3 resultados para artificial language

em DI-fusion - The institutional repository of Université Libre de Bruxelles


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Statistical learning can be used to extract the words from continuous speech. Gómez, Bion, and Mehler (Language and Cognitive Processes, 26, 212–223, 2011) proposed an online measure of statistical learning: They superimposed auditory clicks on a continuous artificial speech stream made up of a random succession of trisyllabic nonwords. Participants were instructed to detect these clicks, which could be located either within or between words. The results showed that, over the length of exposure, reaction times (RTs) increased more for within-word than for between-word clicks. This result has been accounted for by means of statistical learning of the between-word boundaries. However, even though statistical learning occurs without an intention to learn, it nevertheless requires attentional resources. Therefore, this process could be affected by a concurrent task such as click detection. In the present study, we evaluated the extent to which the click detection task indeed reflects successful statistical learning. Our results suggest that the emergence of RT differences between within- and between-word click detection is neither systematic nor related to the successful segmentation of the artificial language. Therefore, instead of being an online measure of learning, the click detection task seems to interfere with the extraction of statistical regularities.

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Whether a terminally ill cancer patient should be actively fed or simply hydrated through subcutaneous or intravenous infusion of isotonic fluids is a matter of ongoing controversy among clinicians involved in the care of these patients. Under the auspices of the European Association for Palliative Care, a committee of experts developed guidelines to help clinicians make a reasonable decision on what type of nutritional support should be provided on a case-by-case basis. It was acknowledged that part of the controversy related to the definition of the terminal cancer patient, since this is a heterogeneous group of patients with different needs, expectations, and potential for a medical intervention. A major difficulty is the prediction of life expectancy and the patient's likely response to vigorous nutritional support. In an attempt to reach a decision on the type of treatment support (artificial nutrition vs. hydration) which would best meet the needs and expectations of the patient, we propose a three-step process: Step I: define the eight key elements necessary to reach a decision: Step II: make the decision; and Step III: reevaluate the patient and the proposed treatment at specified intervals. Step I involves assessing the patient concerning the following: 1) oncological/clinical condition; 2) symptoms; 3) expected length of survival; 4) hydration and nutritional status; 5) spontaneous or voluntary nutrient intake; 6) psychological profile; 7) gut function and potential route of administration; and 8) need for special services based on type of nutritional support prescribed. Step II involves the overall assessment of pros and cons, based on information determined in Step I, in order to reach an appropriate decision based on a well-defined end point (i.e. improvement of quality of life; maintaining patient survival; attaining rehydration). Step III involves the periodic reevaluation of the decision made in Step II based on the proposed goal and the attained result.

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Nowadays, the idea of a reciprocal influence of physiological and psychological processes seems to be widely accepted. For instance, current theories of embodied emotion suggest that knowledge about an emotion concept involves simulations of bodily experienced emotional states relevant to the concept. In line with this framework, the present study investigated whether actual levels of physiological arousal interact with the processing of emotional words. Participants performed 2 blocks of an attentional blink task, once after a cycling session (increased arousal) and once after a relaxation session (reduced arousal). Concretely, participants were instructed to detect and report 2 target words (T1 and T2) presented among a series of nonword distractors. T1 and T2 were either neutral, high arousal, or low arousal words. Results revealed that increased physiological arousal led to improved reports of high arousal T2 words, whereas reduced physiological arousal led to improved reports of low arousal T2 words. Neutral T2 remained unaffected by the arousing conditions. These findings emphasize that actual levels of physiological arousal modulate the cognitive access to arousal (in-)congruent emotional concepts and suggest a direct grounding of emotion knowledge in our bodily systems of arousal.