半人工活神经元网络中突触增强诱导的活动模式改变

Masaaki Murata, Hidekatsu Ito, Teppei Taenaka, S. Kudoh
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引用次数: 1

摘要

诸如记忆形成之类的高级脑功能不是由单个神经元的活动完成的,而是由复杂的神经细胞网络的功能完成的。简单的小尺度神经细胞网络完全适合这种神经元之间的相互作用。解离的神经元根据它们的电活动和一周内经常观察到的自发活动形成一个网络。我们在一个有64个微电极的培养皿上培养了一个分离的神经元网络。我们在无Mg2+条件下培养神经网络20分钟,诱导其突触增强。通过将正常细胞外源性溶液交换为无Mg2+记录液来实现无Mg2+状态。在诱导突触增强后,我们采用基于自相关图和基于交叉评分图的方法分析活动模式。神经元活动的自相关图集中,表明周期的准确性提高。这种剧烈的变化仅在20分钟内就发生了。交叉评分图显示,这些网络活动的同步性明显高于无Mg2+条件下的网络活动。这些结果表明,半人工神经网络中的功能连接被改变为具有比以前增强的网络活动的连接。在体内实验中,活动时空模式的改变被认为是记忆的基础。我们在这个半人工的、自主重组的神经元网络中进行了类似的实验。通过对神经网络中这些修改后的功能连接的阐明,我们可以找到如何控制生物记忆形成的线索。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modification of activity pattern induced by synaptic enhancements in a semi-artificial network of living neurons
Higher brain function such as memory formation was not performed by activity of a single neuron but performed by functions of a complex network of neuronal cells. The simple small-scaled network of neuronal cells is fully suitable for such interactions between neurons. Dissociated neurons form a network depending on their electrical activity and spontaneous activity frequently observed within a week. We cultured a network of dissociated neurons on a culture dish with 64 planer microelectrodes. We induced synaptic enhancement in cultured neuronal networks by exposing to Mg2+-free condition for 20 min. Mg2+-free condition was achieved by exchanging of normal cell external solution to Mg2+-free recording solution. After the induction of synaptic enhancement, we analyzed activity pattern by an autocorrelogram-based and crosscorrelogram-based method. Autocorrelogram of the neuronal activity centralized, suggesting that the accuracy of the periodicity increased. This drastic change was induced within only 20 minutes. Crosscorrelogram shows those network activity changed to be more synchronously than one before exposure to Mg2+-free condition. These results suggest that functional connections in a semi-artificial neuronal network were changed to ones performing enhanced network activity than before. The modification of the spatiotemporal pattern of activity is thought to be a base of memory in vivo experiments. We performed similar phenomenon in this semi-artificial, autonomously reorganized network of neurons. By elucidation of these modified functional connections in neural network, we can find a cue how to control biological memory formation.
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