Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Quantifying the Internal Structure of Categories Using a Neural Typicality Measure

Quantifying the Internal Structure of Categories Using a Neural Typicality Measure How categories are represented continues to be hotly debated across neuroscience and psychology. One topic that is central to cognitive research on category representation but underexplored in neurobiological research concerns the internal structure of categories. Internal structure refers to how the natural variability between-category members is coded so that we are able to determine which members are more typical or better examples of their category. Psychological categorization models offer tools for predicting internal structure and suggest that perceptions of typicality arise from similarities between the representations of category members in a psychological space. Inspired by these models, we develop a neural typicality measure that allows us to measure which category members elicit patterns of activation that are similar to other members of their category and are thus more central in a neural space. Using an artificial categorization task, we test how psychological and physical typicality contribute to neural typicality, and find that neural typicality in occipital and temporal regions is significantly correlated with subjects' perceptions of typicality. The results reveal a convergence between psychological and neural category representations and suggest that our neural typicality measure is a useful tool for connecting psychological and neural measures of internal category structure. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Cerebral Cortex Oxford University Press

Quantifying the Internal Structure of Categories Using a Neural Typicality Measure

Cerebral Cortex , Volume 24 (7) – Jul 26, 2014

Loading next page...
 
/lp/oxford-university-press/quantifying-the-internal-structure-of-categories-using-a-neural-7iswxKdxRB

References (102)

Publisher
Oxford University Press
Copyright
© The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com
Subject
Articles
ISSN
1047-3211
eISSN
1460-2199
DOI
10.1093/cercor/bht014
pmid
23442348
Publisher site
See Article on Publisher Site

Abstract

How categories are represented continues to be hotly debated across neuroscience and psychology. One topic that is central to cognitive research on category representation but underexplored in neurobiological research concerns the internal structure of categories. Internal structure refers to how the natural variability between-category members is coded so that we are able to determine which members are more typical or better examples of their category. Psychological categorization models offer tools for predicting internal structure and suggest that perceptions of typicality arise from similarities between the representations of category members in a psychological space. Inspired by these models, we develop a neural typicality measure that allows us to measure which category members elicit patterns of activation that are similar to other members of their category and are thus more central in a neural space. Using an artificial categorization task, we test how psychological and physical typicality contribute to neural typicality, and find that neural typicality in occipital and temporal regions is significantly correlated with subjects' perceptions of typicality. The results reveal a convergence between psychological and neural category representations and suggest that our neural typicality measure is a useful tool for connecting psychological and neural measures of internal category structure.

Journal

Cerebral CortexOxford University Press

Published: Jul 26, 2014

Keywords: categorization fMRI representation similarity

There are no references for this article.