Literature DB >> 31965462

Taking pigeons to heart: Birds proficiently diagnose human cardiac disease.

Victor M Navarro1, Edward A Wasserman2, Piotr Slomka3.   

Abstract

In two experiments, we trained pigeons (Columba livia) to sort visual images (obtained by clinical myocardial perfusion imaging techniques) depicting different degrees of human cardiac disfunction (myocardial hypoperfusion of the left ventricle) into normal and abnormal categories by providing food reward only after correct choice responses. Pigeons proved to be highly proficient at categorizing pseudo-colorized images as well as highly sensitive to the degree of the perfusion deficit depicted in the abnormal images. In later testing, the pigeons completely transferred discriminative responding to novel stimuli, demonstrating that they had fully learned the normal and abnormal categories. Yet, these pigeons failed to transfer discriminative responding to grayscale images containing no color information. We therefore trained a second cohort of pigeons to categorize grayscale image sets from the outset. These birds required substantially more training to achieve similar levels of performance. Yet, they too completely transferred discriminative responding to novel stimuli by relying on both global and local disparities in brightness between the normal and abnormal images. These results confirm that pseudo-colorization can enhance pigeons' categorization of human cardiac images, a result also found with human observers. Overall, our findings further document the potential of the pigeon as a useful aide in studies of medical image perception.

Entities:  

Keywords:  Attention; Categorization; Concept learning; Discrimination; Generalization; Pigeon

Mesh:

Year:  2020        PMID: 31965462      PMCID: PMC7085459          DOI: 10.3758/s13420-020-00410-z

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


  37 in total

1.  Additivity of cues and transfer in discrimination of consonant clusters.

Authors:  F RESTLE
Journal:  J Exp Psychol       Date:  1959-01

2.  Engineering behavior: Project Pigeon, World War II, and the conditioning of B. F. Skinner.

Authors:  J H Capshew
Journal:  Technol Cult       Date:  1993-10       Impact factor: 0.850

Review 3.  The role of the translation table in cardiac image display.

Authors:  Christopher L Hansen
Journal:  J Nucl Cardiol       Date:  2006-07       Impact factor: 5.952

4.  Orthographic processing in pigeons (Columba livia).

Authors:  Damian Scarf; Karoline Boy; Anelisie Uber Reinert; Jack Devine; Onur Güntürkün; Michael Colombo
Journal:  Proc Natl Acad Sci U S A       Date:  2016-09-16       Impact factor: 11.205

5.  Multiple feature use in pigeons' category discrimination: The influence of stimulus set structure and the salience of stimulus differences.

Authors:  Stephen E G Lea; Emmanuel M Pothos; Andy J Wills; Lisa A Leaver; Catriona M E Ryan; Christina Meier
Journal:  J Exp Psychol Anim Learn Cogn       Date:  2018-04       Impact factor: 2.478

Review 6.  Current perspectives in medical image perception.

Authors:  Elizabeth A Krupinski
Journal:  Atten Percept Psychophys       Date:  2010-07       Impact factor: 2.199

7.  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

8.  Improved accuracy of myocardial perfusion SPECT for the detection of coronary artery disease using a support vector machine algorithm.

Authors:  Reza Arsanjani; Yuan Xu; Damini Dey; Matthews Fish; Sharmila Dorbala; Sean Hayes; Daniel Berman; Guido Germano; Piotr Slomka
Journal:  J Nucl Med       Date:  2013-03-12       Impact factor: 10.057

9.  What makes a categorization task difficult?

Authors:  Leola A Alfonso-Reese; F Gregory Ashby; David H Brainard
Journal:  Percept Psychophys       Date:  2002-05

10.  Carotid artery dissection on non-contrast CT: does color improve the diagnostic confidence?

Authors:  Luca Saba; Giovanni Maria Argiolas; Eytan Raz; Stefano Sannia; Jasjit S Suri; Paolo Siotto; Roberto Sanfilippo; Roberto Montisci; Mario Piga; Max Wintermark
Journal:  Eur J Radiol       Date:  2014-09-21       Impact factor: 3.528

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  1 in total

1.  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

  1 in total

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