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NEURAL BASIS OF VISUAL PATTERN APPEARANCE

NEURAL BASIS OF VISUAL PATTERN APPEARANCE
视觉模式外观的神经基础
批准号:
2487187
负责人:
DAVID J HEEGER
金额:
$22.84万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
1998
资助国家:
美国
项目状态:
已结题
起止时间:
1998-01-01 至 2002-12-31

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英文摘要
DESCRIPTION (Adapted from the Investigator's Abstract): We propose to use functional magnetic resonance imaging (fMRI) in conjunction with psychophysical experiments to establish a link between perceptual appearance and neural activity in human visual cortex. The goal of the proposed research is to understand the neural computations mediated visual pattern appearance. We hypothesize that subjects' psychophysical judgments about pattern appearance are reflected by neural activity in particular visual brain areas. Because the stimuli and the tasks are similar across the proposed experiments, we expect that the neural activity in these brain areas will prove to be good predictors of psychophysical performance in all of the experiments. Functional magnetic resonance imaging (fMRI) is very well-suited for this goal. FMRI is a noninvasive technique that can be used to measure neural activity throughout the occipital lobe of the human brain at a spatial resolution of roughly 2 mm. FMRI can be used to identify the retinotopically organized visual brain areas, so that subsequent data can be analyzed separately within each visual area. A successful demonstration of using fMRI to establish the neural basis of pattern vision would benefit the entire neuroscience community by opening the door for a wide variety of analogous fMRI studies of perception and cognition. To be confident in the proposed approach to this goal, we must demonstrate the feasibility of using fMRI to quantitatively characterize the neurophysiology of human cortex. Therefore, several of the proposed fMRI experiments are designed to measure physiological phenomena that have already been explored with other techniques (single unit recording, optical imaging, VEP). Successful demonstrations that fMRI accurately reflects the underlying neural activity would help lead the way to more powerful uses of this new technology.
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