Science2014-07-01 1:34 PM

全脑图将神经元与行为挂钩 Discovery of Brainwide Neural-Behavioral Maps via Multiscale Unsupervised Structure Learning

论文摘要 

将神经元回路与某种活的生物体的特定行为挂钩已被证明是出了名地困难。但是,Joshua Vogelstein及其同事研发出了一种用于调查这类神经元回路以及受到这些回路激发的行为的新技术,他们用该技术创建了一个在果蝇幼虫的神经元参考图谱。据这些研究人员披露,这一图谱将果蝇幼虫的神经元中的一大部分与29种果蝇的一般行为,如“后退”、“转身-避开”或“逃逸”等挂钩,而且它为在动物王国中调查选择并控制这些独特行为的基础机制提供了一个宝贵的起点。Vogelstein及他的团队在3万7780个果蝇幼虫的脑中使用了一种会对光做出反应的被称作视紫红质通道蛋白的蛋白质来选择性地激活1054个不同的神经元通路。高速摄像机捕捉到了该神经元在刺激之前、之中及之后果蝇幼虫的形状及运动的视频,而最先进的软件将这些运动归类为不同的“行为类型”,或者说是行为的基本族及亚族。研究人员的光遗传学筛检方法确认了会影响通过自然刺激所触发的日常行为以及从前没有被记录过的行为类型的神经元。他们说,将来,它也许也能适用于其它的生物体。

Abstract

A single nervous system can generate many distinct motor patterns. Identifying which neurons and circuits control which behaviors has been a laborious piecemeal process, usually for one observer-defined behavior at a time. We present a fundamentally different approach to neuron-behavior mapping. We optogenetically activated 1054 identified neuron lines in Drosophila larvae and tracked the behavioral responses from 37,780 animals. Application of multiscale unsupervised structure learning methods to the behavioral data enabled us to identify 29 discrete, statistically distinguishable, observer-unbiased behavioral phenotypes. Mapping the neural lines to the behavior(s) they evoke provides a behavioral reference atlas for neuron subsets covering a large fraction of larval neurons. This atlas is a starting point for connectivity- and activity-mapping studies to further investigate the mechanisms by which neurons mediate diverse behaviors.

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