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通过神经网络优化识别出的空间定向行为的回路基序。

Circuit motifs for spatial orientation behaviors identified by neural network optimization.

作者信息

Dunn N A, Conery J S, Lockery S R

机构信息

Institute of Neuroscience, University of Oregon, Eugene, Oregon 97403, USA.

出版信息

J Neurophysiol. 2007 Aug;98(2):888-97. doi: 10.1152/jn.00074.2007. Epub 2007 May 23.

Abstract

Spatial orientation behavior is universal among animals, but its neuronal basis is poorly understood. The main objective of the present study was to identify candidate patterns of neuronal connectivity (motifs) for two widely recognized classes of spatial orientation behaviors: hill climbing, in which the organism seeks the highest point in a spatial gradient, and goal seeking, in which the organism seeks an intermediate point in the gradient. Focusing on simple networks of graded processing neurons characteristic of Caenorhabditis elegans and other nematodes, we used an unbiased optimization algorithm to seek values of neuronal time constants, resting potentials, and synaptic strengths sufficient for each type of behavior. We found many different hill-climbing and goal-seeking networks that performed equally well in the two tasks. Surprisingly, however, each hill-climbing network represented one of just three fundamental circuit motifs, and each goal-seeking network comprised two of these motifs acting in concert. These motifs are likely to inform the search for the real circuits that underlie these behaviors in nematodes and other organisms.

摘要

空间定向行为在动物中普遍存在,但其神经元基础却知之甚少。本研究的主要目的是为两类广泛认可的空间定向行为确定神经元连接模式(基序)的候选模式:爬山行为,即生物体在空间梯度中寻找最高点;目标导向行为,即生物体在梯度中寻找中间点。我们聚焦于秀丽隐杆线虫和其他线虫特有的分级处理神经元的简单网络,使用一种无偏优化算法来寻找足以实现每种行为类型的神经元时间常数、静息电位和突触强度的值。我们发现了许多不同的爬山和目标导向网络,它们在这两项任务中的表现同样出色。然而,令人惊讶的是,每个爬山网络仅代表三种基本电路基序之一,而每个目标导向网络则由其中两种协同作用的基序组成。这些基序可能有助于寻找线虫和其他生物体中这些行为背后的真实电路。

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