Literature DB >> 29120213

Feature predictiveness and selective attention in pigeons' categorization learning.

Leyre Castro1, Edward A Wasserman1.   

Abstract

Prior categorization studies have shown that pigeons reliably track features that are perfect predictors of category membership (Castro & Wasserman, 2014, 2016a). One might further ask whether pigeons would also track features that are relevant, but imperfect predictors of category membership. In our present project, pigeons had to categorize multiple exemplars from 2 different artificial categories, in which the exemplars were composed of 4 different features that were associated with 1 of 2 different report responses. Each exemplar contained 1 feature that perfectly predicted category membership; 1 feature that imperfectly predicted category membership; and, 2 irrelevant features that did not predict category membership. We monitored pigeons' choice accuracy as well as the location of their pecks to each of the 4 exemplar features to determine to which attributes the birds attended. As categorization accuracy rose, pecks to the perfect predictor of each category rose as well. Pigeons also showed evidence of attending more to the imperfect predictor than to the irrelevant features, but to a lesser degree. Overall, our results provide evidence of selective attention in pigeons' categorization behavior. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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Year:  2017        PMID: 29120213      PMCID: PMC5684886          DOI: 10.1037/xan0000146

Source DB:  PubMed          Journal:  J Exp Psychol Anim Learn Cogn        ISSN: 2329-8456            Impact factor:   2.478


  29 in total

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7.  Pigeons' tracking of relevant attributes in categorization learning.

Authors:  Leyre Castro; Edward A Wasserman
Journal:  J Exp Psychol Anim Learn Cogn       Date:  2014-04       Impact factor: 2.478

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Authors:  R Desimone; J Duncan
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  7 in total

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Review 2.  The neuroscience of perceptual categorization in pigeons: A mechanistic hypothesis.

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7.  Digital embryos: a novel technical approach to investigate perceptual categorization in pigeons (Columba livia) using machine learning.

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  7 in total

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