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Resonant song recognition and the evolution of acoustic communication in crickets
Winston Mann1, Bettina Erregger2, Ralf Matthias Hennig3
1ENI-G, a Joint Initiative of the University Medical Center Göttingen and the Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany.
Abstract:
Cricket song recognition is thought to evolve through modifications of a shared neural network. However, the species Anurogryllus muticus has an unusual recognition pattern that challenges this view: females respond to both normal male song pulse periods and periods twice as long. Of the three minimal models tested, only a single-neuron model with an oscillating membrane could explain this unusual behavior. A minimal model of the cricket's song network reproduced the behavior after adding a mechanism that, while present in the full network, is not crucial for song recognition in other species. This shows how a shared neural network can produce diverse behaviors and highlights how different computations contribute to evolution. Our results also demonstrate how nonlinear computations can lead to rapid behavioral changes during evolution because small changes in network parameters can lead to large changes in behavior.
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