Literature DB >> 26304297

Visual category learning.

Jennifer J Richler1, Thomas J Palmeri1.   

Abstract

Visual categories group together different objects as the same kinds of thing. We review a selection of research on how visual categories are learned. We begin with a guide to visual category learning experiments, describing a space of common manipulations of objects, categories, and methods used in the category learning literature. We open with a guide to these details in part because throughout our review we highlight how methodological details can sometimes loom large in theoretical discussions of visual category learning, how variations in methodological details can significantly affect our understanding of visual category learning, and how manipulations of methodological details can affect how visual categories are learned. We review a number of core theories of visual category learning, specifically those theories instantiated as computational models, highlighting just some of the experimental results that help distinguish between competing models. We examine behavioral and neural evidence for single versus multiple representational systems for visual category learning. We briefly discuss how visual category learning influences visual perception, describing empirical and brain imaging results that show how learning to categorize objects can influence how those objects are represented and perceived. We close with work that can potentially impact translation, describing recent experiments that explicitly manipulate key methodological details of category learning procedures with the goal of optimizing visual category learning. WIREs Cogn Sci 2014, 5:75-94. doi: 10.1002/wcs.1268 CONFLICT OF INTEREST: The authors have declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website.
© 2013 John Wiley & Sons, Ltd.

Entities:  

Year:  2013        PMID: 26304297     DOI: 10.1002/wcs.1268

Source DB:  PubMed          Journal:  Wiley Interdiscip Rev Cogn Sci        ISSN: 1939-5078


  17 in total

1.  The dynamics of categorization: Unraveling rapid categorization.

Authors:  Michael L Mack; Thomas J Palmeri
Journal:  J Exp Psychol Gen       Date:  2015-05-04

2.  Modelling individual difference in visual categorization.

Authors:  Jianhong Shen; Thomas J Palmeri
Journal:  Vis cogn       Date:  2016-11-10

3.  Visual statistical learning is modulated by arbitrary and natural categories.

Authors:  Leeland L Rogers; Su Hyoun Park; Timothy J Vickery
Journal:  Psychon Bull Rev       Date:  2021-03-31

4.  The style of a stranger: Identification expertise generalizes to coarser level categories.

Authors:  Rachel A Searston; Jason M Tangen
Journal:  Psychon Bull Rev       Date:  2017-08

5.  On the Role of Cortex-Basal Ganglia Interactions for Category Learning: A Neurocomputational Approach.

Authors:  Francesc Villagrasa; Javier Baladron; Julien Vitay; Henning Schroll; Evan G Antzoulatos; Earl K Miller; Fred H Hamker
Journal:  J Neurosci       Date:  2018-09-18       Impact factor: 6.167

6.  Category Learning Stretches Neural Representations in Visual Cortex.

Authors:  Jonathan Folstein; Thomas J Palmeri; Ana E Van Gulick; Isabel Gauthier
Journal:  Curr Dir Psychol Sci       Date:  2015-02

7.  An exemplar of model-based cognitive neuroscience.

Authors:  Thomas J Palmeri
Journal:  Trends Cogn Sci       Date:  2013-12-05       Impact factor: 20.229

8.  Tracking the emergence of memories: A category-learning paradigm to explore schema-driven recognition.

Authors:  Felipe De Brigard; Timothy F Brady; Luka Ruzic; Daniel L Schacter
Journal:  Mem Cognit       Date:  2017-01

Review 9.  Bayesian statistical approaches to evaluating cognitive models.

Authors:  Jeffrey Annis; Thomas J Palmeri
Journal:  Wiley Interdiscip Rev Cogn Sci       Date:  2017-11-28

10.  A computational cognitive model of judgments of relative direction.

Authors:  Phillip M Newman; Gregory E Cox; Timothy P McNamara
Journal:  Cognition       Date:  2020-12-31
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