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Striatal and Tegmental Neurons Code Critical Signals for Temporal-Difference Learning of State Value in Domestic Chicks

机译:纹状体和背盖神经元代码关键信号的家禽的状态值的时差学习。

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摘要

To ensure survival, animals must update the internal representations of their environment in a trial-and-error fashion. Psychological studies of associative learning and neurophysiological analyses of dopaminergic neurons have suggested that this updating process involves the temporal-difference (TD) method in the basal ganglia network. However, the way in which the component variables of the TD method are implemented at the neuronal level is unclear. To investigate the underlying neural mechanisms, we trained domestic chicks to associate color cues with food rewards. We recorded neuronal activities from the medial striatum or tegmentum in a freely behaving condition and examined how reward omission changed neuronal firing. To compare neuronal activities with the signals assumed in the TD method, we simulated the behavioral task in the form of a finite sequence composed of discrete steps of time. The three signals assumed in the simulated task were the prediction signal, the target signal for updating, and the TD-error signal. In both the medial striatum and tegmentum, the majority of recorded neurons were categorized into three types according to their fitness for three models, though these neurons tended to form a continuum spectrum without distinct differences in the firing rate. Specifically, two types of striatal neurons successfully mimicked the target signal and the prediction signal. A linear summation of these two types of striatum neurons was a good fit for the activity of one type of tegmental neurons mimicking the TD-error signal. The present study thus demonstrates that the striatum and tegmentum can convey the signals critically required for the TD method. Based on the theoretical and neurophysiological studies, together with tract-tracing data, we propose a novel model to explain how the convergence of signals represented in the striatum could lead to the computation of TD error in tegmental dopaminergic neurons.
机译:为了确保生存,动物必须以反复试验的方式更新其环境的内部表示。对多巴胺能神经元的关联学习和神经生理学分析的心理学研究表明,这种更新过程涉及基底神经节网络中的时差(TD)方法。但是,尚不清楚在神经元水平上实现TD方法的组成变量的方式。为了研究潜在的神经机制,我们训练了家养小鸡将颜色提示与食物奖励相关联。我们在自由行为的情况下记录了内侧纹状体或睑板的神经元活动,并检查了奖励遗漏如何改变神经元的放电。为了将神经元活动与TD方法中假定的信号进行比较,我们以由离散时间步长组成的有限序列的形式模拟了行为任务。在模拟任务中假设的三个信号是预测信号,更新目标信号和TD错误信号。在内侧纹状体和盖骨中,大多数记录的神经元根据它们对三种模型的适应性而分为三类,尽管这些神经元倾向于形成连续谱,而发射速率没有明显差异。具体而言,两种类型的纹状体神经元成功地模仿了目标信号和预测信号。这两种纹状体神经元的线性求和非常适合模拟TD误差信号的一种类型的被膜神经元的活动。因此,本研究表明纹状体和睑板能够传达TD方法至关重要的信号。在理论和神经生理学研究的基础上,结合道追踪数据,我们提出了一个新颖的模型来解释纹状体中所代表信号的收敛如何导致被盖多巴胺能神经元中TD误差的计算。

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