Neuronal membrane and synapse polarities have been attracting considerable interest in recent years. Certain functional roles for such polarities have been suggested, yet, they have largely remained a subject for speculation and debate. Here, we note that neural circuit polarity codes, defined as sets of polarity permutations, divide into primal-size circuit polarity subcodes, which, sharing certain connectivity attributes, are called categories. Two long-debated, seemingly competing paradigms of neuronal self-feedback, namely, axonal discharge and synaptic mediation, are shown to jointly define the distinction between these categories. However, as the second paradigm contains the first, it is mathematically sufficient for complete specification of all categories. The analysis of primal-size circuit polarity categories is found to reveal, explain and extend experimentally observed cortical information capacity values termed “magical numbers”, associated with “working memory”. While these have been previously argued on grounds of psychological experiments, here they are further supported on analytic grounds by the so-called Hebbian memory paradigm. The information dimensionality associated with these capacities is found to be a consequence of prime factorization of composite circuit polarity code sizes. Different categories of circuit polarity, identical in size and neuronal parameters, are shown to generate different firing rate dynamics.

中文翻译：

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神经极性代码的原始类别

近年来，神经元膜和突触的极性引起了极大的兴趣。已经提出了这种极性的某些功能角色，但是，它们在很大程度上仍然是猜测和辩论的主题。在这里，我们注意到神经电路极性代码（定义为极性置换集）分为原始大小的电路极性子代码，这些子代码共享某些连通性属性，称为类别。神经元自我反馈的两个长期争论的，看似竞争的范式，即轴突放电和突触调解，共同定义了这些类别之间的区别。但是，由于第二个范例包含第一个范例，因此在数学上足以完整说明所有类别。发现对原始电路极性类别的分析可以揭示，解释和扩展实验观察到的皮层信息容量值，称为“幻数”，与“工作记忆”相关。尽管以前已经基于心理学实验对这些进行了争论，但是在这里，它们被所谓的“希伯来记忆范式”以分析为基础得到了进一步的支持。发现与这些容量相关的信息维数是复合电路极性代码大小的素因分解的结果。显示出不同类别的电路极性，大小和神经元参数相同，从而产生不同的放电速率动态。