A small, computationally flexible network produces the phenotypic diversity of song recognition in crickets

How neural networks evolved to generate the diversity of species-specific communication signals is unknown. For receivers of the signals, one hypothesis is that novel recognition phenotypes arise from parameter variation in computationally flexible feature detection networks. We test this hypothesis...

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Autores principales:	Jan Clemens, Stefan Schöneich, Konstantinos Kostarakos, R Matthias Hennig, Berthold Hedwig
Formato:	article
Lenguaje:	EN
Publicado:	eLife Sciences Publications Ltd 2021
Materias:	cricket Gryllus bimaculatus acoustic communication mating signals evolution neural networks Medicine R Science Q Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/90491ad66bec4ba99c01a0aad8ca2281
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spelling	oai:doaj.org-article:90491ad66bec4ba99c01a0aad8ca22812021-12-01T12:52:26ZA small, computationally flexible network produces the phenotypic diversity of song recognition in crickets10.7554/eLife.614752050-084Xe61475https://doaj.org/article/90491ad66bec4ba99c01a0aad8ca22812021-11-01T00:00:00Zhttps://elifesciences.org/articles/61475https://doaj.org/toc/2050-084XHow neural networks evolved to generate the diversity of species-specific communication signals is unknown. For receivers of the signals, one hypothesis is that novel recognition phenotypes arise from parameter variation in computationally flexible feature detection networks. We test this hypothesis in crickets, where males generate and females recognize the mating songs with a species-specific pulse pattern, by investigating whether the song recognition network in the cricket brain has the computational flexibility to recognize different temporal features. Using electrophysiological recordings from the network that recognizes crucial properties of the pulse pattern on the short timescale in the cricket Gryllus bimaculatus, we built a computational model that reproduces the neuronal and behavioral tuning of that species. An analysis of the model’s parameter space reveals that the network can provide all recognition phenotypes for pulse duration and pause known in crickets and even other insects. Phenotypic diversity in the model is consistent with known preference types in crickets and other insects, and arises from computations that likely evolved to increase energy efficiency and robustness of pattern recognition. The model’s parameter to phenotype mapping is degenerate – different network parameters can create similar changes in the phenotype – which likely supports evolutionary plasticity. Our study suggests that computationally flexible networks underlie the diverse pattern recognition phenotypes, and we reveal network properties that constrain and support behavioral diversity.Jan ClemensStefan SchöneichKonstantinos KostarakosR Matthias HennigBerthold HedwigeLife Sciences Publications LtdarticlecricketGryllus bimaculatusacoustic communicationmating signalsevolutionneural networksMedicineRScienceQBiology (General)QH301-705.5ENeLife, Vol 10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	cricket Gryllus bimaculatus acoustic communication mating signals evolution neural networks Medicine R Science Q Biology (General) QH301-705.5
spellingShingle	cricket Gryllus bimaculatus acoustic communication mating signals evolution neural networks Medicine R Science Q Biology (General) QH301-705.5 Jan Clemens Stefan Schöneich Konstantinos Kostarakos R Matthias Hennig Berthold Hedwig A small, computationally flexible network produces the phenotypic diversity of song recognition in crickets
description	How neural networks evolved to generate the diversity of species-specific communication signals is unknown. For receivers of the signals, one hypothesis is that novel recognition phenotypes arise from parameter variation in computationally flexible feature detection networks. We test this hypothesis in crickets, where males generate and females recognize the mating songs with a species-specific pulse pattern, by investigating whether the song recognition network in the cricket brain has the computational flexibility to recognize different temporal features. Using electrophysiological recordings from the network that recognizes crucial properties of the pulse pattern on the short timescale in the cricket Gryllus bimaculatus, we built a computational model that reproduces the neuronal and behavioral tuning of that species. An analysis of the model’s parameter space reveals that the network can provide all recognition phenotypes for pulse duration and pause known in crickets and even other insects. Phenotypic diversity in the model is consistent with known preference types in crickets and other insects, and arises from computations that likely evolved to increase energy efficiency and robustness of pattern recognition. The model’s parameter to phenotype mapping is degenerate – different network parameters can create similar changes in the phenotype – which likely supports evolutionary plasticity. Our study suggests that computationally flexible networks underlie the diverse pattern recognition phenotypes, and we reveal network properties that constrain and support behavioral diversity.
format	article
author	Jan Clemens Stefan Schöneich Konstantinos Kostarakos R Matthias Hennig Berthold Hedwig
author_facet	Jan Clemens Stefan Schöneich Konstantinos Kostarakos R Matthias Hennig Berthold Hedwig
author_sort	Jan Clemens
title	A small, computationally flexible network produces the phenotypic diversity of song recognition in crickets
title_short	A small, computationally flexible network produces the phenotypic diversity of song recognition in crickets
title_full	A small, computationally flexible network produces the phenotypic diversity of song recognition in crickets
title_fullStr	A small, computationally flexible network produces the phenotypic diversity of song recognition in crickets
title_full_unstemmed	A small, computationally flexible network produces the phenotypic diversity of song recognition in crickets
title_sort	small, computationally flexible network produces the phenotypic diversity of song recognition in crickets
publisher	eLife Sciences Publications Ltd
publishDate	2021
url	https://doaj.org/article/90491ad66bec4ba99c01a0aad8ca2281
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A small, computationally flexible network produces the phenotypic diversity of song recognition in crickets

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