Statistical context dictates the relationship between feedback-related EEG signals and learning
Statistical context dictates the relationship between feedback-related EEG signals and learning
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DOI：
10.7554/elife.46975
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发表时间：
2019-08-21
期刊：
影响因子：
7.7
通讯作者：
Frank, Michael J.
中科院分区：
文献类型：
--
作者：
Nassar, Matthew R.;Bruckner, Rasmus;Frank, Michael J.
学习应该根据观察到的结果带来的惊喜进行调整，但要根据统计背景进行校准。例如，当预期偶尔会出现变化点时，应该对意外结果进行加权，以加快学习速度。相反，当预期偶尔出现无信息的离群值时，令人惊讶的结果应该影响较小。在这里，我们将令人惊讶的结果与它们需要使用预测推理任务和计算建模进行学习的程度分离开来。我们发现，P300，刺激锁定的电生理反应，以前与学习行为的调整，这样做有条件的惊喜的来源。更大的P300信号预测在变化的背景下学习更好，但在惊喜指示一次性离群值（oddball）的背景下学习更少。我们的研究结果表明，P300提供了一个令人惊讶的信号，下游学习过程根据统计背景进行不同的解释，以便在复杂的环境中适当地校准学习。
Learning should be adjusted according to the surprise associated with observed outcomes but calibrated according to statistical context. For example, when occasional changepoints are expected, surprising outcomes should be weighted heavily to speed learning. In contrast, when uninformative outliers are expected to occur occasionally, surprising outcomes should be less influential. Here we dissociate surprising outcomes from the degree to which they demand learning using a predictive inference task and computational modeling. We show that the P300, a stimulus-locked electrophysiological response previously associated with adjustments in learning behavior, does so conditionally on the source of surprise. Larger P300 signals predicted greater learning in a changing context, but less learning in a context where surprise was indicative of a one-off outlier (oddball). Our results suggest that the P300 provides a surprise signal that is interpreted by downstream learning processes differentially according to statistical context in order to appropriately calibrate learning across complex environments.