Publications by authors named "Arash Aryani"

Prior investigations have demonstrated that people tend to link pseudowords such as to rounded shapes and to spiky shapes, but the cognitive processes underlying this matching bias have remained controversial. Here, we present three experiments underscoring the fundamental role of emotional mediation in this sound-shape mapping. Using stimuli from key previous studies, we found that -like pseudowords and spiky shapes, compared with -like pseudowords and rounded shapes, consistently elicit higher levels of affective arousal, which we assessed through both subjective ratings (Experiment 1, = 52) and acoustic models implemented on the basis of pseudoword material (Experiment 2, = 70).

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Recent studies have shown that a similarity between sound and meaning of a word (i.e., iconicity) can help more readily access the meaning of that word, but the neural mechanisms underlying this beneficial role of iconicity in semantic processing remain largely unknown.

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We compared event-related potentials during sentence reading, using impression formation equations of a model of affective coherence, to investigate the role of affective content processing during meaning making. The model of Affect Control Theory (ACT; Heise, 1979, 2007) predicts and quantifies the degree to which social interactions deflect from prevailing social norms and values - based on the affective meanings of involved concepts. We tested whether this model can predict the amplitude of brain waves traditionally associated with semantic processing.

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Most language users agree that some words sound harsh (e.g. grotesque) whereas others sound soft and pleasing (e.

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A similarity between the form and meaning of a word (i.e., iconicity) may help language users to more readily access its meaning through direct form-meaning mapping.

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The long history of poetry and the arts, as well as recent empirical results suggest that the way a word sounds (e.g., soft vs.

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The literary genre of poetry is inherently related to the expression and elicitation of emotion via both content and form. To explore the nature of this affective impact at an extremely basic textual level, we collected ratings on eight different scales-valence, arousal, friendliness, sadness, spitefulness, poeticity, onomatopoeia, and liking-for 57 German poems ("") which the contemporary author H. M.

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While linguistic theory posits an arbitrary relation between signifiers and the signified (de Saussure, 1916), our analysis of a large-scale German database containing affective ratings of words revealed that certain phoneme clusters occur more often in words denoting concepts with negative and arousing meaning. Here, we investigate how such phoneme clusters that potentially serve as sublexical markers of affect can influence language processing. We registered the EEG signal during a lexical decision task with a novel manipulation of the words' putative sublexical affective potential: the means of valence and arousal values for single phoneme clusters, each computed as a function of respective values of words from the database these phoneme clusters occur in.

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A crucial aspect of bilingual communication is the ability to identify the language of an input. Yet, the neural and cognitive basis of this ability is largely unknown. Moreover, it cannot be easily incorporated into neuronal models of bilingualism, which posit that bilinguals rely on the same neural substrates for both languages and concurrently activate them even in monolingual settings.

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A GROWING BODY OF LITERATURE IN PSYCHOLOGY, LINGUISTICS, AND THE NEUROSCIENCES HAS PAID INCREASING ATTENTION TO THE UNDERSTANDING OF THE RELATIONSHIPS BETWEEN PHONOLOGICAL REPRESENTATIONS OF WORDS AND THEIR MEANING: a phenomenon also known as phonological iconicity. In this article, we investigate how a text's intended emotional meaning, particularly in literature and poetry, may be reflected at the level of sublexical phonological salience and the use of foregrounded elements. To extract such elements from a given text, we developed a probabilistic model to predict the exceeding of a confidence interval for specific sublexical units concerning their frequency of occurrence within a given text contrasted with a reference linguistic corpus for the German language.

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