A small, computationally flexible network produces the phenotypic diversity of song recognition in crickets.
A small, computationally flexible network produces the phenotypic diversity of song recognition in crickets.
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DOI：
10.7554/elife.61475
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发表时间：
2021-11-11
期刊：
影响因子：
7.7
通讯作者：
Hedwig B
中科院分区：
文献类型：
--
作者：
Clemens J;Schöneich S;Kostarakos K;Hennig RM;Hedwig B
神经网络是如何进化来产生物种特定通信信号的多样性的，这一点尚不清楚。对于信号的接收者，一种假设是新的识别表型产生于计算灵活的特征检测网络中的参数变化。我们在蟋蟀身上测试了这一假设，通过调查蟋蟀大脑中的歌曲识别网络是否具有识别不同时间特征的计算灵活性，在蟋蟀中，雄性产生交配歌曲，雌性通过特定物种的脉冲模式识别交配歌曲。使用从网络中识别短时间尺度上脉冲模式的关键属性的电生理记录，我们建立了一个计算模型，再现了该物种的神经元和行为调节。对模型参数空间的分析表明，该网络可以提供蟋蟀甚至其他昆虫中已知的脉冲持续时间和停顿的所有识别表型。该模型中的表型多样性与蟋蟀和其他昆虫的已知偏好类型是一致的，并源于可能为提高模式识别的能效和稳健性而进化的计算。该模型的表型映射参数是退化的--不同的网络参数可以在表型中产生类似的变化--这可能支持进化可塑性。我们的研究表明，计算灵活的网络是不同模式识别表型的基础，我们揭示了限制和支持行为多样性的网络属性。
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.
DOI：
10.1007/s00359-020-01448-0
发表时间：
2020-11
期刊：
Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology
影响因子：
--
作者：
Jacob PF;Hedwig B
通讯作者：
Hedwig B