Multimodal Imaging of Spatiotemporal Integration in the Human Visual System

7.项目总结 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。这个 一项提案寻求建立实验和计算基础设施，以表征 人类视觉系统利用多重成像从简单的时空刺激中汇集信息 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将来自功能磁共振的测量结果与 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。空间求和度量与时间求和 将进行测量以推导出大脑皮层时空感受场的模型。我们 将测试关于这些感受性区域在整个视觉系统中是如何组织的假设 中枢和外周皮质表现之间的差异 以及早期和晚期视觉区域之间。跨区域的空间求和组织 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总和；时间 总结将在后面的阶段强调。 在授奖的指导阶段，将进行一组研究，以确定 基本的计算基础设施。将开发一种使用测量方法的方法 以另一种模式预测数据的模式。这项工作将涉及到空间建模 使用功能磁共振成像对许多视野图进行求和，然后使用这些模型 预测响应简单视觉刺激的跨电极阵列的活动模式。为. 第二组研究，这些模型将被用作解析时间反应的约束 以fMRI的空间分辨率与EEG进行比较。这两组研究的结果都将得到验证 通过对临床受试者人群中的颅内电极进行测量。计算型 将开发模型，以整合各种模式的可视化和分析。 在奖项的独立阶段，将使用fmri研究时间总和。 并将结果与EEG结果进行了比较。时间总和的测量将 表征不同脑区的时间整合周期。同步脑电和脑电 将进行心理物理实验，以确定相关的神经活动模式 对不同的刺激类别有感知。综合起来，结果的模式将提供 描述跨越视觉层次的时间处理如何塑造知觉。 指导阶段将在斯坦福大学进行，主要是在 神经生物学成像。这些研究将建立在候选人在功能磁共振方面的专业知识的基础上 实验、计算模型和心理物理学。指挥和指挥方面的培训 分析EEG实验并将结果与MRI数据相关联将是 指导阶段的培训。候选人将在年内寻求一个独立的教职。 指导阶段的第二年。

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.