Grounded Cognition Entails Linguistic Relativity: A Neglected Implication of a Major Semantic Theory

Invariant representations in abstract concept grounding - the physical world in grounded cognition

Grounded cognition states that mental representations of concepts consist of experiential aspects. For example, the concept "cup" consists of the sensorimotor experiences from interactions with cups. Typical modalities in which concepts are grounded are: The sensorimotor system (including interoception), emotion, action, language, and social aspects. Here, we argue that this list should be expanded to include physical invariants (unchanging features of physical motion; e.g., gravity, momentum, friction). Research on physical reasoning consistently demonstrates that physical invariants are represented as fundamentally as other grounding substrates, and therefore should qualify. We assess several theories of concept representation (simulation, conceptual metaphor, conceptual spaces, predictive processing) and their positions on physical invariants. We find that the classic grounded cognition theories, simulation and conceptual metaphor theory, have not considered physical invariants, while conceptual spaces and predictive processing have. We conclude that physical invariants should be included into grounded cognition theories, and that the core mechanisms of simulation and conceptual metaphor theory are well suited to do this. Furthermore, conceptual spaces and predictive processing are very promising and should also be integrated with grounded cognition in the future.

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.

Grounded Cognition, Linguistic Relativity, and Abstract Concepts

Kemmerer's paper convincingly claims that the grounded cognition model (GCM) entails linguistic relativity. Here, we underline that tackling linguistic relativity and cultural differences is vital for GCM. First, it allows GCM to focus more on flexible rather than stable aspects of cognition. Second, it highlights the centrality of linguistic experience for human cognition. While GCM-inspired research underscored the similarity between linguistic and nonlinguistic concepts, it is now paramount to understand when and how language(s) influence knowledge. To this aim, we argue that linguistic variation might be particularly relevant for more abstract concepts-which are more debatable and open to revisions.

Beyond Linguistic Relativity, Emotion Concepts Illustrate How Meaning is Contextually and Individually Variable

Kemmerer describes grounded accounts of cognition and, using crosslinguistic diversity across conceptual domains, argues that these accounts entail linguistic relativity. In this comment, I extend Kemmerer's position to the domain of emotion. Emotion concepts exemplify characteristics highlighted by grounded accounts of cognition and differ by culture and language. Recent research further demonstrates considerable situation- and person-specific differences. Based on this evidence, I argue that emotion concepts carry unique implications for variation in meaning and experience, entailing a relativity that is contextual and individual in addition to linguistic. I conclude by considering what such pervasive relativity means for interpersonal understanding.

The Iconicity Ring Hypothesis Bridges the Gap Between Symbol Grounding and Linguistic Relativity

Kemmerer captured the drastic change in theories of word meaning representations, contrasting the view that word meaning representations are amodal and universal, with the view that they are grounded and language-specific. However, he does not address how language can be simultaneously grounded and language-specific. Here, we approach this question from the perspective of language acquisition and evolution. We argue that adding a new element-iconicity-is critically beneficial and offer the iconicity ring hypothesis, which explains how language-specific, secondary iconicity might emerge from biologically grounded and universally shared iconicity in the course of language acquisition and evolution.

Language is a Source of Grounding and a Mode of Action

Kemmerer argues that grounded cognition explains how language-specific semantic structures can influence nonlinguistic cognition. In this commentary, I argue that his proposal fails to fully consider the possibility that language itself can serve as a source of grounding. Our concepts are not merely shaped by a disembodied language system; they emerge in the context of linguistic experience and action. This inclusive approach to grounded cognition offers an expanded conception of the phenomena associated with linguistic relativity. I provide empirical and theoretical reasons to adopt this theoretical perspective.

Over-reliance on English hinders cognitive science

English is the dominant language in the study of human cognition and behavior: the individuals studied by cognitive scientists, as well as most of the scientists themselves, are frequently English speakers. However, English differs from other languages in ways that have consequences for the whole of the cognitive sciences, reaching far beyond the study of language itself. Here, we review an emerging body of evidence that highlights how the particular characteristics of English and the linguistic habits of English speakers bias the field by both warping research programs (e.g., overemphasizing features and mechanisms present in English over others) and overgeneralizing observations from English speakers' behaviors, brains, and cognition to our entire species. We propose mitigating strategies that could help avoid some of these pitfalls.