Lawrence W. Barsalou

Perceptual symbol systems

Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statistics, 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 recording 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 storage and reactivation of perceptual symbols operates at the level of perceptual components--not at the level of holistic perceptual experiences. 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 common 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 introspection (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 abstract concepts, thereby implementing a fully functional conceptual system. Productivity results from integrating simulators combinatorially 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 perceptual theory of knowledge can implement a fully functional conceptual system while avoiding problems associated with amodal symbol systems. Implications for cognition, neuroscience, evolution, development, and artificial intelligence are explored.

Ad hoc categories

People construct ad hoc categories to achieve goals. For example, constructing the category of “things to sell at a garage sale” can be instrumental to achieving the goal of selling unwanted possessions. These categories differ from common categories (e.g., “fruit,” “furniture”) in that ad hoc categories violate the correlational structure of the environment and are not well established in memory. Regarding the latter property, the category concepts, concept-to-instance associations, and instance-to-concept associations structuring ad hoc categories are shown to be much less established in memory than those of common categories. Regardless of these differences, however, ad hoc categories possess graded structures (i.e., typicality gradients) as salient as those structuring common categories. This appears to be the result of a similarity comparison process that imposes graded structure on any category regardless of type.

Embodiment in Attitudes, Social Perception, and Emotion

Findings in the social psychology literatures on attitudes, social perception, and emotion demonstrate that social information processing involves embodiment, where embodiment refers both to actual bodily states and to simulations of experience in the brains modality-specific systems for perception, action, and introspection. We show that embodiment underlies social information processing when the perceiver interacts with actual social objects (online cognition) and when the perceiver represents social objects in their absence (offline cognition). Although many empirical demonstrations of social embodiment exist, no particularly compelling account of them has been offered. We propose that theories of embodied cognition, such as the Perceptual Symbol Systems (PSS) account (Barsalou, 1999), explain and integrate these findings, and that they also suggest exciting new directions for research. We compare the PSS account to a variety of related proposals and show how it addresses criticisms that have previously posed problems for the general embodiment approach.

Ideals, Central Tendency, and Frequency of Instantiation as Determinants of Graded Structure in Categories

Three possible determinants of graded structure (typicality) were observed in common taxonomic categories and goal-derived categories: (1) an exemplars similarity to ideals associated with goals its category serves; (2) an exemplars similarity to the central tendency of its category (family resemblance); and (3) an exemplars frequency of instantiation (peoples subjective estimates of how often it is encountered as a category member). Experiment 1 found that central tendency did not predict graded structure in goal-derived categories, although it did predict graded structure in common taxonomic categories. Ideals and frequency of instantiation predicted graded structure in both category types to sizeable and equal extents. A fourth possible determinant--familiarity--did not predict typicality in either common taxonomic or goal-derived categories. Experiment 2 demonstrated that both central tendency and ideals causally determine graded structure, and work showing that frequency causally determines graded structure is discussed. Experiment 2 also demonstrated that the determinants of a particular categorys graded structure can change with context. Whereas ideals may determine a categorys graded structure in one context, central tendency may determine a different graded structure in another. It is proposed that graded structures do not reflect invariant structures associated with categories but instead reflect peoples dynamic ability to construct concepts.

Grounding conceptual knowledge in modality-specific systems.

The human conceptual system contains knowledge that supports all cognitive activities, including perception, memory, language and thought. According to most current theories, states in modality-specific systems for perception, action and emotion do not represent knowledge - rather, redescriptions of these states in amodal representational languages do. Increasingly, however, researchers report that re-enactments of states in modality-specific systems underlie conceptual processing. In behavioral experiments, perceptual and motor variables consistently produce effects in conceptual tasks. In brain imaging experiments, conceptual processing consistently activates modality-specific brain areas. Theoretical research shows how modality-specific re-enactments could produce basic conceptual functions, such as the type-token distinction, categorical inference, productivity, propositions and abstract concepts. Together these empirical results and theoretical analyses implicate modality-specific systems in the representation and use of conceptual knowledge.

Context-independent and context-dependent information in concepts

It is proposed that concepts contain two types of properties. Context-independent properties are activated by the word for a concept on all occasions. The activation of these properties is unaffected by contextual relevance. Context-dependent properties are not activated by the respective word independent of context. Rather, these properties are activated only by relevant contexts in which the word appears. Context-independent properties form the core meanings of words, whereas context-dependent properties are a source of semantic encoding variability. This proposal lies between two opposing theories of meaning, one that argues all properties of a concept are active on all occasions and another that argues the active properties are completely determined by context. The existence of context-independent and context-dependent properties is demonstrated in two experimental settings: the property-verification task and judgments of similarity. The relevance of these property types to cross-classification, problem solving, metaphor and sentence comprehension, and the semantic-episodic distinction is discussed.

Situated Simulation in the Human Conceptual System.

Four theories of the human conceptual system—semantic memory, exemplar models, feed‐forward connectionist nets, and situated simulation theory—are characterised and contrasted on five dimensions: (1) architecture (modular vs. non‐modular), (2) representation (amodal vs. modal), (3) abstraction (decontextualised vs. situated), (4) stability (stable vs. dynamical), and (5) organisation (taxonomic vs. action–environment interface). Empirical evidence is then reviewed for the situated simulation theory, and the following conclusions are reached. Because the conceptual system shares mechanisms with perception and action, it is non-modular. As a result, conceptual representations are multi-modal simulations distributed across modality‐specific systems. A given simulation for a concept is situated, preparing an agent for situated action with a particular instance, in a particular setting. Because a concept delivers diverse simulations that prepare agents for action in many different situations, it is dynamical. Because the conceptual system’s primary purpose is to support situated action, it becomes organised around the action–environment interface.

Simulation, situated conceptualization, and prediction

Based on accumulating evidence, simulation appears to be a basic computational mechanism in the brain that supports a broad spectrum of processes from perception to social cognition. Further evidence suggests that simulation is typically situated, with the situated character of experience in the environment being reflected in the situated character of the representations that underlie simulation. A basic architecture is sketched of how the brain implements situated simulation. Within this framework, simulators implement the concepts that underlie knowledge, and situated conceptualizations capture patterns of multi-modal simulation associated with frequently experienced situations. A pattern completion inference mechanism uses current perception to activate situated conceptualizations that produce predictions via simulations on relevant modalities. Empirical findings from perception, action, working memory, conceptual processing, language and social cognition illustrate how this framework produces the extensive prediction that characterizes natural intelligence.

Deriving categories to achieve goals

Publisher Summary This chapter discusses that categorization focuses on the issue of access. Prototype models, exemplar models, and connectionist models are all attempts to address this issue. Certainly, the issue of access is important and challenging, and solving it has significant implications for both theoretical and applied research. Models of categorization seem to view categorization as an end in itself. The purpose of categorization is not to know an entitys category. Instead, the purpose of categorization is to identify information in memory that provides useful inferences. Upon accessing a category for an entity, a tremendous amount of knowledge becomes available that is useful in a variety of ways. This knowledge may specify the origins of the entity, its physical structure, its probable behavior, its implications for the perceivers goals, or actions for interacting with it successfully. Accessing a category is not an end in itself but is instead the gateway to knowledge for understanding an entity and interacting with it appropriately. The chapter focuses on the roles that categories play in the cognitive system following their access. For example, it has been proposed that goal-derived categories provide sets of instantiations for frame attributes during planning and that common taxonomic categories constitute the building blocks of world models. To make significant progress, it is necessary to explore important issues for which meticulous answers do not exist initially but exist eventually.

Situating abstract concepts

Situating Abstract Concepts Lawrence W. Barsalou (barsalou@emory.edu) Department of Psychology Emory University, Atlanta, GA 30322 USA Katja Wiemer-Hastings (katja@niu.edu) Department of Psychology Northern Illinois University, DeKalb IL 60115 USA Roughly speaking, abstract concepts such as TRUTH refer to entities that are neither purely physical nor spatially constrained (Wiemer-Hastings, Krug, & Xu, 2001). Such concepts pose a classic problem for theories that ground knowledge in modality-specific systems (e.g., Barsalou, 1999, 2003a,b). Abstract concepts also pose a significant problem for traditional theories that represent knowledge with amodal symbols. Surprisingly, few researchers have attempted to specify the content of abstract concepts using feature lists, semantic networks, or frames. It is not enough to say that an amodal node or a pattern of amodal units represents an abstract concept. It is first necessary to specify the concept’s content, before beginning the task of identifying how this content is represented. concepts. For all concepts, participants tended to describe background situations, including information about entities, settings, events, and mental states. Indeed the similarities between concepts were more striking than the differernces. Both analyses also offered support for Hypothesis 2, namely, concrete and abstract concepts differed in their situational foci. Whereas concrete concepts focused more on objects, locations, and behaviors, abstract concepts focused more on social aspects of situations (e.g., people, communication, social institutions) and mental states (e.g., beliefs. complex relations). Intermediate concepts lay in between. Consistent with Hypothesis 3, conceptual structures were most complex for abstract concepts. Abstract concepts were most likely to contain deep hierarchies of large conceptual clusters organized by complex relations. Regarding Hypothesis 4, we see no reason that the content of abstract concepts cannot be represented in simulations. Because their content is perceived in the situations that involve abstract concepts, it could, in principle, be reenacted later when representing them. Clearly, much further research beyond this exploratory study is necessary. Hypotheses A common assumption is that abstract and concrete concepts have little conceptual content in common, if any. Alternatively, we propose that concrete and abstract concepts share important similarities. In particular, we propose that they share common situational content, namely, information about agents, objects, settings, events, and mental states (Hypothesis 1). Where concrete and abstract concepts differ is in their specific foci within background situations. Whereas concrete concepts focus on objects and settings, abstract concepts focus on events and mental states (Hypothesis 2). As a result of these different foci, the representations of abstract concepts are more complex, being less localized in situational content (Hypothesis 3). Finally, because the content of abstract concepts is grounded in situations, modality-specific simulations could, in principle, represent it (Hypothesis 4). Acknowledgement This work was supported by National Science Foundation Grants SBR-9905024 and BCS-0212134 to Lawrence W. Barsalou. References Barsalou, L.W. (1999). Perceptual symbol systems. Behavioral and Brain Sciences, 22, 577-609. Barsalou, L.W. (2003a). Abstraction in perceptual symbol systems. Philosophical Transactions of the Royal Society of London: Biological Sciences, 358, 1177-1187. Barsalou, L.W. (2003b). Situated simulation in the human conceptual system. Language and Cognitive Processes, Barsalou, L.W., & Wiemer-Hastings, K. (in press). Situating abstract concepts. In D. Pecher and R. Zwaan (Eds.), Grounding cognition: The role of perception and action in memory, language, and thought. New York: Cambridge University Press. Wiemer-Hastings, K., Krug, J., & Xu, X. (2001). Imagery, context availability, contextual constraint, and abstractness. Proceedings of the 23 rd Annual Conference of the Cognitive Science Society, 1134-1139. Mahwah, NJ: Erlbaum. Method In an exploratory study, we assessed the content of three abstract concepts: TRUTH, FREEDOM, and INVENTION. These concepts were compared to three concrete concepts— BIRD, CAR, and SOFA—and also to three intermediate concepts—COOKING, FARMING, and CARPETING. We first asked participants to produce properties typically true of these concepts. We then analyzed these properties using two coding schemes, one that coded small protocol units, and a second that coded large ones. Results For the complete results, see Barsalou and Wiemer-Hastings (in press). Both coding analyses offered support for Hypothesis 1, namely, common situational content was produced across concrete, intermediate, and abstract