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用于分析雄性大鼠交配时骨盆推挤动作期间脑电活动的计算机程序。

Computer programs to analyze brain electrical activity during copulatory pelvic thrusting in male rats.

作者信息

Hernandez-Gonzalez M, Guevara M A, Moralí G, Cervantes M

机构信息

Instituto de Neurociencias, Universidad de Guadalajara, Jalisco., México.

出版信息

Physiol Behav. 1997 Oct;62(4):701-8. doi: 10.1016/s0031-9384(97)00006-1.

DOI:10.1016/s0031-9384(97)00006-1
PMID:9284487
Abstract

Two microcomputer programs have been developed to simultaneously record and analyze the brain electrical activity: multiple unit activity (MUA) and electroencephalogram (EEG), and the accelerometric signals generated in relation to the pelvic thrusting that performs the male rat during the copulatory responses of mount, intromission, and ejaculation. CAPTUMUL is a program allowing the on line capture of the different signals and the further off line delimitation of the brain signals occurring in exact temporal relation with the accelerometric record of motor responses. The ANAMUA program allows the off line analysis of the neuronal firing rate in MUA records at different discrimination levels according to the amplitude of the neuronal spikes, and compare these data in various behavioral situations. The use of these programs provides a way of correlating in time the changes of brain electrical activity occurring in animals in free-movement with the brief motor events of copulation as well as with other behaviors (i.e., genital grooming, sniffing, running, walking). Advantages of this software include the recording of sequential events, a better and rapid handling of data and a reliable method to analyze the MUA with different discrimination levels according to the amplitude of the neuronal spikes.

摘要

已经开发了两个微机程序,用于同时记录和分析脑电活动:多单位活动(MUA)和脑电图(EEG),以及与雄性大鼠在交配反应(包括爬跨、插入和射精)期间进行的骨盆推顶相关产生的加速度信号。CAPTUMUL是一个程序,允许在线捕获不同信号,并进一步离线界定与运动反应的加速度记录具有精确时间关系的脑信号。ANAMUA程序允许根据神经元尖峰的幅度在不同辨别水平下对MUA记录中的神经元放电率进行离线分析,并在各种行为情况下比较这些数据。这些程序的使用提供了一种方法,可将自由活动动物中发生的脑电活动变化与交配的短暂运动事件以及其他行为(即生殖器梳理、嗅探、奔跑、行走)在时间上进行关联。该软件的优点包括记录连续事件、更好且快速地处理数据,以及一种根据神经元尖峰幅度在不同辨别水平下分析MUA的可靠方法。

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