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编码、运算、测量与神经网络。

Codes, operations, measurements and neural networks.

作者信息

Lábos E

机构信息

United Research Organization of Hungarian Academy of Sciences and Semmelweis Medical University, Budapest.

出版信息

Biosystems. 2000 Oct-Dec;58(1-3):9-18. doi: 10.1016/s0303-2647(00)00101-5.

Abstract

Numerous neural codes and primary neural operations (logical and arithmetical ones, mappings, transformations) were listed [e.g. Perkel, D., Bullock, T.H., 1968. Neurosci. Res. Program Bull 6, 221-348] during the past decades. None of them is ubiquitous or universal. In reality neural operations take place in continuous time and working with unreliable elements, but they still can be simulated with synchronized discrete time scales and chaotic models. Here, a possible neural mechanism, called 'measure like' code is introduced and examined. The neurons are regarded as measuring devices, dealing with 'measures', more or less in mathematical sense. The subadditivity--eminent property of measures--may be implemented with neuronal refractoriness and such synapses operate like particle counters with dead time. This hypothetical code is neither ubiquitous, nor universal, e.g. temporal summation (multiplication) causes just the opposite phenomenon, the supra-additivity also with respect to the number of spikes (anti-measures). This is a cause of more difficult neural implementation of OR gate, than that of the AND. Possibilities for transitional mechanisms (e.g. between traditional logical gates, etc.) are stressed here. Parameter tuning might change either code or operation.

摘要

在过去几十年里,人们列出了许多神经编码和主要神经操作(逻辑和算术操作、映射、变换)[例如,Perkel, D., Bullock, T.H., 1968. Neurosci. Res. Program Bull 6, 221 - 348]。但它们都不是普遍存在或通用的。实际上,神经操作是在连续时间内进行的,并且涉及不可靠的元件,但仍可以用同步离散时间尺度和混沌模型来模拟。在这里,我们引入并研究了一种可能的神经机制,称为“类似测量”编码。神经元被视为测量装置,或多或少在数学意义上处理“测量值”。次可加性——测量的显著特性——可以通过神经元不应期来实现,并且这样的突触就像具有死区时间的粒子计数器一样工作。这种假设的编码既不是普遍存在的,也不是通用的,例如,时间总和(乘法)会导致相反的现象,即关于尖峰数量的超可加性(反测量)。这就是“或”门的神经实现比“与”门更困难的原因。这里强调了过渡机制(例如在传统逻辑门之间等)的可能性。参数调整可能会改变编码或操作。

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