The free energy principle induces neuromorphic development

C. Fields, K. Friston, J. Glazebrook, Michael Levin, A. Marcianò
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引用次数: 9

Abstract

We show how any finite physical system with morphological, i.e. three-dimensional embedding or shape, degrees of freedom and locally limited free energy will, under the constraints of the free energy principle, evolve over time towards a neuromorphic morphology that supports hierarchical computations in which each ‘level’ of the hierarchy enacts a coarse-graining of its inputs, and dually, a fine-graining of its outputs. Such hierarchies occur throughout biology, from the architectures of intracellular signal transduction pathways to the large-scale organization of perception and action cycles in the mammalian brain. The close formal connections between cone-cocone diagrams (CCCD) as models of quantum reference frames on the one hand, and between CCCDs and topological quantum field theories on the other, allow the representation of such computations in the fully-general quantum-computational framework of topological quantum neural networks.
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自由能原理诱导神经形态发育
我们展示了任何具有形态,即三维嵌入或形状,自由度和局部有限自由能的有限物理系统将如何在自由能原理的约束下,随着时间的推移演变成支持分层计算的神经形态形态,其中分层的每个“级别”制定了其输入的粗粒度,以及其输出的细粒度。从细胞内信号转导途径的结构到哺乳动物大脑中感知和行动周期的大规模组织,这种层次结构在整个生物学中都存在。锥-圆锥图(CCCD)作为量子参考系模型之间的密切形式联系,以及CCCD与拓扑量子场论之间的密切形式联系,允许在拓扑量子神经网络的完整一般量子计算框架中表示此类计算。
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