Dual mechanisms governing reward-driven perceptual learning

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.