Self-organization of non-random mono-synaptic networks in cultured neurons
作者单位：Lab of Synaptic Development and PlasticityInstitute of NeuroscienceShanghai Institutes of Biological SciencesChinese Academy of Sciences Lab of Synaptic Development and PlasticityInstitute of NeuroscienceMedical School of Zhejiang University
会议名称：《中国神经科学学会第十届全国学术会议》
会议日期：2013年
学科分类：1001[医学-基础医学(可授医学、理学学位)] 10[医学]
关 键 词：neural network cultured neural network self-organize complex network non-random early development
摘 要：The comprehension and analysis of the complexity of neural networks are fundamental to our understanding of the dynamics and cognitive functions of the *** from cellular level to the whole brain have proved that structural connections in both micro- and macro-scale neural networks are not random but exhibit many complex-network ***,the conditions and mechanisms underlying the development of these non-random structural features,as well as their biological significances,are still not *** answers to these questions could benefit from a direct study of the non-random network features in early-developing neural *** this study,we cultured mice hippocampal neurons in vitro,and investigated non-random structural features in developing neural circuits independent of anatomical brain structures and behavioral *** multi-channel whole cell patch recordings and GAD-GFP transgenic mice whose GABAergic neurons are tagged by fluorescence,we were able to distinguish and detect both glutamatergic and GABAergic mono-synapse,and record *** found that,cultured neurons self-organized into non-random mono-synaptic neural networks that exhibited complex network features which were also found in neural networks in the brain but not in randomly connected *** example,the numbers of certain network motifs,as well as the numbers of neurons with multiple output connections exceeded expectations;synaptic connections clustered in local neuronal subgroups;synaptic weights positively correlated to the numbers of GABA connections in local *** on these findings,we proposed a rule that is capable of explaining the self-organizations of complex neural networks during early development:the probability of synapse formation between a pair of neurons depends on neuron types,and is negatively correlated to the distance between the neurons and positively correlated to the number of outgoing connections already formed on