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Poster B in Poster Session B: Tuesday, August 4, 2:00 – 3:45 pm, Kimmel Center, Shorin & Rosenthal Rooms

Attention Gain as a Learning Mechanism in a Visual Search Meta-Task

Christos Karaneen¹, Grace W Lindsay¹; ¹New York University

Presenter: Christos Karaneen

Most perceptual learning studies track a subject's behavior as they get better at a very precise visual task. Such studies have informed several theories regarding the neural changes that underlie these performance enhancements. Real world visual challenges, however, require learning that enhances visual processing in a more flexible way across many conditions. The neural mechanisms of this type of meta-task learning remain unclear. Here, based off an experimental study of how humans learn to perform a triple conjunction search task, we build a model to show that changes in top-down attention can account for learning in this meta-task. Specifically, we show that a simple increase in the magnitude of top-down gain modulation enhances search accuracy. It also decreases a proxy measure of intersaccadic interval by making it easier for the visual system to reject distractors. This is consistent with the behavioral findings of the original study. We therefore identify top-down modulatory signals as a potential locus of learning. Our work is a first step towards theories of the neural mechanisms that support learning in flexible visual tasks.

Topic Area: Computational Models of Vision & Visual Cortex