Title Uncertainty, inference, and introspection in the primate visual system Abstract Perceptual systems offer a window onto a world that cannot be known perfectly. Uncertainty about the world can arise externally, when sensory cues are incomplete or contradictory, or internally, when noise corrupts neural representations. Ideal perceptual systems do not ignore uncertainty, but take it into account. For example, if a sensory cue is ambiguous, prior experience should guide the interpretation of the environment. Likewise, the reliability of sensory signals should inform confidence in perceptual decisions. When humans and monkeys perform perceptual tasks, they often follow these normative predictions. This implies that the neural circuits which process sensory information also survey the uncertainty of this information, and put this estimate to use for perceptual inference and perceptual introspection. How they do so is not well understood. A more precise understanding of the neural processing of sensory uncertainty and its role in perception and cognition may help to advance the treatment of pathologies such as agnosia, autism, and schizophrenia. Recently, several theoretical frameworks have been proposed that offer explicit accounts of the neural processing of uncertainty in low-level sensory and high-level decision-making circuits (linear probabilistic population codes, quadratic probabilistic population codes, temporal sampling models, and the curved manifold hypothesis). These developments form the background for this proposal. We will trace the processing of sensory uncertainty from its initial computation and representation in early visual cortex to its eventual use in informing confidence in perceptual decisions and in regulating the integration of sensory signals and prior information in high-level decision-making areas in prefrontal cortex. We will use the data we collect to compare and contrast the predictions of various theories of neural coding. First, we will study V1 population activity in awake, fixating macaques while presenting stimuli whose orientation uncertainty is manipulated in distinct ways. Next, we will examine how neural activity in primary visual cortex informs confidence in a perceptual estimate of stimulus orientation. Finally, we will identify how sensory uncertainty shapes neural population representations in prefrontal cortex during a perceptual inference task. The outcomes of this work will not only enhance our understanding of the visual system, but will also provide a novel experimental paradigm to study perceptual introspection in animals and a novel computational tool for analyzing behavioral confidence reports.