Visual (perceptual) reasoning is a critical skill in many medical specialties, including pathology, diagnostic imaging, and dermatology. However, in an ever-compressed medical curriculum, learning and practicing this skill can be challenging. Previous studies (including work with pigeons) have suggested that using reward-feedback-based activities, novices can gain expert levels of visual diagnostic accuracy in shortened training times. But is this level of diagnostic accuracy a result of image recognition (categorization) or is it the acquisition of diagnostic expertise? To answer this, the authors measured electroencephalographic data (EEG) and two components of the human event-related brain potential (reward positivity and N170) to explore the nature of visual expertise in a novice-expert study in pathology visual diagnosis. It was found that the amplitude of the reward positivity decreased with learning in novices (suggesting a decrease in reliance on feedback, as in other studies). However, this signal remained significantly different from the experts whose reward positivity signal did not change over the course of the experiment. There were no changes in the amplitude of the N170 (a reported neural marker of visual expertise) in novices over time. Novice N170 signals remained statistically and significantly lower in amplitude compared to experts throughout task performance. These data suggest that, while novices gained the ability to recognize (categorize) pathologies through reinforcement learning as quantified by the change in reward positivity, increased accuracy, and decreased time for responses, there was little change in the neural marker associated with visual expertise (N170). This is consistent with the multi-dimensional and complex nature of visual expertise and provides insight into future training programs for novices to bridge the expertise gap.