Disrupting Perceptual Learning

Perceptual learning is learning to perceive and is essential for all forms of perception and learning. For a long time it was believed that perceptual learning was a simple process suitable as a model for studying general mechanism of learning. Researchers set out on a quest to conquer this "holy grail" of learning. It proved an effortful journey. Decades later, the grail remains elusive and the field of perceptual learning has established itself a research field of its own. In this work, I show that simple tasks do not follow previously established rules of perceptual learning. Instead it seems that perceptual learning rules, which were once believed to generalize over paradigms, depend on the experimental paradigms themselves. Hence, systematic studies are required to comb out the rules of perceptual learning and generization should be done with caution. In conclusion, there is no holy grail of perceptual learning

Temporal patterning of 'unlearnable' stimuli types does not always enable learning

Presenting two or more stimulus types randomly interleaved, so-called roving stimuli, disrupts perceptual learning in many paradigms. It was recently reported that learning with disrupting stimuli types is possible when stimuli are presented in an alternating sequence, ie stimulus from type A, then type B, then type A, etc. In our experiment we used used bisection stimuli, but found the opposite pattern of results. Presentation of bisection stimuli in a sequence disrupted perceptual learning. We tried to explain these seemingly contradictory results by conducting a meta-analysis. Participants who initially performed the task at a low level, ie 'bad performers', were able to learn, whereas the 'good performers' did not (good performers were still outside the ceiling range). Therefore, interleaving stimuli may not abolish perceptual learning, they may just make it more difficult and more prone to interact with other factors, such as the initial performance level

Hemispheric Asymmetries in Striatal Reward Responses Relate to Approach-Avoidance Learning and Encoding of Positive-Negative Prediction Errors in Dopaminergic Midbrain Regions

Some individuals are better at learning about rewarding situations, whereas others are inclined to avoid punishments (i.e., enhanced approach or avoidance learning, respectively). In reinforcement learning, action values are increased when outcomes are better than predicted (positive prediction errors [PEs]) and decreased for worse than predicted outcomes (negative PEs). Because actions with high and low values are approached and avoided, respectively, individual differences in the neural encoding of PEs may influence the balance between approach-avoidance learning. Recent correlational approaches also indicate that biases in approach-avoidance learning involve hemispheric asymmetries in dopamine function. However, the computational and neural mechanisms underpinning such learning biases remain unknown. Here we assessed hemispheric reward asymmetry in striatal activity in 34 human participants who performed a task involving rewards and punishments. We show that the relative difference in reward response between hemispheres relates to individual biases in approach-avoidance learning. Moreover, using a computational modeling approach, we demonstrate that better encoding of positive (vs negative) PEs in dopaminergic midbrain regions is associated with better approach (vs avoidance) learning, specifically in participants with larger reward responses in the left (vs right) ventral striatum. Thus, individual dispositions or traits may be determined by neural processes acting to constrain learning about specific aspects of the world