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

iScience

Andreas Nieder¹  Khaled Nasr¹ 

[1] Animal Physiology Unit, Institute of Neurobiology, Auf der Morgenstelle 28, University of Tübingen, 72076 Tübingen, Germany;

关键词: Biological sciences;    Neuroscience;    Sensory neuroscience;    Machine learning;   

DOI  :  

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown