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: 8737904
• 负责人: JONATHAN A WINAWER
• 金额: $ 23.85万
• 依托单位: NEW YORK UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-30 至 2016-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8737904
• 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; 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

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.

七、项目概要 观看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。这 该提案旨在建立实验和计算基础设施来描述如何 人类视觉系统使用多重成像从简单的时空刺激中汇集信息 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将功能性 MRI 的测量与 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 将进行测量以获得皮质时空感受野的模型。我们 将测试有关这些感受野如何在整个视觉中组织的假设 通路，表征中枢和外周皮层表征之间的差异 以及早期和晚期视觉区域之间。跨空间求和的组织 视觉通路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；颞 后期会强调总结。 在该奖项的指导阶段，将进行一组研究以确定 基本的计算基础设施。将开发一种方法来使用测量 模态来预测另一种模态中的数据。这项工作将涉及空间建模 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 预测电极阵列响应简单视觉刺激的活动模式。对于一个 第二组研究，这些模型将用作解决时间响应的约束 脑电图的功能磁共振成像空间分辨率。两组研究的结果都将得到验证 对临床受试者群体的颅内电极进行测量。计算型 将开发模型以整合跨模式的可视化和分析。 在奖励的独立阶段，将使用功能磁共振成像来研究时间求和 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。同步脑电图和 将进行心理物理学实验来识别相关的神经活动模式 与各种刺激类别的感知。结果的模式将共同提供 考虑跨视觉层次的时间处理如何塑造感知。 指导阶段将在斯坦福大学进行，主要是在斯坦福大学中心 神经生物学成像。这些研究将建立在候选人在功能性 MRI 方面的专业知识的基础上 实验、计算模型和心理物理学。进行和 分析脑电图实验并将结果与​​ MRI 数据联系起来将是 指导阶段的培训。候选人将在期间寻求独立的教职职位 指导阶段的第二年。