How Does Normalization Regulate Visual Competition?

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PROJECT SUMMARY/ABSTRACT How does the visual system regulate competing sensory information? Recent theories propose that a computation known as divisive normalization plays a key role in governing neural competition. Normalization is considered a canonical neural computation, potentially driving responses throughout the neural and cognitive system. Interestingly, there is evidence to suggest that normalization's pervasive role relies on an exquisite tuning to stimulus features, such as orientation, but this feature-selective nature of normalization is surprisingly understudied, particularly in humans. The goal of the proposed work is to employ state-of-the-art functional neuroimaging techniques and analyses to shed light on the tuning characteristics that allow normalization to control population responses within human visual cortex, and to understand how this form of normalization can support functions as diverse as attentional selection and interocular competition. We approach the problem by first characterizing the selective properties of normalization within early visual cortex during normal, passive, scene viewing. We will then assess the unifying potential of models based on divisive normalization, examining the role of feature-tuned normalization in regulating competition in apparently unrelated settings, namely those involving selective attention and interocular competition. By revealing the properties of tuned normalization within human visual cortex, and characterizing the role of normalization in attentional feedback and competition at large, these studies will provide the necessary framework for the development of diagnostic tools and treatments for clinical disorders that involve deficits in central visual processing.