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)

This article examined the effects of body–object interaction (BOI) on semantic processing. BOI measures perceptions of the ease with which a human body can physically interact with a word's referent. In Experiment 1, BOI effects were examined in 2 semantic categorization tasks (SCT) in which participants decided if words are easily imageable. Responses were faster and more accurate for high BOI words (e.g., mask) than for low BOI words (e.g., ship). In Experiment 2, BOI effects were examined in a semantic (...) lexical decision task (SLDT), which taps both semantic feedback and semantic processing. The BOI effect was larger in the SLDT than in the SCT, suggesting that BOI facilitates both semantic feedback and semantic processing. The findings are consistent with the embodied cognition perspective (e.g., Barsalou's, 1999, Perceptual Symbols Theory), which proposes that sensorimotor interactions with the environment are incorporated in semantic knowledge. (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)

Abstract Since their inception, distributional models of semantics have been criticized as inadequate cognitive theories of human semantic learning and representation. A principal challenge is that the representations derived by distributional models are purely symbolic and are not grounded in perception and action; this challenge has led many to favor feature-based models of semantic representation. We argue that the amount of perceptual and other semantic information that can be learned from purely distributional statistics has been underappreciated. We compare the representations (...) of three feature-based and nine distributional models using a semantic clustering task. Several distributional models demonstrated semantic clustering comparable with clustering-based on feature-based representations. Furthermore, when trained on child-directed speech, the same distributional models perform as well as sensorimotor-based feature representations of children’s lexical semantic knowledge. These results suggest that, to a large extent, information relevant for extracting semantic categories is redundantly coded in perceptual and linguistic experience. Detailed analyses of the semantic clusters of the feature-based and distributional models also reveal that the models make use of complementary cues to semantic organization from the two data streams. Rather than conceptualizing feature-based and distributional models as competing theories, we argue that future focus should be on understanding the cognitive mechanisms humans use to integrate the two sources. (shrink)

In Furnishing the Mind, Jesse Prinz attempts to swing the pendulum back toward empiricism.

What are the vehicles of conceptual thought? Recently, cognitive scientists and philosophers of psychology have developed quite different theories about what kinds of representations concepts are. At one extreme, amodal theories claim that concepts are representations whose vehicles are distinct from those used in perceptual processes. At the other end of the spectrum, neo-empiricism proposes that concepts are perceptual representations grounded in the mind's sensory, motor, and affective systems. In this essay, I examine how evidence from the neuropsychological disorder semantic (...) dementia bears on philosophical debates about the nature of conceptual vehicles. I argue that the pattern of deficits in semantic dementia undermines recent neo-empiricist predictions about where and how conceptual knowledge is organized in the brain. I do not intend my analysis of semantic dementia to wholly discredit neo-empiricism; instead, I draw lessons for future theorizing about conceptual vehicles. (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)

The now-classic Metaphors We Live By changed our understanding of metaphor and its role in language and the mind. Metaphor, the authors explain, is a fundamental mechanism of mind, one that allows us to use what we know about our physical and social experience to provide understanding of countless other subjects. Because such metaphors structure our most basic understandings of our experience, they are "metaphors we live by"--metaphors that can shape our perceptions and actions without our ever noticing them. In (...) this updated edition of Lakoff and Johnson's influential book, the authors supply an afterword surveying how their theory of metaphor has developed within the cognitive sciences to become central to the contemporary understanding of how we think and how we express our thoughts in language. (shrink)

Imitation, deliberation, and mindreading are characteristically human sociocognitive skills. Research on imitation and its role in social cognition is flourishing across various disciplines. Imitation is surveyed in this target article under headings of behavior, subpersonal mechanisms, and functions of imitation. A model is then advanced within which many of the developments surveyed can be located and explained. The shared circuits model (SCM) explains how imitation, deliberation, and mindreading can be enabled by subpersonal mechanisms of control, mirroring, and simulation. It is (...) cast at a middle, functional level of description, that is, between the level of neural implementation and the level of conscious perceptions and intentional actions. The SCM connects shared informational dynamics for perception and action with shared informational dynamics for self and other, while also showing how the action/perception, self/other, and actual/possible distinctions can be overlaid on these shared informational dynamics. It avoids the common conception of perception and action as separate and peripheral to central cognition. Rather, it contributes to the situated cognition movement by showing how mechanisms for perceiving action can be built on those for active perception.;>;>The SCM is developed heuristically, in five layers that can be combined in various ways to frame specific ontogenetic or phylogenetic hypotheses. The starting point is dynamic online motor control, whereby an organism is closely attuned to its embedding environment through sensorimotor feedback. Onto this are layered functions of prediction and simulation of feedback, mirroring, simulation of mirroring, monitored inhibition of motor output, and monitored simulation of input. Finally, monitored simulation of input specifying possible actions plus inhibited mirroring of such possible actions can generate information about the possible as opposed to actual instrumental actions of others, and the possible causes and effects of such possible actions, thereby enabling strategic social deliberation. Multiple instances of such shared circuits structures could be linked into a network permitting decomposition and recombination of elements, enabling flexible control, imitative learning, understanding of other agents, and instrumental and strategic deliberation. While more advanced forms of social cognition, which require tracking multiple others and their multiple possible actions, may depend on interpretative theorizing or language, the SCM shows how layered mechanisms of control, mirroring, and simulation can enable distinctively human cognitive capacities for imitation, deliberation, and mindreading. (shrink)

Recently, there has been a great deal of interest in the idea that natural language enhances and extends our cognitive capabilities. Supporters of embodied cognition have been particularly interested in the way in which language may provide a solution to the problem of abstract concepts. Toward this end, some have emphasized the way in which language may act as form of cognitive scaffolding and others have emphasized the potential importance of language-based distributional information. This essay defends a version of the (...) cognitive enhancement thesis that integrates and builds on both of these proposals. I argue that the embodied representations associated with language processing serve as a supplementary medium for conceptual processing. The acquisition of a natural language provides a means of extending our cognitive reach by giving us access to an internalized combinatorial symbol system that augments and supports the context-sensitive embodied representational systems that exist independently of language. (shrink)

Recent evidence from cognitive neuroscience suggests that certain cognitive processes employ perceptual representations. Inspired by this evidence, a few researchers have proposed that cognition is inherently perceptual. They have developed an innovative theoretical approach that rests on the notion of perceptual simulation and marshaled several general arguments supporting the centrality of perceptual representations to concepts. In this article, I identify a number of weaknesses in these arguments and defend a multiple semantic code approach that posits both perceptual and non-perceptual representations.

As embodied theories of cognition are increasingly formalized and tested, care must be taken to make informed assumptions regarding the nature of concepts and representations. In this study, we outline three reasons why one cannot, in effect, represent the same concept twice. First, online perception affects offline representation: Current representational content depends on how ongoing demands direct attention to modality-specific systems. Second, language is a fundamental facilitator of offline representation: Bootstrapping and shortcuts within the computationally cheaper linguistic system continuously modify (...) representational content. Third, time itself is a source of representational change: As the content of underlying concepts shifts with the accumulation of direct and vicarious experience, so too does the content of representations that draw upon these concepts. We discuss the ramifications of these principles for research into both human and synthetic cognitive systems. (shrink)

There is mounting evidence that language comprehension involves the activation of mental imagery of the content of utterances (Barsalou, 1999;Bergen, Chang, & Narayan, 2004;Bergen, Narayan, & Feldman, 2003;Narayan, Bergen, & Weinberg, 2004;Richardson, Spivey, McRae, & Barsalou, 2003;Stanfield & Zwaan, 2001;Zwaan, Stanfield, & Yaxley, 2002). This imagery can have motor or perceptual content. Three main questions about the process remain under‐explored, however. First, are lexical associations with perception or motion sufficient to yield mental simulation, or is the integration of lexical semantics (...) into larger structures, like sentences, necessary? Second, what linguistic elements (e.g., verbs, nouns, etc.) trigger mental simulations? Third, how detailed are the visual simulations that are performed? A series of behavioral experiments address these questions, using a visual object categorization task to investigate whether up‐ or down‐related language selectively interferes with visual processing in the same part of the visual field (followingRichardson et al., 2003). The results demonstrate that either subject nouns or main verbs can trigger visual imagery, but only when used in literal sentences about real space—metaphorical language does not yield significant effects—which implies that it is the comprehension of the sentence as a whole and not simply lexical associations that yields imagery effects. These studies also show that the evoked imagery contains detail as to the part of the visual field where the described scene would take place. (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)

Thirty years ago, grounded cognition had roots in philosophy, perception, cognitive linguistics, psycholinguistics, cognitive psychology, and cognitive neuropsychology. During the next 20 years, grounded cognition continued developing in these areas, and it also took new forms in robotics, cognitive ecology, cognitive neuroscience, and developmental psychology. In the past 10 years, research on grounded cognition has grown rapidly, especially in cognitive neuroscience, social neuroscience, cognitive psychology, social psychology, and developmental psychology. Currently, grounded cognition appears to be achieving increased acceptance throughout cognitive (...) science, shifting from relatively minor status to increasing importance. Nevertheless, researchers wonder whether grounded mechanisms lie at the heart of the cognitive system or are peripheral to classic symbolic mechanisms. Although grounded cognition is currently dominated by demonstration experiments in the absence of well-developed theories, the area is likely to become increasingly theory driven over the next 30 years. Another likely development is the increased incorporation of grounding mechanisms into cognitive architectures and into accounts of classic cognitive phenomena. As this incorporation occurs, much functionality of these architectures and phenomena is likely to remain, along with many original mechanisms. Future theories of grounded cognition are likely to be heavily influenced by both cognitive neuroscience and social neuroscience, and also by developmental science and robotics. Aspects from the three major perspectives in cognitive science—classic symbolic architectures, statistical/dynamical systems, and grounded cognition—will probably be integrated increasingly in future theories, each capturing indispensable aspects of intelligence. (shrink)

Over the past 15 years, there have been two increasingly popular approaches to the study of meaning in cognitive science. One, based on theories of embodied cognition, treats meaning as a simulation of perceptual and motor states. An alternative approach treats meaning as a consequence of the statistical distribution of words across spoken and written language. On the surface, these appear to be opposing scientific paradigms. In this review, we aim to show how recent cross-disciplinary developments have done much to (...) reconcile these two approaches. The foundation to these developments has been the recognition that intralinguistic distributional and sensory-motor data are interdependent. We describe recent work in philosophy, psychology, cognitive neuroscience, and computational modeling that are all based on or consistent with this conclusion. We conclude by considering some possible directions for future research that arise as a consequence of these developments. (shrink)

This book explores how people's subjective, felt experiences of their bodies in action provide part of the fundamental grounding for human cognition and language. Cognition is what occurs when the body engages the physical and cultural world and must be studied in terms of the dynamical interactions between people and the environment. Human language and thought emerge from recurring patterns of embodied activity that constrain ongoing intelligent behavior. We must not assume cognition to be purely internal, symbolic, computational, and disembodied, (...) but seek out the gross and detailed ways that language and thought are inextricably shaped by embodied action. Embodiment and Cognitive Science describes the abundance of empirical evidence from many disciplines, including work on perception, concepts, imagery and reasoning, language and communication, cognitive development, and emotions and consciousness, that support the idea that the mind is embodied. (shrink)

In Supersizing the Mind, Andy Clark argues that the human mind is not bound inside the head but extends into body and environment.

There has been much discussion recently about the scope and limits of purely symbolic models of the mind and about the proper role of connectionism in cognitive modeling. This paper describes the symbol grounding problem : How can the semantic interpretation of a formal symbol system be made intrinsic to the system, rather than just parasitic on the meanings in our heads? How can the meanings of the meaningless symbol tokens, manipulated solely on the basis of their shapes, be grounded (...) in anything but other meaningless symbols? The problem is analogous to trying to learn Chinese from a Chinese/Chinese dictionary alone. A candidate solution is sketched: Symbolic representations must be grounded bottom-up in nonsymbolic representations of two kinds: iconic representations, which are analogs of the proximal sensory projections of distal objects and events, and categorical representations, which are learned and innate feature-detectors that pick out the invariant features of object and event categories from their sensory projections. Elementary symbols are the names of these object and event categories, assigned on the basis of their categorical representations. Higher-order symbolic representations, grounded in these elementary symbols, consist of symbol strings describing category membership relations. Connectionism is one natural candidate for the mechanism that learns the invariant features underlying categorical representations, thereby connecting names to the proximal projections of the distal objects they stand for. In this way connectionism can be seen as a complementary component in a hybrid nonsymbolic/symbolic model of the mind, rather than a rival to purely symbolic modeling. Such a hybrid model would not have an autonomous symbolic module, however; the symbolic functions would emerge as an intrinsically dedicated symbol system as a consequence of the bottom-up grounding of categories ' names in their sensory representations. Symbol manipulation would be governed not just by the arbitrary shapes of the symbol tokens, but by the nonarbitrary shapes of the icons and category invariants in which they are grounded. (shrink)

Concept empiricists are committed to the claim that the vehicles of thought are re-activated perceptual representations. Evidence for empiricism comes from a range of neuroscientific studies showing that perceptual regions of the brain are employed during cognitive tasks such as categorization and inference. I examine the extant neuroscientific evidence and argue that it falls short of establishing this core empiricist claim. During conceptual tasks, the causal structure of the brain produces widespread activity in both perceptual and non-perceptual systems. I lay (...) out several conditions on what is required for a neural state to be a realizer of the functional role played by concepts, and argue that no subset of this activity can be singled out as the unique neural vehicle of conceptual thought. Finally, I suggest that, while the strongest form of empiricism is probably false, the evidence is consistent with several weaker forms of empiricism. (shrink)