In recent years there has been an increasing awareness that a comprehensive understanding of language, cognitive and affective processes, and social and interpersonal phenomena cannot be achieved without understanding the ways these processes are grounded in bodily states. The term ‘embodiment’ captures the common denominator of these developments, which come from several disciplinary perspectives ranging from neuroscience, cognitive science, social psychology, and affective sciences. For the first time, this volume brings together these varied developments under one umbrella and furnishes a (...) comprehensive overview of this intellectual movement in the cognitive-behavioral sciences. (shrink)

INTRODUCTION: TWO KINDS OF RLDUCTIONISM The man who laughs is the one who has not yet heard the terrible news. BERTHOLD BRECHT I propose, in this book, ...

According to the Perceptual Symbols Theory of cognition (Barsalou, 1999), modality‐specific simulations underlie the representation of concepts. A strong prediction of this view is that perceptual processing affects conceptual processing. In this study, participants performed a perceptual detection task and a conceptual property‐verification task in alternation. Responses on the property‐verification task were slower for those trials that were preceded by a perceptual trial in a different modality than for those that were preceded by a perceptual trial in the same modality. (...) This finding of a modality‐switch effect across perceptual processing and conceptual processing supports the hypothesis that perceptual and conceptual representations are partially based on the same systems. (shrink)

Recent theories of cognition have argued that embodied experience is important for conceptual processing. Embodiment can be contrasted with linguistic factors such as the typical order in which words appear in language. Here, we report four experiments that investigated the conditions under which embodiment and linguistic factors determine performance. Participants made speeded judgments about whether pairs of words or pictures were semantically related or had an iconic relationship. The embodiment factor was operationalized as the degree to which stimulus pairs were (...) presented in the spatial configurations in which they usually occur (i.e., an iconic configuration, e.g., attic presented above basement). The linguistic factor was operationalized as the frequency of the stimulus pairs in language. The embodiment factor predicted error rates and response time better for pictures, whereas the linguistic factor predicted error rates and response time better for words. These findings were modified by task, with the embodiment factor being strongest in iconicity judgments for pictures and the linguistic factor being strongest in semantic judgments for words. Both factors predicted error rates and response time for both semantic and iconicity judgments. These findings support the view that conceptual processing is both linguistic and embodied, with a bias for the embodiment or the linguistic factor depending on the nature of the task and the stimuli. (shrink)

Whether computational algorithms such as latent semantic analysis (LSA) can both extract meaning from language and advance theories of human cognition has become a topic of debate in cognitive science, whereby accounts of symbolic cognition and embodied cognition are often contrasted. Albeit for different reasons, in both accounts the importance of statistical regularities in linguistic surface structure tends to be underestimated. The current article gives an overview of the symbolic and embodied cognition accounts and shows how meaning induction attributed to (...) a specific statistical process or to activation of embodied representations should be attributed to language itself. Specifically, the performance of LSA can be attributed to the linguistic surface structure, more than special characteristics of the algorithm, and embodiment findings attributed to perceptual simulations can be explained by distributional linguistic information. (shrink)

I address the commentators' calls for clarification of theoretical terms, discussion of similarities to other proposals, and extension of the ideas. In doing so, I keep the focus on the purpose of memory: enabling the organism to make sense of its environment so that it can take action appropriate to constraints resulting from the physical, personal, social, and cultural situations.

Theories of embodied cognition hold that the conceptual system uses perceptual simulations for the purposes of representation. A strong prediction is that perceptual phenomena should emerge in conceptual processing, and, in support, previous research has shown that switching modalities from one trial to the next incurs a processing cost during conceptual tasks. However, to date, such research has been limited by its reliance on the retrieval of familiar concepts. We therefore examined concept creation by asking participants to interpret modality-specific compound (...) phrases (i.e., conceptual combinations). Results show that modality switching costs emerge during the creation of new conceptual entities: People are slower to simulate a novel concept (e.g., auditory jingling onion) when their attention has already been engaged by a different modality in simulating a familiar concept (e.g., visual shiny penny). Furthermore, these costs cannot be accounted for by linguistic factors alone. Rather, our findings support the embodied view that concept creation, as well as retrieval, requires situated perceptual simulation. (shrink)

It is widely assumed that human learning and the structure of human languages are intimately related. This relationship is frequently suggested to derive from a language-specific biological endowment, which encodes universal, but communicatively arbitrary, principles of language structure (a Universal Grammar or UG). How might such a UG have evolved? We argue that UG could not have arisen either by biological adaptation or non-adaptationist genetic processes, resulting in a logical problem of language evolution. Specifically, as the processes of language change (...) are much more rapid than processes of genetic change, language constitutes a both over time and across different human populations, and, hence, cannot provide a stable environment to which language genes could have adapted. We conclude that a biologically determined UG is not evolutionarily viable. Instead, the original motivation for UG arises because language has been shaped to fit the human brain, rather than vice versa. Following Darwin, we view language itself as a complex and interdependent which evolves under selectional pressures from human learning and processing mechanisms. That is, languages themselves are shaped by severe selectional pressure from each generation of language users and learners. This suggests that apparently arbitrary aspects of linguistic structure may result from general learning and processing biases deriving from the structure of thought processes, perceptuo-motor factors, cognitive limitations, and pragmatics. (shrink)

Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statis- tics, and programming languages have inspired amodal theories that rest on principles fundamentally different from those underlying perception. In addition, perceptual approaches have become widely viewed as untenable because they are assumed to implement record- ing systems, not conceptual systems. A perceptual theory of knowledge is developed here in the context of current cognitive science and neuroscience. During perceptual experience, association areas in the (...) brain capture bottom-up patterns of activation in sensory-motor areas. Later, in a top-down manner, association areas partially reactivate sensory-motor areas to implement perceptual symbols. The stor- age and reactivation of perceptual symbols operates at the level of perceptual components – not at the level of holistic perceptual expe- riences. Through the use of selective attention, schematic representations of perceptual components are extracted from experience and stored in memory (e.g., individual memories of green, purr, hot). As memories of the same component become organized around a com- mon frame, they implement a simulator that produces limitless simulations of the component (e.g., simulations of purr). Not only do such simulators develop for aspects of sensory experience, they also develop for aspects of proprioception (e.g., lift, run) and introspec- tion (e.g., compare, memory, happy, hungry). Once established, these simulators implement a basic conceptual system that represents types, supports categorization, and produces categorical inferences. These simulators further support productivity, propositions, and ab- stract concepts, thereby implementing a fully functional conceptual system. Productivity results from integrating simulators combinato- rially and recursively to produce complex simulations. Propositions result from binding simulators to perceived individuals to represent type-token relations. Abstract concepts are grounded in complex simulations of combined physical and introspective events. Thus, a per- ceptual theory of knowledge can implement a fully functional conceptual system while avoiding problems associated with amodal sym- bol systems. Implications for cognition, neuroscience, evolution, development, and artificial intelligence are explored. (shrink)

This systematic investigation of computation and mental phenomena by a noted psychologist and computer scientist argues that cognition is a form of computation, that the semantic contents of mental states are encoded in the same general way as computer representations are encoded. It is a rich and sustained investigation of the assumptions underlying the directions cognitive science research is taking. 1 The Explanatory Vocabulary of Cognition 2 The Explanatory Role of Representations 3 The Relevance of Computation 4 The Psychological Reality (...) of Programs: Strong Equivalence 5 Constraining Functional Architecture 6 The Bridge from Physical to Symbolic: Transduction 7 Functional Architecture and Analogue Processes 8 Mental Imagery and Functional Architecture 9 Epilogue: What is Cognitive Science the Science of? (shrink)