The role of statistical summary representations in visual learning

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Intuition would suggest that the brain should represent sets of items in the same way it represents individual items. Contrary to this intuition, researchers have discovered that sets of information are represented according to their statistical properties, such as their average size or variability in colour. Over the past 15 years, researchers have established important roles for such statistical summary representations (SSRs) in perception and attention. The purpose of this program of research is to determine whether there might also be a role for SSRs in visual learning, and, if so, to understand the conditions that facilitate such learning. To address these questions, I will carry out experiments designed to explore the contribution of SSRs to learning in three everyday tasks: categorization, search, and learning to recognize faces. The findings have the potential to advance models of these processes, which currently do not incorporate a role for SSRs. Of equal importance, they have the potential to inform advances in medical decision making, artificial navigation systems, and face recognition software.