scholarly journals A-current and type I/type II transition determine collective spiking from common input

2012 ◽  
Vol 108 (6) ◽  
pp. 1631-1645 ◽  
Author(s):  
Andrea K. Barreiro ◽  
Evan L. Thilo ◽  
Eric Shea-Brown
Keyword(s):  
Time Scales ◽  
Cell Populations ◽  
Type I ◽  
Time Lags ◽  
Type Ii ◽  
Neuron Models ◽  
Common Input ◽  
Time Constants ◽  
Long Time ◽  
Short Time

The mechanisms and impact of correlated, or synchronous, firing among pairs and groups of neurons are under intense investigation throughout the nervous system. A ubiquitous circuit feature that can give rise to such correlations consists of overlapping, or common, inputs to pairs and populations of cells, leading to common spike train responses. Here, we use computational tools to study how the transfer of common input currents into common spike outputs is modulated by the physiology of the recipient cells. We focus on a key conductance, gA, for the A-type potassium current, which drives neurons between “type II” excitability (low gA), and “type I” excitability (high gA). Regardless of gA, cells transform common input fluctuations into a tendency to spike nearly simultaneously. However, this process is more pronounced at low gA values. Thus, for a given level of common input, type II neurons produce spikes that are relatively more correlated over short time scales. Over long time scales, the trend reverses, with type II neurons producing relatively less correlated spike trains. This is because these cells' increased tendency for simultaneous spiking is balanced by an anticorrelation of spikes at larger time lags. These findings extend and interpret prior findings for phase oscillators to conductance-based neuron models that cover both oscillatory (superthreshold) and subthreshold firing regimes. We demonstrate a novel implication for neural signal processing: downstream cells with long time constants are selectively driven by type I cell populations upstream and those with short time constants by type II cell populations. Our results are established via high-throughput numerical simulations and explained via the cells' filtering properties and nonlinear dynamics.

The Spread of Pollutants from Harbour Sludge Depots

1984 ◽  
Vol 16 (3-4) ◽  
pp. 623-633
Author(s):  
M Loxham ◽  
F Weststrate
Keyword(s):  
Time Scales ◽  
Molecular Diffusion ◽  
Near Field ◽  
Parameter Analysis ◽  
Migration Patterns ◽  
Long Time ◽  
Dilution Effects ◽  
Short Time ◽  
Harbour Sludge

It is generally agreed that both the landfill option, or the civil techniques option for the final disposal of contaminated harbour sludge involves the isolation of the sludge from the environment. For short time scales, engineered barriers such as a bentonite screen, plastic sheets, pumping strategies etc. can be used. However for long time scales the effectiveness of such measures cannot be counted upon. It is thus necessary to be able to predict the long term environmenttal spread of contaminants from a mature landfill. A model is presented that considers diffusion and adsorption in the landfill site and convection and adsorption in the underlaying aquifer. From a parameter analysis starting form practical values it is shown that the adsorption behaviour and the molecular diffusion coefficient of the sludge, are the key parameters involved in the near field. The dilution effects of the far field migration patterns are also illustrated.

scholarly journals Nonlinearities of heart rate variability in animal models of impaired cardiac control: contribution of different time scales

2017 ◽  
Vol 123 (2) ◽  
pp. 344-351 ◽  
Author(s):  
Luiz Eduardo Virgilio Silva ◽  
Renata Maria Lataro ◽  
Jaci Airton Castania ◽  
Carlos Alberto Aguiar Silva ◽  
Helio Cesar Salgado ◽  
...  
Keyword(s):  
Nonlinear Dynamics ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Time Scales ◽  
Multiscale Entropy ◽  
Time Frequency ◽  
Cardiac Control ◽  
Long Time ◽  
Nonlinear Features ◽  
Short Time

Heart rate variability (HRV) has been extensively explored by traditional linear approaches (e.g., spectral analysis); however, several studies have pointed to the presence of nonlinear features in HRV, suggesting that linear tools might fail to account for the complexity of the HRV dynamics. Even though the prevalent notion is that HRV is nonlinear, the actual presence of nonlinear features is rarely verified. In this study, the presence of nonlinear dynamics was checked as a function of time scales in three experimental models of rats with different impairment of the cardiac control: namely, rats with heart failure (HF), spontaneously hypertensive rats (SHRs), and sinoaortic denervated (SAD) rats. Multiscale entropy (MSE) and refined MSE (RMSE) were chosen as the discriminating statistic for the surrogate test utilized to detect nonlinearity. Nonlinear dynamics is less present in HF animals at both short and long time scales compared with controls. A similar finding was found in SHR only at short time scales. SAD increased the presence of nonlinear dynamics exclusively at short time scales. Those findings suggest that a working baroreflex contributes to linearize HRV and to reduce the likelihood to observe nonlinear components of the cardiac control at short time scales. In addition, an increased sympathetic modulation seems to be a source of nonlinear dynamics at long time scales. Testing nonlinear dynamics as a function of the time scales can provide a characterization of the cardiac control complementary to more traditional markers in time, frequency, and information domains. NEW & NOTEWORTHY Although heart rate variability (HRV) dynamics is widely assumed to be nonlinear, nonlinearity tests are rarely used to check this hypothesis. By adopting multiscale entropy (MSE) and refined MSE (RMSE) as the discriminating statistic for the nonlinearity test, we show that nonlinear dynamics varies with time scale and the type of cardiac dysfunction. Moreover, as complexity metrics and nonlinearities provide complementary information, we strongly recommend using the test for nonlinearity as an additional index to characterize HRV.

scholarly journals Stratified Flows over and around Long Dynamically Tall Mountain Ridges

2019 ◽  
Vol 76 (5) ◽  
pp. 1265-1287 ◽  
Author(s):  
Arjun Jagannathan ◽  
Kraig Winters ◽  
Laurence Armi
Keyword(s):  
Time Scales ◽  
Time Scale ◽  
Stratified Flows ◽  
Half Width ◽  
Short Time Scale ◽  
Late Time ◽  
Low Level ◽  
Long Time ◽  
Flow Splitting ◽  
Short Time

Abstract Uniformly stratified flows approaching long and dynamically tall ridges develop two distinct flow components over disparate time scales. The fluid upstream and below a “blocking level” is stagnant in the limit of an infinite ridge and flows around the sides when the ridge extent is finite. The streamwise half-width of the obstacle at the blocking level arises as a natural inner length scale for the flow, while the excursion time over this half-width is an associated short time scale for the streamwise flow evolution. Over a longer time scale, low-level horizontal flow splitting leads to the establishment of an upstream layerwise potential flow beneath the blocking level. We demonstrate through numerical experiments that for sufficiently long ridges, crest control and streamwise asymmetry are seen on both the short and long time scales. On the short time scale, upstream blocking is established quickly and the flow is well described as a purely infinite-ridge overflow. Over the long time scale associated with flow splitting, low-level flow escapes around the sides, but the overflow continues to be hydraulically controlled and streamwise asymmetric in the neighborhood of the crest. We quantify this late-time overflow by estimating its volumetric transport and then briefly demonstrate how this approach can be extended to predict the overflow across nonuniform ridge shapes.

scholarly journals Simultaneous isolation of endothelial and alveolar epithelial type I and type II cells during mouse lung development in the absence of a transgenic reporter

2020 ◽  
Vol 318 (4) ◽  
pp. L619-L630 ◽  
Author(s):  
Yves Donati ◽  
Sanja Blaskovic ◽  
Isabelle Ruchonnet-Métrailler ◽  
Josefina Lascano Maillard ◽  
Constance Barazzone-Argiroffo
Keyword(s):  
Epithelial Cell ◽  
De Novo ◽  
Morphological Changes ◽  
Alveolar Epithelial Cell ◽  
Mouse Lung ◽  
Cell Populations ◽  
Type I ◽  
Type Ii ◽  
Alveolar Cells ◽  
Alveolar Epithelial

Mouse lung developmental maturation and final alveolarization phase begin at birth. During this dynamic process, alveolar cells modify their morphology and anchorage to the extracellular matrix. In particular, alveolar epithelial cell (AEC) type I undergo cytoplasmic flattening and folding to ensure alveoli lining. We developed FACS conditions for simultaneous isolation of alveolar epithelial and endothelial cells in the absence of specific reporters during the early and middle alveolar phase. We evidenced for the first time a pool of extractable epithelial cell populations expressing high levels of podoplanin at postnatal day (pnd)2, and we confirmed by RT-qPCR that these cells are already differentiated but still immature AEC type I. Maturation causes a decrease in isolation yields, reflecting the morphological changes that these cell populations are undergoing. Moreover, we find that major histocompatibility complex II (MHCII), reported as a good marker of AEC type II, is poorly expressed at pnd2 but highly present at pnd8. Combined experiments using LysoTracker and MHCII demonstrate the de novo acquisition of MCHII in AEC type II during lung alveolarization. The lung endothelial populations exhibit FACS signatures from vascular and lymphatic compartments. They can be concomitantly followed throughout alveolar development and were obtained with a noticeable increased yield at the last studied time point (pnd16). Our results provide new insights into early lung alveolar cell isolation feasibility and represent a valuable tool for pure AEC type I preparation as well as further in vitro two- and three-dimensional studies.

scholarly journals Graph-Based Prediction of Meeting Participation

2019 ◽  
Vol 3 (3) ◽  
pp. 54
Author(s):  
Gabriel Murray
Keyword(s):  
Predictive Models ◽  
Prediction Models ◽  
Group Discussion ◽  
Activity Level ◽  
Multiple Time ◽  
Time Lags ◽  
Activity Levels ◽  
Linguistic Features ◽  
Long Time ◽  
Short Time

Given a meeting participant’s turn-taking dynamics during one segment of a meeting, and their contribution to the group discussion up to that point, our aim is to automatically predict their activity level at a later point of the meeting. The predictive models use verbal and nonverbal features derived from social network representations of each small group interaction. The best automatic prediction models consistently outperform two baseline models at multiple time-lags. We analyze which interaction features are most predictive of later meeting activity levels, and investigate the efficacy of the verbal vs. nonverbal feature classes for this prediction task. At long time-lags, linguistic features become more crucial, but performance degrades compared with prediction at short time-lags.

Identification of Molecular and Biological Predictors of Genomic Complexity in Chronic Lymphocytic Leukemia.

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 2061-2061
Author(s):  
Sami Malek ◽  
Sam Fossum ◽  
Kerby Shedden ◽  
Peter Ouillette
Keyword(s):  
Multivariate Analysis ◽  
Snp Array ◽  
Type I ◽  
Type Ii ◽  
Snp Arrays ◽  
Post Irradiation ◽  
Cd38 Expression ◽  
Genomic Complexity ◽  
Complexity Score ◽  
Short Time

Abstract Unbiased quantitative assessments of genomic complexity in CLL using SNP arrays have identified high genomic complexity (≥3 subchromosomal lesions per genome) as a strong negative independent prognostic factor for short time to first therapy (TTFT) and short time to subsequent therapy (TTST) in CLL. In the present study, we have analyzed various variables as potential predictors for genomic complexity in CLL, including ZAP-70 status, CD38 status, IgVH mutation status, p53 aberrations (exon 5–9 sequence mutations or absent expression), CLL FISH categories (del17p, del11q, trisomy 12, and del13q14 type I or del13q14 type II, based on SNP arrays), MDM2 SNP309 allele status and the fraction of CLL cells alive 40 hours post-irradiation using univariate (N=178 cases) and multivariate (N=138 to 166 cases, depending on the included variables) analysis. Data on irradiation-induced ATM autophosphorylation are nearing completion and will be analyzed once available. SNP array-based genomic complexity was analyzed either as a dichotomous variable (<3 versus ≥3 subchromosomal lesions per genome) or as a quantitative variable and was based on either losses only (~85% of all lesions in CLL) or as total complexity (losses, gains and UPD). Results: Using the dichotomous genomic complexity score based on losses, the percentage of cells alive post-irradiation (odds ratio [OR] 3.26, p<0.0001), CD38 expression (OR=3.42, p=0.006), ZAP-70 expression (OR=4.06, p=0.005), IgVH-unmutated (OR=3.54, p=0.008), p53 aberrations (OR=13.2, p<0.0001), del13q14 type II (OR=3.42, p=0.015), del17p (OR=21, p<0.0001) and del11q (OR=6.6, p=0.002) all emerged as significant predictors of genomic complexity in univariate analysis. For multivariate analysis, various models were built incorporating factors with significant univariate associations and alternatively incorporating either del17p, p53 aberrations or the fraction of CLL cells alive post-irradiation (all three variables are p53 status-dependent) into the model. Using the dichotomous genomic complexity score based on losses, the fraction of cells alive post-irradiation, del17p, del11q, del13q14 type II, p53 aberrations and CD38 expression, emerged as significant independent predictors of genomic complexity in multivariate analysis. ZAP-70, IgVH status and del13q14 type I were not independent predictors. Using quantitative genomic complexity based on losses, the fraction of cells alive post-irradiation, del17p, del11q, del13q14 type I or II, and p53 aberrations emerged as significant predictors of genomic complexity in multivariate analysis. ZAP-70, CD38 expression and IgVH status were not independent predictors. In summary, multiple markers independently predict for genomic complexity in CLL, facilitating identification of genes/mutations (p53, ATM, Rb and others) involved in conferring unstable genomes in CLL. This analysis identifies SNP array-based genome interrogations as a single test uniquely able to capture genomic complexity in CLL.

scholarly journals Optical variability of quasars: a damped random walk

2013 ◽  
Vol 9 (S304) ◽  
pp. 395-398 ◽  
Author(s):  
Željko Ivezić ◽  
Chelsea MacLeod
Keyword(s):  
Random Walk ◽  
Time Scales ◽  
Model Parameters ◽  
Optical Wavelength ◽  
Long Time ◽  
Asymptotic Variability ◽  
Short Time ◽  
Quasar Variability ◽  
Best Fit

AbstractA damped random walk is a stochastic process, defined by an exponential covariance matrix that behaves as a random walk for short time scales and asymptotically achieves a finite variability amplitude at long time scales. Over the last few years, it has been demonstrated, mostly but not exclusively using SDSS data, that a damped random walk model provides a satisfactory statistical description of observed quasar variability in the optical wavelength range, for rest-frame timescales from 5 days to 2000 days. The best-fit characteristic timescale and asymptotic variability amplitude scale with the luminosity, black hole mass, and rest wavelength, and appear independent of redshift. In addition to providing insights into the physics of quasar variability, the best-fit model parameters can be used to efficiently separate quasars from stars in imaging surveys with adequate long-term multi-epoch data, such as expected from LSST.

scholarly journals The relationship between meteorological variables and sporadic cases of Legionnaires' disease in residents of England and Wales

2014 ◽  
Vol 142 (11) ◽  
pp. 2352-2359 ◽  
Author(s):  
K. D. HALSBY ◽  
C. A. JOSEPH ◽  
J. V. LEE ◽  
P. WILKINSON
Keyword(s):  
Conditional Logistic Regression ◽  
Time Lag ◽  
Time Lags ◽  
England And Wales ◽  
Long Time ◽  
Sporadic Cases ◽  
Risk Of Disease ◽  
Legionnaires Disease ◽  
Short Time ◽  
The Relationship

SUMMARYWe studied the timing of occurrence of 1676 sporadic, community-acquired cases of Legionnaires' disease in England and Wales between 1993 and 2008, in relation to temperature, relative humidity, rainfall, windspeed and ultraviolet light using a fixed-stratum case-crossover approach. The analysis was conducted using conditional logistic regression, with consideration of appropriate lag periods. There was evidence of an association between the risk of Legionnaires' disease and temperature with an apparently long time lag of 1–9 weeks [odds of disease at 95thvs. 75th centiles: 3·91, 95% confidence interval (CI) 2·06–7·40], and with rainfall at short time lags (of 2–10 days) (odds of disease at 75thvs.50th centiles: 1·78, 95% CI 1·50–2·13). There was some evidence that the risk of disease in relation to high temperatures was greater at high relative humidities. A higher risk of Legionnaires' disease may be indicated by preceding periods of warmer wetter weather.

scholarly journals Slow Decay of Impact in Equity Markets: Insights from the ANcerno Database

2018 ◽  
Vol 04 (03n04) ◽  
pp. 1950006
Author(s):  
Frédéric Bucci ◽  
Michael Benzaquen ◽  
Fabrizio Lillo ◽  
Jean-Philippe Bouchaud
Keyword(s):  
Empirical Study ◽  
Time Scales ◽  
Equity Markets ◽  
Equity Market ◽  
Slow Decay ◽  
The Us ◽  
Long Time ◽  
Power Law Function ◽  
Short Time ◽  
The Impact

We present an empirical study of price reversion after the executed metaorders. We use a dataset with more than 8 million metaorders executed by institutional investors in the US equity market. We show that relaxation takes place as soon as the metaorder ends: while at the end of the same day, it is on average [Formula: see text] of the peak impact, the decay continues for the next few days, following a power-law function at short-time scales, and converges to a non-zero asymptotic value at long-time scales ([Formula: see text] days) equal to [Formula: see text] of the impact at the end of the first day, that is [Formula: see text] of peak impact. Due to a significant, multiday correlation of the sign of executed metaorders, a careful deconvolution of the observed impact must be performed to extract the estimate of the impact decay of isolated metaorders.

scholarly journals Failure through expanding voids in bacterial streamers

2017 ◽  
Author(s):  
Ishita Biswas ◽  
Ranajay Ghosh ◽  
Mohtada Sadrzadeh ◽  
Aloke Kumar
Keyword(s):  
Time Scales ◽  
Void Growth ◽  
Growth Time ◽  
Long Time ◽  
Void Propagation ◽  
Growth Of Voids ◽  
Micro Pillars ◽  
Fracture Arrest ◽  
Short Time ◽  
Strong Contrast

AbstractWe investigate the failure of thick bacterial floc-mediated streamers in a microfluidic device with micro-pillars. We found that streamers could fail due to the growth of voids in the biomass that originate near the pillar walls. The quantification of void growth was made possible by the use of 200 nm fluorescent polystyrene beads. The beads get trapped in the extra-cellular matrix of the streamer biomass and act as tracers. Void growth time-scales could be characterized into short-time scales and long time-scales and the crack/void propagation showed several instances of fracture-arrest ultimately leading to a catastrophic failure of the entire streamer structure. This mode of fracture stands in strong contrast to necking-type instability observed before in streamers.

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