State-Space Algorithms for Estimating Spike Rate Functions
Smith, Anne C.; Scalon, Joao D.; Wirth, Sylvia; Yanike, Marianna; Suzuki, Wendy A.; Brown, Emery N.
2010-01-01
The accurate characterization of spike firing rates including the determination of when changes in activity occur is a fundamental issue in the analysis of neurophysiological data. Here we describe a state-space model for estimating the spike rate function that provides a maximum likelihood estimate of the spike rate, model goodness-of-fit assessments, as well as confidence intervals for the spike rate function and any other associated quantities of interest. Using simulated spike data, we first compare the performance of the state-space approach with that of Bayesian adaptive regression splines (BARS) and a simple cubic spline smoothing algorithm. We show that the state-space model is computationally efficient and comparable with other spline approaches. Our results suggest both a theoretically sound and practical approach for estimating spike rate functions that is applicable to a wide range of neurophysiological data. PMID:19911062
Estimating spiking irregularities under changing environments.
Miura, Keiji; Okada, Masato; Amari, Shun-Ichi
2006-10-01
We considered a gamma distribution of interspike intervals as a statistical model for neuronal spike generation. A gamma distribution is a natural extension of the Poisson process taking the effect of a refractory period into account. The model is specified by two parameters: a time-dependent firing rate and a shape parameter that characterizes spiking irregularities of individual neurons. Because the environment changes over time, observed data are generated from a model with a time-dependent firing rate, which is an unknown function. A statistical model with an unknown function is called a semiparametric model and is generally very difficult to solve. We used a novel method of estimating functions in information geometry to estimate the shape parameter without estimating the unknown function. We obtained an optimal estimating function analytically for the shape parameter independent of the functional form of the firing rate. This estimation is efficient without Fisher information loss and better than maximum likelihood estimation. We suggest a measure of spiking irregularity based on the estimating function, which may be useful for characterizing individual neurons in changing environments. PMID:16907630
Optimal firing rate estimation
NASA Technical Reports Server (NTRS)
Paulin, M. G.; Hoffman, L. F.
2001-01-01
We define a measure for evaluating the quality of a predictive model of the behavior of a spiking neuron. This measure, information gain per spike (Is), indicates how much more information is provided by the model than if the prediction were made by specifying the neuron's average firing rate over the same time period. We apply a maximum Is criterion to optimize the performance of Gaussian smoothing filters for estimating neural firing rates. With data from bullfrog vestibular semicircular canal neurons and data from simulated integrate-and-fire neurons, the optimal bandwidth for firing rate estimation is typically similar to the average firing rate. Precise timing and average rate models are limiting cases that perform poorly. We estimate that bullfrog semicircular canal sensory neurons transmit in the order of 1 bit of stimulus-related information per spike.
Estimating membrane voltage correlations from extracellular spike trains.
Dorn, Jessy D; Ringach, Dario L
2003-04-01
The cross-correlation coefficient between neural spike trains is a commonly used tool in the study of neural interactions. Two well-known complications that arise in its interpretation are 1) modulations in the correlation coefficient may result solely from changes in the mean firing rate of the cells and 2) the mean firing rates of the neurons impose upper and lower bounds on the correlation coefficient whose absolute values differ by an order of magnitude or more. Here, we propose a model-based approach to the interpretation of spike train correlations that circumvents these problems. The basic idea of our proposal is to estimate the cross-correlation coefficient between the membrane voltages of two cells from their extracellular spike trains and use the resulting value as the degree of correlation (or association) of neural activity. This is done in the context of a model that assumes the membrane voltages of the cells have a joint normal distribution and spikes are generated by a simple thresholding operation. We show that, under these assumptions, the estimation of the correlation coefficient between the membrane voltages reduces to the calculation of a tetrachoric correlation coefficient (a measure of association in nominal data introduced by Karl Pearson) on a contingency table calculated from the spike data. Simulations of conductance-based leaky integrate-and-fire neurons indicate that, despite its simplicity, the technique yields very good estimates of the intracellular membrane voltage correlation from the extracellular spike trains in biologically realistic models. PMID:12686584
Estimating nonstationary input signals from a single neuronal spike train
NASA Astrophysics Data System (ADS)
Kim, Hideaki; Shinomoto, Shigeru
2012-11-01
Neurons temporally integrate input signals, translating them into timed output spikes. Because neurons nonperiodically emit spikes, examining spike timing can reveal information about input signals, which are determined by activities in the populations of excitatory and inhibitory presynaptic neurons. Although a number of mathematical methods have been developed to estimate such input parameters as the mean and fluctuation of the input current, these techniques are based on the unrealistic assumption that presynaptic activity is constant over time. Here, we propose tracking temporal variations in input parameters with a two-step analysis method. First, nonstationary firing characteristics comprising the firing rate and non-Poisson irregularity are estimated from a spike train using a computationally feasible state-space algorithm. Then, information about the firing characteristics is converted into likely input parameters over time using a transformation formula, which was constructed by inverting the neuronal forward transformation of the input current to output spikes. By analyzing spike trains recorded in vivo, we found that neuronal input parameters are similar in the primary visual cortex V1 and middle temporal area, whereas parameters in the lateral geniculate nucleus of the thalamus were markedly different.
Optimal Estimation and Rank Detection for Sparse Spiked Covariance Matrices
Cai, Tony; Ma, Zongming; Wu, Yihong
2014-01-01
This paper considers a sparse spiked covariancematrix model in the high-dimensional setting and studies the minimax estimation of the covariance matrix and the principal subspace as well as the minimax rank detection. The optimal rate of convergence for estimating the spiked covariance matrix under the spectral norm is established, which requires significantly different techniques from those for estimating other structured covariance matrices such as bandable or sparse covariance matrices. We also establish the minimax rate under the spectral norm for estimating the principal subspace, the primary object of interest in principal component analysis. In addition, the optimal rate for the rank detection boundary is obtained. This result also resolves the gap in a recent paper by Berthet and Rigollet [2] where the special case of rank one is considered. PMID:26257453
Asynchronous Rate Chaos in Spiking Neuronal Circuits.
Harish, Omri; Hansel, David
2015-07-01
The brain exhibits temporally complex patterns of activity with features similar to those of chaotic systems. Theoretical studies over the last twenty years have described various computational advantages for such regimes in neuronal systems. Nevertheless, it still remains unclear whether chaos requires specific cellular properties or network architectures, or whether it is a generic property of neuronal circuits. We investigate the dynamics of networks of excitatory-inhibitory (EI) spiking neurons with random sparse connectivity operating in the regime of balance of excitation and inhibition. Combining Dynamical Mean-Field Theory with numerical simulations, we show that chaotic, asynchronous firing rate fluctuations emerge generically for sufficiently strong synapses. Two different mechanisms can lead to these chaotic fluctuations. One mechanism relies on slow I-I inhibition which gives rise to slow subthreshold voltage and rate fluctuations. The decorrelation time of these fluctuations is proportional to the time constant of the inhibition. The second mechanism relies on the recurrent E-I-E feedback loop. It requires slow excitation but the inhibition can be fast. In the corresponding dynamical regime all neurons exhibit rate fluctuations on the time scale of the excitation. Another feature of this regime is that the population-averaged firing rate is substantially smaller in the excitatory population than in the inhibitory population. This is not necessarily the case in the I-I mechanism. Finally, we discuss the neurophysiological and computational significance of our results. PMID:26230679
Spike timing precision changes with spike rate adaptation in the owl's auditory space map.
Keller, Clifford H; Takahashi, Terry T
2015-10-01
Spike rate adaptation (SRA) is a continuing change of responsiveness to ongoing stimuli, which is ubiquitous across species and levels of sensory systems. Under SRA, auditory responses to constant stimuli change over time, relaxing toward a long-term rate often over multiple timescales. With more variable stimuli, SRA causes the dependence of spike rate on sound pressure level to shift toward the mean level of recent stimulus history. A model based on subtractive adaptation (Benda J, Hennig RM. J Comput Neurosci 24: 113-136, 2008) shows that changes in spike rate and level dependence are mechanistically linked. Space-specific neurons in the barn owl's midbrain, when recorded under ketamine-diazepam anesthesia, showed these classical characteristics of SRA, while at the same time exhibiting changes in spike timing precision. Abrupt level increases of sinusoidally amplitude-modulated (SAM) noise initially led to spiking at higher rates with lower temporal precision. Spike rate and precision relaxed toward their long-term values with a time course similar to SRA, results that were also replicated by the subtractive model. Stimuli whose amplitude modulations (AMs) were not synchronous across carrier frequency evoked spikes in response to stimulus envelopes of a particular shape, characterized by the spectrotemporal receptive field (STRF). Again, abrupt stimulus level changes initially disrupted the temporal precision of spiking, which then relaxed along with SRA. We suggest that shifts in latency associated with stimulus level changes may differ between carrier frequency bands and underlie decreased spike precision. Thus SRA is manifest not simply as a change in spike rate but also as a change in the temporal precision of spiking. PMID:26269555
Estimating Neuronal Information: Logarithmic Binning of Neuronal Inter-Spike Intervals.
Dorval, Alan D
2011-02-01
Neurons communicate via the relative timing of all-or-none biophysical signals called spikes. For statistical analysis, the time between spikes can be accumulated into inter-spike interval histograms. Information theoretic measures have been estimated from these histograms to assess how information varies across organisms, neural systems, and disease conditions. Because neurons are computational units that, to the extent they process time, work not by discrete clock ticks but by the exponential decays of numerous intrinsic variables, we propose that neuronal information measures scale more naturally with the logarithm of time. For the types of inter-spike interval distributions that best describe neuronal activity, the logarithm of time enables fewer bins to capture the salient features of the distributions. Thus, discretizing the logarithm of inter-spike intervals, as compared to the inter-spike intervals themselves, yields histograms that enable more accurate entropy and information estimates for fewer bins and less data. Additionally, as distribution parameters vary, the entropy and information calculated from the logarithm of the inter-spike intervals are substantially better behaved, e.g., entropy is independent of mean rate, and information is equally affected by rate gains and divisions. Thus, when compiling neuronal data for subsequent information analysis, the logarithm of the inter-spike intervals is preferred, over the untransformed inter-spike intervals, because it yields better information estimates and is likely more similar to the construction used by nature herself. PMID:24839390
Generalized analog thresholding for spike acquisition at ultralow sampling rates.
He, Bryan D; Wein, Alex; Varshney, Lav R; Kusuma, Julius; Richardson, Andrew G; Srinivasan, Lakshminarayan
2015-07-01
Efficient spike acquisition techniques are needed to bridge the divide from creating large multielectrode arrays (MEA) to achieving whole-cortex electrophysiology. In this paper, we introduce generalized analog thresholding (gAT), which achieves millisecond temporal resolution with sampling rates as low as 10 Hz. Consider the torrent of data from a single 1,000-channel MEA, which would generate more than 3 GB/min using standard 30-kHz Nyquist sampling. Recent neural signal processing methods based on compressive sensing still require Nyquist sampling as a first step and use iterative methods to reconstruct spikes. Analog thresholding (AT) remains the best existing alternative, where spike waveforms are passed through an analog comparator and sampled at 1 kHz, with instant spike reconstruction. By generalizing AT, the new method reduces sampling rates another order of magnitude, detects more than one spike per interval, and reconstructs spike width. Unlike compressive sensing, the new method reveals a simple closed-form solution to achieve instant (noniterative) spike reconstruction. The base method is already robust to hardware nonidealities, including realistic quantization error and integration noise. Because it achieves these considerable specifications using hardware-friendly components like integrators and comparators, generalized AT could translate large-scale MEAs into implantable devices for scientific investigation and medical technology. PMID:25904712
Generalized analog thresholding for spike acquisition at ultralow sampling rates
He, Bryan D.; Wein, Alex; Varshney, Lav R.; Kusuma, Julius; Richardson, Andrew G.
2015-01-01
Efficient spike acquisition techniques are needed to bridge the divide from creating large multielectrode arrays (MEA) to achieving whole-cortex electrophysiology. In this paper, we introduce generalized analog thresholding (gAT), which achieves millisecond temporal resolution with sampling rates as low as 10 Hz. Consider the torrent of data from a single 1,000-channel MEA, which would generate more than 3 GB/min using standard 30-kHz Nyquist sampling. Recent neural signal processing methods based on compressive sensing still require Nyquist sampling as a first step and use iterative methods to reconstruct spikes. Analog thresholding (AT) remains the best existing alternative, where spike waveforms are passed through an analog comparator and sampled at 1 kHz, with instant spike reconstruction. By generalizing AT, the new method reduces sampling rates another order of magnitude, detects more than one spike per interval, and reconstructs spike width. Unlike compressive sensing, the new method reveals a simple closed-form solution to achieve instant (noniterative) spike reconstruction. The base method is already robust to hardware nonidealities, including realistic quantization error and integration noise. Because it achieves these considerable specifications using hardware-friendly components like integrators and comparators, generalized AT could translate large-scale MEAs into implantable devices for scientific investigation and medical technology. PMID:25904712
Benchmarking Spike Rate Inference in Population Calcium Imaging.
Theis, Lucas; Berens, Philipp; Froudarakis, Emmanouil; Reimer, Jacob; Román Rosón, Miroslav; Baden, Tom; Euler, Thomas; Tolias, Andreas S; Bethge, Matthias
2016-05-01
A fundamental challenge in calcium imaging has been to infer spike rates of neurons from the measured noisy fluorescence traces. We systematically evaluate different spike inference algorithms on a large benchmark dataset (>100,000 spikes) recorded from varying neural tissue (V1 and retina) using different calcium indicators (OGB-1 and GCaMP6). In addition, we introduce a new algorithm based on supervised learning in flexible probabilistic models and find that it performs better than other published techniques. Importantly, it outperforms other algorithms even when applied to entirely new datasets for which no simultaneously recorded data is available. Future data acquired in new experimental conditions can be used to further improve the spike prediction accuracy and generalization performance of the model. Finally, we show that comparing algorithms on artificial data is not informative about performance on real data, suggesting that benchmarking different methods with real-world datasets may greatly facilitate future algorithmic developments in neuroscience. PMID:27151639
Incorporating spike-rate adaptation into a rate code in mathematical and biological neurons.
Ralston, Bridget N; Flagg, Lucas Q; Faggin, Eric; Birmingham, John T
2016-06-01
For a slowly varying stimulus, the simplest relationship between a neuron's input and output is a rate code, in which the spike rate is a unique function of the stimulus at that instant. In the case of spike-rate adaptation, there is no unique relationship between input and output, because the spike rate at any time depends both on the instantaneous stimulus and on prior spiking (the "history"). To improve the decoding of spike trains produced by neurons that show spike-rate adaptation, we developed a simple scheme that incorporates "history" into a rate code. We utilized this rate-history code successfully to decode spike trains produced by 1) mathematical models of a neuron in which the mechanism for adaptation (IAHP) is specified, and 2) the gastropyloric receptor (GPR2), a stretch-sensitive neuron in the stomatogastric nervous system of the crab Cancer borealis, that exhibits long-lasting adaptation of unknown origin. Moreover, when we modified the spike rate either mathematically in a model system or by applying neuromodulatory agents to the experimental system, we found that changes in the rate-history code could be related to the biophysical mechanisms responsible for altering the spiking. PMID:26888106
Philosophy of the Spike: Rate-Based vs. Spike-Based Theories of the Brain
Brette, Romain
2015-01-01
Does the brain use a firing rate code or a spike timing code? Considering this controversial question from an epistemological perspective, I argue that progress has been hampered by its problematic phrasing. It takes the perspective of an external observer looking at whether those two observables vary with stimuli, and thereby misses the relevant question: which one has a causal role in neural activity? When rephrased in a more meaningful way, the rate-based view appears as an ad hoc methodological postulate, one that is practical but with virtually no empirical or theoretical support. PMID:26617496
A memristive spiking neuron with firing rate coding
Ignatov, Marina; Ziegler, Martin; Hansen, Mirko; Petraru, Adrian; Kohlstedt, Hermann
2015-01-01
Perception, decisions, and sensations are all encoded into trains of action potentials in the brain. The relation between stimulus strength and all-or-nothing spiking of neurons is widely believed to be the basis of this coding. This initiated the development of spiking neuron models; one of today's most powerful conceptual tool for the analysis and emulation of neural dynamics. The success of electronic circuit models and their physical realization within silicon field-effect transistor circuits lead to elegant technical approaches. Recently, the spectrum of electronic devices for neural computing has been extended by memristive devices, mainly used to emulate static synaptic functionality. Their capabilities for emulations of neural activity were recently demonstrated using a memristive neuristor circuit, while a memristive neuron circuit has so far been elusive. Here, a spiking neuron model is experimentally realized in a compact circuit comprising memristive and memcapacitive devices based on the strongly correlated electron material vanadium dioxide (VO2) and on the chemical electromigration cell Ag/TiO2−x/Al. The circuit can emulate dynamical spiking patterns in response to an external stimulus including adaptation, which is at the heart of firing rate coding as first observed by E.D. Adrian in 1926. PMID:26539074
Cao, Ying; Maran, Selva K; Dhamala, Mukesh; Jaeger, Dieter; Heck, Detlef H
2012-06-20
Purkinje cells (PCs) in the mammalian cerebellum express high-frequency spontaneous activity with average spike rates between 30 and 200 Hz. Cerebellar nuclear (CN) neurons receive converging input from many PCs, resulting in a continuous barrage of inhibitory inputs. It has been hypothesized that pauses in PC activity trigger increases in CN spiking activity. A prediction derived from this hypothesis is that pauses in PC simple-spike activity represent relevant behavioral or sensory events. Here, we asked whether pauses in the simple-spike activity of PCs related to either fluid licking or respiration, play a special role in representing information about behavior. Both behaviors are widely represented in cerebellar PC simple-spike activity. We recorded PC activity in the vermis and lobus simplex of head-fixed mice while monitoring licking and respiratory behavior. Using cross-correlation and Granger causality analysis, we examined whether short interspike intervals (ISIs) had a different temporal relationship to behavior than long ISIs or pauses. Behavior-related simple-spike pauses occurred during low-rate simple-spike activity in both licking- and breathing-related PCs. Granger causality analysis revealed causal relationships between simple-spike pauses and behavior. However, the same results were obtained from an analysis of surrogate spike trains with gamma ISI distributions constructed to match rate modulations of behavior-related Purkinje cells. Our results therefore suggest that the occurrence of pauses in simple-spike activity does not represent additional information about behavioral or sensory events that goes beyond the simple-spike rate modulations. PMID:22723707
Separating Spike Count Correlation from Firing Rate Correlation
Vinci, Giuseppe; Ventura, Valérie; Smith, Matthew A.; Kass, Robert E.
2016-01-01
Populations of cortical neurons exhibit shared fluctuations in spiking activity over time. When measured for a pair of neurons over multiple repetitions of an identical stimulus, this phenomenon emerges as correlated trial-to-trial response variability via spike count correlation (SCC). However, spike counts can be viewed as noisy versions of firing rates, which can vary from trial to trial. From this perspective, the SCC for a pair of neurons becomes a noisy version of the corresponding firing-rate correlation (FRC). Furthermore, the magnitude of the SCC is generally smaller than that of the FRC, and is likely to be less sensitive to experimental manipulation. We provide statistical methods for disambiguating time-averaged drive from within-trial noise, thereby separating FRC from SCC. We study these methods to document their reliability, and we apply them to neurons recorded in vivo from area V4, in an alert animal. We show how the various effects we describe are reflected in the data: within-trial effects are largely negligible, while attenuation due to trial-to-trial variation dominates, and frequently produces comparisons in SCC that, because of noise, do not accurately reflect those based on the underlying FRC. PMID:26942746
Separating Spike Count Correlation from Firing Rate Correlation.
Vinci, Giuseppe; Ventura, Valérie; Smith, Matthew A; Kass, Robert E
2016-05-01
Populations of cortical neurons exhibit shared fluctuations in spiking activity over time. When measured for a pair of neurons over multiple repetitions of an identical stimulus, this phenomenon emerges as correlated trial-to-trial response variability via spike count correlation (SCC). However, spike counts can be viewed as noisy versions of firing rates, which can vary from trial to trial. From this perspective, the SCC for a pair of neurons becomes a noisy version of the corresponding firing rate correlation (FRC). Furthermore, the magnitude of the SCC is generally smaller than that of the FRC and is likely to be less sensitive to experimental manipulation. We provide statistical methods for disambiguating time-averaged drive from within-trial noise, thereby separating FRC from SCC. We study these methods to document their reliability, and we apply them to neurons recorded in vivo from area V4 in an alert animal. We show how the various effects we describe are reflected in the data: within-trial effects are largely negligible, while attenuation due to trial-to-trial variation dominates and frequently produces comparisons in SCC that, because of noise, do not accurately reflect those based on the underlying FRC. PMID:26942746
How adaptation shapes spike rate oscillations in recurrent neuronal networks
Augustin, Moritz; Ladenbauer, Josef; Obermayer, Klaus
2012-01-01
Neural mass signals from in-vivo recordings often show oscillations with frequencies ranging from <1 to 100 Hz. Fast rhythmic activity in the beta and gamma range can be generated by network-based mechanisms such as recurrent synaptic excitation-inhibition loops. Slower oscillations might instead depend on neuronal adaptation currents whose timescales range from tens of milliseconds to seconds. Here we investigate how the dynamics of such adaptation currents contribute to spike rate oscillations and resonance properties in recurrent networks of excitatory and inhibitory neurons. Based on a network of sparsely coupled spiking model neurons with two types of adaptation current and conductance-based synapses with heterogeneous strengths and delays we use a mean-field approach to analyze oscillatory network activity. For constant external input, we find that spike-triggered adaptation currents provide a mechanism to generate slow oscillations over a wide range of adaptation timescales as long as recurrent synaptic excitation is sufficiently strong. Faster rhythms occur when recurrent inhibition is slower than excitation and oscillation frequency increases with the strength of inhibition. Adaptation facilitates such network-based oscillations for fast synaptic inhibition and leads to decreased frequencies. For oscillatory external input, adaptation currents amplify a narrow band of frequencies and cause phase advances for low frequencies in addition to phase delays at higher frequencies. Our results therefore identify the different key roles of neuronal adaptation dynamics for rhythmogenesis and selective signal propagation in recurrent networks. PMID:23450654
Estimating individual firing frequencies in a multiple spike train record.
Pokora, Ondrej; Lansky, Petr
2012-11-15
Neuronal activity of several neurons is commonly recorded by a single electrode and then the individual spike trains are separated. If the separation is difficult or fails, then as a minimal result of the experiment, the individual firing rates are of interest. The proposed method solves the problem of their identification. This is possible under the condition that the recorded neurons are independent in their activities. The number of the neurons in the multi-unit record needs to be given (known or assumed) prior the calculation. The proposed method is based on the presence of the refractory period in neuronal firing, however, its precise value is not required. In addition to the determination of the individual firing rates the method can be used for an inference about the refractory period itself. PMID:23000722
NASA Astrophysics Data System (ADS)
Quintero-Quiroz, C.; Sorrentino, Taciano; Torrent, M. C.; Masoller, Cristina
2016-04-01
We study the dynamics of semiconductor lasers with optical feedback and direct current modulation, operating in the regime of low frequency fluctuations (LFFs). In the LFF regime the laser intensity displays abrupt spikes: the intensity drops to zero and then gradually recovers. We focus on the inter-spike-intervals (ISIs) and use a method of symbolic time-series analysis, which is based on computing the probabilities of symbolic patterns. We show that the variation of the probabilities of the symbols with the modulation frequency and with the intrinsic spike rate of the laser allows to identify different regimes of noisy locking. Simulations of the Lang-Kobayashi model are in good qualitative agreement with experimental observations.
Estimating temporal causal interaction between spike trains with permutation and transfer entropy.
Li, Zhaohui; Li, Xiaoli
2013-01-01
Estimating the causal interaction between neurons is very important for better understanding the functional connectivity in neuronal networks. We propose a method called normalized permutation transfer entropy (NPTE) to evaluate the temporal causal interaction between spike trains, which quantifies the fraction of ordinal information in a neuron that has presented in another one. The performance of this method is evaluated with the spike trains generated by an Izhikevich's neuronal model. Results show that the NPTE method can effectively estimate the causal interaction between two neurons without influence of data length. Considering both the precision of time delay estimated and the robustness of information flow estimated against neuronal firing rate, the NPTE method is superior to other information theoretic method including normalized transfer entropy, symbolic transfer entropy and permutation conditional mutual information. To test the performance of NPTE on analyzing simulated biophysically realistic synapses, an Izhikevich's cortical network that based on the neuronal model is employed. It is found that the NPTE method is able to characterize mutual interactions and identify spurious causality in a network of three neurons exactly. We conclude that the proposed method can obtain more reliable comparison of interactions between different pairs of neurons and is a promising tool to uncover more details on the neural coding. PMID:23940662
Estimating Temporal Causal Interaction between Spike Trains with Permutation and Transfer Entropy
Li, Zhaohui; Li, Xiaoli
2013-01-01
Estimating the causal interaction between neurons is very important for better understanding the functional connectivity in neuronal networks. We propose a method called normalized permutation transfer entropy (NPTE) to evaluate the temporal causal interaction between spike trains, which quantifies the fraction of ordinal information in a neuron that has presented in another one. The performance of this method is evaluated with the spike trains generated by an Izhikevich’s neuronal model. Results show that the NPTE method can effectively estimate the causal interaction between two neurons without influence of data length. Considering both the precision of time delay estimated and the robustness of information flow estimated against neuronal firing rate, the NPTE method is superior to other information theoretic method including normalized transfer entropy, symbolic transfer entropy and permutation conditional mutual information. To test the performance of NPTE on analyzing simulated biophysically realistic synapses, an Izhikevich’s cortical network that based on the neuronal model is employed. It is found that the NPTE method is able to characterize mutual interactions and identify spurious causality in a network of three neurons exactly. We conclude that the proposed method can obtain more reliable comparison of interactions between different pairs of neurons and is a promising tool to uncover more details on the neural coding. PMID:23940662
Estimating Extracellular Spike Waveforms from CA1 Pyramidal Cells with Multichannel Electrodes
Molden, Sturla; Moldestad, Olve; Storm, Johan F.
2013-01-01
Extracellular (EC) recordings of action potentials from the intact brain are embedded in background voltage fluctuations known as the “local field potential” (LFP). In order to use EC spike recordings for studying biophysical properties of neurons, the spike waveforms must be separated from the LFP. Linear low-pass and high-pass filters are usually insufficient to separate spike waveforms from LFP, because they have overlapping frequency bands. Broad-band recordings of LFP and spikes were obtained with a 16-channel laminar electrode array (silicone probe). We developed an algorithm whereby local LFP signals from spike-containing channel were modeled using locally weighted polynomial regression analysis of adjoining channels without spikes. The modeled LFP signal was subtracted from the recording to estimate the embedded spike waveforms. We tested the method both on defined spike waveforms added to LFP recordings, and on in vivo-recorded extracellular spikes from hippocampal CA1 pyramidal cells in anaesthetized mice. We show that the algorithm can correctly extract the spike waveforms embedded in the LFP. In contrast, traditional high-pass filters failed to recover correct spike shapes, albeit produceing smaller standard errors. We found that high-pass RC or 2-pole Butterworth filters with cut-off frequencies below 12.5 Hz, are required to retrieve waveforms comparable to our method. The method was also compared to spike-triggered averages of the broad-band signal, and yielded waveforms with smaller standard errors and less distortion before and after the spike. PMID:24391714
Deneux, Thomas; Kaszas, Attila; Szalay, Gergely; Katona, Gergely; Lakner, Tamás; Grinvald, Amiram; Rózsa, Balázs; Vanzetta, Ivo
2016-01-01
Extracting neuronal spiking activity from large-scale two-photon recordings remains challenging, especially in mammals in vivo, where large noises often contaminate the signals. We propose a method, MLspike, which returns the most likely spike train underlying the measured calcium fluorescence. It relies on a physiological model including baseline fluctuations and distinct nonlinearities for synthetic and genetically encoded indicators. Model parameters can be either provided by the user or estimated from the data themselves. MLspike is computationally efficient thanks to its original discretization of probability representations; moreover, it can also return spike probabilities or samples. Benchmarked on extensive simulations and real data from seven different preparations, it outperformed state-of-the-art algorithms. Combined with the finding obtained from systematic data investigation (noise level, spiking rate and so on) that photonic noise is not necessarily the main limiting factor, our method allows spike extraction from large-scale recordings, as demonstrated on acousto-optical three-dimensional recordings of over 1,000 neurons in vivo. PMID:27432255
Deneux, Thomas; Kaszas, Attila; Szalay, Gergely; Katona, Gergely; Lakner, Tamás; Grinvald, Amiram; Rózsa, Balázs; Vanzetta, Ivo
2016-01-01
Extracting neuronal spiking activity from large-scale two-photon recordings remains challenging, especially in mammals in vivo, where large noises often contaminate the signals. We propose a method, MLspike, which returns the most likely spike train underlying the measured calcium fluorescence. It relies on a physiological model including baseline fluctuations and distinct nonlinearities for synthetic and genetically encoded indicators. Model parameters can be either provided by the user or estimated from the data themselves. MLspike is computationally efficient thanks to its original discretization of probability representations; moreover, it can also return spike probabilities or samples. Benchmarked on extensive simulations and real data from seven different preparations, it outperformed state-of-the-art algorithms. Combined with the finding obtained from systematic data investigation (noise level, spiking rate and so on) that photonic noise is not necessarily the main limiting factor, our method allows spike extraction from large-scale recordings, as demonstrated on acousto-optical three-dimensional recordings of over 1,000 neurons in vivo. PMID:27432255
NASA Astrophysics Data System (ADS)
Shimazaki, Hideaki
2013-12-01
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.
A spike correction approach for variability analysis of heart rate sick infants
NASA Astrophysics Data System (ADS)
Govindan, R. B.; Al-Shargabi, Tareq; Metzler, Marina; Andescavage, Nickie N.; Joshi, Radhika; du Plessis, Adré
2016-02-01
In critical care monitoring, the heart rate (HR) offers valuable insight into the autonomic function of sick infants. However, the intensity of monitoring and clinical care such as intubation, suctioning, and venesection as well as routine movement, create a hostile environment for contamination of continuous signals. These artifacts usually present as spikes in the HR signal, which interfere with the characterization and subsequent evaluation of the HR. Post hoc spike removal is commonly required in research studies but is not feasible in clinical monitoring. We propose a two-step process to correct spikes in HR data. Step 1 comprises of two sub-steps to remove the spikes with upward deflection and downward deflection. In Step 2, we repeat Step 1, for different ɛ values and calculate root mean square (RMS) of the difference between the uncorrected HR and the corrected HR. The corrected HR that displayed either the smallest RMS value or the same RMS values for two or more ɛ values is considered optimally corrected data. We demonstrate the application of this approach to HR data collected from 5 preterm infants. We show that there is a significant difference between the spectral powers obtained for spike uncorrected and spike corrected HR.
Associative Memory Neural Network with Low Temporal Spiking Rates
NASA Astrophysics Data System (ADS)
Amit, Daniel J.; Treves, A.
1989-10-01
We describe a modified attractor neural network in which neuronal dynamics takes place on a time scale of the absolute refractory period but the mean temporal firing rate of any neuron in the network is lower by an arbitrary factor that characterizes the strength of the effective inhibition. It operates by encoding information on the excitatory neurons only and assuming the inhibitory neurons to be faster and to inhibit the excitatory ones by an effective postsynaptic potential that is expressed in terms of the activity of the excitatory neurons themselves. Retrieval is identified as a nonergodic behavior of the network whose consecutive states have a significantly enhanced activity rate for the neurons that should be active in a stored pattern and a reduced activity rate for the neurons that are inactive in the memorized pattern. In contrast to the Hopfield model the network operates away from fixed points and under the strong influence of noise. As a consequence, of the neurons that should be active in a pattern, only a small fraction is active in any given time cycle and those are randomly distributed, leading to reduced temporal rates. We argue that this model brings neural network models much closer to biological reality. We present the results of detailed analysis of the model as well as simulations.
NASA Astrophysics Data System (ADS)
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.
Goodness-of-Fit Tests and Nonparametric Adaptive Estimation for Spike Train Analysis.
Reynaud-Bouret, Patricia; Rivoirard, Vincent; Grammont, Franck; Tuleau-Malot, Christine
2014-01-01
When dealing with classical spike train analysis, the practitioner often performs goodness-of-fit tests to test whether the observed process is a Poisson process, for instance, or if it obeys another type of probabilistic model (Yana et al. in Biophys. J. 46(3):323-330, 1984; Brown et al. in Neural Comput. 14(2):325-346, 2002; Pouzat and Chaffiol in Technical report, http://arxiv.org/abs/arXiv:0909.2785, 2009). In doing so, there is a fundamental plug-in step, where the parameters of the supposed underlying model are estimated. The aim of this article is to show that plug-in has sometimes very undesirable effects. We propose a new method based on subsampling to deal with those plug-in issues in the case of the Kolmogorov-Smirnov test of uniformity. The method relies on the plug-in of good estimates of the underlying model that have to be consistent with a controlled rate of convergence. Some nonparametric estimates satisfying those constraints in the Poisson or in the Hawkes framework are highlighted. Moreover, they share adaptive properties that are useful from a practical point of view. We show the performance of those methods on simulated data. We also provide a complete analysis with these tools on single unit activity recorded on a monkey during a sensory-motor task.Electronic Supplementary MaterialThe online version of this article (doi:10.1186/2190-8567-4-3) contains supplementary material. PMID:24742008
Goodness-of-Fit Tests and Nonparametric Adaptive Estimation for Spike Train Analysis
2014-01-01
When dealing with classical spike train analysis, the practitioner often performs goodness-of-fit tests to test whether the observed process is a Poisson process, for instance, or if it obeys another type of probabilistic model (Yana et al. in Biophys. J. 46(3):323–330, 1984; Brown et al. in Neural Comput. 14(2):325–346, 2002; Pouzat and Chaffiol in Technical report, http://arxiv.org/abs/arXiv:0909.2785, 2009). In doing so, there is a fundamental plug-in step, where the parameters of the supposed underlying model are estimated. The aim of this article is to show that plug-in has sometimes very undesirable effects. We propose a new method based on subsampling to deal with those plug-in issues in the case of the Kolmogorov–Smirnov test of uniformity. The method relies on the plug-in of good estimates of the underlying model that have to be consistent with a controlled rate of convergence. Some nonparametric estimates satisfying those constraints in the Poisson or in the Hawkes framework are highlighted. Moreover, they share adaptive properties that are useful from a practical point of view. We show the performance of those methods on simulated data. We also provide a complete analysis with these tools on single unit activity recorded on a monkey during a sensory-motor task. Electronic Supplementary Material The online version of this article (doi:10.1186/2190-8567-4-3) contains supplementary material. PMID:24742008
Glascoe, E
2008-08-11
It is estimated that PBXN-110 will burn laminarly with a burn function of B = (0.6-1.3)*P{sup 1.0} (B is the burn rate in mm/s and P is pressure in MPa). This paper provides a brief discussion of how this burn behavior was estimated.
Effect of marital status on death rates. Part 2: Transient mortality spikes
NASA Astrophysics Data System (ADS)
Richmond, Peter; Roehner, Bertrand M.
2016-05-01
We examine what happens in a population when it experiences an abrupt change in surrounding conditions. Several cases of such "abrupt transitions" for both physical and living social systems are analyzed from which it can be seen that all share a common pattern. First, a steep rising death rate followed by a much slower relaxation process during which the death rate decreases as a power law. This leads us to propose a general principle which can be summarized as follows: "Any abrupt change in living conditions generates a mortality spike which acts as a kind of selection process". This we term the Transient Shock conjecture. It provides a qualitative model which leads to testable predictions. For example, marriage certainly brings about a major change in personal and social conditions and according to our conjecture one would expect a mortality spike in the months following marriage. At first sight this may seem an unlikely proposition but we demonstrate (by three different methods) that even here the existence of mortality spikes is supported by solid empirical evidence.
NASA Astrophysics Data System (ADS)
Fournier, Alexandre; Gallet, Yves; Usoskin, Ilya; Livermore, Philip W.; Kovaltsov, Gennady A.
2015-04-01
We seek corroborative evidence of the geomagnetic spikes detected in the Near East ca. 980 BC and 890 BC in the records of the past production rates of the cosmogenic nuclides 14C and 10Be. Our forward modeling strategy rests on global, time-dependent, geomagnetic spike field models feeding state-of-the-art models of cosmogenic nuclide production. We find that spike models with an energy budget in line with presently inferred large-scale flow at Earth's core surface fail to produce a visible imprint in the nuclide record. Spike models able to reproduce the intensity changes reported in the Near East require an unaccountably high-magnitude core flow, yet their computed impact on cosmogenic isotope production rates remains ambiguous. No simple and unequivocal agreement is obtained between the observed and modeled nuclide records at the epochs of interest. This indicates that cosmogenic nuclides cannot immediately be used to confirm the occurrence of these two geomagnetic spikes.
Shan, Bonan; Wang, Jiang; Deng, Bin; Wei, Xile; Yu, Haitao; Zhang, Zhen; Li, Huiyan
2016-07-01
This paper proposes an epilepsy detection and closed-loop control strategy based on Particle Swarm Optimization (PSO) algorithm. The proposed strategy can effectively suppress the epileptic spikes in neural mass models, where the epileptiform spikes are recognized as the biomarkers of transitions from the normal (interictal) activity to the seizure (ictal) activity. In addition, the PSO algorithm shows capabilities of accurate estimation for the time evolution of key model parameters and practical detection for all the epileptic spikes. The estimation effects of unmeasurable parameters are improved significantly compared with unscented Kalman filter. When the estimated excitatory-inhibitory ratio exceeds a threshold value, the epileptiform spikes can be inhibited immediately by adopting the proportion-integration controller. Besides, numerical simulations are carried out to illustrate the effectiveness of the proposed method as well as the potential value for the model-based early seizure detection and closed-loop control treatment design. PMID:27475078
NASA Astrophysics Data System (ADS)
Shan, Bonan; Wang, Jiang; Deng, Bin; Wei, Xile; Yu, Haitao; Zhang, Zhen; Li, Huiyan
2016-07-01
This paper proposes an epilepsy detection and closed-loop control strategy based on Particle Swarm Optimization (PSO) algorithm. The proposed strategy can effectively suppress the epileptic spikes in neural mass models, where the epileptiform spikes are recognized as the biomarkers of transitions from the normal (interictal) activity to the seizure (ictal) activity. In addition, the PSO algorithm shows capabilities of accurate estimation for the time evolution of key model parameters and practical detection for all the epileptic spikes. The estimation effects of unmeasurable parameters are improved significantly compared with unscented Kalman filter. When the estimated excitatory-inhibitory ratio exceeds a threshold value, the epileptiform spikes can be inhibited immediately by adopting the proportion-integration controller. Besides, numerical simulations are carried out to illustrate the effectiveness of the proposed method as well as the potential value for the model-based early seizure detection and closed-loop control treatment design.
Automatic Spike Sorting Using Tuning Information
Ventura, Valérie
2011-01-01
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. PMID:19548802
Patel, Mainak; Reed, Mike
2013-01-01
The optic tectum of the barn owl is a multimodal structure with multiple layers, with each layer topographically organized according to spatial receptive field. The response of a site to a stimulus can be measured as either spike rate or local field potential (LFP) gamma (25-90 Hz) power; within superficial layers, spike rate and gamma power spatial tuning curves are narrow and contrast-response functions rise slowly. Within deeper layers, however, spike rate tuning curves broaden and gamma power contrast-response functions sharpen. In this work, we employ a computational model to describe the inputs required to generate these transformations from superficial to deep layers and show that gamma power and spike rate can act as parallel information processing streams. PMID:23406211
Effects of sodium salicylate on spontaneous and evoked spike rate in the dorsal cochlear nucleus
Wei, Lei; Ding, Dalian; Sun, Wei; Xu-Friedman, Matthew A.; Salvi, Richard
2010-01-01
Spontaneous hyperactivity in the dorsal cochlear nucleus (DCN), particularly in fusiform cells, has been proposed as a neural generator of tinnitus. To determine if sodium salicylate, a reliable tinnitus inducer, could evoke hyperactivity in the DCN, we measured the spontaneous and depolarization-evoked spike rate in fusiform and cartwheel cells during salicylate superfusion. Five minute treatment with 1.4 mM salicylate suppressed spontaneous and evoked firing in fusiform cells; this decrease partially recovered after salicylate washout. Less suppression and greater recovery occurred with 3 minute treatment using 1.4 mM salicylate. In contrast, salicylate had no effect on the spontaneous or evoked firing of cartwheel cells indicating that salicylate’s suppressive effects are specific to fusiform cells. To determine if salicylate’s suppressive effects were a consequence of increased synaptic inhibition, spontaneous inhibitory post-synaptic currents (IPSC) were measured during salicylate treatment. Salicylate unexpectedly reduced IPSC thereby ruling out increased inhibition as a mechanism to explain the depressed firing rates in fusiform cells. The salicylate-induced suppression of fusiform spike rate apparently arises from unidentified changes in the cell’s intrinsic excitability. PMID:20430089
Spike rate of multi-unit muscle sympathetic nerve fibers after catheter-based renal nerve ablation.
Tank, Jens; Heusser, Karsten; Brinkmann, Julia; Schmidt, Bernhard M; Menne, Jan; Bauersachs, Johann; Haller, Hermann; Diedrich, André; Jordan, Jens
2015-10-01
Patients with treatment-resistant arterial hypertension exhibited profound reductions in single sympathetic vasoconstrictor fiber firing rates after renal nerve ablation. In contrast, integrated multi-unit muscle sympathetic nerve activity (MSNA) changed little or not at all. We hypothesized that conventional MSNA analysis may have missed single fiber discharges, thus, obscuring sympathetic inhibition after renal denervation. We studied patients with difficult-to-control arterial hypertension (age 45-74 years) before, 6 (n = 11), and 12 months (n = 8) after renal nerve ablation. Electrocardiogram, respiration, brachial, and finger arterial blood pressure (BP), as well as the MSNA and raw MSNA signals were analyzed. We detected MSNA action-potential spikes using 2 stage kurtosis wavelet denoising techniques to assess mean, median, and maximum spike rates for each beat-to-beat interval. Supine heart rate and systolic BP did not change at 6 (ΔHR: -2 ± 3 bpm; ΔSBP: 2 ± 9 mm Hg) or at 12 months (ΔHR: -1 ± 3 mm Hg, ΔSBP: -1 ± 9 mm Hg) after renal nerve ablation. Mean burst frequency and mean spike frequency at baseline were 34 ± 3 bursts per minute and 8 ± 1 spikes per second. Both measurements did not change at 6 months (-1.4 ± 3.6 bursts/minute; -0.6 ± 1.4 spikes/second) or at 12 months (-2.5 ± 4.0 bursts/minute; -2.0 ± 1.6 spikes/second) after renal nerve ablation. After renal nerve ablation, BP decreased in 3 of 11 patients. BP and MSNA spike frequency changes were not correlated (slope = -0.06; P = .369). Spike rate analysis of multi-unit MSNA neurograms further suggests that profound sympathetic inhibition is not a consistent finding after renal nerve ablation. PMID:26324745
A biophysically-based neuromorphic model of spike rate- and timing-dependent plasticity.
Rachmuth, Guy; Shouval, Harel Z; Bear, Mark F; Poon, Chi-Sang
2011-12-01
Current advances in neuromorphic engineering have made it possible to emulate complex neuronal ion channel and intracellular ionic dynamics in real time using highly compact and power-efficient complementary metal-oxide-semiconductor (CMOS) analog very-large-scale-integrated circuit technology. Recently, there has been growing interest in the neuromorphic emulation of the spike-timing-dependent plasticity (STDP) Hebbian learning rule by phenomenological modeling using CMOS, memristor or other analog devices. Here, we propose a CMOS circuit implementation of a biophysically grounded neuromorphic (iono-neuromorphic) model of synaptic plasticity that is capable of capturing both the spike rate-dependent plasticity (SRDP, of the Bienenstock-Cooper-Munro or BCM type) and STDP rules. The iono-neuromorphic model reproduces bidirectional synaptic changes with NMDA receptor-dependent and intracellular calcium-mediated long-term potentiation or long-term depression assuming retrograde endocannabinoid signaling as a second coincidence detector. Changes in excitatory or inhibitory synaptic weights are registered and stored in a nonvolatile and compact digital format analogous to the discrete insertion and removal of AMPA or GABA receptor channels. The versatile Hebbian synapse device is applicable to a variety of neuroprosthesis, brain-machine interface, neurorobotics, neuromimetic computation, machine learning, and neural-inspired adaptive control problems. PMID:22089232
Onizuka, Miho; Hoang, Huu; Kawato, Mitsuo; Tokuda, Isao T; Schweighofer, Nicolas; Katori, Yuichi; Aihara, Kazuyuki; Lang, Eric J; Toyama, Keisuke
2013-11-01
The inferior olive (IO) possesses synaptic glomeruli, which contain dendritic spines from neighboring neurons and presynaptic terminals, many of which are inhibitory and GABAergic. Gap junctions between the spines electrically couple neighboring neurons whereas the GABAergic synaptic terminals are thought to act to decrease the effectiveness of this coupling. Thus, the glomeruli are thought to be important for determining the oscillatory and synchronized activity displayed by IO neurons. Indeed, the tendency to display such activity patterns is enhanced or reduced by the local administration of the GABA-A receptor blocker picrotoxin (PIX) or the gap junction blocker carbenoxolone (CBX), respectively. We studied the functional roles of the glomeruli by solving the inverse problem of estimating the inhibitory (gi) and gap-junctional conductance (gc) using an IO network model. This model was built upon a prior IO network model, in which the individual neurons consisted of soma and dendritic compartments, by adding a glomerular compartment comprising electrically coupled spines that received inhibitory synapses. The model was used in the forward mode to simulate spike data under PIX and CBX conditions for comparison with experimental data consisting of multi-electrode recordings of complex spikes from arrays of Purkinje cells (complex spikes are generated in a one-to-one manner by IO spikes and thus can substitute for directly measuring IO spike activity). The spatiotemporal firing dynamics of the experimental and simulation spike data were evaluated as feature vectors, including firing rates, local variation, auto-correlogram, cross-correlogram, and minimal distance, and were contracted onto two-dimensional principal component analysis (PCA) space. gc and gi were determined as the solution to the inverse problem such that the simulation and experimental spike data were closely matched in the PCA space. The goodness of the match was confirmed by an analysis of variance
Cao, Yongqiang; Grossberg, Stephen
2012-02-01
A laminar cortical model of stereopsis and 3D surface perception is developed and simulated. The model shows how spiking neurons that interact in hierarchically organized laminar circuits of the visual cortex can generate analog properties of 3D visual percepts. The model describes how monocular and binocular oriented filtering interact with later stages of 3D boundary formation and surface filling-in in the LGN and cortical areas V1, V2, and V4. It proposes how interactions between layers 4, 3B, and 2/3 in V1 and V2 contribute to stereopsis, and how binocular and monocular information combine to form 3D boundary and surface representations. The model suggests how surface-to-boundary feedback from V2 thin stripes to pale stripes helps to explain how computationally complementary boundary and surface formation properties lead to a single consistent percept, eliminate redundant 3D boundaries, and trigger figure-ground perception. The model also shows how false binocular boundary matches may be eliminated by Gestalt grouping properties. In particular, the disparity filter, which helps to solve the correspondence problem by eliminating false matches, is realized using inhibitory interneurons as part of the perceptual grouping process by horizontal connections in layer 2/3 of cortical area V2. The 3D sLAMINART model simulates 3D surface percepts that are consciously seen in 18 psychophysical experiments. These percepts include contrast variations of dichoptic masking and the correspondence problem, the effect of interocular contrast differences on stereoacuity, Panum's limiting case, the Venetian blind illusion, stereopsis with polarity-reversed stereograms, da Vinci stereopsis, and perceptual closure. The model hereby illustrates a general method of unlumping rate-based models that use the membrane equations of neurophysiology into models that use spiking neurons, and which may be embodied in VLSI chips that use spiking neurons to minimize heat production. PMID
Dinath, Faheem; Bruce, Ian C
2008-01-01
Linear and nonlinear amplification schemes for hearing aids have thus far been developed and evaluated based on perceptual criteria such as speech intelligibility, sound comfort, and loudness equalization. Finding amplification schemes that optimize all of these perceptual metrics has proven difficult. Using a physiological model, Bruce et al. [1] investigated the effects of single-band gain adjustments to linear amplification prescriptions. Optimal gain adjustments for model auditory-nerve fiber responses to speech sentences from the TIMIT database were dependent on whether the error metric included the spike timing information (i.e., a time-resolution of several microseconds) or the mean firing rates (i.e., a time-resolution of several milliseconds). Results showed that positive gain adjustments are required to optimize the mean firing rate responses, whereas negative gain adjustments tend to optimize spike timing information responses. In this paper we examine the results in more depth using a similar optimization scheme applied to a synthetic vowel /E/. It is found that negative gain adjustments (i.e., below the linear gain prescriptions) minimize the spread of synchrony and deviation of the phase response to vowel formants in responses containing spike-timing information. In contrast, positive gain adjustments (i.e., above the linear gain prescriptions) normalize the distribution of mean discharge rates in the auditory nerve responses. Thus, linear amplification prescriptions appear to find a balance between restoring the spike-timing and mean-rate information in auditory-nerve responses. PMID:19163029
Mendoza-Poudereux, Isabel; Muñoz-Bertomeu, Jesús; Arrillaga, Isabel; Segura, Juan
2014-11-01
Spike lavender (Lavandula latifolia) is an economically important aromatic plant producing essential oils, whose components (mostly monoterpenes) are mainly synthesized through the plastidial methylerythritol 4-phosphate (MEP) pathway. 1-Deoxy-D-xylulose-5-phosphate (DXP) synthase (DXS), that catalyzes the first step of the MEP pathway, plays a crucial role in monoterpene precursors biosynthesis in spike lavender. To date, however, it is not known whether the DXP reductoisomerase (DXR), that catalyzes the conversion of DXP into MEP, is also a rate-limiting enzyme for the biosynthesis of monoterpenes in spike lavender. To investigate it, we generated transgenic spike lavender plants constitutively expressing the Arabidopsis thaliana DXR gene. Although two out of the seven transgenic T0 plants analyzed accumulated more essential oils than the controls, this is hardly imputable to the DXR transgene effect since a clear correlation between transcript accumulation and monoterpene production could not be established. Furthermore, these increased essential oil phenotypes were not maintained in their respective T1 progenies. Similar results were obtained when total chlorophyll and carotenoid content in both T0 transgenic plants and their progenies were analyzed. Our results then demonstrate that DXR enzyme does not play a crucial role in the synthesis of plastidial monoterpene precursors, suggesting that the control flux of the MEP pathway in spike lavender is primarily exerted by the DXS enzyme. PMID:25151124
Methods for estimating neural firing rates, and their application to brain-machine interfaces.
Cunningham, John P; Gilja, Vikash; Ryu, Stephen I; Shenoy, Krishna V
2009-11-01
Neural spike trains present analytical challenges due to their noisy, spiking nature. Many studies of neuroscientific and neural prosthetic importance rely on a smoothed, denoised estimate of a spike train's underlying firing rate. Numerous methods for estimating neural firing rates have been developed in recent years, but to date no systematic comparison has been made between them. In this study, we review both classic and current firing rate estimation techniques. We compare the advantages and drawbacks of these methods. Then, in an effort to understand their relevance to the field of neural prostheses, we also apply these estimators to experimentally gathered neural data from a prosthetic arm-reaching paradigm. Using these estimates of firing rate, we apply standard prosthetic decoding algorithms to compare the performance of the different firing rate estimators, and, perhaps surprisingly, we find minimal differences. This study serves as a review of available spike train smoothers and a first quantitative comparison of their performance for brain-machine interfaces. PMID:19349143
Multiscale analysis of neural spike trains.
Ramezan, Reza; Marriott, Paul; Chenouri, Shojaeddin
2014-01-30
This paper studies the multiscale analysis of neural spike trains, through both graphical and Poisson process approaches. We introduce the interspike interval plot, which simultaneously visualizes characteristics of neural spiking activity at different time scales. Using an inhomogeneous Poisson process framework, we discuss multiscale estimates of the intensity functions of spike trains. We also introduce the windowing effect for two multiscale methods. Using quasi-likelihood, we develop bootstrap confidence intervals for the multiscale intensity function. We provide a cross-validation scheme, to choose the tuning parameters, and study its unbiasedness. Studying the relationship between the spike rate and the stimulus signal, we observe that adjusting for the first spike latency is important in cross-validation. We show, through examples, that the correlation between spike trains and spike count variability can be multiscale phenomena. Furthermore, we address the modeling of the periodicity of the spike trains caused by a stimulus signal or by brain rhythms. Within the multiscale framework, we introduce intensity functions for spike trains with multiplicative and additive periodic components. Analyzing a dataset from the retinogeniculate synapse, we compare the fit of these models with the Bayesian adaptive regression splines method and discuss the limitations of the methodology. Computational efficiency, which is usually a challenge in the analysis of spike trains, is one of the highlights of these new models. In an example, we show that the reconstruction quality of a complex intensity function demonstrates the ability of the multiscale methodology to crack the neural code. PMID:23996238
Estimating birth and death rates of zooplankton
Taylor, B.E.; Slatkin, M.
1981-01-01
Two estimates of the birth rate using an egg ratio are derived from a three-stage (eggs, juveniles, and adults) model for an exponentially growing population, and the sensitivity of these estimates to time and age-dependence of the birth and death rates and to measurement errors is explored. Tests to determine whether a population violates the assumptions of the model are suggested, and birth rate estimates which partially compensate for some departures from the model are proposed. Other methods for estimating birth and death rates based on this type of model are reviewed. Four birth rate estimates are compared using data for a population of Daphnia pulicaria, and recommendations on the use of birth and death rates based on the egg ratio are made.
Least squares estimation of avian molt rates
Johnson, D.H.
1989-01-01
A straightforward least squares method of estimating the rate at which birds molt feathers is presented, suitable for birds captured more than once during the period of molt. The date of molt onset can also be estimated. The method is applied to male and female mourning doves.
Estimating mutation rate: how to count mutations?
Fu, Yun-Xin; Huai, Haying
2003-01-01
Mutation rate is an essential parameter in genetic research. Counting the number of mutant individuals provides information for a direct estimate of mutation rate. However, mutant individuals in the same family can share the same mutations due to premeiotic mutation events, so that the number of mutant individuals can be significantly larger than the number of mutation events observed. Since mutation rate is more closely related to the number of mutation events, whether one should count only independent mutation events or the number of mutants remains controversial. We show in this article that counting mutant individuals is a correct approach for estimating mutation rate, while counting only mutation events will result in underestimation. We also derived the variance of the mutation-rate estimate, which allows us to examine a number of important issues about the design of such experiments. The general strategy of such an experiment should be to sample as many families as possible and not to sample much more offspring per family than the reciprocal of the pairwise correlation coefficient within each family. To obtain a reasonably accurate estimate of mutation rate, the number of sampled families needs to be in the same or higher order of magnitude as the reciprocal of the mutation rate. PMID:12807798
Monitoring spike train synchrony.
Kreuz, Thomas; Chicharro, Daniel; Houghton, Conor; Andrzejak, Ralph G; Mormann, Florian
2013-03-01
Recently, the SPIKE-distance has been proposed as a parameter-free and timescale-independent measure of spike train synchrony. This measure is time resolved since it relies on instantaneous estimates of spike train dissimilarity. However, its original definition led to spuriously high instantaneous values for eventlike firing patterns. Here we present a substantial improvement of this measure that eliminates this shortcoming. The reliability gained allows us to track changes in instantaneous clustering, i.e., time-localized patterns of (dis)similarity among multiple spike trains. Additional new features include selective and triggered temporal averaging as well as the instantaneous comparison of spike train groups. In a second step, a causal SPIKE-distance is defined such that the instantaneous values of dissimilarity rely on past information only so that time-resolved spike train synchrony can be estimated in real time. We demonstrate that these methods are capable of extracting valuable information from field data by monitoring the synchrony between neuronal spike trains during an epileptic seizure. Finally, the applicability of both the regular and the real-time SPIKE-distance to continuous data is illustrated on model electroencephalographic (EEG) recordings. PMID:23221419
Graupner, Michael; Brunel, Nicolas
2012-03-01
Multiple stimulation protocols have been found to be effective in changing synaptic efficacy by inducing long-term potentiation or depression. In many of those protocols, increases in postsynaptic calcium concentration have been shown to play a crucial role. However, it is still unclear whether and how the dynamics of the postsynaptic calcium alone determine the outcome of synaptic plasticity. Here, we propose a calcium-based model of a synapse in which potentiation and depression are activated above calcium thresholds. We show that this model gives rise to a large diversity of spike timing-dependent plasticity curves, most of which have been observed experimentally in different systems. It accounts quantitatively for plasticity outcomes evoked by protocols involving patterns with variable spike timing and firing rate in hippocampus and neocortex. Furthermore, it allows us to predict that differences in plasticity outcomes in different studies are due to differences in parameters defining the calcium dynamics. The model provides a mechanistic understanding of how various stimulation protocols provoke specific synaptic changes through the dynamics of calcium concentration and thresholds implementing in simplified fashion protein signaling cascades, leading to long-term potentiation and long-term depression. The combination of biophysical realism and analytical tractability makes it the ideal candidate to study plasticity at the synapse, neuron, and network levels. PMID:22357758
Danzl, Per; Hespanha, João; Moehlis, Jeff
2009-12-01
We present an event-based feedback control method for randomizing the asymptotic phase of oscillatory neurons. Phase randomization is achieved by driving the neuron's state to its phaseless set, a point at which its phase is undefined and is extremely sensitive to background noise. We consider the biologically relevant case of a fixed magnitude constraint on the stimulus signal, and show how the control objective can be accomplished in minimum time. The control synthesis problem is addressed using the minimum-time-optimal Hamilton-Jacobi-Bellman framework, which is quite general and can be applied to any spiking neuron model in the conductance-based Hodgkin-Huxley formalism. We also use this methodology to compute a feedback control protocol for optimal spike rate increase. This framework provides a straightforward means of visualizing isochrons, without actually calculating them in the traditional way. Finally, we present an extension of the phase randomizing control scheme that is applied at the population level, to a network of globally coupled neurons that are firing in synchrony. The applied control signal desynchronizes the population in a demand-controlled way. PMID:19911192
Yi, Guo-Sheng; Wang, Jiang; Tsang, Kai-Ming; Wei, Xi-Le; Deng, Bin
2015-01-01
Dynamic spike threshold plays a critical role in neuronal input-output relations. In many neurons, the threshold potential depends on the rate of membrane potential depolarization (dV/dt) preceding a spike. There are two basic classes of neural excitability, i.e., Type I and Type II, according to input-output properties. Although the dynamical and biophysical basis of their spike initiation has been established, the spike threshold dynamic for each cell type has not been well described. Here, we use a biophysical model to investigate how spike threshold depends on dV/dt in two types of neuron. It is observed that Type II spike threshold is more depolarized and more sensitive to dV/dt than Type I. With phase plane analysis, we show that each threshold dynamic arises from the different separatrix and K+ current kinetics. By analyzing subthreshold properties of membrane currents, we find the activation of hyperpolarizing current prior to spike initiation is a major factor that regulates the threshold dynamics. The outward K+ current in Type I neuron does not activate at the perithresholds, which makes its spike threshold insensitive to dV/dt. The Type II K+ current activates prior to spike initiation and there is a large net hyperpolarizing current at the perithresholds, which results in a depolarized threshold as well as a pronounced threshold dynamic. These predictions are further attested in several other functionally equivalent cases of neural excitability. Our study provides a fundamental description about how intrinsic biophysical properties contribute to the threshold dynamics in Type I and Type II neurons, which could decipher their significant functions in neural coding. PMID:26083350
Estimated recharge rates at the Hanford Site
Fayer, M.J.; Walters, T.B.
1995-02-01
The Ground-Water Surveillance Project monitors the distribution of contaminants in ground water at the Hanford Site for the U.S. Department of Energy. A subtask called {open_quotes}Water Budget at Hanford{close_quotes} was initiated in FY 1994. The objective of this subtask was to produce a defensible map of estimated recharge rates across the Hanford Site. Methods that have been used to estimate recharge rates at the Hanford Site include measurements (of drainage, water contents, and tracers) and computer modeling. For the simulations of 12 soil-vegetation combinations, the annual rates varied from 0.05 mm/yr for the Ephrata sandy loam with bunchgrass to 85.2 mm/yr for the same soil without vegetation. Water content data from the Grass Site in the 300 Area indicated that annual rates varied from 3.0 to 143.5 mm/yr during an 8-year period. The annual volume of estimated recharge was calculated to be 8.47 {times} 10{sup 9} L for the potential future Hanford Site (i.e., the portion of the current Site bounded by Highway 240 and the Columbia River). This total volume is similar to earlier estimates of natural recharge and is 2 to 10x higher than estimates of runoff and ground-water flow from higher elevations. Not only is the volume of natural recharge significant in comparison to other ground-water inputs, the distribution of estimated recharge is highly skewed to the disturbed sandy soils (i.e., the 200 Areas, where most contaminants originate). The lack of good estimates of the means and variances of the supporting data (i.e., the soil map, the vegetation/land use map, the model parameters) translates into large uncertainties in the recharge estimates. When combined, the significant quantity of estimated recharge, its high sensitivity to disturbance, and the unquantified uncertainty of the data and model parameters suggest that the defensibility of the recharge estimates should be improved.
Satellite Angular Rate Estimation From Vector Measurements
NASA Technical Reports Server (NTRS)
Azor, Ruth; Bar-Itzhack, Itzhack Y.; Harman, Richard R.
1996-01-01
This paper presents an algorithm for estimating the angular rate vector of a satellite which is based on the time derivatives of vector measurements expressed in a reference and body coordinate. The computed derivatives are fed into a spacial Kalman filter which yields an estimate of the spacecraft angular velocity. The filter, named Extended Interlaced Kalman Filter (EIKF), is an extension of the Kalman filter which, although being linear, estimates the state of a nonlinear dynamic system. It consists of two or three parallel Kalman filters whose individual estimates are fed to one another and are considered as known inputs by the other parallel filter(s). The nonlinear dynamics stem from the nonlinear differential equation that describes the rotation of a three dimensional body. Initial results, using simulated data, and real Rossi X ray Timing Explorer (RXTE) data indicate that the algorithm is efficient and robust.
Consensus-Based Sorting of Neuronal Spike Waveforms
Fournier, Julien; Mueller, Christian M.; Shein-Idelson, Mark; Hemberger, Mike
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. PMID:27536990
Consensus-Based Sorting of Neuronal Spike Waveforms.
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. PMID:27536990
Baker, R.J.; Baehr, A.L.; Lahvis, M.A.
2000-01-01
An open microcosm method for quantifying microbial respiration and estimating biodegradation rates of hydrocarbons in gasoline-contaminated sediment samples has been developed and validated. Stainless-steel bioreactors are filled with soil or sediment samples, and the vapor-phase composition (concentrations of oxygen (O2), nitrogen (N2), carbon dioxide (CO2), and selected hydrocarbons) is monitored over time. Replacement gas is added as the vapor sample is taken, and selection of the replacement gas composition facilitates real-time decision-making regarding environmental conditions within the bioreactor. This capability allows for maintenance of field conditions over time, which is not possible in closed microcosms. Reaction rates of CO2 and O2 are calculated from the vapor-phase composition time series. Rates of hydrocarbon biodegradation are either measured directly from the hydrocarbon mass balance, or estimated from CO2 and O2 reaction rates and assumed reaction stoichiometries. Open microcosm experiments using sediments spiked with toluene and p-xylene were conducted to validate the stoichiometric assumptions. Respiration rates calculated from O2 consumption and from CO2 production provide estimates of toluene and p- xylene degradation rates within about ??50% of measured values when complete mineralization stoichiometry is assumed. Measured values ranged from 851.1 to 965.1 g m-3 year-1 for toluene, and 407.2-942.3 g m-3 year-1 for p- xylene. Contaminated sediment samples from a gasoline-spill site were used in a second set of microcosm experiments. Here, reaction rates of O2 and CO2 were measured and used to estimate hydrocarbon respiration rates. Total hydrocarbon reaction rates ranged from 49.0 g m-3 year-1 in uncontaminated (background) to 1040.4 g m-3 year-1 for highly contaminated sediment, based on CO2 production data. These rate estimates were similar to those obtained independently from in situ CO2 vertical gradient and flux determinations at the
Conwit, R A; Tracy, B; Cowl, A; McHugh, M; Stashuk, D; Brown, W F; Metter, E J
1998-10-01
Electromyographic signals detected from the quadriceps femoris during various constant force contractions were decomposed to identify individual motor unit discharges and mean firing rates (FRs). Subject and group mean FRs were calculated for each force level. Mean FR values and FR variability increased with force. Individual, subject, and group mean FRs showed slight increases until 30% of maximum voluntary contraction and larger increases thereafter. Findings are discussed in relation to motor unit recruitment, frequency modulation, and fatigue. PMID:9736067
Towards universal hybrid star formation rate estimators
NASA Astrophysics Data System (ADS)
Boquien, M.; Kennicutt, R.; Calzetti, D.; Dale, D.; Galametz, M.; Sauvage, M.; Croxall, K.; Draine, B.; Kirkpatrick, A.; Kumari, N.; Hunt, L.; De Looze, I.; Pellegrini, E.; Relaño, M.; Smith, J.-D.; Tabatabaei, F.
2016-06-01
Context. To compute the star formation rate (SFR) of galaxies from the rest-frame ultraviolet (UV), it is essential to take the obscuration by dust into account. To do so, one of the most popular methods consists in combining the UV with the emission from the dust itself in the infrared (IR). Yet, different studies have derived different estimators, showing that no such hybrid estimator is truly universal. Aims: In this paper we aim at understanding and quantifying what physical processes fundamentally drive the variations between different hybrid estimators. In so doing, we aim at deriving new universal UV+IR hybrid estimators to correct the UV for dust attenuation at local and global scales, taking the intrinsic physical properties of galaxies into account. Methods: We use the CIGALE code to model the spatially resolved far-UV to far-IR spectral energy distributions of eight nearby star-forming galaxies drawn from the KINGFISH sample. This allows us to determine their local physical properties, and in particular their UV attenuation, average SFR, average specific SFR (sSFR), and their stellar mass. We then examine how hybrid estimators depend on said properties. Results: We find that hybrid UV+IR estimators strongly depend on the stellar mass surface density (in particular at 70 μm and 100 μm) and on the sSFR (in particular at 24 μm and the total infrared). Consequently, the IR scaling coefficients for UV obscuration can vary by almost an order of magnitude: from 1.55 to 13.45 at 24 μm for instance. This result contrasts with other groups who found relatively constant coefficients with small deviations. We exploit these variations to construct a new class of adaptative hybrid estimators based on observed UV to near-IR colours and near-IR luminosity densities per unit area. We find that they can reliably be extended to entire galaxies. Conclusions: The new estimators provide better estimates of attenuation-corrected UV emission than classical hybrid estimators
NASA Astrophysics Data System (ADS)
Hashemi, M.; Valizadeh, A.; Azizi, Y.
2012-02-01
A recurrent loop consisting of a single Hodgkin-Huxley neuron influenced by a chemical excitatory delayed synaptic feedback is considered. We show that the behavior of the system depends on the duration of the activity of the synapse, which is determined by the activation and deactivation time constants of the synapse. For the fast synapses, those for which the effect of the synaptic activity is small compared to the period of firing, depending on the delay time, spiking with single and multiple interspike intervals is possible and the average firing rate can be smaller or larger than that of the open loop neuron. For slow synapses for which the synaptic time constants are of order of the period of the firing, the self-excitation increases the firing rate for all values of the delay time. We also show that for a chain consisting of few similar oscillators, if the synapses are chosen from different time constants, the system will follow the dynamics imposed by the fastest element, which is the oscillator that receives excitations via a slow synapse. The generalization of the results to other types of relaxation oscillators is discussed and the results are compared to those of the loops with inhibitory synapses as well as with gap junctions.
Quantitative Estimation of Tissue Blood Flow Rate.
Tozer, Gillian M; Prise, Vivien E; Cunningham, Vincent J
2016-01-01
The rate of blood flow through a tissue (F) is a critical parameter for assessing the functional efficiency of a blood vessel network following angiogenesis. This chapter aims to provide the principles behind the estimation of F, how F relates to other commonly used measures of tissue perfusion, and a practical approach for estimating F in laboratory animals, using small readily diffusible and metabolically inert radio-tracers. The methods described require relatively nonspecialized equipment. However, the analytical descriptions apply equally to complementary techniques involving more sophisticated noninvasive imaging.Two techniques are described for the quantitative estimation of F based on measuring the rate of tissue uptake following intravenous administration of radioactive iodo-antipyrine (or other suitable tracer). The Tissue Equilibration Technique is the classical approach and the Indicator Fractionation Technique, which is simpler to perform, is a practical alternative in many cases. The experimental procedures and analytical methods for both techniques are given, as well as guidelines for choosing the most appropriate method. PMID:27172960
A Model-Based Spike Sorting Algorithm for Removing Correlation Artifacts in Multi-Neuron Recordings
Chichilnisky, E. J.; Simoncelli, Eero P.
2013-01-01
We examine the problem of estimating the spike trains of multiple neurons from voltage traces recorded on one or more extracellular electrodes. Traditional spike-sorting methods rely on thresholding or clustering of recorded signals to identify spikes. While these methods can detect a large fraction of the spikes from a recording, they generally fail to identify synchronous or near-synchronous spikes: cases in which multiple spikes overlap. Here we investigate the geometry of failures in traditional sorting algorithms, and document the prevalence of such errors in multi-electrode recordings from primate retina. We then develop a method for multi-neuron spike sorting using a model that explicitly accounts for the superposition of spike waveforms. We model the recorded voltage traces as a linear combination of spike waveforms plus a stochastic background component of correlated Gaussian noise. Combining this measurement model with a Bernoulli prior over binary spike trains yields a posterior distribution for spikes given the recorded data. We introduce a greedy algorithm to maximize this posterior that we call “binary pursuit”. The algorithm allows modest variability in spike waveforms and recovers spike times with higher precision than the voltage sampling rate. This method substantially corrects cross-correlation artifacts that arise with conventional methods, and substantially outperforms clustering methods on both real and simulated data. Finally, we develop diagnostic tools that can be used to assess errors in spike sorting in the absence of ground truth. PMID:23671583
Revisiting the Estimation of Dinosaur Growth Rates
Myhrvold, Nathan P.
2013-01-01
Previous growth-rate studies covering 14 dinosaur taxa, as represented by 31 data sets, are critically examined and reanalyzed by using improved statistical techniques. The examination reveals that some previously reported results cannot be replicated by using the methods originally reported; results from new methods are in many cases different, in both the quantitative rates and the qualitative nature of the growth, from results in the prior literature. Asymptotic growth curves, which have been hypothesized to be ubiquitous, are shown to provide best fits for only four of the 14 taxa. Possible reasons for non-asymptotic growth patterns are discussed; they include systematic errors in the age-estimation process and, more likely, a bias toward younger ages among the specimens analyzed. Analysis of the data sets finds that only three taxa include specimens that could be considered skeletally mature (i.e., having attained 90% of maximum body size predicted by asymptotic curve fits), and eleven taxa are quite immature, with the largest specimen having attained less than 62% of predicted asymptotic size. The three taxa that include skeletally mature specimens are included in the four taxa that are best fit by asymptotic curves. The totality of results presented here suggests that previous estimates of both maximum dinosaur growth rates and maximum dinosaur sizes have little statistical support. Suggestions for future research are presented. PMID:24358133
Estimating instantaneous respiratory rate from the photoplethysmogram.
Dehkordi, Parastoo; Garde, Ainara; Molavi, Behnam; Petersen, Christian L; Ansermino, J Mark; Dumont, Guy A
2015-08-01
The photoplethysmogram (PPG) obtained from pulse oximetry shows the local changes of blood volume in tissues. Respiration induces variation in the PPG baseline due to the variation in venous blood return during each breathing cycle. We have proposed an algorithm based on the synchrosqueezing transform (SST) to estimate instantaneous respiratory rate (IRR) from the PPG. The SST is a combination of wavelet analysis and a reallocation method which aims to sharpen the time-frequency representation of the signal and can provide an accurate estimation of instantaneous frequency. In this application, the SST was applied to the PPG and IRR was detected as the predominant ridge in the respiratory band (0.1 Hz - 1 Hz) in the SST plane. The algorithm was tested against the Capnobase benchmark dataset that contains PPG, capnography, and expert labelled reference respiratory rate from 42 subjects. The IRR estimation accuracy was assessed using the root mean square (RMS) error and Bland-Altman plot. The median RMS error was 0.39 breaths/min for all subjects which ranged from the lowest error of 0.18 breaths/min to the highest error of 13.86 breaths/min. A Bland-Altman plot showed an agreement between the IRR obtained from PPG and reference respiratory rate with a bias of -0.32 and limits agreement of -7.72 to 7.07. Extracting IRR from PPG expands the functionality of pulse oximeters and provides additional diagnostic power to this non-invasive monitoring tool. PMID:26737696
Kruijne, Wouter; Van der Stigchel, Stefan; Meeter, Martijn
2014-03-01
The trajectory of saccades to a target is often affected whenever there is a distractor in the visual field. Distractors can cause a saccade to deviate towards their location or away from it. The oculomotor mechanisms that produce deviation towards distractors have been thoroughly explored in behavioral, neurophysiological and computational studies. The mechanisms underlying deviation away, on the other hand, remain unclear. Behavioral findings suggest a mechanism of spatially focused, top-down inhibition in a saccade map, and deviation away has become a tool to investigate such inhibition. However, this inhibition hypothesis has little neuroanatomical or neurophysiological support, and recent findings go against it. Here, we propose that deviation away results from an unbalanced saccade drive from the brainstem, caused by spike rate adaptation in brainstem long-lead burst neurons. Adaptation to stimulation in the direction of the distractor results in an unbalanced drive away from it. An existing model of the saccade system was extended with this theory. The resulting model simulates a wide range of findings on saccade trajectories, including findings that have classically been interpreted to support inhibition views. Furthermore, the model replicated the effect of saccade latency on deviation away, but predicted this effect would be absent with large (400 ms) distractor-target onset asynchrony. This prediction was confirmed in an experiment, which demonstrates that the theory both explains classical findings on saccade trajectories and predicts new findings. PMID:24486387
Robust Speech Rate Estimation for Spontaneous Speech
Wang, Dagen; Narayanan, Shrikanth S.
2010-01-01
In this paper, we propose a direct method for speech rate estimation from acoustic features without requiring any automatic speech transcription. We compare various spectral and temporal signal analysis and smoothing strategies to better characterize the underlying syllable structure to derive speech rate. The proposed algorithm extends the methods of spectral subband correlation by including temporal correlation and the use of prominent spectral subbands for improving the signal correlation essential for syllable detection. Furthermore, to address some of the practical robustness issues in previously proposed methods, we introduce some novel components into the algorithm such as the use of pitch confidence for filtering spurious syllable envelope peaks, magnifying window for tackling neighboring syllable smearing, and relative peak measure thresholds for pseudo peak rejection. We also describe an automated approach for learning algorithm parameters from data, and find the optimal settings through Monte Carlo simulations and parameter sensitivity analysis. Final experimental evaluations are conducted based on a portion of the Switchboard corpus for which manual phonetic segmentation information, and published results for direct comparison are available. The results show a correlation coefficient of 0.745 with respect to the ground truth based on manual segmentation. This result is about a 17% improvement compared to the current best single estimator and a 11% improvement over the multiestimator evaluated on the same Switchboard database. PMID:20428476
Park, Hyeon-Mi; Nakasato, Nobukazu; Iwasaki, Masaki; Shamoto, Hiroshi; Tominaga, Teiji; Yoshimoto, Takashi
2004-07-01
Interictal spikes in patients with epilepsy may be detected by either electroencephalography (EEG) (E-spikes) or magnetoencephalography (MEG) (M-spikes), or both MEG and EEG (E/M-spikes). Localization and amplitude were compared between E/M-spikes and M-spikes in 7 adult patients with extratemporal epilepsy to evaluate the clinical significance of MEG spikes. MEG and EEG were simultaneously measured using a helmet-shaped MEG system with planar-type gradiometers and scalp electrodes of the international 10-20 system. Sources of E/M-spikes and M-spikes were estimated by an equivalent current dipole (ECD) model for MEG at peak latency. Each subject showed 9 to 20 (mean 13.4) E/M-spikes and 9 to 31 (mean 16.3) M-spikes. No subjects showed significant differences in the ECD locations between E/M- and M-spikes. ECD moments of the E/M-spikes were significantly larger in 2 patients and not significantly different in the other 5 patients. The similar localizations of E/M-spikes and M-spikes suggest that combination of MEG and EEG is useful to detect more interictal spikes in patients with extratemporal epilepsy. The smaller tendency of ECD amplitude of the M-spikes than E/M-spikes suggests that scalp EEG may overlook small tangential spikes due to background brain noise. Localization value of M-spikes is clinically equivalent to that of E/M-spikes. PMID:15240925
NASA Astrophysics Data System (ADS)
Constable, C.; Davies, C. J.
2015-12-01
Geomagnetic field intensities corresponding to virtual axial dipole moments of up to 200 ZAm2, more than twice the modern value, have been inferred from archeomagnetic measurements on artifacts dated at or shortly after 1000 BC. Anomalously high values occur in the Levant and Georgia, but not in Bulgaria. The origin of this spike is believed to lie in Earth's core: however, its spatio-temporal characteristics and the geomagnetic processes responsible for such a feature remain a mystery. We show that a localized spike in the radial magnetic field at the core-mantle boundary (CMB) must necessarily contribute to the largest scale changes in Earth's surface field, namely the dipole. Even the limiting spike of a delta function at the CMB produces a minimum surface cap size of 60 degrees for a factor of two increase in paleointensity. Combined evidence from modern satellite and millennial scale field modeling suggests that the Levantine Spike is intimately associated with a strong increase in dipole moment prior to 1000 BC and likely the product of north-westward motion of concentrated near equatorial Asian flux patches like those seen in the modern field. New archeomagnetic studies are needed to confirm this interpretation. Minimum estimates of the power dissipated by the spike are comparable to independent estimates of the dissipation associated with the entire steady state geodynamo. This suggests that geomagnetic spikes are either associated with rapid changes in magnetic energy or strong Lorentz forces.
Accidental Turbulent Discharge Rate Estimation from Videos
NASA Astrophysics Data System (ADS)
Ibarra, Eric; Shaffer, Franklin; Savaş, Ömer
2015-11-01
A technique to estimate the volumetric discharge rate in accidental oil releases using high speed video streams is described. The essence of the method is similar to PIV processing, however the cross correlation is carried out on the visible features of the efflux, which are usually turbulent, opaque and immiscible. The key step in the process is to perform a pixelwise time filtering on the video stream, in which the parameters are commensurate with the scales of the large eddies. The velocity field extracted from the shell of visible features is then used to construct an approximate velocity profile within the discharge. The technique has been tested on laboratory experiments using both water and oil jets at Re ~105 . The technique is accurate to 20%, which is sufficient for initial responders to deploy adequate resources for containment. The software package requires minimal user input and is intended for deployment on an ROV in the field. Supported by DOI via NETL.
Information geometry of interspike intervals in spiking neurons.
Ikeda, Kazushi
2005-12-01
An information geometrical method is developed for characterizing or classifying neurons in cortical areas, whose spike rates fluctuate in time. Under the assumption that the interspike intervals of a spike sequence of a neuron obey a gamma process with a time-variant spike rate and a fixed shape parameter, we formulate the problem of characterization as a semiparametric statistical estimation, where the spike rate is a nuisance parameter. We derive optimal criteria from the information geometrical viewpoint when certain assumptions are added to the formulation, and we show that some existing measures, such as the coefficient of variation and the local variation, are expressed as estimators of certain functions under the same assumptions. PMID:16212769
Nonparametric estimation of the rediscovery rate.
Lee, Donghwan; Ganna, Andrea; Pawitan, Yudi; Lee, Woojoo
2016-08-15
Validation studies have been used to increase the reliability of the statistical conclusions for scientific discoveries; such studies improve the reproducibility of the findings and reduce the possibility of false positives. Here, one of the important roles of statistics is to quantify reproducibility rigorously. Two concepts were recently defined for this purpose: (i) rediscovery rate (RDR), which is the expected proportion of statistically significant findings in a study that can be replicated in the validation study and (ii) false discovery rate in the validation study (vFDR). In this paper, we aim to develop a nonparametric approach to estimate the RDR and vFDR and show an explicit link between the RDR and the FDR. Among other things, the link explains why reproducing statistically significant results even with low FDR level may be difficult. Two metabolomics datasets are considered to illustrate the application of the RDR and vFDR concepts in high-throughput data analysis. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26910365
Spike sorting of synchronous spikes from local neuron ensembles.
Franke, Felix; Pröpper, Robert; Alle, Henrik; Meier, Philipp; Geiger, Jörg R P; Obermayer, Klaus; Munk, Matthias H J
2015-10-01
Synchronous spike discharge of cortical neurons is thought to be a fingerprint of neuronal cooperativity. Because neighboring neurons are more densely connected to one another than neurons that are located further apart, near-synchronous spike discharge can be expected to be prevalent and it might provide an important basis for cortical computations. Using microelectrodes to record local groups of neurons does not allow for the reliable separation of synchronous spikes from different cells, because available spike sorting algorithms cannot correctly resolve the temporally overlapping waveforms. We show that high spike sorting performance of in vivo recordings, including overlapping spikes, can be achieved with a recently developed filter-based template matching procedure. Using tetrodes with a three-dimensional structure, we demonstrate with simulated data and ground truth in vitro data, obtained by dual intracellular recording of two neurons located next to a tetrode, that the spike sorting of synchronous spikes can be as successful as the spike sorting of nonoverlapping spikes and that the spatial information provided by multielectrodes greatly reduces the error rates. We apply the method to tetrode recordings from the prefrontal cortex of behaving primates, and we show that overlapping spikes can be identified and assigned to individual neurons to study synchronous activity in local groups of neurons. PMID:26289473
19 CFR 159.38 - Rates for estimated duties.
Code of Federal Regulations, 2010 CFR
2010-04-01
... 19 Customs Duties 2 2010-04-01 2010-04-01 false Rates for estimated duties. 159.38 Section 159.38... TREASURY (CONTINUED) LIQUIDATION OF DUTIES Conversion of Foreign Currency § 159.38 Rates for estimated duties. For purposes of calculating estimated duties, the port director shall use the rate or...
A robust estimator of rainfall rate using differential reflectivity
NASA Technical Reports Server (NTRS)
Gorgucci, Eugenio; Scarchilli, Gianfranco; Chandrasekar, V.
1994-01-01
Conventional estimator of rainfall rate using reflectivity factor and differential reflectivity Z(sub DR) becomes unstable when the measured values of Z(sub DR) are small due to measurement errors. An alternate estimator of rainfall rate using reflectivity factor and Z(sub DR) is derived, so that this estimator is fairly robust over the full dynamic range of reflectivity factor and Z(sub DR). Simulations are used to study the error structure of this robust estimator in comparison with the conventional estimator of rainfall rate. It is shown that the alternate estimator performs better than the conventional estimator of rainfall rate at all rainfall values. In particular the largest improvement of this estimator is proved to be in light rain. The robust estimator is obtained as a direct regression of rainfall rate against reflectivity factor and Z(sub DR) instead of solving for the drop size distribution.
Angular-Rate Estimation Using Quaternion Measurements
NASA Technical Reports Server (NTRS)
Azor, Ruth; Bar-Itzhack, Y.; Deutschmann, Julie K.; Harman, Richard R.
1998-01-01
In most spacecraft (SC) there is a need to know the SC angular rate. Precise angular rate is required for attitude determination, and a coarse rate is needed for attitude control damping. Classically, angular rate information is obtained from gyro measurements. These days, there is a tendency to build smaller, lighter and cheaper SC, therefore the inclination now is to do away with gyros and use other means and methods to determine the angular rate. The latter is also needed even in gyro equipped satellites when performing high rate maneuvers whose angular-rate is out of range of the on board gyros or in case of gyro failure. There are several ways to obtain the angular rate in a gyro-less SC. When the attitude is known, one can differentiate the attitude in whatever parameters it is given and use the kinematics equation that connects the derivative of the attitude with the satellite angular-rate and compute the latter. Since SC usually utilize vector measurements for attitude determination, the differentiation of the attitude introduces a considerable noise component in the computed angular-rate vector.
Bias in Estimation of Misclassification Rates
ERIC Educational Resources Information Center
Haberman, Shelby J.
2006-01-01
When a simple random sample of size n is employed to establish a classification rule for prediction of a polytomous variable by an independent variable, the best achievable rate of misclassification is higher than the corresponding best achievable rate if the conditional probability distribution is known for the predicted variable given the…
Estimation of transition probabilities of credit ratings
NASA Astrophysics Data System (ADS)
Peng, Gan Chew; Hin, Pooi Ah
2015-12-01
The present research is based on the quarterly credit ratings of ten companies over 15 years taken from the database of the Taiwan Economic Journal. The components in the vector mi (mi1, mi2,⋯, mi10) may first be used to denote the credit ratings of the ten companies in the i-th quarter. The vector mi+1 in the next quarter is modelled to be dependent on the vector mi via a conditional distribution which is derived from a 20-dimensional power-normal mixture distribution. The transition probability Pkl (i ,j ) for getting mi+1,j = l given that mi, j = k is then computed from the conditional distribution. It is found that the variation of the transition probability Pkl (i ,j ) as i varies is able to give indication for the possible transition of the credit rating of the j-th company in the near future.
Attitude and Trajectory Determination using Magnetometers and Estimated Rates
NASA Technical Reports Server (NTRS)
Schierman, J. D.; Schmidt, D. K.; Deutschmann, J.
1997-01-01
A simultaneous attitude and orbit determination algorithm which uses magnetometer measurements and estimated attitude rates is presented. This is an extension of an algorithm which uses magnetometer and rate gyro measurements. The new algorithm is intended for gyroless spacecraft, or in the case of gyro failures/saturation. Torque control input data is used in forming the rate estimates. Simulation tests of the algorithm are presented. First, tests were performed using the 'true' rate values at each time step. This simulated using accurate gyro measurements. Then, tests were performed estimating the rates. Using estimated rates rather than 'gyro measurements' did not significantly degrade the algorithm's performance if accurate estimates of the initial rates were available. An initial Root-Sum-Square (RSS) position error of 1,400 km was reduced to an average error of approximately 100 km within the first two minutes. The RSS attitude error converged to less than 1.5 degrees within three orbits.
Guo, Zifeng; Slafer, Gustavo A; Schnurbusch, Thorsten
2016-07-01
Spike fertility traits are critical attributes for grain yield in wheat (Triticum aestivum L.). Here, we examine the genotypic variation in three important traits: maximum number of floret primordia, number of fertile florets, and number of grains. We determine their relationship in determining spike fertility in 30 genotypes grown under two contrasting conditions: field and greenhouse. The maximum number of floret primordia per spikelet (MFS), fertile florets per spikelet (FFS), and number of grains per spikelet (GS) not only exhibited large genotypic variation in both growth conditions and across all spikelet positions studied, but also displayed moderate levels of heritability. FFS was closely associated with floret survival and only weakly related to MFS. We also found that the post-anthesis process of grain set/abortion was important in determining genotypic variation in GS; an increase in GS was mainly associated with improved grain survival. Ovary size at anthesis was associated with both floret survival (pre-anthesis) and grain survival (post-anthesis), and was thus believed to 'connect' the two traits. In this work, proximal florets (i.e. the first three florets from the base of a spikelet: F1, F2, and F3) produced fertile florets and set grains in most cases. The ovary size of more distal florets (F4 and beyond) seemed to act as a decisive factor for grain setting and effectively reflected pre-anthesis floret development. In both growth conditions, GS positively correlated with ovary size of florets in the distal position (F4), suggesting that assimilates allocated to distal florets may play a critical role in regulating grain set. PMID:27279276
Data-Rate Estimation for Autonomous Receiver Operation
NASA Technical Reports Server (NTRS)
Tkacenko, A.; Simon, M. K.
2005-01-01
In this article, we present a series of algorithms for estimating the data rate of a signal whose admissible data rates are integer base, integer powered multiples of a known basic data rate. These algorithms can be applied to the Electra radio currently used in the Deep Space Network (DSN), which employs data rates having the above relationship. The estimation is carried out in an autonomous setting in which very little a priori information is assumed. It is done by exploiting an elegant property of the split symbol moments estimator (SSME), which is traditionally used to estimate the signal-to-noise ratio (SNR) of the received signal. By quantizing the assumed symbol-timing error or jitter, we present an all-digital implementation of the SSME which can be used to jointly estimate the data rate, SNR, and jitter. Simulation results presented show that these joint estimation algorithms perform well, even in the low SNR regions typically encountered in the DSN.
Estimated soil ingestion rates for use in risk assessment
LaGoy, P.K.
1987-09-01
Assessing the risks to human health posed by contaminants present in soil requires an estimate of likely soil ingestion rates. In the past, direct measurements of soil ingestion were not available and risk assessors were forced to estimate soil ingestion rates based on observations of mouthing behavior and measurements of soil on hands. Recently, empirical data on soil ingestion rates have become available from two sources. Although preliminary, these data can be used to derive better estimates of soil ingestion rates for use in risk assessments. Estimates of average soil ingestion rates derived in this paper range from 25 to 100 mg/day, depending on the age of the individual at risk. Maximum soil ingestion rates that are unlikely to underestimate exposure range from 100 to 500 mg. A value of 5000 mg/day is considered a reasonable estimate of a maximum single-day exposure for a child with habitual pica. 12 references.
ESTIMATING DIVERSIFICATION RATES: HOW USEFUL ARE DIVERGENCE TIMES?
Wertheim, Joel O.; Sanderson, Michael J.
2010-01-01
The dynamics of species diversification rates are a key component of macroevolutionary patterns. Though not absolutely necessary, the use of divergence times inferred from sequence data has led to development of more powerful methods for inferring diversification rates. However, it is unclear what impact uncertainty in age estimates has on diversification rate inferences. Here we quantify these effects using both Bayesian and frequentist methodology. Through simulation, we demonstrate that adding sequence data results in more precise estimates of internal node ages, but a reasonable approximation of these node ages is often sufficient to approach the theoretical minimum variance in speciation rate estimates. We also find that even crude estimates of divergence times increase the power of tests of diversification rate differences between sister clades. Finally, because Bayesian and frequentist methods provided similar assessments of error, novel Bayesian approaches may provide a useful framework for tests of diversification rates in more complex contexts than are addressed here. PMID:21044059
Asymptotically robust variance estimation for person-time incidence rates.
Scosyrev, Emil
2016-05-01
Person-time incidence rates are frequently used in medical research. However, standard estimation theory for this measure of event occurrence is based on the assumption of independent and identically distributed (iid) exponential event times, which implies that the hazard function remains constant over time. Under this assumption and assuming independent censoring, observed person-time incidence rate is the maximum-likelihood estimator of the constant hazard, and asymptotic variance of the log rate can be estimated consistently by the inverse of the number of events. However, in many practical applications, the assumption of constant hazard is not very plausible. In the present paper, an average rate parameter is defined as the ratio of expected event count to the expected total time at risk. This rate parameter is equal to the hazard function under constant hazard. For inference about the average rate parameter, an asymptotically robust variance estimator of the log rate is proposed. Given some very general conditions, the robust variance estimator is consistent under arbitrary iid event times, and is also consistent or asymptotically conservative when event times are independent but nonidentically distributed. In contrast, the standard maximum-likelihood estimator may become anticonservative under nonconstant hazard, producing confidence intervals with less-than-nominal asymptotic coverage. These results are derived analytically and illustrated with simulations. The two estimators are also compared in five datasets from oncology studies. PMID:26439107
Prolonged decay of molecular rate estimates for metazoan mitochondrial DNA
Ho, Simon Y.W.
2015-01-01
Evolutionary timescales can be estimated from genetic data using the molecular clock, often calibrated by fossil or geological evidence. However, estimates of molecular rates in mitochondrial DNA appear to scale negatively with the age of the clock calibration. Although such a pattern has been observed in a limited range of data sets, it has not been studied on a large scale in metazoans. In addition, there is uncertainty over the temporal extent of the time-dependent pattern in rate estimates. Here we present a meta-analysis of 239 rate estimates from metazoans, representing a range of timescales and taxonomic groups. We found evidence of time-dependent rates in both coding and non-coding mitochondrial markers, in every group of animals that we studied. The negative relationship between the estimated rate and time persisted across a much wider range of calibration times than previously suggested. This indicates that, over long time frames, purifying selection gives way to mutational saturation as the main driver of time-dependent biases in rate estimates. The results of our study stress the importance of accounting for time-dependent biases in estimating mitochondrial rates regardless of the timescale over which they are inferred. PMID:25780773
Günay, Cengiz; Sieling, Fred H; Dharmar, Logesh; Lin, Wei-Hsiang; Wolfram, Verena; Marley, Richard; Baines, Richard A; Prinz, Astrid A
2015-05-01
Studying ion channel currents generated distally from the recording site is difficult because of artifacts caused by poor space clamp and membrane filtering. A computational model can quantify artifact parameters for correction by simulating the currents only if their exact anatomical location is known. We propose that the same artifacts that confound current recordings can help pinpoint the source of those currents by providing a signature of the neuron's morphology. This method can improve the recording quality of currents initiated at the spike initiation zone (SIZ) that are often distal to the soma in invertebrate neurons. Drosophila being a valuable tool for characterizing ion currents, we estimated the SIZ location and quantified artifacts in an identified motoneuron, aCC/MN1-Ib, by constructing a novel multicompartmental model. Initial simulation of the measured biophysical channel properties in an isopotential Hodgkin-Huxley type neuron model partially replicated firing characteristics. Adding a second distal compartment, which contained spike-generating Na+ and K+ currents, was sufficient to simulate aCC's in vivo activity signature. Matching this signature using a reconstructed morphology predicted that the SIZ is on aCC's primary axon, 70 μm after the most distal dendritic branching point. From SIZ to soma, we observed and quantified selective morphological filtering of fast activating currents. Non-inactivating K+ currents are filtered ∼3 times less and despite their large magnitude at the soma they could be as distal as Na+ currents. The peak of transient component (NaT) of the voltage-activated Na+ current is also filtered more than the magnitude of slower persistent component (NaP), which can contribute to seizures. The corrected NaP/NaT ratio explains the previously observed discrepancy when the same channel is expressed in different cells. In summary, we used an in vivo signature to estimate ion channel location and recording artifacts, which
Günay, Cengiz; Sieling, Fred H.; Dharmar, Logesh; Lin, Wei-Hsiang; Wolfram, Verena; Marley, Richard
2015-01-01
Studying ion channel currents generated distally from the recording site is difficult because of artifacts caused by poor space clamp and membrane filtering. A computational model can quantify artifact parameters for correction by simulating the currents only if their exact anatomical location is known. We propose that the same artifacts that confound current recordings can help pinpoint the source of those currents by providing a signature of the neuron’s morphology. This method can improve the recording quality of currents initiated at the spike initiation zone (SIZ) that are often distal to the soma in invertebrate neurons. Drosophila being a valuable tool for characterizing ion currents, we estimated the SIZ location and quantified artifacts in an identified motoneuron, aCC/MN1-Ib, by constructing a novel multicompartmental model. Initial simulation of the measured biophysical channel properties in an isopotential Hodgkin-Huxley type neuron model partially replicated firing characteristics. Adding a second distal compartment, which contained spike-generating Na+ and K+ currents, was sufficient to simulate aCC’s in vivo activity signature. Matching this signature using a reconstructed morphology predicted that the SIZ is on aCC’s primary axon, 70 μm after the most distal dendritic branching point. From SIZ to soma, we observed and quantified selective morphological filtering of fast activating currents. Non-inactivating K+ currents are filtered ∼3 times less and despite their large magnitude at the soma they could be as distal as Na+ currents. The peak of transient component (NaT) of the voltage-activated Na+ current is also filtered more than the magnitude of slower persistent component (NaP), which can contribute to seizures. The corrected NaP/NaT ratio explains the previously observed discrepancy when the same channel is expressed in different cells. In summary, we used an in vivo signature to estimate ion channel location and recording artifacts
Spike Inference from Calcium Imaging Using Sequential Monte Carlo Methods
Vogelstein, Joshua T.; Watson, Brendon O.; Packer, Adam M.; Yuste, Rafael; Jedynak, Bruno; Paninski, Liam
2009-01-01
Abstract As recent advances in calcium sensing technologies facilitate simultaneously imaging action potentials in neuronal populations, complementary analytical tools must also be developed to maximize the utility of this experimental paradigm. Although the observations here are fluorescence movies, the signals of interest—spike trains and/or time varying intracellular calcium concentrations—are hidden. Inferring these hidden signals is often problematic due to noise, nonlinearities, slow imaging rate, and unknown biophysical parameters. We overcome these difficulties by developing sequential Monte Carlo methods (particle filters) based on biophysical models of spiking, calcium dynamics, and fluorescence. We show that even in simple cases, the particle filters outperform the optimal linear (i.e., Wiener) filter, both by obtaining better estimates and by providing error bars. We then relax a number of our model assumptions to incorporate nonlinear saturation of the fluorescence signal, as well external stimulus and spike history dependence (e.g., refractoriness) of the spike trains. Using both simulations and in vitro fluorescence observations, we demonstrate temporal superresolution by inferring when within a frame each spike occurs. Furthermore, the model parameters may be estimated using expectation maximization with only a very limited amount of data (e.g., ∼5–10 s or 5–40 spikes), without the requirement of any simultaneous electrophysiology or imaging experiments. PMID:19619479
FRAGS: estimation of coding sequence substitution rates from fragmentary data
Swart, Estienne C; Hide, Winston A; Seoighe, Cathal
2004-01-01
Background Rates of substitution in protein-coding sequences can provide important insights into evolutionary processes that are of biomedical and theoretical interest. Increased availability of coding sequence data has enabled researchers to estimate more accurately the coding sequence divergence of pairs of organisms. However the use of different data sources, alignment protocols and methods to estimate substitution rates leads to widely varying estimates of key parameters that define the coding sequence divergence of orthologous genes. Although complete genome sequence data are not available for all organisms, fragmentary sequence data can provide accurate estimates of substitution rates provided that an appropriate and consistent methodology is used and that differences in the estimates obtainable from different data sources are taken into account. Results We have developed FRAGS, an application framework that uses existing, freely available software components to construct in-frame alignments and estimate coding substitution rates from fragmentary sequence data. Coding sequence substitution estimates for human and chimpanzee sequences, generated by FRAGS, reveal that methodological differences can give rise to significantly different estimates of important substitution parameters. The estimated substitution rates were also used to infer upper-bounds on the amount of sequencing error in the datasets that we have analysed. Conclusion We have developed a system that performs robust estimation of substitution rates for orthologous sequences from a pair of organisms. Our system can be used when fragmentary genomic or transcript data is available from one of the organisms and the other is a completely sequenced genome within the Ensembl database. As well as estimating substitution statistics our system enables the user to manage and query alignment and substitution data. PMID:15005802
Estimating Rain Rates from Tipping-Bucket Rain Gauge Measurements
NASA Technical Reports Server (NTRS)
Wang, Jianxin; Fisher, Brad L.; Wolff, David B.
2007-01-01
This paper describes the cubic spline based operational system for the generation of the TRMM one-minute rain rate product 2A-56 from Tipping Bucket (TB) gauge measurements. Methodological issues associated with applying the cubic spline to the TB gauge rain rate estimation are closely examined. A simulated TB gauge from a Joss-Waldvogel (JW) disdrometer is employed to evaluate effects of time scales and rain event definitions on errors of the rain rate estimation. The comparison between rain rates measured from the JW disdrometer and those estimated from the simulated TB gauge shows good overall agreement; however, the TB gauge suffers sampling problems, resulting in errors in the rain rate estimation. These errors are very sensitive to the time scale of rain rates. One-minute rain rates suffer substantial errors, especially at low rain rates. When one minute rain rates are averaged to 4-7 minute or longer time scales, the errors dramatically reduce. The rain event duration is very sensitive to the event definition but the event rain total is rather insensitive, provided that the events with less than 1 millimeter rain totals are excluded. Estimated lower rain rates are sensitive to the event definition whereas the higher rates are not. The median relative absolute errors are about 22% and 32% for 1-minute TB rain rates higher and lower than 3 mm per hour, respectively. These errors decrease to 5% and 14% when TB rain rates are used at 7-minute scale. The radar reflectivity-rainrate (Ze-R) distributions drawn from large amount of 7-minute TB rain rates and radar reflectivity data are mostly insensitive to the event definition.
Estimating the exceedance probability of rain rate by logistic regression
NASA Technical Reports Server (NTRS)
Chiu, Long S.; Kedem, Benjamin
1990-01-01
Recent studies have shown that the fraction of an area with rain intensity above a fixed threshold is highly correlated with the area-averaged rain rate. To estimate the fractional rainy area, a logistic regression model, which estimates the conditional probability that rain rate over an area exceeds a fixed threshold given the values of related covariates, is developed. The problem of dependency in the data in the estimation procedure is bypassed by the method of partial likelihood. Analyses of simulated scanning multichannel microwave radiometer and observed electrically scanning microwave radiometer data during the Global Atlantic Tropical Experiment period show that the use of logistic regression in pixel classification is superior to multiple regression in predicting whether rain rate at each pixel exceeds a given threshold, even in the presence of noisy data. The potential of the logistic regression technique in satellite rain rate estimation is discussed.
Inclination Dependence of Estimated Galaxy Masses and Star Formation Rates
NASA Astrophysics Data System (ADS)
Hernandez, Betsy; Maller, Ariyeh; McKernan, Barry; Ford, Saavik
2016-01-01
We examine the inclination dependence of inferred star formation rates and galaxy mass estimates in the Sloan Digital Sky Survey by combining the disk/bulge de-convolved catalog of Simard et al 2011 with stellar mass estimates catalog of Mendel et al 2014 and star formation rates measured from spectra by Brinchmann et al 2004. We know that optical star formation indicators are reddened by dust, but calculated star formation rates and stellar mass estimates should account for this. However, we find that face-on galaxies have a higher calculated average star formation rates than edge-on galaxies. We also find edge-on galaxies have ,on average, slightly smaller but similar estimated masses to face-on galaxies, suggesting that there are issues with the applied dust corrections for both models.
Effect of impactor area on collision rate estimates
Canavan, G.H.
1996-08-01
Analytic and numercial estimates provide an assessment of the effect of impactor area on space debris collision rates, which is sufficiently small and insensitive to parameters of inerest that it could be neglected or corrected.
Estimating the encounter rate variance in distance sampling
Fewster, R.M.; Buckland, S.T.; Burnham, K.P.; Borchers, D.L.; Jupp, P.E.; Laake, J.L.; Thomas, L.
2009-01-01
The dominant source of variance in line transect sampling is usually the encounter rate variance. Systematic survey designs are often used to reduce the true variability among different realizations of the design, but estimating the variance is difficult and estimators typically approximate the variance by treating the design as a simple random sample of lines. We explore the properties of different encounter rate variance estimators under random and systematic designs. We show that a design-based variance estimator improves upon the model-based estimator of Buckland et al. (2001, Introduction to Distance Sampling. Oxford: Oxford University Press, p. 79) when transects are positioned at random. However, if populations exhibit strong spatial trends, both estimators can have substantial positive bias under systematic designs. We show that poststratification is effective in reducing this bias. ?? 2008, The International Biometric Society.
Estimating Meiotic Gene Conversion Rates From Population Genetic Data
Gay, J.; Myers, S.; McVean, G.
2007-01-01
Gene conversion plays an important part in shaping genetic diversity in populations, yet estimating the rate at which it occurs is difficult because of the short lengths of DNA involved. We have developed a new statistical approach to estimating gene conversion rates from genetic variation, by extending an existing model for haplotype data in the presence of crossover events. We show, by simulation, that when the rate of gene conversion events is at least comparable to the rate of crossover events, the method provides a powerful approach to the detection of gene conversion and estimation of its rate. Application of the method to data from the telomeric X chromosome of Drosophila melanogaster, in which crossover activity is suppressed, indicates that gene conversion occurs ∼400 times more often than crossover events. We also extend the method to estimating variable crossover and gene conversion rates and estimate the rate of gene conversion to be ∼1.5 times higher than the crossover rate in a region of human chromosome 1 with known recombination hotspots. PMID:17660532
Estimating survival rates from banding of adult and juvenile birds
Johnson, D.H.
1974-01-01
The restrictive assumptions required by most available methods for estimating survival probabilities render them unsuitable for analyzing real banding data. A model is proposed which allows survival rates and recovery rates to vary with the calendar year, and also allows juveniles to have rates different from adults. In addition to survival rates and recovery rates, the differential vulnerability factors of juveniles relative to adults are estimated. Minimum values of the variances of the estimators are also given. The new procedure is applied to sets of duck and goose data in which reasonably large numbers of adult and juvenile birds were banded. The results are shown to be generally comparable to those procured by other methods, but, in addition, insight into the extent of annual variation is gained. Combining data from adults and juveniles also increases the effective sample size, since the juveniles are assumed to enter the adult age class after surviving their initial year.
Spikes in quantum trajectories
NASA Astrophysics Data System (ADS)
Tilloy, Antoine; Bauer, Michel; Bernard, Denis
2015-11-01
A quantum system subjected to a strong continuous monitoring undergoes quantum jumps. This very-well-known fact hides a neglected subtlety: sharp scale-invariant fluctuations invariably decorate the jump process, even in the limit where the measurement rate is very large. This article is devoted to the quantitative study of these remaining fluctuations, which we call spikes, and to a discussion of their physical status. We start by introducing a classical model where the origin of these fluctuations is more intuitive, and then jump to the quantum realm where their existence is less intuitive. We compute the exact distribution of the spikes for a continuously monitored qubit. We conclude by discussing their physical and operational relevance.
Estimating the normal background rate of species extinction.
De Vos, Jurriaan M; Joppa, Lucas N; Gittleman, John L; Stephens, Patrick R; Pimm, Stuart L
2015-04-01
A key measure of humanity's global impact is by how much it has increased species extinction rates. Familiar statements are that these are 100-1000 times pre-human or background extinction levels. Estimating recent rates is straightforward, but establishing a background rate for comparison is not. Previous researchers chose an approximate benchmark of 1 extinction per million species per year (E/MSY). We explored disparate lines of evidence that suggest a substantially lower estimate. Fossil data yield direct estimates of extinction rates, but they are temporally coarse, mostly limited to marine hard-bodied taxa, and generally involve genera not species. Based on these data, typical background loss is 0.01 genera per million genera per year. Molecular phylogenies are available for more taxa and ecosystems, but it is debated whether they can be used to estimate separately speciation and extinction rates. We selected data to address known concerns and used them to determine median extinction estimates from statistical distributions of probable values for terrestrial plants and animals. We then created simulations to explore effects of violating model assumptions. Finally, we compiled estimates of diversification-the difference between speciation and extinction rates for different taxa. Median estimates of extinction rates ranged from 0.023 to 0.135 E/MSY. Simulation results suggested over- and under-estimation of extinction from individual phylogenies partially canceled each other out when large sets of phylogenies were analyzed. There was no evidence for recent and widespread pre-human overall declines in diversity. This implies that average extinction rates are less than average diversification rates. Median diversification rates were 0.05-0.2 new species per million species per year. On the basis of these results, we concluded that typical rates of background extinction may be closer to 0.1 E/MSY. Thus, current extinction rates are 1,000 times higher than natural
McCormick, Joshua L.; Quist, Michael C.; Schill, Daniel J.
2012-01-01
Roving–roving and roving–access creel surveys are the primary techniques used to obtain information on harvest of Chinook salmon Oncorhynchus tshawytscha in Idaho sport fisheries. Once interviews are conducted using roving–roving or roving–access survey designs, mean catch rate can be estimated with the ratio-of-means (ROM) estimator, the mean-of-ratios (MOR) estimator, or the MOR estimator with exclusion of short-duration (≤0.5 h) trips. Our objective was to examine the relative bias and precision of total catch estimates obtained from use of the two survey designs and three catch rate estimators for Idaho Chinook salmon fisheries. Information on angling populations was obtained by direct visual observation of portions of Chinook salmon fisheries in three Idaho river systems over an 18-d period. Based on data from the angling populations, Monte Carlo simulations were performed to evaluate the properties of the catch rate estimators and survey designs. Among the three estimators, the ROM estimator provided the most accurate and precise estimates of mean catch rate and total catch for both roving–roving and roving–access surveys. On average, the root mean square error of simulated total catch estimates was 1.42 times greater and relative bias was 160.13 times greater for roving–roving surveys than for roving–access surveys. Length-of-stay bias and nonstationary catch rates in roving–roving surveys both appeared to affect catch rate and total catch estimates. Our results suggest that use of the ROM estimator in combination with an estimate of angler effort provided the least biased and most precise estimates of total catch for both survey designs. However, roving–access surveys were more accurate than roving–roving surveys for Chinook salmon fisheries in Idaho.
Estimating divergence dates and substitution rates in the Drosophila phylogeny.
Obbard, Darren J; Maclennan, John; Kim, Kang-Wook; Rambaut, Andrew; O'Grady, Patrick M; Jiggins, Francis M
2012-11-01
An absolute timescale for evolution is essential if we are to associate evolutionary phenomena, such as adaptation or speciation, with potential causes, such as geological activity or climatic change. Timescales in most phylogenetic studies use geologically dated fossils or phylogeographic events as calibration points, but more recently, it has also become possible to use experimentally derived estimates of the mutation rate as a proxy for substitution rates. The large radiation of drosophilid taxa endemic to the Hawaiian islands has provided multiple calibration points for the Drosophila phylogeny, thanks to the "conveyor belt" process by which this archipelago forms and is colonized by species. However, published date estimates for key nodes in the Drosophila phylogeny vary widely, and many are based on simplistic models of colonization and coalescence or on estimates of island age that are not current. In this study, we use new sequence data from seven species of Hawaiian Drosophila to examine a range of explicit coalescent models and estimate substitution rates. We use these rates, along with a published experimentally determined mutation rate, to date key events in drosophilid evolution. Surprisingly, our estimate for the date for the most recent common ancestor of the genus Drosophila based on mutation rate (25-40 Ma) is closer to being compatible with independent fossil-derived dates (20-50 Ma) than are most of the Hawaiian-calibration models and also has smaller uncertainty. We find that Hawaiian-calibrated dates are extremely sensitive to model choice and give rise to point estimates that range between 26 and 192 Ma, depending on the details of the model. Potential problems with the Hawaiian calibration may arise from systematic variation in the molecular clock due to the long generation time of Hawaiian Drosophila compared with other Drosophila and/or uncertainty in linking island formation dates with colonization dates. As either source of error will
Estimating Divergence Dates and Substitution Rates in the Drosophila Phylogeny
Obbard, Darren J.; Maclennan, John; Kim, Kang-Wook; Rambaut, Andrew; O’Grady, Patrick M.; Jiggins, Francis M.
2012-01-01
An absolute timescale for evolution is essential if we are to associate evolutionary phenomena, such as adaptation or speciation, with potential causes, such as geological activity or climatic change. Timescales in most phylogenetic studies use geologically dated fossils or phylogeographic events as calibration points, but more recently, it has also become possible to use experimentally derived estimates of the mutation rate as a proxy for substitution rates. The large radiation of drosophilid taxa endemic to the Hawaiian islands has provided multiple calibration points for the Drosophila phylogeny, thanks to the "conveyor belt" process by which this archipelago forms and is colonized by species. However, published date estimates for key nodes in the Drosophila phylogeny vary widely, and many are based on simplistic models of colonization and coalescence or on estimates of island age that are not current. In this study, we use new sequence data from seven species of Hawaiian Drosophila to examine a range of explicit coalescent models and estimate substitution rates. We use these rates, along with a published experimentally determined mutation rate, to date key events in drosophilid evolution. Surprisingly, our estimate for the date for the most recent common ancestor of the genus Drosophila based on mutation rate (25–40 Ma) is closer to being compatible with independent fossil-derived dates (20–50 Ma) than are most of the Hawaiian-calibration models and also has smaller uncertainty. We find that Hawaiian-calibrated dates are extremely sensitive to model choice and give rise to point estimates that range between 26 and 192 Ma, depending on the details of the model. Potential problems with the Hawaiian calibration may arise from systematic variation in the molecular clock due to the long generation time of Hawaiian Drosophila compared with other Drosophila and/or uncertainty in linking island formation dates with colonization dates. As either source of error will
NASA Astrophysics Data System (ADS)
Granados, Albert; Krupa, Maciej
2015-05-01
In this work we consider a periodically forced generic integrate-and-fire model with a unique attracting equilibrium in the subthreshold dynamics and study the dependence of the firing-rate on the frequency of the drive. In an earlier study we have obtained rigorous results on the bifurcation structure in such systems, with emphasis on the relation between the firing-rate and the rotation number of the existing periodic orbits. In this work we study how these bifurcation structures behave upon variation of the frequency of the input. This allows us to show that the dependence of the firing-rate on frequency of the drive follows a devil's staircase with non-monotonic steps and that there is an optimal response in the whole frequency domain. We also characterize certain bounded frequency windows in which the firing-rate exhibits a bell-shaped envelope with a global maximum.
Unbiased estimation of mutation rates under fluctuating final counts.
Ycart, Bernard; Veziris, Nicolas
2014-01-01
Estimation methods for mutation rates (or probabilities) in Luria-Delbrück fluctuation analysis usually assume that the final number of cells remains constant from one culture to another. We show that this leads to systematically underestimate the mutation rate. Two levels of information on final numbers are considered: either the coefficient of variation has been independently estimated, or the final number of cells in each culture is known. In both cases, unbiased estimation methods are proposed. Their statistical properties are assessed both theoretically and through Monte-Carlo simulation. As an application, the data from two well known fluctuation analysis studies on Mycobacterium tuberculosis are reexamined. PMID:24988217
Estimation of the Dose and Dose Rate Effectiveness Factor
NASA Technical Reports Server (NTRS)
Chappell, L.; Cucinotta, F. A.
2013-01-01
Current models to estimate radiation risk use the Life Span Study (LSS) cohort that received high doses and high dose rates of radiation. Transferring risks from these high dose rates to the low doses and dose rates received by astronauts in space is a source of uncertainty in our risk calculations. The solid cancer models recommended by BEIR VII [1], UNSCEAR [2], and Preston et al [3] is fitted adequately by a linear dose response model, which implies that low doses and dose rates would be estimated the same as high doses and dose rates. However animal and cell experiments imply there should be curvature in the dose response curve for tumor induction. Furthermore animal experiments that directly compare acute to chronic exposures show lower increases in tumor induction than acute exposures. A dose and dose rate effectiveness factor (DDREF) has been estimated and applied to transfer risks from the high doses and dose rates of the LSS cohort to low doses and dose rates such as from missions in space. The BEIR VII committee [1] combined DDREF estimates using the LSS cohort and animal experiments using Bayesian methods for their recommendation for a DDREF value of 1.5 with uncertainty. We reexamined the animal data considered by BEIR VII and included more animal data and human chromosome aberration data to improve the estimate for DDREF. Several experiments chosen by BEIR VII were deemed inappropriate for application to human risk models of solid cancer risk. Animal tumor experiments performed by Ullrich et al [4], Alpen et al [5], and Grahn et al [6] were analyzed to estimate the DDREF. Human chromosome aberration experiments performed on a sample of astronauts within NASA were also available to estimate the DDREF. The LSS cohort results reported by BEIR VII were combined with the new radiobiology results using Bayesian methods.
Sexually violent predators: toward reasonable estimates of recidivism base rates.
Neller, Daniel J; Petris, Giovanni
2013-01-01
The sexual recidivism rate of sex offenders is a controversial issue. Perhaps as controversial is the sexual recidivism rate of the select group of sex offenders who are examined pursuant to sexually violent predator (SVP) statutes. At present, reliable estimates of SVP recidivism are unavailable. We propose that reasonable estimates of SVP recidivism can be reached by considering three available pieces of data: (i) a likely recidivism rate of the general population of sex offenders; (ii) procedures typically followed by jurisdictions that civilly commit sex offenders; and (iii) classification accuracy of procedures. Although sexual recidivism rates vary across jurisdictions, the results of our analyses suggest sex offenders referred for examination pursuant to SVP statutes recidivate at substantially higher rates than typical sex offenders. Our results further suggest that sex offenders recommended for commitment as SVPs recidivate at even greater rates than SVP respondents who are not recommended for commitment. We discuss practice and policy implications of these findings. PMID:23620130
Evaluation and refinement of leak-rate estimation models
Paul, D.D.; Ahmad, J.; Scott, P.M.; Flanigan, L.F.; Wilkowski, G.M. )
1991-04-01
Leak-rate estimation models are important elements in developing a leak-before-break methodology in piping integrity and safety analyses. Existing thermal-hydraulic and crack-opening-area models used in current leak-rate estimations have been incorporated into a single computer code for leak-rate estimation. The code is called SQUIRT, which stands for Seepage Quantification of Upsets In Reactor Tubes. The SQUIRT program has been validated by comparing its thermal-hydraulic predictions with the limited experimental data that have been published on two-phase flow through slits and cracks, and by comparing its crack-opening-area predictions with data from the Degraded Piping Program. In addition, leak-rate experiments were conducted to obtain validation data for a circumferential fatigue crack in a carbon steel pipe girth weld. 56 refs., 30 figs., 4 tabs.
The cooling-rate effect on microwave archeointensity estimates
NASA Astrophysics Data System (ADS)
Poletti, Wilbor; Hartmann, Gelvam A.; Hill, Mimi J.; Biggin, Andrew J.; Trindade, Ricardo I. F.
2013-08-01
microwave (MW) paleointensity data on historical bricks from Northeast Brazil presented a bias toward higher fields when compared to previous cooling-rate corrected double-heating paleointensity estimates; the same relates to the previously reported values for pottery from Southwestern Pacific islands. A simple theoretical approach suggests that the MW bias in both collections is due to a cooling-rate effect on MW estimates. We then experimentally corrected the MW cooling-rate effect on Brazilian fragments, increasing the degree of consistency between the previous and new results (reducing discrepancies from 25% to 8%). Results indicate similar experimental behavior between microwave and thermal procedures despite the different ways in which the energy is transferred into the spin system. Finally, they allow cooling times of less than 90 s to be empirically estimated in most of these MW experiments highlighting the need for systematic cooling-rate corrections to be applied in similar MW paleointensity studies in the future.
Franke, Felix; Quian Quiroga, Rodrigo; Hierlemann, Andreas; Obermayer, Klaus
2015-06-01
Spike sorting, i.e., the separation of the firing activity of different neurons from extracellular measurements, is a crucial but often error-prone step in the analysis of neuronal responses. Usually, three different problems have to be solved: the detection of spikes in the extracellular recordings, the estimation of the number of neurons and their prototypical (template) spike waveforms, and the assignment of individual spikes to those putative neurons. If the template spike waveforms are known, template matching can be used to solve the detection and classification problem. Here, we show that for the colored Gaussian noise case the optimal template matching is given by a form of linear filtering, which can be derived via linear discriminant analysis. This provides a Bayesian interpretation for the well-known matched filter output. Moreover, with this approach it is possible to compute a spike detection threshold analytically. The method can be implemented by a linear filter bank derived from the templates, and can be used for online spike sorting of multielectrode recordings. It may also be applicable to detection and classification problems of transient signals in general. Its application significantly decreases the error rate on two publicly available spike-sorting benchmark data sets in comparison to state-of-the-art template matching procedures. Finally, we explore the possibility to resolve overlapping spikes using the template matching outputs and show that they can be resolved with high accuracy. PMID:25652689
Overestimating Outcome Rates: Statistical Estimation When Reliability Is Suboptimal
Hayward, Rodney A; Heisler, Michele; Adams, John; Dudley, R Adams; Hofer, Timothy P
2007-01-01
Objective To demonstrate how failure to account for measurement error in an outcome (dependent) variable can lead to significant estimation errors and to illustrate ways to recognize and avoid these errors. Data Sources Medical literature and simulation models. Study Design/Data Collection Systematic review of the published and unpublished epidemiological literature on the rate of preventable hospital deaths and statistical simulation of potential estimation errors based on data from these studies. Principal Findings Most estimates of the rate of preventable deaths in U.S. hospitals rely upon classifying cases using one to three physician reviewers (implicit review). Because this method has low to moderate reliability, estimates based on statistical methods that do not account for error in the measurement of a “preventable death” can result in significant overestimation. For example, relying on a majority rule rating with three reviewers per case (reliability ∼0.45 for the average of three reviewers) can result in a 50–100 percent overestimation compared with an estimate based upon a reliably measured outcome (e.g., by using 50 reviewers per case). However, there are statistical methods that account for measurement error that can produce much more accurate estimates of outcome rates without requiring a large number of measurements per case. Conclusion The statistical principles discussed in this case study are critically important whenever one seeks to estimate the proportion of cases belonging to specific categories (such as estimating how many patients have inadequate blood pressure control or identifying high-cost or low-quality physicians). When the true outcome rate is low ( < 20 percent), using an outcome measure that has low-to-moderate reliability will generally result in substantially overestimating the proportion of the population having the outcome unless statistical methods that adjust for measurement error are used. PMID:17610445
Respiratory rate estimation during triage of children in hospitals.
Shah, Syed Ahmar; Fleming, Susannah; Thompson, Matthew; Tarassenko, Lionel
2015-01-01
Accurate assessment of a child's health is critical for appropriate allocation of medical resources and timely delivery of healthcare in Emergency Departments. The accurate measurement of vital signs is a key step in the determination of the severity of illness and respiratory rate is currently the most difficult vital sign to measure accurately. Several previous studies have attempted to extract respiratory rate from photoplethysmogram (PPG) recordings. However, the majority have been conducted in controlled settings using PPG recordings from healthy subjects. In many studies, manual selection of clean sections of PPG recordings was undertaken before assessing the accuracy of the signal processing algorithms developed. Such selection procedures are not appropriate in clinical settings. A major limitation of AR modelling, previously applied to respiratory rate estimation, is an appropriate selection of model order. This study developed a novel algorithm that automatically estimates respiratory rate from a median spectrum constructed applying multiple AR models to processed PPG segments acquired with pulse oximetry using a finger probe. Good-quality sections were identified using a dynamic template-matching technique to assess PPG signal quality. The algorithm was validated on 205 children presenting to the Emergency Department at the John Radcliffe Hospital, Oxford, UK, with reference respiratory rates up to 50 breaths per minute estimated by paediatric nurses. At the time of writing, the authors are not aware of any other study that has validated respiratory rate estimation using data collected from over 200 children in hospitals during routine triage. PMID:26548638
A Spiking Neural Network in sEMG Feature Extraction
Lobov, Sergey; Mironov, Vasiliy; Kastalskiy, Innokentiy; Kazantsev, Victor
2015-01-01
We have developed a novel algorithm for sEMG feature extraction and classification. It is based on a hybrid network composed of spiking and artificial neurons. The spiking neuron layer with mutual inhibition was assigned as feature extractor. We demonstrate that the classification accuracy of the proposed model could reach high values comparable with existing sEMG interface systems. Moreover, the algorithm sensibility for different sEMG collecting systems characteristics was estimated. Results showed rather equal accuracy, despite a significant sampling rate difference. The proposed algorithm was successfully tested for mobile robot control. PMID:26540060
A Spiking Neural Network in sEMG Feature Extraction.
Lobov, Sergey; Mironov, Vasiliy; Kastalskiy, Innokentiy; Kazantsev, Victor
2015-01-01
We have developed a novel algorithm for sEMG feature extraction and classification. It is based on a hybrid network composed of spiking and artificial neurons. The spiking neuron layer with mutual inhibition was assigned as feature extractor. We demonstrate that the classification accuracy of the proposed model could reach high values comparable with existing sEMG interface systems. Moreover, the algorithm sensibility for different sEMG collecting systems characteristics was estimated. Results showed rather equal accuracy, despite a significant sampling rate difference. The proposed algorithm was successfully tested for mobile robot control. PMID:26540060
A new index to estimate precipitation using cloud growing rate
NASA Astrophysics Data System (ADS)
Bergès, Jean Claude; Jobard, Isabelle; Roca, Rémy
2009-04-01
A new index assessing the cloud growing rate is described in this paper. It has been designed to be integrated in rainfall estimation procedures. As the highest precipitation rates occur in growing convective cores, integrating this information should enhance the precipitation estimations. The index computation relies on image processing methods. It is composed of two steps: first a watershed segmentation is applied and then an original heritage process is performed. This second step, which is based on a simple matrix computation, is adapted to the watershed algorithm as it mitigates the over-segmentation artefact. This cloud growing rate index is compared with a cooling index which is usually computed to help in identifying raining cells and it is demonstrated to be more efficient. Moreover a simple integration of this index in a widespread rainfall estimation method leads to an improvement of the diurnal cycle retrieval.
The estimation of galactic cosmic ray penetration and dose rates
NASA Technical Reports Server (NTRS)
Burrell, M. O.; Wright, J. J.
1972-01-01
This study is concerned with approximation methods that can be readily applied to estimate the absorbed dose rate from cosmic rays in rads - tissue or rems inside simple geometries of aluminum. The present work is limited to finding the dose rate at the center of spherical shells or behind plane slabs. The dose rate is calculated at tissue-point detectors or for thin layers of tissue. This study considers cosmic-rays dose rates for both free-space and earth-orbiting missions.
Automating proliferation rate estimation from Ki-67 histology images
NASA Astrophysics Data System (ADS)
Al-Lahham, Heba Z.; Alomari, Raja S.; Hiary, Hazem; Chaudhary, Vipin
2012-03-01
Breast cancer is the second cause of women death and the most diagnosed female cancer in the US. Proliferation rate estimation (PRE) is one of the prognostic indicators that guide the treatment protocols and it is clinically performed from Ki-67 histopathology images. Automating PRE substantially increases the efficiency of the pathologists. Moreover, presenting a deterministic and reproducible proliferation rate value is crucial to reduce inter-observer variability. To that end, we propose a fully automated CAD system for PRE from the Ki-67 histopathology images. This CAD system is based on a model of three steps: image pre-processing, image clustering, and nuclei segmentation and counting that are finally followed by PRE. The first step is based on customized color modification and color-space transformation. Then, image pixels are clustered by K-Means depending on the features extracted from the images derived from the first step. Finally, nuclei are segmented and counted using global thresholding, mathematical morphology and connected component analysis. Our experimental results on fifty Ki-67-stained histopathology images show a significant agreement between our CAD's automated PRE and the gold standard's one, where the latter is an average between two observers' estimates. The Paired T-Test, for the automated and manual estimates, shows ρ = 0.86, 0.45, 0.8 for the brown nuclei count, blue nuclei count, and proliferation rate, respectively. Thus, our proposed CAD system is as reliable as the pathologist estimating the proliferation rate. Yet, its estimate is reproducible.
Magnetometer-Only Attitude and Rate Estimates for Spinning Spacecraft
NASA Technical Reports Server (NTRS)
Challa, M.; Natanson, G.; Ottenstein, N.
2000-01-01
A deterministic algorithm and a Kalman filter for gyroless spacecraft are used independently to estimate the three-axis attitude and rates of rapidly spinning spacecraft using only magnetometer data. In-flight data from the Wide-Field Infrared Explorer (WIRE) during its tumble, and the Fast Auroral Snapshot Explorer (FAST) during its nominal mission mode are used to show that the algorithms can successfully estimate the above in spite of the high rates. Results using simulated data are used to illustrate the importance of accurate and frequent data.
Angular-Rate Estimation using Star Tracker Measurements
NASA Technical Reports Server (NTRS)
Azor, R.; Bar-Itzhack, Itzhack Y.; Deutschmann, Julie K.; Harman, Richard R.
1999-01-01
This paper presents algorithms for estimating the angular-rate vector of satellites using quaternion measurements. Two approaches are compared, one that uses differentiated quaternion measurements to yield coarse rate measurements which are then fed into two different estimators. In the other approach the raw quaternion measurements themselves are fed directly into the two estimators. The two estimators rely on the ability to decompose the non-linear rate dependent part of the rotational dynamics equation of a rigid body into a product of an angular-rate dependent matrix and the angular-rate vector itself. This decomposition, which is not unique, enables the treatment of the nonlinear spacecraft dynamics model as a linear one and, consequently, the application of a Pseudo-Linear Kalman Filter (PSELIKA). It also enables the application of a special Kalman filter which is based on the use of the solution of the State Dependent Algebraic Riccati Equation (SDARE) in order to compute the Kalman gain matrix and thus eliminates the need to propagate and update the filter covariance matrix. The replacement of the elaborate rotational dynamics by a simple first order Markov model is also examined. In this paper a special consideration is given to the problem of delayed quaternion measurements. Two solutions to this problem are suggested and tested. Real Rossi X-Ray Timing Explorer (RXTE) data is used to test these algorithms, and results of these tests are presented.
Angular-Rate Estimation Using Star Tracker Measurements
NASA Technical Reports Server (NTRS)
Azor, R.; Bar-Itzhack, I.; Deutschmann, Julie K.; Harman, Richard R.
1999-01-01
This paper presents algorithms for estimating the angular-rate vector of satellites using quaternion measurements. Two approaches are compared, one that uses differentiated quatemion measurements to yield coarse rate measurements which are then fed into two different estimators. In the other approach the raw quatemion measurements themselves are fed directly into the two estimators. The two estimators rely on the ability to decompose the non-linear rate dependent part of the rotational dynamics equation of a rigid body into a product of an angular-rate dependent matrix and the angular-rate vector itself This decomposition, which is not unique, enables the treatment of the nonlinear spacecraft dynamics model as a linear one and, consequently, the application of a Pseudo-Linear Kalman Filter (PSELIKA). It also enables the application of a special Kalman filter which is based on the use of the solution of the State Dependent Algebraic Riccati Equation (SDARE) in order to compute the Kalman gain matrix and thus eliminates the need to propagate and update the filter covariance matrix. The replacement of the elaborate rotational dynamics by a simple first order Markov model is also examined. In this paper a special consideration is given to the problem of delayed quatemion measurements. Two solutions to this problem are suggested and tested. Real Rossi X-Ray Timing Explorer (RXTE) data is used to test these algorithms, and results of these tests are presented.
Estimating cause-specific mortality rates using recovered carcasses.
Joly, Damien O; Heisey, Dennis M; Samuel, Michael D; Ribic, Christine A; Thomas, Nancy J; Wright, Scott D; Wright, Irene E
2009-01-01
Stranding networks, in which carcasses are recovered and sent to diagnostic laboratories for necropsy and determination of cause of death, have been developed to monitor the health of marine mammal and bird populations. These programs typically accumulate comprehensive, long-term datasets on causes of death that can be used to identify important sources of mortality or changes in mortality patterns that lead to management actions. However, the utility of these data in determining cause-specific mortality rates has not been explored. We present a maximum likelihood-based approach that partitions total mortality rate, estimated by independent sources, into cause-specific mortality rates. We also demonstrate how variance estimates are derived for these rates. We present examples of the method using mortality data for California sea otters (Enhydra lutris nereis) and Florida manatees (Trichechus manatus latirostris). PMID:19204341
Anthropogenic radionuclides for estimating rates of soil redistribution by wind
Technology Transfer Automated Retrieval System (TEKTRAN)
Erosion of soil by wind and water is a degrading process that affects millions of hectares worldwide. Atmospheric testing of nuclear weapons and the resulting fallout of anthropogenic radioisotopes, particularly Cesium 137, has made possible the estimation of mean soil redistribution rates. The pe...
Anthropogenic radioisotopes to estimate rates of soil redistribution by wind
Technology Transfer Automated Retrieval System (TEKTRAN)
Erosion of soil by wind and water is a degrading process that affects millions of hectares worldwide. Atmospheric testing of nuclear weapons and the resulting fallout of anthropogenic radioisotopes, particularly Cesium 137, has made possible the estimation of mean soil redistribution rates. The pe...
Angular-Rate Estimation Using Delayed Quaternion Measurements
NASA Technical Reports Server (NTRS)
Azor, R.; Bar-Itzhack, I. Y.; Harman, R. R.
1999-01-01
This paper presents algorithms for estimating the angular-rate vector of satellites using quaternion measurements. Two approaches are compared one that uses differentiated quaternion measurements to yield coarse rate measurements, which are then fed into two different estimators. In the other approach the raw quaternion measurements themselves are fed directly into the two estimators. The two estimators rely on the ability to decompose the non-linear part of the rotas rotational dynamics equation of a body into a product of an angular-rate dependent matrix and the angular-rate vector itself. This non unique decomposition, enables the treatment of the nonlinear spacecraft (SC) dynamics model as a linear one and, thus, the application of a PseudoLinear Kalman Filter (PSELIKA). It also enables the application of a special Kalman filter which is based on the use of the solution of the State Dependent Algebraic Riccati Equation (SDARE) in order to compute the gain matrix and thus eliminates the need to compute recursively the filter covariance matrix. The replacement of the rotational dynamics by a simple Markov model is also examined. In this paper special consideration is given to the problem of delayed quaternion measurements. Two solutions to this problem are suggested and tested. Real Rossi X-Ray Timing Explorer (RXTE) data is used to test these algorithms, and results are presented.
Quantifying Spike Train Oscillations: Biases, Distortions and Solutions
Matzner, Ayala; Bar-Gad, Izhar
2015-01-01
Estimation of the power spectrum is a common method for identifying oscillatory changes in neuronal activity. However, the stochastic nature of neuronal activity leads to severe biases in the estimation of these oscillations in single unit spike trains. Different biological and experimental factors cause the spike train to differentially reflect its underlying oscillatory rate function. We analyzed the effect of factors, such as the mean firing rate and the recording duration, on the detectability of oscillations and their significance, and tested these theoretical results on experimental data recorded in Parkinsonian non-human primates. The effect of these factors is dramatic, such that in some conditions, the detection of existing oscillations is impossible. Moreover, these biases impede the comparison of oscillations across brain regions, neuronal types, behavioral states and separate recordings with different underlying parameters, and lead inevitably to a gross misinterpretation of experimental results. We introduce a novel objective measure, the "modulation index", which overcomes these biases, and enables reliable detection of oscillations from spike trains and a direct estimation of the oscillation magnitude. The modulation index detects a high percentage of oscillations over a wide range of parameters, compared to classical spectral analysis methods, and enables an unbiased comparison between spike trains recorded from different neurons and using different experimental protocols. PMID:25909328
Quantifying spike train oscillations: biases, distortions and solutions.
Matzner, Ayala; Bar-Gad, Izhar
2015-04-01
Estimation of the power spectrum is a common method for identifying oscillatory changes in neuronal activity. However, the stochastic nature of neuronal activity leads to severe biases in the estimation of these oscillations in single unit spike trains. Different biological and experimental factors cause the spike train to differentially reflect its underlying oscillatory rate function. We analyzed the effect of factors, such as the mean firing rate and the recording duration, on the detectability of oscillations and their significance, and tested these theoretical results on experimental data recorded in Parkinsonian non-human primates. The effect of these factors is dramatic, such that in some conditions, the detection of existing oscillations is impossible. Moreover, these biases impede the comparison of oscillations across brain regions, neuronal types, behavioral states and separate recordings with different underlying parameters, and lead inevitably to a gross misinterpretation of experimental results. We introduce a novel objective measure, the "modulation index", which overcomes these biases, and enables reliable detection of oscillations from spike trains and a direct estimation of the oscillation magnitude. The modulation index detects a high percentage of oscillations over a wide range of parameters, compared to classical spectral analysis methods, and enables an unbiased comparison between spike trains recorded from different neurons and using different experimental protocols. PMID:25909328
A Pulse Rate Estimation Algorithm Using PPG and Smartphone Camera.
Siddiqui, Sarah Ali; Zhang, Yuan; Feng, Zhiquan; Kos, Anton
2016-05-01
The ubiquitous use and advancement in built-in smartphone sensors and the development in big data processing have been beneficial in several fields including healthcare. Among the basic vitals monitoring, pulse rate monitoring is the most important healthcare necessity. A multimedia video stream data acquired by built-in smartphone camera can be used to estimate it. In this paper, an algorithm that uses only smartphone camera as a sensor to estimate pulse rate using PhotoPlethysmograph (PPG) signals is proposed. The results obtained by the proposed algorithm are compared with the actual pulse rate and the maximum error found is 3 beats per minute. The standard deviation in percentage error and percentage accuracy is found to be 0.68 % whereas the average percentage error and percentage accuracy is found to be 1.98 % and 98.02 % respectively. PMID:27067432
Estimation of Eruption Source Parameters from Plume Growth Rate
NASA Astrophysics Data System (ADS)
Pouget, Solene; Bursik, Marcus; Webley, Peter; Dehn, Jon; Pavalonis, Michael; Singh, Tarunraj; Singla, Puneet; Patra, Abani; Pitman, Bruce; Stefanescu, Ramona; Madankan, Reza; Morton, Donald; Jones, Matthew
2013-04-01
The eruption of Eyjafjallajokull, Iceland in April and May, 2010, brought to light the hazards of airborne volcanic ash and the importance of Volcanic Ash Transport and Dispersion models (VATD) to estimate the concentration of ash with time. These models require Eruption Source Parameters (ESP) as input, which typically include information about the plume height, the mass eruption rate, the duration of the eruption and the particle size distribution. However much of the time these ESP are unknown or poorly known a priori. We show that the mass eruption rate can be estimated from the downwind plume or umbrella cloud growth rate. A simple version of the continuity equation can be applied to the growth of either an umbrella cloud or the downwind plume. The continuity equation coupled with the momentum equation using only inertial and gravitational terms provides another model. Numerical modeling or scaling relationships can be used, as necessary, to provide values for unknown or unavailable parameters. Use of these models applied to data on plume geometry provided by satellite imagery allows for direct estimation of plume volumetric and mass growth with time. To test our methodology, we compared our results with five well-studied and well-characterized historical eruptions: Mount St. Helens, 1980; Pinatubo, 1991, Redoubt, 1990; Hekla, 2000 and Eyjafjallajokull, 2010. These tests show that the methodologies yield results comparable to or better than currently accepted methodologies of ESP estimation. We then applied the methodology to umbrella clouds produced by the eruptions of Okmok, 12 July 2008, and Sarychev Peak, 12 June 2009, and to the downwind plume produced by the eruptions of Hekla, 2000; Kliuchevsko'i, 1 October 1994; Kasatochi 7-8 August 2008 and Bezymianny, 1 September 2012. The new methods allow a fast, remote assessment of the mass eruption rate, even for remote volcanoes. They thus provide an additional path to estimation of the ESP and the forecasting
Estimates of Biogenic Methane Production Rates in Deep Marine Sediments
NASA Astrophysics Data System (ADS)
Colwell, F. S.; Boyd, S.; Delwiche, M. E.; Reed, D. W.
2004-12-01
Much of the methane in natural gas hydrates in marine sediments is made by methanogens. Current models used to predict hydrate distribution and concentration in these sediments require estimates of microbial methane production rates. However, accurate estimates are difficult to achieve because of the bias introduced by sampling and because methanogen activities in these sediments are low and not easily detected. To derive useful methane production rates for marine sediments we have measured the methanogen biomass in samples taken from different depths in Hydrate Ridge (HR) sediments off the coast of Oregon and, separately, the minimal rates of activity for a methanogen in a laboratory reactor. For methanogen biomass, we used a polymerase chain reaction assay in real time to target the methanogen-specific mcr gene. Using this method we found that a majority of the samples collected from boreholes at HR show no evidence of methanogens (detection limit: less than 100 methanogens per g of sediment). Most of the samples with detectable numbers of methanogens were from shallow sediments (less than 10 meters below seafloor [mbsf]) although a few samples with apparently high numbers of methanogens (greater than 10,000 methanogens per g) were from as deep as 230 mbsf and were associated with notable geological features (e.g., the bottom-simulating reflector and an ash-bearing zone with high fluid movement). Laboratory studies with Methanoculleus submarinus (isolated from a hydrate zone at the Nankai Trough) maintained in a biomass recycle reactor showed that when this methanogen is merely surviving, as is likely the case in deep marine sediments, it produces approximately 0.06 fmol methane per cell per day. This is far lower than rates reported for methanogens in other environments. By combining this estimate of specific methanogenic rates and an extrapolation from the numbers of methanogens at selected depths in the sediment column at HR sites we have derived a maximum
Respiratory rate estimation using respiratory sinus arrhythmia from photoplethysmography.
Karlen, Walter; Brouse, Christopher J; Cooke, Erin; Ansermino, J Mark; Dumont, Guy A
2011-01-01
Respiratory rate (RR) is an important measurement for ambulatory care and there is high interest in its detection using unobtrusive mobile devices. For this study, we investigated the estimation of RR from a photoplethysmography (PPG) signal that originated from a pulse oximeter sensor and had a sub-optimal sampling rate. We explored the possibility of estimating RR by extracting respiratory sinus arrhythmia (RSA) from the PPG-derived heart rate variability (HRV) measurement using real-time algorithms. Data from 29 children and 13 adults undergoing general anesthesia were analyzed. We compared the RSA power derived from electrocardiography (ECG) with PPG at the reference RR derived from capnography. The power of the PPG was significantly higher than that of the ECG (182.42 ± 36.75 dB vs. 162.30 ± 43.66 dB). Further, the mean RR error for PPG was lower than ECG. Both PPG and ECG RR estimation techniques were more powerful and reliable in cases of spontaneous ventilation than when pressure controlled ventilation was used. The analysis of cases containing artifacts in the PPG revealed a significant increase in RR error, a trend that was less pronounced for controlled ventilation. These results indicate that the estimation of RR from the sub-optimally sampled PPG signal is possible and more reliable than from the ECG. PMID:22254531
Banerjee, Arunava
2016-05-01
We derive a synaptic weight update rule for learning temporally precise spike train-to-spike train transformations in multilayer feedforward networks of spiking neurons. The framework, aimed at seamlessly generalizing error backpropagation to the deterministic spiking neuron setting, is based strictly on spike timing and avoids invoking concepts pertaining to spike rates or probabilistic models of spiking. The derivation is founded on two innovations. First, an error functional is proposed that compares the spike train emitted by the output neuron of the network to the desired spike train by way of their putative impact on a virtual postsynaptic neuron. This formulation sidesteps the need for spike alignment and leads to closed-form solutions for all quantities of interest. Second, virtual assignment of weights to spikes rather than synapses enables a perturbation analysis of individual spike times and synaptic weights of the output, as well as all intermediate neurons in the network, which yields the gradients of the error functional with respect to the said entities. Learning proceeds via a gradient descent mechanism that leverages these quantities. Simulation experiments demonstrate the efficacy of the proposed learning framework. The experiments also highlight asymmetries between synapses on excitatory and inhibitory neurons. PMID:26942750
The electromagnetic spike solutions
NASA Astrophysics Data System (ADS)
Nungesser, Ernesto; Lim, Woei Chet
2013-12-01
The aim of this paper is to use the existing relation between polarized electromagnetic Gowdy spacetimes and vacuum Gowdy spacetimes to find explicit solutions for electromagnetic spikes by a procedure which has been developed by one of the authors for gravitational spikes. We present new inhomogeneous solutions which we call the EME and MEM electromagnetic spike solutions.
Estimating digital information throughput rates for radiology networks. A model.
Cox, G G; Templeton, A W; Anderson, W H; Cook, L T; Hensley, K S; Dwyer, S J
1986-02-01
The design and implementation of a digital radiology image management system requires the definition, evaluation, and comparison of appropriate measures of system performance. The mean throughput rate is an important measure of the actual performance of a finished system. The mean throughput rate identifies the transmission of digital information either in bits/second or tasks/second. It is dependent on software, database management, equipment interface designs, number of users and display stations, and communications media. The mean throughput rate can document resource allocation bottlenecks within a given system. A model for estimating the mean throughput rate and its application in helping us design our radiology digital image networks is described. PMID:3957590
Suicide rates, national intelligence estimates, and differential K theory.
Voracek, Martin
2009-12-01
In a nation sample of 75 countries around the world, higher suicide rates of the total male, and female population corresponded to higher levels on the superordinate K factor from differential K theory, thought to reflect a set of mutually interrelated life history and reproductive strategy traits. Countries ranking high on suicide rates concurrently ranked high on national intelligence estimates, longevity, and affluence, whilst low on rates of births, infant mortality, HIV/AIDS, and crimes (rape, serious assault, and homicide). These findings integrate previously reported positive population-level associations between suicide rates and cognitive ability variables into the conceptual space of differential K theory. The propensity toward suicidal behavior is a positive correlate of the K superfactor. PMID:20178273
Precise estimates of mutation rate and spectrum in yeast
Zhu, Yuan O.; Siegal, Mark L.; Hall, David W.; Petrov, Dmitri A.
2014-01-01
Mutation is the ultimate source of genetic variation. The most direct and unbiased method of studying spontaneous mutations is via mutation accumulation (MA) lines. Until recently, MA experiments were limited by the cost of sequencing and thus provided us with small numbers of mutational events and therefore imprecise estimates of rates and patterns of mutation. We used whole-genome sequencing to identify nearly 1,000 spontaneous mutation events accumulated over ∼311,000 generations in 145 diploid MA lines of the budding yeast Saccharomyces cerevisiae. MA experiments are usually assumed to have negligible levels of selection, but even mild selection will remove strongly deleterious events. We take advantage of such patterns of selection and show that mutation classes such as indels and aneuploidies (especially monosomies) are proportionately much more likely to contribute mutations of large effect. We also provide conservative estimates of indel, aneuploidy, environment-dependent dominant lethal, and recessive lethal mutation rates. To our knowledge, for the first time in yeast MA data, we identified a sufficiently large number of single-nucleotide mutations to measure context-dependent mutation rates and were able to (i) confirm strong AT bias of mutation in yeast driven by high rate of mutations from C/G to T/A and (ii) detect a higher rate of mutation at C/G nucleotides in two specific contexts consistent with cytosine methylation in S. cerevisiae. PMID:24847077
Robust efficient estimation of heart rate pulse from video
Xu, Shuchang; Sun, Lingyun; Rohde, Gustavo Kunde
2014-01-01
We describe a simple but robust algorithm for estimating the heart rate pulse from video sequences containing human skin in real time. Based on a model of light interaction with human skin, we define the change of blood concentration due to arterial pulsation as a pixel quotient in log space, and successfully use the derived signal for computing the pulse heart rate. Various experiments with different cameras, different illumination condition, and different skin locations were conducted to demonstrate the effectiveness and robustness of the proposed algorithm. Examples computed with normal illumination show the algorithm is comparable with pulse oximeter devices both in accuracy and sensitivity. PMID:24761294
Estimating rates of debris flow entrainment from ground vibrations
NASA Astrophysics Data System (ADS)
Kean, J. W.; Coe, J. A.; Coviello, V.; Smith, J. B.; McCoy, S. W.; Arattano, M.
2015-08-01
Debris flows generate seismic waves as they travel downslope and can become more dangerous as they entrain sediment along their path. We present field observations that show a systematic relation between the magnitude of seismic waves and the amount of erodible sediment beneath the flow. Specifically, we observe that a debris flow traveling along a channel filled initially with sediment 0.34 m thick generates about 2 orders of magnitude less spectral power than a similar-sized flow over the same channel without sediment fill. We adapt a model from fluvial seismology to explain this observation and then invert it to estimate the level of bed sediment (and rate of entrainment) beneath a passing series of surges. Our estimates compare favorably with previous direct measurements of entrainment rates at the site, suggesting the approach may be a new indirect way to obtain rare field constraints needed to test models of debris flow entrainment.
Improved Versions of Common Estimators of the Recombination Rate.
Gärtner, Kerstin; Futschik, Andreas
2016-09-01
The scaled recombination parameter [Formula: see text] is one of the key parameters, turning up frequently in population genetic models. Accurate estimates of [Formula: see text] are difficult to obtain, as recombination events do not always leave traces in the data. One of the most widely used approaches is composite likelihood. Here, we show that popular implementations of composite likelihood estimators can often be uniformly improved by optimizing the trade-off between bias and variance. The amount of possible improvement depends on parameters such as the sequence length, the sample size, and the mutation rate, and it can be considerable in some cases. It turns out that approximate Bayesian computation, with composite likelihood as a summary statistic, also leads to improved estimates, but now in terms of the posterior risk. Finally, we demonstrate a practical application on real data from Drosophila. PMID:27409412
Probabilistic precipitation rate estimates with ground-based radar networks
NASA Astrophysics Data System (ADS)
Kirstetter, Pierre-Emmanuel; Gourley, Jonathan J.; Hong, Yang; Zhang, Jian; Moazamigoodarzi, Saber; Langston, Carrie; Arthur, Ami
2015-03-01
The uncertainty structure of radar quantitative precipitation estimation (QPE) is largely unknown at fine spatiotemporal scales near the radar measurement scale. By using the WSR-88D radar network and gauge data sets across the conterminous US, an investigation of this subject has been carried out within the framework of the NOAA/NSSL ground radar-based Multi-Radar Multi-Sensor (MRMS) QPE system. A new method is proposed and called PRORATE for probabilistic QPE using radar observations of rate and typology estimates. Probability distributions of precipitation rates are computed instead of deterministic values using a model quantifying the relation between radar reflectivity and the corresponding "true" precipitation. The model acknowledges the uncertainty arising from many factors operative at the radar measurement scale and from the correction algorithm. Ensembles of reflectivity-to-precipitation rate relationships accounting explicitly for precipitation typology were derived at a 5 min/1 km scale. This approach conditions probabilistic quantitative precipitation estimates (PQPE) on the precipitation rate and type. The model components were estimated on the basis of a 1 year long data sample over the CONUS. This PQPE model provides the basis for precipitation probability maps and the generation of radar precipitation ensembles. Maps of the precipitation exceedance probability for specific thresholds (e.g., precipitation return periods) are computed. Precipitation probability maps are accumulated to the hourly time scale and compare favorably to the deterministic QPE. As an essential property of precipitation, the impact of the temporal correlation on the hourly accumulation is examined. This approach to PQPE can readily apply to other systems including space-based passive and active sensor algorithms.
bz-rates: A Web Tool to Estimate Mutation Rates from Fluctuation Analysis.
Gillet-Markowska, Alexandre; Louvel, Guillaume; Fischer, Gilles
2015-11-01
Fluctuation analysis is the standard experimental method for measuring mutation rates in micro-organisms. The appearance of mutants is classically described by a Luria-Delbrück distribution composed of two parameters: the number of mutations per culture (m) and the differential growth rate between mutant and wild-type cells (b). A precise estimation of these two parameters is a prerequisite to the calculation of the mutation rate. Here, we developed bz-rates, a Web tool to calculate mutation rates that provides three useful advances over existing Web tools. First, it allows taking into account b, the differential growth rate between mutant and wild-type cells, in the estimation of m with the generating function. Second, bz-rates allows the user to take into account a deviation from the Luria-Delbrück distribution called z, the plating efficiency, in the estimation of m. Finally, the Web site provides a graphical visualization of the goodness-of-fit between the experimental data and the model. bz-rates is accessible at http://www.lcqb.upmc.fr/bzrates. PMID:26338660
bz-rates: A Web Tool to Estimate Mutation Rates from Fluctuation Analysis
Gillet-Markowska, Alexandre; Louvel, Guillaume; Fischer, Gilles
2015-01-01
Fluctuation analysis is the standard experimental method for measuring mutation rates in micro-organisms. The appearance of mutants is classically described by a Luria-Delbrück distribution composed of two parameters: the number of mutations per culture (m) and the differential growth rate between mutant and wild-type cells (b). A precise estimation of these two parameters is a prerequisite to the calculation of the mutation rate. Here, we developed bz-rates, a Web tool to calculate mutation rates that provides three useful advances over existing Web tools. First, it allows taking into account b, the differential growth rate between mutant and wild-type cells, in the estimation of m with the generating function. Second, bz-rates allows the user to take into account a deviation from the Luria-Delbrück distribution called z, the plating efficiency, in the estimation of m. Finally, the Web site provides a graphical visualization of the goodness-of-fit between the experimental data and the model. bz-rates is accessible at http://www.lcqb.upmc.fr/bzrates. PMID:26338660
Estimated diffusion rates of inorganic gases from southeastern Colorado reservoirs
Nelson, J.S.; Simmons, E.C. )
1991-08-01
Helium, argon, and nitrogen are small, chemically unreactive molecules with relatively large effective diffusion coefficients compared to most hydrocarbons. If these gases have existed in gas fields for even the shortest geologic time spans, steady-state diffusion must be at least approximated, and the diffusional flux of these gases through a reservoir cap rock may be estimated using Fick's First Law of Diffusion. Diffusional loss represents a minimum loss rate since mass transfer along fractures and faults would be faster. Under a steady-state condition, the rate of diffusional loss most be balanced by an equal influx of the gas into the reservoir. Using a natural gas field's estimated reserves, natural gas composition, area, and the estimated flux of a given gas through the field's cap rock, the turnover time of the gas is estimated. Southeastern Colorado gas fields producing from the Morrow Formation often contain anomalously high concentrations of nitrogen (to 70%), helium (to 5%) and yield turnover times for these gases of generally less than 100,000 years. Unless the N{sub 2}, He, and Ar were emplaced within the last 100,000 years, there must be a continuing large flux of gas into these fields to balance the diffusional loss. The large fluxes of inorganic gases required to maintain their concentrations in natural gases raises questions about the age and longevity of gas fields. Extension of these calculations to light hydrocarbons implies that catagenesis is a more recent and ongoing process than is often believed.
Robust estimation of fetal heart rate from US Doppler signals
NASA Astrophysics Data System (ADS)
Voicu, Iulian; Girault, Jean-Marc; Roussel, Catherine; Decock, Aliette; Kouame, Denis
2010-01-01
Introduction: In utero, Monitoring of fetal wellbeing or suffering is today an open challenge, due to the high number of clinical parameters to be considered. An automatic monitoring of fetal activity, dedicated for quantifying fetal wellbeing, becomes necessary. For this purpose and in a view to supply an alternative for the Manning test, we used an ultrasound multitransducer multigate Doppler system. One important issue (and first step in our investigation) is the accurate estimation of fetal heart rate (FHR). An estimation of the FHR is obtained by evaluating the autocorrelation function of the Doppler signals for ills and healthiness foetus. However, this estimator is not enough robust since about 20% of FHR are not detected in comparison to a reference system. These non detections are principally due to the fact that the Doppler signal generated by the fetal moving is strongly disturbed by the presence of others several Doppler sources (mother' s moving, pseudo breathing, etc.). By modifying the existing method (autocorrelation method) and by proposing new time and frequency estimators used in the audio' s domain, we reduce to 5% the probability of non-detection of the fetal heart rate. These results are really encouraging and they enable us to plan the use of automatic classification techniques in order to discriminate between healthy and in suffering foetus.
Estimating Divergence Times and Substitution Rates in Rhizobia.
Chriki-Adeeb, Rim; Chriki, Ali
2016-01-01
Accurate estimation of divergence times of soil bacteria that form nitrogen-fixing associations with most leguminous plants is challenging because of a limited fossil record and complexities associated with molecular clocks and phylogenetic diversity of root nodule bacteria, collectively called rhizobia. To overcome the lack of fossil record in bacteria, divergence times of host legumes were used to calibrate molecular clocks and perform phylogenetic analyses in rhizobia. The 16S rRNA gene and intergenic spacer region remain among the favored molecular markers to reconstruct the timescale of rhizobia. We evaluate the performance of the random local clock model and the classical uncorrelated lognormal relaxed clock model, in combination with four tree models (coalescent constant size, birth-death, birth-death incomplete sampling, and Yule processes) on rhizobial divergence time estimates. Bayes factor tests based on the marginal likelihoods estimated from the stepping-stone sampling analyses strongly favored the random local clock model in combination with Yule process. Our results on the divergence time estimation from 16S rRNA gene and intergenic spacer region sequences are compatible with age estimates based on the conserved core genes but significantly older than those obtained from symbiotic genes, such as nodIJ genes. This difference may be due to the accelerated evolutionary rates of symbiotic genes compared to those of other genomic regions not directly implicated in nodulation processes. PMID:27168719
Estimating Divergence Times and Substitution Rates in Rhizobia
Chriki-Adeeb, Rim; Chriki, Ali
2016-01-01
Accurate estimation of divergence times of soil bacteria that form nitrogen-fixing associations with most leguminous plants is challenging because of a limited fossil record and complexities associated with molecular clocks and phylogenetic diversity of root nodule bacteria, collectively called rhizobia. To overcome the lack of fossil record in bacteria, divergence times of host legumes were used to calibrate molecular clocks and perform phylogenetic analyses in rhizobia. The 16S rRNA gene and intergenic spacer region remain among the favored molecular markers to reconstruct the timescale of rhizobia. We evaluate the performance of the random local clock model and the classical uncorrelated lognormal relaxed clock model, in combination with four tree models (coalescent constant size, birth–death, birth–death incomplete sampling, and Yule processes) on rhizobial divergence time estimates. Bayes factor tests based on the marginal likelihoods estimated from the stepping-stone sampling analyses strongly favored the random local clock model in combination with Yule process. Our results on the divergence time estimation from 16S rRNA gene and intergenic spacer region sequences are compatible with age estimates based on the conserved core genes but significantly older than those obtained from symbiotic genes, such as nodIJ genes. This difference may be due to the accelerated evolutionary rates of symbiotic genes compared to those of other genomic regions not directly implicated in nodulation processes. PMID:27168719
Rotzoll, K.; El-Kadi, A. I.; Gingerich, S.B.
2007-01-01
In recent years the ground-water demand of the population of the island of Maui, Hawaii, has significantly increased. To ensure prudent management of the ground-water resources, an improved understanding of ground-water flow systems is needed. At present, large-scale estimations of aquifer properties are lacking for Maui. Seven analytical methods using constant-rate and variable-rate withdrawals for single wells provide an estimate of hydraulic conductivity and transmissivity for 103 wells in central Maui. Methods based on constant-rate tests, although not widely used on Maui, offer reasonable estimates. Step-drawdown tests, which are more abundantly used than other tests, provide similar estimates as constant-rate tests. A numerical model validates the suitability of analytical solutions for step-drawdown tests and additionally provides an estimate of storage parameters. The results show that hydraulic conductivity is log-normally distributed and that for dike-free volcanic rocks it ranges over several orders of magnitude from 1 to 2,500 m/d. The arithmetic mean, geometric mean, and median values of hydraulic conductivity are respectively 520, 280, and 370 m/d for basalt and 80, 50, and 30 m/d for sediment. A geostatistical approach using ordinary kriging yields a prediction of hydraulic conductivity on a larger scale. Overall, the results are in agreement with values published for other Hawaiian islands. ?? 2007 American Water Resources Association.
Ancient hyaenas highlight the old problem of estimating evolutionary rates.
Shapiro, Beth; Ho, Simon Y W
2014-02-01
Phylogenetic analyses of ancient DNA data can provide a timeline for evolutionary change even in the absence of fossils. The power to infer the evolutionary rate is, however, highly dependent on the number and age of samples, the information content of the sequence data and the demographic history of the sampled population. In this issue of Molecular Ecology, Sheng et al. (2014) analysed mitochondrial DNA sequences isolated from a combination of ancient and present-day hyaenas, including three Pleistocene samples from China. Using an evolutionary rate inferred from the ages of the ancient sequences, they recalibrated the timing of hyaena diversification and suggest a much more recent evolutionary history than was believed previously. Their results highlight the importance of accurately estimating the evolutionary rate when inferring timescales of geographical and evolutionary diversification. PMID:24450980
Can we estimate bacterial growth rates from ribosomal RNA content?
Kemp, P.F.
1995-12-31
Several studies have demonstrated a strong relationship between the quantity of RNA in bacterial cells and their growth rate under laboratory conditions. It may be possible to use this relationship to provide information on the activity of natural bacterial communities, and in particular on growth rate. However, if this approach is to provide reliably interpretable information, the relationship between RNA content and growth rate must be well-understood. In particular, a requisite of such applications is that the relationship must be universal among bacteria, or alternately that the relationship can be determined and measured for specific bacterial taxa. The RNA-growth rate relationship has not been used to evaluate bacterial growth in field studies, although RNA content has been measured in single cells and in bulk extracts of field samples taken from coastal environments. These measurements have been treated as probable indicators of bacterial activity, but have not yet been interpreted as estimators of growth rate. The primary obstacle to such interpretations is a lack of information on biological and environmental factors that affect the RNA-growth rate relationship. In this paper, the available data on the RNA-growth rate relationship in bacteria will be reviewed, including hypotheses regarding the regulation of RNA synthesis and degradation as a function of growth rate and environmental factors; i.e. the basic mechanisms for maintaining RNA content in proportion to growth rate. An assessment of the published laboratory and field data, the current status of this research area, and some of the remaining questions will be presented.
Redefinition and global estimation of basal ecosystem respiration rate
Yuan, W.; Luo, Y.; Li, X.; Liu, S.; Yu, G.; Zhou, T.; Bahn, M.; Black, A.; Desai, A.R.; Cescatti, A.; Marcolla, B.; Jacobs, C.; Chen, J.; Aurela, M.; Bernhofer, C.; Gielen, B.; Bohrer, G.; Cook, D.R.; Dragoni, D.; Dunn, A.L.; Gianelle, D.; Grnwald, T.; Ibrom, A.; Leclerc, M.Y.; Lindroth, A.; Liu, H.; Marchesini, L.B.; Montagnani, L.; Pita, G.; Rodeghiero, M.; Rodrigues, A.; Starr, G.; Stoy, P.C.
2011-01-01
Basal ecosystem respiration rate (BR), the ecosystem respiration rate at a given temperature, is a common and important parameter in empirical models for quantifying ecosystem respiration (ER) globally. Numerous studies have indicated that BR varies in space. However, many empirical ER models still use a global constant BR largely due to the lack of a functional description for BR. In this study, we redefined BR to be ecosystem respiration rate at the mean annual temperature. To test the validity of this concept, we conducted a synthesis analysis using 276 site-years of eddy covariance data, from 79 research sites located at latitudes ranging from ???3S to ???70N. Results showed that mean annual ER rate closely matches ER rate at mean annual temperature. Incorporation of site-specific BR into global ER model substantially improved simulated ER compared to an invariant BR at all sites. These results confirm that ER at the mean annual temperature can be considered as BR in empirical models. A strong correlation was found between the mean annual ER and mean annual gross primary production (GPP). Consequently, GPP, which is typically more accurately modeled, can be used to estimate BR. A light use efficiency GPP model (i.e., EC-LUE) was applied to estimate global GPP, BR and ER with input data from MERRA (Modern Era Retrospective-Analysis for Research and Applications) and MODIS (Moderate resolution Imaging Spectroradiometer). The global ER was 103 Pg C yr -1, with the highest respiration rate over tropical forests and the lowest value in dry and high-latitude areas. Copyright 2011 by the American Geophysical Union.
Estimation of evapotranspiration rate in irrigated lands using stable isotopes
NASA Astrophysics Data System (ADS)
Umirzakov, Gulomjon; Windhorst, David; Forkutsa, Irina; Brauer, Lutz; Frede, Hans-Georg
2013-04-01
Agriculture in the Aral Sea basin is the main consumer of water resources and due to the current agricultural management practices inefficient water usage causes huge losses of freshwater resources. There is huge potential to save water resources in order to reach a more efficient water use in irrigated areas. Therefore, research is required to reveal the mechanisms of hydrological fluxes in irrigated areas. This paper focuses on estimation of evapotranspiration which is one of the crucial components in the water balance of irrigated lands. Our main objective is to estimate the rate of evapotranspiration on irrigated lands and partitioning of evaporation into transpiration using stable isotopes measurements. Experiments has done in 2 different soil types (sandy and sandy loam) irrigated areas in Ferghana Valley (Uzbekistan). Soil samples were collected during the vegetation period. The soil water from these samples was extracted via a cryogenic extraction method and analyzed for the isotopic ratio of the water isotopes (2H and 18O) based on a laser spectroscopy method (DLT 100, Los Gatos USA). Evapotranspiration rates were estimated with Isotope Mass Balance method. The results of evapotranspiration obtained using isotope mass balance method is compared with the results of Catchment Modeling Framework -1D model results which has done in the same area and the same time.
Estimation of glomerular filtration rate in cynomolgus monkeys (Macaca fascicularis).
Iwama, Ryosuke; Sato, Tsubasa; Sakurai, Ken; Takasuna, Kiyoshi; Ichijo, Toshihiro; Furuhama, Kazuhisa; Satoh, Hiroshi
2014-10-01
To estimate the glomerular filtration rate (GFR) in cynomolgus monkeys (Macaca fascicularis), a three-blood-sample method using iodixanol was assessed in comparison with the conventional multisample strategy using inulin. Iodixanol and inulin were coadministered intravenously 40 mg I/kg and 50 mg/kg, respectively, to male monkeys, followed by blood collection 60, 90 and 120 min later. A close correlation (r=0.96) was noted between the GFR values estimated by both methods. In clinically healthy monkeys, the basal values were determined to be 3.06 ± 0.50 ml/min/kg. This is the first report, suggesting that serum clearance of iodixanol is a ready-to-use tool for a screening the GFR in monkeys, although it is necessary to perform a more longitudinal study using animals with reduced renal function. PMID:24998395
Estimating Fault Slip Rates: Four Ways to Evaluate Differences Between GPS and Geologic Rates
NASA Astrophysics Data System (ADS)
Thatcher, W.
2008-12-01
Block modeling of GPS velocity fields worldwide is providing hundreds of new decadal fault slip rate estimates that can be compared with independent Holocene (10 ka) to late Quaternary (125 ka) rates obtained by geological methods. A compilation of over 40 available GPS/geologic comparisons shows general agreement but a subset of apparently significant outliers. Some of these outliers have been discussed previously and attributed either to a temporal change in slip rate or systematic error in one of the estimates. I suggest 4 criteria for assessing the differing rates. First: Is there even-handed evaluation of random and systematic errors? 'Random error' is sometimes subjectively estimated and its statistical properties may be unknown or idealized. Differences between equally likely block models introduces a systematic error into GPS rate estimates that is difficult to assess and seldom discussed. Difficulties in constraining the true initiation date of offset of geomorphic markers by faulting can introduce uncertainties much larger than quoted random errors. Second: Are rate estimates obtained by more than one geodetic or geologic method? For example, agreement between GPS and InSAR slip rate estimates on the Altyn Tagh and Haiyuan faults of Tibet make the geodetic estimates more reliable. Similarly, dating of multiple offset markers of differing age across these faults supports the consistency of the geologic rate estimates. Third: Is proposed rate change mechanism consistent with examples of changes in style and rate of deformation preserved in the geologic record? For example, temporal evolution of the multi-stranded San Andreas system during the past 5-10 Ma (Powell and Weldon 1992; Graymer et al. 2002) indicates activation and deactivation of different faults within the system accompanied by consequent changes in fault slip rate and/or creation of new crustal blocks. Similarly, reactivation of Cenozoic normal faults as thrusts indicates a late Cenozoic change
Simple estimates of vehicle-induced resuspension rates.
Escrig, A; Amato, F; Pandolfi, M; Monfort, E; Querol, X; Celades, I; Sanfélix, V; Alastuey, A; Orza, J A G
2011-10-01
Road dust emissions are considered to be a major source of airborne particulate matter (PM). This is particularly true for industrial environments, where there are high resuspension rates of deposited dust. The calculation of roads as PM emission sources has mostly focused on the consequences of this emission, viz. the increase in PM concentrations. That approach addresses the atmospheric transport of the emitted dust, and not its primary origin. In contrast, this paper examines the causes of the emission. The study is based on mass conservation of the dust deposited on the road surface. On the basis of this premise, estimates of emission rates were calculated from experimental data obtained in a road in a ceramic industrial area. PMID:21763062
Interictal spikes and epileptic seizures: their relationship and underlying rhythmicity.
Karoly, Philippa J; Freestone, Dean R; Boston, Ray; Grayden, David B; Himes, David; Leyde, Kent; Seneviratne, Udaya; Berkovic, Samuel; O'Brien, Terence; Cook, Mark J
2016-04-01
We report on a quantitative analysis of electrocorticography data from a study that acquired continuous ambulatory recordings in humans over extended periods of time. The objectives were to examine patterns of seizures and spontaneous interictal spikes, their relationship to each other, and the nature of periodic variation. The recorded data were originally acquired for the purpose of seizure prediction, and were subsequently analysed in further detail. A detection algorithm identified potential seizure activity and a template matched filter was used to locate spikes. Seizure events were confirmed manually and classified as either clinically correlated, electroencephalographically identical but not clinically correlated, or subclinical. We found that spike rate was significantly altered prior to seizure in 9 out of 15 subjects. Increased pre-ictal spike rate was linked to improved predictability; however, spike rate was also shown to decrease before seizure (in 6 out of the 9 subjects). The probability distribution of spikes and seizures were notably similar, i.e. at times of high seizure likelihood the probability of epileptic spiking also increased. Both spikes and seizures showed clear evidence of circadian regulation and, for some subjects, there were also longer term patterns visible over weeks to months. Patterns of spike and seizure occurrence were highly subject-specific. The pre-ictal decrease in spike rate is not consistent with spikes promoting seizures. However, the fact that spikes and seizures demonstrate similar probability distributions suggests they are not wholly independent processes. It is possible spikes actively inhibit seizures, or that a decreased spike rate is a secondary symptom of the brain approaching seizure. If spike rate is modulated by common regulatory factors as seizures then spikes may be useful biomarkers of cortical excitability.media-1vid110.1093/brain/aww019_video_abstractaww019_video_abstract. PMID:26912639
Optimized support vector regression for drilling rate of penetration estimation
NASA Astrophysics Data System (ADS)
Bodaghi, Asadollah; Ansari, Hamid Reza; Gholami, Mahsa
2015-12-01
In the petroleum industry, drilling optimization involves the selection of operating conditions for achieving the desired depth with the minimum expenditure while requirements of personal safety, environment protection, adequate information of penetrated formations and productivity are fulfilled. Since drilling optimization is highly dependent on the rate of penetration (ROP), estimation of this parameter is of great importance during well planning. In this research, a novel approach called `optimized support vector regression' is employed for making a formulation between input variables and ROP. Algorithms used for optimizing the support vector regression are the genetic algorithm (GA) and the cuckoo search algorithm (CS). Optimization implementation improved the support vector regression performance by virtue of selecting proper values for its parameters. In order to evaluate the ability of optimization algorithms in enhancing SVR performance, their results were compared to the hybrid of pattern search and grid search (HPG) which is conventionally employed for optimizing SVR. The results demonstrated that the CS algorithm achieved further improvement on prediction accuracy of SVR compared to the GA and HPG as well. Moreover, the predictive model derived from back propagation neural network (BPNN), which is the traditional approach for estimating ROP, is selected for comparisons with CSSVR. The comparative results revealed the superiority of CSSVR. This study inferred that CSSVR is a viable option for precise estimation of ROP.
Heart rate and estimated energy expenditure during ballroom dancing.
Blanksby, B A; Reidy, P W
1988-01-01
Ten competitive ballroom dance couples performed simulated competitive sequences of Modern and Latin American dance. Heart rate was telemetered during the dance sequences and related to direct measures of oxygen uptake and heart rate obtained while walking on a treadmill. Linear regression was employed to estimate gross and net energy expenditures of the dance sequences. A multivariate analysis of variance with repeated measures on the dance factor was applied to the data to test for interaction and main effects on the sex and dance factors. Overall mean heart rate values for the Modern dance sequence were 170 beats.min-1 and 173 beats.min-1 for males and females respectively. During the Latin American sequence mean overall heart rate for males was 168 beats.min-1 and 177 beats.min-1 for females. Predicted mean gross values of oxygen consumption for the males were 42.8 +/- 5.7 ml.kg-1 min-1 and 42.8 +/- 6.9 ml.kg-1 min-1 for the Modern and Latin American sequences respectively. Corresponding gross estimates of oxygen consumption for the females were 34.7 +/- 3.8 ml.kg-1 min-1 and 36.1 +/- 4.1 ml.kg-1 min-1. Males were estimated to expand 54.1 +/- 8.1 kJ.min-1 of energy during the Modern sequence and 54.0 +/- 9.6 kJ.min-1 during the Latin American sequence, while predicted energy expenditure for females was 34.7 +/- 3.8 kJ.min-1 and 36.1 +/- 4.1 kJ.min-1 for Modern and Latin American dance respectively. The results suggested that both males and females were dancing at greater than 80% of their maximum oxygen consumption. A significant difference between males and females was observed for predicted gross and net values of oxygen consumption (in L.min-1 and ml.kg-1 min-1). PMID:3167503
Heart rate and estimated energy expenditure during ballroom dancing.
Blanksby, B A; Reidy, P W
1988-06-01
Ten competitive ballroom dance couples performed simulated competitive sequences of Modern and Latin American dance. Heart rate was telemetered during the dance sequences and related to direct measures of oxygen uptake and heart rate obtained while walking on a treadmill. Linear regression was employed to estimate gross and net energy expenditures of the dance sequences. A multivariate analysis of variance with repeated measures on the dance factor was applied to the data to test for interaction and main effects on the sex and dance factors. Overall mean heart rate values for the Modern dance sequence were 170 beats.min-1 and 173 beats.min-1 for males and females respectively. During the Latin American sequence mean overall heart rate for males was 168 beats.min-1 and 177 beats.min-1 for females. Predicted mean gross values of oxygen consumption for the males were 42.8 +/- 5.7 ml.kg-1 min-1 and 42.8 +/- 6.9 ml.kg-1 min-1 for the Modern and Latin American sequences respectively. Corresponding gross estimates of oxygen consumption for the females were 34.7 +/- 3.8 ml.kg-1 min-1 and 36.1 +/- 4.1 ml.kg-1 min-1. Males were estimated to expand 54.1 +/- 8.1 kJ.min-1 of energy during the Modern sequence and 54.0 +/- 9.6 kJ.min-1 during the Latin American sequence, while predicted energy expenditure for females was 34.7 +/- 3.8 kJ.min-1 and 36.1 +/- 4.1 kJ.min-1 for Modern and Latin American dance respectively. The results suggested that both males and females were dancing at greater than 80% of their maximum oxygen consumption. A significant difference between males and females was observed for predicted gross and net values of oxygen consumption (in L.min-1 and ml.kg-1 min-1). PMID:3167503
NASA Technical Reports Server (NTRS)
Oshman, Yaakov; Markley, Landis
1998-01-01
A sequential filtering algorithm is presented for attitude and attitude-rate estimation from Global Positioning System (GPS) differential carrier phase measurements. A third-order, minimal-parameter method for solving the attitude matrix kinematic equation is used to parameterize the filter's state, which renders the resulting estimator computationally efficient. Borrowing from tracking theory concepts, the angular acceleration is modeled as an exponentially autocorrelated stochastic process, thus avoiding the use of the uncertain spacecraft dynamic model. The new formulation facilitates the use of aiding vector observations in a unified filtering algorithm, which can enhance the method's robustness and accuracy. Numerical examples are used to demonstrate the performance of the method.
Estimation of the diffusion-limited rate of microtubule assembly.
Odde, D J
1997-01-01
Microtubule assembly is a complex process with individual microtubules alternating stochastically between extended periods of assembly and disassembly, a phenomenon known as dynamic instability. Since the discovery of dynamic instability, molecular models of assembly have generally assumed that tubulin incorporation into the microtubule lattice is primarily reaction-limited. Recently this assumption has been challenged and the importance of diffusion in microtubule assembly dynamics asserted on the basis of scaling arguments, with tubulin gradients predicted to extend over length scales exceeding a cell diameter, approximately 50 microns. To assess whether individual microtubules in vivo assemble at diffusion-limited rates and to predict the theoretical upper limit on the assembly rate, a steady-state mean-field model for the concentration of tubulin about a growing microtubule tip was developed. Using published parameter values for microtubule assembly in vivo (growth rate = 7 microns/min, diffusivity = 6 x 10(-12) m2/s, tubulin concentration = 10 microM), the model predicted that the tubulin concentration at the microtubule tip was approximately 89% of the concentration far from the tip, indicating that microtubule self-assembly is not diffusion-limited. Furthermore, the gradients extended less than approximately 50 nm (the equivalent of about two microtubule diameters) from the microtubule tip, a distance much less than a cell diameter. In addition, a general relation was developed to predict the diffusion-limited assembly rate from the diffusivity and bulk tubulin concentration. Using this relation, it was estimated that the maximum theoretical assembly rate is approximately 65 microns/min, above which tubulin can no longer diffuse rapidly enough to support faster growth. Images FIGURE 1 PMID:9199774
Rainfall Estimation Over Tropical Oceans. 1; Area Average Rain Rate
NASA Technical Reports Server (NTRS)
Cuddapah, Prabhakara; Cadeddu, Maria; Meneghini, R.; Short, David A.; Yoo, Jung-Moon; Dalu, G.; Schols, J. L.; Weinman, J. A.
1997-01-01
Multichannel dual polarization microwave radiometer SSM/I observations over oceans do not contain sufficient information to differentiate quantitatively the rain from other hydrometeors on a scale comparable to the radiometer field of view (approx. 30 km). For this reason we have developed a method to retrieve average rain rate over a mesoscale grid box of approx. 300 x 300 sq km area over the TOGA COARE region where simultaneous radiometer and radar observations are available for four months (Nov. 92 to Feb. 93). The rain area in the grid box, inferred from the scattering depression due to hydrometeors in the 85 Ghz brightness temperature, constitutes a key parameter in this method. Then the spectral and polarization information contained in all the channels of the SSM/I is utilized to deduce a second parameter. This is the ratio S/E of scattering index S, and emission index E calculated from the SSM/I data. The rain rate retrieved from this method over the mesoscale area can reproduce the radar observed rain rate with a correlation coefficient of about 0.85. Furthermore monthly total rainfall estimated from this method over that area has an average error of about 15%.
Estimation of adjusted rate differences using additive negative binomial regression.
Donoghoe, Mark W; Marschner, Ian C
2016-08-15
Rate differences are an important effect measure in biostatistics and provide an alternative perspective to rate ratios. When the data are event counts observed during an exposure period, adjusted rate differences may be estimated using an identity-link Poisson generalised linear model, also known as additive Poisson regression. A problem with this approach is that the assumption of equality of mean and variance rarely holds in real data, which often show overdispersion. An additive negative binomial model is the natural alternative to account for this; however, standard model-fitting methods are often unable to cope with the constrained parameter space arising from the non-negativity restrictions of the additive model. In this paper, we propose a novel solution to this problem using a variant of the expectation-conditional maximisation-either algorithm. Our method provides a reliable way to fit an additive negative binomial regression model and also permits flexible generalisations using semi-parametric regression functions. We illustrate the method using a placebo-controlled clinical trial of fenofibrate treatment in patients with type II diabetes, where the outcome is the number of laser therapy courses administered to treat diabetic retinopathy. An R package is available that implements the proposed method. Copyright © 2016 John Wiley & Sons, Ltd. PMID:27073156
Wadehn, Federico; Carnal, David; Loeliger, Hans-Andrea
2015-08-01
Heart rate variability is one of the key parameters for assessing the health status of a subject's cardiovascular system. This paper presents a local model fitting algorithm used for finding single heart beats in photoplethysmogram recordings. The local fit of exponentially decaying cosines of frequencies within the physiological range is used to detect the presence of a heart beat. Using 42 subjects from the CapnoBase database, the average heart rate error was 0.16 BPM and the standard deviation of the absolute estimation error was 0.24 BPM. PMID:26737125
Estimating rates of authigenic carbonate precipitation in modern marine sediments
NASA Astrophysics Data System (ADS)
Mitnick, E. H.; Lammers, L. N.; DePaolo, D. J.
2015-12-01
The formation of authigenic carbonate (AC) in marine sediments provides a plausible explanation for large, long-lasting marine δ13C excursions that does not require extreme swings in atmospheric O2 or CO2. AC precipitation during diagenesis is driven by alkalinity production during anaerobic organic matter oxidation and is coupled to sulfate reduction. To evaluate the extent to which this process contributes to global carbon cycling, we need to relate AC production to the geochemical and geomicrobiological processes and ocean chemical conditions that control it. We present a method to estimate modern rates of AC precipitation using an inversion approach based on the diffusion-advection-reaction equation and sediment pore fluid chemistry profiles as a function of depth. SEM images and semi-quantitative elemental map analyses provide further constraints. Our initial focus is on ODP sites 807 and 1082. We sum the diffusive, advective, and reactive terms that describe changes in pore fluid Ca and Mg concentrations due to precipitation of secondary carbonate. We calculate the advective and diffusive terms from the first and second derivatives of the Ca and Mg pore fluid concentrations using a spline fit to the data. Assuming steady-state behavior we derive net AC precipitation rates of up to 8 x 10-4 mmol m-2 y-1 for Site 807 and 0.6 mmol m-2 y-1 for Site 1082. Site 1082 sediments contain pyrite, which increases in amount down-section towards the estimated peak carbonate precipitation rate, consistent with sulfate-reduction-induced AC precipitation. However, the presence of gypsum and barite throughout the sediment column implies incomplete sulfate reduction and merits further investigation of the biogeochemical reactions controlling authigenesis. Further adjustments to our method could account for the small but non-negligible fraction of groundmass with a CaSO4 signature. Our estimates demonstrate that AC formation may represent a sizeable flux in the modern global
Estimating cougar predation rates from GPS location clusters
Anderson, C.R., Jr.; Lindzey, F.G.
2003-01-01
We examined cougar (Puma concolor) predation from Global Positioning System (GPS) location clusters (???2 locations within 200 m on the same or consecutive nights) of 11 cougars during September-May, 1999-2001. Location success of GPS averaged 2.4-5.0 of 6 location attempts/night/cougar. We surveyed potential predation sites during summer-fall 2000 and summer 2001 to identify prey composition (n = 74; 3-388 days post predation) and record predation-site variables (n = 97; 3-270 days post predation). We developed a model to estimate probability that a cougar killed a large mammal from data collected at GPS location clusters where the probability of predation increased with number of nights (defined as locations at 2200, 0200, or 0500 hr) of cougar presence within a 200-m radius (P < 0.001). Mean estimated cougar predation rates for large mammals were 7.3 days/kill for subadult females (1-2.5 yr; n = 3, 90% CI: 6.3 to 9.9), 7.0 days/kill for adult females (n = 2, 90% CI: 5.8 to 10.8), 5.4 days/kill for family groups (females with young; n = 3, 90% CI: 4.5 to 8.4), 9.5 days/kill for a subadult male (1-2.5 yr; n = 1, 90% CI: 6.9 to 16.4), and 7.8 days/kill for adult males (n = 2, 90% CI: 6.8 to 10.7). We may have slightly overestimated cougar predation rates due to our inability to separate scavenging from predation. We detected 45 deer (Odocoileus spp.), 15 elk (Cervus elaphus), 6 pronghorn (Antilocapra americana), 2 livestock, 1 moose (Alces alces), and 6 small mammals at cougar predation sites. Comparisons between cougar sexes suggested that females selected mule deer and males selected elk (P < 0.001). Cougars averaged 3.0 nights on pronghorn carcasses, 3.4 nights on deer carcasses, and 6.0 nights on elk carcasses. Most cougar predation (81.7%) occurred between 1901-0500 hr and peaked from 2201-0200 hr (31.7%). Applying GPS technology to identify predation rates and prey selection will allow managers to efficiently estimate the ability of an area's prey base to
The Second Spiking Threshold: Dynamics of Laminar Network Spiking in the Visual Cortex.
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
The Second Spiking Threshold: Dynamics of Laminar Network Spiking in the Visual Cortex
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
Inference of neuronal network spike dynamics and topology from calcium imaging data
Lütcke, Henry; Gerhard, Felipe; Zenke, Friedemann; Gerstner, Wulfram; Helmchen, Fritjof
2013-01-01
Two-photon calcium imaging enables functional analysis of neuronal circuits by inferring action potential (AP) occurrence (“spike trains”) from cellular fluorescence signals. It remains unclear how experimental parameters such as signal-to-noise ratio (SNR) and acquisition rate affect spike inference and whether additional information about network structure can be extracted. Here we present a simulation framework for quantitatively assessing how well spike dynamics and network topology can be inferred from noisy calcium imaging data. For simulated AP-evoked calcium transients in neocortical pyramidal cells, we analyzed the quality of spike inference as a function of SNR and data acquisition rate using a recently introduced peeling algorithm. Given experimentally attainable values of SNR and acquisition rate, neural spike trains could be reconstructed accurately and with up to millisecond precision. We then applied statistical neuronal network models to explore how remaining uncertainties in spike inference affect estimates of network connectivity and topological features of network organization. We define the experimental conditions suitable for inferring whether the network has a scale-free structure and determine how well hub neurons can be identified. Our findings provide a benchmark for future calcium imaging studies that aim to reliably infer neuronal network properties. PMID:24399936
Groundwater recharge rate and zone structure estimation using PSOLVER algorithm.
Ayvaz, M Tamer; Elçi, Alper
2014-01-01
The quantification of groundwater recharge is an important but challenging task in groundwater flow modeling because recharge varies spatially and temporally. The goal of this study is to present an innovative methodology to estimate groundwater recharge rates and zone structures for regional groundwater flow models. Here, the unknown recharge field is partitioned into a number of zones using Voronoi Tessellation (VT). The identified zone structure with the recharge rates is associated through a simulation-optimization model that couples MODFLOW-2000 and the hybrid PSOLVER optimization algorithm. Applicability of this procedure is tested on a previously developed groundwater flow model of the Tahtalı Watershed. Successive zone structure solutions are obtained in an additive manner and penalty functions are used in the procedure to obtain realistic and plausible solutions. One of these functions constrains the optimization by forcing the sum of recharge rates for the grid cells that coincide with the Tahtalı Watershed area to be equal to the areal recharge rate determined in the previous modeling by a separate precipitation-runoff model. As a result, a six-zone structure is selected as the best zone structure that represents the areal recharge distribution. Comparison to results of a previous model for the same study area reveals that the proposed procedure significantly improves model performance with respect to calibration statistics. The proposed identification procedure can be thought of as an effective way to determine the recharge zone structure for groundwater flow models, in particular for situations where tangible information about groundwater recharge distribution does not exist. PMID:23746002
Estimates of Lava Eruption Rates at Alba Patera, Mars
NASA Technical Reports Server (NTRS)
Baloga, S. M.; Pieri, D. C.
1985-01-01
The Martian volcanic complex Alba Patera exhibits a suite of well-defined, long and relatively narrow lava flows qualitatively resembling those found in Hawaii. Even without any information on the duration of the Martian flows, eruption rates (total volume discharge/duration of the extrusion) estimates are implied by the physical dimensions of the flows and the likely conjecture that Stephan-Boltzmann radiation is the dominating thermal loss mechanism. The ten flows in this analysis emanate radially from the central vent and were recently measured in length, plan areas, and average thicknesses by shadow measurement techniques. The dimensions of interest are shown. Although perhaps morphologically congruent to certain Hawaiian flows, the dramatically expanded physical dimensions of the Martian flows argues for some markedly distinct differences in lava flow composition for eruption characteristics.
Gambling disorder: estimated prevalence rates and risk factors in Macao.
Wu, Anise M S; Lai, Mark H C; Tong, Kwok-Kit
2014-12-01
An excessive, problematic gambling pattern has been regarded as a mental disorder in the Diagnostic and Statistical Manual for Mental Disorders (DSM) for more than 3 decades (American Psychiatric Association [APA], 1980). In this study, its latest prevalence in Macao (one of very few cities with legalized gambling in China and the Far East) was estimated with 2 major changes in the diagnostic criteria, suggested by the 5th edition of DSM (APA, 2013): (a) removing the "Illegal Act" criterion, and (b) lowering the threshold for diagnosis. A random, representative sample of 1,018 Macao residents was surveyed with a phone poll design in January 2013. After the 2 changes were adopted, the present study showed that the estimated prevalence rate of gambling disorder was 2.1% of the Macao adult population. Moreover, the present findings also provided empirical support to the application of these 2 recommended changes when assessing symptoms of gambling disorder among Chinese community adults. Personal risk factors of gambling disorder, namely being male, having low education, a preference for casino gambling, as well as high materialism, were identified. PMID:25134026
Analyzing multiple spike trains with nonparametric Granger causality.
Nedungadi, Aatira G; Rangarajan, Govindan; Jain, Neeraj; Ding, Mingzhou
2009-08-01
Simultaneous recordings of spike trains from multiple single neurons are becoming commonplace. Understanding the interaction patterns among these spike trains remains a key research area. A question of interest is the evaluation of information flow between neurons through the analysis of whether one spike train exerts causal influence on another. For continuous-valued time series data, Granger causality has proven an effective method for this purpose. However, the basis for Granger causality estimation is autoregressive data modeling, which is not directly applicable to spike trains. Various filtering options distort the properties of spike trains as point processes. Here we propose a new nonparametric approach to estimate Granger causality directly from the Fourier transforms of spike train data. We validate the method on synthetic spike trains generated by model networks of neurons with known connectivity patterns and then apply it to neurons simultaneously recorded from the thalamus and the primary somatosensory cortex of a squirrel monkey undergoing tactile stimulation. PMID:19137420
Prospective Coding by Spiking Neurons
Brea, Johanni; Gaál, Alexisz Tamás; Senn, Walter
2016-01-01
Animals learn to make predictions, such as associating the sound of a bell with upcoming feeding or predicting a movement that a motor command is eliciting. How predictions are realized on the neuronal level and what plasticity rule underlies their learning is not well understood. Here we propose a biologically plausible synaptic plasticity rule to learn predictions on a single neuron level on a timescale of seconds. The learning rule allows a spiking two-compartment neuron to match its current firing rate to its own expected future discounted firing rate. For instance, if an originally neutral event is repeatedly followed by an event that elevates the firing rate of a neuron, the originally neutral event will eventually also elevate the neuron’s firing rate. The plasticity rule is a form of spike timing dependent plasticity in which a presynaptic spike followed by a postsynaptic spike leads to potentiation. Even if the plasticity window has a width of 20 milliseconds, associations on the time scale of seconds can be learned. We illustrate prospective coding with three examples: learning to predict a time varying input, learning to predict the next stimulus in a delayed paired-associate task and learning with a recurrent network to reproduce a temporally compressed version of a sequence. We discuss the potential role of the learning mechanism in classical trace conditioning. In the special case that the signal to be predicted encodes reward, the neuron learns to predict the discounted future reward and learning is closely related to the temporal difference learning algorithm TD(λ). PMID:27341100
Energy Detection Based Estimation of Channel Occupancy Rate with Adaptive Noise Estimation
NASA Astrophysics Data System (ADS)
Lehtomäki, Janne J.; Vuohtoniemi, Risto; Umebayashi, Kenta; Mäkelä, Juha-Pekka
Recently, there has been growing interest in opportunistically utilizing the 2.4GHz ISM-band. Numerous spectrum occupancy measurements covering the ISM-band have been performed to analyze the spectrum usage. However, in these campaigns the verification of the correctness of the obtained occupancy values for the highly dynamic ISM-band has not been presented. In this paper, we propose and verify channel occupancy rate (COR) estimation utilizing energy detection mechanism with a novel adaptive energy detection threshold setting method. The results are compared with the true reference COR values. Several different types of verification measurements showed that our setup can estimate the COR values of 802.11 traffic well, with negligible overestimation. The results from real-time real-life measurements also confirm that the proposed adaptive threshold setting method enables accurate thresholds even in the situations where multiple interferers are present in the received signal.
Program CONTRAST--A general program for the analysis of several survival or recovery rate estimates
Hines, J.E.; Sauer, J.R.
1989-01-01
This manual describes the use of program CONTRAST, which implements a generalized procedure for the comparison of several rate estimates. This method can be used to test both simple and composite hypotheses about rate estimates, and we discuss its application to multiple comparisons of survival rate estimates. Several examples of the use of program CONTRAST are presented. Program CONTRAST will run on IBM-cimpatible computers, and requires estimates of the rates to be tested, along with associated variance and covariance estimates.
NASA Astrophysics Data System (ADS)
Zea, Sven
1992-09-01
During a study of the spatial and temporal patterns of desmosponge (Porifera, Demospongiae) recruitment on rocky and coral reef habitats of Santa Marta, Colombian Caribbean Sea, preliminary attempts were made to estimate actual settlement rates from short-term (1 to a few days) recruitment censuses. Short-term recruitment rates on black, acrylic plastic plates attached to open, non-cryptic substratum by anchor screws were low and variable (0 5 recruits/plate in 1 2 days, sets of n=5 10 plates), but reflected the depth and seasonal trends found using mid-term (1 to a few months) censusing intervals. Moreover, mortality of recruits during 1 2 day intervals was low (0 12%). Thus, short-term censusing intervals can be used to estimate actual settlement rates. To be able to make statistical comparisons, however, it is necessary to increase the number of recruits per census by pooling data of n plates per set, and to have more than one set per site or treatment.
Vibration (?) spikes during natural rain events
NASA Technical Reports Server (NTRS)
Short, David A.
1994-01-01
Limited analysis of optical rain gauge (ORG) data from shipboard and ground based sensors has shown the existence of spikes, possibly attributable to sensor vibration, while rain is occurring. An extreme example of this behavior was noted aboard the PRC#5 on the evening of December 24, 1992 as the ship began repositioning during a rain event in the TOGA/COARE IFA. The spikes are readily evident in the one-second resolution data, but may be indistinguishable from natural rain rate fluctuations in subsampled or averaged data. Such spikes result in increased rainfall totals.
Using minute ventilation for ambulatory estimation of additional heart rate.
Wilhelm, F H; Roth, W T
1998-09-01
Both physical activity and emotion produce physiological activation. The emotional component of heart rate (HR) can be estimated as the additional HR (aHR) above that predicted by O2 consumption. Our innovation was to substitute minute ventilation (V) for O2 consumption, calculating aHR from individual relations between V and HR during an exercise test. We physiologically monitored 28 flight phobics and 15 non-anxious controls while walking (leaving the hospital, entering a plane), and during a commercial flight. Raw HR did not differ between phobics and controls when leaving the hospital (118/114 bpm) or entering the plane (117/110 bpm). However, although aHR was not different when leaving the hospital (7.0/8.6 bpm), it was significantly greater when entering the plane (17.5/9.9 bpm), accurately reflecting the increased subjective anxiety of the phobics. V was not higher in phobics than controls during any condition, suggesting an absence of hyperventilation in the phobics. The results demonstrate the utility of our method for analyzing HR in people whose stress occurs when they are physically active. PMID:9792490
Macroscopic Description for Networks of Spiking Neurons
NASA Astrophysics Data System (ADS)
Montbrió, Ernest; Pazó, Diego; Roxin, Alex
2015-04-01
A major goal of neuroscience, statistical physics, and nonlinear dynamics is to understand how brain function arises from the collective dynamics of networks of spiking neurons. This challenge has been chiefly addressed through large-scale numerical simulations. Alternatively, researchers have formulated mean-field theories to gain insight into macroscopic states of large neuronal networks in terms of the collective firing activity of the neurons, or the firing rate. However, these theories have not succeeded in establishing an exact correspondence between the firing rate of the network and the underlying microscopic state of the spiking neurons. This has largely constrained the range of applicability of such macroscopic descriptions, particularly when trying to describe neuronal synchronization. Here, we provide the derivation of a set of exact macroscopic equations for a network of spiking neurons. Our results reveal that the spike generation mechanism of individual neurons introduces an effective coupling between two biophysically relevant macroscopic quantities, the firing rate and the mean membrane potential, which together govern the evolution of the neuronal network. The resulting equations exactly describe all possible macroscopic dynamical states of the network, including states of synchronous spiking activity. Finally, we show that the firing-rate description is related, via a conformal map, to a low-dimensional description in terms of the Kuramoto order parameter, called Ott-Antonsen theory. We anticipate that our results will be an important tool in investigating how large networks of spiking neurons self-organize in time to process and encode information in the brain.
Temporal spike pattern learning
NASA Astrophysics Data System (ADS)
Talathi, Sachin S.; Abarbanel, Henry D. I.; Ditto, William L.
2008-09-01
Sensory systems pass information about an animal’s environment to higher nervous system units through sequences of action potentials. When these action potentials have essentially equivalent wave forms, all information is contained in the interspike intervals (ISIs) of the spike sequence. How do neural circuits recognize and read these ISI sequences? We address this issue of temporal sequence learning by a neuronal system utilizing spike timing dependent plasticity (STDP). We present a general architecture of neural circuitry that can perform the task of ISI recognition. The essential ingredients of this neural circuit, which we refer to as “interspike interval recognition unit” (IRU) are (i) a spike selection unit, the function of which is to selectively distribute input spikes to downstream IRU circuitry; (ii) a time-delay unit that can be tuned by STDP; and (iii) a detection unit, which is the output of the IRU and a spike from which indicates successful ISI recognition by the IRU. We present two distinct configurations for the time-delay circuit within the IRU using excitatory and inhibitory synapses, respectively, to produce a delayed output spike at time t0+τ(R) in response to the input spike received at time t0 . R is the tunable parameter of the time-delay circuit that controls the timing of the delayed output spike. We discuss the forms of STDP rules for excitatory and inhibitory synapses, respectively, that allow for modulation of R for the IRU to perform its task of ISI recognition. We then present two specific implementations for the IRU circuitry, derived from the general architecture that can both learn the ISIs of a training sequence and then recognize the same ISI sequence when it is presented on subsequent occasions.
Temporal spike pattern learning.
Talathi, Sachin S; Abarbanel, Henry D I; Ditto, William L
2008-09-01
Sensory systems pass information about an animal's environment to higher nervous system units through sequences of action potentials. When these action potentials have essentially equivalent wave forms, all information is contained in the interspike intervals (ISIs) of the spike sequence. How do neural circuits recognize and read these ISI sequences? We address this issue of temporal sequence learning by a neuronal system utilizing spike timing dependent plasticity (STDP). We present a general architecture of neural circuitry that can perform the task of ISI recognition. The essential ingredients of this neural circuit, which we refer to as "interspike interval recognition unit" (IRU) are (i) a spike selection unit, the function of which is to selectively distribute input spikes to downstream IRU circuitry; (ii) a time-delay unit that can be tuned by STDP; and (iii) a detection unit, which is the output of the IRU and a spike from which indicates successful ISI recognition by the IRU. We present two distinct configurations for the time-delay circuit within the IRU using excitatory and inhibitory synapses, respectively, to produce a delayed output spike at time t_{0}+tau(R) in response to the input spike received at time t_{0} . R is the tunable parameter of the time-delay circuit that controls the timing of the delayed output spike. We discuss the forms of STDP rules for excitatory and inhibitory synapses, respectively, that allow for modulation of R for the IRU to perform its task of ISI recognition. We then present two specific implementations for the IRU circuitry, derived from the general architecture that can both learn the ISIs of a training sequence and then recognize the same ISI sequence when it is presented on subsequent occasions. PMID:18851076
Measuring multiple spike train synchrony.
Kreuz, Thomas; Chicharro, Daniel; Andrzejak, Ralph G; Haas, Julie S; Abarbanel, Henry D I
2009-10-15
Measures of multiple spike train synchrony are essential in order to study issues such as spike timing reliability, network synchronization, and neuronal coding. These measures can broadly be divided in multivariate measures and averages over bivariate measures. One of the most recent bivariate approaches, the ISI-distance, employs the ratio of instantaneous interspike intervals (ISIs). In this study we propose two extensions of the ISI-distance, the straightforward averaged bivariate ISI-distance and the multivariate ISI-diversity based on the coefficient of variation. Like the original measure these extensions combine many properties desirable in applications to real data. In particular, they are parameter-free, time scale independent, and easy to visualize in a time-resolved manner, as we illustrate with in vitro recordings from a cortical neuron. Using a simulated network of Hindemarsh-Rose neurons as a controlled configuration we compare the performance of our methods in distinguishing different levels of multi-neuron spike train synchrony to the performance of six other previously published measures. We show and explain why the averaged bivariate measures perform better than the multivariate ones and why the multivariate ISI-diversity is the best performer among the multivariate methods. Finally, in a comparison against standard methods that rely on moving window estimates, we use single-unit monkey data to demonstrate the advantages of the instantaneous nature of our methods. PMID:19591867
Estimating mental fatigue based on electroencephalogram and heart rate variability
NASA Astrophysics Data System (ADS)
Zhang, Chong; Yu, Xiaolin
2010-01-01
The effects of long term mental arithmetic task on psychology are investigated by subjective self-reporting measures and action performance test. Based on electroencephalogram (EEG) and heart rate variability (HRV), the impacts of prolonged cognitive activity on central nervous system and autonomic nervous system are observed and analyzed. Wavelet packet parameters of EEG and power spectral indices of HRV are combined to estimate the change of mental fatigue. Then wavelet packet parameters of EEG which change significantly are extracted as the features of brain activity in different mental fatigue state, support vector machine (SVM) algorithm is applied to differentiate two mental fatigue states. The experimental results show that long term mental arithmetic task induces the mental fatigue. The wavelet packet parameters of EEG and power spectral indices of HRV are strongly correlated with mental fatigue. The predominant activity of autonomic nervous system of subjects turns to the sympathetic activity from parasympathetic activity after the task. Moreover, the slow waves of EEG increase, the fast waves of EEG and the degree of disorder of brain decrease compared with the pre-task. The SVM algorithm can effectively differentiate two mental fatigue states, which achieves the maximum classification accuracy (91%). The SVM algorithm could be a promising tool for the evaluation of mental fatigue. Fatigue, especially mental fatigue, is a common phenomenon in modern life, is a persistent occupational hazard for professional. Mental fatigue is usually accompanied with a sense of weariness, reduced alertness, and reduced mental performance, which would lead the accidents in life, decrease productivity in workplace and harm the health. Therefore, the evaluation of mental fatigue is important for the occupational risk protection, productivity, and occupational health.
Shimazaki, Hideaki; Amari, Shun-ichi; Brown, Emery N.; Grün, Sonja
2012-01-01
Precise spike coordination between the spiking activities of multiple neurons is suggested as an indication of coordinated network activity in active cell assemblies. Spike correlation analysis aims to identify such cooperative network activity by detecting excess spike synchrony in simultaneously recorded multiple neural spike sequences. Cooperative activity is expected to organize dynamically during behavior and cognition; therefore currently available analysis techniques must be extended to enable the estimation of multiple time-varying spike interactions between neurons simultaneously. In particular, new methods must take advantage of the simultaneous observations of multiple neurons by addressing their higher-order dependencies, which cannot be revealed by pairwise analyses alone. In this paper, we develop a method for estimating time-varying spike interactions by means of a state-space analysis. Discretized parallel spike sequences are modeled as multi-variate binary processes using a log-linear model that provides a well-defined measure of higher-order spike correlation in an information geometry framework. We construct a recursive Bayesian filter/smoother for the extraction of spike interaction parameters. This method can simultaneously estimate the dynamic pairwise spike interactions of multiple single neurons, thereby extending the Ising/spin-glass model analysis of multiple neural spike train data to a nonstationary analysis. Furthermore, the method can estimate dynamic higher-order spike interactions. To validate the inclusion of the higher-order terms in the model, we construct an approximation method to assess the goodness-of-fit to spike data. In addition, we formulate a test method for the presence of higher-order spike correlation even in nonstationary spike data, e.g., data from awake behaving animals. The utility of the proposed methods is tested using simulated spike data with known underlying correlation dynamics. Finally, we apply the methods
Shimazaki, Hideaki; Amari, Shun-Ichi; Brown, Emery N; Grün, Sonja
2012-01-01
Precise spike coordination between the spiking activities of multiple neurons is suggested as an indication of coordinated network activity in active cell assemblies. Spike correlation analysis aims to identify such cooperative network activity by detecting excess spike synchrony in simultaneously recorded multiple neural spike sequences. Cooperative activity is expected to organize dynamically during behavior and cognition; therefore currently available analysis techniques must be extended to enable the estimation of multiple time-varying spike interactions between neurons simultaneously. In particular, new methods must take advantage of the simultaneous observations of multiple neurons by addressing their higher-order dependencies, which cannot be revealed by pairwise analyses alone. In this paper, we develop a method for estimating time-varying spike interactions by means of a state-space analysis. Discretized parallel spike sequences are modeled as multi-variate binary processes using a log-linear model that provides a well-defined measure of higher-order spike correlation in an information geometry framework. We construct a recursive Bayesian filter/smoother for the extraction of spike interaction parameters. This method can simultaneously estimate the dynamic pairwise spike interactions of multiple single neurons, thereby extending the Ising/spin-glass model analysis of multiple neural spike train data to a nonstationary analysis. Furthermore, the method can estimate dynamic higher-order spike interactions. To validate the inclusion of the higher-order terms in the model, we construct an approximation method to assess the goodness-of-fit to spike data. In addition, we formulate a test method for the presence of higher-order spike correlation even in nonstationary spike data, e.g., data from awake behaving animals. The utility of the proposed methods is tested using simulated spike data with known underlying correlation dynamics. Finally, we apply the methods
Rate control algorithm based on frame complexity estimation for MVC
NASA Astrophysics Data System (ADS)
Yan, Tao; An, Ping; Shen, Liquan; Zhang, Zhaoyang
2010-07-01
Rate control has not been well studied for multi-view video coding (MVC). In this paper, we propose an efficient rate control algorithm for MVC by improving the quadratic rate-distortion (R-D) model, which reasonably allocate bit-rate among views based on correlation analysis. The proposed algorithm consists of four levels for rate bits control more accurately, of which the frame layer allocates bits according to frame complexity and temporal activity. Extensive experiments show that the proposed algorithm can efficiently implement bit allocation and rate control according to coding parameters.
ESTIMATION OF PHOSPHATE ESTER HYDROLYSIS RATE CONSTANTS. I. ALKALINE HYDROLYSIS
SPARC (SPARC Performs Automated Reasoning in Chemistry) chemical reactivity models were extended to allow the calculation of alkaline hydrolysis rate constants of phosphate esters in water. The rate is calculated from the energy difference between the initial and transition state...
ESTIMATION OF PHOSPHATE ESTER HYDROLYSIS RATE CONSTANTS - ALKALINE HYDROLYSIS
SPARC (SPARC Performs Automated Reasoning in Chemistry) chemical reactivity models were extended to allow the calculation of alkaline hydrolysis rate constants of phosphate esters in water. The rate is calculated from the energy difference between the initial and transition state...
An Overview of Bayesian Methods for Neural Spike Train Analysis
2013-01-01
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. PMID:24348527
Millisecond solar radio spikes observed at 1420 MHz
NASA Astrophysics Data System (ADS)
Dabrowski, B. P.; Kus, A. J.
We present results from observations of narrowband solar millisecond radio spikes at 1420 MHz. Observing data were collected between February 2000 and December 2001 with the 15-m radio telescope at the Centre for Astronomy Nicolaus Copernicus University in Torun, Poland, equipped with a radio spectrograph that covered the 1352-1490 MHz frequency band. The radio spectrograph has 3 MHz frequency resolution and 80 microsecond time resolution. We analyzed the individual radio spike duration, bandwidth and rate of frequency drift. A part of the observed spikes showed well-outlined subtle structures. On dynamic radio spectrograms of the investigated events we notice complex structures formed by numerous individual spikes known as chains of spikes and distinctly different structure of columns. Positions of active regions connected with radio spikes emission were investigated. It turns out that most of them are located near the center of the solar disk, suggesting strong beaming of the spikes emission.
Chatterjee, Bishu; Sharp, Peter A.
2006-07-15
Electric transmission and other rate cases use a form of the discounted cash flow model with a single long-term growth rate to estimate rates of return on equity. It cannot incorporate information about the appropriate time horizon for which analysts' estimates of earnings growth have predictive powers. Only a non-constant growth model can explicitly recognize the importance of the time horizon in an ROE calculation. (author)
Improved estimates of environmental copper release rates from antifouling products.
Finnie, Alistair A
2006-01-01
The US Navy Dome method for measuring copper release rates from antifouling paint in-service on ships' hulls can be considered to be the most reliable indicator of environmental release rates. In this paper, the relationship between the apparent copper release rate and the environmental release rate is established for a number of antifouling coating types using data from a variety of available laboratory, field and calculation methods. Apart from a modified Dome method using panels, all laboratory, field and calculation methods significantly overestimate the environmental release rate of copper from antifouling coatings. The difference is greatest for self-polishing copolymer antifoulings (SPCs) and smallest for certain erodible/ablative antifoulings, where the ASTM/ISO standard and the CEPE calculation method are seen to typically overestimate environmental release rates by factors of about 10 and 4, respectively. Where ASTM/ISO or CEPE copper release rate data are used for environmental risk assessment or regulatory purposes, it is proposed that the release rate values should be divided by a correction factor to enable more reliable generic environmental risk assessments to be made. Using a conservative approach based on a realistic worst case and accounting for experimental uncertainty in the data that are currently available, proposed default correction factors for use with all paint types are 5.4 for the ASTM/ISO method and 2.9 for the CEPE calculation method. Further work is required to expand this data-set and refine the correction factors through correlation of laboratory measured and calculated copper release rates with the direct in situ environmental release rate for different antifouling paints under a range of environmental conditions. PMID:17110352
Estimation of alga growth stage and lipid content growth rate
NASA Technical Reports Server (NTRS)
Embaye, Tsegereda N. (Inventor); Trent, Jonathan D. (Inventor)
2012-01-01
Method and system for estimating a growth stage of an alga in an ambient fluid. Measured light beam absorption or reflection values through or from the alga and through an ambient fluid, in each of two or more wavelength sub-ranges, are compared with reference light beam absorption values for corresponding wavelength sub-ranges for in each alga growth stage to determine (1) which alga growth stage, if any, is more likely and (2) whether estimated lipid content of the alga is increasing or has peaked. Alga growth is preferably terminated when lipid content has approximately reached a maximum value.
Estimation of leakage rates through flexible membrane liners
Murray, G.B.; McBean, E.A.; Sykes, J.F.
1995-12-31
Leakage rate calculations for both low-permeability soil liners and composite liners using flexible membrane liners (FMLs) overlying low-permeability soil are developed. Latin-Hypercube simulations with uncertainty assigned to the soil liner hydraulic conductivity value and the spatial frequency of FML holes are used to examine the variability in the liner leakage rats. The low-permeability soil hydraulic conductivity is the parameter with the greatest effect on landfill liner leakages rates. Composite liners have a significant impact on reducing leakage rates through the landfill liner.
Using genetic data to estimate diffusion rates in heterogeneous landscapes.
Roques, L; Walker, E; Franck, P; Soubeyrand, S; Klein, E K
2016-08-01
Having a precise knowledge of the dispersal ability of a population in a heterogeneous environment is of critical importance in agroecology and conservation biology as it can provide management tools to limit the effects of pests or to increase the survival of endangered species. In this paper, we propose a mechanistic-statistical method to estimate space-dependent diffusion parameters of spatially-explicit models based on stochastic differential equations, using genetic data. Dividing the total population into subpopulations corresponding to different habitat patches with known allele frequencies, the expected proportions of individuals from each subpopulation at each position is computed by solving a system of reaction-diffusion equations. Modelling the capture and genotyping of the individuals with a statistical approach, we derive a numerically tractable formula for the likelihood function associated with the diffusion parameters. In a simulated environment made of three types of regions, each associated with a different diffusion coefficient, we successfully estimate the diffusion parameters with a maximum-likelihood approach. Although higher genetic differentiation among subpopulations leads to more accurate estimations, once a certain level of differentiation has been reached, the finite size of the genotyped population becomes the limiting factor for accurate estimation. PMID:26707856
Neuronal Spike Trains and Stochastic Point Processes
Perkel, Donald H.; Gerstein, George L.; Moore, George P.
1967-01-01
In a growing class of neurophysiological experiments, the train of impulses (“spikes”) produced by a nerve cell is subjected to statistical treatment involving the time intervals between spikes. The statistical techniques available for the analysis of single spike trains are described and related to the underlying mathematical theory, that of stochastic point processes, i.e., of stochastic processes whose realizations may be described as series of point events occurring in time, separated by random intervals. For single stationary spike trains, several orders of complexity of statistical treatment are described; the major distinction is that between statistical measures that depend in an essential way on the serial order of interspike intervals and those that are order-independent. The interrelations among the several types of calculations are shown, and an attempt is made to ameliorate the current nomenclatural confusion in this field. Applications, interpretations, and potential difficulties of the statistical techniques are discussed, with special reference to types of spike trains encountered experimentally. Next, the related types of analysis are described for experiments which involve repeated presentations of a brief, isolated stimulus. Finally, the effects of nonstationarity, e.g. long-term changes in firing rate, on the various statistical measures are discussed. Several commonly observed patterns of spike activity are shown to be differentially sensitive to such changes. A companion paper covers the analysis of simultaneously observed spike trains. PMID:4292791
ESTIMATION OF CARBOXYLIC ACID ESTER HYDROLYSIS RATE CONSTANTS
SPARC chemical reactivity models were extended to calculate hydrolysis rate constants for carboxylic acid esters from molecular structure. The energy differences between the initial state and the transition state for a molecule of interest are factored into internal and external...
SEE Rate Estimation: Model Complexity and Data Requirements
NASA Technical Reports Server (NTRS)
Ladbury, Ray
2008-01-01
Statistical Methods outlined in [Ladbury, TNS20071 can be generalized for Monte Carlo Rate Calculation Methods Two Monte Carlo Approaches: a) Rate based on vendor-supplied (or reverse-engineered) model SEE testing and statistical analysis performed to validate model; b) Rate calculated based on model fit to SEE data Statistical analysis very similar to case for CREME96. Information Theory allows simultaneous consideration of multiple models with different complexities: a) Model with lowest AIC usually has greatest predictive power; b) Model averaging using AIC weights may give better performance if several models have similar good performance; and c) Rates can be bounded for a given confidence level over multiple models, as well as over the parameter space of a model.
Chen, Rongda; Wang, Ze
2013-01-01
Recovery rate is essential to the estimation of the portfolio’s loss and economic capital. Neglecting the randomness of the distribution of recovery rate may underestimate the risk. The study introduces two kinds of models of distribution, Beta distribution estimation and kernel density distribution estimation, to simulate the distribution of recovery rates of corporate loans and bonds. As is known, models based on Beta distribution are common in daily usage, such as CreditMetrics by J.P. Morgan, Portfolio Manager by KMV and Losscalc by Moody’s. However, it has a fatal defect that it can’t fit the bimodal or multimodal distributions such as recovery rates of corporate loans and bonds as Moody’s new data show. In order to overcome this flaw, the kernel density estimation is introduced and we compare the simulation results by histogram, Beta distribution estimation and kernel density estimation to reach the conclusion that the Gaussian kernel density distribution really better imitates the distribution of the bimodal or multimodal data samples of corporate loans and bonds. Finally, a Chi-square test of the Gaussian kernel density estimation proves that it can fit the curve of recovery rates of loans and bonds. So using the kernel density distribution to precisely delineate the bimodal recovery rates of bonds is optimal in credit risk management. PMID:23874558
Chen, Rongda; Wang, Ze
2013-01-01
Recovery rate is essential to the estimation of the portfolio's loss and economic capital. Neglecting the randomness of the distribution of recovery rate may underestimate the risk. The study introduces two kinds of models of distribution, Beta distribution estimation and kernel density distribution estimation, to simulate the distribution of recovery rates of corporate loans and bonds. As is known, models based on Beta distribution are common in daily usage, such as CreditMetrics by J.P. Morgan, Portfolio Manager by KMV and Losscalc by Moody's. However, it has a fatal defect that it can't fit the bimodal or multimodal distributions such as recovery rates of corporate loans and bonds as Moody's new data show. In order to overcome this flaw, the kernel density estimation is introduced and we compare the simulation results by histogram, Beta distribution estimation and kernel density estimation to reach the conclusion that the Gaussian kernel density distribution really better imitates the distribution of the bimodal or multimodal data samples of corporate loans and bonds. Finally, a Chi-square test of the Gaussian kernel density estimation proves that it can fit the curve of recovery rates of loans and bonds. So using the kernel density distribution to precisely delineate the bimodal recovery rates of bonds is optimal in credit risk management. PMID:23874558
Capture-recapture analysis for estimating manatee reproductive rates
Kendall, W.L.; Langtimm, C.A.; Beck, C.A.; Runge, M.C.
2004-01-01
Modeling the life history of the endangered Florida manatee (Trichechus manatus latirostris) is an important step toward understanding its population dynamics and predicting its response to management actions. We developed a multi-state mark-resighting model for data collected under Pollock's robust design. This model estimates breeding probability conditional on a female's breeding state in the previous year; assumes sighting probability depends on breeding state; and corrects for misclassification of a cow with first-year calf, by estimating conditional sighting probability for the calf. The model is also appropriate for estimating survival and unconditional breeding probabilities when the study area is closed to temporary emigration across years. We applied this model to photo-identification data for the Northwest and Atlantic Coast populations of manatees, for years 1982?2000. With rare exceptions, manatees do not reproduce in two consecutive years. For those without a first-year calf in the previous year, the best-fitting model included constant probabilities of producing a calf for the Northwest (0.43, SE = 0.057) and Atlantic (0.38, SE = 0.045) populations. The approach we present to adjust for misclassification of breeding state could be applicable to a large number of marine mammal populations.
On Estimation of GPS-based Indonesian Strain Rate Map
NASA Astrophysics Data System (ADS)
Susilo, Susilo; Abidin, Hasanuddin Z.; Meilano, Irwan; Sapiie, Benyamin; Wijanarto, Antonius B.
2016-04-01
Using the GPS-derived rates at survey mode (sGPS) stations and continuous GPS stations across Indonesian region, covering the 22 years period from 1993 to 2014, the linear deformation velocities with an accuracy of about 2 to 3 mm/year level are derived. These velocities are corrected to the coseismic and postseismic deformation caused by significant earthquakes in that period. In this study, we use this GPS velocities field to construct a crustal strain rate map without including the physical model yet. An interpolation method was used to compute the velocity model. By differentiation of the continuous velocity model, we derive the strain rate map of Indonesia. At present, our result is only the magnitude of the strain rate. The Indonesian strain rate map is very important for studying the deformation characteristics in the region and to establish a deformation (velocity) model for supporting the implementation of the Indonesian Geospatial Reference System 2013 (IGRS 2013). This is a new semi-dynamic geocentric datum of Indonesia, which uses the global ITRF2008 reference frame, with a reference epoch of 1 January 2012. A deformation (velocity) model is required to transform coordinates from an observation epoch to or from this reference epoch.
Estimation of the nucleation rate by differential scanning calorimetry
NASA Technical Reports Server (NTRS)
Kelton, Kenneth F.
1992-01-01
A realistic computer model is presented for calculating the time-dependent volume fraction transformed during the devitrification of glasses, assuming the classical theory of nucleation and continuous growth. Time- and cluster-dependent nucleation rates are calculated by modeling directly the evolving cluster distribution. Statistical overlap in the volume fraction transformed is taken into account using the standard Johnson-Mehl-Avrami formalism. Devitrification behavior under isothermal and nonisothermal conditions is described. The model is used to demonstrate that the recent suggestion by Ray and Day (1990) that nonisothermal DSC studies can be used to determine the temperature for the peak nucleation rate, is qualitatively correct for lithium disilicate, the glass investigated.
Ottosen, Lisbeth M; Lepkova, Katarina; Kubal, Martin
2006-09-01
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/cm(2) 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 that the removal rate was higher in kaolinite than in both spiked soil and industrial polluted soil. The duration of spiking was found to be an important factor too, when attempting to relate remediation of spiked soil or kaolinite to remediation of industrially polluted soils. Spiking for 2 days was too short. However, spiking for 30 days resulted in a pattern that was more similar to that of industrially polluted soils with similar compositions both regarding sequential extraction and electrodialytic remediation result, though the remediation still progressed slightly faster in the spiked soil. Generalisation of remediation results to a variety of soil types must on the other hand be done with caution since the remediation results of different industrially polluted soils were very different. In one soil a total of 76% Cu was removed and in another soil no Cu was removed only redistributed within the soil. The factor with the highest influence on removal success was soil pH, which must be low in order to mobilize Cu, and thus the buffering capacity against acidification was
Rating Curve Estimation from Local Levels and Upstream Discharges
NASA Astrophysics Data System (ADS)
Franchini, M.; Mascellani, G.
2003-04-01
Current technology allows for low cost and easy level measurements while the discharge measurements are still difficult and expensive. Thus, these are rarely performed and usually not in flood conditions because of lack of safety and difficulty in activating the measurement team in due time. As a consequence, long series of levels are frequently available without the corresponding discharge values. However, for the purpose of planning, management of water resources and real time flood forecasting, discharge is needed and it is therefore essential to convert local levels into discharge values by using the appropriate rating curve. Over this last decade, several methods have been proposed to relate local levels at a site of interest to data recorded at a river section located upstream where a rating curve is available. Some of these methods are based on a routing approach which uses the Muskingum model structure in different ways; others are based on the entropy concepts. Lately, fuzzy logic has been applied more and more frequently in the framework of hydraulic and hydrologic problems and this has prompted to the authors to use it for synthesising the rating curves. A comparison between all these strategies is performed, highlighting the difficulties and advantages of each of them, with reference to a long reach of the Po river in Italy, where several hydrometers and the relevant rating curves are available, thus allowing for both a parameterization and validation of the different strategies.
Modeled Estimates of Soil and Dust Ingestion Rates for Children
Daily soil/dust ingestion rates typically used in exposure and risk assessments are based on tracer element studies, which have a number of limitations and do not separate contributions from soil and dust. This article presents an alternate approach of modeling soil and dust inge...
Time-dependent estimates of molecular evolutionary rates: evidence and causes.
Ho, Simon Y W; Duchêne, Sebastián; Molak, Martyna; Shapiro, Beth
2015-12-01
We are writing in response to a recent critique by Emerson & Hickerson (2015), who challenge the evidence of a time-dependent bias in molecular rate estimates. This bias takes the form of a negative relationship between inferred evolutionary rates and the ages of the calibrations on which these estimates are based. Here, we present a summary of the evidence obtained from a broad range of taxa that supports a time-dependent bias in rate estimates, with a consideration of the potential causes of these observed trends. We also describe recent progress in improving the reliability of evolutionary rate estimation and respond to the concerns raised by Emerson & Hickerson (2015) about the validity of rates estimated from time-structured sequence data. In doing so, we hope to dispel some misconceptions and to highlight several research directions that will improve our understanding of time-dependent biases in rate estimates. PMID:26769402
Frame rate up conversion via Bayesian motion estimation
NASA Astrophysics Data System (ADS)
Wang, Yue; Ma, Siwei; Gao, Wen
2010-07-01
In this paper, a novel block-based motion compensated frame interpolation (MCI) algorithm is proposed to enhance the temporal resolution of video sequences. We formulated motion estimation into MAP framework, and solved it via Bayesian belief propagation. By effectively incorporating a priori knowledge of the motion field and optimizing the whole motion field synchronously, it could derive more accurate motion vectors than traditional methods. Finally, adaptive overlapped block motion compensation (OBMC) is used to reduce blocking artifacts. Experimental results show that the proposed method outperforms other methods in both objective and subjective quality.
Continuous functions determined by spike trains of a neuron subject to stimulation.
Awiszus, F
1988-01-01
Several ways of estimating a continuous function from the spike train output of a neuron subjected to repeated stimuli are compared: (i) the probability of firing function estimated by a PST-histogram (ii) the rate of discharge function estimated by a "frequencygram" (Bessou et al. 1968) and (iii) the interspike-interval function which is introduced in this paper. For a special class of neuronal responses, called deterministic, these functions may be expressed in terms of each other. It is shown that the current clamped Hodgkin-Huxley model of an action potential encoding membrane (Hodgkin and Huxley 1952) is able to generate such deterministic responses. As an experimental example, a deterministic response of a primary muscle spindle afferent is used to demonstrate the estimation of the functions. Interpretability and numerical estimatability of these spike train describing functions are discussed for deterministic neuronal responses. PMID:3382703
Population trend of the Yellowstone grizzly bear as estimated from reproductive and survival rates
Eberhardt, L. L.; Blanchard, B. M.; Knight, R. R.
1993-01-01
The trend of the Yellowstone grizzly bear (Ursus arctos horribilis) population was estimated using reproductive rates calculated from 22 individual females and survival rates from 400 female bear-years. The point estimate of the rate of increase was 4.6%, with 95% confidence limits of 0 and 9%. Caution in interpreting this result is advised because of possible biases in the population parameter estimates. The main prospects for improving present knowledge of the population trend appear to be further study of possible biases in the parameter estimates, and the continued use of radiotelemetry to increase the number of samples on which the estimates are based.
Occupational Injury Rate Estimates in Magnetic Fusion Experiments
cadwallader, lee
2006-11-01
In nuclear facilities, there are two primary aspects of occupational safety. The first aspect is radiological safety, which has rightly been treated in detail in nuclear facilities. Radiological exposure data have been collected from the existing tokamaks to serve as forecasts for ITER radiation safety. The second aspect of occupational safety, “traditional” industrial safety, must also be considered for a complete occupational safety program. Industrial safety data on occupational injury rates from the JET and TFTR tokamaks, three accelerators, and U.S. nuclear fission plants have been collected to set industrial safety goals for the ITER operations staff. The results of this occupational safety data collection and analysis activity are presented here. The data show that an annual lost workday case rate of 0.3 incidents per 100 workers is a conceivable goal for ITER operations.
Estimation of Eddy Dissipation Rates from Mesoscale Model Simulations
NASA Technical Reports Server (NTRS)
Ahmad, Nashat N.; Proctor, Fred H.
2012-01-01
The Eddy Dissipation Rate is an important metric for representing the intensity of atmospheric turbulence and is used as an input parameter for predicting the decay of aircraft wake vortices. In this study, the forecasts of eddy dissipation rates obtained from the current state-of-the-art mesoscale model are evaluated for terminal area applications. The Weather Research and Forecast mesoscale model is used to simulate the planetary boundary layer at high horizontal and vertical mesh resolutions. The Bougeault-Lacarrer and the Mellor-Yamada-Janji schemes implemented in the Weather Research and Forecast model are evaluated against data collected during the National Aeronautics and Space Administration s Memphis Wake Vortex Field Experiment. Comparisons with other observations are included as well.
Temporal Correlations and Neural Spike Train Entropy
Schultz, Simon R.; Panzeri, Stefano
2001-06-18
Sampling considerations limit the experimental conditions under which information theoretic analyses of neurophysiological data yield reliable results. We develop a procedure for computing the full temporal entropy and information of ensembles of neural spike trains, which performs reliably for limited samples of data. This approach also yields insight to the role of correlations between spikes in temporal coding mechanisms. The method, when applied to recordings from complex cells of the monkey primary visual cortex, results in lower rms error information estimates in comparison to a {open_quotes}brute force{close_quotes} approach.
Estimation of the mass outflow rates around rotating black holes
NASA Astrophysics Data System (ADS)
Aktar, Ramiz; Das, Santabrata
We consider steady, advective, rotating, inviscid accretion disc around the spinning black holes to compute the mass outflow rate (R_{dot{m}}) defined as the ratio of mass flux of outflowing to the inflowing matter. Due to centrifugal barrier, accreting matter suffers discontinuous shock transition and because of shock compression, the post-shock matter becomes hot and denser than the pre-shock matter. We call the post-shock disc as Post Shock Corona (PSC). During accretion, a part of the inflowing matter deflects as bipolar outflows due to the presence of excess thermal gradient force at PSC. We find that R_{dot{m}}is directly correlated with the spin of the black hole (a_{k}) for the same set of inflow parameter, namely specific energy (E) and specific angular momentum (λ). We observe that the maximum outflow rate(R_{dot{m}}^{max}) weakly depends on spin (a_{k}) that lies in the range˜ 17% - 18% of the inflow rate.
Estimating division and death rates from CFSE data
NASA Astrophysics Data System (ADS)
de Boer, Rob J.; Perelson, Alan S.
2005-12-01
The division tracking dye, carboxyfluorescin diacetate succinimidyl ester (CFSE) is currently the most informative labeling technique for characterizing the division history of cells in the immune system. Gett and Hodgkin (Nat. Immunol. 1 (2000) 239-244) have proposed to normalize CFSE data by the 2-fold expansion that is associated with each division, and have argued that the mean of the normalized data increases linearly with time, t, with a slope reflecting the division rate p. We develop a number of mathematical models for the clonal expansion of quiescent cells after stimulation and show, within the context of these models, under which conditions this approach is valid. We compare three means of the distribution of cells over the CFSE profile at time t: the mean, [mu](t), the mean of the normalized distribution, [mu]2(t), and the mean of the normalized distribution excluding nondivided cells, .In the simplest models, which deal with homogeneous populations of cells with constant division and death rates, the normalized frequency distribution of the cells over the respective division numbers is a Poisson distribution with mean [mu]2(t)=pt, where p is the division rate. The fact that in the data these distributions seem Gaussian is therefore insufficient to establish that the times at which cells are recruited into the first division have a Gaussian variation because the Poisson distribution approaches the Gaussian distribution for large pt. Excluding nondivided cells complicates the data analysis because , and only approaches a slope p after an initial transient.In models where the first division of the quiescent cells takes longer than later divisions, all three means have an initial transient before they approach an asymptotic regime, which is the expected [mu](t)=2pt and . Such a transient markedly complicates the data analysis. After the same initial transients, the normalized cell numbers tend to decrease at a rate e-dt, where d is the death rate
Estimate of avoidance maneuver rate for HASTOL tether boost facility
NASA Astrophysics Data System (ADS)
Forward, Robert L.
2002-01-01
The Hypersonic Airplane Space Tether Orbital Launch (HASTOL) Architecture uses a hypersonic airplane (or reusable launch vehicle) to carry a payload from the surface of the Earth to 150 km altitude and a speed of Mach 17. The hypersonic airplane makes a rendezvous with the grapple at the tip of a long, rotating, orbiting space tether boost facility, which picks up the payload from the airplane. Release of the payload at the proper point in the tether rotation boosts the payload into a higher orbit, typically into a Geosynchronous Transfer Orbit (GTO), with lower orbits and Earth escape other options. The HASTOL Tether Boost Facility will have a length of 636 km. Its center of mass will be in a 604 km by 890 km equatorial orbit. It is estimated that by the time of the start of operations of the HASTOL Tether Boost facility in the year 2020, there will be 500 operational spacecraft using the same volume of space as the HASTOL facility. These operational spacecraft would likely be made inoperative by an impact with one of the lines in the multiline HASTOL Hoytether™ and should be avoided. There will also be non-operational spacecraft and large pieces of orbital debris with effective size greater than five meters in diameter that could cut a number of lines in the HASTOL Hoytether™, and should also be avoided. It is estimated, using two different methods and combining them, that the HASTOL facility will need to make avoidance maneuvers about once every four days if the 500 operational spacecraft and large pieces of orbital debris greater than 5 m in diameter, were each protected by a 2 km diameter miss distance protection sphere. If by 2020, the ability to know the positions of operational spacecraft and large pieces of orbital debris improved to allow a 600 m diameter miss distance protection sphere around each object, then the number of HASTOL facility maneuvers needed drops to one every two weeks. .
Impact of spike train autostructure on probability distribution of joint spike events.
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. PMID:23470124
NASA Astrophysics Data System (ADS)
Futter, M. N.; Klaminder, J.; Lucas, R. W.; Laudon, H.; Köhler, S. J.
2012-06-01
Precise and accurate estimates of silicate mineral weathering rates are crucial when setting policy targets for long-term forest sustainability, critical load calculations and assessing consequences of proposed geo-engineering solutions to climate change. In this paper, we scrutinize 394 individual silicate mineral weathering estimates from 82 sites on three continents. We show that within-site differences of several hundred per cent arise when different methods are used to estimate weathering rates, mainly as a result of uncertainties related to input data rather than conceptually different views of the weathering process. While different methods tend to rank sites congruently from high to low weathering rates, large within-site differences in estimated weathering rate suggest that policies relying on quantitative estimates based upon a single method may have undesirable outcomes. We recommend the use of at least three independent estimates when making management decisions related to silicate mineral weathering rates.
Infrared imaging based hyperventilation monitoring through respiration rate estimation
NASA Astrophysics Data System (ADS)
Basu, Anushree; Routray, Aurobinda; Mukherjee, Rashmi; Shit, Suprosanna
2016-07-01
A change in the skin temperature is used as an indicator of physical illness which can be detected through infrared thermography. Thermograms or thermal images can be used as an effective diagnostic tool for monitoring and diagnosis of various diseases. This paper describes an infrared thermography based approach for detecting hyperventilation caused due to stress and anxiety in human beings by computing their respiration rates. The work employs computer vision techniques for tracking the region of interest from thermal video to compute the breath rate. Experiments have been performed on 30 subjects. Corner feature extraction using Minimum Eigenvalue (Shi-Tomasi) algorithm and registration using Kanade Lucas-Tomasi algorithm has been used here. Thermal signature around the extracted region is detected and subsequently filtered through a band pass filter to compute the respiration profile of an individual. If the respiration profile shows unusual pattern and exceeds the threshold we conclude that the person is stressed and tending to hyperventilate. Results obtained are compared with standard contact based methods which have shown significant correlations. It is envisaged that the thermal image based approach not only will help in detecting hyperventilation but can assist in regular stress monitoring as it is non-invasive method.
Decision tree rating scales for workload estimation: Theme and variations
NASA Technical Reports Server (NTRS)
Wierwille, W. W.; Skipper, J. H.; Rieger, C. A.
1984-01-01
The Modified Cooper-Harper (MCH) scale which is a sensitive indicator of workload in several different types of aircrew tasks was examined. The study determined if variations of the scale might provide greater sensitivity and the reasons for the sensitivity of the scale. The MCH scale and five newly devised scales were examined in two different aircraft simulator experiments in which pilot loading was treated as an independent variable. It is indicated that while one of the new scales may be more sensitive in a given experiment, task dependency is a problem. The MCH scale exhibits consistent senstivity and remains the scale recommended for general use. The MCH scale results are consistent with earlier experiments. The rating scale experiments are reported and the questionnaire results which were directed to obtain a better understanding of the reasons for the relative sensitivity of the MCH scale and its variations are described.
Decision Tree Rating Scales for Workload Estimation: Theme and Variations
NASA Technical Reports Server (NTRS)
Wietwille, W. W.; Skipper, J. H.; Rieger, C. A.
1984-01-01
The modified Cooper-Harper (MCH) scale has been shown to be a sensitive indicator of workload in several different types of aircrew tasks. The MCH scale was examined to determine if certain variations of the scale might provide even greater sensitivity and to determine the reasons for the sensitivity of the scale. The MCH scale and five newly devised scales were studied in two different aircraft simulator experiments in which pilot loading was treated as an independent variable. Results indicate that while one of the new scales may be more sensitive in a given experiment, task dependency is a problem. The MCH scale exhibits consistent sensitivity and remains the scale recommended for general use. The results of the rating scale experiments are presented and the questionnaire results which were directed at obtaining a better understanding of the reasons for the relative sensitivity of the MCH scale and its variations are described.
Nichols, J.D.; Pollock, K.H.
1983-01-01
Capture-recapture models can be used to estimate parameters of interest from paleobiological data when encouter probabilities are unknown and variable over time. These models also permit estimation of sampling variances and goodness-of-fit tests are available for assessing the fit of data to most models. The authors describe capture-recapture models which should be useful in paleobiological analyses and discuss the assumptions which underlie them. They illustrate these models with examples and discuss aspects of study design.
NASA Astrophysics Data System (ADS)
Muchlisoh, Siti; Kurnia, Anang; Notodiputro, Khairil Anwar; Mangku, I. Wayan
2016-02-01
Labor force surveys conducted over time by the rotating panel design have been carried out in many countries, including Indonesia. Labor force survey in Indonesia is regularly conducted by Statistics Indonesia (Badan Pusat Statistik-BPS) and has been known as the National Labor Force Survey (Sakernas). The main purpose of Sakernas is to obtain information about unemployment rates and its changes over time. Sakernas is a quarterly survey. The quarterly survey is designed only for estimating the parameters at the provincial level. The quarterly unemployment rate published by BPS (official statistics) is calculated based on only cross-sectional methods, despite the fact that the data is collected under rotating panel design. The study purpose to estimate a quarterly unemployment rate at the district level used small area estimation (SAE) model by combining time series and cross-sectional data. The study focused on the application and comparison between the Rao-Yu model and dynamic model in context estimating the unemployment rate based on a rotating panel survey. The goodness of fit of both models was almost similar. Both models produced an almost similar estimation and better than direct estimation, but the dynamic model was more capable than the Rao-Yu model to capture a heterogeneity across area, although it was reduced over time.
Spiking optical patterns and synchronization
NASA Astrophysics Data System (ADS)
Rosenbluh, Michael; Aviad, Yaara; Cohen, Elad; Khaykovich, Lev; Kinzel, Wolfgang; Kopelowitz, Evi; Yoskovits, Pinhas; Kanter, Ido
2007-10-01
We analyze the time resolved spike statistics of a solitary and two mutually interacting chaotic semiconductor lasers whose chaos is characterized by apparently random, short intensity spikes. Repulsion between two successive spikes is observed, resulting in a refractory period, which is largest at laser threshold. For time intervals between spikes greater than the refractory period, the distribution of the intervals follows a Poisson distribution. The spiking pattern is highly periodic over time windows corresponding to the optical length of the external cavity, with a slow change of the spiking pattern as time increases. When zero-lag synchronization between two lasers is established, the statistics of the nearly perfectly matched spikes are not altered. The similarity of these features to those found in complex interacting neural networks, suggests the use of laser systems as simpler physical models for neural networks.
ESTIMATING THE RATE OF PLASMID TRANSFER: AN END-POINT METHOD
A method is described for determining rate parameter of conjugative plasmid transfer that is based on single estimates of donor, recipient and transconjugant densities, and the growth rate in exponential phase of the mating culture. he formula for estimating the plasmid transfer ...
Two Approaches to Estimation of Classification Accuracy Rate under Item Response Theory
ERIC Educational Resources Information Center
Lathrop, Quinn N.; Cheng, Ying
2013-01-01
Within the framework of item response theory (IRT), there are two recent lines of work on the estimation of classification accuracy (CA) rate. One approach estimates CA when decisions are made based on total sum scores, the other based on latent trait estimates. The former is referred to as the Lee approach, and the latter, the Rudner approach,…
Spike-Timing Theory of Working Memory
Szatmáry, Botond; Izhikevich, Eugene M.
2010-01-01
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. PMID:20808877
Spiking models for level-invariant encoding.
Brette, Romain
2011-01-01
Levels of ecological sounds vary over several orders of magnitude, but the firing rate and membrane potential of a neuron are much more limited in range. In binaural neurons of the barn owl, tuning to interaural delays is independent of level differences. Yet a monaural neuron with a fixed threshold should fire earlier in response to louder sounds, which would disrupt the tuning of these neurons. How could spike timing be independent of input level? Here I derive theoretical conditions for a spiking model to be insensitive to input level. The key property is a dynamic change in spike threshold. I then show how level invariance can be physiologically implemented, with specific ionic channel properties. It appears that these ingredients are indeed present in monaural neurons of the sound localization pathway of birds and mammals. PMID:22291634
NASA Technical Reports Server (NTRS)
Challa, M. S.; Natanson, G. A.; Baker, D. F.; Deutschmann, J. K.
1994-01-01
This paper describes real-time attitude determination results for the Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX), a gyroless spacecraft, using a Kalman filter/Euler equation approach denoted the real-time sequential filter (RTSF). The RTSF is an extended Kalman filter whose state vector includes the attitude quaternion and corrections to the rates, which are modeled as Markov processes with small time constants. The rate corrections impart a significant robustness to the RTSF against errors in modeling the environmental and control torques, as well as errors in the initial attitude and rates, while maintaining a small state vector. SAMPLEX flight data from various mission phases are used to demonstrate the robustness of the RTSF against a priori attitude and rate errors of up to 90 deg and 0.5 deg/sec, respectively, as well as a sensitivity of 0.0003 deg/sec in estimating rate corrections in torque computations. In contrast, it is shown that the RTSF attitude estimates without the rate corrections can degrade rapidly. RTSF advantages over single-frame attitude determination algorithms are also demonstrated through (1) substantial improvements in attitude solutions during sun-magnetic field coalignment and (2) magnetic-field-only attitude and rate estimation during the spacecraft's sun-acquisition mode. A robust magnetometer-only attitude-and-rate determination method is also developed to provide for the contingency when both sun data as well as a priori knowledge of the spacecraft state are unavailable. This method includes a deterministic algorithm used to initialize the RTSF with coarse estimates of the spacecraft attitude and rates. The combined algorithm has been found effective, yielding accuracies of 1.5 deg in attitude and 0.01 deg/sec in the rates and convergence times as little as 400 sec.
Estimating respiratory rate from FBG optical sensors by using signal quality measurement.
Yongwei Zhu; Maniyeri, Jayachandran; Fook, Victor Foo Siang; Haihong Zhang
2015-08-01
Non-intrusiveness is one of the advantages of in-bed optical sensor device for monitoring vital signs, including heart rate and respiratory rate. Estimating respiratory rate reliably using such sensors, however, is challenging, due to body movement, signal variation according to different subjects or body positions, etc. This paper presents a method for reliable respiratory rate estimation for FBG optical sensors by introducing signal quality estimation. The method estimates the quality of the signal waveform by detecting regularly repetitive patterns using proposed spectrum and cepstrum analysis. Multiple window sizes are used to cater for a wide range of target respiratory rates. Furthermore, the readings of multiple sensors are fused to derive a final respiratory rate. Experiments with 12 subjects and 2 body positions were conducted using polysomnography belt signal as groundtruth. The results demonstrated the effectiveness of the method. PMID:26736396
The Estimation and Control of the Electroslag Remelting Melt Rate by Mechanism-Based Modeling
NASA Astrophysics Data System (ADS)
Li, Wanzhou; Wang, Weiyu; Hu, Yuechen; Chen, Yixing
2012-04-01
The process control of industrial electroslag remelting production is addressed in this work. This article proposes a mechanism-based model using electrode displacement to estimate the melt rate, designs the remelting process control system, and uses practical application data to verify the validity of the model. The soft measurement of the melt rate based on mechanism modeling is proved to be an economical and reliable solution to the online melt rate estimation and control for large industrial electroslag remelting furnaces.
Spiking Neurons for Analysis of Patterns
NASA Technical Reports Server (NTRS)
Huntsberger, Terrance
2008-01-01
neurons). These features enable the neurons to adapt their responses to high-rate inputs from sensors, and to adapt their firing thresholds to mitigate noise or effects of potential sensor failure. The mathematical derivation of the SVM starts from a prior model, known in the art as the point soma model, which captures all of the salient properties of neuronal response while keeping the computational cost low. The point-soma latency time is modified to be an exponentially decaying function of the strength of the applied potential. Choosing computational efficiency over biological fidelity, the dendrites surrounding a neuron are represented by simplified compartmental submodels and there are no dendritic spines. Updates to the dendritic potential, calcium-ion concentrations and conductances, and potassium-ion conductances are done by use of equations similar to those of the point soma. Diffusion processes in dendrites are modeled by averaging among nearest-neighbor compartments. Inputs to each of the dendritic compartments come from sensors. Alternatively or in addition, when an affected neuron is part of a pool, inputs can come from other spiking neurons. At present, SVM neural networks are implemented by computational simulation, using algorithms that encode the SVM and its submodels. However, it should be possible to implement these neural networks in hardware: The differential equations for the dendritic and cellular processes in the SVM model of spiking neurons map to equivalent circuits that can be implemented directly in analog very-large-scale integrated (VLSI) circuits.
Maximum likelihood estimation of population growth rates based on the coalescent.
Kuhner, M K; Yamato, J; Felsenstein, J
1998-01-01
We describe a method for co-estimating 4Nemu (four times the product of effective population size and neutral mutation rate) and population growth rate from sequence samples using Metropolis-Hastings sampling. Population growth (or decline) is assumed to be exponential. The estimates of growth rate are biased upwards, especially when 4Nemu is low; there is also a slight upwards bias in the estimate of 4Nemu itself due to correlation between the parameters. This bias cannot be attributed solely to Metropolis-Hastings sampling but appears to be an inherent property of the estimator and is expected to appear in any approach which estimates growth rate from genealogy structure. Sampling additional unlinked loci is much more effective in reducing the bias than increasing the number or length of sequences from the same locus. PMID:9584114
Solving Constraint Satisfaction Problems with Networks of Spiking Neurons
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. PMID:27065785
Solving Constraint Satisfaction Problems with Networks of Spiking Neurons.
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. PMID:27065785
Silva, Romesh
2012-01-01
Background Given the lack of complete vital registration data in most developing countries, for many countries it is not possible to accurately estimate under-five mortality rates from vital registration systems. Heavy reliance is often placed on direct and indirect methods for analyzing data collected from birth histories to estimate under-five mortality rates. Yet few systematic comparisons of these methods have been undertaken. This paper investigates whether analysts should use both direct and indirect estimates from full birth histories, and under what circumstances indirect estimates derived from summary birth histories should be used. Methods and Findings Usings Demographic and Health Surveys data from West Africa, East Africa, Latin America, and South/Southeast Asia, I quantify the differences between direct and indirect estimates of under-five mortality rates, analyze data quality issues, note the relative effects of these issues, and test whether these issues explain the observed differences. I find that indirect estimates are generally consistent with direct estimates, after adjustment for fertility change and birth transference, but don't add substantial additional insight beyond direct estimates. However, choice of direct or indirect method was found to be important in terms of both the adjustment for data errors and the assumptions made about fertility. Conclusions Although adjusted indirect estimates are generally consistent with adjusted direct estimates, some notable inconsistencies were observed for countries that had experienced either a political or economic crisis or stalled health transition in their recent past. This result suggests that when a population has experienced a smooth mortality decline or only short periods of excess mortality, both adjusted methods perform equally well. However, the observed inconsistencies identified suggest that the indirect method is particularly prone to bias resulting from violations of its strong
Watrous, Matthew G; Delmore, James E; Hague, Robert K; Houghton, Tracy P; Jenson, Douglas D; Mann, Nick R
2015-12-01
Four of the radioactive xenon isotopes ((131m)Xe, (133m)Xe, (133)Xe and (135)Xe) with half-lives ranging from 9 h to 12 days are produced from nuclear fission and can be detected from days to weeks following their production and release. Being inert gases, they are readily transported through the atmosphere. Sources for release of radioactive xenon isotopes include operating nuclear reactors via leaks in fuel rods, medical isotope production facilities, and nuclear weapons' detonations. They are not normally released from fuel reprocessing due to the short half-lives. The Comprehensive Nuclear-Test-Ban Treaty has led to creation of the International Monitoring System. The International Monitoring System, when fully implemented, will consist of one component with 40 stations monitoring radioactive xenon around the globe. Monitoring these radioactive xenon isotopes is important to the Comprehensive Nuclear-Test-Ban Treaty in determining whether a seismically detected event is or is not a nuclear detonation. A variety of radioactive xenon quality control check standards, quantitatively spiked into various gas matrices, could be used to demonstrate that these stations are operating on the same basis in order to bolster defensibility of data across the International Monitoring System. This paper focuses on Idaho National Laboratory's capability to produce three of the xenon isotopes in pure form and the use of the four xenon isotopes in various combinations to produce radioactive xenon spiked air samples that could be subsequently distributed to participating facilities. PMID:26318775
Watrous, Matthew G.; Delmore, James E.; Hague, Robert K.; Houghton, Tracy P.; Jenson, Douglas D.; Mann, Nick R.
2015-08-27
Four of the radioactive xenon isotopes (131mXe, 133mXe, 133Xe and 135Xe) with half-lives ranging from 9 h to 12 days are produced from nuclear fission and can be detected from days to weeks following their production and release. Being inert gases, they are readily transported through the atmosphere. Sources for release of radioactive xenon isotopes include operating nuclear reactors via leaks in fuel rods, medical isotope production facilities, and nuclear weapons' detonations. They are not normally released from fuel reprocessing due to the short half-lives. The Comprehensive Nuclear-Test-Ban Treaty has led to creation of the International Monitoring System. The Internationalmore » Monitoring System, when fully implemented, will consist of one component with 40 stations monitoring radioactive xenon around the globe. Monitoring these radioactive xenon isotopes is important to the Comprehensive Nuclear-Test-Ban Treaty in determining whether a seismically detected event is or is not a nuclear detonation. A variety of radioactive xenon quality control check standards, quantitatively spiked into various gas matrices, could be used to demonstrate that these stations are operating on the same basis in order to bolster defensibility of data across the International Monitoring System. This study focuses on Idaho National Laboratory's capability to produce three of the xenon isotopes in pure form and the use of the four xenon isotopes in various combinations to produce radioactive xenon spiked air samples that could be subsequently distributed to participating facilities.« less
Effects of tag loss on direct estimates of population growth rate
Rotella, J.J.; Hines, J.E.
2005-01-01
The temporal symmetry approach of R. Pradel can be used with capture-recapture data to produce retrospective estimates of a population's growth rate, lambda(i), and the relative contributions to lambda(i) from different components of the population. Direct estimation of lambda(i) provides an alternative to using population projection matrices to estimate asymptotic lambda and is seeing increased use. However, the robustness of direct estimates of lambda(1) to violations of several key assumptions has not yet been investigated. Here, we consider tag loss as a possible source of bias for scenarios in which the rate of tag loss is (1) the same for all marked animals in the population and (2) a function of tag age. We computed analytic approximations of the expected values for each of the parameter estimators involved in direct estimation and used those values to calculate bias and precision for each parameter estimator. Estimates of lambda(i) were robust to homogeneous rates of tag loss. When tag loss rates varied by tag age, bias occurred for some of the sampling situations evaluated, especially those with low capture probability, a high rate of tag loss, or both. For situations with low rates of tag loss and high capture probability, bias was low and often negligible. Estimates of contributions of demographic components to lambda(i) were not robust to tag loss. Tag loss reduced the precision of all estimates because tag loss results in fewer marked animals remaining available for estimation. Clearly tag loss should be prevented if possible, and should be considered in analyses of lambda(i), but tag loss does not necessarily preclude unbiased estimation of lambda(i).
Markov models and the ensemble Kalman filter for estimation of sorption rates.
Vugrin, Eric D.; McKenna, Sean Andrew; Vugrin, Kay White
2007-09-01
Non-equilibrium sorption of contaminants in ground water systems is examined from the perspective of sorption rate estimation. A previously developed Markov transition probability model for solute transport is used in conjunction with a new conditional probability-based model of the sorption and desorption rates based on breakthrough curve data. Two models for prediction of spatially varying sorption and desorption rates along a one-dimensional streamline are developed. These models are a Markov model that utilizes conditional probabilities to determine the rates and an ensemble Kalman filter (EnKF) applied to the conditional probability method. Both approaches rely on a previously developed Markov-model of mass transfer, and both models assimilate the observed concentration data into the rate estimation at each observation time. Initial values of the rates are perturbed from the true values to form ensembles of rates and the ability of both estimation approaches to recover the true rates is examined over three different sets of perturbations. The models accurately estimate the rates when the mean of the perturbations are zero, the unbiased case. For the cases containing some bias, addition of the ensemble Kalman filter is shown to improve accuracy of the rate estimation by as much as an order of magnitude.
Direct Magnitude Estimation of Articulation Rate in Boys with Fragile X Syndrome
ERIC Educational Resources Information Center
Zajac, David J.; Harris, Adrianne A.; Roberts, Joanne E.; Martin, Gary E.
2009-01-01
Purpose: To compare the perceived articulation rate of boys with fragile X syndrome (FXS) with that of chronologically age-matched (CA) boys and to determine segmental and/or prosodic factors that account for perceived rate. Method: Ten listeners used direct magnitude estimation procedures to judge the articulation rates of 7 boys with FXS only, 5…
NATURAL VOLATILE ORGANIC COMPOUND EMISSION RATE ESTIMATES FOR U.S. WOODLAND LANDSCAPES
Volatile organic compound (VOC) emission rate factors are estimated for 49 tree genera based on a review of foliar emission rate measurements. oliar VOC emissions are grouped into three categories: isoprene, monoterpenes and other VOC'S. ypical emission rates at a leaf temperatur...
A computer program for estimating fish population sizes and annual production rates
Railsback, S.F.; Holcomb, B.D.; Ryon, M.G.
1989-10-01
This report documents a program that estimates fish population sizes and annual production rates in small streams from multiple-pass sampling data. A maximum weighted likelihood method is used to estimate population sizes (Carle and Strub, 1978), and a size-frequency method is used to estimate production (Garman and Waters, 1983). The program performs the following steps: (1) reads in the data and performs error checking; (2) where required, uses length-weight regression to fill in missing weights; (3) assigns length classes to the fish; (4) for each date, species, and length class, estimates the population size and its variance; (5) for each date and species, estimates the total population size and its variance; and (6) for each species, estimates the annual production rate and its variance between sampling dates selected by the user. If data from only date are used, only populations are estimated. 9 refs.
Odor emission rate estimation of indoor industrial sources using a modified inverse modeling method.
Li, Xiang; Wang, Tingting; Sattayatewa, Chakkrid; Venkatesan, Dhesikan; Noll, Kenneth E; Pagilla, Krishna R; Moschandreas, Demetrios J
2011-08-01
Odor emission rates are commonly measured in the laboratory or occasionally estimated with inverse modeling techniques. A modified inverse modeling approach is used to estimate source emission rates inside of a postdigestion centrifuge building of a water reclamation plant. Conventionally, inverse modeling methods divide an indoor environment in zones on the basis of structural design and estimate source emission rates using models that assume homogeneous distribution of agent concentrations within a zone and experimentally determined link functions to simulate airflows among zones. The modified approach segregates zones as a function of agent distribution rather than building design and identifies near and far fields. Near-field agent concentrations do not satisfy the assumption of homogeneous odor concentrations; far-field concentrations satisfy this assumption and are the only ones used to estimate emission rates. The predictive ability of the modified inverse modeling approach was validated with measured emission rate values; the difference between corresponding estimated and measured odor emission rates is not statistically significant. Similarly, the difference between measured and estimated hydrogen sulfide emission rates is also not statistically significant. The modified inverse modeling approach is easy to perform because it uses odor and odorant field measurements instead of complex chamber emission rate measurements. PMID:21874959
Estimated Pregnancy Rates and Rates of Pregnancy Outcomes for the United States, 1990-2008
... of decline slowed in the mid-2000s. The teenage pregnancy rate in 2008 was the lowest reported since ... 1708–12. 2000. 24. Kost K, Henshaw S. U.S. teenage pregnancies, births, and abortions, 2008: National trends by age, ...
Constants in estimates for the rates of convergence in von Neumann's and Birkhoff's ergodic theorems
Kachurovskii, Alexander G; Sedalishchev, Vladimir V
2011-08-31
The paper investigates estimates which relate two equivalent phenomena: the power-type rate of convergence in von Neumann's ergodic theorem and the power-type singularity at zero (with the same exponent) exhibited by the spectral measure of the function being averaged with respect to the corresponding dynamical system. The same rate of convergence is also estimated in terms of the rate of decrease of the correlation coefficients. Also, constants are found in analogous estimates for the power-type convergence in Birkhoff's ergodic theorem. All the results have exact analogues for wide-sense stationary stochastic processes. Bibliography: 15 titles.
Spike Detection for Large Neural Populations Using High Density Multielectrode Arrays
Muthmann, Jens-Oliver; Amin, Hayder; Sernagor, Evelyne; Maccione, Alessandro; Panas, Dagmara; Berdondini, Luca; Bhalla, Upinder S.; Hennig, Matthias H.
2015-01-01
An emerging generation of high-density microelectrode arrays (MEAs) is now capable of recording spiking activity simultaneously from thousands of neurons with closely spaced electrodes. Reliable spike detection and analysis in such recordings is challenging due to the large amount of raw data and the dense sampling of spikes with closely spaced electrodes. Here, we present a highly efficient, online capable spike detection algorithm, and an offline method with improved detection rates, which enables estimation of spatial event locations at a resolution higher than that provided by the array by combining information from multiple electrodes. Data acquired with a 4096 channel MEA from neuronal cultures and the neonatal retina, as well as synthetic data, was used to test and validate these methods. We demonstrate that these algorithms outperform conventional methods due to a better noise estimate and an improved signal-to-noise ratio (SNR) through combining information from multiple electrodes. Finally, we present a new approach for analyzing population activity based on the characterization of the spatio-temporal event profile, which does not require the isolation of single units. Overall, we show how the improved spatial resolution provided by high density, large scale MEAs can be reliably exploited to characterize activity from large neural populations and brain circuits. PMID:26733859
Rayleigh--Taylor spike evaporation
Schappert, G. T.; Batha, S. H.; Klare, K. A.; Hollowell, D. E.; Mason, R. J.
2001-09-01
Laser-based experiments have shown that Rayleigh--Taylor (RT) growth in thin, perturbed copper foils leads to a phase dominated by narrow spikes between thin bubbles. These experiments were well modeled and diagnosed until this '' spike'' phase, but not into this spike phase. Experiments were designed, modeled, and performed on the OMEGA laser [T. R. Boehly, D. L. Brown, R. S. Craxton , Opt. Commun. 133, 495 (1997)] to study the late-time spike phase. To simulate the conditions and evolution of late time RT, a copper target was fabricated consisting of a series of thin ridges (spikes in cross section) 150 {mu}m apart on a thin flat copper backing. The target was placed on the side of a scale-1.2 hohlraum with the ridges pointing into the hohlraum, which was heated to 190 eV. Side-on radiography imaged the evolution of the ridges and flat copper backing into the typical RT bubble and spike structure including the '' mushroom-like feet'' on the tips of the spikes. RAGE computer models [R. M. Baltrusaitis, M. L. Gittings, R. P. Weaver, R. F. Benjamin, and J. M. Budzinski, Phys. Fluids 8, 2471 (1996)] show the formation of the '' mushrooms,'' as well as how the backing material converges to lengthen the spike. The computer predictions of evolving spike and bubble lengths match measurements fairly well for the thicker backing targets but not for the thinner backings.
Estimation of uncertainty in tracer gas measurement of air change rates.
Iizuka, Atsushi; Okuizumi, Yumiko; Yanagisawa, Yukio
2010-12-01
Simple and economical measurement of air change rates can be achieved with a passive-type tracer gas doser and sampler. However, this is made more complex by the fact many buildings are not a single fully mixed zone. This means many measurements are required to obtain information on ventilation conditions. In this study, we evaluated the uncertainty of tracer gas measurement of air change rate in n completely mixed zones. A single measurement with one tracer gas could be used to simply estimate the air change rate when n = 2. Accurate air change rates could not be obtained for n ≥ 2 due to a lack of information. However, the proposed method can be used to estimate an air change rate with an accuracy of <33%. Using this method, overestimation of air change rate can be avoided. The proposed estimation method will be useful in practical ventilation measurements. PMID:21318005
The manuscript reviews the issues concerning the use of results on pesticide effects from laboratory avian reproduction tests for estimating potential impacts of pesticides on fecundity rates in avian population models.
A GIS TECHNIQUE FOR ESTIMATING NATURAL ATTENUATION RATES AND MASS BALANCES: JOURNAL ARTICLE
NRMRL-ADA-01308 Durant, ND, Srinivasan, P, Faust, CR, Burnell, DK, Klein, KL, and Burden*, D.S. A GIS Technique for Estimating Natural Attenuation Rates and Mass Balances. Battelle's Sixth International ...