Topic: analysis tools

In the first part of this talk I will present work showing that recurrent neural networks can replicate broad behavioral patterns associated with dynamic visual object recognition in humans. An analysis of these networks shows that different types of recurrence use different strategies to solve the object recognition problem. The similarities between artificial neural networks and the brain presents another opportunity, beyond using them just as models of biological processing. In the second part of this talk, I will discuss—and solicit feedback on—a proposed research plan for testing a wide r

Whether we are deciding about Covid-related restrictions, estimating a ball’s trajectory when playing tennis, or interpreting radiological images – most any choice we make is based on uncertain evidence. How do we infer that information is more or less reliable when making these decisions? How does the brain represent knowledge of this uncertainty? In this talk, I will present recent neuroimaging data combined with novel analysis tools to address these questions. Our results indicate that sensory uncertainty can reliably be estimated from the human visual cortex on a trial-by-trial basis, and