Multimodal Imaging of Spatiotemporal Integration in the Human Visual System

人类视觉系统时空整合的多模态成像

• 批准号: 8223964
• 负责人: JONATHAN A WINAWER
• 金额: $ 9.6万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-03-01 至 2014-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8223964
• 关键词: Accounting; Amblyopia; Area; Award; Basic Science; Blinking; Brain; Brain region; Clinical; Clinical Research; Communities; Computer Simulation; Data; Electrodes; Electroencephalography; Event; Evolution; Eye Movements; Faculty; Failure; Functional Magnetic Resonance Imaging; Head; Human; Image; Imagery; Judgment; Knowledge; Length; Link; Location; Magnetic Resonance Imaging; Maps; Measurement; Measures; Memory; Mentors; Methods; Modality; Modeling; Multimodal Imaging; Nervous system structure; Neural Pathways; Neurobiology; Neurodevelopmental Disorder; Neurons; Neurosciences; Pattern; Perception; Performance; Peripheral; Phase; Population; Positioning Attribute; Process; Property; Psychophysics; Psychophysiology; Relative (related person); Resolution; Scalp structure; Sensory; Shapes; Signal Transduction; Site; Staging; Stimulus; Study models; Testing; Time; Training; Universities; Validation; Visual; Visual Cortex; Visual Fields; Visual Pathways; Visual Perception; Visual system structure; Work; base; computer infrastructure; data modeling; extrastriate visual cortex; flexibility; foot; imaging modality; improved; instrument; model development; predictive modeling; receptive field; relating to nervous system; research study; response; sensor; spatiotemporal; success; tool; trend; visual information; visual map; visual process; visual processing; visual stimulus

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.

描述（由申请人提供）： 视觉需要汇集空间和时间上的信息。神经系统必须适当地整合和分离输入，以便正确解释视觉场景。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模式从简单的时空刺激中汇集信息，并将这些测量结果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 的测量结果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。将进行空间求和测量和时间求和测量以导出皮质时空感受野的模型。我们将测试关于这些感受野如何在整个视觉通路中组织的假设，表征中央和外围皮层表征之间以及早期和晚期视觉区域之间的差异。跨视觉通路的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；后期会强调时间求和。 在该奖项的指导阶段，将进行一组研究来建立基本的计算基础设施。将开发方法以使用一种模态中的测量来预测另一种模态中的数据。这项工作将涉及使用功能磁共振成像对许多视野图的空间总和进行建模，然后使用这些模型来预测电极阵列响应简单视觉刺激的活动模式。对于第二组研究，这些模型将用作约束条件，以在功能磁共振成像的空间分辨率下解决脑电图的时间响应。两组研究的结果将通过临床受试者群体中颅内电极的测量来验证。将开发计算模型以整合跨模式的可视化和分析。 在奖项的独立阶段，将使用功能磁共振成像来研究时间总和，并将结果与​​脑电图的结果进行比较。时间总和的测量将表征不同大脑区域的时间整合周期。将同时进行脑电图和心理物理学实验，以确定与各种刺激类别的感知相关的神经活动模式。结果的模式将共同说明整个视觉层次结构的时间处理如何塑造感知。 指导阶段将在斯坦福大学进行，主要是在神经生物成像中心。这些研究将建立在候选人在功能性核磁共振实验、计算模型和心理物理学方面的专业知识的基础上。进行和分析脑电图实验以及将结果与 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职职位。 公共健康相关性：该研究将描述视觉输入如何在整个皮质视觉通路的空间和时间上整合。这些措施将有助于更好地了解低水平和高水平因素在弱视等神经发育障碍中的相对作用。例如，某些类型的弱视患者有明显的时间缺陷——无法在短时间内正确整合视觉信息。这种失败对视力产生了深远的影响。获得典型发育的视觉系统如何整合信息的模型对于理解和测量神经发育障碍中这些反应的偏差具有重要意义。