Spontaneous representation of numerosity zero in a deep neural network for visual object recognition

Summary: Conceiving “nothing” as a numerical value zero is considered a sophisticated numerical capability that humans share with cognitively advanced animals. We demonstrate that representation of zero spontaneously emerges in a deep learning neural network without any number training. As a signatu...

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Auteurs principaux:	Khaled Nasr, Andreas Nieder
Format:	article
Langue:	EN
Publié:	Elsevier 2021
Sujets:	Biological sciences Neuroscience Sensory neuroscience Machine learning Science Q
Accès en ligne:	https://doaj.org/article/bf057a05c0f849e09117dac907aca694
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spelling	oai:doaj.org-article:bf057a05c0f849e09117dac907aca6942021-11-20T05:09:38ZSpontaneous representation of numerosity zero in a deep neural network for visual object recognition2589-004210.1016/j.isci.2021.103301https://doaj.org/article/bf057a05c0f849e09117dac907aca6942021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2589004221012700https://doaj.org/toc/2589-0042Summary: Conceiving “nothing” as a numerical value zero is considered a sophisticated numerical capability that humans share with cognitively advanced animals. We demonstrate that representation of zero spontaneously emerges in a deep learning neural network without any number training. As a signature of numerical quantity representation, and similar to real neurons from animals, numerosity zero network units show maximum activity to empty sets and a gradual decrease in activity with increasing countable numerosities. This indicates that the network spontaneously ordered numerosity zero as the smallest numerical value along the number line. Removal of empty-set network units caused specific deficits in the network's judgment of numerosity zero, thus reflecting these units' functional relevance. These findings suggest that processing visual information is sufficient for a visual number sense that includes zero to emerge and explains why cognitively advanced animals with whom we share a nonverbal number system exhibit rudiments of numerosity zero.Khaled NasrAndreas NiederElsevierarticleBiological sciencesNeuroscienceSensory neuroscienceMachine learningScienceQENiScience, Vol 24, Iss 11, Pp 103301- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biological sciences Neuroscience Sensory neuroscience Machine learning Science Q
spellingShingle	Biological sciences Neuroscience Sensory neuroscience Machine learning Science Q Khaled Nasr Andreas Nieder Spontaneous representation of numerosity zero in a deep neural network for visual object recognition
description	Summary: Conceiving “nothing” as a numerical value zero is considered a sophisticated numerical capability that humans share with cognitively advanced animals. We demonstrate that representation of zero spontaneously emerges in a deep learning neural network without any number training. As a signature of numerical quantity representation, and similar to real neurons from animals, numerosity zero network units show maximum activity to empty sets and a gradual decrease in activity with increasing countable numerosities. This indicates that the network spontaneously ordered numerosity zero as the smallest numerical value along the number line. Removal of empty-set network units caused specific deficits in the network's judgment of numerosity zero, thus reflecting these units' functional relevance. These findings suggest that processing visual information is sufficient for a visual number sense that includes zero to emerge and explains why cognitively advanced animals with whom we share a nonverbal number system exhibit rudiments of numerosity zero.
format	article
author	Khaled Nasr Andreas Nieder
author_facet	Khaled Nasr Andreas Nieder
author_sort	Khaled Nasr
title	Spontaneous representation of numerosity zero in a deep neural network for visual object recognition
title_short	Spontaneous representation of numerosity zero in a deep neural network for visual object recognition
title_full	Spontaneous representation of numerosity zero in a deep neural network for visual object recognition
title_fullStr	Spontaneous representation of numerosity zero in a deep neural network for visual object recognition
title_full_unstemmed	Spontaneous representation of numerosity zero in a deep neural network for visual object recognition
title_sort	spontaneous representation of numerosity zero in a deep neural network for visual object recognition
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/bf057a05c0f849e09117dac907aca694
work_keys_str_mv	AT khalednasr spontaneousrepresentationofnumerosityzeroinadeepneuralnetworkforvisualobjectrecognition AT andreasnieder spontaneousrepresentationofnumerosityzeroinadeepneuralnetworkforvisualobjectrecognition
_version_	1718419564311609344

Spontaneous representation of numerosity zero in a deep neural network for visual object recognition

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