Phonological Iconicity electrifies: An ERP study on affective sound-to-meaning correspondences in German

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. Our experimental manipulations also investigate potential contributions of formal salience to the sublexical affective potential: Typically, negative high-arousing phonological segments-based on our calculations-tend to be less frequent and more structurally complex than neutral ones. We thus constructed two experimental sets, one involving this natural confound, while controlling for it in the other. A negative high-arousing sublexical affective potential in the strictly controlled stimulus set yielded an early posterior negativity (EPN), in similar ways as an independent manipulation of lexical affective content did. When other potentially salient formal features at the sublexical level were not controlled for, the effect of the sublexical affective potential was strengthened and prolonged (250-650 ms), presumably because formal salience helps making specific phoneme clusters efficient sublexical markers of negative high-arousing affective meaning. These neurophysiological data support the assumption that the organization of a language's vocabulary involves systematic sound-to-meaning correspondences at the phonemic level that influence the way we process language.

Abstract licence: CC BY

40 more references, whose wording the paper’s licence keeps private.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.