The Physical Design of Biological Systems - Insights from the Fly Brain

L. Scheffer
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引用次数: 2

Abstract

Many different physical substrates can support complex computation. This is particularly apparent when considering human made and biological systems that perform similar functions, such as visually guided navigation. In common, however, is the need for good physical design, as such designs are smaller, faster, lighter, and lower power, factors in both the jungle and the marketplace. Although the physical design of man-made systems is relatively well understood, the physical design of biological computation has remained murky due to a lack of detailed information on their construction. The recent EM (electron microscope) reconstruction of the central brain of the fruit fly now allows us to start to examine these issues. Here we look at the physical design of the fly brain, including such factors as fan-in and fanout, logic depth, division into physical compartments and how this affects electrical response, pin to computation ratios (Rent's rule), and other physical characteristics of at least one biological computation substrate. From this we speculate on how physical design algorithms might change if the target implementation was a biological neural network.
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生物系统的物理设计——来自苍蝇大脑的见解
许多不同的物理基底可以支持复杂的计算。当考虑到执行类似功能的人造系统和生物系统时,这一点尤其明显,例如视觉引导导航。然而,共同点是需要良好的物理设计,因为这样的设计更小、更快、更轻、更低功耗,这是丛林和市场的因素。虽然人造系统的物理设计相对来说已经被很好地理解了,但由于缺乏有关其结构的详细信息,生物计算的物理设计仍然模糊不清。最近对果蝇中央大脑的电子显微镜重建使我们能够开始研究这些问题。在这里,我们看看苍蝇大脑的物理设计,包括诸如扇入和扇出,逻辑深度,划分到物理隔间以及这如何影响电响应,引脚计算比率(Rent’s rule),以及至少一种生物计算基板的其他物理特征。由此,我们推测如果目标实现是生物神经网络,物理设计算法可能会如何变化。
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