893 resultados para non-conscious cognitive processing (NCCP) time.


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In this paper, a real-time optimal control technique for non-linear plants is proposed. The control system makes use of the cell-mapping (CM) techniques, widely used for the global analysis of highly non-linear systems. The CM framework is employed for designing approximate optimal controllers via a control variable discretization. Furthermore, CM-based designs can be improved by the use of supervised feedforward artificial neural networks (ANNs), which have proved to be universal and efficient tools for function approximation, providing also very fast responses. The quantitative nature of the approximate CM solutions fits very well with ANNs characteristics. Here, we propose several control architectures which combine, in a different manner, supervised neural networks and CM control algorithms. On the one hand, different CM control laws computed for various target objectives can be employed for training a neural network, explicitly including the target information in the input vectors. This way, tracking problems, in addition to regulation ones, can be addressed in a fast and unified manner, obtaining smooth, averaged and global feedback control laws. On the other hand, adjoining CM and ANNs are also combined into a hybrid architecture to address problems where accuracy and real-time response are critical. Finally, some optimal control problems are solved with the proposed CM, neural and hybrid techniques, illustrating their good performance.

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There are several studies that suggest that different people deposit different quantities of their own DNA on items they touch, i.e. some are good shedders and others are bad shedders. It is of interest to determine if individuals deposit consistent quantities of their own DNA, no matter the occasion, as well as the degree of variability among individuals. To investigate this, participants were tested for their ability to deposit DNA by placing right and left handprints on separate DNA-free glass plates at three set times during the day (morning, midday and afternoon) on four different days spaced over several weeks. Information regarding recent activities performed by the individual was recorded, along with information on gender, hand dominance and hand size. A total of 240 handprint deposits were collected from 10 individuals and analyzed for differences in DNA quantity and the type of the DNA profile obtained at different times of the day, on different days, between the two hands of the same individual, and between different individuals. Furthermore, the correlation between the deposit quantity and the ratio of self to non-self DNA in the mixed deposits was analyzed to determine if the amount of non-self DNA has an effect on overall DNA quantities obtained. In general, this study has shown that while there is substantial variation in the quantities deposited by individuals on different occasions, some clear trends were evident with some individuals consistently depositing significantly more or less DNA than others. Non-self DNA was usually deposited along with self DNA and, in most instances, was the minor component. Incidents where the non-self portion was the major component were very rare and, when observed, were associated with a poor depositor/shedder. Forensic DNA scientists need to consider the range and variability of DNA a person deposits when touching an object, the likelihood of non-self DNA being co-deposited onto the handled object of interest and the factors that may affect the relative quantity of this component within the deposit.

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In this paper, the problem of global exponential stability analysis of a class of non-autonomous neural networks with heterogeneous delays and time-varying impulses is considered. Based on the comparison principle, explicit conditions are derived in terms of testable matrix inequalities ensuring that the system is globally exponentially stableunder destabilizing impulsive effects. Numerical examples are given to demonstrate the effectiveness of the obtained results.

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Des interventions ciblant l’amélioration cognitive sont de plus en plus à l’intérêt dans nombreux domaines, y compris la neuropsychologie. Bien qu'il existe de nombreuses méthodes pour maximiser le potentiel cognitif de quelqu’un, ils sont rarement appuyé par la recherche scientifique. D’abord, ce mémoire examine brièvement l'état des interventions d'amélioration cognitives. Il décrit premièrement les faiblesses observées dans ces pratiques et par conséquent il établit un modèle standard contre lequel on pourrait et devrait évaluer les diverses techniques ciblant l'amélioration cognitive. Une étude de recherche est ensuite présenté qui considère un nouvel outil de l'amélioration cognitive, une tâche d’entrainement perceptivo-cognitive : 3-dimensional multiple object tracking (3D-MOT). Il examine les preuves actuelles pour le 3D-MOT auprès du modèle standard proposé. Les résultats de ce projet démontrent de l’augmentation dans les capacités d’attention, de mémoire de travail visuel et de vitesse de traitement d’information. Cette étude représente la première étape dans la démarche vers l’établissement du 3D-MOT comme un outil d’amélioration cognitive.

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Min/max autocorrelation factor analysis (MAFA) and dynamic factor analysis (DFA) are complementary techniques for analysing short (> 15-25 y), non-stationary, multivariate data sets. We illustrate the two techniques using catch rate (cpue) time-series (1982-2001) for 17 species caught during trawl surveys off Mauritania, with the NAO index, an upwelling index, sea surface temperature, and an index of fishing effort as explanatory variables. Both techniques gave coherent results, the most important common trend being a decrease in cpue during the latter half of the time-series, and the next important being an increase during the first half. A DFA model with SST and UPW as explanatory variables and two common trends gave good fits to most of the cpue time-series. (c) 2004 International Council for the Exploration of the Sea. Published by Elsevier Ltd. All rights reserved.

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It is well known that self-generated stimuli are processed differently from externally generated stimuli. For example, many people have noticed since childhood that it is very difficult to make a self-tickling. In the auditory domain, self-generated sounds elicit smaller brain responses as compared to externally generated sounds, known as the sensory attenuation (SA) effect. SA is manifested in reduced amplitudes of evoked responses as measured through MEEG, decreased firing rates of neurons and a lower level of perceived loudness for self-generated sounds. The predominant explanation for SA is based on the idea that self-generated stimuli are predicted (e.g., the forward model account). It is the nature of their predictability that is crucial for SA. On the contrary, the sensory gating account emphasizes a general suppressive effect of actions on sensory processing, regardless of the predictability of the stimuli. Both accounts have received empirical support, which suggests that both mechanisms may exist. In chapter 2, three behavioural studies concerning the influence of motor activation on auditory perception were presented. Study 1 compared the effect of SA and attention in an auditory detection task and showed that SA was present even when substantial attention was paid to unpredictable stimuli. Study 2 compared the loudness perception of tones generated by others between Chinese and British participants. Compared to externally generated tones, a decrease in perceived loudness for others generated tones was found among Chinese but not among the British. In study 3, partial evidence was found that even when reading words that are related to action, auditory detection performance was impaired. In chapter 3, the classic SA effect of M100 suppression was replicated with MEG in study 4. With time-frequency analysis, a potential neural information processing sequence was found in auditory cortex. Prior to the onset of self-generated tones, there was an increase of oscillatory power in the alpha band. After the stimulus onset, reduced gamma power and alpha/beta phase locking were found. The three temporally segregated oscillatory events correlated with each other and with SA effect, which may be the underlying neural implementation of SA. In chapter 4, a TMS-MEG study was presented investigating the role of the cerebellum in adapting to delayed presentation of self-generated tones (study 5). It demonstrated that in sham stimulation condition, the brain can adapt to the delay (about 100 ms) within 300 trials of learning by showing a significant increase of SA effect in the suppression of M100, but not M200 component. Whereas after stimulating the cerebellum with a suppressive TMS protocol, the adaptation in M100 suppression disappeared and the pattern of M200 suppression reversed to M200 enhancement. These data support the idea that the suppressive effect of actions on auditory processing is a consequence of both motor driven sensory predictions and general sensory gating. The results also demonstrate the importance of neural oscillations in implementing SA effect and the critical role of the cerebellum in learning sensory predictions under sensory perturbation.

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El propósito de este estudio es medir los efectos que tiene el videojuego League of Legends en los procesos cognitivos de memoria de trabajo visual (MVT) y solución de problemas (SP). Para medir dichos efectos se implementó un diseño pre test-post con un grupo experimental y uno control, compuestos cada uno por siete participantes, en donde se evaluaron los procesos previamente mencionados utilizando los cubos de Corsi para MVT y las matrices del WAIS III para SP. Después de realizar los respectivos entrenamientos se encontraron resultados significativos en los diferentes momentos de aplicación. En el grupo experimental se encontraron diferencias en la variable dependiente SP, mientras que en el grupo control en MVT, pero no en la interacción entre grupos ni diferencias entre grupos, lo que sugiere un efecto de familiarización a la prueba.

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We present some estimates of the time of convergence to the equilibrium distribution in autonomous and periodic non-autonomous graphs, with ergodic stochastic adjacency matrices, using the eigenvalues of these matrices. On this way we generalize previous results from several authors, that only considered reversible matrices.