Literature DB >> 24893218

Pigeons' tracking of relevant attributes in categorization learning.

Leyre Castro1, Edward A Wasserman1.   

Abstract

Most theories and experimental investigations of discrimination learning and categorization, in both humans and animals, hypothesize that attention must be allocated to the relevant attributes of the training stimuli for learning to occur. Attention has conventionally been inferred after learning has transpired rather than examined while learning is transpiring. We presented pigeons with a visual categorization task in which we monitored their choice accuracy through their responses to different report buttons; critically, we tracked the location of the pigeons' pecks to both the relevant and irrelevant attributes of the training stimuli using touchscreen technology, in order to find out where the birds may have been attending during the course of categorization learning. Pigeons readily mastered the categorization task; most importantly, as training progressed, they increasingly concentrated their pecks on the relevant features of the category exemplars, suggesting that the birds were tracking the relevant information to solve the task. When either new irrelevant features were introduced (Experiment 1) or when new relevant features were introduced and later the discriminative value of these new relevant features was reversed (Experiment 2), pigeons' choice accuracy and peck tracking were strongly affected. These results help elucidate the dynamics and interplay of attention and learning; they also suggest that peck tracking can be a suitable measure of the allocation of attention in pigeons, much as eyetracking is deemed to be a suitable measure of attention in humans.

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Year:  2014        PMID: 24893218     DOI: 10.1037/xan0000022

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


  10 in total

1.  Relative reinforcer rates determine pigeons' attention allocation when separately trained stimuli are presented together.

Authors:  Stephanie Gomes-Ng; Douglas Elliffe; Sarah Cowie
Journal:  Learn Behav       Date:  2019-09       Impact factor: 1.986

2.  The role of category density in pigeons' tracking of relevant information.

Authors:  Cassandra L Sheridan; Leyre Castro; Sol Fonseca; Edward A Wasserman
Journal:  Learn Behav       Date:  2019-09       Impact factor: 1.986

3.  Feature predictiveness and selective attention in pigeons' categorization learning.

Authors:  Leyre Castro; Edward A Wasserman
Journal:  J Exp Psychol Anim Learn Cogn       Date:  2017-07       Impact factor: 2.478

Review 4.  The neuroscience of perceptual categorization in pigeons: A mechanistic hypothesis.

Authors:  Onur Güntürkün; Charlotte Koenen; Fabrizio Iovine; Alexis Garland; Roland Pusch
Journal:  Learn Behav       Date:  2018-09       Impact factor: 1.986

5.  Pigeon category learning: Revisiting the Shepard, Hovland, and Jenkins (1961) tasks.

Authors:  Victor M Navarro; Ridhi Jani; Edward A Wasserman
Journal:  J Exp Psychol Anim Learn Cogn       Date:  2019-03-14       Impact factor: 2.478

6.  Assessing Attention in Category Learning by Animals.

Authors:  Edward A Wasserman; Leyre Castro
Journal:  Curr Dir Psychol Sci       Date:  2021-10-20

7.  Focusing and shifting attention in pigeon category learning.

Authors:  Leyre Castro; Ella Remund Wiger; Edward Wasserman
Journal:  J Exp Psychol Anim Learn Cogn       Date:  2021-07       Impact factor: 2.088

8.  Pigeons exhibit flexibility but not rule formation in dimensional learning, stimulus generalization, and task switching.

Authors:  Ellen M O'Donoghue; Matthew B Broschard; Edward A Wasserman
Journal:  J Exp Psychol Anim Learn Cogn       Date:  2020-01-09       Impact factor: 2.478

9.  Mechanisms of object recognition: what we have learned from pigeons.

Authors:  Fabian A Soto; Edward A Wasserman
Journal:  Front Neural Circuits       Date:  2014-10-13       Impact factor: 3.492

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

Authors:  Roland Pusch; Julian Packheiser; Charlotte Koenen; Fabrizio Iovine; Onur Güntürkün
Journal:  Anim Cogn       Date:  2022-01-06       Impact factor: 2.899

  10 in total

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