SELF-STIMULATION IN RAT - QUANTITATIVE CHARACTERISTICS OF REWARD PATHWAY

SELF-STIMULATION IN RAT - QUANTITATIVE CHARACTERISTICS OF REWARD PATHWAY
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DOI:
10.1037/h0077513
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发表时间:
1978-01-01
期刊:
JOURNAL OF COMPARATIVE AND PHYSIOLOGICAL PSYCHOLOGY
影响因子:
--
通讯作者:
GALLISTEL, CR
GALLISTEL, CR
中科院分区:
其他
文献类型:
--
作者:
GALLISTEL, CR

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通过找出哪种刺激参数组合在跑道上提供相同的性能,建立了在大脑电自我刺激中携带增强信号的神经路径的定量特征。每跑一次的回报是来自单极电极的一串均匀分布的单相阴极脉冲。在列车持续时间和脉冲频率保持不变的情况下,所需电流是脉冲持续时间的双曲线函数,时间轴为c·apprxeq。1.5毫秒。在脉冲持续时间保持不变的情况下,列车所需的强度(每个S传递的电荷)是列车持续时间的双曲线函数,时间轴为C.apprxeq。500毫秒。对于第一近似值,c和C的值分别与序列持续时间和脉冲频率或脉冲持续时间的选择无关。任何列车持续时间、脉冲频率和脉冲持续时间的选择所需的电流强度仅取决于2个基本参数c和C,以及所需的脉冲电荷1个量qi。它们可以分别反映直接兴奋的神经元的电流整合;神经网络中突触过程的神经活动的时间整合;以及假设网络具有线性动力学并且奖励取决于网络输出的峰值,网络的脉冲响应的峰值。
Quantitative characteristics of the neural pathway that carries the reinforcing signal in electrical self-stimulation of the brain were established by finding which combinations of stimulation parameters give the same performance in a runway. The reward for each run was a train of evenly spaced monophasic cathodal pulses from a monopolar electrode. With train duration and pulse frequency held constant, the required current was a hyperbolic function of pulse duration, with chronaxie c .apprxeq. 1.5 ms. With pulse duration held constant, the required strength of the train (the charge delivered per s) was a hyperbolic function of train duration, with chronaxie C .apprxeq. 500 ms. To a first approximation, the values of c and C were independent of the choice either of train duration and pulse frequency or of pulse duration, respectively. The current intensity required by any choice of train duration, pulse frequency, and pulse duration depended on only 2 basic parameters, c and C, and 1 quantity, Qi, the required impulse charge. These may reflect, respectively, current integration by directly excited neurons; temporal integration of neural activity by synaptic processes in a neural network; and the peak of the impulse response of the network, assuming that the network has linear dynamics and that the reward depends on the peak of the output of the network.