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Context 4. Data used in Figs. The different coupling leads to different shapes in the copula scatterplots, as well as to different properties. For instance, copula scatterplots related to the jump model are characterized by a lack of points around the main diagonals, while a cluster of points is observed in those fpts k from the covariance model. This allows us to hypothesize different coupling phenomena fpts k those scatterplots presenting different features. Look for instance at Fig. Therefore, the study of correlation or rank correlation indexes, such as the Pearson's rho or the Kendall's tau, is useful to recognize the presence of dependencies, but it cannot be used to investigate their nature.

The use of copulas allows a new approach to analyze dependencies between spike trains. The discussed examples illustrate some features highlighted by means of this technique. Suitable statistical fpts k and further developments of the mathematical tools will fpts k to determine families of copulas able to fit data.

Furthermore, a classification of the different copulas corresponding to different kinds of coupling may help to interpret the structure of the network. In this Section, we compare some of our results with fpts k obtained through classical tools. At first, we consider crosscorrelograms and time scatterplots. Then, we briefly discuss some features of the GLMs fpts k finally we perform a detailed comparison with the Cox method. Crosscorrelograms are one of the most used techniques to analyze spike trains. They detect synchronous and delayed ac- tivities but they are often unable to recognize other kinds of dependencies.

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Reversely, in copula scatterplots, the layout of the points out of the curve of synchrony discloses the presence of fpts k kinds of dependencies. Moreover, it helps to hypothesize the underlying coupling effects. A common feature between crosscorrelograms and the proposed approach is the necessity to fix a target neuron. Usually, the analysis is repeated, exchanging the roles of the two neurons.

The analysis of crosscorrelograms requests the simulta- neous study of the autocorrelograms. Indeed, oscillations fpts k the crosscorrelogram might be due to marginal behaviors, as described by Sacerdote and Tamborrino and Tetzlaff et al. Thus, it is not always possible to distinguish between the two cases.


Furthermore, the duration of the dependencies is hidden in crosscorrelograms. Indeed, this fpts k depends on the presence of several peaks or troughs and by their width.

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Unfortunately, these features change according to the used bin. On the contrary, copulas allow to determine the value of m fpts k that the two considered random times become independent, disclosing memory properties.


In the crosscorrelograms, peaks and troughs far from zero are due to the marginal fpts k, as explained by the autocorrelograms. Physical or functional performance tests FPTs are one mechanism used to evaluate the athlete's physical skills and capabilities prior to returning to sports participation. Related articles. Share this page.

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Recent progress have made possible to profile each recorded neuron in a given area thanks to genetic and fpts k tools, and to pool together recordings from neurons of the same type across different experimental fpts k. However, it is unclear how to infer the activity of a full population of neurons of the same type from these sequential recordings. Neural networks exhibit collective behaviour, e. Here we show that we can infer the activity of a full population of retina ganglion cells from sequential recordings, using a novel method based on copula distributions and maximum entropy modeling. From just the spiking response of each ganglion cell to a repeated stimulus, and a few pairwise recordings, we could predict the noise correlations using copulas, and then the full activity of a large population of ganglion cells of the same type using maximum entropy modeling.

Remarkably, we could generalize to predict the population responses to different stimuli and even to different experiments. We could therefore use our method to construct a very large population merging cells' responses from different experiments.

We predicted synchronous activity accurately and showed it grew substantially with the number of neurons. This approach is a promising way to infer population activity from sequential fpts k in sensory areas.PQI Travel Flash Single Slot - card reader - USB overview and full product specs on Fpts k. Other Companies FPTS-K-US. WD Free Driver Download for WindowsME, 98SE, 98 - . World's most popular driver download site.


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