Kim Dongho, Ling Sam, Watanabe Takeo
Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA ; Center for Computational Neuroscience and Neural Technology, Boston University, Boston, MA, USA.
Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA ; Center for Computational Neuroscience and Neural Technology, Boston University, Boston, MA, USA ; Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, Netherlands.
F1000Res. 2015 Sep 10;4:764. doi: 10.12688/f1000research.6853.1. eCollection 2015.
In this review, we explore how reward signals shape perceptual learning in animals and humans. Perceptual learning is the well-established phenomenon by which extensive practice elicits selective improvement in one's perceptual discrimination of basic visual features, such as oriented lines or moving stimuli. While perceptual learning has long been thought to rely on 'top-down' processes, such as attention and decision-making, a wave of recent findings suggests that these higher-level processes are, in fact, not necessary. Rather, these recent findings indicate that reward signals alone, in the absence of the contribution of higher-level cognitive processes, are sufficient to drive the benefits of perceptual learning. Here, we will review the literature tying reward signals to perceptual learning. Based on these findings, we propose dual underlying mechanisms that give rise to perceptual learning: one mechanism that operates 'automatically' and is tied directly to reward signals, and another mechanism that involves more 'top-down', goal-directed computations.
在本综述中，我们探讨奖励信号如何塑造动物和人类的知觉学习。知觉学习是一种已被充分证实的现象，即大量练习会使人对基本视觉特征（如定向线条或移动刺激）的知觉辨别能力得到选择性提高。长期以来，人们一直认为知觉学习依赖于“自上而下”的过程，如注意力和决策，但最近的一系列研究结果表明，这些高级过程实际上并非必要条件。相反，这些最新研究结果表明，仅奖励信号本身，在没有高级认知过程参与的情况下，就足以产生知觉学习的效果。在此，我们将回顾将奖励信号与知觉学习联系起来的文献。基于这些研究结果，我们提出了导致知觉学习的两种潜在机制：一种机制是“自动”运行的，直接与奖励信号相关联；另一种机制则涉及更多“自上而下”的、目标导向的计算。
