The Salk Institute, La Jolla, CA 92037, USA.
Neuron. 2010 Apr 15;66(1):45-56. doi: 10.1016/j.neuron.2010.02.013.
Axonal and dendritic arbors can be characterized statistically by their spatial density function, a function that specifies the probability of finding a branch of a particular arbor at each point in a neural circuit. Based on an analysis of over a thousand arbors from many neuron types in various species, we have discovered an unexpected simplicity in arbor structure: all of the arbors we have examined, both axonal and dendritic, can be described by a Gaussian density function truncated at about two standard deviations. Because all arbors are characterized by density functions with this single functional form, only four parameters are required to specify an arbor's size and shape: the total length of its branches and the standard deviations of the Gaussian in three orthogonal directions. This simplicity in arbor structure can have implications for the developmental wiring of neural circuits.
轴突和树突的分支可以通过它们的空间密度函数进行统计描述，该函数指定了在神经回路的每个点上找到特定分支的概率。基于对来自不同物种的多种神经元类型的一千多个分支的分析，我们发现分支结构具有出人意料的简单性：我们检查过的所有分支，无论是轴突还是树突，都可以用截断约两个标准差的高斯密度函数来描述。由于所有分支都具有这种单一功能形式的密度函数，因此只需四个参数即可指定分支的大小和形状：分支的总长度以及三个正交方向上的高斯标准偏差。分支结构的这种简单性可能对神经回路的发育布线具有影响。
