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Neural reconstructions of visual information across dynamic shifts of attention and working memory

Neural reconstructions of visual information across dynamic shifts of attention and working memory
通过注意力和工作记忆的动态变化对视觉信息进行神经重建
批准号:
9328233
负责人:
Emma Wu Dowd
金额:
$5.67万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-01 至 2020-08-31

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Project Summary At any given moment, the human visual system is overwhelmed by a wealth of sensory inputs, necessitating attentional mechanisms that selectively filter and process information for effective behavior. Attention, however, is dynamic—we are constantly distracted by competing inputs and goals, such that our attention (and our eyes) are always moving across the visual environment. The overarching goal of this research is to better understand the visual system, by investigating how humans update and integrate visual information across dynamic and unstable shifts of attention. Using a combination of behavioral, neuroimaging (fMRI), and computational modeling techniques, Aim 1 examines how external shifts of attention affect perceptual and neural representations of visual information that is visible to the eyes, while Aim 2 examines how internal shifts of attention modulate information maintained in visual working memory. Together, these aims demonstrate how dynamic changes of attentional focus can impact—and distort—our perception of the world, and provide insight into how humans flexibly prioritize information that is more or less relevant for current behavioral goals. The current proposal adopts a novel approach of measuring specific visual information in the mind and in the brain by combining computational models of behavior with computational models of neural activity—which may be ultimately integrated into a cohesive theory for the perceptual and neural mechanisms of visual stability. This research will have an immediate impact on the understanding of typical visual functioning in healthy human populations. While the proposed work is rooted in basic science, these advances would have a longer-term translational impact on public health, by informing the knowledge, assessment, and treatment of clinical disorders that are characterized by deficits in visual processing (e.g., schizophrenia, autism, ADHD). This research thus complements several training goals that will help the applicant acquire new technical skills and theoretical knowledge to prepare for a future career as an independent investigator.
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