Multimodal Imaging of Spatiotemporal Integration in the Human Visual System

描述（由申请人提供）：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，以正确地解释视觉场景。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如何使用多种成像方式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功能性MRI的测量与头皮和颅内电极相结合。测量人脑功能的不同仪器具有非常不同的灵敏度。将进行空间总和测量和时间总和测量，以导出皮层时空感受野的模型。我们将测试这些感受野是如何组织在整个视觉通路的假设，中央和周边皮质表征之间的差异和早期和晚期视觉区域之间的特征。视觉通路中空间求和的组织比时间求和的组织更容易理解。因此，在模型开发和验证中将强调空间求和;在稍后阶段将强调时间求和。 在该奖项的指导阶段，将进行一组研究，以建立基本的计算基础设施。将开发使用一种模态中的测量来预测另一种模态中的数据的方法。这项工作将涉及使用fMRI对许多视野图的空间求和进行建模，然后使用这些模型来预测电极阵列对简单视觉刺激的反应模式。对于第二组研究，这些模型将被用来作为约束，以解决与EEG的fMRI的空间分辨率的时间响应。将通过在临床受试者人群中测量颅内电极来验证两组研究的结果。将开发计算模型，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和结果相比，从脑电图。时间总和的测量将表征不同脑区的时间整合期。同时进行脑电图和心理物理实验，以确定与各种刺激类的感知相关的神经活动模式。结果的模式将提供一个跨视觉层次的时间处理如何塑造感知的帐户。 指导阶段将在斯坦福大学进行，主要是在神经生物学成像中心。这些研究将建立在候选人在功能性MRI实验，计算建模和心理物理学方面的专业知识基础上。进行和分析EEG实验以及将结果与MRI数据相关联的培训将是指导阶段培训的重要组成部分。候选人将在指导阶段的第二年寻求独立的教师职位。 公共卫生相关性：该研究将描述视觉输入如何在整个皮层视觉通路中随时间和空间进行整合。这些措施将使我们能够更好地了解神经发育障碍，如弱视的低层次和高层次的因素的相对贡献。例如，某些类型的弱视有明显的时间缺陷-无法在短时间内正确整合视觉信息。这种失败对视觉能力有着深远的影响。获得模型的典型发展的视觉系统如何整合信息将是有价值的理解和测量偏离这些反应的神经发育障碍。

DESCRIPTION (provided by applicant): 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. PUBLIC HEALTH RELEVANCE: The study will characterize how visual inputs are integrated over space and time throughout the cortical visual pathways. These measures will enable a better understanding of the relative contribution of low-level and high-level factors in neurodevelopmental disorders, such as amblyopia. Certain types of amblyopes, for example, have significant temporal deficits - a failure to properly integrate visual information over short intervals. This failure has a profound impact on the ability to see. Obtaining models of how the typically developing visual system integrates information will be of value in understanding and measuring deviations from these responses in neurodevelopmental disorders.