Neuroscience Area, International School for Advanced Studies (ISAS-SISSA) Trieste, Italy.
Front Integr Neurosci. 2013 Sep 27;7:69. doi: 10.3389/fnint.2013.00069. eCollection 2013.
The present manuscript aims at identifying patterns of electrical activity recorded from neurons of the leech nervous system, characterizing specific behaviors. When leeches are at rest, the electrical activity of neurons and motoneurons is poorly correlated. When leeches move their head and/or tail, in contrast, action potential (AP) firing becomes highly correlated. When the head or tail suckers detach, specific patterns of electrical activity are detected. During elongation and contraction the electrical activity of motoneurons in the Medial Anterior and Dorsal Posterior nerves increase, respectively, and several motoneurons are activated both during elongation and contraction. During crawling, swimming, and pseudo-swimming patterns of electrical activity are better described by the dendrograms of cross-correlations of motoneurons pairs. Dendrograms obtained from different animals exhibiting the same behavior are similar and by averaging these dendrograms we obtained a template underlying a given behavior. By using this template, the corresponding behavior is reliably identified from the recorded electrical activity. The analysis of dendrograms during different leech behavior reveals the fine orchestration of motoneurons firing specific to each stereotyped behavior. Therefore, dendrograms capture the subtle changes in the correlation pattern of neuronal networks when they become involved in different tasks or functions.
本文旨在识别从秀丽隐杆线虫神经系统神经元记录的电活动模式,表征特定行为。当水蛭处于静止状态时,神经元和运动神经元的电活动相关性较差。相比之下,当水蛭移动头部和/或尾部时,动作电位 (AP) 发射变得高度相关。当头或尾吸盘脱落时,会检测到特定的电活动模式。在伸长和收缩过程中,中前神经和背后神经中的运动神经元的电活动分别增加,并且在伸长和收缩过程中都会激活多个运动神经元。在爬行、游泳和拟游泳过程中,运动神经元对的互相关联的 dendrograms 更好地描述了电活动模式。来自表现出相同行为的不同动物的 dendrograms 相似,通过对这些 dendrograms 进行平均,我们获得了一个基础模板,用于表示给定的行为。通过使用此模板,可以从记录的电活动中可靠地识别出相应的行为。对不同水蛭行为期间 dendrograms 的分析揭示了特定于每种刻板行为的运动神经元发射的精细协调。因此,dendrograms 捕捉到神经元网络在参与不同任务或功能时相关模式的细微变化。