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