进化导致了运动检测神经元回路的多样性
Evolution leads to a diversity of motion-detection neuronal circuits
摘要：
进化生物学的一个核心目标是解释生物多样性的起源和分布。除了物种或遗传多样性〈动〉性<动>，我们还观察到复杂功能特征背后的回路（遗传或其他）的多样性。然而，虽然遗传和物种多样性〈动〉性<动>的起源和维持背后的理论已经研究了几十年，但关于不同功能回路起源的理论仍处于起步阶段。目前还不知道有多少不同的电路结构可以实现任何给定的功能，哪些进化因素导致不同的电路，以及特定电路的进化是由于自适应还是非自适应过程。在这里，我们使用数字实验进化来研究数字（人工）大脑中编码运动检测的神经回路的多样性。我们发现，进化导致编码运动检测电路的潜在神经架构的巨大多样性，即使是编码完全相同功能的电路。进化后的电路在冗余度和复杂性方面都有所不同（如以前在遗传电路中发现的那样），这表明类似的进化原理是使用任何基底形成电路的基础。我们还表明，一个简单的（设计）的运动检测电路，是最佳适应增益的复杂性时，进一步发展，并选择突变的鲁棒性导致这种增益的复杂性。
英文摘要：
A central goal of evolutionary biology is to explain the origins and distribution of diversity across life. Beyond species or genetic diversity, we also observe diversity in the circuits (genetic or otherwise) underlying complex functional traits. However, while the theory behind the origins and maintenance of genetic and species diversity has been studied for decades, theory concerning the origin of diverse functional circuits is still in its infancy. It is not known how many different circuit structures can implement any given function, which evolutionary factors lead to different circuits, and whether the evolution of a particular circuit was due to adaptive or non-adaptive processes. Here, we use digital experimental evolution to study the diversity of neural circuits that encode motion detection in digital (artificial) brains. We find that evolution leads to an enormous diversity of potential neural architectures encoding motion detection circuits, even for circuits encoding the exact same function. Evolved circuits vary in both redundancy and complexity (as previously found in genetic circuits) suggesting that similar evolutionary principles underlie circuit formation using any substrate. We also show that a simple (designed) motion detection circuit that is optimally-adapted gains in complexity when evolved further, and that selection for mutational robustness led this gain in complexity.
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