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

ABSTRACT: 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

SUBMITTER: Clemens J 

PROVIDER: S-EPMC8635984 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature