The empirical study of language has historically relied heavily upon concrete word stimuli. By definition, concrete words evoke salient perceptual associations that fit well within feature-based, sensorimotor models of word meaning. In contrast, many theorists argue that abstract words are “disembodied” in that their meaning is mediated through language. We investigated word meaning as distributed in multidimensional space using hierarchical cluster analysis. Participants (N = 365) rated target words (n = 400 English nouns) across 12 cognitive dimensions (e.g., polarity, ease of teaching, emotional valence). Factor reduction revealed three latent factors, corresponding roughly to perceptual salience, affective association, and magnitude. We plotted the original 400 words for the three latent factors. Abstract and concrete words showed overlap in their topography but also differentiated themselves in semantic space. This topographic approach to word meaning offers a unique perspective to word concreteness.

This study harnessed control ratings of the contribution of different types of information (sensation, action, emotion, thought, social interaction, morality, time, space, quantity, and polarity) to 400 individual abstract and concrete verbal concepts. These abstract conceptual feature (ACF) ratings were used to generate a high dimensional semantic space, from which Euclidean distance measurements between individual concepts were extracted as a metric of the semantic relatedness of those words. The validity of these distances as a marker of semantic relatedness was then tested by evaluating whether they could predict the comprehension performance of a patient with global aphasia on two verbal comprehension tasks. It was hypothesized that if the high-dimensional space generated from ACF control ratings approximates the organization of abstract conceptual space, then words separated by small distances should be more semantically related than words separated by greater distances, and should therefore be more difficult to distinguish for the comprehension-impaired patient, SKO. SKO was significantly worse at identifying targets presented within word pairs with low ACF distances. Response accuracy was not predicted by Latent Semantic Analysis (LSA) cosines, any of the individual feature ratings, or any of the background variables. It is argued that this novel rating procedure provides a window on the semantic attributes of individual abstract concepts, and that multiple cognitive systems may influence the acquisition and organization of abstract conceptual knowledge. More broadly, it is suggested that cognitive models of abstract conceptual knowledge must account for the representation not only of the relationships between abstract concepts but also of the attributes which constitute those individual concepts.

Cognitive science has a longstanding interest in the ways that people acquire and use abstract vs. concrete words (e.g., truth vs. piano). One dominant theory holds that abstract and concrete words are subserved by two parallel semantic systems. We recently proposed an alternative account of abstract-concrete word representation premised upon a unitary, high dimensional semantic space wherein word meaning is nested. We hypothesize that a range of cognitive and perceptual dimensions (e.g., emotion, time, space, color, size, visual form) bound this space, forming a conceptual topography. Here we report a normative study where we examined the clustering properties of a sample of English words (N = 750) spanning a spectrum of concreteness in a continuous manner from highly abstract to highly concrete. Participants (N = 328) rated each target word on a range of 14 cognitive dimensions (e.g., color, emotion, valence, polarity, motion, space). The dimensions reduced to three factors: Endogenous factor, Exogenous factor, and Magnitude factor. Concepts were plotted in a unified, multimodal space with concrete and abstract concepts along a continuous continuum. We discuss theoretical implications and practical applications of this dataset. These word norms are freely available for download and use at http://www.reilly-coglab.com/data/.

Purpose Deficits in auditory perception compromise a range of linguistic processes in persons with Parkinson’s disease (PD), including speech perception and sensitivity to affective and linguistic prosody. An unanswered question is whether this deficit exists not only at the level of speech perception, but also at a more pervasive level of auditory perception. It is possible that PD produces a selective impairment in the perception of a salient acoustic feature such as frequency, amplitude, or duration. Method Auditory perception in persons with PD was investigated using a tone discrimination task where clients (N = 12) and age-matched controls (N = 15) made same/different judgments for pairs of pure tones that were factorially varied by acoustic feature (i.e., frequency, amplitude, or duration) crossed with perceptual distance (i.e., close vs. far). Results Relative to healthy age-matched controls, persons with PD showed marked impairment in tone discrimination. Persons with PD showed an acoustic feature by perceptual distance interaction that was characterized by deficits in detecting frequency and amplitude differences for perceptually near tones. Conclusion These results suggest that persons with PD show a reduced ability to notice change in frequency and amplitude as compared to normal older adults. More generally, these findings implicate a frontal–striatal contribution to auditory perception.

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