Montague P Read, McClure Samuel M, Baldwin P R, Phillips Paul E M, Budygin Evgeny A, Stuber Garret D, Kilpatrick Michaux R, Wightman R Mark
Human Neuroimaging Laboratory, Center for Theoretical Neuroscience, Division of Neuroscience, Baylor College of Medicine, Houston, Texas 77030, USA.
J Neurosci. 2004 Feb 18;24(7):1754-9. doi: 10.1523/JNEUROSCI.4279-03.2004.
Activity changes in a large subset of midbrain dopamine neurons fulfill numerous assumptions of learning theory by encoding a prediction error between actual and predicted reward. This computational interpretation of dopaminergic spike activity invites the important question of how changes in spike rate are translated into changes in dopamine delivery at target neural structures. Using electrochemical detection of rapid dopamine release in the striatum of freely moving rats, we established that a single dynamic model can capture all the measured fluctuations in dopamine delivery. This model revealed three independent short-term adaptive processes acting to control dopamine release. These short-term components generalized well across animals and stimulation patterns and were preserved under anesthesia. The model has implications for the dynamic filtering interposed between changes in spike production and forebrain dopamine release.
中脑多巴胺神经元的一个大子集的活动变化通过编码实际奖励与预测奖励之间的预测误差，满足了学习理论的众多假设。对多巴胺能尖峰活动的这种计算解释引发了一个重要问题，即尖峰频率的变化如何转化为目标神经结构中多巴胺释放的变化。通过对自由活动大鼠纹状体中快速多巴胺释放的电化学检测，我们确定了一个单一的动态模型可以捕捉多巴胺释放的所有测量波动。该模型揭示了三个独立的短期适应性过程，它们共同作用来控制多巴胺释放。这些短期成分在不同动物和刺激模式中具有良好的普遍性，并且在麻醉状态下得以保留。该模型对介于尖峰产生变化和前脑多巴胺释放之间的动态过滤具有启示意义。
