Literature DB >> 29532328

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

Onur Güntürkün1, Charlotte Koenen2, Fabrizio Iovine2,3, Alexis Garland2, Roland Pusch2.   

Abstract

We are surrounded by an endless variation of objects. The ability to categorize these objects represents a core cognitive competence of humans and possibly all vertebrates. Research on category learning in nonhuman animals started with the seminal studies of Richard Herrnstein on the category "human" in pigeons. Since then, we have learned that pigeons are able to categorize a large number of stimulus sets, ranging from Cubist paintings to English orthography. Strangely, this prolific field has largely neglected to also study the avian neurobiology of categorization. Here, we present a hypothesis that combines experimental results and theories from categorization research in pigeons with neurobiological insights on visual processing and dopamine-mediated learning in primates. We conclude that in both fields, similar conclusions on the mechanisms of perceptual categorization have been drawn, despite very little cross-reference or communication between these two areas to date. We hypothesize that perceptual categorization is a two-component process in which stimulus features are first rapidly extracted in a feed-forward process, thereby enabling a fast subdivision along multiple category borders. In primates this seems to happen in the inferotemporal cortex, while pigeons may primarily use a cluster of associative visual forebrain areas. The second process rests on dopaminergic error-prediction learning that enables prefrontal areas to connect top down the relevant visual category dimension to the appropriate action dimension.

Entities:  

Keywords:  Avian; Dopamine; Nonhuman primates; Prefrontal areas; Rescorla–Wagner; Tectofugal system

Mesh:

Year:  2018        PMID: 29532328     DOI: 10.3758/s13420-018-0321-6

Source DB:  PubMed          Journal:  Learn Behav        ISSN: 1543-4494            Impact factor:   1.986


  104 in total

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Journal:  Brain Res       Date:  2001-10-26       Impact factor: 3.252

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3.  Lateralized reward-related visual discrimination in the avian entopallium.

Authors:  Josine Verhaal; Janina A Kirsch; Ioannis Vlachos; Martina Manns; Onur Güntürkün
Journal:  Eur J Neurosci       Date:  2012-03-27       Impact factor: 3.386

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Authors:  R J Herrnstein
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Review 5.  Neural mechanisms of visual categorization: insights from neurophysiology.

Authors:  David J Freedman; Earl K Miller
Journal:  Neurosci Biobehav Rev       Date:  2007-08-15       Impact factor: 8.989

6.  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:  J Cerella
Journal:  J Exp Psychol Hum Percept Perform       Date:  1979-02       Impact factor: 3.332

8.  Gamma and Beta Bursts Underlie Working Memory.

Authors:  Mikael Lundqvist; Jonas Rose; Pawel Herman; Scott L Brincat; Timothy J Buschman; Earl K Miller
Journal:  Neuron       Date:  2016-03-17       Impact factor: 17.173

9.  Natural scene statistics account for the representation of scene categories in human visual cortex.

Authors:  Dustin E Stansbury; Thomas Naselaris; Jack L Gallant
Journal:  Neuron       Date:  2013-08-08       Impact factor: 17.173

10.  Categorization of birds, mammals, and chimeras by pigeons.

Authors:  Robert G Cook; Anthony A Wright; Eric E Drachman
Journal:  Behav Processes       Date:  2012-11-19       Impact factor: 1.777

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  7 in total

1.  Assessing Attention in Category Learning by Animals.

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

2.  "Prefrontal" Neuronal Foundations of Visual Asymmetries in Pigeons.

Authors:  Qian Xiao; Onur Güntürkün
Journal:  Front Physiol       Date:  2022-05-02       Impact factor: 4.755

3.  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

4.  Pigeons show how meta-control enables decision-making in an ambiguous world.

Authors:  Martina Manns; Tobias Otto; Laurenz Salm
Journal:  Sci Rep       Date:  2021-02-15       Impact factor: 4.379

5.  RUBubbles as a novel tool to study categorization learning.

Authors:  Aylin Apostel; Jonas Rose
Journal:  Behav Res Methods       Date:  2021-10-20

6.  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

Review 7.  Current Approaches and Applications in Avian Genome Editing.

Authors:  Joonbum Lee; Dong-Hwan Kim; Kichoon Lee
Journal:  Int J Mol Sci       Date:  2020-05-30       Impact factor: 5.923

  7 in total

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