Universität zu Köln

Rapp, Hannes, Nawrot, Martin Paul ORCID: 0000-0003-4133-6419 and Stern, Merav (2020). Numerical Cognition Based on Precise Counting with a Single Spiking Neuron. iScience, 23 (2). CAMBRIDGE: CELL PRESS. ISSN 2589-0042

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Abstract

Insects are able to solve basic numerical cognition tasks. We show that estimation of numerosity can be realized and learned by a single spiking neuron with an appropriate synaptic plasticity rule. This model can be efficiently trained to detect arbitrary spatiotemporal spike patterns on a noisy and dynamic background with high precision and low variance. When put to test in a task that requires counting of visual concepts in a static image it required considerably less training epochs than a convolutional neural network to achieve equal performance. When mimicking a behavioral task in free-flying bees that requires numerical cognition, the model reaches a similar success rate in making correct decisions. We propose that using action potentials to represent basic numerical concepts with a single spiking neuron is beneficial for organisms with small brains and limited neuronal resources.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Rapp, Hannes UNSPECIFIED UNSPECIFIED UNSPECIFIED Nawrot, Martin Paul UNSPECIFIED orcid.org/0000-0003-4133-6419 UNSPECIFIED Stern, Merav UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-344244
DOI:	10.1016/j.isci.2020.100852
Journal or Publication Title:	iScience
Volume:	23
Number:	2
Date:	2020
Publisher:	CELL PRESS
Place of Publication:	CAMBRIDGE
ISSN:	2589-0042
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language Multidisciplinary Sciences Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/34424