Experimental observations of simultaneous activity in large cortical areas have seemed to justify a large network approach in early studies of neural information codes and memory capacity. This approach has overlooked, however, the segregated nature of cortical structure and functionality. Employing graph-theoretic results, we show that, given the estimated number of neurons in the human brain, there are only a few primal sizes that can be attributed to neural circuits under probabilistically sparse connectivity. The significance of this finding is that neural circuits of relatively small primal sizes in cyclic interaction, implied by inhibitory interneuron potentiation and excitatory inter-circuit potentiation, generate relatively long non-repetitious sequences of asynchronous primal-length periods. The meta-periodic nature of such circuit interaction translates into meta-periodic firing-rate dynamics, representing cortical information. It is finally shown that interacting neural circuits of primal sizes 7 or less exhaust most of the capacity of the human brain, with relatively little room to spare for circuits of larger primal sizes. This also appears to ratify experimental findings on the human working memory capacity.

在大皮层区域同时活动的实验观察似乎证明了在神经信息代码和记忆容量的早期研究中采用大型网络方法是合理的。然而，这种方法忽略了皮质结构和功能的分离性质。使用图论结果，我们表明，给定人脑中神经元的估计数量，只有少数原始大小可以归因于概率稀疏连接下的神经回路。这一发现的意义在于，在循环相互作用中原始尺寸相对较小的神经回路，由抑制性中间神经元增强和兴奋性回路间增强所暗示，产生相对较长的非重复异步原始长度周期序列。这种电路交互的元周期性质转化为元周期放电率动力学，代表皮层信息。最终表明，原始大小为 7 或更小的交互神经回路耗尽了人脑的大部分容量，而为更大原始大小的回路留出的空间相对较小。这似乎也证实了关于人类工作记忆能力的实验结果。