One of the main limitations of natural language‐based approaches to meaning is that they do not incorporate multimodal representations the way humans do. In this study, we evaluate how well different kinds of models account for people's representations of both concrete and abstract concepts. The models we compare include unimodal distributional linguistic models as well as multimodal models which combine linguistic with perceptual or affective information. There are two types of linguistic models: those based on text corpora and those derived (...) from word association data. We present two new studies and a reanalysis of a series of previous studies. The studies demonstrate that both visual and affective multimodal models better capture behavior that reflects human representations than unimodal linguistic models. The size of the multimodal advantage depends on the nature of semantic representations involved, and it is especially pronounced for basic‐level concepts that belong to the same superordinate category. Additional visual and affective features improve the accuracy of linguistic models based on text corpora more than those based on word associations; this suggests systematic qualitative differences between what information is encoded in natural language versus what information is reflected in word associations. Altogether, our work presents new evidence that multimodal information is important for capturing both abstract and concrete words and that fully representing word meaning requires more than purely linguistic information. Implications for both embodied and distributional views of semantic representation are discussed. (shrink)

Conceptual knowledge is dynamic, fluid, and flexible, changing as a function of contextual factors at multiple scales. The Covid-19 pandemic can be considered a large-scale, global context that has fundamentally altered most people's experiences with the world. It has also introduced a new concept, COVID (or COVID-19), into our collective knowledgebase. What are the implications of this introduction for how existing conceptual knowledge is structured? Our collective emotional and social experiences with the world have been profoundly impacted by the Covid-19 (...) pandemic, and experience-based perspectives on concept representation suggest that emotional and social experiences are critical components of conceptual knowledge. Such changes in collective experience should, then, have downstream consequences on knowledge of emotion- and social-related concepts. Using a naturally occurring dataset derived from the social media platform Twitter, we show that semantic spaces for concepts related to our emotional experiences with Covid-19 (i.e., emotional concepts like FEAR)—but not for unrelated concepts (i.e., animals like CAT)—show quantifiable shifts as a function of the emergence of COVID-19 as a concept and its associated emotional and social experiences, shifts which persist 6 months after the onset of the pandemic. The findings support a dynamic view of conceptual knowledge wherein shared experiences affect conceptual structure. (shrink)

There is considerable evidence that language comprehenders derive lexical-semantic meaning by mentally simulating perceptual and motor attributes of described events. However, the nature of these simulations—including the level of detail that is incorporated and contexts under which simulations occur—is not well understood. Here, we examine the effects of first- versus third-person perspective on mental simulations during sentence comprehension. First-person sentences describing physical transfer towards or away from the body modulated response latencies when responses were made along a front-back axis, consistent (...) with the action-sentence compatibility effect. This effect was not observed for third-person sentences. The ACE was observed when making responses along a left-right axis for third-person, but not first-person sentences.sentences did not show an ACE along either axis. These results show that perspective is a detail that is simulated during action sentence comprehension, and that motoric activations are flexible and affected by the pronominal perspective used in the sentence. (shrink)

The topic is characterized by a highly interdisciplinary approach to the issue of action and language integration. Such an approach, combining computational models and cognitive robotics experiments with neuroscience, psychology, philosophy, and linguistic approaches, can be a powerful means that can help researchers disentangle ambiguous issues, provide better and clearer definitions, and formulate clearer predictions on the links between action and language. In the introduction we briefly describe the papers and discuss the challenges they pose to future research. We identify (...) four important phenomena the papers address and discuss in light of empirical and computational evidence: (a) the role played not only by sensorimotor and emotional information but also of natural language in conceptual representation; (b) the contextual dependency and high flexibility of the interaction between action, concepts, and language; (c) the involvement of the mirror neuron system in action and language processing; (d) the way in which the integration between action and language can be addressed by developmental robotics and Human-Robot Interaction. (shrink)

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. Current views are presented in their most recent and advanced form in this special issue, and directly compared and discussed in a lively debate, reported at the end of each chapter. The main results are reported in the editors’ introduction.

The attribution of mental states (MS) to other species typically follows ascala naturaepattern. However, “simple” mental states, including emotions, sensing, and feelings are attributed to a wider range of animals as compared to the so-called “higher” cognitive abilities. We propose that such attributions are based on the perceptual quality (i.e.imageability) of mental representations related toMSconcepts. We hypothesized that the attribution of highly imaginableMSis more dependent on the familiarity of participants with animals when compared to the attribution ofMSlow in imageability. In (...) addition, we also assessed how animal agreeableness, familiarity with animals, and the type of human-animal interaction related to the judged similarity of animals to humans. Sixty-one participants (19 females, 42 males) with a rural (n = 20) and urban (n = 41) background rated twenty-six wild and domestic animals for their perceived similarity with humans and ability to experience a set ofMS: (1) Highly imageableMS: joy, anger, and fear, and (2)MSlow in imageability: capacity to plan and deceive. Results show that more agreeable and familiar animals were considered more human-like. Primates, followed by carnivores, suines, ungulates, and rodents were rated more human-like than xenarthrans, birds, arthropods, and reptiles. HigherMSratings were given to more similar animals and more so if theMSattributed were high in imageability. Familiarity with animals was only relevant for the attribution of theMShigh in imageability. (shrink)

Humans can understand thousands of abstract words, even when they do not have clearly perceivable referents. Recent views highlight an important role of social experience in grounding of abstract concepts and sub-kinds of abstract concepts, but empirical work in this area is still in its early stages. In the present study, a picture-word semantic priming paradigm was employed to investigate the contribution effect of social experience that is provided by real-life pictures to social abstract concepts and emotional abstract concepts. Using (...) a lexical decision task, we examined responses to picture-SA word pairs and picture-EA word pairs in social/emotional semantically related and unrelated conditions. All pairs shared either positive or negative valence. The results showed quicker responses to positive SA and EA words that were preceded by related vs. unrelated prime pictures. Specifically, positive SA words were facilitated by the corresponding social scene pictures, whereas positive EA words were facilitated by pictures depict the corresponding facial expressions and gestures. However, such facilitatory effect was not observed in negative picture-SA/EA word conditions. This pattern of results suggests that a facilitatory effect of social experience on abstract concepts varies with different sub-kinds of abstract concepts, that seems to be limited to positive SA concepts. Overall, our findings confirm the crucial role of social experience for abstract concepts and further suggest that not all abstract concepts can benefit from social experience, at least in the semantic priming. (shrink)

Embodied approaches to cognition see abstract thought and language as grounded in interactions between mind, body, and world. A particularly important challenge for embodied approaches to cognition is mathematics, perhaps the most abstract domain of human knowledge. Conceptual metaphor theory, a branch of cognitive linguistics, describes how abstract mathematical concepts are grounded in concrete physical representations. In this paper, we consider the implications of this research for the metaphysics and epistemology of mathematics. In the case of metaphysics, we argue that (...) embodied mathematics is neutral in the sense of being compatible with all existing accounts of what mathematical entities really are. However, embodied mathematics may be able to revive an older position known as psychologism and overcome the difficulties it faces. In the case of epistemology, we argue that the evidence collected in the embodied mathematics literature is inconclusive: It does not show that abstract mathematical thinking is constituted by metaphor; it may simply show that abstract thinking is facilitated by metaphor. Our arguments suggest that closer interaction between the philosophy and cognitive science of mathematics could yield a more precise, empirically informed account of what mathematics is and how we come to have knowledge of it. (shrink)

How many words—and which ones—are sufficient to define all other words? When dictionaries are analyzed as directed graphs with links from defining words to defined words, they reveal a latent structure. Recursively removing all words that are reachable by definition but that do not define any further words reduces the dictionary to a Kernel of about 10% of its size. This is still not the smallest number of words that can define all the rest. About 75% of the Kernel turns (...) out to be its Core, a “Strongly Connected Subset” of words with a definitional path to and from any pair of its words and no word's definition depending on a word outside the set. But the Core cannot define all the rest of the dictionary. The 25% of the Kernel surrounding the Core consists of small strongly connected subsets of words: the Satellites. The size of the smallest set of words that can define all the rest—the graph's “minimum feedback vertex set” or MinSet—is about 1% of the dictionary, about 15% of the Kernel, and part-Core/part-Satellite. But every dictionary has a huge number of MinSets. The Core words are learned earlier, more frequent, and less concrete than the Satellites, which are in turn learned earlier, more frequent, but more concrete than the rest of the Dictionary. In principle, only one MinSet's words would need to be grounded through the sensorimotor capacity to recognize and categorize their referents. In a dual-code sensorimotor/symbolic model of the mental lexicon, the symbolic code could do all the rest through recombinatory definition. (shrink)

The Affective grounding hypothesis suggests that affective experiences play a crucial role in abstract concepts’ processing (Kousta et al. 2011). Vigliocco and colleagues test the role of affective experiences as well as the role of language in learning words denoting abstract concepts, comparing children with typical and atypical development. They conclude that besides the affective experiences also language plays a critical role in the processing of words referring to abstract concepts.

There is considerable evidence that language comprehenders derive lexical‐semantic meaning by mentally simulating perceptual and motor attributes of described events. However, the nature of these simulations—including the level of detail that is incorporated and contexts under which simulations occur—is not well understood. Here, we examine the effects of first‐ versus third‐person perspective on mental simulations during sentence comprehension. First‐person sentences describing physical transfer towards or away from the body (e.g., “You threw the microphone,” “You caught the microphone”) modulated response latencies (...) when responses were made along a front‐back axis, consistent with the action‐sentence compatibility effect (ACE). This effect was not observed for third‐person sentences (“He threw the microphone,” “He caught the microphone”). The ACE was observed when making responses along a left‐right axis for third‐person, but not first‐person sentences. Abstract sentences (e.g., “He heard the message”) did not show an ACE along either axis. These results show that perspective is a detail that is simulated during action sentence comprehension, and that motoric activations are flexible and affected by the pronominal perspective used in the sentence. (shrink)

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. (shrink)

Previous studies of the lexical psycholinguistic properties in second language production have assessed the degree of an LPP dimension of an L2 corpus by computing the mean ratings of unique content words in the corpus for that dimension, without considering the possibility that learners at different proficiency levels may perceive the degree of that dimension of the same words differently. This study extended a dynamic semantic similarity algorithm to estimate the degree of five different LPP dimensions of several sub-corpora of (...) the Education First-Cambridge Open Language Database representing L2 English learners at different proficiency levels. Our findings provide initial evidence for the validity of the algorithm for assessing the LPPs in L2 production and contribute useful insights into between-proficiency relationships and cross-proficiency differences in the LPPs in L2 production as well as the relationships among different LPP dimensions. (shrink)

Pupillary responses and associated vergence eye movements were monitored during imagery of objects of differing sizes (“large” or “small”) from varying distances (“near” or “far”). Objects’ imagined size and distance affected oculomotor behavior. Objects visualized as “far” resulted in the larger pupil dilations and smaller visual angle, while small objects imagined “near” were associated with smaller pupils in contrast to relatively larger pupils when imagined as “far” away. Furthermore, near objects resulted in larger visual angle, and particularly, vergence adjustments were (...) observed that were dependent on imagined size and distance of the small objects. The findings are consistent with the idea that imagery emulates perception, also at the embodied level of oculomotor behaviors. (shrink)

This study investigates how speed of motion is processed in language. In three eye-tracking experiments, participants were presented with visual scenes and spoken sentences describing fast or slow events (e.g., The lion ambled/dashed to the balloon). Results showed that looking time to relevant objects in the visual scene was affected by the speed of verb of the sentence, speaking rate, and configuration of a supporting visual scene. The results provide novel evidence for the mental simulation of speed in language and (...) show that internal dynamic simulations can be played out via eye movements toward a static visual scene. (shrink)

In this study, we examined the effects of emotional experience, a relatively new dimension of emotional knowledge that gauges the ease with which words evoke emotional experience, on abstract word processing in the Stroop task. In order to test the context-dependency of these effects, we accentuated the saliency of this dimension in Experiment 1A by blocking the stimuli such that one block consisted of the stimuli with the highest emotional experience ratings and the other block consisted of the stimuli with (...) the lowest emotional experience ratings. We attenuated the saliency of this dimension in Experiment 1B by intermixing the stimuli. We observed slower color naming performance for words with higher emotional experience ratings only in Experiment 1A, suggesting that the dimension of emotional experience is an aspect of semantic representation for abstract words but that its influence can be modulated by context. We interpret these results more generally using Vigliocco, Meteyard, Andrews, and Kousta's framework of semantic representation, and more specifically using Cohen, Dunbar, and McClelland's model of Stroop task performance. (shrink)

The hypothesis that word representations are emotionally impoverished in a second language (L2) has variable support. However, this hypothesis has only been tested using tasks that present words in isolation or that require laboratory-specific decisions. Here, we recorded eye movements for 34 bilinguals who read sentences in their L2 with no goal other than comprehension, and compared them to 43 first language readers taken from our prior study. Positive words were read more quickly than neutral words in the L2 across (...) first-pass reading time measures. However, this emotional advantage was absent for negative words for the earliest measures. Moreover, negative words but not positive words were influenced by concreteness, frequency and L2 proficiency in a manner similar to neutral words. Taken together, the findings suggest that only negative words are at risk of emotional disembodiment during L2 reading, perhaps because a positivity bias in L2 experiences ensures that positive words are emotionally grounded. (shrink)

People categorize objects slowly when visual input is highly impoverished instead of optimal. While bottom-up models may explain a decision with optimal input, perceptual hypothesis testing (PHT) theories implicate top-down processes with impoverished input. Brain mechanisms and the time course of PHT are largely unknown. This event-related potential study used a neuroimaging paradigm that implicated prefrontal cortex in top-down modulation of occipitotemporal cortex. Subjects categorized more impoverished and less impoverished real and pseudo objects. PHT theories predict larger impoverishment effects for (...) real than pseudo objects because top-down processes modulate knowledge only for real objects, but different PHT variants predict different timing. Consistent with parietal-prefrontal PHT variants, around 250 ms, the earliest impoverished real object interaction started on an N3 complex, which reflects interactive cortical activity for object cognition. N3 impoverishment effects localized to both prefrontal and occipitotemporal cortex for real objects only. The N3 also showed knowledge effects by 230 ms that localized to occipitotemporal cortex. Later effects reflected (a) word meaning in temporal cortex during the N400, (b) internal evaluation of prior decision and memory processes and secondary higher-order memory involving anterotemporal parts of a default mode network during posterior positivity (P600), and (c) response related activity in posterior cingulate during an anterior slow wave (SW) after 700 ms. Finally, response activity in supplementary motor area during a posterior SW after 900 ms showed impoverishment effects that correlated with RTs. Convergent evidence from studies of vision, memory, and mental imagery which reflects purely top-down inputs, indicates that the N3 reflects the critical top-down processes of PHT. A hybrid multiple-state interactive, PHT and decision theory best explains the visual constancy of object cognition. (shrink)

A number of recent models of semantics combine linguistic information, derived from text corpora, and visual information, derived from image collections, demonstrating that the resulting multimodal models are better than either of their unimodal counterparts, in accounting for behavioral data. Empirical work on semantic processing has shown that emotion also plays an important role especially in abstract concepts; however, models integrating emotion along with linguistic and visual information are lacking. Here, we first improve on visual and affective representations, derived from (...) state‐of‐the‐art existing models, by choosing models that best fit available human semantic data and extending the number of concepts they cover. Crucially then, we assess whether adding affective representations (obtained from a neural network model designed to predict emojis from co‐occurring text) improves the model's ability to fit semantic similarity/relatedness judgments from a purely linguistic and linguistic–visual model. We find that, given specific weights assigned to the models, adding both visual and affective representations improves performance, with visual representations providing an improvement especially for more concrete words, and affective representations improving especially the fit for more abstract words. (shrink)

Arbitrary symbolism is a linguistic doctrine that predicts an orthogonal relationship between word forms and their corresponding meanings. Recent corpora analyses have demonstrated violations of arbitrary symbolism with respect to concreteness, a variable characterizing the sensorimotor salience of a word. In addition to qualitative semantic differences, abstract and concrete words are also marked by distinct morphophonological structures such as length and morphological complexity. Native English speakers show sensitivity to these markers in tasks such as auditory word recognition and naming. One (...) unanswered question is whether this violation of arbitrariness reflects an idiosyncratic property of the English lexicon or whether word concreteness is a marked phenomenon across other natural languages. We isolated concrete and abstract English nouns, and translated each into Russian, Arabic, Dutch, Mandarin, Hindi, Korean, Hebrew, and American Sign Language. We conducted offline acoustic analyses of abstract and concrete word length discrepancies across languages. In a separate experiment, native English speakers with no prior knowledge of these foreign languages judged concreteness of these nouns. Each naïve participant heard pre-recorded words presented in randomized blocks of three foreign languages following a brief listening exposure to a narrative sample from each respective language. Concrete and abstract words differed by length across five of eight languages, and prediction accuracy exceeded chance for four of eight languages. These results suggest that word concreteness is a marked phenomenon across several of the world's most widely spoken languages. We interpret these findings as supportive of an adaptive cognitive heuristic that allows listeners to exploit non-arbitrary mappings of word form to word meaning. (shrink)

The Abstract Conceptual Feature (ACF) framework predicts that word meaning is represented within a high‐dimensional semantic space bounded by weighted contributions of perceptual, affective, and encyclopedic information. The ACF, like latent semantic analysis, is amenable to distance metrics between any two words. We applied predictions of the ACF framework to abstract words using eyetracking via an adaptation of the classical “visual word paradigm” (VWP). Healthy adults (n = 20) selected the lexical item most related to a probe word in a (...) 4‐item written word array comprising the target and three distractors. The relation between the probe and each of the four words was determined using the semantic distance metrics derived from ACF ratings. Eye movement data indicated that the word that was most semantically related to the probe received more and longer fixations relative to distractors. Importantly, in sets where participants did not provide an overt behavioral response, the fixation rates were nonetheless significantly higher for targets than distractors, closely resembling trials where an expected response was given. Furthermore, ACF ratings which are based on individual words predicted eye fixation metrics of probe‐target similarity at least as well as latent semantic analysis ratings which are based on word co‐occurrence. The results provide further validation of Euclidean distance metrics derived from ACF ratings as a measure of one facet of the semantic relatedness of abstract words and suggest that they represent a reasonable approximation of the organization of abstract conceptual space. The data are also compatible with the broad notion that multiple sources of information (not restricted to sensorimotor and emotion information) shape the organization of abstract concepts. While the adapted “VWP” is potentially a more metacognitive task than the classical visual world paradigm, we argue that it offers potential utility for studying abstract word comprehension. (shrink)

To explain how abstract concepts are grounded in sensory-motor experiences, several theories have been proposed. I will discuss two of these proposals, Conceptual Metaphor Theory and Situated Cognition, and argue why they do not fully explain grounding. A central idea in Conceptual Metaphor Theory is that image schemas ground abstract concepts in concrete experiences. Image schemas might themselves be abstractions, however, and therefore do not solve the grounding problem. Moreover, image schemas are too simple to explain the full richness of (...) abstract concepts. Situated cognition might provide such richness. Research in our laboratory, however, has shown that even for concrete concepts, sensory-motor grounding is task dependent. Therefore, it is questionable whether abstract concepts can be significantly grounded in sensory-motor processing. (shrink)

Name der Zeitschrift: Semiotica Jahrgang: 2017 Heft: 218 Seiten: 65-79.

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.