Affective Arousal Links Sound to Meaning.

Prior investigations have demonstrated that people tend to link pseudowords such as bouba to rounded shapes and kiki 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 kiki-like pseudowords and spiky shapes, compared with bouba-like pseudowords and rounded shapes, consistently elicit higher levels of affective arousal, which we assessed through both subjective ratings (Experiment 1, N = 52) and acoustic models implemented on the basis of pseudoword material (Experiment 2, N = 70). Crucially, the mediating effect of arousal generalizes to novel pseudowords (Experiment 3, N = 64, which was preregistered). These findings highlight the role that human emotion may play in language development and evolution by grounding associations between abstract concepts (e.g., shapes) and linguistic signs (e.g., words) in the affective system.

Affective iconic words benefit from additional sound-meaning integration in the left amygdala.

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. In an fMRI study, we focused on the affective domain and examined whether affective iconic words (e.g., high arousal in both sound and meaning) activate additional brain regions that integrate emotional information from different domains (i.e., sound and meaning). In line with our hypothesis, affective iconic words, compared to their non-iconic counterparts, elicited additional BOLD responses in the left amygdala known for its role in multimodal representation of emotions. Functional connectivity analyses revealed that the observed amygdalar activity was modulated by an interaction of iconic condition and activations in two hubs representative for processing sound (left superior temporal gyrus) and meaning (left inferior frontal gyrus) of words. These results provide a neural explanation for the facilitative role of iconicity in language processing and indicate that language users are sensitive to the interaction between sound and meaning aspect of words, suggesting the existence of iconicity as a general property of human language.

Making sense of social interaction: Emotional coherence drives semantic integration as assessed by event-related potentials.

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. To this end, we visually presented sentences describing basic subject-verb-object social interactions and measured event-related potentials for final words of sentences from three different conditions of affective deflection (low, medium, high) as computed by a variant of the ACT model (Schröder, 2011). Sentence stimuli were closely controlled across conditions for alternate semantic dimensions such as contextual constraints, cloze probabilities, co-occurrences of subject-object and verb-object relations. Personality characteristics (schizotypy, Big Five) were assessed to account for individual differences, assumed to influence emotion-language interactions in information processing. Affective deflection provoked increased negativity of ERP waves during the P2/N2 and N400 components. Our data suggest that affective incoherence is perceived as conflicting information interfering with early semantic processing and that increased respective processing demands - in particular in the case of medium violations of social norms - linger on until the N400 time window classically associated with the integration of concepts into embedding context. We conclude from these results that affective meanings influence basic stages of meaning making.

Why 'piss' is ruder than 'pee'? The role of sound in affective meaning making.

Most language users agree that some words sound harsh (e.g. grotesque) whereas others sound soft and pleasing (e.g. lagoon). While this prominent feature of human language has always been creatively deployed in art and poetry, it is still largely unknown whether the sound of a word in itself makes any contribution to the word's meaning as perceived and interpreted by the listener. In a large-scale lexicon analysis, we focused on the affective substrates of words' meaning (i.e. affective meaning) and words' sound (i.e. affective sound); both being measured on a two-dimensional space of valence (ranging from pleasant to unpleasant) and arousal (ranging from calm to excited). We tested the hypothesis that the sound of a word possesses affective iconic characteristics that can implicitly influence listeners when evaluating the affective meaning of that word. The results show that a significant portion of the variance in affective meaning ratings of printed words depends on a number of spectral and temporal acoustic features extracted from these words after converting them to their spoken form (study1). In order to test the affective nature of this effect, we independently assessed the affective sound of these words using two different methods: through direct rating (study2a), and through acoustic models that we implemented based on pseudoword materials (study2b). In line with our hypothesis, the estimated contribution of words' sound to ratings of words' affective meaning was indeed associated with the affective sound of these words; with a stronger effect for arousal than for valence. Further analyses revealed crucial phonetic features potentially causing the effect of sound on meaning: For instance, words with short vowels, voiceless consonants, and hissing sibilants (as in 'piss') feel more arousing and negative. Our findings suggest that the process of meaning making is not solely determined by arbitrary mappings between formal aspects of words and concepts they refer to. Rather, even in silent reading, words' acoustic profiles provide affective perceptual cues that language users may implicitly use to construct words' overall meaning.

Affective Congruence between Sound and Meaning of Words Facilitates Semantic Decision.

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. Previous work has supported this view by providing empirical evidence for this facilitatory effect in sign language, as well as for onomatopoetic words (e.g., cuckoo) and ideophones (e.g., zigzag). Thus, it remains largely unknown whether the beneficial role of iconicity in making semantic decisions can be considered a general feature in spoken language applying also to "ordinary" words in the lexicon. By capitalizing on the affective domain, and in particular arousal, we organized words in two distinctive groups of iconic vs. non-iconic based on the congruence vs. incongruence of their lexical (meaning) and sublexical (sound) arousal. In a two-alternative forced choice task, we asked participants to evaluate the arousal of printed words that were lexically either high or low arousing. In line with our hypothesis, iconic words were evaluated more quickly and more accurately than their non-iconic counterparts. These results indicate a processing advantage for iconic words, suggesting that language users are sensitive to sound-meaning mappings even when words are presented visually and read silently.

The Sound of Words Evokes Affective Brain Responses.

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. harsh) can convey affective information related to emotional responses (e.g., pleasantness vs. harshness). However, the neural correlates of the affective potential of the sound of words remain unknown. In an fMRI study involving passive listening, we focused on the affective dimension of arousal and presented words organized in two discrete groups of sublexical (i.e., sound) arousal (high vs. low), while controlling for lexical (i.e., semantic) arousal. Words sounding high arousing, compared to their low arousing counterparts, resulted in an enhanced BOLD signal in bilateral posterior insula, the right auditory and premotor cortex, and the right supramarginal gyrus. This finding provides first evidence on the neural correlates of affectivity in the sound of words. Given the similarity of this neural network to that of nonverbal emotional expressions and affective prosody, our results support a unifying view that suggests a core neural network underlying any type of affective sound processing.

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.

On the Relation between the General Affective Meaning and the Basic Sublexical, Lexical, and Inter-lexical Features of Poetic Texts-A Case Study Using 57 Poems of H. M. Enzensberger.

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 general affective meaning scales-valence, arousal, friendliness, sadness, spitefulness, poeticity, onomatopoeia, and liking-for 57 German poems ("die verteidigung der wölfe") which the contemporary author H. M. Enzensberger had labeled as either "friendly," "sad," or "spiteful." Following Jakobson's (1960) view on the vivid interplay of hierarchical text levels, we used multiple regression analyses to explore the specific influences of affective features from three different text levels (sublexical, lexical, and inter-lexical) on the perceived general affective meaning of the poems using three types of predictors: (1) Lexical predictor variables capturing the mean valence and arousal potential of words; (2) Inter-lexical predictors quantifying peaks, ranges, and dynamic changes within the lexical affective content; (3) Sublexical measures of basic affective tone according to sound-meaning correspondences at the sublexical level (see Aryani et al., 2016). We find the lexical predictors to account for a major amount of up to 50% of the variance in affective ratings. Moreover, inter-lexical and sublexical predictors account for a large portion of additional variance in the perceived general affective meaning. Together, the affective properties of all used textual features account for 43-70% of the variance in the affective ratings and still for 23-48% of the variance in the more abstract aesthetic ratings. In sum, our approach represents a novel method that successfully relates a prominent part of variance in perceived general affective meaning in this corpus of German poems to quantitative estimates of affective properties of textual components at the sublexical, lexical, and inter-lexical level.

Activation Patterns throughout the Word Processing Network of L1-dominant Bilinguals Reflect Language Similarity and Language Decisions.

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. Here we hypothesized that bilinguals can employ language-specific sublexical (bigram frequency) and lexical (orthographic neighborhood size) statistics for language recognition. Moreover, we investigated the neural networks representing language-specific statistics and hypothesized that language identity is encoded in distributed activation patterns within these networks. To this end, German-English bilinguals made speeded language decisions on visually presented pseudowords during fMRI. Language attribution followed lexical neighborhood sizes both in first (L1) and second (L2) language. RTs revealed an overall tuning to L1 bigram statistics. Neuroimaging results demonstrated tuning to L1 statistics at sublexical (occipital lobe) and phonological (temporoparietal lobe) levels, whereas neural activation in the angular gyri reflected sensitivity to lexical similarity to both languages. Analysis of distributed activation patterns reflected language attribution as early as in the ventral stream of visual processing. We conclude that in language-ambiguous contexts visual word processing is dominated by L1 statistical structure at sublexical orthographic and phonological levels, whereas lexical search is determined by the structure of both languages. Moreover, our results demonstrate that language identity modulates distributed activation patterns throughout the reading network, providing a key to language identity representations within this shared network.

Extracting salient sublexical units from written texts: "Emophon," a corpus-based approach to phonological iconicity.

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. Implementing this model in a computational application, we provide a text analysis tool which automatically delivers information about sublexical phonological salience allowing researchers, inter alia, to investigate effects of the sublexical emotional tone of texts based on current findings on phonological iconicity.