Structural and functional properties of a probabilistic model of neuronal connectivity in a simple locomotor network.
Structural and functional properties of a probabilistic model of neuronal connectivity in a simple locomotor network.
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DOI：
10.7554/elife.33281
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发表时间：
2018-03-28
期刊：
影响因子：
7.7
通讯作者：
Borisyuk R
中科院分区：
文献类型：
--
作者：
Ferrario A;Merrison-Hort R;Soffe SR;Borisyuk R
尽管在大多数动物中，个体之间的大脑连接是不同的，但同一物种的行为往往是相似的。定义这种行为的各个网络共有哪些基本结构属性？我们描述了蝌蚪爪幼仔脊髓连通性的概率模型，当与尖刺模型相结合时，可靠地产生与游泳相对应的节律性活动。概率模型允许计算反映共同网络属性的结构特征，独立于单个网络实现。我们使用结构特征来研究神经元动力学的例子，在完整的网络和各种子网络中，这使我们能够解释关键实验发现的基础，并为实验做出预测。我们还研究了详细解剖连接体与我们新的、更简单的模型（元模型）生成的连接体之间的结构和功能特征的差异。
Although, in most animals, brain connectivity varies between individuals, behaviour is often similar across a species. What fundamental structural properties are shared across individual networks that define this behaviour? We describe a probabilistic model of connectivity in the hatchling Xenopus tadpole spinal cord which, when combined with a spiking model, reliably produces rhythmic activity corresponding to swimming. The probabilistic model allows calculation of structural characteristics that reflect common network properties, independent of individual network realisations. We use the structural characteristics to study examples of neuronal dynamics, in the complete network and various sub-networks, and this allows us to explain the basis for key experimental findings, and make predictions for experiments. We also study how structural and functional features differ between detailed anatomical connectomes and those generated by our new, simpler, model (meta-model).