Idiosyncratic Tower of Babel: Individual Differences in Word-Meaning Representation Increase as Word Abstractness Increases

Abstractness impacts conversational dynamics

Conversation topics may vary in abstractness. This might impact the effort required by speakers to reach a common ground and, ultimately, an interactive alignment. In fact, people typically feel less confident with abstract concepts and single-words rating studies suggest abstract concepts are more associated with social interactions than concrete concepts-hence suggesting increasing levels of abstractness enhance inner and mutual monitoring processes. However, experimental studies addressing conversational dynamics afforded by abstract concepts are still sparse. In three preregistered experiments we ask whether abstract sentences are associated with specific constructs in dialogue, i.e., higher uncertainty, more curiosity and willingness to continue a conversation, and more questions related to causal and agency aspects. We do so by asking participants to evaluate the plausibility of linguistic exchanges referring to concrete and abstract concepts. Results support theories proposing that abstract concepts involve more inner monitoring and social dynamics compared to concrete concepts and suggest that reaching alignment in dialogue is more effortful with abstract than with concrete concepts.

Alexithymia shapes intersubject synchrony in brain activity during interoceptive sensation representations

Alexithymia is a subclinical condition that affects individuals' processing of emotions. Emerging evidence suggests that alexithymia results from a multidomain and multidimensional interoceptive failure. Although extensive research has examined the relationship between alexithymia and interoception, less is known about how alexithymia modulates the brain activity evoked by interoceptive sensations. In this study, we used task-based functional magnetic resonance imaging (fMRI) to assess intersubject correlations in response to interoceptive sensation words in individuals with high alexithymia and low alexithymia. Participants with high alexithymia (n = 29) and low alexithymia (n = 28) were instructed to view words during MRI scanning, each word corresponding to a specific emotional category related to interoceptive sensations. Intersubject correlation analysis identified several brain regions exhibiting increased synchronization in individuals with high alexithymia, including those involved in cognitive control. Follow-up analyses revealed that the left middle occipital gyrus and the right inferior frontal gyrus (orbital part) were more active during interoceptive sensation events in individuals with high alexithymia. Validation analyses revealed that the amygdala and insula are also crucial in representing interoceptive sensations. These findings shed light on the neural basis of interoceptive deficits in high alexithymia and have significant implications for the mechanisms regulating these differences.

Distributional Semantics: Meaning Through Culture and Interaction

Mastering how to convey meanings using language is perhaps the main challenge facing any language learner. However, satisfactory accounts of how this is achieved, and even of what it is for a linguistic item to have meaning, are hard to come by. Nick Chater was one of the pioneers involved in the early development of one of the most successful methodologies within the cognitive science of language for discovering meaning: distributional semantics. In this article, we review this approach and discuss its successes and shortcomings in capturing semantic phenomena. In particular, we discuss what we dub the "distributional paradox:" how can models that do not implement essential dimensions of human semantic processing, such as sensorimotor grounding, capture so many meaning-related phenomena? We conclude by providing a preliminary answer, arguing that distributional models capture the statistical scaffolding of human language acquisition that allows for communication, which, in line with Nick Chater's more recent ideas, has been shaped by the features of human cognition on the timescale of cultural evolution.

Neural Representations of Concreteness and Concrete Concepts Are Specific to the Individual

Different people listening to the same story may converge upon a largely shared interpretation while still developing idiosyncratic experiences atop that shared foundation. What linguistic properties support this individualized experience of natural language? Here, we investigate how the "concrete-abstract" axis-the extent to which a word is grounded in sensory experience-relates to within- and across-subject variability in the neural representations of language. Leveraging a dataset of human participants of both sexes who each listened to four auditory stories while undergoing functional magnetic resonance imaging, we demonstrate that neural representations of "concreteness" are both reliable across stories and relatively unique to individuals, while neural representations of "abstractness" are variable both within individuals and across the population. Using natural language processing tools, we show that concrete words exhibit similar neural representations despite spanning larger distances within a high-dimensional semantic space, which potentially reflects an underlying representational signature of sensory experience-namely, imageability-shared by concrete words but absent from abstract words. Our findings situate the concrete-abstract axis as a core dimension that supports both shared and individualized representations of natural language.

Becoming word meaning experts: Infants' processing of familiar words in the context of typical and atypical exemplars

How do infants become word meaning experts? This registered report investigated the structure of infants' early lexical representations by manipulating the typicality of exemplars from familiar animal categories. 14- to 18-month-old infants (N = 84; 51 female; M = 15.7 months; race/ethnicity: 64% White, 8% Asian, 2% Hispanic, 1% Black, and 23% multiple categories; participating 2022-2023) were tested on their ability to recognize typical and atypical category exemplars after hearing familiar basic-level category labels. Infants robustly recognized both typical (d = 0.79, 95% CI [0.54, 1.03]) and atypical (d = 0.70, 95% CI [0.46, 0.94]) exemplars, with no significant difference between typicality conditions (d = 0.14, 95% CI [-0.08, 0.35]). These results support a broad-to-narrow account of infants' early word meanings. Implications for the role of experience in the development of lexical knowledge are discussed.

Flexibility in conceptual combinations: A neural network model of gradable adjective modification

Our ability to combine simple constituents into more complex conceptual combinations is a fundamental aspect of cognition. Gradable adjectives (e.g., 'tall' and 'light') are a critical example of this process, as their meanings vary depending on the noun with which they are combined. For example, a dark diamond is less dark than dark charcoal. Here, we investigate how a neural network encodes the flexible nature of gradable adjectives in adjective-noun pairs, using the perceptual feature of brightness as a test case. We trained a neural network to predict human brightness ratings for unmodified nouns and adjective-noun pairs and assessed its ability to generalize to untrained combinations (e.g., 'light paint' vs. 'dark paint'). We also explored how this information is encoded. We found that flexible learning of gradable adjectives was possible, with neural networks first making predictions based on the adjective alone, and then modulating these with information from the noun later in learning. We also found that model outputs mimicked the kind of non-additive feature modulation present in human data. Our results have implications for understanding how semantic composition occurs and generate testable predictions for future work.

Driving and suppressing the human language network using large language models

Transformer models such as GPT generate human-like language and are predictive of human brain responses to language. Here, using functional-MRI-measured brain responses to 1,000 diverse sentences, we first show that a GPT-based encoding model can predict the magnitude of the brain response associated with each sentence. We then use the model to identify new sentences that are predicted to drive or suppress responses in the human language network. We show that these model-selected novel sentences indeed strongly drive and suppress the activity of human language areas in new individuals. A systematic analysis of the model-selected sentences reveals that surprisal and well-formedness of linguistic input are key determinants of response strength in the language network. These results establish the ability of neural network models to not only mimic human language but also non-invasively control neural activity in higher-level cortical areas, such as the language network.

Determining the Relativity of Word Meanings Through the Construction of Individualized Models of Semantic Memory

Distributional models of lexical semantics are capable of acquiring sophisticated representations of word meanings. The main theoretical insight provided by these models is that they demonstrate the systematic connection between the knowledge that people acquire and the experience that they have with the natural language environment. However, linguistic experience is inherently variable and differs radically across people due to demographic and cultural variables. Recently, distributional models have been used to examine how word meanings vary across languages and it was found that there is considerable variability in the meanings of words across languages for most semantic categories. The goal of this article is to examine how variable word meanings are across individual language users within a single language. This was accomplished by assembling 500 individual user corpora attained from the online forum Reddit. Each user corpus ranged between 3.8 and 32.3 million words each, and a count-based distributional framework was used to extract word meanings for each user. These representations were then used to estimate the semantic alignment of word meanings across individual language users. It was found that there are significant levels of relativity in word meanings across individuals, and these differences are partially explained by other psycholinguistic factors, such as concreteness, semantic diversity, and social aspects of language usage. These results point to word meanings being fundamentally relative and contextually fluid, with this relativeness being related to the individualized nature of linguistic experience.

Consensus Paper: Current Perspectives on Abstract Concepts and Future Research Directions

concepts are relevant to a wide range of disciplines, including cognitive science, linguistics, psychology, cognitive, social, and affective neuroscience, and philosophy. This consensus paper synthesizes the work and views of researchers in the field, discussing current perspectives on theoretical and methodological issues, and recommendations for future research. In this paper, we urge researchers to go beyond the traditional abstract-concrete dichotomy and consider the multiple dimensions that characterize concepts (e.g., sensorimotor experience, social interaction, conceptual metaphor), as well as the mediating influence of linguistic and cultural context on conceptual representations. We also promote the use of interactive methods to investigate both the comprehension and production of abstract concepts, while also focusing on individual differences in conceptual representations. Overall, we argue that abstract concepts should be studied in a more nuanced way that takes into account their complexity and diversity, which should permit us a fuller, more holistic understanding of abstract cognition.

Abstract concepts: external influences, internal constraints, and methodological issues

There is a longstanding and widely held misconception about the relative remoteness of abstract concepts from concrete experiences. This review examines the current evidence for external influences and internal constraints on the processing, representation, and use of abstract concepts, like truth, friendship, and number. We highlight the theoretical benefit of distinguishing between grounded and embodied cognition and then ask which roles do perception, action, language, and social interaction play in acquiring, representing and using abstract concepts. By reviewing several studies, we show that they are, against the accepted definition, not detached from perception and action. Focussing on magnitude-related concepts, we also discuss evidence for cultural influences on abstract knowledge and explore how internal processes such as inner speech, metacognition, and inner bodily signals (interoception) influence the acquisition and retrieval of abstract knowledge. Finally, we discuss some methodological developments. Specifically, we focus on the importance of studies that investigate the time course of conceptual processing and we argue that, because of the paramount role of sociality for abstract concepts, new methods are necessary to study concepts in interactive situations. We conclude that bodily, linguistic, and social constraints provide important theoretical limitations for our theories of conceptual knowledge.

The map trap: Why and how word learning research should move beyond mapping

A pervasive goal in the study of how children learn word meanings is to explain how young children solve the mapping problem. The mapping problem asks how language learners connect a label to its referent. Mapping is one part of word learning, however, it does not reflect other critical components of word meaning construction, such as the encoding of lexico-semantic relations and socio-pragmatic context. In this paper, we argue that word learning researchers' overemphasis of mapping has constrained our experimental paradigms and hypotheses, leading to misconceived theories and policy interventions. We first explain how the mapping focus limits our ability to study the richness and complexity of what infants and children learn about, and do with, word meanings. Then, we describe how our focus on mapping has constrained theory development. Specifically, we show how it has led to (a) the misguided emphasis on referent selection and ostensive labeling, and (b) the undervaluing of diverse pathways to word knowledge, both within and across cultures. We also review the consequences of the mapping focus outside of the lab, including myopic language learning interventions. Last, we outline an alternative, more inclusive approach to experimental study and theory construction in word learning research. This article is categorized under: Psychology > Language Psychology > Theory and Methods Psychology > Learning.

Concepts for Which We Need Others More: The Case of Abstract Concepts

The capability to form and use concepts is a core component of human cognition. Although all concepts are grounded in sensorimotor processes, more abstract concepts (e.g., “truth”) collect more heterogeneous and perceptually dissimilar exemplars; thus, linguistic interaction and social interaction are particularly crucial for their acquisition and use. Because of their indeterminacy, abstract concepts generate more uncertainty than more concrete concepts; hence, they induce people to monitor their inner knowledge longer and then to consult others to ask for information and negotiate the concept’s meaning. I propose that people need others more for abstract concepts than for concrete concepts: Other people are essential to acquire, process, and use abstract concepts. Conceiving abstract concepts in these terms requires the employment of novel, interactive methods to investigate how people represent them during their use.