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Rusu, Cătălin V., et Răzvan V. Florian. « A New Class of Metrics for Spike Trains ». Neural Computation 26, no 2 (février 2014) : 306–48. http://dx.doi.org/10.1162/neco_a_00545.
Texte intégralRésumé :
The distance between a pair of spike trains, quantifying the differences between them, can be measured using various metrics. Here we introduce a new class of spike train metrics, inspired by the Pompeiu-Hausdorff distance, and compare them with existing metrics. Some of our new metrics (the modulus-metric and the max-metric) have characteristics that are qualitatively different from those of classical metrics like the van Rossum distance or the Victor and Purpura distance. The modulus-metric and the max-metric are particularly suitable for measuring distances between spike trains where information is encoded in bursts, but the number and the timing of spikes inside a burst do not carry information. The modulus-metric does not depend on any parameters and can be computed using a fast algorithm whose time depends linearly on the number of spikes in the two spike trains. We also introduce localized versions of the new metrics, which could have the biologically relevant interpretation of measuring the differences between spike trains as they are perceived at a particular moment in time by a neuron receiving these spike trains.
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Ciba, Manuel, Robert Bestel, Christoph Nick, Guilherme Ferraz de Arruda, Thomas Peron, Comin César Henrique, Luciano da Fontoura Costa, Francisco Aparecido Rodrigues et Christiane Thielemann. « Comparison of Different Spike Train Synchrony Measures Regarding Their Robustness to Erroneous Data From Bicuculline-Induced Epileptiform Activity ». Neural Computation 32, no 5 (mai 2020) : 887–911. http://dx.doi.org/10.1162/neco_a_01277.
Texte intégralRésumé :
As synchronized activity is associated with basic brain functions and pathological states, spike train synchrony has become an important measure to analyze experimental neuronal data. Many measures of spike train synchrony have been proposed, but there is no gold standard allowing for comparison of results from different experiments. This work aims to provide guidance on which synchrony measure is best suited to quantify the effect of epileptiform-inducing substances (e.g., bicuculline, BIC) in in vitro neuronal spike train data. Spike train data from recordings are likely to suffer from erroneous spike detection, such as missed spikes (false negative) or noise (false positive). Therefore, different timescale-dependent (cross-correlation, mutual information, spike time tiling coefficient) and timescale-independent (Spike-contrast, phase synchronization (PS), A-SPIKE-synchronization, A-ISI-distance, ARI-SPIKE-distance) synchrony measures were compared in terms of their robustness to erroneous spike trains. For this purpose, erroneous spike trains were generated by randomly adding (false positive) or deleting (false negative) spikes (in silico manipulated data) from experimental data. In addition, experimental data were analyzed using different spike detection threshold factors in order to confirm the robustness of the synchrony measures. All experimental data were recorded from cortical neuronal networks on microelectrode array chips, which show epileptiform activity induced by the substance BIC. As a result of the in silico manipulated data, Spike-contrast was the only measure that was robust to false-negative as well as false-positive spikes. Analyzing the experimental data set revealed that all measures were able to capture the effect of BIC in a statistically significant way, with Spike-contrast showing the highest statistical significance even at low spike detection thresholds. In summary, we suggest using Spike-contrast to complement established synchrony measures because it is timescale independent and robust to erroneous spike trains.
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Kreuz, Thomas, Daniel Chicharro, Conor Houghton, Ralph G. Andrzejak et Florian Mormann. « Monitoring spike train synchrony ». Journal of Neurophysiology 109, no 5 (1 mars 2013) : 1457–72. http://dx.doi.org/10.1152/jn.00873.2012.
Texte intégralRésumé :
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.
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Kreuz, Thomas, Mario Mulansky et Nebojsa Bozanic. « SPIKY : a graphical user interface for monitoring spike train synchrony ». Journal of Neurophysiology 113, no 9 (mai 2015) : 3432–45. http://dx.doi.org/10.1152/jn.00848.2014.
Texte intégralRésumé :
Techniques for recording large-scale neuronal spiking activity are developing very fast. This leads to an increasing demand for algorithms capable of analyzing large amounts of experimental spike train data. One of the most crucial and demanding tasks is the identification of similarity patterns with a very high temporal resolution and across different spatial scales. To address this task, in recent years three time-resolved measures of spike train synchrony have been proposed, the ISI-distance, the SPIKE-distance, and event synchronization. The Matlab source codes for calculating and visualizing these measures have been made publicly available. However, due to the many different possible representations of the results the use of these codes is rather complicated and their application requires some basic knowledge of Matlab. Thus it became desirable to provide a more user-friendly and interactive interface. Here we address this need and present SPIKY, a graphical user interface that facilitates the application of time-resolved measures of spike train synchrony to both simulated and real data. SPIKY includes implementations of the ISI-distance, the SPIKE-distance, and the SPIKE-synchronization (an improved and simplified extension of event synchronization) that have been optimized with respect to computation speed and memory demand. It also comprises a spike train generator and an event detector that makes it capable of analyzing continuous data. Finally, the SPIKY package includes additional complementary programs aimed at the analysis of large numbers of datasets and the estimation of significance levels.
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Paiva, António R. C., Il Park et José C. Príncipe. « A Reproducing Kernel Hilbert Space Framework for Spike Train Signal Processing ». Neural Computation 21, no 2 (février 2009) : 424–49. http://dx.doi.org/10.1162/neco.2008.09-07-614.
Texte intégralRésumé :
This letter presents a general framework based on reproducing kernel Hilbert spaces (RKHS) to mathematically describe and manipulate spike trains. The main idea is the definition of inner products to allow spike train signal processing from basic principles while incorporating their statistical description as point processes. Moreover, because many inner products can be formulated, a particular definition can be crafted to best fit an application. These ideas are illustrated by the definition of a number of spike train inner products. To further elicit the advantages of the RKHS framework, a family of these inner products, the cross-intensity (CI) kernels, is analyzed in detail. This inner product family encapsulates the statistical description from the conditional intensity functions of spike trains. The problem of their estimation is also addressed. The simplest of the spike train kernels in this family provide an interesting perspective to others' work, as will be demonstrated in terms of spike train distance measures. Finally, as an application example, the RKHS framework is used to derive a clustering algorithm for spike trains from simple principles.
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Adamatzky, Andrew, Alessandro Chiolerio et Georgios Sirakoulis. « Electrical Resistive Spiking of Fungi ». Biophysical Reviews and Letters 16, no 01 (21 janvier 2021) : 1–7. http://dx.doi.org/10.1142/s1793048021500016.
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We study long-term electrical resistance dynamics in mycelium and fruit bodies of oyster fungi P. ostreatus. A nearly homogeneous sheet of mycelium on the surface of a growth substrate exhibits trains of resistance spikes. The average width of spikes is c. 23[Formula: see text]min and the average amplitude is c. 1[Formula: see text]k[Formula: see text]. The distance between neighboring spikes in a train of spikes is c. 30[Formula: see text]min. Typically, there are 4–6 spikes in a train of spikes. Two types of electrical resistance spikes trains are found in fruit bodies: low frequency and high amplitude (28[Formula: see text]min spike width, 1.6[Formula: see text]k[Formula: see text] amplitude, 57[Formula: see text]min distance between spikes) and high frequency and low amplitude (10[Formula: see text]min width, 0.6[Formula: see text]k[Formula: see text] amplitude, 44[Formula: see text]min distance between spikes). The findings could be applied in monitoring of physiological states of fungi and future development of living electronic devices and sensors.
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Houghton, Conor, et Kamal Sen. « A New Multineuron Spike Train Metric ». Neural Computation 20, no 6 (juin 2008) : 1495–511. http://dx.doi.org/10.1162/neco.2007.10-06-350.
Texte intégralRésumé :
The Victor-Purpura spike train metric has recently been extended to a family of multineuron metrics and used to analyze spike trains recorded simultaneously from pairs of proximate neurons. The metric is one of the two metrics commonly used for quantifying the distance between two spike trains; the other is the van Rossum metric. Here, we suggest an extension of the van Rossum metric to a multineuron metric. We believe this gives a metric that is both natural and easy to calculate. Both types of multineuron metric are applied to simulated data and are compared.
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Chen, Yan, Vitaliy Marchenko et Robert F. Rogers. « Joint Probability-Based Neuronal Spike Train Classification ». Computational and Mathematical Methods in Medicine 10, no 3 (2009) : 229–39. http://dx.doi.org/10.1080/17486700802448615.
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Neuronal spike trains are used by the nervous system to encode and transmit information. Euclidean distance-based methods (EDBMs) have been applied to quantify the similarity between temporally-discretized spike trains and model responses. In this study, using the same discretization procedure, we developed and applied a joint probability-based method (JPBM) to classify individual spike trains of slowly adapting pulmonary stretch receptors (SARs). The activity of individual SARs was recorded in anaesthetized, paralysed adult male rabbits, which were artificially-ventilated at constant rate and one of three different volumes. Two-thirds of the responses to the 600 stimuli presented at each volume were used to construct three response models (one for each stimulus volume) consisting of a series of time bins, each with spike probabilities. The remaining one-third of the responses where used as test responses to be classified into one of the three model responses. This was done by computing the joint probability of observing the same series of events (spikes or no spikes, dictated by the test response) in a given model and determining which probability of the three was highest. The JPBM generally produced better classification accuracy than the EDBM, and both performed well above chance. Both methods were similarly affected by variations in discretization parameters, response epoch duration, and two different response alignment strategies. Increasing bin widths increased classification accuracy, which also improved with increased observation time, but primarily during periods of increasing lung inflation. Thus, the JPBM is a simple and effective method performing spike train classification.
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Brasselet, Romain, Roland S. Johansson et Angelo Arleo. « Quantifying Neurotransmission Reliability Through Metrics-Based Information Analysis ». Neural Computation 23, no 4 (avril 2011) : 852–81. http://dx.doi.org/10.1162/neco_a_00099.
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We set forth an information-theoretical measure to quantify neurotransmission reliability while taking into full account the metrical properties of the spike train space. This parametric information analysis relies on similarity measures induced by the metrical relations between neural responses as spikes flow in. Thus, in order to assess the entropy, the conditional entropy, and the overall information transfer, this method does not require any a priori decoding algorithm to partition the space into equivalence classes. It therefore allows the optimal parameters of a class of distances to be determined with respect to information transmission. To validate the proposed information-theoretical approach, we study precise temporal decoding of human somatosensory signals recorded using microneurography experiments. For this analysis, we employ a similarity measure based on the Victor-Purpura spike train metrics. We show that with appropriate parameters of this distance, the relative spike times of the mechanoreceptors’ responses convey enough information to perform optimal discrimination—defined as maximum metrical information and zero conditional entropy—of 81 distinct stimuli within 40 ms of the first afferent spike. The proposed information-theoretical measure proves to be a suitable generalization of Shannon mutual information in order to consider the metrics of temporal codes explicitly. It allows neurotransmission reliability to be assessed in the presence of large spike train spaces (e.g., neural population codes) with high temporal precision.
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Itskov, Vladimir, Carina Curto et Kenneth D. Harris. « Valuations for Spike Train Prediction ». Neural Computation 20, no 3 (mars 2008) : 644–67. http://dx.doi.org/10.1162/neco.2007.3179.
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The ultimate product of an electrophysiology experiment is often a decision on which biological hypothesis or model best explains the observed data. We outline a paradigm designed for comparison of different models, which we refer to as spike train prediction. A key ingredient of this paradigm is a prediction quality valuation that estimates how close a predicted conditional intensity function is to an actual observed spike train. Although a valuation based on log likelihood (L) is most natural, it has various complications in this context. We propose that a quadratic valuation (Q) can be used as an alternative to L. Q shares some important theoretical properties with L, including consistency, and the two valuations perform similarly on simulated and experimental data. Moreover, Q is more robust than L, and optimization with Q can dramatically improve computational efficiency. We illustrate the utility of Q for comparing models of peer prediction, where it can be computed directly from cross-correlograms. Although Q does not have a straightforward probabilistic interpretation, Q is essentially given by Euclidean distance.
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Koyama, Shinsuke, et Robert E. Kass. « Spike Train Probability Models for Stimulus-Driven Leaky Integrate-and-Fire Neurons ». Neural Computation 20, no 7 (juillet 2008) : 1776–95. http://dx.doi.org/10.1162/neco.2008.06-07-540.
Texte intégralRésumé :
Mathematical models of neurons are widely used to improve understanding of neuronal spiking behavior. These models can produce artificial spike trains that resemble actual spike train data in important ways, but they are not very easy to apply to the analysis of spike train data. Instead, statistical methods based on point process models of spike trains provide a wide range of data-analytical techniques. Two simplified point process models have been introduced in the literature: the time-rescaled renewal process (TRRP) and the multiplicative inhomogeneous Markov interval (m-IMI) model. In this letter we investigate the extent to which the TRRP and m-IMI models are able to fit spike trains produced by stimulus-driven leaky integrate-and-fire (LIF) neurons. With a constant stimulus, the LIF spike train is a renewal process, and the m-IMI and TRRP models will describe accurately the LIF spike train variability. With a time-varying stimulus, the probability of spiking under all three of these models depends on both the experimental clock time relative to the stimulus and the time since the previous spike, but it does so differently for the LIF, m-IMI, and TRRP models. We assessed the distance between the LIF model and each of the two empirical models in the presence of a time-varying stimulus. We found that while lack of fit of a Poisson model to LIF spike train data can be evident even in small samples, the m-IMI and TRRP models tend to fit well, and much larger samples are required before there is statistical evidence of lack of fit of the m-IMI or TRRP models. We also found that when the mean of the stimulus varies across time, the m-IMI model provides a better fit to the LIF data than the TRRP, and when the variance of the stimulus varies across time, the TRRP provides the better fit.
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Vargas-Irwin, Carlos E., David M. Brandman, Jonas B. Zimmermann, John P. Donoghue et Michael J. Black. « Spike Train SIMilarity Space (SSIMS) : A Framework for Single Neuron and Ensemble Data Analysis ». Neural Computation 27, no 1 (janvier 2015) : 1–31. http://dx.doi.org/10.1162/neco_a_00684.
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Increased emphasis on circuit level activity in the brain makes it necessary to have methods to visualize and evaluate large-scale ensemble activity beyond that revealed by raster-histograms or pairwise correlations. We present a method to evaluate the relative similarity of neural spiking patterns by combining spike train distance metrics with dimensionality reduction. Spike train distance metrics provide an estimate of similarity between activity patterns at multiple temporal resolutions. Vectors of pair-wise distances are used to represent the intrinsic relationships between multiple activity patterns at the level of single units or neuronal ensembles. Dimensionality reduction is then used to project the data into concise representations suitable for clustering analysis as well as exploratory visualization. Algorithm performance and robustness are evaluated using multielectrode ensemble activity data recorded in behaving primates. We demonstrate how spike train SIMilarity space (SSIMS) analysis captures the relationship between goal directions for an eight-directional reaching task and successfully segregates grasp types in a 3D grasping task in the absence of kinematic information. The algorithm enables exploration of virtually any type of neural spiking (time series) data, providing similarity-based clustering of neural activity states with minimal assumptions about potential information encoding models.
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Tomas, P., et L. Sousa. « Statistical Analysis of a Spike Train Distance in Poisson Models ». IEEE Signal Processing Letters 15 (2008) : 357–60. http://dx.doi.org/10.1109/lsp.2008.919994.
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Du, Ying, Rubin Wang et Jingyi Qu. « Noise and Synchronization Analysis of the Cold-Receptor Neuronal Network Model ». Discrete Dynamics in Nature and Society 2014 (2014) : 1–8. http://dx.doi.org/10.1155/2014/173894.
Texte intégralRésumé :
This paper analyzes the dynamics of the cold receptor neural network model. First, it examines noise effects on neuronal stimulus in the model. FromISIplots, it is shown that there are considerable differences between purely deterministic simulations and noisy ones. TheISI-distance is used to measure the noise effects on spike trains quantitatively. It is found that spike trains observed in neural models can be more strongly affected by noise for different temperatures in some aspects; meanwhile, spike train has greater variability with the noise intensity increasing. The synchronization of neuronal network with different connectivity patterns is also studied. It is shown that chaotic and high period patterns are more difficult to get complete synchronization than the situation in single spike and low period patterns. The neuronal network will exhibit various patterns of firing synchronization by varying some key parameters such as the coupling strength. Different types of firing synchronization are diagnosed by a correlation coefficient and theISI-distance method. The simulations show that the synchronization status of neurons is related to the network connectivity patterns.
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Larson, Eric, Cyrus P. Billimoria et Kamal Sen. « A Biologically Plausible Computational Model for Auditory Object Recognition ». Journal of Neurophysiology 101, no 1 (janvier 2009) : 323–31. http://dx.doi.org/10.1152/jn.90664.2008.
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Object recognition is a task of fundamental importance for sensory systems. Although this problem has been intensively investigated in the visual system, relatively little is known about the recognition of complex auditory objects. Recent work has shown that spike trains from individual sensory neurons can be used to discriminate between and recognize stimuli. Multiple groups have developed spike similarity or dissimilarity metrics to quantify the differences between spike trains. Using a nearest-neighbor approach the spike similarity metrics can be used to classify the stimuli into groups used to evoke the spike trains. The nearest prototype spike train to the tested spike train can then be used to identify the stimulus. However, how biological circuits might perform such computations remains unclear. Elucidating this question would facilitate the experimental search for such circuits in biological systems, as well as the design of artificial circuits that can perform such computations. Here we present a biologically plausible model for discrimination inspired by a spike distance metric using a network of integrate-and-fire model neurons coupled to a decision network. We then apply this model to the birdsong system in the context of song discrimination and recognition. We show that the model circuit is effective at recognizing individual songs, based on experimental input data from field L, the avian primary auditory cortex analog. We also compare the performance and robustness of this model to two alternative models of song discrimination: a model based on coincidence detection and a model based on firing rate.
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Satuvuori, Eero, et Thomas Kreuz. « Which spike train distance is most suitable for distinguishing rate and temporal coding ? » Journal of Neuroscience Methods 299 (avril 2018) : 22–33. http://dx.doi.org/10.1016/j.jneumeth.2018.02.009.
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Yi, Zhengkun, et Yilei Zhang. « A spike train distance-based method to evaluate the response of mechanoreceptive afferents ». Neural Computing and Applications 31, no 10 (29 mars 2018) : 6319–30. http://dx.doi.org/10.1007/s00521-018-3465-6.
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Kruger, J., et F. Aiple. « Multimicroelectrode investigation of monkey striate cortex : spike train correlations in the infragranular layers ». Journal of Neurophysiology 60, no 2 (1 août 1988) : 798–828. http://dx.doi.org/10.1152/jn.1988.60.2.798.
Texte intégralRésumé :
1. In the infragranular layers of the striate cortex of three monkeys, we studied tangential neuronal interactions by analyzing cross-correlograms calculated from spike trains recorded with 30 closely spaced microelectrodes. 2. There are two major types of correlogram structures--"narrow" peaks a few milliseconds wide, sometimes accompanied by small lateral troughs, and "broad" peaks approximately 30- to 100-ms wide. Isolated troughs are rare. Both types of structures are superimposed in the same correlograms; they are not due to shared optical stimulation. 3. In layer VI, narrow peaks are largest in a short lateral range of approximately 220 micron, and they depend on ocularity. In layer V, the lateral range is greater, and the dependency on ocularity is weak. 4. In addition, narrow peaks are largest at distances of 160 micron if the angles of preferred orientation are similar. In layer VI, however, at tangential distances of 300-400 micron, peaks are smaller, and troughs are found more often, for neuron pairs with parallel orientations compared with those with orthogonal orientations. From the agreement of this finding with a cooperative theory, we conclude that orientation selectivity is shaped by collective interactions. 5. Broad peaks always depend on ocularity, and the associated lateral interaction range exceeds the maximum of 1 mm investigated. Their size sharply decreases with receptive-field distance. 6. Average mutual delays of spikes of neuron pairs, manifest as lateral displacements of broad peaks, are interdependent; the delay between neurons 1 and 3 is the sum of that of neurons 1 and 2 and of neurons 2 and 3. This feature permits to rank the neurons on a "delay scale." 7. We conclude from 5 and 6 above that broad peaks partly result from intraretinal interactions whose effects are transmitted to the cortex via slow and fast pathways. 8. Lateral troughs adjacent to narrow peaks provide evidence that neurons at the "slow" end of the delay scale inhibit those at the "fast" end, and to a lesser extent, nondirectional neurons inhibit directional ones.
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Gasparini, Sonia. « Distance- and activity-dependent modulation of spike back-propagation in layer V pyramidal neurons of the medial entorhinal cortex ». Journal of Neurophysiology 105, no 3 (mars 2011) : 1372–79. http://dx.doi.org/10.1152/jn.00014.2010.
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Layer V principal neurons of the medial entorhinal cortex receive the main hippocampal output and relay processed information to the neocortex. Despite the fundamental role hypothesized for these neurons in memory replay and consolidation, their dendritic features are largely unknown. High-speed confocal and two-photon Ca2+ imaging coupled with somatic whole cell patch-clamp recordings were used to investigate spike back-propagation in these neurons. The Ca2+ transient associated with a single back-propagating action potential was considerably smaller at distal dendritic locations (>200 μm from the soma) compared with proximal ones. Perfusion of Ba2+ (150 μM) or 4-aminopyridine (2 mM) to block A-type K+ currents significantly increased the amplitude of the distal, but not proximal, Ca2+ transients, which is strong evidence for an increased density of these channels at distal dendritic locations. In addition, the Ca2+ transients decreased with each subsequent spike in a 20-Hz train; this activity-dependent decrease was also more prominent at more distal locations and was attenuated by the perfusion of the protein kinase C activator phorbol-di-acetate. These data are consistent with a phosphorylation-dependent control of back-propagation during trains of action potentials, attributable mainly to an increase in the time constant of recovery from voltage-dependent inactivation of dendritic Na+ channels. In summary, dendritic Na+ and A-type K+ channels control spike back-propagation in layer V entorhinal neurons. Because the activity of these channels is highly modulated, the extent of the dendritic Ca2+ influx is as well, with important functional implications for dendritic integration and associative synaptic plasticity.
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Victor, J. D., et K. P. Purpura. « Nature and precision of temporal coding in visual cortex : a metric-space analysis ». Journal of Neurophysiology 76, no 2 (1 août 1996) : 1310–26. http://dx.doi.org/10.1152/jn.1996.76.2.1310.
Texte intégralRésumé :
1. We recorded single-unit and multi-unit activity in response to transient presentation of texture and grating patterns at 25 sites within the parafoveal representation of V1, V2, and V3 of two awake monkeys trained to perform a fixation task. In grating experiments, stimuli varied in orientation, spatial frequency, or both. In texture experiments, stimuli varied in contrast, check size, texture type, or pairs of these attributes. 2. To examine the nature and precision of temporal coding, we compared individual responses elicited by each set of stimuli in terms of two families of metrics. One family of metrics, D(spike), was sensitive to the absolute spike time (following stimulus onset). The second family of metrics, D(interval), was sensitive to the pattern of interspike intervals. In each family, the metrics depend on a parameter q, which expresses the precision of temporal coding. For q = 0, both metrics collapse into the "spike count" metric D(Count), which is sensitive to the number of impulses but insensitive to their position in time. 3. Each of these metrics, with values of q ranging from 0 to 512/s, was used to calculate the distance between all pairs of spike trains within each dataset. The extent of stimulus-specific clustering manifest in these pairwise distances was quantified by an information measure. Chance clustering was estimated by applying the same procedure to synthetic data sets in which responses were assigned randomly to the input stimuli. 4. Of the 352 data sets, 170 showed evidence of tuning via the spike count (q = 0) metric, 294 showed evidence of tuning via the spike time metric, 272 showed evidence of tuning via the spike interval metric to the stimulus attribute (contrast, check size, orientation, spatial frequency, or texture type) under study. Across the entire dataset, the information not attributable to chance clustering averaged 0.042 bits for the spike count metric, 0.171 bits for the optimal spike time metric, and 0.107 bits for the optimal spike interval metric. 5. The reciprocal of the optimal cost q serves as a measure of the temporal precision of temporal coding. In V1 and V2, with both metrics, temporal precision was highest for contrast (ca. 10-30 ms) and lowest for texture type (ca. 100 ms). This systematic dependence of q on stimulus attribute provides a possible mechanism for the simultaneous representation of multiple stimulus attributes in one spike train. 6. Our findings are inconsistent with Poisson models of spike trains. Synthetic data sets in which firing rate was governed by a time-dependent Poisson process matched to the observed poststimulus time histogram (PSTH) overestimated clustering induced by D(count) and, for low values of q, D(spike)[q] and D(intervals)[q]. Synthetic data sets constructed from a modified Poisson process, which preserved not only the PSTH but also spike count statistics accounted for the clustering induced by D(count) but underestimated the clustering induced by D(spike)[q] and D(interval)[q].
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Colbert, Costa M., et Daniel Johnston. « Protein Kinase C Activation Decreases Activity-Dependent Attenuation of Dendritic Na+ Current in Hippocampal CA1 Pyramidal Neurons ». Journal of Neurophysiology 79, no 1 (1 janvier 1998) : 491–95. http://dx.doi.org/10.1152/jn.1998.79.1.491.
Texte intégralRésumé :
Colbert, Costa M. and Daniel Johnston. Protein kinase C activation decreases activity-dependent attenuation of dendritic Na+ current in hippocampal CA1 pyramidal neurons. J. Neurophysiol. 79: 491–495, 1998. Action potentials recorded from the soma of CA1 pyramidal neurons remain relatively uniform in amplitude during repetitive firing. In contrast, the amplitudes of back-propagating action potentials in dendrites decrease progressively during a spike train. This activity-dependent decrease in amplitude is dependent on the frequency of firing during the train and distance from the soma. Previously, we described a property of Na+ channels that provides a plausible mechanism for the activity dependence of the amplitude of the dendritic action potentials: available Na+ current decreases during trains of action potentials through an inactivation, distinct from fast inactivation, that appears rapid in onset, but slow and voltage-dependent in its recovery. In this study we found that activation of protein kinase C by phorbol esters decreased this activity-dependent inactivation of pharmacologically isolated Na+ current in cell-attached dendritic, but not somatic, patches. Similarly in whole cell recordings phorbol esters decreased the attenuation of back-propagating dendritic action potentials during trains. These results indicate a novel effect of protein kinase C on the dendritic Na+ channel and further support the hypothesis that the activity dependence of the dendritic action potentials is derived from the inactivation properties of Na+ channels.
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Brockmeier, Austin J., John S. Choi, Evan G. Kriminger, Joseph T. Francis et Jose C. Principe. « Neural Decoding with Kernel-Based Metric Learning ». Neural Computation 26, no 6 (juin 2014) : 1080–107. http://dx.doi.org/10.1162/neco_a_00591.
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In studies of the nervous system, the choice of metric for the neural responses is a pivotal assumption. For instance, a well-suited distance metric enables us to gauge the similarity of neural responses to various stimuli and assess the variability of responses to a repeated stimulus—exploratory steps in understanding how the stimuli are encoded neurally. Here we introduce an approach where the metric is tuned for a particular neural decoding task. Neural spike train metrics have been used to quantify the information content carried by the timing of action potentials. While a number of metrics for individual neurons exist, a method to optimally combine single-neuron metrics into multineuron, or population-based, metrics is lacking. We pose the problem of optimizing multineuron metrics and other metrics using centered alignment, a kernel-based dependence measure. The approach is demonstrated on invasively recorded neural data consisting of both spike trains and local field potentials. The experimental paradigm consists of decoding the location of tactile stimulation on the forepaws of anesthetized rats. We show that the optimized metrics highlight the distinguishing dimensions of the neural response, significantly increase the decoding accuracy, and improve nonlinear dimensionality reduction methods for exploratory neural analysis.
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Ojakangas, C. L., et T. J. Ebner. « Purkinje cell complex spike activity during voluntary motor learning : relationship to kinematics ». Journal of Neurophysiology 72, no 6 (1 décembre 1994) : 2617–30. http://dx.doi.org/10.1152/jn.1994.72.6.2617.
Texte intégralRésumé :
1. We examined the relationship of cerebellar Purkinje cell discharge to the scaling of kinematics during a voluntary motor learning paradigm. The study focused on whether the occurrence of complex spike (CS) discharge was associated with kinematic changes. Two primates (Macaca mulatta) were trained to move a cursor using a two-joint manipulandum over a horizontal video screen from a start target to one of four target boxes. The relationship between the cursor and the hand (gain) was changed, requiring scaling of movement distance to complete the task. As previously described, when the novel gain was presented over 100-200 movement trials the animals adapted their movements by using a strategy of scaling the amplitude and velocity of the first phase of the movement while keeping time to peak velocity constant. 2. The paradigm consisted of four different phases. A control phase at a gain of 1.0 was initially performed. The learning phase over the next 180-210 movements used one of four gains (0.6, 0.75, 1.5, or 2.0). Last, a testing phase involved 80% of 100 trials at the learned gain and 20% of the trials at the control gain of 1.0. The distance control phase consisted of using a gain of 1.0 but having the animal move to targets placed at the distance and direction the hand moved in the adapted state. 3. Simple spikes (SSs) and CSs of 141 Purkinje cells recorded primarily in the intermediate and lateral regions of zones V and VI in three cerebellar hemispheres from the two primates were recorded during the distance control, control, learning, and testing phases. Some cells were recorded in lobule VII and Crus I. CS activity increased during the learning phase, as documented previously. The increase in CS discharge occurred before or during the first 200-300 ms of the movement. This is the same time period in which the kinematic changes necessary for adaptation to the novel gain occur. Of 141 Purkinje cells recorded during the learning paradigm, 104 (74%) demonstrated significant increases in CS firing rate during the learning-testing phase. Of these 104 cells, 82 had statistically significant SS modulation. 4. Movement trials with CSs were separated from the trials without CSs. Aligning the kinematic and spike train data on movement onset, the average velocity profiles were subtracted from each other and a strict statistical criterion applied to test for the significance of any differences. Movement trials randomly sorted into two groups served as a control.(ABSTRACT TRUNCATED AT 400 WORDS)
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Lee, J. C. F., J. C. Callaway et R. C. Foehring. « Effects of Temperature on Calcium Transients and Ca2+-Dependent Afterhyperpolarizations in Neocortical Pyramidal Neurons ». Journal of Neurophysiology 93, no 4 (avril 2005) : 2012–20. http://dx.doi.org/10.1152/jn.01017.2004.
Texte intégralRésumé :
In neocortical pyramidal neurons, the medium (mAHP) and slow AHP (sAHP) have different relationships with intracellular [Ca2+]. To further explore these differences, we varied bath temperature and compared passive and active membrane properties and Ca2+ transients in response to a single action potential (AP) or trains of APs. We tested whether Ca2+-dependent events are more temperature sensitive than voltage-dependent ones, the slow rise time of the sAHP is limited by diffusion, and temperature sensitivity differs between the mAHP and sAHP. The onset and decay kinetics of the sAHP were very temperature sensitive (more so than diffusion). We found that the decay time course of Ca2+ transients was also very temperature sensitive. In contrast, the mAHP (amplitude, time to peak, and exponential decay) and sAHP peak amplitude were moderately sensitive to temperature. The amplitudes of intracellular Ca2+ transients evoked either by a single spike or a train of spikes showed modest temperature sensitivities. Pyramidal neuron input resistance was increased by cooling. With the exception of threshold, which remained unchanged between 22 and 35°C, action potential parameters (amplitude, half-width, maximum rates of rise and fall) were modestly affected by temperature. Collectively, these data suggest that temperature sensitivity was higher for the Ca2+-dependent sAHP than for voltage-dependent AP parameters or for the mAHP, diffusion of Ca2+ over distance cannot explain the slow rise of the sAHP in these cells, and the kinetics of the sAHP and mAHP are affected differently by temperature.
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Wohlgemuth, Sandra, et Bernhard Ronacher. « Auditory Discrimination of Amplitude Modulations Based on Metric Distances of Spike Trains ». Journal of Neurophysiology 97, no 4 (avril 2007) : 3082–92. http://dx.doi.org/10.1152/jn.01235.2006.
Texte intégralRésumé :
Sound envelope cues play a crucial role for the recognition and discrimination of communication signals in diverse taxa, such as vertebrates and arthropods. Using a classification based on metric similarities of spike trains we investigate how well amplitude modulations (AMs) of sound signals can be distinguished at three levels of the locust's auditory pathway: receptors and local and ascending neurons. The spike train metric has the advantage of providing information about the necessary evaluation time window and about the optimal temporal resolution of processing, thereby yielding clues to possible coding principles. It further allows one to disentangle the respective contributions of spike count and spike timing to the fidelity of discrimination. These results are compared with the traditional paradigm using modulation transfer functions. Spike trains of receptors and two primary-like local interneurons enable an excellent discrimination of different AM frequencies, up to about 150 Hz. In these neurons discriminability depends almost completely on the timing of spikes, which must be evaluated with a temporal resolution of <5 ms. Even short spike-train segments of 150 ms, equivalent to five to eight spikes, suffice for a high (70%) discrimination performance. For the third level of processing, the ascending interneurons, the overall discrimination accuracy is reduced. Spike count differences become more important for the discrimination whereas the exact timing of spikes contributes less. This shift in temporal resolution does not primarily depend on the investigated stimulus space. Rather it appears to reflect a transformation of how amplitude modulations are represented at more central stages of processing.
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El-Laithy, Karim, et Martin Bogdan. « A Reinforcement Learning Framework for Spiking Networks with Dynamic Synapses ». Computational Intelligence and Neuroscience 2011 (2011) : 1–12. http://dx.doi.org/10.1155/2011/869348.
Texte intégralRésumé :
An integration of both the Hebbian-based and reinforcement learning (RL) rules is presented for dynamic synapses. The proposed framework permits the Hebbian rule to update the hidden synaptic model parameters regulating the synaptic response rather than the synaptic weights. This is performed using both the value and the sign of the temporal difference in the reward signal after each trial. Applying this framework, a spiking network with spike-timing-dependent synapses is tested to learn the exclusive-OR computation on a temporally coded basis. Reward values are calculated with the distance between the output spike train of the network and a reference target one. Results show that the network is able to capture the required dynamics and that the proposed framework can reveal indeed an integrated version of Hebbian and RL. The proposed framework is tractable and less computationally expensive. The framework is applicable to a wide class of synaptic models and is not restricted to the used neural representation. This generality, along with the reported results, supports adopting the introduced approach to benefit from the biologically plausible synaptic models in a wide range of intuitive signal processing.
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Mata, Mario L., et Dario L. Ringach. « Spatial Overlap of on and off Subregions and Its Relation to Response Modulation Ratio in Macaque Primary Visual Cortex ». Journal of Neurophysiology 93, no 2 (février 2005) : 919–28. http://dx.doi.org/10.1152/jn.00668.2004.
Texte intégralRésumé :
We studied the spatial overlap of on and off subregions in macaque primary visual cortex and its relation to the response modulation ratio (the F1/ F0 ratio). Spatial maps of on and off subregions were obtained by reverse correlation with a dynamic noise pattern of bright and dark spots. Two spatial maps, on and off, were produced by cross-correlating the spike train with the location of bright and dark spots in the stimulus respectively. Several measures were used to assess the degree of overlap between subregions. In a subset of neurons, we also computed the F1/ F0 ratio in response to drifting sinusoidal gratings. Significant correlations were found among all the overlap measures and the F1/ F0 ratio. Most overlap indices considered, and the F1/ F0 measure, had bimodal distributions. In contrast, the distance between on and off subregions normalized by their size was unimodal. Surprisingly, a simple model that additively combines on and off subregions with spatial separations drawn from a unimodal distribution, can readily explain the data. These analyses clarify the relationship between subregion overlap and the F1/ F0 ratio in macaque primary visual cortex, and a simple model provides a parsimonious explanation for the co-existence of bimodal distributions of overlap indices and a unimodal distribution of the normalized distance.
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Dubbs, Alexander J., Brad A. Seiler et Marcelo O. Magnasco. « A Fast ℒp Spike Alignment Metric ». Neural Computation 22, no 11 (novembre 2010) : 2785–808. http://dx.doi.org/10.1162/neco_a_00026.
Texte intégralRésumé :
The metrization of the space of neural responses is an ongoing research program seeking to find natural ways to describe, in geometrical terms, the sets of possible activities in the brain. One component of this program is spike metrics—notions of distance between two spike trains recorded from a neuron. Alignment spike metrics work by identifying “equivalent” spikes in both trains. We present an alignment spike metric having [Formula: see text] underlying geometrical structure; the [Formula: see text] version is Euclidean and is suitable for further embedding in Euclidean spaces by multidimensional scaling methods or related procedures. We show how to implement a fast algorithm for the computation of this metric based on bipartite graph matching theory.
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Rossum, M. C. W. van. « A Novel Spike Distance ». Neural Computation 13, no 4 (1 avril 2001) : 751–63. http://dx.doi.org/10.1162/089976601300014321.
Texte intégralRésumé :
The discrimination between two spike trains is a fundamental problem for both experimentalists and the nervous system itself. We introduce a measure for the distance between two spike trains. The distance has a time constant as a parameter. Depending on this parameter, the distance interpolates between a coincidence detector and a rate difference counter. The dependence of the distance on noise is studied with an integrate-andfire model. For an intermediate range of the time constants, the distance depends linearly on the noise. This property can be used to determine the intrinsic noise of a neuron.
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Rasch, Malte J., Arthur Gretton, Yusuke Murayama, Wolfgang Maass et Nikos K. Logothetis. « Inferring Spike Trains From Local Field Potentials ». Journal of Neurophysiology 99, no 3 (mars 2008) : 1461–76. http://dx.doi.org/10.1152/jn.00919.2007.
Texte intégralRésumé :
We investigated whether it is possible to infer spike trains solely on the basis of the underlying local field potentials (LFPs). Using support vector machines and linear regression models, we found that in the primary visual cortex (V1) of monkeys, spikes can indeed be inferred from LFPs, at least with moderate success. Although there is a considerable degree of variation across electrodes, the low-frequency structure in spike trains (in the 100-ms range) can be inferred with reasonable accuracy, whereas exact spike positions are not reliably predicted. Two kinds of features of the LFP are exploited for prediction: the frequency power of bands in the high γ-range (40–90 Hz) and information contained in low-frequency oscillations (<10 Hz), where both phase and power modulations are informative. Information analysis revealed that both features code (mainly) independent aspects of the spike-to-LFP relationship, with the low-frequency LFP phase coding for temporally clustered spiking activity. Although both features and prediction quality are similar during seminatural movie stimuli and spontaneous activity, prediction performance during spontaneous activity degrades much more slowly with increasing electrode distance. The general trend of data obtained with anesthetized animals is qualitatively mirrored in that of a more limited data set recorded in V1 of non-anesthetized monkeys. In contrast to the cortical field potentials, thalamic LFPs (e.g., LFPs derived from recordings in the dorsal lateral geniculate nucleus) hold no useful information for predicting spiking activity.
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TITO ARECCHI, F. « NEURON DYNAMICS AND CHAOTIC SYNCHRONIZATION ». Fluctuation and Noise Letters 05, no 02 (juin 2005) : L163—L173. http://dx.doi.org/10.1142/s0219477505002525.
Texte intégralRésumé :
At the borderline between neuroscience and physics of complex phenomena, a new paradigm is under investigation, namely feature binding. This terminology denotes how a large collection of coupled neurons combines external signals with internal memories into new coherent patterns of meaning. An external stimulus spreads over an assembly of coupled neurons, building up a corresponding collective state. Thus, the synchronization of spike trains of many individual neurons is the basis of a coherent perception. Based on recent investigations, a novel conjecture for the dynamics of single neurons and, consequently, for neuron assemblies has been formulated. Homoclinic chaos is proposed as the most suitable way to code information in time by trains of equal spikes occurring at apparently erratic times; a new quantitative indicator, called propensity, is introduced to select the most appropriate neuron model. In order to classify the set of different perceptions, the percept space is given a metric structure by introducing a distance measure between distinct percepts. The distance in percept space is conjugate to the duration of the perception in the sense that an uncertainty relation in percept space is associated with time limited perceptions. (Thus coding of different percepts by synchronized spike trains entails fundamental quantum features. It is conjectured that they are related to the details of the perceptual chain rather than depending on Planck's action.)
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Chicharro, Daniel, Thomas Kreuz et Ralph G. Andrzejak. « What can spike train distances tell us about the neural code ? » Journal of Neuroscience Methods 199, no 1 (juillet 2011) : 146–65. http://dx.doi.org/10.1016/j.jneumeth.2011.05.002.
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Satuvuori, Eero, Mario Mulansky, Andreas Daffertshofer et Thomas Kreuz. « Using spike train distances to identify the most discriminative neuronal subpopulation ». Journal of Neuroscience Methods 308 (octobre 2018) : 354–65. http://dx.doi.org/10.1016/j.jneumeth.2018.09.008.
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Kociuba, Wanda, Wieslaw Mądry, Aneta Kramek, Krzysztof Ukalski et Marcin Studnicki. « Multtvariate diversity of Polish winter triticale cultivars for spike and other traits ». Plant Breeding and Seed Science 62, no 1 (1 janvier 2010) : 31–42. http://dx.doi.org/10.2478/v10129-011-0003-4.
Texte intégralRésumé :
Multtvariate diversity of Polish winter triticale cultivars for spike and other traits The objective of the present study was to determine the extent and pattern of genotypic diversity for six spike quantitative characters and two other traits in 36 winter triticale cultivars released in Poland, to classify the cultivars into similarity groups (clusters) and to identify those traits, among the studied ones, which mostly discriminated distinguished groups of cultivars. The 36 cultivars, released in the period from 1982 to 1999, were evaluated across three years 2002-2004 at the Experimental Field Station in Czesławice near Nałęczów, Poland. The experiments were carried out on the brown soil with loess subsoil. In each year the one-replicated experimental design was used with 2 m2 plots, rows 20 cm apart, and dense sowing using about 2 cm spacing of seeds. Analyses of variance for each trait data according to the random model (both cultivars and years were assumed to be random factors) were done. To classify and characterize genotypic diversity of the cultivars for the eight traits, the pattern analysis was used. It involved both cluster analysis using Ward's procedure with a measure of the multivariate similarity among cultivars being Squared Euclidean Distance and canonical variate analysis (CVA) on the basis of cultivar BLUPs for the original traits. Quite different groups of cultivars for the studied traits were found, specially one group was substantially distanced to the others. As it was shown by CVA, spike length and number of spikelets per spike as negatively correlated with number of grains per spikelet in the studied set of the cultivars relatively largest contributed to overall differentiation of the distinguished eight groups and then, these traits best discriminated among the eight cultivar groups in the term of Mahalanobis distance for the considered traits. The 1000 grain weight and grain protein content much less contributed to overall discrimination of the cultivar groups than the previous four traits. The most important agronomic traits characterizing productivity of the spike grain weight and its two components, e.g. number of grains per spikelet and number of grains per spike had least discriminating power for the groups of cultivars. Grain yield per unit area of cereals is a result of spike grain yield and the number of spikes per unit area. In these studies of winter triticale cultivar diversity only grain spike yield and its components were included. Thus, the presented study are a primary evaluating of phenotypic diversity in the cultivars. The further study on the cultivar diversity evaluation for grain yield per unit area and its components is necessary.
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Bardin, Jean-Baptiste, Gard Spreemann et Kathryn Hess. « Topological exploration of artificial neuronal network dynamics ». Network Neuroscience 3, no 3 (janvier 2019) : 725–43. http://dx.doi.org/10.1162/netn_a_00080.
Texte intégralRésumé :
One of the paramount challenges in neuroscience is to understand the dynamics of individual neurons and how they give rise to network dynamics when interconnected. Historically, researchers have resorted to graph theory, statistics, and statistical mechanics to describe the spatiotemporal structure of such network dynamics. Our novel approach employs tools from algebraic topology to characterize the global properties of network structure and dynamics. We propose a method based on persistent homology to automatically classify network dynamics using topological features of spaces built from various spike train distances. We investigate the efficacy of our method by simulating activity in three small artificial neural networks with different sets of parameters, giving rise to dynamics that can be classified into four regimes. We then compute three measures of spike train similarity and use persistent homology to extract topological features that are fundamentally different from those used in traditional methods. Our results show that a machine learning classifier trained on these features can accurately predict the regime of the network it was trained on and also generalize to other networks that were not presented during training. Moreover, we demonstrate that using features extracted from multiple spike train distances systematically improves the performance of our method.
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Gardella, Christophe, Olivier Marre et Thierry Mora. « Blindfold learning of an accurate neural metric ». Proceedings of the National Academy of Sciences 115, no 13 (12 mars 2018) : 3267–72. http://dx.doi.org/10.1073/pnas.1718710115.
Texte intégralRésumé :
The brain has no direct access to physical stimuli but only to the spiking activity evoked in sensory organs. It is unclear how the brain can learn representations of the stimuli based on those noisy, correlated responses alone. Here we show how to build an accurate distance map of responses solely from the structure of the population activity of retinal ganglion cells. We introduce the Temporal Restricted Boltzmann Machine to learn the spatiotemporal structure of the population activity and use this model to define a distance between spike trains. We show that this metric outperforms existing neural distances at discriminating pairs of stimuli that are barely distinguishable. The proposed method provides a generic and biologically plausible way to learn to associate similar stimuli based on their spiking responses, without any other knowledge of these stimuli.
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Harvey, Michael, David Lau, Eugene Civillico, Bernardo Rudy et Diego Contreras. « Impaired long-range synchronization of gamma oscillations in the neocortex of a mouse lacking Kv3.2 potassium channels ». Journal of Neurophysiology 108, no 3 (1 août 2012) : 827–33. http://dx.doi.org/10.1152/jn.00102.2012.
Texte intégralRésumé :
Inhibitory interneurons play a critical role in the generation of gamma (20–50 Hz) oscillations, either by forming mutually inhibitory networks or as part of recurrent networks with pyramidal cells. A key property of fast spiking interneurons is their ability to generate brief spikes and high-frequency spike trains with little accommodation. However, the role of their firing properties in network oscillations has not been tested in vivo. Studies in hippocampus in vitro have shown that high-frequency spike doublets in interneurons play a key role in the long-range synchronization of gamma oscillations with little phase lag despite long axonal conduction delays. We generated a knockout (KO) mouse lacking Kv3.2 potassium channel subunits, where infragranular inhibitory interneurons lose the ability both to sustain high-frequency firing and reliably generate high-frequency spike doublets. We recorded cortical local field potentials in anesthetized and awake, restrained mice. Spontaneous activity of the KO and the wild-type (WT) showed similar content of gamma and slow (0.1–15 Hz) frequencies, but the KO showed a significantly larger decay of synchronization of gamma oscillations with distance. Coronal cuts in the cortex of WT mice decreased synchronization to values similar to the intact KO. The synchronization of the slow oscillation showed little decay with distance in both mice and was largely reduced after coronal cuts. Our results show that the firing properties of inhibitory interneurons are critical for long-range synchronization of gamma oscillations, and emphasize that intrinsic electrophysiological properties of single cells may play a key role in the spatiotemporal characteristics of network activity.
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Tezuka, Taro, et Christophe Claramunt. « Kernel Analysis for Estimating the Connectivity of a Network with Event Sequences ». Journal of Artificial Intelligence and Soft Computing Research 7, no 1 (1 janvier 2017) : 17–31. http://dx.doi.org/10.1515/jaiscr-2017-0002.
Texte intégralRésumé :
AbstractEstimating the connectivity of a network from events observed at each node has many applications. One prominent example is found in neuroscience, where spike trains (sequences of action potentials) are observed at each neuron, but the way in which these neurons are connected is unknown. This paper introduces a novel method for estimating connections between nodes using a similarity measure between sequences of event times. Specifically, a normalized positive definite kernel defined on spike trains was used. The proposed method was evaluated using synthetic and real data, by comparing with methods using transfer entropy and the Victor-Purpura distance. Synthetic data was generated using CERM (Coupled Escape-Rate Model), a model that generates various spike trains. Real data recorded from the visual cortex of an anaesthetized cat was analyzed as well. The results showed that the proposed method provides an effective way of estimating the connectivity of a network when the time sequences of events are the only available information.
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Houghton, Conor. « Calculating mutual information for spike trains and other data with distances but no coordinates ». Royal Society Open Science 2, no 5 (mai 2015) : 140391. http://dx.doi.org/10.1098/rsos.140391.
Texte intégralRésumé :
Many important data types, such as the spike trains recorded from neurons in typical electrophysiological experiments, have a natural notion of distance or similarity between data points, even though there is no obvious coordinate system. Here, a simple Kozachenko–Leonenko estimator is derived for calculating the mutual information between datasets of this type.
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Gandahi, Naila, Abdul Wahid Baloch, Mir Yar Muhammad Khan Talpur, Nasreen Fatima, Tanweer Fatah Abro, Ghulam Hussain Jatoi, Asadullah Mari, Liaquat Ali Bhutto et Rong Shu Zhang. « Unveiling the genetic divergence and phenotypic association in elite Pakistani wheat (Triticum aestivum L.) genotypes ». Volume 4 Issue 1, Volume 4 Issue 1 (11 septembre 2021) : 119–26. http://dx.doi.org/10.34091/ajls.4.1.14.
Texte intégralRésumé :
The present study was designed to assess genetic divergence between commercial bread wheat genotypes based on yield and its related traits and to carry out phenotypic correlation. Twenty bread hexaploid wheat varieties were assessed for mean performance, correlation analysis and genetic distance. Randomized complete block design was used with three replications during growing season, 2018-2019 at Wheat and Barley Research Institute, Tandojam. The mean squares depicted significant differences (P<0.01) for all the investigated traits among the tested genotypes, proving that used genetic resources possess a great potential for further breeding experiments. Regarding mean performance, the genotypes Sassui and TD-1 displayed desirable performance for a variety of traits, unveiling their importance in wheat breeding programs. The results also showed that tillers plant-1, grains spike-1 and seed index developed significantly positive (P<0.05) interrelationship with grain yield plant-1. This demonstrates that genotypes possessing higher extent of these traits may be chosen in selection for developing high yielding bread wheat genotypes. The larger genetic distance was witnessed between Johar-78 and TD-1, followed by SKD-1 and TJ-83, SKD-1 and Mehran-89, SKD-1 and Johar-78, TD-1 and Khirman, TJ-83 and Imdad-05, Mehran-89 and TD-1 and Johar-78 and TJ-83. These paired showed wide genetic distances, which may also be preferred in wheat hybridization program. Keywords: Genetic distance, hexaploid wheat, morphological traits, trait
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Li, X. J., W. H. Ding, X. D. Chen, G. Li, X. L. Jiang, N. Dong, Y. J. Xiao, C. C. Ren, X. H. Gao et Z. G. Ru. « Genetics and mapping of the novel leaf-colour mutant gene yglw-1 on wheat chromosome arm 2BS ». Crop and Pasture Science 69, no 10 (2018) : 955. http://dx.doi.org/10.1071/cp18321.
Texte intégralRésumé :
Leaf colour plays an important role in plant growth and development. In this study, a stably inherited yellow–green leaf mutation, temporarily designated yglw-1, was initially isolated from progenies of wheat (Triticum aestivum L.) cross Bainong58409/Caifumai. The yellow-leaf phenotype could be observed in the yglw-1 mutant during the seedling stage, and then the yellow leaves gradually progressed from the bottom to the top throughout development. Compared with its sister line Cf5019-21 with a normal leaf-colour phenotype, the main agronomic traits of the yglw-1 mutant including spike length, number of kernels per spike and 1000-kernel weight were significantly decreased. Measurement of chlorophyll contents showed that chlorophylls a and b in the third top leaf at the jointing stage and the penultimate leaf and third top leaf at the heading stage were obviously lower in yglw-1 than in Cf5019-21. Genetic analysis indicated that the yellow–green leaf trait was controlled by a single recessive gene. Bulked segregant analysis found that two published simple sequence repeat (SSR) markers and four expressed sequence tag-sequence tagged site (EST-STS) markers were linked to the yglw-1 gene, and BE494262 was the most closely linked marker to yglw-1, at a genetic distance of 2.3 cM. To increase the density of the genetic map, 135 novel SSR markers at a certain distance near the marker BE494262 were developed according to SSR loci detected in the Chinese Spring reference sequence. Of these, nine SSR markers detected polymorphic fragments between the two parents as well as between the contrasting DNA bulks. Finally, the yglw-1 gene was mapped between SSR markers Xhwm1 and Xhwm43 and showed genetic distances 1.9 cM and 23.9 cM on chromosome 2BS. These findings can facilitate candidate-gene prediction and map-based cloning of the yglw-1 gene.
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Golomb, David. « Models of Neuronal Transient Synchrony During Propagation of Activity Through Neocortical Circuitry ». Journal of Neurophysiology 79, no 1 (1 janvier 1998) : 1–12. http://dx.doi.org/10.1152/jn.1998.79.1.1.
Texte intégralRésumé :
Golomb, David. Models of neuronal transient synchrony during propagation of activity through neorcortical circuitry. J. Neurophysiol. 79: 1–12, 1998. Stereotypic paroxysmal discharges that propagate in neocortical tissues after electrical stimulations are used as a probe for studying cortical circuitry. I use modeling to investigate the effects of sparse connectivity, heterogeneity of intrinsic neuronal properties, and synaptic noise on synchronization of evoked propagating neuronal discharges in a network of excitatory, regular spiking neurons with spatially decaying connectivity. The global coherence of the traveling discharge is characterized by the correlation function between spike trains of neurons, averaged over all the pairs of neurons in the system at the same distance. Local coherence of two neurons is characterized by their correlation function averaged over many trials or, for persistent activity, over a long time interval. Spike synchronization between neurons emerges as a result of the transient activity; if activity is persistent, there is no synchrony, and cross-correlation functions are flat. During discharge propagation, system-average cross-correlation between neurons does not depend on their mutual distance except for a time shift. Spike synchronization occurs only when the average number of synapses M a cell receives is large enough. As M increases, there is a cross-over from an asynchronized to a synchronized discharge. Synaptic depression appears to help synchrony; it reduces the M value at the cross-over. The strengths of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) and N-methyl-d-aspartate (NMDA) conductances affect synchrony only weakly. Spike synchronization is robust even with large levels of heterogeneity. Synaptic noise reduces synchrony, but strong synchrony is observed at a noise level that cannot evoke spontaneous discharges. System-average spike synchronization is determined by the levels of sparseness, heterogeneity, and noise, whereas trial-average spike synchronization is determined only by the noise level. Therefore, I predict that experiments will reveal local, two-cell spike synchrony, but not global synchrony.
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Pyza, Agnieszka, Helena Kubicka-Matusiewicz et Dariusz Gozdowski. « Assessment of similarity of inbred lines and F1 generations in collection of winter rye (Secale cereale L.) / Ocena podobieństwa linii wsobnych i pokolenia F1 w kolekcji żyta ozimego (Secale cereale L.) ». Ochrona Srodowiska i Zasobów Naturalnych 26, no 4 (1 décembre 2015) : 30–34. http://dx.doi.org/10.1515/oszn-2015-0026.
Texte intégralRésumé :
Abstract Effective tools for evaluation of diversity in the collected gene resources of a given species are multivariate statistical methods. They provide information on phenotypic and genetic variability of collected material. The subjects of this study were nine inbred lines and three F1 generations of winter rye (Secale cereale L.), growing in experimental plots of the Polish Academy of Sciences Botanical Garden, Centre for Biological Diversity Conservation in Powsin. The evaluation was performed over the period of 3 years. Observations were made of the following traits: length of stem, length of spike, number of nodes in spike rachis, number of kernels per spike, weight of kernels per spike, weight of 1000 kernels, length of flag leaf, length of subflag leaf, length of third leaf, width of flag leaf, width of subflag leaf, width of third leaf, area of leaves per stem, number of stems per plant and area of leaves per plant. On the basis of cluster analysis and principal components analysis, two genetically homogeneous groups were identified. Mean values and standard deviations were calculated for each trait in each group and for all genotypes together. Multivariate distance matrix permitted identification of the most genetically similar and most distant forms.
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Fried, S. I., H. A. Hsueh et F. S. Werblin. « A Method for Generating Precise Temporal Patterns of Retinal Spiking Using Prosthetic Stimulation ». Journal of Neurophysiology 95, no 2 (février 2006) : 970–78. http://dx.doi.org/10.1152/jn.00849.2005.
Texte intégralRésumé :
The goal of retinal prosthetic devices is to generate meaningful visual information in patients that have lost outer retinal function. To accomplish this, these devices should generate patterns of ganglion cell activity that closely resemble the spatial and temporal components of those patterns that are normally elicited by light. Here, we developed a stimulus paradigm that generates precise temporal patterns of activity in retinal ganglion cells, including those patterns normally generated by light. Electrical stimulus pulses (≥1-ms duration) elicited activity in neurons distal to the ganglion cells; this resulted in ganglion cell spiking that could last as long as 100 ms. However, short pulses, <0.15 ms, elicited only a single spike within 0.7 ms of the leading edge of the pulse. Trains of these short pulses elicited one spike per pulse at frequencies ≤250 Hz. Patterns of short electrical pulses (derived from normal light elicited spike patterns) were delivered to ganglion cells and generated spike patterns that replicated the normal light patterns. Finally, we found that one spike per pulse was elicited over almost a 2.5:1 range of stimulus amplitudes. Thus a common stimulus amplitude could accommodate a 2.5:1 range of activation thresholds, e.g., caused by differences arising from cell biophysical properties or from variations in electrode-to-cell distance arising when a multielectrode array is placed on the retina. This stimulus paradigm can generate the temporal resolution required for a prosthetic device.
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Xiong, Biao, Bo Wang, Shengwu Xiong, Chengde Lin et Xiaohui Yuan. « 3D Morphological Processing for Wheat Spike Phenotypes Using Computed Tomography Images ». Remote Sensing 11, no 9 (9 mai 2019) : 1110. http://dx.doi.org/10.3390/rs11091110.
Texte intégralRésumé :
Wheat is the main food crop today world-wide. In order to improve its yields, researchers are committed to understand the relationships between wheat genotypes and phenotypes. Compared to progressive technology of wheat gene section identification, wheat trait measurement is mostly done manually in a destructive, labor-intensive and time-consuming way. Therefore, this study will be greatly accelerated and promoted if we can automatically discover wheat phenotype in a nondestructive and fast manner. In this paper, we propose a novel pipeline based on 3D morphological processing to detect wheat spike grains and stem nodes from 3D X-ray micro computed tomography (CT) images. We also introduce a set of newly defined 3D phenotypes, including grain aspect ratio, porosity, Grain-to-Grain distance, and grain angle, which are very difficult to be manually measured. The analysis of the associations among these traits would be very helpful for wheat breeding. Experimental results show that our method is able to count grains more accurately than normal human performance. By analyzing the relationships between traits and environment conditions, we find that the Grain-to-Grain distance, aspect ratio and porosity are more likely affected by the genome than environment (only tested temperature and water conditions). We also find that close grains will inhibit grain volume growth and that the aspect ratio 3.5 may be the best for higher yield in wheat breeding.
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Matos, Sérgio, Filipe Manuel Clemente, Rui Silva et José María Cancela Carral. « Variations of Workload Indices Prior to Injuries : A Study in Trail Runners ». International Journal of Environmental Research and Public Health 17, no 11 (5 juin 2020) : 4037. http://dx.doi.org/10.3390/ijerph17114037.
Texte intégralRésumé :
The purpose of this study was to compare the variations of weekly workload indices of internal and external load measures across the three weeks prior to injury occurrences in trail runners. Twenty-five trail runners (age: 36.23 ± 8.30 years old; body mass: 67.24 ± 5.97 kg; height: 172.12 ± 5.12 cm) were monitored daily for 52 weeks using global positioning systems (GPSs) to determine the total distance covered. Additionally, a rate of perceived exertion (RPE) scale was applied to determine session-RPE (sRPE: RPE multiplied by training time). The accumulated load (AL), acute: chronic workload ratio (ACWR), training monotony (TM), and training strain (TS) indices were calculated weekly for each runner. During the period of analysis, the injury occurrences were recorded. The differences were observed in AL and ACWR for sRPE and training time were significantly greater during the injury week when compared to the previous weeks. Similar evidence was found in TM and TS indices for sRPE, training time, and total distance. Furthermore, no meaningful differences were observed in AL and ACWR for total distance in the weeks prior to injury occurrence. Nevertheless, significant between-subjects variability was found, and this should be carefully considered. For that reason, an individualized analysis of the workload dynamics is recommended, avoiding greater spikes in load by aiming to keep a progressive increment of load without consequences for injury risk.
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Nave, Moran, Mihriban Taş, John Raupp, Vijay K. Tiwari, Hakan Ozkan, Jesse Poland, Iago Hale, Takao Komatsuda et Assaf Distelfeld. « The Independent Domestication of Timopheev’s Wheat : Insights from Haplotype Analysis of the Brittle rachis 1 (BTR1-A) Gene ». Genes 12, no 3 (25 février 2021) : 338. http://dx.doi.org/10.3390/genes12030338.
Texte intégralRésumé :
Triticum turgidum and T. timopheevii are two tetraploid wheat species sharing T. urartu as a common ancestor, and domesticated accessions from both of these allopolyploids exhibit nonbrittle rachis (i.e., nonshattering spikes). We previously described the loss-of-function mutations in the Brittle Rachis 1 genes BTR1-A and BTR1-B in the A and B subgenomes, respectively, that are responsible for this most visible domestication trait in T. turgidum. Resequencing of a large panel of wild and domesticated T. turgidum accessions subsequently led to the identification of the two progenitor haplotypes of the btr1-A and btr1-B domesticated alleles. Here, we extended the haplotype analysis to other T. turgidum subspecies and to the BTR1 homologues in the related T. timopheevii species. Our results showed that all the domesticated wheat subspecies within T. turgidum share common BTR1-A and BTR1-B haplotypes, confirming their common origin. In T. timopheevii, however, we identified a novel loss-of-function btr1-A allele underlying a partially brittle spike phenotype. This novel recessive allele appeared fixed within the pool of domesticated Timopheev’s wheat but was also carried by one wild timopheevii accession exhibiting partial brittleness. The promoter region for BTR1-B could not be amplified in any T. timopheevii accessions with any T. turgidum primer combination, exemplifying the gene-level distance between the two species. Altogether, our results support the concept of independent domestication processes for the two polyploid, wheat-related species.
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Burnett, Mackenzie, Imogen Hobbs et Alexa Ripple. « Seeing the Forest for the Deer : Plant Abundance and Diversity at the Gault Nature Reserve During a Spike in White-Tailed Deer ». McGill Science Undergraduate Research Journal 15, no 1 (13 avril 2020) : 12–17. http://dx.doi.org/10.26443/msurj.v15i1.4.
Texte intégralRésumé :
Background: Deer populations have been rising across North America for decades. At the Gault Nature Reserve in Quebec, half of which is open to the public, the population of white-tailed deer (Odocoileus virginianus) has exceeded the region’s carrying capacity, estimated to be 5 deer/km2, since 1996. Given that heavy grazing profoundly impacts forests, the purpose of this paper was to investigate the potential influence of white-tailed deer on plant abundance and diversity at the Gault Nature Reserve. We hypothesized that the abundance of deer, and by extension the effect of deer on vegetation, was negatively correlated with the proximity and frequency of human visitors on pedestrian trails. Our alternative hypothesis was that the effect of deer on vegetation was positively correlated with human disturbance, which is greater on the public side of the reserve.Methods: We recorded the abundance and diversity of vascular plants along 14 transects of increasing distance from pedestrian trails on the public and private sides of the reserve.Results: Contrary to our hypothesis, generalized linear models indicated that overall, plant abundance and diversity declined significantly as the distance from trails increased and that the effect of distance was significantly different on the two sides of the reserve. Pearson correlation tests revealed that there was not a significant correlation between distance and plant abundance and diversity on the public side, although there was a significantly negative correlation between these variables on the private side.Limitations: White-tailed deer were not directly studied, which limited the inferences that could be made about their influence on plant abundance and diversity.Conclusion: The distance from trails was a strong determinant of plant abundance and diversity on the private of the reserve, but not on the public side, possibly because trail edges generally receive more sunlight and because the increased number of trails on the public side may have confounded our results. Although we did not find support for our hypothesis, the influence of trail edges on plant communities was reinforced. Researchers should continue to monitor the influence of white-tailed deer and forest managers should be mindful of edge effects when making decisions.
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Klomsten Andersen, Oddbjørn, Benjamin Clarsen, Ina Garthe, Morten Mørland et Trine Stensrud. « Bone health in elite Norwegian endurance cyclists and runners : a cross-sectional study ». BMJ Open Sport & ; Exercise Medicine 4, no 1 (décembre 2018) : e000449. http://dx.doi.org/10.1136/bmjsem-2018-000449.
Texte intégralRésumé :
BackgroundAthletes who compete in non-weight-bearing activities such as swimming and cycling are at risk of developing low bone mineral density (BMD). Athletes in long-distance running are at risk of low BMD.Objective (1) To evaluate the bone health in Norwegian male and female national elite road cyclists and middle-distance and long-distance runners, and to identify cases of low BMD. (2) To identify possible risk factors associated with low BMD.MethodsTwenty-one runners (11 females and 10 males) and 19 road cyclists (7 females and 12 males) were enrolled in this cross-sectional study. Dual-energy X-ray absorptiometry measurement of BMD in total body, femoral neck and lumbar spine was measured. Participants completed a questionnaire regarding training, injuries, calcium intake and health variables.ResultsThe cyclists had lower BMD for all measured sites compared with the runners (p≤0.05). Ten of 19 cyclists were classified as having low BMD according to American College of Sports Medicine criteria (Z-score ≤−1), despite reporting to train heavy resistance training on the lower extremities. Low BMD was site specific having occurred in the lumbar spine and the femoral neck and was not confined to females. Type of sport was the only factor significantly associated with low BMD.ConclusionNational elite Norwegian road cyclists had lower BMD compared with runners, and a large proportion was classified as having low BMD, despite having performed heavy resistance training. Interventions to increase BMD in this population should be considered.
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Bobowicz, Maria A., et Anna Radziejewska. « The variability of Scots pine from Piekielna Góra as expressed by morphological and anatomical traits of needles ». Acta Societatis Botanicorum Poloniae 58, no 3 (2014) : 375–84. http://dx.doi.org/10.5586/asbp.1989.032.
Texte intégralRésumé :
Two-year old needles were collected from 30 standing Scots pine trees on Piekielna Góra. These needles were analysed in respect to 13 morphological and anatomical traits. The data so obtained was subjected to a whole range of multi-trait analytical methods in an attempt to determine the variability among the randomly chosen trees. Multivariate analysis of variance and canonical analysis were done as well as calculation of Mahalanobis distances between each pair of trees and their significance was tested by the Hotelling T2 statistics. Aminimum spanning tree was constructed on the basis of the shortest Mahalanobis distances, while a dendrogram (cluster analysis) was compiled on the basis of Euclidean distances. It was found that in spite of the fact that the studied population sample of pines did not form internal, significantly differentiated groups, the variability among particular trees was large and depended on the given trait. The number of resin canals best differentiated the studied trees, while the Marcet coefficient did not significantly differentiate any pair of trees.