Neural correlates of active vision

主动视觉的神经相关性

• 批准号: RGPIN-2020-06018
• 负责人: Niemeier, Matthias
• 金额: $ 2.4万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=764218
• 关键词: Neural; correlates; active; vision

Major insights into the brain's processes come from studying how processes are modulated by top-down effects. Specifically, there is growing interest in how actions shape perception. Brain imaging has deepened the understanding of the neural networks engaged in visuomotor transformations. Yet there is little knowledge of the temporal aspects of these transformations, because brain imaging cannot resolve small details in time, and because electroencephalography (EEG) comes at the expense of poor spatial resolution. Thus, there is little understanding of how action-dependent activation of perception regions evolves in time. Recent advances in multivariate analysis, however, have demonstrated that EEG data recorded from the human scalp allow for detailed insights into the time course of visual and visuomotor computations. The objectives of my research project are - show that the brain's preparations for actions trigger activity in perceptual areas that carry information about the objects of actions, and to identify the purpose of these action-dependent activations - identify the patterns of brain activity in space and time that bind together information about multiple aspects of objects targeted by actions - identify the spatial coordinate systems in which action-dependent perceptual information works I will use multivariate EEG analysis, alone or in combination with brain imaging. Theme 1 of my project aims to show that EEG signals reflect visual information about object shapes that builds up aligned in time with subsequent grasp but not reach movements which require no shape information. I will test information about which object parts are embedded in the EEG signals (probably parts near the points where participants will grasp). I will test EEG responses to objects that feel different from what they look like to probe for action control mechanisms. Also, I will probe for interference between grasping and working memory. Theme 2 will investigate the neural correlates of action-dependent enhancement of multiple visual aspects about objects conveying information about shape, size, and weight of objects features important to plan grasping. I will use EEG together with brain imaging to integrate detailed temporal and spatial information about brain activity. Theme 3 will be concerned with the influences of hand positions, eye movements as well as object orientations on action-dependent activation of visual shape information. In sum, the proposed research will pursue a comprehensive approach to investigating some of the major action-related top--down influences on vision, effectively using these mechanisms as a lens to study the visual system in action. The outcome of this research has the potential to further our understanding of the brain as a dynamic system that shapes its perceptual processes, depending on its goals and actions with additional important implications for the development of future brain-computer interfaces.

对大脑过程的主要见解来自于研究过程如何受到自上而下效应的调节。具体来说，人们对行为如何塑造感知越来越感兴趣。脑成像加深了对参与视觉转换的神经网络的理解。然而，人们对这些转换的时间方面知之甚少，因为大脑成像无法及时解决小细节，而且脑电图（EEG）的空间分辨率很差。因此，很少有人了解感知区域的动作依赖性激活如何随时间演变。然而，多变量分析的最新进展表明，从人类头皮记录的EEG数据允许详细了解视觉和视觉计算的时间过程。我的研究项目的目标是-表明大脑的准备行动触发活动的知觉领域，携带有关的信息对象的行动，并确定这些依赖于动作的激活的目的-确定大脑活动在空间和时间上的模式，这些模式将关于动作所针对的对象的多个方面的信息结合在一起-确定动作的空间坐标系-依赖知觉信息的工作原理我将使用多元脑电图分析，单独或结合脑成像。 我的项目的主题1旨在表明，EEG信号反映了物体形状的视觉信息，这些信息在时间上与随后的抓握保持一致，但不需要形状信息的运动。我将测试EEG信号中嵌入的对象部分的信息（可能是参与者将抓住的点附近的部分）。我将测试脑电图对感觉与外观不同的物体的反应，以探测动作控制机制。此外，我将探讨之间的干扰把握和工作记忆。主题2将研究神经相关的动作依赖性增强的多个视觉方面的对象传达信息的形状，大小和重量的对象功能重要的计划抓。我将使用脑电图结合脑成像来整合有关大脑活动的详细时空信息。 主题3将关注手的位置，眼动以及物体的取向对视觉形状信息的动作依赖激活的影响。 总之，拟议的研究将寻求一个全面的方法来调查一些主要的行动相关的自上而下的视觉影响，有效地利用这些机制作为一个透镜来研究视觉系统的行动。这项研究的结果有可能进一步加深我们对大脑的理解，将其视为一个动态系统，根据其目标和行动来塑造其感知过程，并对未来脑机接口的发展产生额外的重要影响。