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After reviewing six senses of abstraction, this article focuses on abstractions that take the form of summary representations. Three central properties of these abstractions are established: ( i ) type-token interpretation; (ii) structured representation; and (iii) dynamic realization. Traditional theories of representation handle interpretation and structure well but are not sufficiently dynamical. Conversely, connectionist theories are exquisitely dynamic but have problems with structure. Perceptual symbol systems offer an approach that implements all three properties naturally. Within this framework, a loose collection of property and relation simulators develops to represent abstractions. Type-token interpretation results from binding a property simulator to a region of a perceived or simulated category member. Structured representation results from binding a configuration of property and relation simulators to multiple regions in an integrated manner. Dynamic realization results from applying different subsets of property and relation simulators to category members on different occasions. From this standpoint, there are no permanent or complete abstractions of a category in memory. Instead, abstraction is the skill to construct temporary online interpretations of a category's members. Although an infinite number of abstractions are possible, attractors develop for habitual approaches to interpretation. This approach provides new ways of thinking about abstraction phenomena in categorization, inference, background knowledge and learning.
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Theories typically emphasize affordances or intentions as the primary determinant of an object's perceived function. The HIPE theory assumes that people integrate both into causal models that produce functional attributions. In these models, an object's physical structure and an agent's action specify an affordance jointly, constituting the immediate causes of a perceived function. The object's design history and an agent's goal in using it constitute distant causes. When specified fully, the immediate causes are sufficient for determining the perceived function--distant causes have no effect (the causal proximity principle). When the immediate causes are ambiguous or unknown, distant causes produce inferences about the immediate causes, thereby affecting functional attributions indirectly (the causal updating principle). Seven experiments supported HIPE's predictions.
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In studying categorization, cognitive science has focused primarily on cultural categorization, ignoring individual and institutional categorization. Because recent technological developments have made individual and institutional classification systems much more available and powerful, our understanding of the cognitive and social mechanisms that produce these systems is increasingly important. Furthermore, key aspects of categorization that have received little previous attention emerge from considering diverse types of categorization together, such as the social factors that create stability in classification systems, and the interoperability that shared conceptual systems establish between agents. Finally, the profound impact of recent technological developments on classification systems indicates that basic categorization mechanisms are highly adaptive, producing new classification systems as the situations in which they operate change.
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We propose that cognition is more than a collection of independent processes operating in a modular cognitive system. Instead, we propose that cognition emerges from dependencies between all of the basic systems in the brain, including goal management, perception, action, memory, reward, affect, and learning. Furthermore, human cognition reflects its social evolution and context, as well as contributions from a developmental process. After presenting these themes, we illustrate their application to the process of anticipation. Specifically, we propose that anticipations occur extensively across domains (i.e., goal management, perception, action, reward, affect, and learning) in coordinated manners. We also propose that anticipation is central to situated action and to social interaction, and that many of its key features reflect the process of development.
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The conceptual system contains categorical knowledge about experience that supports the spectrum of cognitive processes. Cognitive science theories assume that categorical knowledge resides in a modular and amodal semantic memory, whereas neuroscience theories assume that categorical knowledge is grounded in the brain's modal systems for perception, action, and affect. Neuroscience has influenced theories of the conceptual system by stressing principles of neural processing in neural networks and by motivating grounded theories of cognition, which propose that simulations of experience represent knowledge. Cognitive science has influenced theories of the conceptual system by documenting conceptual phenomena and symbolic operations that must be grounded in the brain. Significant progress in understanding the conceptual system is most likely to occur if cognitive and neural approaches achieve successful integration.
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Grounded theories assume that there is no central module for cognition. According to this view, all cognitive phenomena, including those considered the province of amodal cognition such as reasoning, numeric, and language processing, are ultimately grounded in (and emerge from) a variety of bodily, affective, perceptual, and motor processes. The development and expression of cognition is constrained by the embodiment of cognitive agents and various contextual factors (physical and social) in which they are immersed. The grounded framework has received numerous empirical confirmations. Still, there are very few explicit computational models that implement grounding in sensory, motor and affective processes as intrinsic to cognition, and demonstrate that grounded theories can mechanistically implement higher cognitive abilities. We propose a new alliance between grounded cognition and computational modeling toward a novel multidisciplinary enterprise: Computational Grounded Cognition. We clarify the defining features of this novel approach and emphasize the importance of using the methodology of Cognitive Robotics, which permits simultaneous consideration of multiple aspects of grounding, embodiment, and situatedness, showing how they constrain the development and expression of cognition.
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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.
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Concepts develop for many aspects of experience, including abstract internal states and abstract social activities that do not refer to concrete entities in the world. The current study assessed the hypothesis that, like concrete concepts, distributed neural patterns of relevant nonlinguistic semantic content represent the meanings of abstract concepts. In a novel neuroimaging paradigm, participants processed two abstract concepts (convince, arithmetic) and two concrete concepts (rolling, red) deeply and repeatedly during a concept-scene matching task that grounded each concept in typical contexts. Using a catch trial design, neural activity associated with each concept word was separated from neural activity associated with subsequent visual scenes to assess activations underlying the detailed semantics of each concept. We predicted that brain regions underlying mentalizing and social cognition (e.g., medial prefrontal cortex, superior temporal sulcus) would become active to represent semantic content central to convince, whereas brain regions underlying numerical cognition (e.g., bilateral intraparietal sulcus) would become active to represent semantic content central to arithmetic. The results supported these predictions, suggesting that the meanings of abstract concepts arise from distributed neural systems that represent concept-specific content.
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In a recent neuroimaging study of macaque monkeys, Gil-da-Costa and colleagues reported that a distributed circuit of modality-specific properties represents macaques' conceptual knowledge of social situations. The circuit identified shows striking similarities to analogous circuits in humans that represent conceptual knowledge. This parallel suggests that a common architecture underlies the conceptual systems of different species, although with additional systems extending human conceptual abilities significantly.
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In a recent neuroimaging study of macaque monkeys, Gil-da-Costa and colleagues reported that a distributed circuit of modality-specific properties represents macaques' conceptual knowledge of social situations. The circuit identified shows striking similarities to analogous circuits in humans that represent conceptual knowledge. This parallel suggests that a common architecture underlies the conceptual systems of different species, although with additional systems extending human conceptual abilities significantly.
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Recent findings have suggested that script actions are not sequentially organized in memory. Instead investigators have argued that (1) the positions of actions within scripts are represented by temporal properties stored with actions, this being analogous to how properties represent the size, color, and other characteristics of exemplars in categories, and (2) actions are organized by centrality in scripts, this being analogous to how exemplars are organized by typicality in categories. To compare the representation of scripts and categories, this study observed timed production of script actions and category exemplars. Subjects generated actions from scripts either in whatever order they came to mind, from most to least central, from first to last, or from last to first. Subjects generated exemplars from categories either in whatever order they came to mind, from most to least typical, from smallest to largest, or from largest to smallest. The results clearly demonstrated that script actions are sequentially organized in memory and that properties are not the means by which script actions are normally ordered during production. The results are also not consistent with the view that ease of production simply depends on the efficiency of retrieval strategies. It is concluded that scripts and categories share invariant properties of abstract representations and that their differences reflect constraints associated with their respective domains.
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Simulations of human cognitive processes often employ discrimination nets to model the access of permanent memory. We consider two types of discrimination nets—EPAM and positive-proper-only nets—and argue that they have insufficient psychological validity. Their deficiencies arise from negative properties, insufficient sensitivity to the discriminativeness of properties, extreme sensitivity to missing or incorrect properties, inefficiency in representing multiple knowledge domains, and seriality. We argue that these deficiencies stem from a high degree of test contingency in utilizing property information during acquisition and memory search. Discrimination nets are compared to other models that have less or no test contingency (e.g., PANDEMONIUM) and that thereby avoid the problems of discrimination nets. We propose that understanding test contingency and discovering psychologically valid ways to implement it will be central to understanding and simulating memory indexing in human cognition.
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This study sought to examine the effect of meditation experience on brain networks underlying cognitive actions employed during contemplative practice. In a previous study, we proposed a basic model of naturalistic cognitive fluctuations that occur during the practice of focused attention meditation. This model specifies four intervals in a cognitive cycle: mind wandering (MW), awareness of MW, shifting of attention, and sustained attention. Using subjective input from experienced practitioners during meditation, we identified activity in salience network regions during awareness of MW and executive network regions during shifting and sustained attention. Brain regions associated with the default mode were active during MW. In the present study, we reasoned that repeated activation of attentional brain networks over years of practice may induce lasting functional connectivity changes within relevant circuits. To investigate this possibility, we created seeds representing the networks that were active during the four phases of the earlier study, and examined functional connectivity during the resting state in the same participants. Connectivity maps were then contrasted between participants with high vs. low meditation experience. Participants with more meditation experience exhibited increased connectivity within attentional networks, as well as between attentional regions and medial frontal regions. These neural relationships may be involved in the development of cognitive skills, such as maintaining attention and disengaging from distraction, that are often reported with meditation practice. Furthermore, because altered connectivity of brain regions in experienced meditators was observed in a non-meditative (resting) state, this may represent a transference of cognitive abilities “off the cushion” into daily life.
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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 brain's 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.
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People believe they see emotion written on the faces of other people. In an instant, simple facial actions are transformed into information about another's emotional state. The present research examined whether a perceiver unknowingly contributes to emotion perception with emotion word knowledge. We present 2 studies that together support a role for emotion concepts in the formation of visual percepts of emotion. As predicted, we found that perceptual priming of emotional faces (e.g., a scowling face) was disrupted when the accessibility of a relevant emotion word (e.g., anger) was temporarily reduced, demonstrating that the exact same face was encoded differently when a word was accessible versus when it was not. The implications of these findings for a linguistically relative view of emotion perception are discussed.
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Grounded cognition rejects traditional views that cognition is computation on amodal symbols in a modular system, independent of the brain's modal systems for perception, action, and introspection. Instead, grounded cognition proposes that modal simulations, bodily states, and situated action underlie cognition. Accumulating behavioral and neural evidence supporting this view is reviewed from research on perception, memory, knowledge, language, thought, social cognition, and development. Theories of grounded cognition are also reviewed, as are origins of the area and common misperceptions of it. Theoretical, empirical, and methodological issues are raised whose future treatment is likely to affect the growth and impact of grounded cognition.
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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.
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According to the Conceptual Act Theory of Emotion, the situated conceptualization used to construe a situation determines the emotion experienced. A neuroimaging experiment tested two core hypotheses of this theory: (1) different situated conceptualizations produce different forms of the same emotion in different situations, (2) the composition of a situated conceptualization emerges from shared multimodal circuitry distributed across the brain that produces emotional states generally. To test these hypotheses, the situation in which participants experienced an emotion was manipulated. On each trial, participants immersed themselves in a physical danger or social evaluation situation and then experienced fear or anger. According to Hypothesis 1, the brain activations for the same emotion should differ as a function of the preceding situation (after removing activations that arose while constructing the situation). According to Hypothesis 2, the critical activations should reflect conceptual processing relevant to the emotion in the current situation, drawn from shared multimodal circuitry underlying emotion. The results supported these predictions and demonstrated the compositional process that produces situated conceptualizations dynamically.
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Many objects typically occur in particular locations, and object words encode these spatial associations. We tested whether such object words (e.g., head, foot) orient attention toward the location where the denoted object typically occurs (i.e., up, down). Because object words elicit perceptual simulations of the denoted objects (i.e., the representations acquired during actual perception are reactivated), we predicted that an object word would interfere with identification of an unrelated visual target subsequently presented in the object's typical location. Consistent with this prediction, three experiments demonstrated that words denoting objects that typically occur high in the visual field hindered identification of targets appearing at the top of the display, whereas words denoting low objects hindered target identification at the bottom of the display. Thus, object words oriented attention to and activated perceptual simulations in the objects' typical locations. These results shed new light on how language affects perception.
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Three possible determinants of graded structure (typicality) were observed in common taxonomic categories and goal-derived categories: (1) an exemplar's similarity to ideals associated with goals its category serves; (2) an exemplar's similarity to the central tendency of its category (family resemblance); and (3) an exemplar's frequency of instantiation (people's 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 category's graded structure can change with context. Whereas ideals may determine a category's graded structure
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According to the instantiation principle, the representation of a category includes detailed information about its diverse range of instances. Many accounts of categorization, including classical and standard prototype theories, do not follow the instantiation principle, because they assume that detailed, exemplar-level information is filtered out of category representations. Nevertheless, the instantiation principle can be implemented in a wide class of models, including both exemplar and abstraction models. To assess the instantiation principle empirically, a parameter-free exemplarbased model of instantiation was applied to typicality judgments for 16 simple categories (e.g., mammal, beverage) and 14 complex categories (e.g., dangerous mammal) in four superordinates (animal, food, small animal, dangerous animal). Across three studies, the model did an excellent job of predicting mean typicality judgments (correlations generally above .9) and a good job of predicting standard deviati...
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Grounded cognition offers a natural approach for integrating Bayesian accounts of optimality with mechanistic accounts of cognition, the brain, the body, the physical environment, and the social environment. The constructs of simulator and situated conceptualization illustrate how Bayesian priors and likelihoods arise naturally in grounded mechanisms to predict and control situated action.
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