Self-Organization of Polymorphic Circuits in Cultured Neural Networks

一般来说，感觉和运动系统中的解剖神经网络有助于信息处理的各种功能。这就是所谓的“多态”网络概念。多态网络是一种嵌入有多个电路的网络，这些电路由神经元之间的功能相互作用定义。对于理解大脑的功能，如感觉知觉，运动控制，学习或记忆，这是非常重要的，以澄清新兴的原则，多态电路。在本研究中，我们对多态电路的自组织进行了生理学和模型化研究，得到了以下结果.使用KYS振荡器作为神经元，我们模拟了运动系统的中央模式发生器（CPG）。CPG的多态性可以通过控制抑制后反弹和静息膜电位等神经特性而表现出来，而不改变突触的连接性.用细胞外液灌流生物源单胺，蛞蝓中枢神经系统的嗅觉网络呈现多态性。这表明单胺在生物感觉网络的多态性中起着重要作用.在生物系统中，单胺通过细胞内Ca^<++>改变内在神经特性。因此，我们用计算机模拟的方法研究了细胞内Ca^<++>的网络动力学，并证明了在不同的外界条件下，网络中的Ca^<++>模式会出现全局性的变化，这些结果揭示了生物网络中多态性是如何控制的，并可能为神经网络的运行规律提供新的认识。

In general, an anatomical neural network in sensory and motor systems subserves various functions of information processing. This is so-called "polymorphic" network concept. A polymorphic network is a network embedded with multiple circuits which are defined by functional interactions between neurons. For undersatanding the function of the brain such as sensory perception, motor control, learning or memory, it is very important to clarify emerging principles of the polymorphic circuits. In this research, we have made physiological and modeling studies about the self-organization of the polymorphic circuits, and obtained following results.1. Using a KYS oscillator as a neural element, we modeled a central pattern generator (CPG) of the motor system. The polymorphic property of the CPG could be emerged by controlling intrinsic neural property such as postinhibitory rebound and resting membrane potential, without changing synaptic connectivity.2. Isolated olfactory network of slug's CNS showed polymorphic property by perfusing biogenic monoamines in extracellular solution. This suggested that monoamines play important roles in emerging the polymorphic property of a biological sensory networks.3. In biological systems, monoamines change intrinsic neural properties through the intracellular Ca^<++>. Therefore we studied a network-dynamics of the intracellular Ca^<++> with computational simulation, and demonstrated that global Ca^<++> patterns in a network could be emerged according to various external conditions.These results suggest how the polymorphic property is controlled in biological network, and might provide a new insight into rules for neural network operation.