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EAPSI: Investigating Neural Coding of Spatiotemporal Events Using Visual Adaptation

EAPSI: Investigating Neural Coding of Spatiotemporal Events Using Visual Adaptation
EAPSI:使用视觉适应研究时空事件的神经编码
批准号:
1614427
负责人:
Katherine Mussell
金额:
$0.54万
依托单位:
依托单位国家:
美国
项目类别:
Fellowship Award
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-06-15 至 2017-05-31

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英文摘要
How we perceive the world depends strongly on our recent experience. For example, after briefly looking at a red square or tilted lines, our perception of color or orientation is biased. These adaptation effects have been widely studied and are thought to play an important role in calibrating and optimizing visual coding. This award research aims to test for analogous adaptation and renormalization to the temporal structure of the world. In particular, the goal is to test for normalization in the temporal domain, testing for adaptation to events, to the unfolding of visual images over time, and measuring measure this for both artificial stimuli and for videos of naturalistic events. The research will be conducted in collaboration with Dr. Gerrit Maus of Nanyang Technological University in Singapore, is a leading authority on temporal and visual coding. The research is expected to contribute to the cognitive science of vision and visual adaptation.This study tests whether the patterns of adaptation found for color and form also extend in similar ways to events and time. The project will test how adaptation affects the norms for temporal information, and whether this points to common coding principles in the visual system. The research will test the following hypothesis: if temporal integration of spatial features is perceptually coded based on deviations from a norm (as is the case in other perceptual categories), then visual adaptation will reveal the perceptual norm for naturalistic events, giving important insight in the perception of spatiotemporal integration.This award under the East Asia and Pacific Summer Institutes program supports summer research by a U.S. graduate student and is jointly funded by NSF and the National Research Foundation of Singapore.
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