Thursday, November 21, 2024
11/21/2024
PROJECT SUMMARY/ABSTRACT How does the human visual system regulate competing sensory information? Prevailing 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 brain. Interestingly, there is evidence to suggest that normalization’s pervasive role relies on an exquisite tuning to stimulus features, such as orientation and spatial frequency, but this feature-selective nature of normalization is surprisingly understudied, particularly in humans. Our long-term goal is to understand the neural mechanisms supporting vision across the visual hierarchy in humans, and to characterize how they flexibly change with selective attention. The aim of this proposal 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 normalization can support selective attention. 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 that normalization plays in regulating competition via spatially- directed and feature-based attention. By revealing the role played by tuned normalization within human visual cortex, 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.
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