Statistics of midbrain dopamine neuron spike trains in the awake primate
Statistics of midbrain dopamine neuron spike trains in the awake primate
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DOI：
10.1152/jn.01140.2006
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发表时间：
2007-09-01
影响因子：
2.5
通讯作者：
Glimcher, Paul W.
中科院分区：
文献类型：
--
作者：
Bayer, Hannah M.;Lau, Brian;Glimcher, Paul W.
对行为灵长类动物的研究表明，中脑多巴胺神经元编码了一个预测错误，即获得的奖励和预期奖励之间的差异。在警觉和麻醉大鼠多巴胺动作电位计时的研究表明，多巴胺神经元在紧张性和相位模式，已较少的特点，在灵长类动物的区别。我们使用尖峰序列模型来研究猴子在执行强化视觉扫视运动任务时多巴胺神经元的紧张和爆发活动模式之间的关系。我们研究了尖峰活动在四个任务相关的时间间隔，其中两个是没有任务相关的事件发生的时间间隔，而两个期间标记的任务相关的阶段性活动。我们发现，在没有事件发生的时间间隔内，多巴胺神经元的峰电位序列被很好地描述为紧张性的。动作电位似乎是独立的，发生在低频率，并几乎同样很好地描述高斯和泊松样（伽马）过程。与大鼠不同的是，在这些假定的紧张性时期，经常观察到低至20毫秒的峰间期。在确定了这些假定的紧张性活动的时期之后，我们能够定量地定义在任务相关事件发生的间隔期间的相位调制（活动的增加和减少）。该分析显示，这些神经元的相位调制包括如前所述的爆发和暂停。爆发和停顿似乎提供了一个连续的，虽然非线性的，表示理论上定义的奖励预测错误的强化学习。
Work in behaving primates indicates that midbrain dopamine neurons encode a prediction error, the difference between an obtained reward and the reward expected. Studies of dopamine action potential timing in the alert and anesthetized rat indicate that dopamine neurons respond in tonic and phasic modes, a distinction that has been less well characterized in the primates. We used spike train models to examine the relationship between the tonic and burst modes of activity in dopamine neurons while monkeys were performing a reinforced visuo-saccadic movement task. We studied spiking activity during four task-related intervals; two of these were intervals during which no task-related events occurred, whereas two were periods marked by task-related phasic activity. We found that dopamine neuron spike trains during the intervals when no events occurred were well described as tonic. Action potentials appeared to be independent, to occur at low frequency, and to be almost equally well described by Gaussian and Poisson-like ( gamma) processes. Unlike in the rat, interspike intervals as low as 20 ms were often observed during these presumptively tonic epochs. Having identified these periods of presumptively tonic activity, we were able to quantitatively define phasic modulations ( both increases and decreases in activity) during the intervals in which task-related events occurred. This analysis revealed that the phasic modulations of these neurons include both bursting, as has been described previously, and pausing. Together bursts and pauses seemed to provide a continuous, although nonlinear, representation of the theoretically defined reward prediction error of reinforcement learning.