49 research outputs found
The effects of sensorimotor and linguistic information on the basic-level advantage
No full textThe basic-level advantage is one of the best-known effects in human categorisation. Traditional accounts argue that basic-level categories present a maximally informative or entry level into a taxonomic organisation of concepts in semantic memory. However, these explanations are not fully compatible with most recent views on the structure of the conceptual system such as linguistic-simulation accounts, which emphasise the dual role of sensorimotor (i.e., perception-action experience of the world) and linguistic distributional information (i.e., statistical distribution of words in language) in conceptual processing. In four preregistered word→picture categorisation studies, we examined whether novel measures of sensorimotor and linguistic distance contribute to the basic level-advantage in categorical decision-making. Results showed that overlap in sensorimotor experience between category concept and member concept (e.g., animal→dog) predicted RT and accuracy at least as well as a traditional division into discrete subordinate, basic, and superordinate taxonomic levels. Furthermore, linguistic distributional information contributed to capturing effects of graded category structure where typicality ratings did not. Finally, when image label production frequency was taken into account (i.e., how often people actually produced specific labels for images), linguistic distributional information predicted RT and accuracy above and beyond sensorimotor information. These findings add to our understanding of how sensorimotor-linguistic theories of the conceptual system can explain categorisation behaviour
Timed picture naming norms for 800 photographs of 200 objects in English
No full textThe present study presents picture-naming norms for a large set of 800 high-quality photographs of 200 natural objects and
artefacts spanning a range of categories, with four unique images per object. Participants were asked to provide a single,
most appropriate name for each image seen. We report recognition latencies for each image, and several normed variables for
the provided names: agreement, H-statistic (i.e. level of naming uncertainty), Zipf word frequency and word length. Rather
than simply focusing on a single name per image (i.e. the modal or most common name), analysis of recognition latencies
showed that it is important to consider the diversity of labels that participants may ascribe to each pictured object. The norms
therefore provide a list of candidate labels per image with weighted measures of word length and frequency per image that
incorporate all provided names, as well as modal measures based on the most common name only
Picture Naming Norms
No full textA normed set of 800 images of 200 objects, paired with their modal and non-idiosyncratic names. Descriptive statistics include name agreement (% agreement, h-statistic) and psycholinguistic characteristics of the names (frequency, word length, both for the modal names and weighted across all given names)
The Role of Sensorimotor and Linguistic Distributional Information in Categorisation
No full textHow do people know what categories objects belong to? Traditional accounts of categorisation typically assume that concepts comprise perceptual or functional features. By contrast, recent accounts of conceptual structure emphasise the dual role of sensorimotor (i.e., perception-action experience of the world) and linguistic distributional information (i.e., statistical distribution of words in language). This thesis contains a literature review and four empirical papers describing pre-registered experiments, which explore how the degree of sensorimotor-linguistic representational overlap between category- and member-concepts may drive object categorisation. Chapter 1 presents a review of the literature, covering relevant theories of categorisation, as well as sensorimotor-linguistic theories of conceptual processing. Chapter 2 presents a study which explored the role of sensorimotor and linguistic distributional information in processing advantages. This study found that overlap in sensorimotor and linguistic distributional representations between category (e.g., dog) and member (e.g., Labrador) concepts reliably predicted performance (accuracy, RT) in a speeded picture category verification task. Chapter 3 reports a study that contrasted the traditional prediction of a basic-level advantage with the sensorimotor-linguistic prediction that representational overlap, not taxonomic level, is more important to categorisation. In a forced-choice categorisation task using labels only, participants decided between a basic- (e.g., dog) and superordinate-level label (e.g., animal) for a target object label (e.g., Labrador). While basic-level labels were overall chosen faster and more frequently, an exploratory analysis suggested that basic-level categorisation was slowed down when sensorimotor-linguistic overlap was greater between the target object label and the superordinate label. Chapter 4 describes the collection of a normed set of 800 photographs of 200 natural objects and artefacts, and their most frequent names. An exploratory analysis of the object recognition latencies associated with each photograph found that word frequency and length averaged over all names given to an image predicted object recognition time better than the word frequency and length of the most frequent response. Chapter 5 reports a study that used the images and names collected in the study reported in Chapter 4, and examined the role of sensorimotor and linguistic distributional information in an ultra-rapid object categorisation paradigm with backwards masking. This study found evidence for the effect of linguistic distributional on sensorimotor information on categorisation accuracy, but not RT, nor was there a systematic relationship between perceptual processing time and sensorimotor-linguistic information. In summary, the findings presented in this thesis provide support for a novel account of object categorisation based on sensorimotor and linguistic distributional representational overlap between category and member concepts
Linguistic distributional information about object labels affects ultrarapid object categorization
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Linguistic distributional information about object labels affects ultrarapid object categorization
No full textWhen given unrestricted time to process an image, people are faster and more accurate at making categorical decisions about a depicted object (e.g., Labrador) if it is close in sensorimotor and linguistic distributional experience to its target category concept (e.g., dog). In this preregistered study, we examined whether sensorimotor and linguistic distributional information affect object categorisation differently as a function of time available for perceptual processing. Using an ultrarapid categorisation paradigm with backwards masking, we systematically varied onset timing (SOA) of a post-stimulus mask (17-133ms) following a briefly displayed (17ms) object. Preliminary results suggest that linguistic distributional distance between concept and category (e.g., Labrador → dog), but not sensorimotor distance, affects categorisation accuracy and RT even in rapid categorisation, and that these effects do not vary systematically by SOA. These findings support the role of a linguistic shortcut (i.e., using linguistic distributional instead of sensorimotor information) in rapid object categorisation
