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参数操作与固定间隔自我刺激。

Parametric manipulations and fixed-interval self-stimulation.

作者信息

Hunt G E, Atrens D M

机构信息

Department of Psychiatry, University of Sydney, New South Wales, Australia.

出版信息

Physiol Behav. 1992 May;51(5):1009-20. doi: 10.1016/0031-9384(92)90085-g.

Abstract

Three experiments investigated hypothalamic self-stimulation under a fixed-interval (FI) reinforcement schedule. An FI 20-s schedule was chosen to reduce stimulation density in order to minimize the influence of priming effects or stimulation aftereffects that can affect responding under other schedules of reinforcement. The first experiment showed that the influence of train duration is greatest at levels up to 1 s and thereafter level off over a wide range of train durations (1-32 s). The second experiment showed that altering frequency, current, or pulse width produced almost identical changes in FI responding. These findings show that the neutral network subserving hypothalamic self-stimulation simply integrates the amount of charge over time. It is relatively insensitive to the combination of stimulation parameters that make up a given waveform. In the third experiment, the chronaxies from the strength-duration curves indicate the neural substrate supporting self-stimulation has a great current-integrating capacity. Together, these experiments show that varying the amount of brain stimulation produce large and consistent changes in a number of FI response measures. These measures effectively describe different attributes of FI performance and include response rate, the postreinforcement pause, interresponse times of short duration and the temporal distribution of responses within the interval.

摘要

三项实验研究了在固定间隔(FI)强化程序下的下丘脑自我刺激。选择FI 20秒的程序来降低刺激密度,以尽量减少启动效应或刺激后效的影响,这些效应可能会影响在其他强化程序下的反应。第一个实验表明,训练持续时间的影响在长达1秒时最大,此后在很宽的训练持续时间范围(1 - 32秒)内趋于平稳。第二个实验表明,改变频率、电流或脉冲宽度在FI反应中产生几乎相同的变化。这些发现表明,支持下丘脑自我刺激的神经网络只是简单地对随时间积累的电荷量进行整合。它对构成给定波形的刺激参数组合相对不敏感。在第三个实验中,强度 - 持续时间曲线的时值表明支持自我刺激的神经基质具有很大的电流整合能力。总之,这些实验表明,改变脑刺激的量会在许多FI反应指标上产生大而一致的变化。这些指标有效地描述了FI表现的不同属性,包括反应率、强化后停顿、短持续时间的反应间隔时间以及间隔内反应的时间分布。

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