1,721,129 research outputs found
Artificial Neural Network Codifies Sensory and Cognitive Events Identifying Chaotic Attractors in EEG Signals
Full text linkIn past researches our group experimented a method to analyze multiple neural signals by means of a novel self-organizing Artificial Neural Network, highlighting the attractors in which the corresponding dynamic system is evolving. If the attractors show to be chaotic, this means that the neural signals are individually self-organized and, analyzing more signals together, that there is a form of coherence between signals. The ANN can also identify different attractors with a unique code. The ANN allows to attribute the same codes to similar but not identical brain events, reaching the necessary range of flexibility. In the present work the method has been tested on signals from a 14 electrodes EEG system connected to immersive glasses that allow a realistic audiovisual experience. A software procedure synchronizes the acquired signals with various sensory experiences presented in a video. Aim of the research is to characterize sensory and emotional stimuli. The analysis lead to positive results, showing that the binary codes corresponding to similar cognitive and perceptive stimuli are similar, and well differentiated for the codes corresponding to different stimuli
Artificial Neural Networks, Dynamical Systems and Self-Organization
No full textThe world around us and the living beings are complex dynamical systems, with a high capability of self-organization: the book explains the principles that rule this exceptional characteristic. As well as living beings, Artificial Neural Networks, that constitute one of the most promising tools for the development of Artificial Intelligence, are self-organizing dynamical systems: this makes them an optimal tool to analyze and simulate the brain and any expression of organized complexity
Coding mental states from EEG signals and evaluating their integrated information content : a computational intelligence approach
No full textThe paper presents a method to identify and code mental states from EEG signals, performing their dynamical analysis by means of an Artificial Neural Network. The method has been tested on signals from a 14 electrodes EEG system connected to immersive glasses that allow a realistic audiovisual experience. A software procedure synchronizes the acquired signals with the sensory experiences presented in a video. A suitable Artificial Neural Network detects and codifies the chaotic attractors signals related to the sensory and cognitive events. The analysis shows that the binary codes corresponding to similar cognitive and perceptive stimuli are similar, and well differentiated from the codes corresponding to different stimuli. The dynamical attractors corresponding to each mental state are submitted to a procedure that evaluates their
Integrated Information content in the qualia space
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
Shaping a Set of Oriented Connections among Brain Areas by Comparison between Coherence and Granger Causality
No full textTo assess the intensity of connections between different human brain areas we processed signals recorded from 16 intracranial electrodes in patients with focal epilepsy during wakefulness. We calculated spectral Coherence and Granger Causality at a network level. The comparison between the two procedures has confirmed the existence of privileged connections. The work analyzes and discusses the achieved results
Paolo Orsi e la necropoli di Torre Galli
No full textSintetico resoconto delle ricerche condotte da Paolo Orsi nella necropoli protostorica calabrese di Torre Gall
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
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