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中枢神经系统中功能几何学元组织的张量网络理论。

Tensor network theory of the metaorganization of functional geometries in the central nervous system.

作者信息

Pellionisz A, Llinás R

出版信息

Neuroscience. 1985 Oct;16(2):245-73. doi: 10.1016/0306-4522(85)90001-6.

DOI:10.1016/0306-4522(85)90001-6
PMID:4080158
Abstract

Here we present an elaboration and a quantitative example for a hypothetical neuronal process, implementing what we refer to as the metaorganization principle. This process allows the internalization of external (body) geometries into the central nervous system (CNS) and a reciprocal and equally important action of the CNS geometry on the external (body) geometry. The hypothesis is based on the distinction, within the CNS, between covariant sensory and contravariant motor vectorial expressions of the extrinsic geometry. These sensory and motor expressions, given in natural co-ordinate systems, are transformed from one to the other by a neuronal network which acts as a metric tensor. The metric tensor determines the relationship of these two expressions and thus comprises the functional geometry of the system. The emergence through metaorganization of networks that implement such metric function is viewed as the result of interactions between the covariant motor execution which generates a physical action on the external world (via the musculoskeletal system) and the covariant sensory proprioception which measures the effect of such motor output. In this transformation of contravariants to covariants by the physical geometry of the motor system, a covariant metric tensor is expressed implicitly. However, co-ordinated motor action requires its dual tensor (the contravariant metric) which is assembled in the CNS based on the metaorganization principle, i.e. the ability of CNS and external geometries to mold one another. The two metric transformations acting on each other detect error signals whenever the match of the physical and functional geometries is imperfect. Such error signals are utilized by the metaorganization process to improve the match between the two metrics, so that with use the internal representation becomes increasingly homeometric with the geometry of the external world. The proposed physical process by which the metaorganization principle is implemented is based on oscillatory reverberation. If covariant proprioception is used as a recurrent signal to the motor apparatus, as if it were a contravariant motor expression, then reverberations at their steady-state yield the eigenvectors and eigenvalues of the system. The stored eigenvectors and eigenvalues can serve, respectively, as a means for the genesis of a metric (in the form of its spectral representation) with the given eigenvectors and as a means of comparing the eigenvalues that are implicit in the external body geometry and those of the internal metric.(ABSTRACT TRUNCATED AT 400 WORDS)

摘要

在此,我们针对一个假设的神经元过程进行阐述并给出一个定量示例,该过程实现了我们所谓的元组织原理。此过程允许将外部(身体)几何形状内化到中枢神经系统(CNS)中,并且CNS几何形状对外部(身体)几何形状具有相互且同等重要的作用。该假设基于中枢神经系统内外部几何形状的协变感觉和逆变运动矢量表达式之间的区别。这些在自然坐标系中给出的感觉和运动表达式,通过一个充当度量张量的神经网络从一种形式转换为另一种形式。度量张量决定了这两种表达式之间的关系,从而构成了系统的功能几何形状。通过实现这种度量功能的网络的元组织而出现的情况,被视为协变运动执行(通过肌肉骨骼系统对外部世界产生物理作用)与协变感觉本体感受(测量这种运动输出的效果)之间相互作用的结果。在运动系统的物理几何形状将逆变转换为协变的过程中,一个协变度量张量被隐含地表达出来。然而,协调的运动动作需要其对偶张量(逆变度量),它是基于元组织原理在中枢神经系统中组装而成的,即中枢神经系统和外部几何形状相互塑造的能力。每当物理几何形状和功能几何形状的匹配不完美时,相互作用的这两种度量变换就会检测到误差信号。元组织过程利用这些误差信号来改善两种度量之间的匹配,以便随着使用,内部表征与外部世界的几何形状越来越趋于等距。所提出的实现元组织原理的物理过程基于振荡回响。如果将协变本体感受用作向运动装置的循环信号,就好像它是一个逆变运动表达式,那么在其稳态下的回响会产生系统的特征向量和特征值。所存储的特征向量和特征值可以分别作为生成具有给定特征向量的度量(以其谱表示的形式)的一种手段,以及作为比较隐含在外部身体几何形状中的特征值和内部度量的特征值的一种手段。(摘要截断于400字)

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