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中文核心期刊

神经能量与神经信息之间内在动力学关系初探

THE FIRST EXPLORATION OF THE DYNAMIC RELATION BETWEEN NERVOUS ENERGY AND NEURAL INFORMATION

  • 摘要: 根据信息论的基本原理和方法,运用最小互信息和最大熵原理对神经编码进行研究和分析.通过对两个原理的基本介绍,描述了最小互信息和最大熵原理是如何用于评估神经反应中的信息量.研究结果表明神经信息的表达和神经能量的利用率密切相关,并发现高度进化的神经系统在能量的消耗和利用上严格遵循着经济性和高效性两个基本原则.为了验证神经信息处理与能量利用率的关系,提出了信能比的新概念,用于衡量最大熵原理对应神经系统在能量利用率上的经济性和高效性.并通过数值计算证实了一个猜想,即神经系统所消耗的能量反映了神经信息处理的内在规律,这为进一步研究一种崭新的神经信息处理原理——能量神经编码奠定了重要的理论基础.

     

    Abstract: In accordance with the basic principles and methods of Information Theory,this article proposes to research and analyze neural coding by using the minimum mutual information principle and the maximum entropy principle.In this paper,firstly,we elaborate their basic principles.Next,we highlight how the minimum mutual information and maximum entropy principle are used to measure the information in neural responses.Studies show that neural information expression and energy utilization rate are closely related,and the fact that highly evolved nervous system on energy consumption is strictly compliance with the two basic principles-economy and efficiency.In order to verify the relation between the neural information processing and energy utilization,this paper put forward a new concept used to measure the efficiency on energy utilization when the neural system follows the maximum entropy principles.Finally,we demonstrate a conjecture that the consumed energy in nervous system reflects the inherent law of neural information energy through the numeric calculation.It lays an important foundation for the further study of a new neural information processing principle—energy neural coding.

     

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