Conscious percept formation using fuzzy entropy measures of neuronal multiplex signals

C. Helgason, T. Jobe
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Abstract

One goal of automation is to mimic the smoothness and efficiency of human performance. Fuzzy logic based soft computing and engineering works towards this goal. The obvious difference between machines and humans is that of life. If one could understand the method by which human perception and motor response takes place one might conceive of a means to automate these capabilities. The anatomy and physiology of the living nervous system are notable in this respect. In the mammalian brain, the pyramidal neuron of the cerebral cortex plays a key role in perception. Pyramidal cell axons exhibit clusters of action potentials that form a multiplex code allowing multiple parallel patterns of information to travel in the same time frame along that axon. Selective decoding at different target locations within the central nervous system then takes place. We propose that the anatomy of the cerebral cortex and pyramidal neuron is uniquely suited to distribute a multiplex signal, and that this property then provides the basis for a common code for perceptual and motor representations. Thinking of the anatomy in terms of geometry, we are able to predict the increase in length of the apical dendrites of pyramidal neurons from cortical layers 2 to 6 on the basis of a property of the doubled fuzzy hypercube (unit square). A decrease in fuzzy entropy of incoming signals takes place as engrams and new signals arrive bband are passed down through these layers to pyramidal cell layer 5. Perceptions and motor action plans are separated out by demultiplexing so that conscious percepts are executed by the thalamoreticular system and corresponding motor plans by the corticospinal tract. This is possible because of differential demultiplexing mediated by inhibitory gabaergic neurons of the same multiplex signal at the relevant target areas. The important feature of this process is its plasticity, due to synaptopoeisis which is a continuous remodeling process of synaptic location.
利用神经元多路信号的模糊熵测度形成意识知觉
自动化的一个目标是模仿人类工作的流畅性和效率。基于模糊逻辑的软计算和工程正朝着这个目标努力。机器和人类之间最明显的区别就是生命。如果人们能够理解人类感知和运动反应发生的方法,人们可能会想到一种使这些能力自动化的方法。活体神经系统的解剖学和生理学在这方面是值得注意的。在哺乳动物的大脑中,大脑皮层的锥体神经元在感知中起着关键作用。锥体细胞轴突表现出动作电位簇,形成一个多重编码,允许多个平行的信息模式在同一时间框架内沿着轴突传播。然后在中枢神经系统的不同目标位置进行选择性解码。我们提出,大脑皮层和锥体神经元的解剖结构是唯一适合分配多路信号的,并且这种特性随后为感知和运动表征提供了共同代码的基础。从几何学的角度考虑解剖学,我们能够根据双重模糊超立方体(单位平方)的性质预测锥体神经元从皮质层2到6的顶端树突长度的增加。当印痕和新到达带的信号通过这些层向下传递到锥体细胞层5时,传入信号的模糊熵就会减少。知觉和运动行动计划通过解复用分离开来,因此有意识的知觉由丘脑系统执行,相应的运动计划由皮质脊髓束执行。这是可能的,因为抑制性gabaergy神经元在相关靶区介导的相同复用信号的差异解复用。这个过程的重要特征是它的可塑性,这是由于突触形成,这是一个持续的突触位置重塑过程。
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