The Emotions of Abstract Words: A Distributional Semantic Analysis

Spice up the moment: The influence of spicy taste on people's metaphorical perspectives on time

Embodied cognition contends that sensorimotor experiences undergird cognitive processes. Three embodied cross-domain metaphorical mappings constitute quintessential illustrations: spatial navigation and orientation underpin the conceptualization of time and emotion and gustatory sensation underlies the formulation of emotion. Threading together these strands of insights, the present research consisted of three studies explored the potential influence of spicy taste on people's metaphorical perspectives on time. The results revealed a positive correlation between spicy taste and the ego-moving metaphor for time such that individuals who enjoyed spicy taste (Study 1) and who consumed spicy (vs. salty) snack (Study 2) exhibited a predilection for the ego-moving perspective when cognizing a temporally ambiguous event. Because both spicy taste and the ego-moving metaphor are associated with anger and approach motivation, the latter two were postulated to be related to the novel taste-time relationship. Corroborative evidence for the hypothesis was found, which indicated that spicy (vs. salty) intake elicited significantly stronger anger toward and significantly greater approach-motivated perception of a rescheduled temporal event (Study 3). Taken together, the current findings demonstrate that spicy taste may play a role in people's perspectives on the movement of events in time and highlight the involved embodied interrelation between language, emotion, and cognition.

Word-association norms for 1,100 French words with varying levels of concreteness

The organisation of concepts in the mental lexicon is a widely studied research topic in experimental psychology. For instance, several studies have shown that whereas concrete concepts are organised according to semantic similarity, abstract concepts are organised according to verbal association. However, these results are not systematically replicated, mainly due to a lack of normative database especially in French. To that end, we introduce a French word-association database for 1,100 cues with varying levels of concreteness from abstract to concrete concepts. Analyses from the word-association task revealed stronger association strength for concrete concepts compared with abstract concepts. Additional results showed that cues tend to elicit responses of a similar level of concreteness. The database will be useful for investigators interested in French verbal associations for abstract and concrete concepts. The data (available on OSF https://osf.io/dhuqs/) introduce responses organised according to association strength and provides cue concreteness.

The good, the bad, and the ambivalent: Extrapolating affective values for 38,000+ Chinese words via a computational model

Word affective ratings are important tools in psycholinguistic research, natural language processing, and many other fields. However, even for well-studied languages, such norms are usually limited in scale. To extrapolate affective (i.e., valence and arousal) values for words in the SUBTLEX-CH database (Cai & Brysbaert, 2010, PLoS ONE, 5(6):e10729), we implemented a computational neural network which captured how words' vector-based semantic representations corresponded to the probability densities of their valence and arousal. Based on these probability density functions, we predicted not only a word's affective values, but also their respective degrees of variability that could characterize individual differences in human affective ratings. The resulting estimates of affective values largely converged with human ratings for both valence and arousal, and the estimated degrees of variability also captured important features of the variability in human ratings. We released the extrapolated affective values, together with their corresponding degrees of variability, for over 38,000 Chinese words in the Open Science Framework ( https://osf.io/s9zmd/ ). We also discussed how the view of embodied cognition could be illuminated by this computational model.

Neurobiological mechanisms for language, symbols and concepts: Clues from brain-constrained deep neural networks

Neural networks are successfully used to imitate and model cognitive processes. However, to provide clues about the neurobiological mechanisms enabling human cognition, these models need to mimic the structure and function of real brains. Brain-constrained networks differ from classic neural networks by implementing brain similarities at different scales, ranging from the micro- and mesoscopic levels of neuronal function, local neuronal links and circuit interaction to large-scale anatomical structure and between-area connectivity. This review shows how brain-constrained neural networks can be applied to study in silico the formation of mechanisms for symbol and concept processing and to work towards neurobiological explanations of specifically human cognitive abilities. These include verbal working memory and learning of large vocabularies of symbols, semantic binding carried by specific areas of cortex, attention focusing and modulation driven by symbol type, and the acquisition of concrete and abstract concepts partly influenced by symbols. Neuronal assembly activity in the networks is analyzed to deliver putative mechanistic correlates of higher cognitive processes and to develop candidate explanations founded in established neurobiological principles.

Brain Signatures of Embodied Semantics and Language: A Consensus Paper

According to embodied theories (including embodied, embedded, extended, enacted, situated, and grounded approaches to cognition), language representation is intrinsically linked to our interactions with the world around us, which is reflected in specific brain signatures during language processing and learning. Moving on from the original rivalry of embodied vs. amodal theories, this consensus paper addresses a series of carefully selected questions that aim at determining when and how rather than whether motor and perceptual processes are involved in language processes. We cover a wide range of research areas, from the neurophysiological signatures of embodied semantics, e.g., event-related potentials and fields as well as neural oscillations, to semantic processing and semantic priming effects on concrete and abstract words, to first and second language learning and, finally, the use of virtual reality for examining embodied semantics. Our common aim is to better understand the role of motor and perceptual processes in language representation as indexed by language comprehension and learning. We come to the consensus that, based on seminal research conducted in the field, future directions now call for enhancing the external validity of findings by acknowledging the multimodality, multidimensionality, flexibility and idiosyncrasy of embodied and situated language and semantic processes.

Words hurt: common and distinct neural substrates underlying nociceptive and semantic pain

Introduction

Recent studies have shown that processing semantic pain, such as words associated with physical pain, modulates pain perception and enhances activity in regions of the pain matrix. A direct comparison between activations due to noxious stimulation and processing of words conveying physical pain may clarify whether and to what extent the neural substrates of nociceptive pain are shared by semantic pain. Pain is triggered also by experiences of social exclusion, rejection or loss of significant others (the so-called social pain), therefore words expressing social pain may modulate pain perception similarly to what happens with words associated with physical pain. This event-related fMRI study aims to compare the brain activity related to perceiving nociceptive pain and that emerging from processing semantic pain, i.e., words related to either physical or social pain, in order to identify common and distinct neural substrates.

Methods

Thirty-four healthy women underwent two fMRI sessions each. In the Semantic session, participants were presented with positive words, negative pain-unrelated words, physical pain-related words, and social pain-related words. In the Nociceptive session, participants received cutaneous mechanical stimulations that could be either painful or not. During both sessions, participants were asked to rate the unpleasantness of each stimulus. Linguistic stimuli were also rated in terms of valence, arousal, pain relatedness, and pain intensity, immediately after the Semantic session.

Results

In the Nociceptive session, the 'nociceptive stimuli' vs. 'non-nociceptive stimuli' contrast revealed extensive activations in SI, SII, insula, cingulate cortex, thalamus, and dorsolateral prefrontal cortex. In the Semantic session, words associated with social pain, compared to negative pain-unrelated words, showed increased activity in most of the same areas, whereas words associated with physical pain, compared to negative pain-unrelated words, only activated the left supramarginal gyrus and partly the postcentral gyrus.

Discussion

Our results confirm that semantic pain partly shares the neural substrates of nociceptive pain. Specifically, social pain-related words activate a wide network of regions, mostly overlapping with those pertaining to the affective-motivational aspects of nociception, whereas physical pain-related words overlap with a small cluster including regions related to the sensory-discriminative aspects of nociception. However, most regions of overlap are differentially activated in different conditions.

Abstract concepts and emotion: cross-linguistic evidence and arguments against affective embodiment

How are abstract concepts such as 'freedom' and 'democracy' represented in the mind? One prominent proposal suggests that abstract concepts are grounded in emotion. Supporting this 'affective embodiment' account, abstract concepts are rated to be more strongly positive or more strongly negative than concrete concepts. This paper demonstrates that this finding generalizes across languages by synthesizing rating data from Cantonese, Mandarin Chinese, Croatian, Dutch, French, German, Indonesian, Italian, Polish and Spanish. However, a deeper look at the same data suggests that the idea of emotional grounding only characterizes a small subset of abstract concepts. Moreover, when the concreteness/abstractness dimension is not operationalized using concreteness ratings, it is actually found that concrete concepts are rated as more emotional than abstract ones. Altogether, these results suggest limitations to the idea that emotion is an important factor in the grounding of abstract concepts. This article is part of the theme issue 'Concepts in interaction: social engagement and inner experiences'.

Editorial concepts in interaction: social engagement and inner experiences

This theme issue aims to view the literature on concepts through a novel lens, that of social interaction and its influence on inner experiences. It discusses unsolved problems in literature on concepts, emphasizing the distinction between concrete versus abstract concepts and external versus internal grounding. This introductory article reflects the two research streams that the theme aims to bridge-in this area, the dimension of embodied interaction with others and how this influences the interaction with ourselves is still underexplored. In the first part, we discuss recent trends in social cognition, showing how interacting with others influences our concepts. In the second part, we address how social interactions become part of our inner world in a Vygotskian fashion. First, we illustrate how interoception, emotion and metacognition are connected with concepts and knowledge. Second, we deal with how language, in both its outer and inner form, can empower cognition and concepts. We also briefly describe how novel experimental and computational methods contribute to investigating the online use of concepts. Overall, this introductory article outlines the potentialities of an integrated and interactive approach that can give new, fresh life to a topic, that of concepts, which lies at the root of human cognition. This article is part of the theme issue 'Concepts in interaction: social engagement and inner experiences'.

The structure of lay-concepts within the fear spectrum revealed using emotional verbal fluency

Given the fact that natural language analysis can distinguish constituents of mental constructs, the present research was designed to investigate the structure of concepts related to the broad spectrum of emotions comprising worry, fear, anxiety, and panic, which in this article is referred to as the ‘fear spectrum’. A new technique presented here is based on a word association task and enables a description of the structure of emotion concepts. The technique is a variant of a verbal fluency task, i.e. emotional verbal fluency technique. Two studies have been conducted: the first to examine the cognitive structure of concepts within the fear spectrum (n = 280, 150 women, 130 men) and the second to confirm the stability of word association in the fear tasks and differentiation of the fear concepts in relation to trait anxiety and dogmatism (n = 190, 100 women, 90 men). A hierarchical clustering analysis, based on the linguistic material, i.e. words produced by the participants for the task of anxiety, was performed to present in what way the emotional verbal fluency technique can be applied to explore the structure of emotional concepts. According to our results, there is a relatively constant tendency in producing semantic clusters (emotional word association) among lay people. Moreover, produced clusters allow to describe the structure and to differentiate lay-concepts within the fear spectrum, such as worry, fear, anxiety, panic [respectively in Polish: obawa, lęk, strach, panika].

Distributional Measures of Semantic Abstraction

This article provides an in-depth study of distributional measures for distinguishing between degrees of semantic abstraction. Abstraction is considered a “central construct in cognitive science” and a “process of information reduction that allows for efficient storage and retrieval of central knowledge”. Relying on the distributional hypothesis, computational studies have successfully exploited measures of contextual co-occurrence and neighbourhood density to distinguish between conceptual semantic categorisations. So far, these studies have modeled semantic abstraction across lexical-semantic tasks such as ambiguity; diachronic meaning changes; abstractness vs. concreteness; and hypernymy. Yet, the distributional approaches target different conceptual types of semantic relatedness, and as to our knowledge not much attention has been paid to apply, compare or analyse the computational abstraction measures across conceptual tasks. The current article suggests a novel perspective that exploits variants of distributional measures to investigate semantic abstraction in English in terms of the abstract–concrete dichotomy (e.g., glory–banana) and in terms of the generality–specificity distinction (e.g., animal–fish), in order to compare the strengths and weaknesses of the measures regarding categorisations of abstraction, and to determine and investigate conceptual differences. In a series of experiments we identify reliable distributional measures for both instantiations of lexical-semantic abstraction and reach a precision higher than 0.7, but the measures clearly differ for the abstract–concrete vs. abstract–specific distinctions and for nouns vs. verbs. Overall, we identify two groups of measures, (i) frequency and word entropy when distinguishing between more and less abstract words in terms of the generality–specificity distinction, and (ii) neighbourhood density variants (especially target–context diversity) when distinguishing between more and less abstract words in terms of the abstract–concrete dichotomy. We conclude that more general words are used more often and are less surprising than more specific words, and that abstract words establish themselves empirically in semantically more diverse contexts than concrete words. Finally, our experiments once more point out that distributional models of conceptual categorisations need to take word classes and ambiguity into account: results for nouns vs. verbs differ in many respects, and ambiguity hinders fine-tuning empirical observations.

Exploring What Is Encoded in Distributional Word Vectors: A Neurobiologically Motivated Analysis

The pervasive use of distributional semantic models or word embeddings for both cognitive modeling and practical application is because of their remarkable ability to represent the meanings of words. However, relatively little effort has been made to explore what types of information are encoded in distributional word vectors. Knowing the internal knowledge embedded in word vectors is important for cognitive modeling using distributional semantic models. Therefore, in this paper, we attempt to identify the knowledge encoded in word vectors by conducting a computational experiment using Binder et al.'s (2016) featural conceptual representations based on neurobiologically motivated attributes. In an experiment, these conceptual vectors are predicted from text-based word vectors using a neural network and linear transformation, and prediction performance is compared among various types of information. The analysis demonstrates that abstract information is generally predicted more accurately by word vectors than perceptual and spatiotemporal information, and specifically, the prediction accuracy of cognitive and social information is higher. Emotional information is also found to be successfully predicted for abstract words. These results indicate that language can be a major source of knowledge about abstract attributes, and they support the recent view that emphasizes the importance of language for abstract concepts. Furthermore, we show that word vectors can capture some types of perceptual and spatiotemporal information about concrete concepts and some relevant word categories. This suggests that language statistics can encode more perceptual knowledge than often expected.

Thematic and other semantic relations central to abstract (and concrete) concepts

In this article, we discuss multiple types of meaningful (semantic) relations underlying abstract (as compared to concrete) concepts. We adopt the viewpoint that words act as cues to meaning (Elman in Ment Lexicon 6(1):1-34, 2011; Lupyan and Lewis in Lang Cogn Neurosci 34(10):1319-1337, 2019), which is dependent on the dynamic contents of a comprehender's mental model of the situation. This view foregrounds the importance of both linguistic and real-world context as individuals make sense of words, flexibly access relevant knowledge, and understand described events and situations. We discuss theories of, and experimental work on, abstract concepts through the lens of the importance of thematic and other semantic relations. We then tie these findings to the sentence processing literature in which such meaningful relations within sentential contexts are often experimentally manipulated. In this literature, some specific classes/types of abstract words have been studied, although not comprehensively, and with limited connection to the literature on knowledge underlying abstract concepts reviewed herein. We conclude by arguing that the ways in which humans understand relatively more abstract concepts, in particular, can be informed by the careful study of words presented not in isolation, but rather in situational and linguistic contexts, and as a function of individual differences in knowledge, goals, and beliefs.

Lexicosemantic, affective, and distributional norms for 1,000 Dutch adjectives

The research of the word is still very much the research of the noun. Adjectives have been largely overlooked, despite being the second-largest word class in many languages and serving an important communicative function, because of the rich, nuanced qualifications they afford. Adjectives are also ideally suited to study the interface between cognition and emotion, as they naturally cover the entire range of lexicosemantic variables such as imageability (infinite-green), and affective variables such as valence (sad-happy). We illustrate this by showing how the centrality of words in the mental lexicon varies as a function of the words' affective dimensions, using newly collected norms for 1,000 Dutch adjectives. The norms include the lexicosemantic variables age of acquisition, familiarity, concreteness, and imageability; the affective variables valence, arousal, and dominance; and a variety of distributional variables, including network statistics resulting from a large-scale word association study. The norms are freely available from https://osf.io/nyg8v/, for researchers studying adjectives specifically or for whom adjectives constitute convenient stimuli to study other topics, such as vagueness, inference, spatial cognition, or affective word processing.

Semantic similarity and associated abstractness norms for 630 French word pairs

The representation of abstract concepts remains a challenge, justifying the need for further experimental investigation. To that end, we introduce a normative database for 630 semantically similar French word pairs and associated levels of abstractness for 1260 isolated words based on data from 900 subjects. The semantic similarity and abstractness norms were obtained in two studies using 7-point scales. The database is organised according to word-pair semantic similarity, abstractness, and associated lexical variables such as word length (in number of letters), word frequency, and other lexical variables to allow for matching of experimental material. The associated variables were obtained by cross-referencing our database with other known psycholinguistic databases including Lexique (New et al., 2004), the French Lexicon Project (Ferrand et al., 2010), Wordlex (Gimenes & New, 2016), and MEGALEX (Ferrand et al., 2018). We introduced sufficient diversity to allow researchers to select pairs with varying levels of semantic similarity and abstractness. In addition, it is possible to use these data as continuous or discrete variables. The full data are available in the supplementary materials as well as on OSF ( https://osf.io/qsd4v/ ).

Redundancy, isomorphism, and propagative mechanisms between emotional and amodal representations of words: A computational study

Some proposals claim that language acts as a link to propagate emotional and other modal information. Thus, there is an eminently amodal path of emotional propagation in the mental lexicon. Following these proposals, we present a computational model that emulates a linking mechanism (mapping function) between emotional and amodal representations of words using vector space models, emotional feature-based models, and neural networks. We analyzed three central concepts within the embodiment debate (redundancy, isomorphism, and propagative mechanisms) comparing two alternative hypotheses: semantic neighborhood hypothesis versus specific dimensionality hypothesis. Univariate and multivariate neural networks were trained for dimensional (N = 11,357) and discrete emotions (N = 2,266), and later we analyzed its predictions in a test set (N = 4,167 and N = 875, respectively). We showed how this computational model could propagate emotional responses to words without a direct emotional experience via amodal propagation, but no direct relations were found between emotional rates and amodal distances. Thereby, we found that there were clear redundancy and propagative mechanisms, but no isomorphism should be assumed. Results suggested that it was necessary to establish complex links to go beyond amodal distances of vector spaces. In this way, although the emotional rates of semantic neighborhoods could predict the emotional rates of target words, the mapping function of specific amodal features seemed to simulate emotional responses better. Thus, both hypotheses would not be mutually exclusive. We also showed that discrete emotions could have simpler relations between modal and amodal representations than dimensional emotions. All these results and their theoretical implications are discussed.

Catching the intangible: a role for emotion?

A crucial aspect of Gilead and colleagues’ ontology is the dichotomy between tangible and intangible representations, but the latter remains rather ill-defined. We propose a fundamental role for interoceptive experience and the statistical distribution of entities in language, especially for intangible representations, that we believe Gilead and colleagues’ ontology needs to incorporate.

Concrete vs. Abstract Semantics: From Mental Representations to Functional Brain Mapping

The nature of abstract and concrete semantics and differences between them have remained a debated issue in psycholinguistic and cognitive studies for decades. Most of the available behavioral and neuroimaging studies reveal distinctions between these two types of semantics, typically associated with a so-called “concreteness effect.” Many attempts have been made to explain these differences using various approaches, from purely theoretical linguistic and cognitive frameworks to neuroimaging experiments. In this brief overview, we will try to provide a snapshot of these diverse views and relationships between them and highlight the crucial issues preventing this problem from being solved. We will argue that one potentially beneficial way forward is to identify the neural mechanisms underpinning acquisition of the different types of semantics (e.g., by using neurostimulation techniques to establish causal relationships), which may help explain the distinctions found between the processing of concrete and abstract semantics.

Editors' Introduction: Abstract Concepts: Structure, Processing, and Modeling

Our ability to deal with abstract concepts is one of the most intriguing faculties of human cognition. Still, we know little about how such concepts are formed, processed, and represented in mind. For example, because abstract concepts do not designate referents that can be experienced through our body, the role of perceptual experiences in shaping their content remains controversial. Current theories suggest a variety of alternative explanations to the question of "how abstract concepts are represented in the human mind." These views pinpoint specific streams of semantic information that would play a prominent role in shaping the content of abstract concepts, such as situation-based information (e.g., Barsalou & Wiemer-Hastings, ), affective information (Kousta, Vigliocco, Vinson, Andrews, & Del Campo, ), and linguistic information (Louwerse, ). Rarely, these theoretical views are directly compared. In this special issue, current views are presented in their most recent and advanced form, and directly compared and discussed in a debate, which is reported at the end of each article. As a result, new exciting questions and challenges arise. These questions and challenges, reported in this introductory article, can arguably pave the way to new empirical studies and theoretical developments on the nature of abstract concepts.