1,721,261 research outputs found
Information Content of Local Field Potentials: Experiments and Models in Principles of Neural Coding
No full textSource data file for the article authored by Tafazoli and colleagues on invariant object representations in rat visual cortex
No full textThis data file provides the full data set processed in the article “Emergence of transformation-tolerant representations of visual objects in rat lateral extrastriate cortex” by Sina Tafazoli, Houman Safaai, Gioia De Franceschi, Federica Bianca Rosselli, Walter Vanzella, Margherita Riggi, Federica Buffolo, Stefano Panzeri and Davide Zoccolan. A detailed description of the file is provided in the companion "Readme.pdf" file
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Transitions between Asynchronous and Synchronous States: A Theory of Correlations in Small Neural Circuits
No full text<p>Model of the cross-correlation structure of a finite-size firing-rate network with graded activation function, from:</p>
<p>Diego Fasoli, Anna Cattani, Stefano Panzeri, arXiv:1605.07383 [q-bio.NC], 2016, submitted to The Journal of Computational Neuroscience.</p>
<p>The file "Python_Script_1.py" calculates the fundamental matrix of a finite-size multi-population neural network composed of an arbitrary number of homogeneous populations, according to the formalism described in the supplemental information of the article.</p>
<p>The file "Python_Script_2.py" calculates the cross-correlation structure of a network composed of two neural populations (one excitatory and one inhibitory). In particular, the script compares the analytical cross-correlation structure of the network (see Eqs. (11)-(13) in the main text of the article) with the same quantities calculated numerically through the techniques described in SubSec. (2.3).</p>
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Categorical encoding of decision variables in orbitofrontal cortex
No full textCategorical encoding of decision variables in orbitofrontal cortexThese are the data and code accompanying the PLoS Computational Biology article "Categorical encoding of decision variables in orbitofrontal cortex" by Arno Onken, Jue Xie, Stefano Panzeri and Camillo Padoa-Schioppa.CodeThe code in the 'code' folder is written in Python and tested with version 3.6.6. The following additional packages are required:- NumPy tested with version 1.16.5- SciPy tested with version 1.1.0- Scikit-learn tested with version 1.19.1- spherecluster https://pypi.org/project/spherecluster/0.1.2/- diptest https://github.com/alimuldal/diptestTo reproduce the figures, run the shell script 'plot_figures.sh'. The 'plot_*.py' scripts use the result data in the folders that are specified in the shell script. To reproduce the result data, use the appropriate 'calculate_*.py' script.DataThe data are located in the 'data' folder.- 'ofc_psth' contains the peri-stimulus time histograms for each cell. These are used for the PAIRS analysis only (corresponding script 'calculate_pairs.py'.- 'ofc_rates_all' contains the rates for each cell and trial type in the files 'rates.mat' and a list of the trial types in 'trialtypes.mat'. The other files in the folder are result files generated by the corresponding 'calculate_*.py' scripts.- 'ofc_rates_shuffled' like 'ofc_rates_all' but the rates where shuffled (see supplementary figure S2 Fig).- 'ofc_rates_time_windows' contains sub folders for each time window. Each of these sub folders has the same structure as 'ofc_rates_all'.- 'synthetic_banana' contains the synthetic data used for Figure 3.- 'synthetic_uniform' contains the synthetic non-categorical data sampled uniformly from the hypersphere (see Figures 5 and 6).- 'synthetic_variable' contains the synthetic categorical data (see Figures 4, 5 and 6)
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