NEURAL BASIS OF VISUAL PATTERN APPEARANCE
NEURAL BASIS OF VISUAL PATTERN APPEARANCE
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
中文摘要
点击翻译按钮获取中文摘要
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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