PROJECT SUMMARY Much progress has been achieved in building computational models that describe how visual stimuli are encoded and transformed across the hierarchy of visual areas in the primate brain. However, relatively little attention has been given to the active component of visual processing, whereby the observer’s engagement in a cognitive or perceptual task can exert substantial influence on stimulus-evoked activity. The long-term goal of the proposed research is to develop models that account for not only stimulus-driven but also task-driven effects in the visual system. To achieve this goal, we invest effort in improving analysis methodology and in generating large high- quality experimental datasets. In Aim 1, we develop and optimize methods that provide robust fMRI measurements at the level of single trials. This includes a method that exploits temporal dynamics to isolate BOLD signals that are more closely related to local neural activity, and an algorithm that improves signal-to- noise ratio in general linear modeling of fMRI data. In Aim 2, we acquire and prepare a high-field (7T) fMRI dataset in which a large variety of tasks are performed on a common set of visual stimuli. This dataset exploits deep sampling of a small number of subjects, and will generate a rich, reusable resource for the fields of cognitive and computational neuroscience. In Aim 3, we exploit the dataset to test an extant model of how top-down influences from the intraparietal sulcus modulate responses in ventral visual cortex and to assess how top-down signals from frontal cortex modulate the fidelity of working memory stimulus encoding in visual cortex. Overall, this multidisciplinary proposal will deliver reusable methods and data resources, and will push computational modeling from the domain of stimulus representation into better understanding how the visual system mediates real-world visual perception and task engagement. Advancing our understanding of the computational mechanisms underlying visual processing in healthy individuals is a critical step for unraveling the nature of sensory disorders such as prosopagnosia and dyslexia.