speculated that in this patient the IgA was the IgA2m(1) allotype. After peripheral blood stem cell transplantation(PBSCT), immunofixation electrophoresis of the patient serum revealed not only the bands of IgA2-lambda type M-protein, but also three bands of IgG1-kappa type M-protein in the gamma region.

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.

An Efficient Supervised Training Algorithm for Multilayer Spiking Neural Networks.

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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.

Determination of carbamazepine in serum and saliva samples by high performance liquid chromatography with ultraviolet detection

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Đorđević Snežana

2009-01-01

Full Text Available Background/Aim. Carbamazepine is antiepileptic drug widely used for the treatment of epilepsy. Due to low therapeutic index of carbamazepine there is a need for routine measuring its concentrations in biological fluids. The aim of the study was to describe a method for concomitant determination of carbamazepine in the serum and saliva. Methods. Separation of the drug from matrix is achieved by reversedphase chromatography on a C18 column, with a mobile phase of methanol-water-acetic acid (65:34:1 at a flow-rate of 1.0 ml/min. Detection was effected by ultra-violet absorption at 285 nm. The total run time was 5 min. Samples were prepared by alkaline extraction (pH 10 using chlorophorm. Results. Calibration curves were in the range 0.1-5 μg/mL for serum and saliva samples. Mean recoveries of spiked serum and saliva were 97.59 and 92.30%, respectively. Limits of detection (LOD of carbamazepine in serum and saliva were 0.166 and 0.178 μg/mL, respectively. Limits of quantification (LOQ in the serum and saliva were 0.237 and 0.226 μg/mL, respectively. The method precision was carried out with coefficient of variation of 2.10% and 4.03% for the serum and saliva, respectively. The obtained data showed that there was a strong correlation between saliva and serum concentrations (r = 0.9481, p < 0.001. Conclusion. The method described here is rapid, precise, accurate and simple, and can be used for quantitative determination of carbamazepine in human serum and saliva after therapy applying. Saliva samples could be used as an alternative matrix for therapeutic drug monitoring of this antiepileptic drug.

Coronavirus spike-receptor interactions

NARCIS (Netherlands)

Mou, H.

2015-01-01

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

Virus-specific immune response in HBeAg-negative chronic hepatitis B: relationship with clinical profile and HBsAg serum levels.

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Elisabetta Loggi

Full Text Available BACKGROUND AIMS: The immune impairment characterizing chronic hepatitis B (cHBV infection is thought to be the consequence of persistent exposure to viral antigens. However, the immune correlates of different clinical stages of cHBV and their relation with different levels of HBsAg have not been investigated. The aim of the present study was to evaluate the relationship between HBV-specific T cells response and the degree of in vivo HBV control and HBsAg serum levels in HBeAg-HBeAb+ cHBV. METHODS: Peripheral blood mononuclear cells from 42 patients with different clinical profiles (treatment-suppressed, inactive carriers and active hepatitis of cHBV, 6 patients with resolved HBV infection and 10 HBV-uninfected individuals were tested with overlapping peptides spanning the entire HBV proteome. The frequency and magnitude of HBV-specific T cell responses was assessed by IFNγ ELISPOT assay. Serum HBsAg was quantified with a chemiluminescent immunoassay. RESULTS: The total breadth and magnitude of HBV-specific T cell responses did not differ significantly between the four groups. However, inactive carriers targeted preferentially the core region. In untreated patients, the breadth of the anti-core specific T cell response was inversely correlated with serum HBsAg concentrations as well as HBV-DNA and ALT levels and was significantly different in patients with HBsAg levels either above or below 1000 IU/mL. The same inverse association between anti-core T cell response and HBsAg levels was found in treated patients. CONCLUSIONS: Different clinical outcomes of cHBV infection are associated with the magnitude, breadth and specificity of the HBV-specific T cell response. Especially, robust anti-core T cell responses were found in the presence of reduced HBsAg serum levels, suggesting that core-specific T cell responses can mediate a protective effect on HBV control.

Elevation in inflammatory serum biomarkers predicts response to trastuzumab-containing therapy.

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Ahmed A Alkhateeb

Full Text Available Approximately half of all HER2/neu-overexpressing breast cancer patients do not respond to trastuzumab-containing therapy. Therefore, there remains an urgent and unmet clinical need for the development of predictive biomarkers for trastuzumab response. Recently, several lines of evidence have demonstrated that the inflammatory tumor microenvironment is a major contributor to therapy resistance in breast cancer. In order to explore the predictive value of inflammation in breast cancer patients, we measured the inflammatory biomarkers serum ferritin and C-reactive protein (CRP in 66 patients immediately before undergoing trastuzumab-containing therapy and evaluated their progression-free and overall survival. The elevation in pre-treatment serum ferritin (>250 ng/ml or CRP (>7.25 mg/l was a significant predictor of reduced progression-free survival and shorter overall survival. When patients were stratified based on their serum ferritin and CRP levels, patients with elevation in both inflammatory biomarkers had a markedly poorer response to trastuzumab-containing therapy. Therefore, the elevation in inflammatory serum biomarkers may reflect a pathological state that decreases the clinical efficacy of this therapy. Anti-inflammatory drugs and life-style changes to decrease inflammation in cancer patients should be explored as possible strategies to sensitize patients to anti-cancer therapeutics.

Consensus-Based Sorting of Neuronal Spike Waveforms.

Science.gov (United States)

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.

Linking structure and activity in nonlinear spiking networks.

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Gabriel Koch Ocker

2017-06-01

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

Linking structure and activity in nonlinear spiking networks.

Science.gov (United States)

Ocker, Gabriel Koch; Josić, Krešimir; Shea-Brown, Eric; Buice, Michael A

2017-06-01

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

Clinical significance of measurement of serum hs-CRP, TNF-α and M-CSF levels after treatment in patients with periodontitis

International Nuclear Information System (INIS)

Zhang Yunming

2007-01-01

Objective: To explore the significance of changes of serum hs-CRP, TNF-α and M-CSF levels after treatment in patients with periodontitis. Methods: Serum TNF-α, M-CSF (with RIA), hs-CRP (with immuneturbitity method) levels were determined in 38 patients with periodontitis both before and after treatment as well as in 35 controls. Results: Before treatment, the serum hs-CRP, TNF-α and M-CSF levels were significantly higher in the patients than those in controls (P 0.05). Conclusion: Detection of serum hs-CRP, TNF-α and M-CSF levels might reflect the progress of disease in patients with periodontitis. (authors)

Recording human cortical population spikes non-invasively--An EEG tutorial.

Science.gov (United States)

Waterstraat, Gunnar; Fedele, Tommaso; Burghoff, Martin; Scheer, Hans-Jürgen; Curio, Gabriel

2015-07-30

Non-invasively recorded somatosensory high-frequency oscillations (sHFOs) evoked by electric nerve stimulation are markers of human cortical population spikes. Previously, their analysis was based on massive averaging of EEG responses. Advanced neurotechnology and optimized off-line analysis can enhance the signal-to-noise ratio of sHFOs, eventually enabling single-trial analysis. The rationale for developing dedicated low-noise EEG technology for sHFOs is unfolded. Detailed recording procedures and tailored analysis principles are explained step-by-step. Source codes in Matlab and Python are provided as supplementary material online. Combining synergistic hardware and analysis improvements, evoked sHFOs at around 600 Hz ('σ-bursts') can be studied in single-trials. Additionally, optimized spatial filters increase the signal-to-noise ratio of components at about 1 kHz ('κ-bursts') enabling their detection in non-invasive surface EEG. sHFOs offer a unique possibility to record evoked human cortical population spikes non-invasively. The experimental approaches and algorithms presented here enable also non-specialized EEG laboratories to combine measurements of conventional low-frequency EEG with the analysis of concomitant cortical population spike responses. Copyright © 2014 Elsevier B.V. All rights reserved.

Superficial dorsal horn neurons with double spike activity in the rat.

Science.gov (United States)

Rojas-Piloni, Gerardo; Dickenson, Anthony H; Condés-Lara, Miguel

2007-05-29

Superficial dorsal horn neurons promote the transfer of nociceptive information from the periphery to supraspinal structures. The membrane and discharge properties of spinal cord neurons can alter the reliability of peripheral signals. In this paper, we analyze the location and response properties of a particular class of dorsal horn neurons that exhibits double spike discharge with a very short interspike interval (2.01+/-0.11 ms). These neurons receive nociceptive C-fiber input and are located in laminae I-II. Double spikes are generated spontaneously or by depolarizing current injection (interval of 2.37+/-0.22). Cells presenting double spike (interval 2.28+/-0.11) increased the firing rate by electrical noxious stimulation, as well as, in the first minutes after carrageenan injection into their receptive field. Carrageenan is a polysaccharide soluble in water and it is used for producing an experimental model of semi-chronic pain. In the present study carrageenan also produces an increase in the interval between double spikes and then, reduced their occurrence after 5-10 min. The results suggest that double spikes are due to intrinsic membrane properties and that their frequency is related to C-fiber nociceptive activity. The present work shows evidence that double spikes in superficial spinal cord neurones are related to the nociceptive stimulation, and they are possibly part of an acute pain-control mechanism.

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

Auto- and Crosscorrelograms for the Spike Response of Leaky Integrate-and-Fire Neurons with Slow Synapses

International Nuclear Information System (INIS)

Moreno-Bote, Ruben; Parga, Nestor

2006-01-01

An analytical description of the response properties of simple but realistic neuron models in the presence of noise is still lacking. We determine completely up to the second order the firing statistics of a single and a pair of leaky integrate-and-fire neurons receiving some common slowly filtered white noise. In particular, the auto- and cross-correlation functions of the output spike trains of pairs of cells are obtained from an improvement of the adiabatic approximation introduced previously by Moreno-Bote and Parga [Phys. Rev. Lett. 92, 028102 (2004)]. These two functions define the firing variability and firing synchronization between neurons, and are of much importance for understanding neuron communication

Integration of growth factor signals at the c-fos serum response element.

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Price, M A; Hill, C; Treisman, R

1996-04-29

A transcription factor ternary complex composed of serum response factor (SRF) and a second factor, ternary complex factor (TCF), mediates the response of the c-fos Serum Response Element to growth factors and mitogens. In NIH3T3 fibroblasts, TCF binding is required for transcriptional activation by the SRE in response to activation of the Ras-Raf-ERK pathway. We compared the properties of three members of the TCF family, Elk-1, SAP-1 and SAP-2 (ERP/NET). Although all the proteins contain sequences required for ternary complex formation with SRF, only Elk-1 and SAP-1 appear to interact with the c-fos SRE efficiently in vivo. Each TCF contains a C-terminal activation domain capable of transcriptional activation in response to activation of the Ras-Raf-ERK pathway, and this is dependent on the integrity of S/T-P motifs conserved between all the TCF family members. In contrast, activation of the SRE by whole serum and the mitogenic phospholipid LPA requires SRF binding alone. Constitutively activated members of the Rho subfamily of Ras-like GTPases are also capable of inducing activation of the SRE in the absence of TCF; unlike activated Ras itself, these proteins do not activate the TCFs in NIH3T3 cells. At the SRE, SRF- and TCF-linked signalling pathways act synergistically to potentiate transcription.

Effects of potassium concentration on firing patterns of low-calcium epileptiform activity in anesthetized rat hippocampus: inducing of persistent spike activity.

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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.

Clinical significance of serum circulating insulin-like growth factor-1 (IGF-1) mRNA in hepatocellular carcinoma.

Science.gov (United States)

Karabulut, S; Duranyıldız, D; Tas, F; Gezer, U; Akyüz, F; Serilmez, M; Ozgür, E; Yasasever, C T; Vatansever, S; Aykan, N F

2014-03-01

The principal aim of our study was to investigate the usefulness of serum protein and circulating mRNA of insulin-like growth factor-1 (IGF-1) as a diagnostic and prognostic tool in hepatocellular carcinoma (HCC). Fifty-four HCC patients and age- and sex-matched 20 healthy controls were enrolled into this study. Pretreatment serum IGF-1 and IGF-1 mRNA were determined by the solid-phase sandwich ELISA and quantitative RT-PCR method, respectively. The median age at diagnosis was 60 years, range 36-77 years; where majority of group were male (n = 48, 88.8%). All patients had cirrhotic history. Forty-six percent (n = 25) of patients had Child-Pugh score A, 30% (n = 16) had score B or C. All of the patients were treated with local therapies and none of them received sorafenib. The baseline serum IGF-1 mRNA levels were significantly higher in HCC patients than in the control group (p = 0.04), whereas no significant difference was observed for IGF-1 protein levels between the two group (p = 0.18). Patients with history of HBV infection, who were not treated, and who received multiple palliative treatment for HCC had higher serum IGF-1 mRNA levels (p = 0.03, 0.03, and 0.05, respectively). Poor performance status (p IGF-1 nor serum IGF-1 mRNA had significantly adverse effect on survival (p = 0.53 and 0.42, respectively).

Fluctuating inhibitory inputs promote reliable spiking at theta frequencies in hippocampal interneurons

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Duluxan eSritharan

2012-05-01

Full Text Available Theta frequency (4-12 Hz rhythms in the hippocampus play important roles in learning and memory. CA1 interneurons located at the stratum lacunosum-moleculare and radiatum junction (LM/RAD are thought to contribute to hippocampal theta population activities by rhythmically pacing pyramidal cells with inhibitory postsynaptic potentials. This implies that LM/RAD cells need to fire reliably at theta frequencies in vivo. To determine whether this could occur, we use biophysically-based LM/RAD model cells and apply different cholinergic and synaptic inputs to simulate in vivo-like network environments. We assess spike reliabilities and spiking frequencies, identifying biophysical properties and network conditions that best promote reliable theta spiking. We find that synaptic background activities that feature large inhibitory, but not excitatory, fluctuations are essential. This suggests that strong inhibitory input to these cells is vital for them to be able to contribute to population theta activities. Furthermore, we find that Type I-like oscillator models produced by augmented persistent sodium currents (INap or diminished A type potassium currents (IA enhance reliable spiking at lower theta frequencies. These Type I-like models are also the most responsive to large inhibitory fluctuations and can fire more reliably under such conditions. In previous work, we showed that INap and IA are largely responsible for establishing LM/RAD cells’ subthreshold activities. Taken together with this study, we see that while both these currents are important for subthreshold theta fluctuations and reliable theta spiking, they contribute in different ways – INap to reliable theta spiking and subthreshold activity generation, and IA to subthreshold activities at theta frequencies. This suggests that linking subthreshold and suprathreshold activities should be done with consideration of both in vivo contexts and biophysical specifics.

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.

Channel noise effects on first spike latency of a stochastic Hodgkin-Huxley neuron

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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.

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

International Nuclear Information System (INIS)

Peng, Xingjie; Li, Qing; Wang, Kan

2017-01-01

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

Trace analysis of icariin in human serum with dansyl chloride derivatization after oral administration of Epimedium decoction by liquid chromatography tandem mass spectrometry.

Science.gov (United States)

Gong, Yinhan; Yip, See Chung; Thamarai, Sennappan Kanagamani; Zhang, Jie; Lee, Hian Kee; Yong, E L

2007-12-15

Epimedium herbs are a type of complex traditional Chinese medicine (TCM) with high estrogenic bioactivity. The Epimedium herbal decoction mixture contains many compounds including icariin that can exert potent effects on numerous physiological processes related to human health. An ultrasensitive liquid chromatography tandem mass spectrometric (LC-MS/MS) method has been developed to determine trace levels of icariin in human serum with dansyl chloride derivatization after oral administration of the Epimedium herbal decoctions. The dansyl-icariin showed an intense protonated molecular ion at m/z 910. The collision-induced dissociation of this ion formed a distinctive product at m/z 764, corresponding to a characteristic removal of a rhamnose sugar moiety of icariin. The selected reaction monitoring, based on the m/z 910-->764 transition, was highly specific and ultrasenstive for icariin in human serum samples. The lower limit of quantitation was 10 pg/mL icariin spiked into blank serum. The ranges of coefficients of variation for interday assays and intraday assays were 0-15.0% and 1.1-17.5%, respectively, for a wide linear range from 10 pg/mL to 4 ng/mL. This method was successfully applied to measure trace levels of icariin in a human serum after oral administration of Epimedium decoction within 48 h for the first time.

Multineuronal Spike Sequences Repeat with Millisecond Precision

Directory of Open Access Journals (Sweden)

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.

Spiking Neural P Systems with Communication on Request.

Science.gov (United States)

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

2017-12-01

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

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

Spike-Timing Dependent Plasticity in Unipolar Silicon Oxide RRAM Devices.

Science.gov (United States)

Zarudnyi, Konstantin; Mehonic, Adnan; Montesi, Luca; Buckwell, Mark; Hudziak, Stephen; Kenyon, Anthony J

2018-01-01

Resistance switching, or Resistive RAM (RRAM) devices show considerable potential for application in hardware spiking neural networks (neuro-inspired computing) by mimicking some of the behavior of biological synapses, and hence enabling non-von Neumann computer architectures. Spike-timing dependent plasticity (STDP) is one such behavior, and one example of several classes of plasticity that are being examined with the aim of finding suitable algorithms for application in many computing tasks such as coincidence detection, classification and image recognition. In previous work we have demonstrated that the neuromorphic capabilities of silicon-rich silicon oxide (SiO x ) resistance switching devices extend beyond plasticity to include thresholding, spiking, and integration. We previously demonstrated such behaviors in devices operated in the unipolar mode, opening up the question of whether we could add plasticity to the list of features exhibited by our devices. Here we demonstrate clear STDP in unipolar devices. Significantly, we show that the response of our devices is broadly similar to that of biological synapses. This work further reinforces the potential of simple two-terminal RRAM devices to mimic neuronal functionality in hardware spiking neural networks.

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

Science.gov (United States)

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

2016-02-01

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

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

Science.gov (United States)

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.

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

Serum calcium response following oral zinc oxide administrations in dairy cows

DEFF Research Database (Denmark)

Thilsing-Hansen, T; Jørgensen, R J; Thilsing, Trine

2001-01-01

Six non-pregnant cows were allocated into 3 groups. Group 1 comprised a pair of lactating cows, whereas groups 2 and 3 each comprised a pair of non-lactating cows. The cows in groups 1 and 2 were dosed intraruminally by stomach tube with zinc oxide at 120 mg Zn per kg of bodyweight at weekly...... intervals for a period of 33 days. Each cow received a total of 4 doses of zinc oxide. Group 3 served as non-treated control group. Blood samples were collected from all 6 cows daily. Serum was analysed for concentration of calcium. Within 12-24 h of each zinc oxide administration the serum calcium...... of the hypocalcaemic response decreased with the number of zinc oxide dosings. This effect was explained as a response from the stimulation of the calcium homeostatic mechanisms. In the Zn dosed non-lactating cows responses were similar but less clear. The perspective of these findings is discussed in relation...

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...

A Three-Dimensional Movement Analysis of the Spike in Fistball

Directory of Open Access Journals (Sweden)

Andreas Bund

2016-12-01

Full Text Available Due to its relevancy to point scoring, the spike is considered as one of the most important skills in fistball. Biomechanical analyses of this sport are very rare. In the present study, we performed a three-dimensional kinematic analysis of the fistball spike, which helps to specify performance parameters on a descriptive level. Recorded by four synchronized cameras (120 Hz and linked to the motion capture software Simi Motion® 5.0, three female fistball players of the second German league (24–26 years, 1.63–1.69 m performed several spikes under standardized conditions. Results show that the segment velocities of the arm reached their maximum successively from proximal to distal, following the principle of temporal coordination of single impulses. The wrist shows maximum speed when the fist hits the ball. The elbow joint angle performs a rapid transition from a strong flexion to a (almost full extension; however, the extension is completed after the moment of ball impact. In contrast, the shoulder joint angle increases almost linearly until the fistball contact and decreases afterward. The findings can be used to optimize the training of the spike.

Gradient Learning in Spiking Neural Networks by Dynamic Perturbation of Conductances

International Nuclear Information System (INIS)

Fiete, Ila R.; Seung, H. Sebastian

2006-01-01

We present a method of estimating the gradient of an objective function with respect to the synaptic weights of a spiking neural network. The method works by measuring the fluctuations in the objective function in response to dynamic perturbation of the membrane conductances of the neurons. It is compatible with recurrent networks of conductance-based model neurons with dynamic synapses. The method can be interpreted as a biologically plausible synaptic learning rule, if the dynamic perturbations are generated by a special class of 'empiric' synapses driven by random spike trains from an external source

Which spike train distance is most suitable for distinguishing rate and temporal coding?

Science.gov (United States)

Satuvuori, Eero; Kreuz, Thomas

2018-04-01

It is commonly assumed in neuronal coding that repeated presentations of a stimulus to a coding neuron elicit similar responses. One common way to assess similarity are spike train distances. These can be divided into spike-resolved, such as the Victor-Purpura and the van Rossum distance, and time-resolved, e.g. the ISI-, the SPIKE- and the RI-SPIKE-distance. We use independent steady-rate Poisson processes as surrogates for spike trains with fixed rate and no timing information to address two basic questions: How does the sensitivity of the different spike train distances to temporal coding depend on the rates of the two processes and how do the distances deal with very low rates? Spike-resolved distances always contain rate information even for parameters indicating time coding. This is an issue for reasonably high rates but beneficial for very low rates. In contrast, the operational range for detecting time coding of time-resolved distances is superior at normal rates, but these measures produce artefacts at very low rates. The RI-SPIKE-distance is the only measure that is sensitive to timing information only. While our results on rate-dependent expectation values for the spike-resolved distances agree with Chicharro et al. (2011), we here go one step further and specifically investigate applicability for very low rates. The most appropriate measure depends on the rates of the data being analysed. Accordingly, we summarize our results in one table that allows an easy selection of the preferred measure for any kind of data. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Efficient evaluation of humoral immune responses by the use of serum pools

DEFF Research Database (Denmark)

Sternbæk, Louise; Draborg, Anette H.; Nielsen, Christoffer T.

2017-01-01

has considered using serum pools as a quick and efficient screening method to confirm or deny hypotheses. Methods We created serum pools from four different patient groups (systemic lupus erythematosus n = 85, rheumatoid arthritis n = 77, Sjögren's syndrome n = 91, systemic sclerosis n = 66) and one......Background Collection and testing of individual serum samples are often used in research to gain knowledge about e.g. the humoral response against bacteria or virus. This is a valid but time-consuming method and might be a waste of valuable serum samples for inefficient research. So far, no study...... healthy control group (n = 67). Each serum pool was analyzed using three well-known immunoassays: enzyme-linked immunosorbent assay (ELISA), line blot, and immunofluorescence microscopy (anti-nuclear antibody (ANA) screening). The presence of Epstein-Barr virus (EBV) EA/D-, EBNA-1-, VCA p23-, and gp350...

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.

Generalized activity equations for spiking neural network dynamics

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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.

Validation of the IDS Octeia ELISA for the determination of insulin-like growth factor 1 in equine serum and tendon tissue extracts

DEFF Research Database (Denmark)

Lygren, Tone; Schjerling, Peter; Jacobsen, Stine

2013-01-01

BACKGROUND: Insulin-like growth factor (IGF-1) is an important mediator of tissue repair in horses. OBJECTIVES: The aim of the study was to evaluate whether IGF-1 could be measured reliably in equine serum and tendon tissue extracts, using an IGF-1 ELISA kit developed for human serum and plasma...... diluted equine serum samples and tendon tissue extracts. The recovery of IGF-1 was evaluated in serum and tendon tissue extracts spiked with known amounts of IGF-1. RESULTS: The range of IGF-1 released using the manufacturer's pretreatment was between 23% and 56% of the amount released using the gly...... with serum, and 72 ± 15% when diluted with PBS. The recovery after dilution was 108 ± 17% in tendon tissue extracts. Recovery from serum spiked with a fixed amount of IGF-1 was 101 ± 5% and 99 ± 7% from tendon tissue samples. CONCLUSIONS: The IDS Octeia IGF-1 ELISA kit can be used for measuring IGF-1...

Input-output relation and energy efficiency in the neuron with different spike threshold dynamics.

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Yi, Guo-Sheng; Wang, Jiang; Tsang, Kai-Ming; Wei, Xi-Le; Deng, Bin

2015-01-01

Neuron encodes and transmits information through generating sequences of output spikes, which is a high energy-consuming process. The spike is initiated when membrane depolarization reaches a threshold voltage. In many neurons, threshold is dynamic and depends on the rate of membrane depolarization (dV/dt) preceding a spike. Identifying the metabolic energy involved in neural coding and their relationship to threshold dynamic is critical to understanding neuronal function and evolution. Here, we use a modified Morris-Lecar model to investigate neuronal input-output property and energy efficiency associated with different spike threshold dynamics. We find that the neurons with dynamic threshold sensitive to dV/dt generate discontinuous frequency-current curve and type II phase response curve (PRC) through Hopf bifurcation, and weak noise could prohibit spiking when bifurcation just occurs. The threshold that is insensitive to dV/dt, instead, results in a continuous frequency-current curve, a type I PRC and a saddle-node on invariant circle bifurcation, and simultaneously weak noise cannot inhibit spiking. It is also shown that the bifurcation, frequency-current curve and PRC type associated with different threshold dynamics arise from the distinct subthreshold interactions of membrane currents. Further, we observe that the energy consumption of the neuron is related to its firing characteristics. The depolarization of spike threshold improves neuronal energy efficiency by reducing the overlap of Na(+) and K(+) currents during an action potential. The high energy efficiency is achieved at more depolarized spike threshold and high stimulus current. These results provide a fundamental biophysical connection that links spike threshold dynamics, input-output relation, energetics and spike initiation, which could contribute to uncover neural encoding mechanism.

Stimulus-dependent modulation of spike burst length in cat striate cortical cells.

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DeBusk, B C; DeBruyn, E J; Snider, R K; Kabara, J F; Bonds, A B

1997-07-01

Burst activity, defined by groups of two or more spikes with intervals of cats. Bursting varied broadly across a population of 507 simple and complex cells. Half of this population had > or = 42% of their spikes contained in bursts. The fraction of spikes in bursts did not vary as a function of average firing rate and was stationary over time. Peaks in the interspike interval histograms were found at both 3-5 ms and 10-30 ms. In many cells the locations of these peaks were independent of firing rate, indicating a quantized control of firing behavior at two different time scales. The activity at the shorter time scale most likely results from intrinsic properties of the cell membrane, and that at the longer scale from recurrent network excitation. Burst frequency (bursts per s) and burst length (spikes per burst) both depended on firing rate. Burst frequency was essentially linear with firing rate, whereas burst length was a nonlinear function of firing rate and was also governed by stimulus orientation. At a given firing rate, burst length was greater for optimal orientations than for nonoptimal orientations. No organized orientation dependence was seen in bursts from lateral geniculate nucleus cells. Activation of cortical contrast gain control at low response amplitudes resulted in no burst length modulation, but burst shortening at optimal orientations was found in responses characterized by supersaturation. At a given firing rate, cortical burst length was shortened by microinjection of gamma-aminobutyric acid (GABA), and bursts became longer in the presence of N-methyl-bicuculline, a GABA(A) receptor blocker. These results are consistent with a model in which responses are reduced at nonoptimal orientations, at least in part, by burst shortening that is mediated by GABA. A similar mechanism contributes to response supersaturation at high contrasts via recruitment of inhibitory responses that are tuned to adjacent orientations. Burst length modulation can serve

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...

Anti-PGL1 salivary IgA/IgM, serum IgG/IgM, and nasal Mycobacterium leprae DNA in individuals with household contact with leprosy.

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Brito e Cabral, Paula; Júnior, José Evandro Cunha; de Macedo, Alexandre Casimiro; Alves, Alexandre Rodrigues; Gonçalves, Thially Braga; Brito e Cabral, Tereza Cristina; Gondim, Ana Paula Soares; Pinto, Maria Isabel Moraes; Oseki, Karen Tubono; Camara, Lilia Maria Carneiro; Rabenhorst, Silvia Helena Barem; Nagao-Dias, Aparecida Tiemi

2013-11-01

Leprosy household contacts represent a group at high risk of developing the disease. The aim of this study was to detect Mycobacterium leprae subclinical infection in this group through serological and molecular parameters. Serum anti-PGL1 IgG/IgM and salivary anti-PGL1 IgA/IgM was investigated using an ELISA, and nasal carriage of M. leprae DNA was detected by PCR, in leprosy household contacts of paucibacillary (PB) and multibacillary (MB) household leprosy patients (n=135), their index cases (n=30), and in persons living in a low endemic city (n=17). Salivary anti-PGL1 IgA and IgM and serum anti-PGL1 IgG showed good correlation comparing contacts and index cases (p0.05). A high frequency of anti-PGL1 IgM positivity was found in IgG-negative samples (pleprae DNA was found in the nasal swabs of nine out of the 85 MB household leprosy contacts (10.6%) and in three out of the 50 PB household leprosy contacts (6.0%). We strongly suggest that serum IgG/IgM and salivary anti-PGL1 IgA/IgM measurements are used to follow leprosy household contacts. Copyright © 2013 International Society for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Cellular and circuit mechanisms maintain low spike co-variability and enhance population coding in somatosensory cortex

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Cheng eLy

2012-03-01

Full Text Available The responses of cortical neurons are highly variable across repeated presentations of a stimulus. Understanding this variability is critical for theories of both sensory and motor processing, since response variance affects the accuracy of neural codes. Despite this influence, the cellular and circuit mechanisms that shape the trial-to-trial variability of population responses remain poorly understood. We used a combination of experimental and computational techniques to uncover the mechanisms underlying response variability of populations of pyramidal (E cells in layer 2/3 of rat whisker barrel cortex. Spike trains recorded from pairs of E-cells during either spontaneous activity or whisker deflected responses show similarly low levels of spiking co-variability, despite large differences in network activation between the two states. We developed network models that show how spike threshold nonlinearities dilutes E-cell spiking co-variability during spontaneous activity and low velocity whisker deflections. In contrast, during high velocity whisker deflections, cancelation mechanisms mediated by feedforward inhibition maintain low E-cell pairwise co-variability. Thus, the combination of these two mechanisms ensure low E-cell population variability over a wide range of whisker deflection velocities. Finally, we show how this active decorrelation of population variability leads to a drastic increase in the population information about whisker velocity. The canonical cellular and circuit components of our study suggest that low network variability over a broad range of neural states may generalize across the nervous system.

Serum lutein response is greater from free lutein than from esterified lutein during 4 weeks of supplementation in healthy adults.

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Norkus, Edward P; Norkus, Katherine L; Dharmarajan, T S; Schierle, Joseph; Schalch, Wolfgang

2010-12-01

Current data suggest great variability in serum response following lutein ingestion from various sources. To compare the relative serum response during supplementation with free lutein (fL) and lutein esters (Le). 72 volunteers (23-52 years; body mass index [BMI] >20 and lutein lutein or 27 mg of lutein ester (equivalent to 13.5 mg free lutein), respectively. Fasting blood was obtained at baseline and after 7, 14, 21, and 28 days of supplementation. Supplements were consumed with standard portions of dry, ready-to-eat cereal and 2% cow's milk. Absolute changes in serum lutein, per mg daily dose, were significantly greater in fL vs. Le after 21 days (p  =  0.0012) and remained so after 28 days (p  =  0.0011) of supplementation. Serum lutein Area Under the Curve [AUC((day 0-28))] response was 17% greater for fL vs. Le (p  =  0.0187). Regression models were used and determined that (1) baseline serum lutein levels and (2) the form of lutein ingested (fL > Le) influence the serum lutein response during supplementation, while subject age, gender, BMI, and serum lipids do not affect serum response. These results suggest that the relative serum lutein response will be significantly greater from supplements containing free lutein than from supplements containing lutein esters. These findings should be useful for future clinical trials exploring the effectiveness of lutein supplementation in the prevention of or protection against age-related macular degeneration and/or cataracts.

Statistical properties of superimposed stationary spike trains.

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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.

Phase Diagram of Spiking Neural Networks

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Hamed eSeyed-Allaei

2015-03-01

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

Genome-wide scan identifies variant in TNFSF13 associated with serum IgM in a healthy Chinese male population.

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Ming Yang

Full Text Available IgM provides a first line of defense during microbial infections. Serum IgM levels are detected routinely in clinical practice. And IgM is a genetically complex trait. We conducted a two-stage genome-wide association study (GWAS to identify genetic variants affecting serum IgM levels in a Chinese population of 3495, including 1999 unrelated subjects in the first stage and 1496 independent individuals in the second stage. Our data show that a common single nucleotide polymorphism (SNP, rs11552708 located in the TNFSF13 gene was significantly associated with IgM levels (p = 5.00×10(-7 in first stage, p = 1.34×10(-3 in second stage, and p = 4.22×10(-9 when combined. Besides, smoking was identified to be associated with IgM levels in both stages (P0.05. It is suggested that TNFSF13 may be a susceptibility gene affecting serum IgM levels in Chinese male population.

Learning Universal Computations with Spikes

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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

Fluctuations and information filtering in coupled populations of spiking neurons with adaptation.

Science.gov (United States)

Deger, Moritz; Schwalger, Tilo; Naud, Richard; Gerstner, Wulfram

2014-12-01

Finite-sized populations of spiking elements are fundamental to brain function but also are used in many areas of physics. Here we present a theory of the dynamics of finite-sized populations of spiking units, based on a quasirenewal description of neurons with adaptation. We derive an integral equation with colored noise that governs the stochastic dynamics of the population activity in response to time-dependent stimulation and calculate the spectral density in the asynchronous state. We show that systems of coupled populations with adaptation can generate a frequency band in which sensory information is preferentially encoded. The theory is applicable to fully as well as randomly connected networks and to leaky integrate-and-fire as well as to generalized spiking neurons with adaptation on multiple time scales.

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.

Comparing Levels of Serum IgA, IgG, IgM and Cortisol in the Professional Bodybuilding Athletes and Non-Athletes

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S. Hadi Naghib

2013-10-01

Full Text Available Background: Bodybuilding athlete's bodies are placed under much pressure in during the exercise, which is causing changes in the immune and hormone system in the long term. The purpose of this study was to compare levels of serum immunoglobulin A (IgA, immunoglobulin G (IgG, immunoglobulin M (IgM and cortisol in the professional bodybuilding athletes (BA and the non-athletes (NA male. Materials and Methods: This study was a descriptive-analytic and 29 volunteer subjects in the professional BA and NA men participated. Levels of serum IgA, IgG, IgM using Single Radial Immunodiffusion (SRID and levels of serum cortisol using Radioimmunoassay (RIA were measured with blood sampling from brachial vein at rest and fasting. Data were analyzed using the Mann-Whitney U-test (p0.05, while, the levels of serum cortisol (22.10±2.60 vs. 15.41±3.44 μg/dl, U=0.001, p=0.001 significantly greater in the BA than the NA.Conclusion: The results of this study showed that participation in training and competitions bodybuilding has no effect on serum levels of IgG, IgA, IgM, but increased levels of serum cortisol.

Time Resolution Dependence of Information Measures for Spiking Neurons: Scaling and Universality

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James P Crutchfield

2015-08-01

Full Text Available The mutual information between stimulus and spike-train response is commonly used to monitor neural coding efficiency, but neuronal computation broadly conceived requires more refined and targeted information measures of input-output joint processes. A first step towards that larger goal is todevelop information measures for individual output processes, including information generation (entropy rate, stored information (statisticalcomplexity, predictable information (excess entropy, and active information accumulation (bound information rate. We calculate these for spike trains generated by a variety of noise-driven integrate-and-fire neurons as a function of time resolution and for alternating renewal processes. We show that their time-resolution dependence reveals coarse-grained structural properties of interspike interval statistics; e.g., $tau$-entropy rates that diverge less quickly than the firing rate indicate interspike interval correlations. We also find evidence that the excess entropy and regularized statistical complexity of different types of integrate-and-fire neurons are universal in the continuous-time limit in the sense that they do not depend on mechanism details. This suggests a surprising simplicity in the spike trains generated by these model neurons. Interestingly, neurons with gamma-distributed ISIs and neurons whose spike trains are alternating renewal processes do not fall into the same universality class. These results lead to two conclusions. First, the dependence of information measures on time resolution reveals mechanistic details about spike train generation. Second, information measures can be used as model selection tools for analyzing spike train processes.

Noise-robust speech recognition through auditory feature detection and spike sequence decoding.

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Schafer, Phillip B; Jin, Dezhe Z

2014-03-01

Speech recognition in noisy conditions is a major challenge for computer systems, but the human brain performs it routinely and accurately. Automatic speech recognition (ASR) systems that are inspired by neuroscience can potentially bridge the performance gap between humans and machines. We present a system for noise-robust isolated word recognition that works by decoding sequences of spikes from a population of simulated auditory feature-detecting neurons. Each neuron is trained to respond selectively to a brief spectrotemporal pattern, or feature, drawn from the simulated auditory nerve response to speech. The neural population conveys the time-dependent structure of a sound by its sequence of spikes. We compare two methods for decoding the spike sequences--one using a hidden Markov model-based recognizer, the other using a novel template-based recognition scheme. In the latter case, words are recognized by comparing their spike sequences to template sequences obtained from clean training data, using a similarity measure based on the length of the longest common sub-sequence. Using isolated spoken digits from the AURORA-2 database, we show that our combined system outperforms a state-of-the-art robust speech recognizer at low signal-to-noise ratios. Both the spike-based encoding scheme and the template-based decoding offer gains in noise robustness over traditional speech recognition methods. Our system highlights potential advantages of spike-based acoustic coding and provides a biologically motivated framework for robust ASR development.

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)

Uso do protocolo Spikes no ensino de habilidades em transmissão de más notícias

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Carolina Arcanjo Lino

Full Text Available O termo "má notícia" designa qualquer informação transmitida ao paciente ou a seus familiares que implique, direta ou indiretamente, alguma alteração negativa na vida destes. Por ser uma tarefa tão estressante, muitos médicos a evitam ou a realizam de maneira inadequada. Esse fato traz inúmeras consequências negativas para o paciente e seus familiares. Embora seja objeto de estudo em diversos cursos de Medicina em nível internacional, o tema ainda é pouco abordado por professores e estudantes no contexto brasileiro. O protocolo Spikes descreve de maneira didática seis passos para comunicar más notícias. Esses passos foram utilizados em aula para alunos do terceiro semestre do curso de Medicina da Universidade Estadual do Ceará. Em seguida, os alunos avaliaram o método por meio de perguntas abertas. De maneira geral, foi considerado um modelo válido, apesar de serem consideradas possíveis limitações, como a necessidade de ser individualizado e adaptado a cada situação.

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.

Evaluation of the in vivo binding of 99mTc-MDP on serum proteins

International Nuclear Information System (INIS)

Freitas, R.S.F.; Mattos, D.M.M.; Gomes, M.L.; Moreno, S.R.F.; Lima, E.A.C.; Dire, G.F.; Aleixo, L.C.M.; Lima Filho, G.L.; Bernardo-Filho, M.

2002-01-01

Aim: In the clinical application of technetium-99m-radiopharmaceuticals (99mTc) these agents are injected into the blood stream and they may bind reversibly and irreversibly to the blood proteins. To evaluate the protein binding of the radiopharmaceutical, the protein-bound 99mTc-radiopharmaceuticals must be separated from the free 99mTc-radiopharmaceuticals complexes. This has been accomplished by precipitation of the proteins. In this study, we have compared the results obtained with the evaluation of the binding of the radiopharmaceutical Tc-99m methylenediphosphonic acid (99mTc-MDP) on serum proteins using precipitation methods with TCA and AS. Material and Methods: 99mTc-MDP was administrated in Wistar rats and after 10 minutes blood was withdrawn and serum (S) isolated. Aliquots of S were precipitated with 1 ml of TCA or AS at various concentrations (0.1, 0.5, 1.0, 5.0, 10.0 and 20.0%) and soluble (SF) and insoluble fractions (IF) were separated. The samples (IF-S and SF-S) were counted in a well counter with NaI(TI)crystal. The percent of the radioactivity (%ATI) was determined in each fraction. Results: The results obtained with the comparison of the in vivo binding of 99mTc-MDP when the precipitation was performed with TCA showed that the %ATI was only statistically different (ANOVA, p<0.05) to the 20% TCA concentration. When various concentrations of AS were used no differences in the %ATI were found and the results were similar to the obtained with TCA, except to the concentration of 20%(TCA - 51.70 ± 10.19 and SA - 10.17 ± 0.98 %). Conclusion: It is possible to suggest that the different concentrations of the precipitating agents (TCA and AS) act, in general, on the same binding sites of the evaluate radiopharmaceutical to the proteins of the serum, except to concentration of 20%

Dynamics of bacterial communities in two unpolluted soils after spiking with phenanthrene: soil type specific and common responders

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Guo-Chun eDing

2012-08-01

Full Text Available Considering their key role for ecosystem processes, it is important to understand the response of microbial communities in unpolluted soils to pollution with polycyclic aromatic hydrocarbons (PAH. Phenanthrene, a model compound for PAH, was spiked to a Cambisol and a Luvisol soil. Total community DNA from phenanthrene-spiked and control soils collected on days 0, 21 and 63 were analyzed based on PCR-amplified 16S rRNA genefragments. Denaturing gradient gel electrophoresis (DGGE fingerprints of bacterial communities increasingly deviated with time between spiked and control soils. In taxon specific DGGE, significant responses of Alphaproteobacteria and Actinobacteria became only detectable after 63 days, while significant effects on Betaproteobacteria were detectable in both soils after 21 days. Comparison of the taxonomic distribution of bacteria in spiked and control soils on day 63 as revealed by pyrosequencing indicated soil type specific negative effects of phenanthrene on several taxa, many of them belonging to the Gamma-, Beta- or Deltaproteobacteria. Bacterial richness and evenness decreased in spiked soils. Despite the significant differences in the bacterial community structure between both soils on day 0, similar genera increased in relative abundance after PAH spiking, especially Sphingomonas and Polaromonas. However, this did not result in an increased overall similarity of the bacterial communities in both soils.

Macroscopic phase-resetting curves for spiking neural networks

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Dumont, Grégory; Ermentrout, G. Bard; Gutkin, Boris

2017-10-01

The study of brain rhythms is an open-ended, and challenging, subject of interest in neuroscience. One of the best tools for the understanding of oscillations at the single neuron level is the phase-resetting curve (PRC). Synchronization in networks of neurons, effects of noise on the rhythms, effects of transient stimuli on the ongoing rhythmic activity, and many other features can be understood by the PRC. However, most macroscopic brain rhythms are generated by large populations of neurons, and so far it has been unclear how the PRC formulation can be extended to these more common rhythms. In this paper, we describe a framework to determine a macroscopic PRC (mPRC) for a network of spiking excitatory and inhibitory neurons that generate a macroscopic rhythm. We take advantage of a thermodynamic approach combined with a reduction method to simplify the network description to a small number of ordinary differential equations. From this simplified but exact reduction, we can compute the mPRC via the standard adjoint method. Our theoretical findings are illustrated with and supported by numerical simulations of the full spiking network. Notably our mPRC framework allows us to predict the difference between effects of transient inputs to the excitatory versus the inhibitory neurons in the network.

Macroscopic phase-resetting curves for spiking neural networks.

Science.gov (United States)

Dumont, Grégory; Ermentrout, G Bard; Gutkin, Boris

2017-10-01

The study of brain rhythms is an open-ended, and challenging, subject of interest in neuroscience. One of the best tools for the understanding of oscillations at the single neuron level is the phase-resetting curve (PRC). Synchronization in networks of neurons, effects of noise on the rhythms, effects of transient stimuli on the ongoing rhythmic activity, and many other features can be understood by the PRC. However, most macroscopic brain rhythms are generated by large populations of neurons, and so far it has been unclear how the PRC formulation can be extended to these more common rhythms. In this paper, we describe a framework to determine a macroscopic PRC (mPRC) for a network of spiking excitatory and inhibitory neurons that generate a macroscopic rhythm. We take advantage of a thermodynamic approach combined with a reduction method to simplify the network description to a small number of ordinary differential equations. From this simplified but exact reduction, we can compute the mPRC via the standard adjoint method. Our theoretical findings are illustrated with and supported by numerical simulations of the full spiking network. Notably our mPRC framework allows us to predict the difference between effects of transient inputs to the excitatory versus the inhibitory neurons in the network.

Population activity statistics dissect subthreshold and spiking variability in V1.

Science.gov (United States)

Bányai, Mihály; Koman, Zsombor; Orbán, Gergő

2017-07-01

Response variability, as measured by fluctuating responses upon repeated performance of trials, is a major component of neural responses, and its characterization is key to interpret high dimensional population recordings. Response variability and covariability display predictable changes upon changes in stimulus and cognitive or behavioral state, providing an opportunity to test the predictive power of models of neural variability. Still, there is little agreement on which model to use as a building block for population-level analyses, and models of variability are often treated as a subject of choice. We investigate two competing models, the doubly stochastic Poisson (DSP) model assuming stochasticity at spike generation, and the rectified Gaussian (RG) model tracing variability back to membrane potential variance, to analyze stimulus-dependent modulation of both single-neuron and pairwise response statistics. Using a pair of model neurons, we demonstrate that the two models predict similar single-cell statistics. However, DSP and RG models have contradicting predictions on the joint statistics of spiking responses. To test the models against data, we build a population model to simulate stimulus change-related modulations in pairwise response statistics. We use single-unit data from the primary visual cortex (V1) of monkeys to show that while model predictions for variance are qualitatively similar to experimental data, only the RG model's predictions are compatible with joint statistics. These results suggest that models using Poisson-like variability might fail to capture important properties of response statistics. We argue that membrane potential-level modeling of stochasticity provides an efficient strategy to model correlations. NEW & NOTEWORTHY Neural variability and covariability are puzzling aspects of cortical computations. For efficient decoding and prediction, models of information encoding in neural populations hinge on an appropriate model of

Retrospective analysis of dengue specific IgM reactive serum samples

OpenAIRE

Nemai Bhattacharya; Bhaswati Bandyopadhyay; Indranil Bhattacharjee; Hiranmoy Mukherjee; Srabani Talukdar; Ruby Mondal; Netai Pramanick; Goutam Chandra; Amiya K. Hati

2013-01-01

Objective: To conduct a retrospective analysis of dengue cases in Kolkata, on the basis of presence of anti-dengue IgM in their sera and presence or absence of anti-dengue IgG and dengue specific Non structural 1 (NS1) antigen in each of the serum sample. Methods: Sample was tested quantitatively employing ELISA technique, using Biorad test kits, with a view to get a more comprehensive picture of dengue in an urban endemic area and also to evaluate individual cases. Results: Th...

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

Directory of Open Access Journals (Sweden)

Michael eHines

2011-11-01

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

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.

Mucorales species activation of a serum leukotactic factor.

Science.gov (United States)

Marx, R S; Forsyth, K R; Hentz, S K

1982-01-01

Previous studies have suggested that the focal accumulation of phagocytic leukocytes is an important feature of the host response in mucormycosis. To ascertain the basis for this influx of inflammatory cells, we evaluated the effect of members of the order Mucorales, including species from the genera Rhizopus, Absidia, and Mucor, on the chemotactic activity of normal human serum for neutrophils and monocytes. Both hyphae and spores produced concentration-dependent chemotaxigenesis in serum to a maximum level equivalent to that produced by zymosan activation of serum. Chemotactic activity was similar for live and heat-killed hyphae. No leukotactic activity was demonstrated in the absence of serum. The pretreatment of serum with anti-C3 antibody, heating at 56 degrees C, or 0.01 M EDTA abolished the activity. The pretreatment of serum with 0.01 M ethylene glycol-bis(beta-aminoethyl ether)-N,N-tetraacetic acid did not abolish the activity. These data provide evidence that the leukotactic activity of Mucorales species is generated through the alternative complement pathway. PMID:6759409

Theta-frequency resonance at the cerebellum input stage improves spike-timing on the millisecond time-scale

Directory of Open Access Journals (Sweden)

Daniela eGandolfi

2013-04-01

Full Text Available The neuronal circuits of the brain are thought to use resonance and oscillations to improve communication over specific frequency bands (Llinas, 1988; Buzsaki, 2006. However, the properties and mechanism of these phenomena in brain circuits remain largely unknown. Here we show that, at the cerebellum input stage, the granular layer generates its maximum response at 5-7 Hz both in vivo following tactile sensory stimulation of the whisker pad and in acute slices following mossy fiber-bundle stimulation. The spatial analysis of granular layer activity performed using voltage-sensitive dye (VSD imaging revealed 5-7 Hz resonance covering large granular layer areas. In single granule cells, resonance appeared as a reorganization of output spike bursts on the millisecond time-scale, such that the first spike occurred earlier and with higher temporal precision and the probability of spike generation increased. Resonance was independent from circuit inhibition, as it persisted with little variation in the presence of the GABAA receptor blocker, gabazine. However, circuit inhibition reduced the resonance area more markedly at 7 Hz. Simulations with detailed computational models suggested that resonance depended on intrinsic granule cells ionic mechanisms: specifically, Kslow (M-like and KA currents acted as resonators and the persistent Na current and NMDA current acted as amplifiers. This form of resonance may play an important role for enhancing coherent spike emission from the granular layer when theta-frequency bursts are transmitted by the cerebral cortex and peripheral sensory structures during sensory-motor processing, cognition and learning.

Fatty acyltranferases in serum in cystic fibrosis (CF) patients

International Nuclear Information System (INIS)

Zielenski, J.; Newman, L.J.; Slomiany, B.L.; Slomiany, A.

1987-01-01

Studies on serum and gastrointestinal secretion from CF patient is suggest that defective accumulation of mucus in gastrointestinal tract and excessive amount of a protease resistant peptides in serum are related to the abnormal activity of enzymes responsible for fatty acylation of proteins. Here, the authors investigated the fatty acyltransferase activities in serum of normal and CF patients. A 15μl of serum was mixed with 0.85 nmol [ 14 C]palmitoyl CoA, 200μg of serine and threonine and incubated at 37 0 C for 30 min. The incubates were immediately frozen, dried extracted with C/M and chromatographed in chloroform/methanol/water. The incorporation of [ 14 C]palmitate was determined using linear radioscanner and authoradiography. The results of HPTLC revealed that CF serum in addition of ACAT and LCAT contained enzymes responsible for the transfer of [ 14 C]palmitate to monoacylphosphoglycerides, and serine and threonine. In normal serum the formation of a small amount of palmitoyl serine and palmitoyl threonine was also observed but the acylation of monoacylphosphoglycerides was not detectable. The authors conclude that in cystic fibrosis the abnormal fatty acyltransferases are responsible for the occurrence of protease resistant glycoprotein, unusual peptides in serum and possibly for the modification of membrane proteins and lipids

Association between Serum Cortisol and DHEA-S Levels and Response to Antipsychotic Treatment in Schizophrenia

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Zoja Babinkostova

2015-02-01

Full Text Available BACKGROUND: Previous studies suggested that alterations in serum cortisol and DHEA-S levels may play a role in the pathophysiology of schizophrenia. AIM: To compare serum cortisol and DHEA-S levels between patients with schizophrenia and healthy controls and to evaluate their association with the response to antipsychotic treatment. MATERIAL AND METHODS: In this clinical prospective study were included 60 patients with schizophrenia and 40 healthy age and sex matched control subjects. Clinical evaluation of patients was performed using the Positive and Negative Symptom Scale. A questionnaire for socio-demographic and clinical data collection was used. For the purposes of the study, the examined group was divided in two subgroups: responders and nonresponders. Serum cortisol and DHEA-S levels were measured at baseline in all participants and after 3 and 6 weeks of the antipsychotic treatment in patients with schizophrenia. RESULTS: Patients with schizophrenia had significantly higher serum cortisol and DHEA-S levels in comparison to the control group. Responders had significantly higher serum cortisol and DHEA-S levels compared with nonresponders. CONCLUSION: Elevated serum cortisol and DHEA-S levels may play a role in the pathophysiology of schizophrenia and they may be related to positive response to antipsychotic treatment in patients with schizophrenia.

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.

Cholinergic neuromodulation changes phase response curve shape and type in cortical pyramidal neurons.

Directory of Open Access Journals (Sweden)

Klaus M Stiefel

Full Text Available Spike generation in cortical neurons depends on the interplay between diverse intrinsic conductances. The phase response curve (PRC is a measure of the spike time shift caused by perturbations of the membrane potential as a function of the phase of the spike cycle of a neuron. Near the rheobase, purely positive (type I phase-response curves are associated with an onset of repetitive firing through a saddle-node bifurcation, whereas biphasic (type II phase-response curves point towards a transition based on a Hopf-Andronov bifurcation. In recordings from layer 2/3 pyramidal neurons in cortical slices, cholinergic action, consistent with down-regulation of slow voltage-dependent potassium currents such as the M-current, switched the PRC from type II to type I. This is the first report showing that cholinergic neuromodulation may cause a qualitative switch in the PRCs type implying a change in the fundamental dynamical mechanism of spike generation.

On the robustness of EC-PC spike detection method for online neural recording.

Science.gov (United States)

Zhou, Yin; Wu, Tong; Rastegarnia, Amir; Guan, Cuntai; Keefer, Edward; Yang, Zhi

2014-09-30

Online spike detection is an important step to compress neural data and perform real-time neural information decoding. An unsupervised, automatic, yet robust signal processing is strongly desired, thus it can support a wide range of applications. We have developed a novel spike detection algorithm called "exponential component-polynomial component" (EC-PC) spike detection. We firstly evaluate the robustness of the EC-PC spike detector under different firing rates and SNRs. Secondly, we show that the detection Precision can be quantitatively derived without requiring additional user input parameters. We have realized the algorithm (including training) into a 0.13 μm CMOS chip, where an unsupervised, nonparametric operation has been demonstrated. Both simulated data and real data are used to evaluate the method under different firing rates (FRs), SNRs. The results show that the EC-PC spike detector is the most robust in comparison with some popular detectors. Moreover, the EC-PC detector can track changes in the background noise due to the ability to re-estimate the neural data distribution. Both real and synthesized data have been used for testing the proposed algorithm in comparison with other methods, including the absolute thresholding detector (AT), median absolute deviation detector (MAD), nonlinear energy operator detector (NEO), and continuous wavelet detector (CWD). Comparative testing results reveals that the EP-PC detection algorithm performs better than the other algorithms regardless of recording conditions. The EC-PC spike detector can be considered as an unsupervised and robust online spike detection. It is also suitable for hardware implementation. Copyright © 2014 Elsevier B.V. All rights reserved.

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...

Precise determination of sodium in serum by simulated isotope dilution method of inductively coupled plasma mass spectrometry

International Nuclear Information System (INIS)

Yan Ying; Zhang Chuanbao; Zhao Haijian; Chen Wenxiang; Shen Ziyu; Wang Xiaoru; Chen Dengyun

2007-01-01

A new precise and accurate method for the determination of sodium in serum by inductively coupled plasma mass spectrometry (ICP-MS) was developed. Since 23 Na is the single isotope element, 27 Al is selected as simulated isotope of Na. Al is spiked into serum samples and Na standard solution. 23 Na/ 27 Al ratio in the Na standard solution is determined to assume the natural Na isotope ratio. The serums samples are digested by purified HNO 3 /H 2 O 2 and diluted to get about 0.6 μg·g -1 Al solutions, and the 23 Na/ 27 Al ratios of the serum samples are obtained to calculate the accurate Na concentrations basing on the isotope dilution method. When the simulated isotope dilution method of ICP-MS is applied and Al is selected as the simulated isotope of Na, the precise and accurate Na concentrations in the serums are determined. The inter-day precision of CV<0.13% for one same serum sample is obtained during 3 days 4 measurements. The spike recoveries are between 99.69% and 100.60% for 4 different serum samples and 3 days multi-measurements. The results of measuring standard reference materials of serum sodium are agree with the certified value. The relative difference between 3 days is 0.22%-0.65%, and the relative difference in one bottle is 0.15%-0.44%. The ICP-MS and Al simulated isotope dilution method is proved to be not only precise and accurate, but also quick and convenient for measuring Na in serum. It is promising to be a reference method for precise determination of Na in serum. Since Al is a low cost isotope dilution reagent, the method is possible to be widely applied for serum Na determination. (authors)

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.

Comparison of Listeria monocytogenes recoveries from spiked mung bean sprouts by the enrichment methods of three regulatory agencies.

Science.gov (United States)

Cauchon, Kaitlin E; Hitchins, Anthony D; Smiley, R Derike

2017-09-01

Three selective enrichment methods, the United States Food and Drug Administration's (FDA method), the United States Department of Agriculture Food Safety Inspection Service's (USDA method), and the EN ISO 11290-1 standard method, were assessed for their suitability for recovery of Listeria monocytogenes from spiked mung bean sprouts. Three parameters were evaluated; the enrichment L. monocytogenes population from singly-spiked sprouts, the enrichment L. monocytogenes population from doubly-spiked (L. monocytogenes and Listeria innocua) sprouts, and the population differential resulting from the enrichment of doubly-spiked sprouts. Considerable L. monocytogenes inter-strain variation was observed. The mean enrichment L. monocytogenes populations for singly-spiked sprouts were 6.1 ± 1.2, 4.9 ± 1.2, and 6.9 ± 2.3 log CFU/mL for the FDA, USDA, and EN ISO 11290-1 methods, respectively. The mean L. monocytogenes populations for doubly-spiked sprouts were 4.7 ± 1.1, 5.5 ± 1.3, and 4.6 ± 1.4 log CFU/mL for the FDA, USDA, and ISO 11290-1 enrichment methods, respectively. The corresponding mean population differentials were 2.8 ± 1.1, 3.3 ± 1.3, and 3.6 ± 1.4 Δlog CFU/mL for the same three enrichment methods, respectively. The presence of L. innocua and resident microorganisms on the sprouts negatively impacted final levels of L. monocytogenes with all three enrichment methods. Published by Elsevier Ltd.

Clinical significance of determination of some serum cytokines (IL-8, IL-10, IL-18, M-CSF) levels in patients with periodontitis

International Nuclear Information System (INIS)

Wei Dong; Zhang Xiaolei; Yang Chunxiu; Chen Guanghua

2008-01-01

Objective: To explore the significance of changes of serum IL-8, IL-10, IL-18 and M-CSF levels in patients with periodontitis. Methods: Serum levels of IL-8, IL-10, M-CSF (with RIA) and IL-18 (with ELISA) were measured in 55 patients with periodontitis both before and after treatment as well as in 35 controls. Results: Before treatment, serum levels of IL-8, IL-10, IL-18 and M-CSF were significantly higher in the patients than those in the controls (P<0.01). After one month of treatment, the serum IL-8, IL-10, IL-18 and M-CSF levels decreased somewhat, but were still significantly higher than those in controls (P<0.05). Conclusion: There was disturbance of immunomodulation in patients with periodontitis as expressed by the changes of several cytokines levels in the eourse of the diseases. (authors)

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

Improving Spiking Dynamical Networks: Accurate Delays, Higher-Order Synapses, and Time Cells.

Science.gov (United States)

Voelker, Aaron R; Eliasmith, Chris

2018-03-01

Researchers building spiking neural networks face the challenge of improving the biological plausibility of their model networks while maintaining the ability to quantitatively characterize network behavior. In this work, we extend the theory behind the neural engineering framework (NEF), a method of building spiking dynamical networks, to permit the use of a broad class of synapse models while maintaining prescribed dynamics up to a given order. This theory improves our understanding of how low-level synaptic properties alter the accuracy of high-level computations in spiking dynamical networks. For completeness, we provide characterizations for both continuous-time (i.e., analog) and discrete-time (i.e., digital) simulations. We demonstrate the utility of these extensions by mapping an optimal delay line onto various spiking dynamical networks using higher-order models of the synapse. We show that these networks nonlinearly encode rolling windows of input history, using a scale invariant representation, with accuracy depending on the frequency content of the input signal. Finally, we reveal that these methods provide a novel explanation of time cell responses during a delay task, which have been observed throughout hippocampus, striatum, and cortex.

Cervical mucus and serum estradiol as predictors of response to progestin challenge.

Science.gov (United States)

Rarick, L D; Shangold, M M; Ahmed, S W

1990-08-01

The present study was undertaken to assess the correlation between and relative predictive value of each of the following variables and progestin-induced withdrawal bleeding: cervical mucus appearance, serum E2 level, patient age, duration of amenorrhea, smoking and exercise habits, and body composition. Of 120 oligomenorrheic and amenorrheic women evaluated, only cervical mucus appearance and serum E2 level were significantly associated with response to progestin challenge. A multivariate logistical regression analysis showed cervical mucus to be the most predictive variable followed by serum E2 level. No absolute E2 level was found to discriminate between those who did and those who did not have withdrawal bleeding after progestin challenge. These data suggest that office examination of cervical mucus may be a useful indicator and guideline in planning therapy.

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.

Clinical significance of measurement of changes of serum hs-CRP, IL-6, IL-8 M-CSF levels after treatment in patients with endometriosis

International Nuclear Information System (INIS)

Chen Xiaochao; Zhou Dongxia; Zhang Limin; Liu Hongshu

2008-01-01

Objective: To explore the significance of changes of serum hs-CRP, IL-6, IL-8 and M-CSF levels after treatment in patients with endometriosis. Methods: Serum IL-6, IL-8, M -CSF(with RIA), hs-CRP(with immuneturbidity method)levels were determined in 33 patients with endometriosis both before and after treatment as well as in 35 controls. Results: Before treatment, the serum hs-CRP, IL-6, IL-8 and M-CSF levels were significantly higher in the patients than those in controls (P 0.05). Conclusion: Detection of serum hs-CRP, IL-6, IL-8 and M-CSF levels might reflect the progress of diseases in patients with endometriosis. (authors)

Pioneer round of translation occurs during serum starvation

International Nuclear Information System (INIS)

Oh, Nara; Kim, Kyoung Mi; Cho, Hana; Choe, Junho; Kim, Yoon Ki

2007-01-01

The pioneer round of translation plays a role in translation initiation of newly spliced and exon junction complex (EJC)-bound mRNAs. Nuclear cap-binding protein complex CBP80/20 binds to those mRNAs at the 5'-end, recruiting translation initiation complex. As a consequence of the pioneer round of translation, the bound EJCs are dissociated from mRNAs and CBP80/20 is replaced by the cytoplasmic cap-binding protein eIF4E. Steady-state translation directed by eIF4E allows for an immediate and rapid response to changes in physiological conditions. Here, we show that nonsense-mediated mRNA decay (NMD), which restricts only to the pioneer round of translation but not to steady-state translation, efficiently occurs even during serum starvation, in which steady-state translation is drastically abolished. Accordingly, CBP80 remains in the nucleus and processing bodies are unaffected in their abundance and number in serum-starved conditions. These results suggest that mRNAs enter the pioneer round of translation during serum starvation and are targeted for NMD if they contain premature termination codons

Voltage spike detection in high field superconducting accelerator magnets

Energy Technology Data Exchange (ETDEWEB)

Orris, D.F.; Carcagno, R.; Feher, S.; Makulski, A.; Pischalnikov, Y.M.; /Fermilab

2004-12-01

A measurement system for the detection of small magnetic flux changes in superconducting magnets, which are due to either mechanical motion of the conductor or flux jump, has been developed at Fermilab. These flux changes are detected as small amplitude, short duration voltage spikes, which are {approx}15mV in magnitude and lasts for {approx}30 {micro}sec. The detection system combines an analog circuit for the signal conditioning of two coil segments and a fast data acquisition system for digitizing the results, performing threshold detection, and storing the resultant data. The design of the spike detection system along with the modeling results and noise analysis will be presented. Data from tests of high field Nb{sub 3}Sn magnets at currents up to {approx}20KA will also be shown.

Voltage spike detection in high field superconducting accelerator magnets

International Nuclear Information System (INIS)

Orris, D.F.; Carcagno, R.; Feher, S.; Makulski, A.; Pischalnikov, Y.M.

2004-01-01

A measurement system for the detection of small magnetic flux changes in superconducting magnets, which are due to either mechanical motion of the conductor or flux jump, has been developed at Fermilab. These flux changes are detected as small amplitude, short duration voltage spikes, which are ∼15mV in magnitude and lasts for ∼30(micro)sec. The detection system combines an analog circuit for the signal conditioning of two coil segments and a fast data acquisition system for digitizing the results, performing threshold detection, and storing the resultant data. The design of the spike detection system along with the modeling results and noise analysis will be presented. Data from tests of high field Nb3Sn magnets at currents up to ∼20KA will also be shown

[The value of serum heavy/light chain immunoassay to assess therapeutic response in patients with multiple myeloma].

Science.gov (United States)

Yu, X C; Su, W; Zhuang, J L

2018-04-14

Objective: To assess the value of immunoglobulin heavy/light chain (HLC) immunoassay on therapeutic response in patients with multiple myeloma(MM). Methods: A total of 45 newly diagnosed MM patients were retrospectively enrolled in Peking Union Medical College Hospital from 2013 to 2016, whose 115 serum samples were consecutively collected. HLC was tested to evaluate response and compare with other methods for M protein detection. Results: ①There were 30 males and 15 females in total of whom the monoclonal immunoglobulin was IgG in 27 (IgGκ∶IgGλ 12∶15) and IgA (IgAκ∶IgAλ 9∶9) in 18. The arerage age of the studied population was 59 (range 43-80) . ② In 34 patients with serum sample at diagnosis, 32 (94.1%) had abnormal HLC ratio (rHLC) while 2 patients with IgG had normal rHLC. The percentages of abnormal rHLC was 81.8% (18/22) at partial response、50.0%(9/18) at very good complete response and 16.0%(4/25) at complete response. ③In 25 patients reaching CR, there were 13 with IgG and 12 with IgA. 4 patients equally split of IgG and IgA had abnormal rHLC at complete response. ④By monitoring the rHLC of some patients consecutively, we found that the remission of rHLC was to some extent behind the remission of SPE and IEF, or even rFLC. Conclusion: Immunoglobulin HLC detection is one feasible method for minimal residual disease detection.

Spike timing precision of neuronal circuits.

Science.gov (United States)

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

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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

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

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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

(99m) Tc-labelled human serum albumin cannot replace (125) I-labelled human serum albumin to determine plasma volume in patients with liver disease

DEFF Research Database (Denmark)

Henriksen, Ulrik Lütken; Henriksen, Jens H; Bendtsen, Flemming

2013-01-01

Summary Background and aims Determination of plasma volume (PV) is important in several clinical situations. Thus, patients with liver disease often have augmented PV as part of their sodium–water retention. This study was undertaken to compare PV determination by two indicators: technetium......-labelled human serum albumin (99mTc-HSA) and iodine-labelled human serum albumin (125I-HSA), as the former may have advantages at repeated measurements and the latter is the classical gold standard. Study population and methods In 88 patients, (64 with liver disease, mainly cirrhosis, and 24 patients without...... In all patients, a close correlation was present between PV determined by the two indicators (r = 0·89, Pdetermined with 99mTc-HSA exceeded PV determined with 125I-HSA by 367 ml (5·2 ml kg...

Utility of serum periostin and free IgE levels in evaluating responsiveness to omalizumab in patients with severe asthma.

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Tajiri, T; Matsumoto, H; Gon, Y; Ito, R; Hashimoto, S; Izuhara, K; Suzukawa, M; Ohta, K; Ono, J; Ohta, S; Ito, I; Oguma, T; Inoue, H; Iwata, T; Kanemitsu, Y; Nagasaki, T; Niimi, A; Mishima, M

2016-10-01

Omalizumab, a humanized anti-IgE monoclonal antibody, has demonstrated efficacy in patients with severe allergic asthma. However, treatment responses vary widely among individuals. Despite a lack of data, free serum IgE levels following omalizumab treatment have been proposed as a marker of treatment responsiveness. In this prospective, observational study, we assessed the utility of biomarkers of type 2 inflammation in predicting omalizumab treatment responses, as determined by the absence of asthma exacerbation during the first year of treatment. Free serum IgE levels were monitored for 2 years to examine their association with baseline biomarker levels and the number of exacerbations. We enrolled thirty patients who had been treated with omalizumab for at least 1 year, of whom 27 were treated for 2 years. Baseline serum periostin levels and blood eosinophil counts were significantly higher in patients without exacerbations during the first year of treatment than in patients with exacerbations. Baseline serum periostin levels, but not eosinophil counts, were negatively associated with free serum IgE levels after 16 or 32 weeks of treatment. Reduced free serum IgE levels during treatment from those at baseline were associated with reduced exacerbation numbers at 2 years. In 14 patients who continued to have exacerbations during the first year of treatment, exacerbation numbers gradually and significantly decreased over the 2-year study period, with concurrent significant reductions in free serum IgE levels. Baseline serum periostin levels and serum free IgE levels during treatment follow-up may be useful in evaluating responses to omalizumab treatment. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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.

Association of basal serum androgen levels with ovarian response and ICSI cycle outcome.

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Abide Yayla, C; Ozkaya, E; Kayatas Eser, S; Sanverdi, I; Devranoglu, B; Kutlu, T

2018-05-01

The purpose of this study was to assess the predictive value of basal serum testosterone (T) and dehydroepiandrosterone sulfate (DHEAS) levels during follicular phase for ovarian response and outcome in intracytoplasmic sperm injection (ICSI) cycles of women with diminished ovarian reserve. We prospectively gathered data of basal serum androgen levels and ICSI cycle characteristics of 120 women with diminished ovarian reserve. Association of basal serum T and DHEAS levels with ovarian response was analyzed. Basal T and DHEAS levels were similar between pregnant and non-pregnant cases (P > 0.05). There were significant differences between groups with and without successful embryo implantation in terms of serum follicle-stimulating hormone (FSH), anti-Müllerian hormone (AMH), gonadotropin starting and total dose, and peak estradiol level (P stimulation due to unresponsiveness (n = 26, 21.7%), no oocyte at oocyte pickup (n = 11, 9.2%), no mature oocyte (n = 6, 5%), and failure of fertilization or embryo development (n = 15, 12.5%). Basal androgen levels were not significant predictors for any of the cycle outcome. AMH level was a significant predictor for failure of fertilization or embryo development (AUC 0.722, P = 0.01) and cancelation of stimulation (AUC 0.801, P stimulation (AUC 0.774, P basal T and DHEAS levels have no value in predicting any of the cycle outcome parameters.

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.

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

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

2016-08-15

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

Expression of the protein serum amyloid A in response to Aspergillus fumigatus in murine models of allergic airway inflammation.

Science.gov (United States)

Moran, Gabriel; Carcamo, Carolina; Concha, Margarita; Folch, Hugo

2015-01-01

Serum amyloid A (SAA) is an acute phase protein that is elevated in blood during inflammation. The role of this protein in allergic diseases of airways remains unclear. The objective of this study was to evaluate the SAA in blood, lung and bronchial cells in a murine model of bronchial hypersensitivity to Aspergillus fumigatus. To achieve this purpose, different groups of 5-month-old mice were housed in cages containing hay bedding that was contaminated with A. fumigatus and were kept in an isolation room for 16 days to allow for the induction of allergic airway inflammation. Subsequently, the mice were then exposed once again to Aspergillus spores at 0, 2, 8, 24 and 72 h, and they were bled to acquire serum and sacrificed to obtain bronchoalveolar lavage fluid (BALF) or lung tissues for analysis. SAA levels were measured in lung, serum and BALF by dot blot assay and RT-PCR (reverse transcription polymerase chain reaction). The results indicated that SAA protein levels increased in both serum and lung within 2-24h after mice were exposed to Aspergillus spores. Moreover, the SAA mRNA expression levels in the lungs and BALF cells demonstrated the same trend that was observed for the protein levels through the dot blot assay; in particular, SAA mRNA levels increased within the first hour after mice were exposed to A. fumigatus. In this allergic airway model, we conclude that A. fumigatus can induce an acute inflammatory response in the airways through the stimulation of the SAA protein, increasing its levels in serum, lung tissue and BALF samples during the early hours of exposure of mice that have been sensitised for this fungus. Copyright © 2012 Revista Iberoamericana de Micología. Published by Elsevier Espana. All rights reserved.

Chip-to-Chip Half Duplex Spiking Data Communication over Power Supply Rails

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Hashida, Takushi; Nagata, Makoto

Chip-to-chip serial data communication is superposed on power supply over common Vdd/Vss connections through chip, package, and board traces. A power line transceiver demonstrates half duplex spiking communication at more than 100Mbps. A pair of transceivers consumes 1.35mA from 3.3V, at 130Mbps. On-chip power line LC low pass filter attenuates pseudo-differential communication spikes by 30dB, purifying power supply current for internal circuits. Bi-directional spiking communication was successfully examined in a 90-nm CMOS prototype setup of on-chip waveform capturing. A micro controller forwards clock pulses to and receives data streams from a comparator based waveform capturer formed on a different chip, through a single pair of power and ground traces. The bit error rate is small enough not to degrade waveform acquisition capability, maintaining the spurious free dynamic range of higher than 50dB.

Constructing Precisely Computing Networks with Biophysical Spiking Neurons.

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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

Prognostic impact of clinical course-specific mRNA expression profiles in the serum of perioperative patients with esophageal cancer in the ICU: a case control study

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Oshima Yoshiaki

2010-10-01

Full Text Available Abstract Background We previously reported that measuring circulating serum mRNAs using quantitative one-step real-time RT-PCR was clinically useful for detecting malignancies and determining prognosis. The aim of our study was to find crucial serum mRNA biomarkers in esophageal cancer that would provide prognostic information for post-esophagectomy patients in the critical care setting. Methods We measured serum mRNA levels of 11 inflammatory-related genes in 27 post-esophagectomy patients admitted to the intensive care unit (ICU. We tracked these levels chronologically, perioperatively and postoperatively, until the two-week mark, investigating their clinical and prognostic significance as compared with clinical parameters. Furthermore, we investigated whether gene expression can accurately predict clinical outcome and prognosis. Results Circulating mRNAs in postoperative esophagectomy patients had gene-specific expression profiles that varied with the clinical phase of their treatment. Multivariate regression analysis showed that upregulation of IL-6, VWF and TGF-β1 mRNA in the intraoperative phase (p = 0.016, 0.0021 and 0.009 and NAMPT and MUC1 mRNA on postoperative day 3 (p ®, Ono Pharmaceutical Co., Ltd. significantly correlated with MUC1 and NAMPT mRNA expression (p = 0.048 and 0.045. IL-6 mRNA correlated with hypercytokinemia and recovery from hypercytokinemia (sensitivity 80.9% and was a significant biomarker in predicting the onset of severe inflammatory diseases. Conclusion Chronological tracking of postoperative mRNA levels of inflammatory-related genes in esophageal cancer patients may facilitate early institution of pharamacologic therapy, prediction of treatment response, and prognostication during ICU management in the perioperative period.

A Simple Deep Learning Method for Neuronal Spike Sorting

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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.

Solving Constraint Satisfaction Problems with Networks of Spiking Neurons.

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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.

A Reinforcement Learning Framework for Spiking Networks with Dynamic Synapses

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Karim El-Laithy

2011-01-01

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

Inferior Olive HCN1 Channels Coordinate Synaptic Integration and Complex Spike Timing

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Derek L.F. Garden

2018-02-01

Full Text Available Cerebellar climbing-fiber-mediated complex spikes originate from neurons in the inferior olive (IO, are critical for motor coordination, and are central to theories of cerebellar learning. Hyperpolarization-activated cyclic-nucleotide-gated (HCN channels expressed by IO neurons have been considered as pacemaker currents important for oscillatory and resonant dynamics. Here, we demonstrate that in vitro, network actions of HCN1 channels enable bidirectional glutamatergic synaptic responses, while local actions of HCN1 channels determine the timing and waveform of synaptically driven action potentials. These roles are distinct from, and may complement, proposed pacemaker functions of HCN channels. We find that in behaving animals HCN1 channels reduce variability in the timing of cerebellar complex spikes, which serve as a readout of IO spiking. Our results suggest that spatially distributed actions of HCN1 channels enable the IO to implement network-wide rules for synaptic integration that modulate the timing of cerebellar climbing fiber signals.

Recent progress in multi-electrode spike sorting methods.

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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.

Correlation of Cyfra 21-1 levels in saliva and serum with CK19 mRNA expression in oral squamous cell carcinoma.

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Malhotra, Rewa; Urs, Aadithya B; Chakravarti, Anita; Kumar, Suman; Gupta, V K; Mahajan, Bhawna

2016-07-01

Oral squamous cell carcinoma (OSCC) accounts for 90 % of malignant lesions of oral cavity. The study assessed the potential of Cyfra 21-1 as a tumor marker in OSCC. The study included 50 patients of OSCC to evaluate levels of Cyfra 21-1 in serum and saliva by electrochemiluminescent immunoassay (ECLIA) and CK19 messenger RNA (mRNA) expression in tissue by florescent quantitative real-time reverse transcriptase polymerase chain reaction (RT-PCR) along with healthy individuals as control. The salivary and serum Cyfra 21-1 levels in patients of OSCC were significantly higher compared to controls (p value < 0.01). There was a 2.75-fold increase in CK19 mRNA expression in OSCC cases compared to controls. A significant positive correlation was found between serum and salivary Cyfra 21-1, serum Cyfra 21-1, and CK19 mRNA expression and between salivary Cyfra 21-1 and CK19 mRNA expression. Among these, correlation between serum and salivary Cyfra 21-1 was highly significant. Salivary and serum Cyfra 21-1 showed significantly elevated levels in grade II OSCC compared to grade I histopathologically. Elevated levels of salivary Cyfra 21-1 were associated with recurrence in OSCC patients. Reverse operating curve constructed using 3 ng/ml as a cutoff for serum Cyfra 21-1 revealed the sensitivity and specificity to be 88 and 78.2 %, respectively. Using a cutoff value of 8.5 ng/ml for salivary Cyfra 21-1, the sensitivity was found to be 93.8 % and specificity 84.3 %. We advocate salivary Cyfra 21-1 as a better diagnostic marker over serum Cyfra 21-1 as well as a potential marker in the prognosis of OSCC.

Multineuron spike train analysis with R-convolution linear combination kernel.

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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.

Evaluation of multielements in human serum of patients with chronic myelogenous leukemia (CML) using SRTXRF

International Nuclear Information System (INIS)

Leitao, Catarine Canellas Gondim

2005-04-01

In this work, trace elements were analyzed in serum of patients with chronic myelogenous leukemia (CML) by Total Reflection X-Ray Fluorescence using synchrotron radiation (SRTXRF). Chronic myelogenous leukemia (CML) affects the myeloid cells in the blood and affects 1 to 2 people per 100,000 and accounts for 7-20% cases of leukemia. Sixty patients with CML and sixty healthy volunteers (control group) were studied. Blood was collected into vacutainers without additives. Directly after collection, each blood sample was centrifuged at 3000 rev/min for 10 min in order to separate blood cells and suspended particles from blood serum. Sera were transferred into polyethylene tubes and stored in a freezer at 253 K. A 500 m u L serum quantity was spiked with Ga (50 m u L ) as internal standard. 10 m u L aliquots were pipetted on Perspex sample carrier. After deposition, the samples were left to dry under an infrared lamp. The measurements were performed at the X-Ray Fluorescence Beamline at Brazilian National Synchrotron Light Laboratory (LNLS), using a polychromatic beam. Standard solutions with gallium as internal standard were prepared for calibration system. It was possible to determine the concentrations of the following elements: P, S, Cl, K, Ca, Cr, Mn, Fe, Ni, Cu, Zn, Br and Rb. Starting from the ANOVA test was observed that the elements P, S, Ca, Cr, Mn, Fe, Cu and Rb presented real significant differences (α = 0.05) between groups (healthy subjects and CML patients) and Sex (males and females). (author)

Supervised learning with decision margins in pools of spiking neurons.

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

2014-10-01

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

Serum protein-binding ability of sup(99m)Tc-diethyl IDA and sup(99m)Tc-para-butyl IDA studied by electrophoresis and precipitation experiments

International Nuclear Information System (INIS)

Sawas-Dimopoulou, C.; Simitzis, G.; Papanicolaou, N.

1982-01-01

The aim of the study was to separate and to identify by electrophoresis the proteins which are able to bind 99mTc-diethyl IDA and 99mTc-p-butyl IDA when these radiopharmaceuticals are incubated in vitro with human serum. The determinations were completed by precipitation experiments. Electrophoresis showed that both radiopharmaceuticals have negative charge and move to the anode like organic anions. And it is known that organic anions can interact with cationic groups on the albumin. Moreover, it is generally accepted that the extent to which a drug is bound to a particular protein depends on the concentration of the drug. Consequently, the logical hypothesis that binding of each radiopharmaceutical to the various serum proteins could be easier demonstrated on autoradiographies and electrophoregrams by high concentrations of 99mTc-diethyl IDA and 99mTc-parabutyl IDA in the incubation medium was put to trial

Direct determination of glucose, lactate and triglycerides in blood serum by a tunable quantum cascade laser-based mid-IR sensor

Science.gov (United States)

Brandstetter, M.; Volgger, L.; Genner, A.; Jungbauer, C.; Lendl, B.

2013-02-01

This work reports on a compact sensor for fast and reagent-free point-of-care determination of glucose, lactate and triglycerides in blood serum based on a tunable (1030-1230 cm-1) external-cavity quantum cascade laser (EC-QCL). For simple and robust operation a single beam set-up was designed and only thermoelectric cooling was used for the employed laser and detector. Full computer control of analysis including liquid handling and data analysis facilitated routine measurements. A high optical pathlength (>100 μm) is a prerequisite for robust measurements in clinical practice. Hence, the optimum optical pathlength for transmission measurements in aqueous solution was considered in theory and experiment. The experimentally determined maximum signal-to-noise ratio (SNR) was around 140 μm for the QCL blood sensor and around 50 μm for a standard FT-IR spectrometer employing a liquid nitrogen cooled mercury cadmium telluride (MCT) detector. A single absorption spectrum was used to calculate the analyte concentrations simultaneously by using a partial-least-squares (PLS) regression analysis. Glucose was determined in blood serum with a prediction error (RMSEP) of 6.9 mg/dl and triglycerides with an error of cross-validation (RMSECV) of 17.5 mg/dl in a set of 42 different patients. In spiked serum samples the lactate concentration could be determined with an RMSECV of 8.9 mg/dl.

The i148m Pnpla3 polymorphism influences serum adiponectin in patients with fatty liver and healthy controls

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Valenti Luca

2012-08-01

Full Text Available Abstract Background Reduced adiponectin is implicated in the pathogenesis of nonalcoholic fatty liver disease (NAFLD and steatohepatitis (NASH, and the I148M Patatin-like phospholipase domain-containing 3 (PNPLA3 polymorphism predisposes to NAFLD and liver damage progression in NASH and chronic hepatitis C (CHC by still undefined mechanisms, possibly involving regulation of adipose tissue function. Aim of this study was to evaluate whether the I148M PNPLA3 polymorphism influences serum adiponectin in liver diseases and healthy controls. Methods To this end, we considered 144 consecutive Italian patients with NAFLD, 261 with CHC, 35 severely obese subjects, and 257 healthy controls with very low probability of steatosis, all with complete clinical and genetic characterization, including adiponectin (ADIPOQ genotype. PNPLA3 rs738409 (I148M and ADIPOQ genotypes were evaluated by Taqman assays, serum adiponectin by ELISA. Adiponectin mRNA levels were evaluated by quantitative real-time PCR in the visceral adipose tissue (VAT of 35 obese subjects undergoing bariatric surgery. Results Adiponectin levels were independently associated with the risk of NAFLD and with the histological severity of the disease. Adiponectin levels decreased with the number of 148 M PNPLA3 alleles at risk of NASH both in patients with NAFLD (p = 0.03, and in healthy subjects (p = 0.04. At multivariate analysis, PNPLA3 148 M alleles were associated with low adiponectin levels (ADIPOQ genotype (OR 1.67, 95% c.i. 1.07-2.1 for each 148 M allele. The p.148 M PNPLA3 variant was associated with decreased adiponectin mRNA levels in the VAT of obese patients (p PNPLA3 and ADIPOQ genotypes and viral features. Conclusions The I148M PNPLA3 variant is associated with adiponectin levels in patients with NAFLD and in healthy subjects, but in the presence of adiponectin resistance not in CHC patients. The I148M PNPLA3 genotype may represent a genetic determinant of serum

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

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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/.

Disposable amperometric magnetoimmunosensor for the sensitive detection of the cardiac biomarker amino-terminal pro-B-type natriuretic peptide in human serum

Energy Technology Data Exchange (ETDEWEB)

Esteban-Fernández de Ávila, Berta, E-mail: berta.efa@quim.ucm.es; Escamilla-Gómez, Vanessa, E-mail: vaneeg@quim.ucm.es; Campuzano, Susana, E-mail: susanacr@quim.ucm.es; Pedrero, María, E-mail: mpedrero@quim.ucm.es; Pingarrón, José M., E-mail: pingarro@quim.ucm.es

2013-06-19

Graphical abstract: -- Highlights: •Novel and sensitive amperometric magnetoimmunosensor for NT-proBNP detection. •Indirect competitive immunoassay onto HOOC-MBs and Au/SPEs as transducers. •Excellent analytical performance at levels clinically relevant in human serum. •Useful in clinical diagnosis and prognosis of cardiac diseases. -- Abstract: A novel amperometric magnetoimmunosensor using an indirect competitive format is developed for the sensitive detection of the amino-terminal pro-B-type natriuretic peptide (NT-proBNP). The immunosensor design involves the covalent immobilization of the antigen onto carboxylic-modified magnetic beads (HOOC-MBs) activated with N-(3-dimethylaminopropyl)-N′-ethylcarbodiimide (EDC) and N-hydroxysulfosuccinimide (sulfo-NHS), and further incubation in a mixture solution containing variable concentrations of the antigen and a fixed concentration of an HRP-labeled detection antibody. Accordingly, the target NT-proBNP in the sample and that immobilized on the MBs compete for binding to a fixed amount of the specific HRP-labeled secondary antibody. The immunoconjugate-bearing MBs are captured by a magnet placed under the surface of a disposable gold screen-printed electrode (Au/SPE). The amperometric responses measured at –0.10 V (vs. a Ag pseudo-reference electrode), upon addition of 3,3′,5,5′-tetramethylbenzidine (TMB) as electron transfer mediator and H{sub 2}O{sub 2} as the enzyme substrate, are used to monitor the affinity reaction. The developed magnetoimmunosensor provides attractive analytical characteristics in 10-times diluted human serum samples, exhibiting a linear range of clinical usefulness (0.12–42.9 ng mL{sup −1}) and a detection limit of 0.02 ng mL{sup −1}, which can be used in clinical diagnosis of chronic heart failure in the elderly and for classifying patients at risk of death after heart transplantation. The magnetoimmunosensor was successfully applied to the analysis of spiked human serum

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

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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.

Supervised learning in spiking neural networks with FORCE training.

Science.gov (United States)

Nicola, Wilten; Clopath, Claudia

2017-12-20

Populations of neurons display an extraordinary diversity in the behaviors they affect and display. Machine learning techniques have recently emerged that allow us to create networks of model neurons that display behaviors of similar complexity. Here we demonstrate the direct applicability of one such technique, the FORCE method, to spiking neural networks. We train these networks to mimic dynamical systems, classify inputs, and store discrete sequences that correspond to the notes of a song. Finally, we use FORCE training to create two biologically motivated model circuits. One is inspired by the zebra finch and successfully reproduces songbird singing. The second network is motivated by the hippocampus and is trained to store and replay a movie scene. FORCE trained networks reproduce behaviors comparable in complexity to their inspired circuits and yield information not easily obtainable with other techniques, such as behavioral responses to pharmacological manipulations and spike timing statistics.

Enhanced polychronisation in a spiking network with metaplasticity

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Mira eGuise

2015-02-01

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

Post-spike hyperpolarization participates in the formation of auditory behavior-related response patterns of inferior collicular neurons in Hipposideros pratti.

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Li, Y-L; Fu, Z-Y; Yang, M-J; Wang, J; Peng, K; Yang, L-J; Tang, J; Chen, Q-C

2015-03-19

To probe the mechanism underlying the auditory behavior-related response patterns of inferior collicular neurons to constant frequency-frequency modulation (CF-FM) stimulus in Hipposideros pratti, we studied the role of post-spike hyperpolarization (PSH) in the formation of response patterns. Neurons obtained by in vivo extracellular (N=145) and intracellular (N=171) recordings could be consistently classified into single-on (SO) and double-on (DO) neurons. Using intracellular recording, we found that both SO and DO neurons have a PSH with different durations. Statistical analysis showed that most SO neurons had a longer PSH duration than DO neurons (p<0.01). These data suggested that the PSH directly participated in the formation of SO and DO neurons, and the PSH elicited by the CF component was the main synaptic mechanism underlying the SO and DO response patterns. The possible biological significance of these findings relevant to bat echolocation is discussed. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

Perfluoroalkyl substance serum concentrations and immune response to FluMist vaccination among healthy adults.

Science.gov (United States)

Stein, Cheryl R; Ge, Yongchao; Wolff, Mary S; Ye, Xiaoyun; Calafat, Antonia M; Kraus, Thomas; Moran, Thomas M

2016-08-01

Perfluoroalkyl substances (PFAS) were shown to be immunotoxic in laboratory animals. There is some epidemiological evidence that PFAS exposure is inversely associated with vaccine-induced antibody concentration. We examined immune response to vaccination with FluMist intranasal live attenuated influenza vaccine in relation to four PFAS (perfluorooctanoate, perfluorononanoate, perfluorooctane sulfonate, perfluorohexane sulfonate) serum concentrations among 78 healthy adults vaccinated during the 2010-2011 influenza season. We measured anti-A H1N1 antibody response and cytokine and chemokine concentrations in serum pre-vaccination, 3 days post-vaccination, and 30 days post-vaccination. We measured cytokine, chemokine, and mucosal IgA concentration in nasal secretions 3 days post-vaccination and 30 days post-vaccination. Adults with higher PFAS concentrations were more likely to seroconvert after FluMist vaccination as compared to adults with lower PFAS concentrations. The associations, however, were imprecise and few participants seroconverted as measured either by hemagglutination inhibition (9%) or immunohistochemical staining (25%). We observed no readily discernable or consistent pattern between PFAS concentration and baseline cytokine, chemokine, or mucosal IgA concentration, or between PFAS concentration and change in these immune markers between baseline and FluMist-response states. The results of this study do not support a reduced immune response to FluMist vaccination among healthy adults in relation to serum PFAS concentration. Given the study's many limitations, however, it does not rule out impaired vaccine response to other vaccines or vaccine components in either children or adults. Copyright © 2016 Elsevier Inc. All rights reserved.

Temporary increase in serum beta 2-microglobulin during treatment with interferon-alpha for AIDS-associated Kaposi's sarcoma

NARCIS (Netherlands)

de Wit, R.; Bakker, P. J.; Reiss, P.; Hoek, F. J.; Lange, J. M.; Goudsmit, J.; Veenhof, K. H.

1990-01-01

Beta 2-microglobulin (beta 2-M) levels were determined in the serum of 24 patients treated with high-dose human recombinant interferon-alpha (IFN alpha) for AIDS-associated Kaposi's sarcoma. There was a significant increase in serum beta 2-M levels, irrespective of the response to treatment.

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.

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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.

Changes of serum endocrine hormone levels in patients with cancerrelated fatigue and their correlation with anti-tumor immune response and tumor load

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Lu Yang

2017-08-01

Full Text Available Objective: To study the changes of serum endocrine hormone levels in patients with cancerrelated fatigue (CRF and their correlation with anti-tumor immune response and tumor load. Methods: A total of 137 patients who were diagnosed with primary lung cancer in West China Hospital, Sichuan University between June 2014 and November 2016 were selected and then divided into CRF group and control group according to their self-reported symptoms, serum was collected to determine the levels of endocrine hormones and tumor markers, and peripheral blood was collected to detect the levels of immune cells. Results: Serum ACTH and TSH levels of CRF group were significantly higher than those of control group while Cor, FT3 and FT4 levels were significantly lower than those of control group; peripheral blood CD11b+ CD15 - CD33+ CD14+ M-MDSC, CD11b+ CD15-CD33+ CD14- G-MDSC, CD4+ CD25+ CD127lowTreg and CD19+ CD5+ CD1d+ Breg levels as well as serum CEA, Cyfra21-1, SCC-Ag, HE4, GDF- 15 and PCNA levels of CRF group were significantly higher than those of control group, positively correlated with serum ACTH and TSH levels, and negatively correlated with Cor, FT3 and FT4 levels. Conclusion: The changes of thyroid hormone and adrenal cortical hormone levels in patients with cancer-related fatigue are closely related to the inhibited antitumor immune response and increased tumor load.

Contribution of LFP dynamics to single-neuron spiking variability in motor cortex during movement execution

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Rule, Michael E.; Vargas-Irwin, Carlos; Donoghue, John P.; Truccolo, Wilson

2015-01-01

Understanding the sources of variability in single-neuron spiking responses is an important open problem for the theory of neural coding. This variability is thought to result primarily from spontaneous collective dynamics in neuronal networks. Here, we investigate how well collective dynamics reflected in motor cortex local field potentials (LFPs) can account for spiking variability during motor behavior. Neural activity was recorded via microelectrode arrays implanted in ventral and dorsal premotor and primary motor cortices of non-human primates performing naturalistic 3-D reaching and grasping actions. Point process models were used to quantify how well LFP features accounted for spiking variability not explained by the measured 3-D reach and grasp kinematics. LFP features included the instantaneous magnitude, phase and analytic-signal components of narrow band-pass filtered (δ,θ,α,β) LFPs, and analytic signal and amplitude envelope features in higher-frequency bands. Multiband LFP features predicted single-neuron spiking (1ms resolution) with substantial accuracy as assessed via ROC analysis. Notably, however, models including both LFP and kinematics features displayed marginal improvement over kinematics-only models. Furthermore, the small predictive information added by LFP features to kinematic models was redundant to information available in fast-timescale (spiking history. Overall, information in multiband LFP features, although predictive of single-neuron spiking during movement execution, was redundant to information available in movement parameters and spiking history. Our findings suggest that, during movement execution, collective dynamics reflected in motor cortex LFPs primarily relate to sensorimotor processes directly controlling movement output, adding little explanatory power to variability not accounted by movement parameters. PMID:26157365

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.

Correlation between Changes in Serum Level of CEA and CYFRA 21-1 and Objective Response of Chemotherapy

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Xinlin MU

2009-09-01

Full Text Available Background and objective Serum levels of tumor markers are associated with tumor metabolism or apoptosis, changes of which after chemotherapy may reflect tumor response to treatment. The aim of this study was to assess the predictive role of changes in serum levels of carcinoembryonic antigen (CEA and cytokeratin 19 fragment (CYFRA 21-1 during chemotherapy in patients with advanced non-small cell lung cancer. Methods Changes in serum levels of CEA and CYFRA 21-1 were investigated retrospectively after one cycle of chemotherapy in 42 patients with advanced NSCLC. Correlations between the changes and radiological objective response were analyzed. Results After two cycles of chemotherapy, radiological objective response rate was 28.6%. At baseline, gender, age, clinical stage, serum levels of CEA and CYFRA 21-1 were not different between patients with objective response (OR and no response (NR. After one cycle of chemotherapy, compared to baseline level, declines in serum levels of CEA and CYFRA 21-1 were observed in patients with OR, but have no statistical significance. In contrast, reduction of CEA and CYFRA 21-1 over baseline after one cycle of chemotherapy showed statistically significant difference between OR and NR. When reduction percentages of CEA and CYFRA 21-1 were used to predict objective response of chemotherapy, the area under the ROC curve (AUC was 0.875 for CEA and 0.919 for CYFRA 21-1. According to the ROC curve, a 22% reduction of CEA yielded a sensitivity of 58.3% and a specificity of 97%, 51% reduction of CYFRA 21-1 with a sensitivity of 83.3% and a specificity of 93.3%. When above reduction percentages were used as cutoffs for prediction of radiological objective response, combination of the CEA and CYFRA 21-1 yielded a sensitivity of 91.7% and a specificity of 86.7%. Conclusion Reduction percentages of CEA and CYFRA 21-1 during chemotherapy could be used to evaluate chemotherapy efficacy in patients with advanced NSCLC. The

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.

Spike sorting for polytrodes: a divide and conquer approach

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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.

Spike timing regulation on the millisecond scale by distributed synaptic plasticity at the cerebellum input stage: a simulation study

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Jesus A Garrido

2013-05-01

Full Text Available The way long-term synaptic plasticity regulates neuronal spike patterns is not completely understood. This issue is especially relevant for the cerebellum, which is endowed with several forms of long-term synaptic plasticity and has been predicted to operate as a timing and a learning machine. Here we have used a computational model to simulate the impact of multiple distributed synaptic weights in the cerebellar granular layer network. In response to mossy fiber bursts, synaptic weights at multiple connections played a crucial role to regulate spike number and positioning in granule cells. The weight at mossy fiber to granule cell synapses regulated the delay of the first spike and the weight at mossy fiber and parallel fiber to Golgi cell synapses regulated the duration of the time-window during which the first-spike could be emitted. Moreover, the weights of synapses controlling Golgi cell activation regulated the intensity of granule cell inhibition and therefore the number of spikes that could be emitted. First spike timing was regulated with millisecond precision and the number of spikes ranged from 0 to 3. Interestingly, different combinations of synaptic weights optimized either first-spike timing precision or spike number, efficiently controlling transmission and filtering properties. These results predict that distributed synaptic plasticity regulates the emission of quasi-digital spike patterns on the millisecond time scale and allows the cerebellar granular layer to flexibly control burst transmission along the mossy fiber pathway.

Rotational Angles and Velocities During Down the Line and Diagonal Across Court Volleyball Spikes

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Justin R. Brown

2014-05-01

Full Text Available The volleyball spike is an explosive movement that is frequently used to end a rally and earn a point. High velocity spikes are an important skill for a successful volleyball offense. Although the influence of vertical jump height and arm velocity on spiked ball velocity (SBV have been investigated, little is known about the relationship of shoulder and hip angular kinematics with SBV. Other sport skills, like the baseball pitch share similar movement patterns and suggest trunk rotation is important for such movements. The purpose of this study was to examine the relationship of both shoulder and hip angular kinematics with ball velocity during the volleyball spike. Methods: Fourteen Division I collegiate female volleyball players executed down the line (DL and diagonally across-court (DAC spikes in a laboratory setting to measure shoulder and hip angular kinematics and velocities. Each spike was analyzed using a 10 Camera Raptor-E Digital Real Time Camera System.  Results: DL SBV was significantly greater than for DAC, respectively (17.54±2.35 vs. 15.97±2.36 m/s, p<0.05.  The Shoulder Hip Separation Angle (S-HSA, Shoulder Angular Velocity (SAV, and Hip Angular Velocity (HAV were all significantly correlated with DAC SBV. S-HSA was the most significant predictor of DAC SBV as determined by regression analysis.  Conclusions: This study provides support for a relationship between a greater S-HSA and SBV. Future research should continue to 1 examine the influence of core training exercise and rotational skill drills on SBV and 2 examine trunk angular velocities during various types of spikes during play.

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

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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.

Serum HSV-1 and 2 IgM in sexually transmitted diseases - more for screening less for diagnosis: An evaluation of clinical manifestation

Directory of Open Access Journals (Sweden)

Dharmishtha G Tada

2012-01-01

Full Text Available Background: Herpes simplex virus type 2 (HSV-2 is the cause of most genital herpes. Now, HSV-1 has become an important cause and represents even about 30% of genital herpes in some countries. So, study related to genital herpes should consider both HSV-1 and HSV-2. Aim: To examine trends in HSV-1 and 2 seroprevalence by Serum HSV-1 and 2 IgM in all type of sexually transmitted disease (STD patients and also to evaluate correlation of serum HSV-1 and 2 IgM in STD. Materials and Methods: 150 patients attending the STD clinic attached to a tertiary care hospital of Ahmedabad were included in the study. Serum HSV-1 and 2 IgM correlations with clinical manifestations of recurrent and non-recurrent type of genital herpes patients and other non-herpetic STD patients were studied. Results: The overall serum HSV-1 and 2 IgM in STD seroprevalence were 15.66%. Female has significant higher prevalence (P < 0.05. STD cases and HSV seroprevalence were specially concentrated in persons aged 21 to 30 years. Among those positive with HSV, the distribution of STD are wide spread and found in non-herpetic group at high frequency. Out of total 23 serum HSV-1 and 2 IgM positive, 12 and 11 are distributed in herpetic and non-herpetic STDs, respectively. Discussion and Conclusion: Though serum HSV-1 and 2 IgM in STDs are less diagnostic, they help to see the iceberg part of the infection among the population concerned in recent scenario or in another words, it provides recent infective burden.

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.

Serum Survivin Levels and Outcome of Chemotherapy in Patients with Malignant Mesothelioma

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Katja Goričar

2015-01-01

Full Text Available Background. Survivin is an inhibitor of apoptosis protein involved in the regulation of cell proliferation that could be used as a marker for cancer diagnosis or prognosis. Our aim was to evaluate whether serum survivin levels influence the outcome of cisplatin-based chemotherapy in patients with malignant mesothelioma (MM. Methods. Serum survivin levels were determined using human survivin enzyme-linked immunosorbent assay in 78 MM patients before chemotherapy, after chemotherapy, and at disease progression. The influence on tumor response and survival was evaluated using nonparametric tests and Cox regression. Results. A median serum survivin level at diagnosis was 4.1 (0–217.5 pg/mL. Patients with a progressive disease had significantly higher survivin levels before chemotherapy (p = 0.041. A median serum survivin level after chemotherapy was 73.1 (0–346.2 pg/mL. If survivin levels increased after chemotherapy, patients had, conversely, better response (p = 0.001, OR = 5.40, 95% CI = 1.98–14.72. Unexpectedly, patients with increased survivin levels after chemotherapy also had longer progression-free (p < 0.001, HR = 0.33, 95% CI = 0.20–0.57 and overall survival (p = 0.001, HR = 0.29, 95% CI = 0.14–0.58. Conclusions. These results suggest that serum survivin levels before and during chemotherapy could serve as a biomarker predicting MM treatment response.

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,

Effect of transportation stress on heat shock protein 70 concentration and mRNA expression in heart and kidney tissues and serum enzyme activities and hormone concentrations of pigs.

Science.gov (United States)

Yu, Hong; Bao, En-Dong; Zhao, Ru-Qian; Lv, Qiong-Xia

2007-11-01

To determine the enzymatic and hormonal responses, heat shock protein 70 (Hsp70) production, and Hsp70 mRNA expression in heart and kidney tissues of transport-stressed pigs. 24 pigs (mean weight, 20 +/- 1 kg). Pigs were randomly placed into groups of 12 each. One group was transported for 2 hours. The other group was kept under normal conditions and used as control pigs. Sera were used to detect triiodothyronine, thyroxine, and cortisol concentrations and alanine aminotransferase, aspartate aminotransferase, and creatine kinase activities. The heart and kidneys of anesthetized pigs were harvested and frozen in liquid nitrogen for quantification of Hsp70 and Hsp70 mRNA. No significant differences were detected in serum alanine aminotransferase activity and triiodothyronine and cortisol concentrations between groups; however, the serum creatine kinase and aspartate aminotransferase activities and thyroxine concentrations were higher in transported pigs. Densitometric readings of western blots revealed that the amount of Hsp70 in heart and kidney tissues was significantly higher in transported pigs, compared with control pigs. Results of fluorescence quantitative real-time PCR assay revealed that the Hsp70 mRNA transcription in heart tissue, but not kidney tissue, was significantly higher in transported pigs, compared with control pigs. Transportation imposed a severe stress on pigs that was manifested as increased serum activities of aspartate aminotransferase and creatine kinase and increased amounts of Hsp70 and Hsp70 mRNA expression in heart and kidney tissues. Changes in serum enzyme activities were related to the tissue damage of transport-stressed pigs.

Qualification and application of a surface plasmon resonance-based assay for monitoring potential HAHA responses induced after passive administration of a humanized anti Lewis-Y antibody.

Science.gov (United States)

Szolar, O H J; Stranner, S; Zinoecker, I; Mudde, G C; Himmler, G; Waxenecker, G; Nechansky, A

2006-06-16

A sensitive, surface plasmon resonance (SPR)-based assay monitoring potential human-anti-human antibody (HAHA) reactions against the monoclonal antibody (mAb) IGN311 is presented. The latter is a fully humanized Lewis-Y carbohydrate specific mAb that is currently tested in a passive immune therapy approach in a clinical phase I trial. For the SPR experiments a BIACORE 3000 analyzer was used. The ligand IGN311 was covalently coupled to the carboxy-methylated dextran matrix of a CM5 research grade chip (BIACORE). In the course of a fully nested experimental design, a four parameter logistic equation was identified as appropriate calibration model ranging from 0.3 microg/mL (lower limit of quantitation, LLOQ) to 200 microg/mL (upper limit of quantitation, ULOQ) using an anti-idiotypic mAb ('HAHA mimic') as calibrator. The bias ranged from -2.4% to 5.5% and the intermediate precision expressed as 95% CI revealed values from 5.6% to 8.3%. Specificity was evaluated using six human serum matrices from healthy donors spiked with calibrator at the limit of quantitation (LOQ) with >80% of values being recovered with less than 25% relative error. The qualified assay was applied to monitor potentially induced HAHA reactivity in 11 patients from a clinical phase I trial with passively administered IGN311. Of the 11 patients, one high HAHA responder and several low responders were identified. Protein-G depletion experiments with human serum samples revealed that the observed response is predominantly caused by IgG binding to the ligand. The characteristics of these HAHA responses were all of the so-called 'Type I' which is defined by a peak response around day 15 that decreases from this point steadily suggesting that some kind of tolerance is established. Therefore, this type of HAHA response is regarded as non critical for the patient's safety.

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

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.

Analysis of Serum Total and Free PSA Using Immunoaffinity Depletion Coupled to SRM: Correlation with Clinical Immunoassay Tests

Science.gov (United States)

Liu, Tao; Hossain, Mahmud; Schepmoes, Athena A.; Fillmore, Thomas L.; Sokoll, Lori J.; Kronewitter, Scott R.; Izmirlian, Grant; Shi, Tujin; Qian, Wei-Jun; Leach, Robin J.; Thompson, Ian M.; Chan, Daniel W.; Smith, Richard D.; Kagan, Jacob; Srivastava, Sudhir; Rodland, Karin D.; Camp, David G.

2012-01-01

Recently, selected reaction monitoring mass spectrometry (SRM-MS) has been more frequently applied to measure low abundance biomarker candidates in tissues and biofluids, owing to its high sensitivity and specificity, simplicity of assay configuration, and exceptional multiplexing capability. In this study, we report for the first time the development of immunoaffinity depletion-based workflows and SRM-MS assays that enable sensitive and accurate quantification of total and free prostate-specific antigen (PSA) in serum without the requirement for specific PSA antibodies. Low ng/mL level detection of both total and free PSA was consistently achieved in both PSA-spiked female serum samples and actual patient serum samples. Moreover, comparison of the results obtained when SRM PSA assays and conventional immunoassays were applied to the same samples showed good correlation in several independent clinical serum sample sets. These results demonstrate that the workflows and SRM assays developed here provide an attractive alternative for reliably measuring candidate biomarkers in human blood, without the need to develop affinity reagents. Furthermore, the simultaneous measurement of multiple biomarkers, including the free and bound forms of PSA, can be performed in a single multiplexed analysis using high-resolution liquid chromatographic separation coupled with SRM-MS. PMID:22846433

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.

BDNF Val66Met in preclinical Alzheimer's disease is associated with short-term changes in episodic memory and hippocampal volume but not serum mBDNF.

Science.gov (United States)

Lim, Yen Ying; Rainey-Smith, Stephanie; Lim, Yoon; Laws, Simon M; Gupta, Veer; Porter, Tenielle; Bourgeat, Pierrick; Ames, David; Fowler, Christopher; Salvado, Olivier; Villemagne, Victor L; Rowe, Christopher C; Masters, Colin L; Zhou, Xin Fu; Martins, Ralph N; Maruff, Paul

2017-11-01

The brain-derived neurotrophic factor (BDNF) Val66Met polymorphism Met allele exacerbates amyloid (Aβ) related decline in episodic memory (EM) and hippocampal volume (HV) over 36-54 months in preclinical Alzheimer's disease (AD). However, the extent to which Aβ+ and BDNF Val66Met is related to circulating markers of BDNF (e.g. serum) is unknown. We aimed to determine the effect of Aβ and the BDNF Val66Met polymorphism on levels of serum mBDNF, EM, and HV at baseline and over 18-months. Non-demented older adults (n = 446) underwent Aβ neuroimaging and BDNF Val66Met genotyping. EM and HV were assessed at baseline and 18 months later. Fasted blood samples were obtained from each participant at baseline and at 18-month follow-up. Aβ PET neuroimaging was used to classify participants as Aβ- or Aβ+. At baseline, Aβ+ adults showed worse EM impairment and lower serum mBDNF levels relative to Aβ- adults. BDNF Val66Met polymorphism did not affect serum mBDNF, EM, or HV at baseline. When considered over 18-months, compared to Aβ- Val homozygotes, Aβ+ Val homozygotes showed significant decline in EM and HV but not serum mBDNF. Similarly, compared to Aβ+ Val homozygotes, Aβ+ Met carriers showed significant decline in EM and HV over 18-months but showed no change in serum mBDNF. While allelic variation in BDNF Val66Met may influence Aβ+ related neurodegeneration and memory loss over the short term, this is not related to serum mBDNF. Longer follow-up intervals may be required to further determine any relationships between serum mBDNF, EM, and HV in preclinical AD.

Chemical speciation of arsenic species in human blood serum by liquid chromatography using a phosphatidylcholine-coated ODS column with detection by ICP-MS

International Nuclear Information System (INIS)

Hasegawa, Takuya; Ishise, Jotaro; Fukumoto, Yasuharu; Matsuura, Hirotaka; Zhu, Yanbei; Umemura, Tomonari; Haraguchi, Hiroki; Yamamoto, Kazuhito; Naoe, Tomoki

2007-01-01

Chemical speciation of arsenic species in human blood serum was performed by high-performance liquid chromatography/inductively coupled plasma mass spectrometry (HPLC/ICP-MS) with direct sample injection, where an octadecylsilyl silica (ODS) column coated with phosphatidylcholine (PC) (hereafter known as 'PC-coated ODS column') was used as the separation column. In arsenic species analysis, a citrate buffer solution (pH 4.0) was used as the mobile phase, in which the following reagents were added: sodium 1-dodecanesulfonate (SDS), tetramethylammonium hydroxide (TMAH), which are ion-pair reagents to separate inorganic and organic arsenic species, and 3-[(3-cholamidopropyl)-dimethylammonio]-1-propane sulfonate (CHAPS), which is a protein-solubilizing agent to prevent adsorption of proteins on the column. As a result of optimization, five representative arsenic species spiked in human blood serum reference material could be separated from each other within 5 min on the PC-coated ODS column by elution with a 5 mM citrate buffer (pH 4.0) containing 5 mM SDS, 5 mM THAH, and 0.2 mM CHAPS. The detection limits obtained by ICP-MS were 3.1, 2.7, 4.5, 2.5, and 2.5 ng of As g -1 for arsenate (iAs V ), arsenite (iAs III ), monomethylarsonic acid (MMA), dimethylarsenic acid (DMA), and arsenobetaine (AB), respectively, when the injection volume was 20 μL. The present separation system was also applied to speciation analysis of arsenic species in human blood serum collected from a leukemia patient after therapeutic treatment with arsenic. (author)

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

Directory of Open Access Journals (Sweden)

Rebecca A. Mease

2017-05-01

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

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

Serum brain-derived neurotrophic factor and interleukin-6 response to high-volume mechanically demanding exercise.

Science.gov (United States)

Verbickas, Vaidas; Kamandulis, Sigitas; Snieckus, Audrius; Venckunas, Tomas; Baranauskiene, Neringa; Brazaitis, Marius; Satkunskiene, Danguole; Unikauskas, Alvydas; Skurvydas, Albertas

2018-01-01

The aim of this study was to follow circulating brain-derived neurotrophic factor (BDNF) and interleukin-6 (IL-6) levels in response to severe muscle-damaging exercise. Young healthy men (N = 10) performed a bout of mechanically demanding stretch-shortening cycle exercise consisting of 200 drop jumps. Voluntary and electrically induced knee extension torque, serum BDNF levels, and IL-6 levels were measured before and for up to 7 days after exercise. Muscle force decreased by up to 40% and did not recover by 24 hours after exercise. Serum BDNF was decreased 1 hour and 24 hours after exercise, whereas IL-6 increased immediately and 1 hour after but recovered to baseline by 24 hours after exercise. IL-6 and 100-Hz stimulation torque were correlated (r = -0.64, P exercise. In response to acute, severe muscle-damaging exercise, serum BDNF levels decrease, whereas IL-6 levels increase and are associated with peripheral fatigue. Muscle Nerve 57: E46-E51, 2018. © 2017 Wiley Periodicals, Inc.

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.

Early prediction of treatment response by serum CRP levels in patients with advanced esophageal cancer who underwent definitive chemoradiotherapy

International Nuclear Information System (INIS)

Yoneda, Masayuki; Fujiwara, Hitoshi; Okamura, Shinichi

2010-01-01

Serum C reactive protein (CRP) has been shown to be associated with the progression of esophageal cancer. The purpose of this study was to examine the relationship between treatment response and serum CRP levels in time course during definitive chemoradiotherapy (CRT) in terms of early prediction of CRT response by serum CRP. The subjects of this study were 36 patients with cT3/cT4 esophageal squamous cell carcinoma who underwent definitive CRT in our hospital. Serum CRP levels during definitive CRT (pretreatment, 1W, 2W and 3W after CRT initiation) were compared between CR and non-CR group. In addition, partition model was constructed to discriminate CR with non-CR and the prediction accuracy was evaluated. The patients were consisted of 28 males and 8 females. At pretreatment diagnosis, tumors were categorized as T3 (n=21) and T4 (n=15). Thirty four patients received FP-based chemotherapy and 2 patients received docetaxel-based chemotherapy. Treatment responses were categorized as CR (n=8), partial response (PR) (n=14), no change (NC) (n=2) and progressive disease (PD) (n=12). Serum CRP levels at the time of 2W after CRT initiation (CRT2W) in CR group were low compared to those in non-CR group (p=0.071). The partition model was constructed based on CRP levels at CRT2W. The prediction accuracies to discriminate CR from non-CR by CRP ≤0.1 were 50%, 82%, and 75% in sensitivity, specificity and accuracy, respectively. Serum CRP is a useful biomarker for an early prediction of CRT response. (author)

Neurofilament light antibodies in serum reflect response to natalizumab treatment in multiple sclerosis.

Science.gov (United States)

Amor, Sandra; van der Star, Baukje J; Bosca, Isabel; Raffel, Joel; Gnanapavan, Sharmilee; Watchorn, Jonathan; Kuhle, Jens; Giovannoni, Gavin; Baker, David; Malaspina, Andrea; Puentes, Fabiola

2014-09-01

Increased levels of antibodies to neurofilament light protein (NF-L) in biological fluids have been found to reflect neuroinflammatory responses and neurodegeneration in multiple sclerosis (MS). To evaluate whether levels of serum antibodies against NF-L correlate with clinical variants and treatment response in MS. The autoantibody reactivity to NF-L protein was tested in serum samples from patients with relapsing-remitting MS (RRMS) (n=22) and secondary progressive MS (SPMS) (n=26). Two other cohorts of RRMS patients under treatment with natalizumab were analysed cross-sectionally (n=16) and longitudinally (n=24). The follow-up samples were taken at 6, 12, 18 and 24 months after treatment, and the NF-L antibody levels were compared against baseline levels. NF-L antibodies were higher in MS clinical groups than healthy controls and in RRMS compared to SPMS patients (ptreatment compared with baseline measurements (p=0.001). Drug efficacy in MS treatment indicates the potential use of monitoring the content of antibodies against the NF-L chain as a predictive biomarker of treatment response in MS. © The Author(s) 2014.

Motif statistics and spike correlations in neuronal networks

International Nuclear Information System (INIS)

Hu, Yu; Shea-Brown, Eric; Trousdale, James; Josić, Krešimir

2013-01-01

Motifs are patterns of subgraphs of complex networks. We studied the impact of such patterns of connectivity on the level of correlated, or synchronized, spiking activity among pairs of cells in a recurrent network of integrate and fire neurons. For a range of network architectures, we find that the pairwise correlation coefficients, averaged across the network, can be closely approximated using only three statistics of network connectivity. These are the overall network connection probability and the frequencies of two second order motifs: diverging motifs, in which one cell provides input to two others, and chain motifs, in which two cells are connected via a third intermediary cell. Specifically, the prevalence of diverging and chain motifs tends to increase correlation. Our method is based on linear response theory, which enables us to express spiking statistics using linear algebra, and a resumming technique, which extrapolates from second order motifs to predict the overall effect of coupling on network correlation. Our motif-based results seek to isolate the effect of network architecture perturbatively from a known network state. (paper)

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...

Phytotoxicity of trace metals in spiked and field-contaminated soils: Linking soil-extractable metals with toxicity.

Science.gov (United States)

Hamels, Fanny; Malevé, Jasmina; Sonnet, Philippe; Kleja, Dan Berggren; Smolders, Erik

2014-11-01

Soil tests have been widely developed to predict trace metal uptake by plants. The prediction of metal toxicity, however, has rarely been tested. The present study was set up to compare 8 established soil tests for diagnosing phytotoxicity in contaminated soils. Nine soils contaminated with Zn or Cu by metal mining, smelting, or processing were collected. Uncontaminated reference soils with similar soil properties were sampled, and series of increasing contamination were created by mixing each with the corresponding soil. In addition, each reference soil was spiked with either ZnCl2 or CuCl2 at several concentrations. Total metal toxicity to barley seedling growth in the field-contaminated soils was up to 30 times lower than that in corresponding spiked soils. Total metal (aqua regia-soluble) toxicity thresholds of 50% effective concentrations (EC50) varied by factors up to 260 (Zn) or 6 (Cu) among soils. For Zn, variations in EC50 thresholds decreased as aqua regia > 0.43 M HNO3  > 0.05 M ethylenediamine tetraacetic acid (EDTA) > 1 M NH4 NO3  > cobaltihexamine > diffusive gradients in thin films (DGT) > 0.001 M CaCl2 , suggesting that the last extraction is the most robust phytotoxicity index for Zn. The EDTA extraction was the most robust for Cu-contaminated soils. The isotopically exchangeable fraction of the total soil metal in the field-contaminated soils markedly explained the lower toxicity compared with spiked soils. The isotope exchange method can be used to translate soil metal limits derived from soils spiked with metal salts to site-specific soil metal limits. © 2014 SETAC.

A reanalysis of "Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons".

Science.gov (United States)

Engelken, Rainer; Farkhooi, Farzad; Hansel, David; van Vreeswijk, Carl; Wolf, Fred

2016-01-01

Neuronal activity in the central nervous system varies strongly in time and across neuronal populations. It is a longstanding proposal that such fluctuations generically arise from chaotic network dynamics. Various theoretical studies predict that the rich dynamics of rate models operating in the chaotic regime can subserve circuit computation and learning. Neurons in the brain, however, communicate via spikes and it is a theoretical challenge to obtain similar rate fluctuations in networks of spiking neuron models. A recent study investigated spiking balanced networks of leaky integrate and fire (LIF) neurons and compared their dynamics to a matched rate network with identical topology, where single unit input-output functions were chosen from isolated LIF neurons receiving Gaussian white noise input. A mathematical analogy between the chaotic instability in networks of rate units and the spiking network dynamics was proposed. Here we revisit the behavior of the spiking LIF networks and these matched rate networks. We find expected hallmarks of a chaotic instability in the rate network: For supercritical coupling strength near the transition point, the autocorrelation time diverges. For subcritical coupling strengths, we observe critical slowing down in response to small external perturbations. In the spiking network, we found in contrast that the timescale of the autocorrelations is insensitive to the coupling strength and that rate deviations resulting from small input perturbations rapidly decay. The decay speed even accelerates for increasing coupling strength. In conclusion, our reanalysis demonstrates fundamental differences between the behavior of pulse-coupled spiking LIF networks and rate networks with matched topology and input-output function. In particular there is no indication of a corresponding chaotic instability in the spiking network.

Orthobunyavirus ultrastructure and the curious tripodal glycoprotein spike.

Directory of Open Access Journals (Sweden)

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.

Transcranial direct current stimulation in refractory continuous spikes and waves during slow sleep: a controlled study

DEFF Research Database (Denmark)

Varga, Edina T; Terney, Daniella; Atkins, Mary D

2011-01-01

Cathodal transcranial direct current stimulation (tDCS) decreases cortical excitability. The purpose of the study was to investigate whether cathodal tDCS could interrupt the continuous epileptiform activity. Five patients with focal, refractory continuous spikes and waves during slow sleep were...... recruited. Cathodal tDCS and sham stimulation were applied to the epileptic focus, before sleep (1 mA; 20 min). Cathodal tDCS did not reduce the spike-index in any of the patients....

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.

Immunoassay for serum amyloid A using a glassy carbon electrode modified with carboxy-polypyrrole, multiwalled carbon nanotubes, ionic liquid and chitosan

International Nuclear Information System (INIS)

Xia, Chunyong; Li, Yuan; Yuan, Guolin; Guo, Yanlei; Yu, Chao

2015-01-01

We report on a highly sensitive electrochemical immunoassay for the serum inflammation marker amyloid A (SAA). It is making use of a glassy carbon electrode that was modified with carboxy-endcapped polypyrrole (PPy-α-COOH), multiwalled carbon nanotubes (MWCNTs), ionic liquid and chitosan acting as the support platform. The nanocomposite increases the sensitivity and stability of the assay. Antibody against SAA was immobilized on a monolayer surface consisting of PPy-α-COOH. The electrode material was characterized by scanning electron microscopy, transmission electron microscopy, Fourier transform infrared spectra, cyclic voltammetry, electrochemical impedance spectroscopy and differential pulse voltammetry. The calibration plot for this assay, when operated at 0.16 V (vs. SCE) and applied to spiked serum samples, is linear in the 0.001 to 900 ng mL −1 SAA concentration range, and the detection limit is as low as 0.3 pg mL −1 (at an S/N ratio of 3). The electrode is stable and highly sensitive. The detection scheme is likely to be applicable to numerous other kinds of immunoassays. (author)

Inositol polyphosphate multikinase is a coactivator for serum response factor-dependent induction of immediate early genes

Science.gov (United States)

Kim, Eunha; Tyagi, Richa; Lee, Joo-Young; Park, Jina; Kim, Young-ran; Beon, Jiyoon; Chen, Po Yu; Cha, Jiyoung Y.; Snyder, Solomon H.; Kim, Seyun

2013-01-01

Inositol polyphosphate multikinase (IPMK) is a notably pleiotropic protein. It displays both inositol phosphate kinase and phosphatidylinositol kinase catalytic activities. Noncatalytically, IPMK stabilizes the mammalian target of rapamycin complex 1 and acts as a transcriptional coactivator for CREB-binding protein/E1A binding protein p300 and tumor suppressor protein p53. Serum response factor (SRF) is a major transcription factor for a wide range of immediate early genes. We report that IPMK, in a noncatalytic role, is a transcriptional coactivator for SRF mediating the transcription of immediate early genes. Stimulation by serum of many immediate early genes is greatly reduced by IPMK deletion. IPMK stimulates expression of these genes, an influence also displayed by catalytically inactive IPMK. IPMK acts by binding directly to SRF and thereby enhancing interactions of SRF with the serum response element of diverse genes. PMID:24248338

Production and characterization of monoclonal antibodies (mAbs) against human serum albumin (HSA) for the development of an immunoaffinity system with oriented anti-HSA mAbs as immobilized ligand.

Science.gov (United States)

Rajak, Poonam; Vijayalakshmi, M A; Jayaprakash, N S

2013-05-05

Proteins present in human serum are of immense importance in the field of biomarker discovery. But, the presence of high-abundant proteins like albumin makes the analysis more challenging because of masking effect on low-abundant proteins. Therefore, removal of albumin using highly specific monoclonal antibodies (mAbs) can potentiate the discovery of low-abundant proteins. In the present study, mAbs against human serum albumin (HSA) were developed and integrated in to an immunoaffinity based system for specific removal of albumin from the serum. Hybridomas were obtained by fusion of Sp2/0 mouse myeloma cells with spleen cells from the mouse immunized with HSA. Five clones (AHSA1-5) producing mAbs specific to HSA were established and characterized by enzyme linked immunosorbent assay (ELISA) and immunoblotting for specificity, sensitivity and affinity in terms of antigen binding. The mAbs were able to bind to both native albumin as well as its glycated isoform. Reactivity of mAbs with different mammalian sera was tested. The affinity constant of the mAbs ranged from 10(8) to 10(9)M(-1). An approach based on oriented immobilization was followed to immobilize purified anti-HSA mAbs on hydrazine activated agarose gel and the dynamic binding capacity of the column was determined. Copyright © 2013 Elsevier B.V. All rights reserved.

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.

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.

Separation of hemagglutination-inhibiting immunoglobulin M antibody to rubella virus in human serum by high-performance liquid chromatography.

OpenAIRE

Kobayashi, N; Suzuki, M; Nakagawa, T; Matumoto, M

1986-01-01

High-performance liquid chromatography was successfully used to separate hemagglutination-inhibiting immunoglobulin M (IgM) rubella virus antibody from IgG rubella virus antibody in human serum. The fractionation by high-performance liquid chromatography was as effective as sucrose density gradient centrifugation in separating IgM antibody from IgG antibody.

Artesunate Reduces Serum Lipopolysaccharide in Cecal Ligation/Puncture Mice via Enhanced LPS Internalization by Macrophages through Increased mRNA Expression of Scavenger Receptors

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Bin Li

2014-01-01

Full Text Available Innate immunity is the first line of defense in human beings against pathogen infection; monocytes/macrophages are the primary cells of the innate immune system. Recently, macrophages/monocytes have been discovered to participate in LPS clearance, and the clearance efficiency determines the magnitude of the inflammatory response and subsequent organ injury. Previously, we reported that artesunate (AS protected sepsis mice against heat-killed E. coli challenge. Herein, we further confirmed that AS protected cecal ligation/puncture (CLP sepsis mice. Its protection on sepsis mice was related to not only reduction of pro-inflammatory cytokines and serum LPS levels but also improvement of liver function. Based on the fact that AS did not directly bind and neutralize LPS, we hypothesized that the reduction of serum LPS level might be related to enhancement of LPS internalization and subsequent detoxification. Our results showed that AS increased FITC-LPS internalization by peritoneal macrophage and liver Kupffer cell, but enhancement of LPS internalization by AS was not related to the clathrin-dependent pathway. However, AS induced mRNA expression of important scavenger receptors (SRs; SR-A and MARCO mRNA expression was upregulated, suggesting that AS enhancement of LPS internalization and inhibition of pro-inflammatory cytokines was related to changes in mRNA expression of SRs.

Parametric models to relate spike train and LFP dynamics with neural information processing.

Science.gov (United States)

Banerjee, Arpan; Dean, Heather L; Pesaran, Bijan

2012-01-01

Spike trains and local field potentials (LFPs) resulting from extracellular current flows provide a substrate for neural information processing. Understanding the neural code from simultaneous spike-field recordings and subsequent decoding of information processing events will have widespread applications. One way to demonstrate an understanding of the neural code, with particular advantages for the development of applications, is to formulate a parametric statistical model of neural activity and its covariates. Here, we propose a set of parametric spike-field models (unified models) that can be used with existing decoding algorithms to reveal the timing of task or stimulus specific processing. Our proposed unified modeling framework captures the effects of two important features of information processing: time-varying stimulus-driven inputs and ongoing background activity that occurs even in the absence of environmental inputs. We have applied this framework for decoding neural latencies in simulated and experimentally recorded spike-field sessions obtained from the lateral intraparietal area (LIP) of awake, behaving monkeys performing cued look-and-reach movements to spatial targets. Using both simulated and experimental data, we find that estimates of trial-by-trial parameters are not significantly affected by the presence of ongoing background activity. However, including background activity in the unified model improves goodness of fit for predicting individual spiking events. Uncovering the relationship between the model parameters and the timing of movements offers new ways to test hypotheses about the relationship between neural activity and behavior. We obtained significant spike-field onset time correlations from single trials using a previously published data set where significantly strong correlation was only obtained through trial averaging. We also found that unified models extracted a stronger relationship between neural response latency and trial

Protein and Carbohydrate Accumulation in Normal and High-Lysine Barley in Spike Culture

DEFF Research Database (Denmark)

Mather, D.E; Giese, Nanna Henriette

1984-01-01

Spikes of barley cv. Bomi and high-lysine mutants Riso 1508 and Riso 56 were cultured on liquid media at varying N and sucrose levels. Bomi accumulated N in response to increasing N levels in the medium and a higher level was reached than in spikes of intact plants. The distribution of N in salt......-soluble, hordein, and non-protein N fractions appeared to be normal. Endosperm dry weight and starch were lower than in intact plants and declined at higher N levels. A linear relationship was observed between starch content and the concentration of sucrose in the endosperm water. Uptake of culture medium...

Impact of sub and supra-threshold adaptation currents in networks of spiking neurons.

Science.gov (United States)

Colliaux, David; Yger, Pierre; Kaneko, Kunihiko

2015-12-01

Neuronal adaptation is the intrinsic capacity of the brain to change, by various mechanisms, its dynamical responses as a function of the context. Such a phenomena, widely observed in vivo and in vitro, is known to be crucial in homeostatic regulation of the activity and gain control. The effects of adaptation have already been studied at the single-cell level, resulting from either voltage or calcium gated channels both activated by the spiking activity and modulating the dynamical responses of the neurons. In this study, by disentangling those effects into a linear (sub-threshold) and a non-linear (supra-threshold) part, we focus on the the functional role of those two distinct components of adaptation onto the neuronal activity at various scales, starting from single-cell responses up to recurrent networks dynamics, and under stationary or non-stationary stimulations. The effects of slow currents on collective dynamics, like modulation of population oscillation and reliability of spike patterns, is quantified for various types of adaptation in sparse recurrent networks.

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.

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.

Stimulus Sensitivity of a Spiking Neural Network Model

Science.gov (United States)

Chevallier, Julien

2018-02-01

Some recent papers relate the criticality of complex systems to their maximal capacity of information processing. In the present paper, we consider high dimensional point processes, known as age-dependent Hawkes processes, which have been used to model spiking neural networks. Using mean-field approximation, the response of the network to a stimulus is computed and we provide a notion of stimulus sensitivity. It appears that the maximal sensitivity is achieved in the sub-critical regime, yet almost critical for a range of biologically relevant parameters.

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.

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.

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.)

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.

A review on cluster estimation methods and their application to neural spike data.

Science.gov (United States)

Zhang, James; Nguyen, Thanh; Cogill, Steven; Bhatti, Asim; Luo, Lingkun; Yang, Samuel; Nahavandi, Saeid

2018-06-01

The extracellular action potentials recorded on an electrode result from the collective simultaneous electrophysiological activity of an unknown number of neurons. Identifying and assigning these action potentials to their firing neurons-'spike sorting'-is an indispensable step in studying the function and the response of an individual or ensemble of neurons to certain stimuli. Given the task of neural spike sorting, the determination of the number of clusters (neurons) is arguably the most difficult and challenging issue, due to the existence of background noise and the overlap and interactions among neurons in neighbouring regions. It is not surprising that some researchers still rely on visual inspection by experts to estimate the number of clusters in neural spike sorting. Manual inspection, however, is not suitable to processing the vast, ever-growing amount of neural data. To address this pressing need, in this paper, thirty-three clustering validity indices have been comprehensively reviewed and implemented to determine the number of clusters in neural datasets. To gauge the suitability of the indices to neural spike data, and inform the selection process, we then calculated the indices by applying k-means clustering to twenty widely used synthetic neural datasets and one empirical dataset, and compared the performance of these indices against pre-existing ground truth labels. The results showed that the top five validity indices work consistently well across variations in noise level, both for the synthetic datasets and the real dataset. Using these top performing indices provides strong support for the determination of the number of neural clusters, which is essential in the spike sorting process.

A compound memristive synapse model for statistical learning through STDP in spiking neural networks

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Johannes eBill

2014-12-01

Full Text Available Memristors have recently emerged as promising circuit elements to mimic the function of biological synapses in neuromorphic computing. The fabrication of reliable nanoscale memristive synapses, that feature continuous conductance changes based on the timing of pre- and postsynaptic spikes, has however turned out to be challenging. In this article, we propose an alternative approach, the compound memristive synapse, that circumvents this problem by the use of memristors with binary memristive states. A compound memristive synapse employs multiple bistable memristors in parallel to jointly form one synapse, thereby providing a spectrum of synaptic efficacies. We investigate the computational implications of synaptic plasticity in the compound synapse by integrating the recently observed phenomenon of stochastic filament formation into an abstract model of stochastic switching. Using this abstract model, we first show how standard pulsing schemes give rise to spike-timing dependent plasticity (STDP with a stabilizing weight dependence in compound synapses. In a next step, we study unsupervised learning with compound synapses in networks of spiking neurons organized in a winner-take-all architecture. Our theoretical analysis reveals that compound-synapse STDP implements generalized Expectation-Maximization in the spiking network. Specifically, the emergent synapse configuration represents the most salient features of the input distribution in a Mixture-of-Gaussians generative model. Furthermore, the network’s spike response to spiking input streams approximates a well-defined Bayesian posterior distribution. We show in computer simulations how such networks learn to represent high-dimensional distributions over images of handwritten digits with high fidelity even in presence of substantial device variations and under severe noise conditions. Therefore, the compound memristive synapse may provide a synaptic design principle for future neuromorphic

A compound memristive synapse model for statistical learning through STDP in spiking neural networks.

Science.gov (United States)

Bill, Johannes; Legenstein, Robert

2014-01-01

Memristors have recently emerged as promising circuit elements to mimic the function of biological synapses in neuromorphic computing. The fabrication of reliable nanoscale memristive synapses, that feature continuous conductance changes based on the timing of pre- and postsynaptic spikes, has however turned out to be challenging. In this article, we propose an alternative approach, the compound memristive synapse, that circumvents this problem by the use of memristors with binary memristive states. A compound memristive synapse employs multiple bistable memristors in parallel to jointly form one synapse, thereby providing a spectrum of synaptic efficacies. We investigate the computational implications of synaptic plasticity in the compound synapse by integrating the recently observed phenomenon of stochastic filament formation into an abstract model of stochastic switching. Using this abstract model, we first show how standard pulsing schemes give rise to spike-timing dependent plasticity (STDP) with a stabilizing weight dependence in compound synapses. In a next step, we study unsupervised learning with compound synapses in networks of spiking neurons organized in a winner-take-all architecture. Our theoretical analysis reveals that compound-synapse STDP implements generalized Expectation-Maximization in the spiking network. Specifically, the emergent synapse configuration represents the most salient features of the input distribution in a Mixture-of-Gaussians generative model. Furthermore, the network's spike response to spiking input streams approximates a well-defined Bayesian posterior distribution. We show in computer simulations how such networks learn to represent high-dimensional distributions over images of handwritten digits with high fidelity even in presence of substantial device variations and under severe noise conditions. Therefore, the compound memristive synapse may provide a synaptic design principle for future neuromorphic architectures.

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.

Sparse Spike Inversion Predicts Lateral Variation of Porosity La méthode Sparse Spike Inversion de prévision des variations latérales de porosité

OpenAIRE

Alam A.; Ardali A.

2006-01-01

The sparse spike inversion method estimates from deconvolved seismic data that reflectivity which has the minimum sum of absolute values subject to two constraints. First, the reflectivity spectrum matches the seismic data spectrum over a specified bandwidth. Second, the impedance function resulting from integration of the reflectivity passes through a set of impedance windows, specified at interpreted horizon times. We use an interactive workstation to identify the phase of the residual wave...

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.

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.

Diagnosis of Protein Losing Enteropathy in connective Tissue Diseases with 99mTc-human Serum Albumin(Hsa)

International Nuclear Information System (INIS)

Won, Kyoung Sook; Oh, Yeong Seok; Bang, Shin Ho; Park, Won

1993-01-01

Anterior abdominal scintigraphy after intravenous injection of 99m Tc-human serum albumin ( 99m Tc-HSA 20 mCi) was done in 16 patients with connective tissue diseases and 15 healthy control patients. Patients with proteinuria or hepatopathy were excluded. 1) 7(44%) patients among 16 connective tissue disease patients without the apparent evidence of external protein loss showed abnormal intestinal accumulation of albumin. 6 patients with positive albumin scintigraphy showed hypoalbuminaemia. 2) There was no false positive scintigraphic finding in control group. 3) The serum albumin level in connective tissue disease patients (3.1 ± 0.6 g/dl, n=16) was lower than control patients(3.9 ± 0.3 g/dl, n=15) (p 99m Tc-HSA scan(2.8 ± 0.6 g/dl, n=7) than the connective tissue disease patients with negative scan(3.3 ± 0.3 g/dl, n=9) (p 99m Tc-HSA scan also must be validated by more extended study and comparison with the quantitative study such as stool α -1 antitrypsin measurement. There must be a reevaluation of PLE in various diseases especially in connective tissue diseases with easy, fast, economical, and noninvasive method.

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

Relationship between serum TSH and the responsiveness of toxic solitary autonomous thyroid nodules to radioiodine therapy

DEFF Research Database (Denmark)

Pedersen-Bjergaard, U; Kirkegaard, B C

1998-01-01

hypothyroidism both had detectable serum TSH at the time of 131I treatment. No other clinical parameter seemed to influence the outcome. CONCLUSION: There is no clinically significant effect of circulating TSH on the response of toxic solitary autonomous thyroid nodules to 131I therapy. However, keeping...... the patients subclinically hyperthyroid when receiving 131I treatment may possibly result in a reduced frequency of hypothyroidism.......) were euthyroid, three (8%) had responded insufficiently and required further antithyroid therapy, and two (5%) had developed hypothyroidism. No significant difference in the response pattern between patients with suppressed or detectable serum TSH could be demonstrated. The two patients who developed...

Spike Timing Matters in Novel Neuronal Code Involved in Vibrotactile Frequency Perception.

Science.gov (United States)

Birznieks, Ingvars; Vickery, Richard M

2017-05-22

Skin vibrations sensed by tactile receptors contribute significantly to the perception of object properties during tactile exploration [1-4] and to sensorimotor control during object manipulation [5]. Sustained low-frequency skin vibration (perception of frequency is still unknown. Measures based on mean spike rates of neurons in the primary somatosensory cortex are sufficient to explain performance in some frequency discrimination tasks [7-11]; however, there is emerging evidence that stimuli can be distinguished based also on temporal features of neural activity [12, 13]. Our study's advance is to demonstrate that temporal features are fundamental for vibrotactile frequency perception. Pulsatile mechanical stimuli were used to elicit specified temporal spike train patterns in tactile afferents, and subsequently psychophysical methods were employed to characterize human frequency perception. Remarkably, the most salient temporal feature determining vibrotactile frequency was not the underlying periodicity but, rather, the duration of the silent gap between successive bursts of neural activity. This burst gap code for frequency represents a previously unknown form of neural coding in the tactile sensory system, which parallels auditory pitch perception mechanisms based on purely temporal information where longer inter-pulse intervals receive higher perceptual weights than short intervals [14]. Our study also demonstrates that human perception of stimuli can be determined exclusively by temporal features of spike trains independent of the mean spike rate and without contribution from population response factors. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

Dendritic spikes amplify the synaptic signal to enhance detection of motion in a simulation of the direction-selective ganglion cell.

Directory of Open Access Journals (Sweden)

Michael J Schachter

2010-08-01

Full Text Available The On-Off direction-selective ganglion cell (DSGC in mammalian retinas responds most strongly to a stimulus moving in a specific direction. The DSGC initiates spikes in its dendritic tree, which are thought to propagate to the soma with high probability. Both dendritic and somatic spikes in the DSGC display strong directional tuning, whereas somatic PSPs (postsynaptic potentials are only weakly directional, indicating that spike generation includes marked enhancement of the directional signal. We used a realistic computational model based on anatomical and physiological measurements to determine the source of the enhancement. Our results indicate that the DSGC dendritic tree is partitioned into separate electrotonic regions, each summing its local excitatory and inhibitory synaptic inputs to initiate spikes. Within each local region the local spike threshold nonlinearly amplifies the preferred response over the null response on the basis of PSP amplitude. Using inhibitory conductances previously measured in DSGCs, the simulation results showed that inhibition is only sufficient to prevent spike initiation and cannot affect spike propagation. Therefore, inhibition will only act locally within the dendritic arbor. We identified the role of three mechanisms that generate directional selectivity (DS in the local dendritic regions. First, a mechanism for DS intrinsic to the dendritic structure of the DSGC enhances DS on the null side of the cell's dendritic tree and weakens it on the preferred side. Second, spatially offset postsynaptic inhibition generates robust DS in the isolated dendritic tips but weak DS near the soma. Third, presynaptic DS is apparently necessary because it is more robust across the dendritic tree. The pre- and postsynaptic mechanisms together can overcome the local intrinsic DS. These local dendritic mechanisms can perform independent nonlinear computations to make a decision, and there could be analogous mechanisms within

Dendritic spikes amplify the synaptic signal to enhance detection of motion in a simulation of the direction-selective ganglion cell.

Science.gov (United States)

Schachter, Michael J; Oesch, Nicholas; Smith, Robert G; Taylor, W Rowland

2010-08-19

The On-Off direction-selective ganglion cell (DSGC) in mammalian retinas responds most strongly to a stimulus moving in a specific direction. The DSGC initiates spikes in its dendritic tree, which are thought to propagate to the soma with high probability. Both dendritic and somatic spikes in the DSGC display strong directional tuning, whereas somatic PSPs (postsynaptic potentials) are only weakly directional, indicating that spike generation includes marked enhancement of the directional signal. We used a realistic computational model based on anatomical and physiological measurements to determine the source of the enhancement. Our results indicate that the DSGC dendritic tree is partitioned into separate electrotonic regions, each summing its local excitatory and inhibitory synaptic inputs to initiate spikes. Within each local region the local spike threshold nonlinearly amplifies the preferred response over the null response on the basis of PSP amplitude. Using inhibitory conductances previously measured in DSGCs, the simulation results showed that inhibition is only sufficient to prevent spike initiation and cannot affect spike propagation. Therefore, inhibition will only act locally within the dendritic arbor. We identified the role of three mechanisms that generate directional selectivity (DS) in the local dendritic regions. First, a mechanism for DS intrinsic to the dendritic structure of the DSGC enhances DS on the null side of the cell's dendritic tree and weakens it on the preferred side. Second, spatially offset postsynaptic inhibition generates robust DS in the isolated dendritic tips but weak DS near the soma. Third, presynaptic DS is apparently necessary because it is more robust across the dendritic tree. The pre- and postsynaptic mechanisms together can overcome the local intrinsic DS. These local dendritic mechanisms can perform independent nonlinear computations to make a decision, and there could be analogous mechanisms within cortical circuitry.

Serum/plasma methylmercury determination by isotope dilution gas chromatography-inductively coupled plasma mass spectrometry

Energy Technology Data Exchange (ETDEWEB)

Baxter, Douglas C., E-mail: douglas.baxter@alsglobal.com [ALS Scandinavia AB, Aurorum 10, 977 75 Lulea (Sweden); Faarinen, Mikko [ALS Scandinavia AB, Aurorum 10, 977 75 Lulea (Sweden); Osterlund, Helene; Rodushkin, Ilia [ALS Scandinavia AB, Aurorum 10, 977 75 Lulea (Sweden); Division of Geosciences, Lulea University of Technology, 977 87 Lulea (Sweden); Christensen, Morten [ALS Scandinavia AB, Maskinvaegen 2, 183 53 Taeby (Sweden)

2011-09-09

Highlights: {center_dot} We determine methylmercury in serum and plasma using isotope dilution calibration. {center_dot} Separation by gas chromatography and detection by inductively coupled plasma mass spectrometry. {center_dot} Data for 50 specimens provides first reference range for methylmercury in serum. {center_dot} Serum samples shown to be stable for 11 months in refrigerator. - Abstract: A method for the determination of methylmercury in plasma and serum samples was developed. The method uses isotope dilution with {sup 198}Hg-labeled methylmercury, extraction into dichloromethane, back-extraction into water, aqueous-phase ethylation, purge and trap collection, thermal desorption, separation by gas chromatography, and mercury isotope specific detection by inductively coupled plasma mass spectrometry. By spiking 2 mL sample with 1.2 ng tracer, measurements in a concentration interval of (0.007-2.9) {mu}g L{sup -1} could be performed with uncertainty amplification factors <2. A limit of quantification of 0.03 {mu}g L{sup -1} was estimated at 10 times the standard deviation of concentrations measured in preparation blanks. Within- and between-run relative standard deviations were <10% at added concentration levels of 0.14 {mu}g L{sup -1}, 0.35 {mu}g L{sup -1} and 2.8 {mu}g L{sup -1}, with recoveries in the range 82-110%. Application of the method to 50 plasma/serum samples yielded a median (mean; range) concentration of methylmercury of 0.081 (0.091; <0.03-0.19) {mu}g L{sup -1}. This is the first time methylmercury has been directly measured in this kind of specimen, and is therefore the first estimate of a reference range.

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)

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.

Bistability induces episodic spike communication by inhibitory neurons in neuronal networks.

Science.gov (United States)

Kazantsev, V B; Asatryan, S Yu

2011-09-01

Bistability is one of the important features of nonlinear dynamical systems. In neurodynamics, bistability has been found in basic Hodgkin-Huxley equations describing the cell membrane dynamics. When the neuron is clamped near its threshold, the stable rest potential may coexist with the stable limit cycle describing periodic spiking. However, this effect is often neglected in network computations where the neurons are typically reduced to threshold firing units (e.g., integrate-and-fire models). We found that the bistability may induce spike communication by inhibitory coupled neurons in the spiking network. The communication is realized in the form of episodic discharges with synchronous (correlated) spikes during the episodes. A spiking phase map is constructed to describe the synchronization and to estimate basic spike phase locking modes.

A note on the electrolytic preparation of sup(99m)Tc human serum albumin

International Nuclear Information System (INIS)

Ligny, C.L. de; Dekker, B.G.

1978-01-01

A note to the simple electrolytic preparations of Tc-99m human serum albumin using tin electrodes, elaborated by Narasimhan and Mani, is described. Narasimhan and Mani's procedure yields mainly hydrolysed reduced Tc. Gil et al described a modification of Narasimhan and Mani's procedure wherein about 60% Tc-HSA chelate can be obtained. Purity analysis was performed by paper chromatography with 85% methanol as eluent. (T.I.)

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

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

A review on cluster estimation methods and their application to neural spike data

Science.gov (United States)

Zhang, James; Nguyen, Thanh; Cogill, Steven; Bhatti, Asim; Luo, Lingkun; Yang, Samuel; Nahavandi, Saeid

2018-06-01

The extracellular action potentials recorded on an electrode result from the collective simultaneous electrophysiological activity of an unknown number of neurons. Identifying and assigning these action potentials to their firing neurons—‘spike sorting’—is an indispensable step in studying the function and the response of an individual or ensemble of neurons to certain stimuli. Given the task of neural spike sorting, the determination of the number of clusters (neurons) is arguably the most difficult and challenging issue, due to the existence of background noise and the overlap and interactions among neurons in neighbouring regions. It is not surprising that some researchers still rely on visual inspection by experts to estimate the number of clusters in neural spike sorting. Manual inspection, however, is not suitable to processing the vast, ever-growing amount of neural data. To address this pressing need, in this paper, thirty-three clustering validity indices have been comprehensively reviewed and implemented to determine the number of clusters in neural datasets. To gauge the suitability of the indices to neural spike data, and inform the selection process, we then calculated the indices by applying k-means clustering to twenty widely used synthetic neural datasets and one empirical dataset, and compared the performance of these indices against pre-existing ground truth labels. The results showed that the top five validity indices work consistently well across variations in noise level, both for the synthetic datasets and the real dataset. Using these top performing indices provides strong support for the determination of the number of neural clusters, which is essential in the spike sorting process.

Leptin receptor (Ob-R) mRNA expression and serum leptin concentration in patients with colorectal and metastatic colorectal cancer

Energy Technology Data Exchange (ETDEWEB)

Erkasap, N.; Ozkurt, M. [Department of Physiology, Osmangazi University Medical Faculty, Meselik, Eskisehir (Turkey); Erkasap, S.; Yasar, F. [Department of General Surgery, Osmangazi University Medical Faculty, Meselik, Eskisehir (Turkey); Uzuner, K. [Department of Physiology, Osmangazi University Medical Faculty, Meselik, Eskisehir (Turkey); Ihtiyar, E. [Department of General Surgery, Osmangazi University Medical Faculty, Meselik, Eskisehir (Turkey); Uslu, S.; Kara, M. [Department of Biochemistry, Osmangazi University Medical Faculty, Meselik, Eskisehir (Turkey); Bolluk, O. [Department of Biostatistics, Osmangazi University Medical Faculty, Meselik, Eskisehir (Turkey)

2013-03-19

The objective of the present study was to investigate the effect of leptin on the progression of colorectal carcinoma to metastatic disease by analyzing the serum leptin concentration and Ob-R gene expression in colon cancer tissues. Tissue samples were obtained from 31 patients who underwent surgical resection for colon (18 cases) and metastatic colon (13 cases) cancer. Serum leptin concentration was determined by an enzyme-linked immunosorbent assay (ELISA) and Ob-R mRNA expression by real-time polymerase chain reaction (RT-PCR) for both groups. ELISA data were analyzed by the Student t-test and RT-PCR data were analyzed by the Mann-Whitney U-test. RT-PCR results demonstrated that mRNA expression of Ob-R in human metastatic colorectal cancer was higher than in local colorectal cancer tissues. On the other hand, mean serum leptin concentration was significantly higher in local colorectal cancer patients compared to patients with metastatic colorectal cancer. The results of the present study suggest a role for leptin in the progression of colon cancer to metastatic disease without weight loss. In other words, significantly increased Ob-R mRNA expression and decreased serum leptin concentration in patients with metastatic colon cancer indicate that sensitization to leptin activity may be a major indicator of metastasis to the colon tissue and the determination of leptin concentration and leptin gene expression may be used to aid the diagnosis.

Leptin receptor (Ob-R) mRNA expression and serum leptin concentration in patients with colorectal and metastatic colorectal cancer

International Nuclear Information System (INIS)

Erkasap, N.; Ozkurt, M.; Erkasap, S.; Yasar, F.; Uzuner, K.; Ihtiyar, E.; Uslu, S.; Kara, M.; Bolluk, O.

2013-01-01

The objective of the present study was to investigate the effect of leptin on the progression of colorectal carcinoma to metastatic disease by analyzing the serum leptin concentration and Ob-R gene expression in colon cancer tissues. Tissue samples were obtained from 31 patients who underwent surgical resection for colon (18 cases) and metastatic colon (13 cases) cancer. Serum leptin concentration was determined by an enzyme-linked immunosorbent assay (ELISA) and Ob-R mRNA expression by real-time polymerase chain reaction (RT-PCR) for both groups. ELISA data were analyzed by the Student t-test and RT-PCR data were analyzed by the Mann-Whitney U-test. RT-PCR results demonstrated that mRNA expression of Ob-R in human metastatic colorectal cancer was higher than in local colorectal cancer tissues. On the other hand, mean serum leptin concentration was significantly higher in local colorectal cancer patients compared to patients with metastatic colorectal cancer. The results of the present study suggest a role for leptin in the progression of colon cancer to metastatic disease without weight loss. In other words, significantly increased Ob-R mRNA expression and decreased serum leptin concentration in patients with metastatic colon cancer indicate that sensitization to leptin activity may be a major indicator of metastasis to the colon tissue and the determination of leptin concentration and leptin gene expression may be used to aid the diagnosis

Leptin receptor (Ob-R mRNA expression and serum leptin concentration in patients with colorectal and metastatic colorectal cancer

Directory of Open Access Journals (Sweden)

N. Erkasap

Full Text Available The objective of the present study was to investigate the effect of leptin on the progression of colorectal carcinoma to metastatic disease by analyzing the serum leptin concentration and Ob-R gene expression in colon cancer tissues. Tissue samples were obtained from 31 patients who underwent surgical resection for colon (18 cases and metastatic colon (13 cases cancer. Serum leptin concentration was determined by an enzyme-linked immunosorbent assay (ELISA and Ob-R mRNA expression by real-time polymerase chain reaction (RT-PCR for both groups. ELISA data were analyzed by the Student t-test and RT-PCR data were analyzed by the Mann-Whitney U-test. RT-PCR results demonstrated that mRNA expression of Ob-R in human metastatic colorectal cancer was higher than in local colorectal cancer tissues. On the other hand, mean serum leptin concentration was significantly higher in local colorectal cancer patients compared to patients with metastatic colorectal cancer. The results of the present study suggest a role for leptin in the progression of colon cancer to metastatic disease without weight loss. In other words, significantly increased Ob-R mRNA expression and decreased serum leptin concentration in patients with metastatic colon cancer indicate that sensitization to leptin activity may be a major indicator of metastasis to the colon tissue and the determination of leptin concentration and leptin gene expression may be used to aid the diagnosis.

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...

Radioimmunoassay of cholylglycine in serum

International Nuclear Information System (INIS)

Wakushima, Tadashi; Yamanishi, Yasuhito; Hirayama, Chisato

1979-01-01

Serum levels of cholylglycines (CG) were determined by radioimmunoassay and that of total bile acids (TBA) by enzymatic method. In normal subjects, serum levels of CG, TBA and CG/TBA ratio were 0.6 +- 0.4 μM, 7 +- 2 μM, and 0.08 +- 0.06, respectively. They were increased markedly in acute hepatitis and moderately in chronic hepatitis and cirrhosis. Thus, measurement of serum CG as compared with serum TBA appears to be a sensitive liver test. (author)

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

Evaluation of serologic and antigenic relationships between middle eastern respiratory syndrome coronavirus and other coronaviruses to develop vaccine platforms for the rapid response to emerging coronaviruses.

Science.gov (United States)

Agnihothram, Sudhakar; Gopal, Robin; Yount, Boyd L; Donaldson, Eric F; Menachery, Vineet D; Graham, Rachel L; Scobey, Trevor D; Gralinski, Lisa E; Denison, Mark R; Zambon, Maria; Baric, Ralph S

2014-04-01

Middle East respiratory syndrome coronavirus (MERS-CoV) emerged in 2012, causing severe acute respiratory disease and pneumonia, with 44% mortality among 136 cases to date. Design of vaccines to limit the virus spread or diagnostic tests to track newly emerging strains requires knowledge of antigenic and serologic relationships between MERS-CoV and other CoVs.  Using synthetic genomics and Venezuelan equine encephalitis virus replicons (VRPs) expressing spike and nucleocapsid proteins from MERS-CoV and other human and bat CoVs, we characterize the antigenic responses (using Western blot and enzyme-linked immunosorbent assay) and serologic responses (using neutralization assays) against 2 MERS-CoV isolates in comparison with those of other human and bat CoVs.  Serologic and neutralization responses against the spike glycoprotein were primarily strain specific, with a very low level of cross-reactivity within or across subgroups. CoV N proteins within but not across subgroups share cross-reactive epitopes with MERS-CoV isolates. Our findings were validated using a convalescent-phase serum specimen from a patient infected with MERS-CoV (NA 01) and human antiserum against SARS-CoV, human CoV NL63, and human CoV OC43.  Vaccine design for emerging CoVs should involve chimeric spike protein containing neutralizing epitopes from multiple virus strains across subgroups to reduce immune pathology, and a diagnostic platform should include a panel of nucleocapsid and spike proteins from phylogenetically distinct CoVs.

Comparison of Brucella immunoglobulin M and G flow assays with serum agglutination and 2-mercaptoethanol tests in the diagnosis of brucellosis

NARCIS (Netherlands)

Zeytinoğlu, Ayşin; Turhan, Ajda; Altuğlu, Imre; Bilgiç, Altinay; Abdoel, Theresia H.; Smits, Henk L.

2006-01-01

The diagnostic value of Brucella IgM/IgG flow assays was evaluated in comparison with serum agglutination and 2-mercaptoethanol tests by testing a selection of serum samples submitted to the laboratory because of clinical suspicion of brucellosis. All 39 admission and 11 follow-up samples that

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

Directory of Open Access Journals (Sweden)

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.

Adenosine A2A Receptors Control Glutamatergic Synaptic Plasticity in Fast Spiking Interneurons of the Prefrontal Cortex

Directory of Open Access Journals (Sweden)

Amber Kerkhofs

2018-03-01

Full Text Available Adenosine A2A receptors (A2AR are activated upon increased synaptic activity to assist in the implementation of long-term plastic changes at synapses. While it is reported that A2AR are involved in the control of prefrontal cortex (PFC-dependent behavior such as working memory, reversal learning and effort-based decision making, it is not known whether A2AR control glutamatergic synapse plasticity within the medial PFC (mPFC. To elucidate that, we tested whether A2AR blockade affects long-term plasticity (LTP of excitatory post-synaptic potentials in pyramidal neurons and fast spiking (FS interneurons in layer 5 of the mPFC and of population spikes. Our results show that A2AR are enriched at mPFC synapses, where their blockade reversed the direction of plasticity at excitatory synapses onto layer 5 FS interneurons from LTP to long-term depression, while their blockade had no effect on the induction of LTP at excitatory synapses onto layer 5 pyramidal neurons. At the network level, extracellularly induced LTP of population spikes was reduced by A2AR blockade. The interneuron-specificity of A2AR in controlling glutamatergic synapse LTP may ensure that during periods of high synaptic activity, a proper excitation/inhibition balance is maintained within the mPFC.

Preparation of Tc-99m human serum albumin using stannous citrate and stannous chloride

International Nuclear Information System (INIS)

El-Asrag, H.A.; El-Wetery, A.S.; El-Mohty, A.A.

1988-01-01

99mTc-albumin is widely used as radioactive indicator in the measurement of cardiac output by external counting techniques and in blood volume studies. The quality of 99mTc-albumin depends on the method of preparation. A comparative study had been carried out on the 99mTc-albumin preparation by the stannous chloride, stannous tartarate and stannous citrate method. The different parameters investigated for each method include: pH, albumin concentration, reductant concentration and ascorbic acid as antioxidant stabilizer. The biological distribution of 99mTc-albumin, prepared by different methods, were determined in mice and rats. A procedure was developed for the preparation of stannous human serum albumin (HSA) kit for human application the kit provides a freeze dried sterile formulation for reconstitution with sterile 99mTc pertechnetate solution to give 99mTc-Hsa, the effect of irradiation sterilization on the freeze dried kit was studied by spectrophotometric determination and biological distribution in mice and rats

Elevated Adiponectin Serum Levels in Women with Systemic Autoimmune Diseases

Directory of Open Access Journals (Sweden)

Éric Toussirot

2010-01-01

Full Text Available Adipose tissue produces a wide range of proteins that may influence the immune system. In this study, we assessed the serum levels of leptin, adiponectin, and ghrelin, in association with the measurements of body composition, in 15 female patients with various autoimmune diseases (systemic lupus erythematosus, primary Sjögren's syndrome, sarcoidosis, mixed connective tissue disease, vasculitis, CREST syndrome, and polymyositis and in 15 healthy female controls. There were no statistically significant differences between the patients and controls with regard to serum leptin, serum ghrelin, global fat mass, adiposity, and fat mass in the android or gynoid regions, whereas serum adiponectin levels were higher in patients than controls (16.3±1.6 μg/mL versus 9.7±0.6 μg/mL; =.01. As adiponectin is known to exhibit potent anti-inflammatory properties, a high adiponectinemia in patients with systemic autoimmune disease may mitigate the inflammatory response. However, the precise consequences of these elevated serum adiponectin levels on the metabolic syndrome development and atherosclerotic cardiovascular risk in this patient population still needs to be determined.

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

Science.gov (United States)

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

2018-03-01

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

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

Directory of Open Access Journals (Sweden)

A. El Yazidi

2018-03-01

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

Monte Carlo point process estimation of electromyographic envelopes from motor cortical spikes for brain-machine interfaces

Science.gov (United States)

Liao, Yuxi; She, Xiwei; Wang, Yiwen; Zhang, Shaomin; Zhang, Qiaosheng; Zheng, Xiaoxiang; Principe, Jose C.

2015-12-01

Objective. Representation of movement in the motor cortex (M1) has been widely studied in brain-machine interfaces (BMIs). The electromyogram (EMG) has greater bandwidth than the conventional kinematic variables (such as position, velocity), and is functionally related to the discharge of cortical neurons. As the stochastic information of EMG is derived from the explicit spike time structure, point process (PP) methods will be a good solution for decoding EMG directly from neural spike trains. Previous studies usually assume linear or exponential tuning curves between neural firing and EMG, which may not be true. Approach. In our analysis, we estimate the tuning curves in a data-driven way and find both the traditional functional-excitatory and functional-inhibitory neurons, which are widely found across a rat’s motor cortex. To accurately decode EMG envelopes from M1 neural spike trains, the Monte Carlo point process (MCPP) method is implemented based on such nonlinear tuning properties. Main results. Better reconstruction of EMG signals is shown on baseline and extreme high peaks, as our method can better preserve the nonlinearity of the neural tuning during decoding. The MCPP improves the prediction accuracy (the normalized mean squared error) 57% and 66% on average compared with the adaptive point process filter using linear and exponential tuning curves respectively, for all 112 data segments across six rats. Compared to a Wiener filter using spike rates with an optimal window size of 50 ms, MCPP decoding EMG from a point process improves the normalized mean square error (NMSE) by 59% on average. Significance. These results suggest that neural tuning is constantly changing during task execution and therefore, the use of spike timing methodologies and estimation of appropriate tuning curves needs to be undertaken for better EMG decoding in motor BMIs.

Cytoplasmic tail of coronavirus spike protein has intracellular

Indian Academy of Sciences (India)

https://www.ias.ac.in/article/fulltext/jbsc/042/02/0231-0244. Keywords. Coronavirus spike protein trafficking; cytoplasmic tail signal; endoplasmic reticulum–Golgi intermediate complex; lysosome. Abstract. Intracellular trafficking and localization studies of spike protein from SARS and OC43 showed that SARS spikeprotein is ...

Correlated Disruption of Resting-State fMRI, LFP, and Spike Connectivity between Area 3b and S2 following Spinal Cord Injury in Monkeys.

Science.gov (United States)

Wu, Ruiqi; Yang, Pai-Feng; Chen, Li Min

2017-11-15

This study aims to understand how functional connectivity (FC) between areas 3b and S2 alters following input deprivation and the neuronal basis of disrupted FC of resting-state fMRI signals. We combined submillimeter fMRI with microelectrode recordings to localize the deafferented digit regions in areas 3b and S2 by mapping tactile stimulus-evoked fMRI activations before and after cervical dorsal column lesion in each male monkey. An average afferent disruption of 97% significantly reduced fMRI, local field potential (LFP), and spike responses to stimuli in both areas. Analysis of resting-state fMRI signal correlation, LFP coherence, and spike cross-correlation revealed significantly reduced functional connectivity between deafferented areas 3b and S2. The degrees of reductions in stimulus responsiveness and FC after deafferentation differed across fMRI, LFP, and spiking signals. The reduction of FC was much weaker than that of stimulus-evoked responses. Whereas the largest stimulus-evoked signal drop (∼80%) was observed in LFP signals, the greatest FC reduction was detected in the spiking activity (∼30%). fMRI signals showed mild reductions in stimulus responsiveness (∼25%) and FC (∼20%). The overall deafferentation-induced changes were quite similar in areas 3b and S2 across signals. Here we demonstrated that FC strength between areas 3b and S2 was much weakened by dorsal column lesion, and stimulus response reduction and FC disruption in fMRI covary with those of LFP and spiking signals in deafferented areas 3b and S2. These findings have important implications for fMRI studies aiming to probe FC alterations in pathological conditions involving deafferentation in humans. SIGNIFICANCE STATEMENT By directly comparing fMRI, local field potential, and spike signals in both tactile stimulation and resting states before and after severe disruption of dorsal column afferent, we demonstrated that reduction in fMRI responses to stimuli is accompanied by weakened

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.

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

Spike-timing theory of working memory.

Directory of Open Access Journals (Sweden)

Botond Szatmáry

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

Dual roles for spike signaling in cortical neural populations

Directory of Open Access Journals (Sweden)

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.

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

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.

Baseline serum CXCL10 and IL-12 levels may predict severe asthmatics' responsiveness to omalizumab.

Science.gov (United States)

Suzukawa, Maho; Matsumoto, Hisako; Ohshima, Nobuharu; Tashimo, Hiroyuki; Asari, Isao; Tajiri, Tomoko; Niimi, Akio; Nagase, Hiroyuki; Matsui, Hirotoshi; Kobayashi, Nobuyuki; Shoji, Shunsuke; Ohta, Ken

2018-01-01

Omalizumab, a humanized anti-IgE monoclonal antibody, is the first molecularly targeted drug for severe asthmatics. However, responses to omalizumab vary widely among patients. This study aimed to assess the potential of baseline serum cytokine levels as predictors of responsiveness to omalizumab. Thirty-one patients with severe, persistent asthma were enrolled in this study and administered omalizumab for at least 1 year. Response to omalizumab was assessed based on the physician's global evaluation of treatment effectiveness (GETE) at 48 weeks of treatment. Blood samples were collected at baseline and 16 and 32 weeks after starting omalizumab and measured for 30 cytokines by Luminex 200 and ELISA. Exhaled nitric oxide (FeNO) levels, peripheral blood eosinophil counts, pre-bronchodilator pulmonary functions and Asthma Quality of Life Questionnaire scores were determined at baseline and 16, 32 and 48 weeks after starting omalizumab. The numbers of clinically significant asthma exacerbations in the previous year and during 48 weeks of treatment with omalizumab were assessed. GETE assessment showed 19 responders (61.3%) and 12 non-responders (38.7%). Responders showed significantly higher levels of CXCL10 and IL-12 at baseline compared to non-responders (CXCL10: responders, 1530.0 ± 315.2 pg/ml vs. non-responders, 1066.0 ± 396.8 pg/ml, P = 0.001; IL-12: responders, 60.2 ± 39.2 pg/ml vs. non-responders, 32.2 ± 26.3 pg/ml, P = 0.04). ROC curves to distinguish responders from non-responders using the baseline serum CXCL10 level showed a good AUC of 0.83. At 32 weeks of omalizumab therapy, serum CXCL10 tended to be increased (1350 ± 412.3 pg/ml at baseline vs. 1529 ± 637.6 pg/ml at 32 weeks, P = 0.16) and serum IL-12 tended to be decreased (49.4 ± 37.0 pg/ml at baseline vs. 43.9 ± 30.9 pg/ml at 32 weeks, P = 0.05). On the other hand, serum IL-5 and PDGF were significantly decreased (IL-5: 54.2 ± 13.8 pg/ml at baseline vs. 49

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

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)

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.