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Проведен анализ пространственной семантики различных категорий русских существительных, входящих в психолингви-стическую базуданных; особое внимание уделяется абстрактным концептам. Выявлены различия пространственной семантики наименований физических ощущений и действий, эмоций, ментальных процессов. Полученны ерезультаты обсуждаются с точки зрения отдельных подходов в рамках теории воплощенного познания – теории концептуальной метафоры, теории слов как социальных инструментов (WAT, Words As social Tools), нейросемантики.
In an eye-tracking study we tested the hypothesis that comprehension is facilitated by a match between the order of the verb and its arguments in a sentence and the order of the actual sensorimotor interaction with these objects (for example, in the phrase put the bag into the box, the order of the arguments corresponds to the order of motor actions: take the bag, put it into the box) could facilitate comprehension of such constructions. We tested 40 native Russian speakers in a visual world sentence-picture matching task. In prepositional constructions, there was no difference between conditions that matched or mismatched sensorimotor stereotypes, whereas in instrumental constructions, sensorimotor stereotypes facilitated comprehension.
Inhalt: 1. Einführung 1.1 Methoden zur Untersuchung sprachlicher Fähigkeiten 1.2 Die Anfänge der Erforschung von Mehrsprachigkeit 2. Funktionelle Bildgebung 2.1 Einfluss des Erwerbsalters 2.2 Einfluss der Sprachkompetenz 3. Elektrophysiologische Daten 3.1 Einfluss des Erwerbsalters 3.2 Einfluss der Sprachkompetenz 4. Neurokognitive Modelle 4.1 Lexikalisch-semantische Modelle 4.2 Lexikalisch-Grammatikalisches Modell 4.3 Implizit-Explizites Modell 5. Schlussfolgerung 6. Literatur
Zur Rolle des Pronomen to/eto in spezifizierenden Kopulaktionstrukturen im polnischen und russischen
(2001)
Inhalt: 1. Einleitung 1.1 Blickbewegungen beim Lesen 1.2 Kognitive Kontrolle und verteilte Verarbeitung 2. Fragestellungen und Hypothesen 3. Methoden 3.1 Probanden 3.2 Material 3.3 Durchführung und Auswertung 4. Ergebnisse 4.1 Unterschiede in Effekten der Wortvorhersagbarkeit 4.2 Unterschiede in Effekten der Wortfrequenz 5. Diskussion 6. Literatur
In the present study, we investigated younger and older Persian preschoolers' response tendency and accuracy toward yes/no questions about a coloring activity. Overall, 107 three- to four-year-olds and five- to six-year-old children were asked positive and negative yes/no questions about a picture coloring activity. The questions focused on three question contents namely, actions, environment and person. As for children's response tendency, they showed a compliance tendency. That is, they provided yes and no responses to positively and negatively formed questions respectively. Children especially younger ones were more compliant toward positive questions and their tendency decreased by age. In addition, the results revealed children's highest rate of compliance tendency toward environment inquiries. Concerning response accuracy, the effects of age and question content were significant. Specifically, older children provided more accurate responses than their younger counterparts, especially to yes/no questions asked about the actions performed during the activity. The findings suggest that depending on the format and the content of yes/no questions younger and older children's response accuracy and tendency differ.
Yet another Theta-System
(2002)
There is a wealth of evidence showing that increasing the distance between an argument and its head leads to more processing effort, namely, locality effects: these are usually associated with constraints in working memory (DLT: Gibson, 2000: activation-based model: Lewis and Vasishth, 2005). In SOV languages, however, the opposite effect has been found: antilocality (see discussion in Levy et al., 2013). Antilocality effects can be explained by the expectation based approach as proposed by Levy (2008) or by the activation-based model of sentence processing as proposed by Lewis and Vasishth (2005). We report an eye-tracking and a self-paced reading study with sentences in Spanish together with measures of individual differences to examine the distinction between expectation- and memory based accounts, and within memory-based accounts the further distinction between DLT and the activation-based model. The experiments show that (i) antilocality effects as predicted by the expectation account appear only for high-capacity readers; (ii) increasing dependency length by interposing material that modifies the head of the dependency (the verb) produces stronger facilitation than increasing dependency length with material that does not modify the head; this is in agreement with the activation-based model but not with the expectation account; and (iii) a possible outcome of memory load on low-capacity readers is the increase in regressive saccades (locality effects as predicted by memory-based accounts) or, surprisingly, a speedup in the self-paced reading task; the latter consistent with good-enough parsing (Ferreira et al., 2002). In sum, the study suggests that individual differences in working memory capacity play a role in dependency resolution, and that some of the aspects of dependency resolution can be best explained with the activation-based model together with a prediction component.
There is a wealth of evidence showing that increasing the distance between an argument and its head leads to more processing effort, namely, locality effects; these are usually associated with constraints in working memory (DLT: Gibson, 2000; activation-based model: Lewis and Vasishth, 2005). In SOV languages, however, the opposite effect has been found: antilocality (see discussion in Levy et al., 2013). Antilocality effects can be explained by the expectation-based approach as proposed by Levy (2008) or by the activation-based model of sentence processing as proposed by Lewis and Vasishth (2005). We report an eye-tracking and a self-paced reading study with sentences in Spanish together with measures of individual differences to examine the distinction between expectation- and memory-based accounts, and within memory-based accounts the further distinction between DLT and the activation-based model. The experiments show that (i) antilocality effects as predicted by the expectation account appear only for high-capacity readers; (ii) increasing dependency length by interposing material that modifies the head of the dependency (the verb) produces stronger facilitation than increasing dependency length with material that does not modify the head; this is in agreement with the activation-based model but not with the expectation account; and (iii) a possible outcome of memory load on low-capacity readers is the increase in regressive saccades (locality effects as predicted by memory-based accounts) or, surprisingly, a speedup in the self-paced reading task; the latter consistent with good-enough parsing (Ferreira et al., 2002). In sum, the study suggests that individual differences in working memory capacity play a role in dependency resolution, and that some of the aspects of dependency resolution can be best explained with the activation-based model together with a prediction component.
Inferences about hypotheses are ubiquitous in the cognitive sciences. Bayes factors provide one general way to compare different hypotheses by their compatibility with the observed data. Those quantifications can then also be used to choose between hypotheses. While Bayes factors provide an immediate approach to hypothesis testing, they are highly sensitive to details of the data/model assumptions and it's unclear whether the details of the computational implementation (such as bridge sampling) are unbiased for complex analyses. Hem, we study how Bayes factors misbehave under different conditions. This includes a study of errors in the estimation of Bayes factors; the first-ever use of simulation-based calibration to test the accuracy and bias of Bayes factor estimates using bridge sampling; a study of the stability of Bayes factors against different MCMC draws and sampling variation in the data; and a look at the variability of decisions based on Bayes factors using a utility function. We outline a Bayes factor workflow that researchers can use to study whether Bayes factors are robust for their individual analysis. Reproducible code is available from haps://osf.io/y354c/. <br /> Translational Abstract <br /> In psychology and related areas, scientific hypotheses are commonly tested by asking questions like "is [some] effect present or absent." Such hypothesis testing is most often carried out using frequentist null hypothesis significance testing (NIIST). The NHST procedure is very simple: It usually returns a p-value, which is then used to make binary decisions like "the effect is present/abscnt." For example, it is common to see studies in the media that draw simplistic conclusions like "coffee causes cancer," or "coffee reduces the chances of geuing cancer." However, a powerful and more nuanced alternative approach exists: Bayes factors. Bayes factors have many advantages over NHST. However, for the complex statistical models that arc commonly used for data analysis today, computing Bayes factors is not at all a simple matter. In this article, we discuss the main complexities associated with computing Bayes factors. This is the first article to provide a detailed workflow for understanding and computing Bayes factors in complex statistical models. The article provides a statistically more nuanced way to think about hypothesis testing than the overly simplistic tendency to declare effects as being "present" or "absent".