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The Evolution of Variability and Robustness in Neural Development

机译:神经发展变异性和鲁棒性的演变

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As in all biological systems, neurons and their networks must balance precision with variability. Phenotypic precision and phenotypic variability can both occur with remarkable robustness, where robustness is defined as the ability to tolerate perturbation. Variability in genotype–phenotype mapping produces phenotypic variability despite identical genetic information. The resulting variability among genetically identical neurons can contribute to the robustness of brain development. Similarly, variability of genetically identical individuals can contribute to evolutionary robustness. We discuss here shared principles of developmental robustness and evolutionary robustness, and highlight scenarios where such principles result in neural networks that achieve robustness of precision or variability.
机译:与所有生物系统一样,神经元及其网络必须平衡具有可变性的精度。 表型精确和表型变异性可以以显着的鲁棒性发生,其中鲁棒性被定义为耐受扰动的能力。 尽管相同的遗传信息,基因型 - 表型映射的变异性产生表型可变性。 产生的遗传相同神经元之间的可变性可以有助于脑发育的鲁棒性。 类似地,遗传上相同的个体的可变性可以有助于进化的鲁棒性。 我们讨论了发育稳健性和进化稳健性的共同原则,并突出了这种原则导致神经网络的方案,实现精度或可变性的稳健性。

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