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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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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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Two groups of subjects classified as high vs. low in the need for power (n power) were assessed for augmenting versus reducing in the event-related potential (ERP) elicited by neutral and power-related words. Words at four different intensity levels in each of these two classes were randomly presented and ERPs in response to each word class at each of the four intensity levels were computed from EEG recorded at Fz. The results indicated that the two groups responded differentially to the power-related vs. neutral words. HIgh n power subjects showed reduction in response to both power-related and neutral words while low n power subjects showed augmentation in response to the power-related words.
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Two groups of subjects classified as high vs. low in the need for power (n power) were assessed for augmenting versus reducing in the event-related potential (ERP) elicited by neutral and power-related words. Words at four different intensity levels in each of these two classes were randomly presented and ERPs in response to each word class at each of the four intensity levels were computed from EEG recorded at Fz. The results indicated that the two groups responded differentially to the power-related vs. neutral words. HIgh n power subjects showed reduction in response to both power-related and neutral words while low n power subjects showed augmentation in response to the power-related words.

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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Theories of knowledge such as feature lists, semantic networks, and localist neural nets typically use a single global symbol to represent a property that occurs in multiple concepts. Thus, a global symbol represents mane across HORSE, PONY, and LION. Alternatively, perceptual theories of knowledge, as well as distributed representational systems, assume that properties take different local forms in different concepts. Thus, different local forms of mane exist for HORSE, PONY, and LION, each capturing the specific form that mane takes in its respective concept. Three experiments used the property verification task to assess whether properties are represented globally or locally (e.g., Does a PONY have mane?). If a single global form represents a property, then verifying it in any concept should increase its accessibility and speed its verification later in any other concept. Verifying mane for PONY should benefit as much from having verified mane for LION earlier as from verifying mane for HORSE. If properties are represented locally, however, verifying a property should only benefit from verifying a similar form earlier. Verifying mane for PONY should only benefit from verifying mane for HORSE, not from verifying mane for LION. Findings from three experiments strongly supported local property representation and ruled out the interpretation that object similarity was responsible (e.g., the greater overall similarity between HORSE and PONY than between LION and PONY). The findings further suggest that property representation and verification are complicated phenomena, grounded in sensory-motor simulations.
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For decades the importance of background situations has been documented across all areas of cognition. Nevertheless, theories of concepts generally ignore background situations, focusing largely on bottom-up, stimulus-based processing. Furthermore, empirical research on concepts typically ignores background situations, not incorporating them into experimental designs. A selective review of relevant literatures demonstrates that concepts are not abstracted out of situations but instead are situated. Background situations constrain conceptual processing in many tasks (e.g., recall, recognition, categorization, lexical decision, color naming, property verification, property generation) across many areas of cognition (e.g., episodic memory, conceptual processing, visual object recognition, language comprehension). A taxonomy of situations is proposed in which grain size, meaningfulness, and tangibility distinguish the cumulative situations that structure cognition hierarchically.
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Four theories of the human conceptual system--semantic memory, exemplar models, feed-forward connectionist nets, and situated simulation theory--are characterized and contrasted on five dimensions. Empirical evidence is then reviewed for the situated simulation theory and conclusions are discussed. (Author/VWL)
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