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Taking Pigeons to Heart: Birds Proficiently Diagnose Human Cardiac Disease

Overview
Journal Learn Behav
Publisher Springer
Date 2020 Jan 23
PMID 31965462
Citations 2
Authors
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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.

Citing Articles

The pigeon as a machine: Complex category structures can be acquired by a simple associative model.

Turner B, Wasserman E iScience. 2023; 26(10):107998.

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

Pusch R, Packheiser J, Koenen C, Iovine F, Gunturkun O Anim Cogn. 2022; 25(4):793-805.

PMID: 34989909 PMC: 9334434. DOI: 10.1007/s10071-021-01594-1.

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