Multimodal Imaging of Spatiotemporal Integration in the Human Visual System

7.项目摘要 观看需要在空间和时间上汇集信息。神经系统必须 适当地整合和分离输入，以便正确地解释视觉场景。的 该提案旨在建立实验和计算基础设施，以表征 人类视觉系统使用多重成像从简单时空刺激汇集信息 模态，并将这些测量与视觉感知联系起来。 该提案的一个关键组成部分是联合收割机功能性MRI的测量结果与 头皮和颅内电极。测量人脑功能的不同仪器 有非常不同的敏感性。空间求和测量和时间求和 将进行测量以导出皮层时空感受野的模型。我们 我将测试关于这些感受野在整个视觉过程中是如何组织的假设。 通路，表征中枢和外周皮质代表之间的差异 以及早期视觉区和晚期视觉区之间。空间求和的组织跨越了 视觉路径比时间总和的组织更容易理解。空间 因此，在模型开发和验证中将强调求和;时间 在后面的阶段将强调总结。 在该奖项的指导阶段，将进行一系列研究，以确定 基本的计算基础设施。将制定方法，在一个 模态来预测另一模态中的数据。这项工作将涉及空间建模 使用fMRI对许多视野图进行求和，然后使用这些模型 预测电极阵列对简单视觉刺激的反应模式。用于 在第二组研究中，这些模型将用作解决时间响应的约束条件 用脑电扫描功能磁共振成像的空间分辨率将对两组研究的结果进行验证 在临床受试者群体中测量颅内电极。计算 将开发各种模型，以整合各种模式的可视化和分析。 在独立阶段的奖励，时间总和将研究与功能磁共振成像 并将结果与EEG结果进行比较。时间总和的测量将 表征不同脑区的时间整合期。同时进行EEG和 将进行心理物理学实验，以确定相关的神经活动模式 对各种刺激类别的感知。结果的模式将提供一个 解释了视觉层次中的时间处理如何塑造感知。 指导阶段将在斯坦福大学进行，主要是在中心， 神经生物学成像。这些研究将建立在候选人在功能磁共振成像方面的专业知识基础上 实验、计算建模和心理物理学。进行培训， 分析EEG实验并将结果与MRI数据相关联将是本研究的重要组成部分。 在辅导阶段进行培训。候选人将寻求一个独立的教师职位， 第二年的辅导阶段。

7. Project Summary Seeing requires pooling information over space and time. The nervous system must appropriately integrate and segregate inputs in order to correctly interpret visual scenes. The proposal seeks to build experimental and computational infrastructure to characterize how the human visual system pools information from simple space-time stimuli using multiple imaging modalities, and to relate these measurements to visual perception. A key component of the proposal is to combine measurements from functional MRI with scalp and intracranial electrodes. The different instruments for measuring human brain function have very different sensitivities. Spatial summation measurements and temporal summation measurements will be conducted to derive models of cortical space-time receptive fields. We will test hypotheses about how these receptive fields are organized throughout the visual pathways, characterizing differences between central and peripheral cortical representations and between early and late visual areas. The organization of spatial summation across the visual pathways is better understood than the organization of temporal summation. Spatial summation will therefore be emphasized in model development and validation; temporal summation will be emphasized in later stages. In the mentored phase of the award, one set of studies will be conducted to establish the basic computational infrastructure. Methods will be developed to use measurements in one modality to predict data in another modality. This work will involve modeling spatial summation across the many visual field maps using fMRI, and then using these models to predict the pattern of activity across electrode arrays in response to simple visual stimuli. For a second set of studies, these models will be used as constraints to resolve temporal responses with EEG at the spatial resolution of fMRI. Findings from both sets of studies will be validated with measurements of intracranial electrodes in a clinical subject population. Computational models will be developed to integrate visualization and analysis across the modalities. In the independent phase of the award, temporal summation will be studied with fMRI and the results compared against those from EEG. Measurements of temporal summation will characterize the temporal integration period of different brain areas. Concurrent EEG and psychophysical experiments will be conducted to identify the neural activity patterns associated with perception of various stimulus classes. Together the pattern of results will provide an account of how temporal processing across the visual hierarchy shapes perception. The mentored phase will take place at Stanford University, mostly in the Center for Neurobiological Imaging. The studies will build on the candidate's expertise in functional MRI experiments, computational modeling, and psychophysics. Training in conducting and analyzing EEG experiments and relating the results to MRI data will be a significant part of the training in the mentored phase. The candidate will seek an independent faculty position during the second year of the mentored phase.