Maximization of the connectivity repertoire as a statistical principle governing the shapes of dendritic arbors
Maximization of the connectivity repertoire as a statistical principle governing the shapes of dendritic arbors
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DOI：
10.1073/pnas.0901530106
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发表时间：
2009-07-28
影响因子：
11.1
通讯作者：
Chklovskii, Dmitri B.
中科院分区：
文献类型：
--
作者：
Wen, Quan;Stepanyants, Armen;Chklovskii, Dmitri B.
树枝状乔木的形状很吸引人，也很重要，但这些复杂多样的结构背后的原理仍然不清楚。本文分析了2,171个哺乳动物脑内锥体神经元的树突，发现树枝大小与树突总长度成比例关系，树枝在树枝内的空间相关性具有普遍的函数形式，树枝的小部分具有自相似性。我们认为，这些特性是由于最大化了树突和周围轴突之间可能的连接模式，同时保持了树突的低成本。我们通过类比统计物理中给定能量的最大熵来解决这个最优化问题。该解与上述观测结果一致，并预测了可通过实验检验的标度关系。此外，我们的理论解释了为什么锥体细胞的树突分支比浦肯野细胞的树突分支分布得更稀疏。我们的结果代表了对神经元形态和功能之间关系的统一看法的一步。
The shapes of dendritic arbors are fascinating and important, yet the principles underlying these complex and diverse structures remain unclear. Here, we analyzed basal dendritic arbors of 2,171 pyramidal neurons sampled from mammalian brains and discovered 3 statistical properties: the dendritic arbor size scales with the total dendritic length, the spatial correlation of dendritic branches within an arbor has a universal functional form, and small parts of an arbor are self-similar. We proposed that these properties result from maximizing the repertoire of possible connectivity patterns between dendrites and surrounding axons while keeping the cost of dendrites low. We solved this optimization problem by drawing an analogy with maximization of the entropy for a given energy in statistical physics. The solution is consistent with the above observations and predicts scaling relations that can be tested experimentally. In addition, our theory explains why dendritic branches of pyramidal cells are distributed more sparsely than those of Purkinje cells. Our results represent a step toward a unifying view of the relationship between neuronal morphology and function.