scholarly journals Correlation-based spike sorting of multivariate data

2019 ◽  
Vol 5 (1) ◽  
pp. 113-116
Author(s):  
Pavel Larionov ◽  
Tom Juergens ◽  
Thomas Schanze

AbstractAutomated classification of waveforms is an important method of data processing used in various fields of science, such as neuroscience, biomedical engineering, etc. This work shows the possibility of sorting special waveforms i.e. spikes recorded with multichannel electrode arrays by using principles of correlation and data-driven reference. A new method to estimate the number of k-means clusters by using a Monte Carlo method is introduced. To demonstrate the performance of the algorithm, generated signals were used, which are created to mimic multichannel recording of the extra-cellular neuronal signals.

2020 ◽  
Vol 20 (1) ◽  
pp. 408-420
Author(s):  
Małgorzata Stec

AbstractResearch background: The article attempts to include the accuracy of statistical data in a synthetic evaluation and classification of EU countries in terms of innovation.Purpose: The aim of the article is to evaluate an influence of the accuracy of statistical data on a classification of EU countries in terms of innovation.Research methodology: The research employed diagnostic variables determining the innovation of EU countries and a methodology proposed by the European Commission in the European Innovation Scoreboard 2019. The influence of the uncertainty of the measurement of the diagnostic variables on the Summary Innovation Index of EU countries was evaluated. In order to do this, a procedure employing the Monte Carlo method was proposed.Results: Taking into account the uncertainty of the measurement of variables in the evaluation of the innovation of EU countries resulted in qualifying one of the countries to another innovation group.Novelty: The article draws attention to an important but often neglected problem related to the accuracy of statistical data used in research, and the evaluation of their influence on the calculation of a value of synthetic measure (based on the innovation of EU countries).


Author(s):  
Brian R. Mullen ◽  
Sydney C. Weiser ◽  
Desiderio Ascencio ◽  
James B. Ackman

Functional imaging of neural cell populations is critical for mapping intra− and inter−regional network dynamics across the neocortex. Recently we showed that an unsupervised machine learning decomposition of densely sampled recordings of cortical calcium dynamics results in a collection of components comprised of neuronal signal sources distinct from optical, movement, and vascular artifacts. Here we build a supervised learning classifier that automatically separates neural activity and artifact components, using a set of extracted spatial and temporal metrics that characterize the respective components. We demonstrate that the performance of the machine classifier matches human identification of signal components in novel data sets. Further, we analyze control data recorded in glial cell reporter and non−fluorescent mouse lines that validates human and machine identification of functional component class. This combined workflow of data−driven video decomposition and machine classification of signal sources will aid robust and scalable mapping of complex cerebral dynamics.


1974 ◽  
Vol 22 ◽  
pp. 307 ◽  
Author(s):  
Zdenek Sekanina

AbstractIt is suggested that the outbursts of Periodic Comet Schwassmann-Wachmann 1 are triggered by impacts of interplanetary boulders on the surface of the comet’s nucleus. The existence of a cloud of such boulders in interplanetary space was predicted by Harwit (1967). We have used the hypothesis to calculate the characteristics of the outbursts – such as their mean rate, optically important dimensions of ejected debris, expansion velocity of the ejecta, maximum diameter of the expanding cloud before it fades out, and the magnitude of the accompanying orbital impulse – and found them reasonably consistent with observations, if the solid constituent of the comet is assumed in the form of a porous matrix of lowstrength meteoric material. A Monte Carlo method was applied to simulate the distributions of impacts, their directions and impact velocities.


Author(s):  
Makoto Shiojiri ◽  
Toshiyuki Isshiki ◽  
Tetsuya Fudaba ◽  
Yoshihiro Hirota

In hexagonal Se crystal each atom is covalently bound to two others to form an endless spiral chain, and in Sb crystal each atom to three others to form an extended puckered sheet. Such chains and sheets may be regarded as one- and two- dimensional molecules, respectively. In this paper we investigate the structures in amorphous state of these elements and the crystallization.HRTEM and ED images of vacuum-deposited amorphous Se and Sb films were taken with a JEM-200CX electron microscope (Cs=1.2 mm). The structure models of amorphous films were constructed on a computer by Monte Carlo method. Generated atoms were subsequently deposited on a space of 2 nm×2 nm as they fulfiled the binding condition, to form a film 5 nm thick (Fig. 1a-1c). An improvement on a previous computer program has been made as to realize the actual film formation. Radial distribution fuction (RDF) curves, ED intensities and HRTEM images for the constructed structure models were calculated, and compared with the observed ones.


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