The neural bases of precision and distractor resistance in visual working memory

Visual working memory, a complex cognitive process that is essential for goal-directed behaviors, allows the internal maintenance and manipulation of detailed visual information that is no longer available in the environment. The neural processes and representations that support this essential ability remain the focus of much research and debate. In this dissertation, I present three experiments that tested key predictions of a sensory recruitment model of visual working memory, which proposes that the same regions responsible for primary sensory processing are recruited to maintain precise sensory details over short delays. All of these experiments involved the collection of functional magnetic resonance imaging (fMRI) data while participants performed cognitive tasks requiring visual working memory. The primary fMRI analyses described here utilize two multivariate approaches that model the information content of distributed patterns of brain activity: inverted encoding models and multivoxel pattern analysis.The first chapter of this dissertation uses an inverted encoding model to reconstruct simple orientation information held in working memory and examines the effect of subsequent visual input on these memory representations. Here, I show that visual working memory representations are flexible and can dynamically adjust to meet task demands. First, I find that the early visual areas maintain precise orientation information over a delay, but that these representations are susceptible to bias from visual interference. Further, I find that the intraparietal sulcus redundantly represents orientation information in anticipation of possible distraction and continues to do so if visual interference renders early visual cortical representations unreliable.In the second chapter, I present strong evidence in favor of a sensory recruitment model of visual working memory for complex images like human faces. Here, I use an encoding model to characterize distributed response p