论文标题
网络级联计算的自发出现
Spontaneous Emergence of Computation in Network Cascades
论文作者
论文摘要
雪崩支持网络的神经元网络计算和计算对物理学，计算机科学（计算理论以及统计或机器学习）和神经科学感兴趣。在这里，我们表明，复杂布尔函数的计算是在阈值网络中自发产生的，该函数是连通性和对抗（抑制）的函数，该函数由逻辑自动机（Motifs）以计算级联的形式计算出来。我们解释了基序的计算复杂性与由于基序引起的函数概率及其与函数空间中对称性的关系之间的紧急反向关系。我们还表明，此处观察到的最佳抑制部分支持与最佳信息处理有关的计算神经科学的结果。
Neuronal network computation and computation by avalanche supporting networks are of interest to the fields of physics, computer science (computation theory as well as statistical or machine learning) and neuroscience. Here we show that computation of complex Boolean functions arises spontaneously in threshold networks as a function of connectivity and antagonism (inhibition), computed by logic automata (motifs) in the form of computational cascades. We explain the emergent inverse relationship between the computational complexity of the motifs and their rank-ordering by function probabilities due to motifs, and its relationship to symmetry in function space. We also show that the optimal fraction of inhibition observed here supports results in computational neuroscience, relating to optimal information processing.
