Role of Supramarginal Gyrus in the Integration of Visual Features Across Eye Movements

边缘上回在眼球运动视觉特征整合中的作用

• 批准号: RGPIN-2016-05359
• 负责人: Crawford, John
• 金额: $ 4.44万
• 依托单位: York University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=709152
• 关键词: Role; Supramarginal; Gyrus; Integration; Visual

Vision is constantly augmented by rapid eye movements called saccades, resulting in frequent spatiotemporal interruptions between brief periods of stable fixation. Trans-saccadic integration of visual features (TSI) is thus fundamental to visual perception, and forms an ideal model system for understanding interactions between different signals in the visual system. In our previous NSERC-funded work we identified a network of cortical areas that contribute to TSI, including the frontal and parietal eye fields, dorsolateral prefrontal cortex, and early visual cortex. But until now, the key site(s) where trans-saccadic feature storage and integration occurs has remained elusive. Recently, using an fMRIa (adaptation) paradigm we identified an area in the supramarginal gyrus (SMG), immediately adjacent to the human parietal eye fields, that appears to be directly involved in the integration of object orientation across saccades. The SMG located in the inferior parietal lobule and couched between the superior parietal and temporal cortices is intriguing because it is associated with complex visual behaviors and has already been implicated in the integration of dorsal stream' (spatial/sensorimotor) and ventral stream' (feature/object) visual signals. Motivated by this exciting finding and its broader implications, we aim to focus on the key role of SMG in the TSI network through a trans-disciplinary approach. We will use 1) state-space models of spatial updating and feature integration to generate simulated predictions for our psychophysical and physiological experiments, 2) fMRIa adaptation protocols to confirm SMG's role in integration for different types of feature integration, frames of reference, and types of eye movement, 3) diffusion tensor imaging to understand its connections with other areas of the brain involved in trans-saccadic integration, 4) fMRI-guided Trans-cranial magnetic stimulation (TMS) to localize the causal role of SMG signals for visuospatial integration, 5) magnetoencephalography (MEG) to investigate the timing and synchrony of SMG with other TSI sites, and 6) animal neurophysiology to explore the detailed cellular responses of SMG in monkeys trained to perform similar TSI tasks. Establishing the specific mechanism and role of SMG in TSI will provide an important advance for understanding active vision. But further, our strategic focus on area SMG could answer a fundamental question in neuroscience: demonstration of a key role of the inferior parietal lobule in the integration of dorsal and ventral stream signals for cognition and behavior. This topic (TSI) has numerous applications for human-computer interaction and computer vision, in areas ranging from transportation to robotics. Finally, our uniquely diverse combination of techniques will provide a powerful training ground for students and post-doctoral fellows.

视觉通过快速的眼球运动（称为扫视）不断增强，导致短暂的稳定注视之间频繁的时空中断。因此，视觉特征的跨扫视整合（TSI）是视觉感知的基础，并形成了一个理想的模型系统，用于理解视觉系统中不同信号之间的相互作用。在我们之前的NSERC资助的工作中，我们确定了一个有助于TSI的皮层区域网络，包括额叶和顶叶眼区，背外侧前额叶皮层和早期视觉皮层。但到目前为止，跨扫视特征存储和整合发生的关键部位仍然难以捉摸。 最近，使用fMRIa（适应）范例，我们确定了一个区域的缘上回（SMG），紧邻人类顶叶眼场，似乎是直接参与整合的对象方向扫视。SMG位于顶下小叶，位于上级顶叶和颞叶之间，与复杂的视觉行为相关，并参与背侧流（空间/感觉运动）和腹侧流（特征/物体）视觉信号的整合。 受这一令人兴奋的发现及其更广泛的影响的激励，我们的目标是通过跨学科的方法专注于SMG在TSI网络中的关键作用。我们将使用1）空间更新和特征整合的状态空间模型来为我们的心理物理学和生理学实验生成模拟预测，2）fMRI a适应协议来确认SMG在不同类型的特征整合、参考系和眼动类型的整合中的作用，3）扩散张量成像以了解其与涉及跨扫视整合的大脑其他区域的连接，4）fMRI引导的经颅磁刺激（TMS），以定位SMG信号对视觉空间整合的因果作用，5）脑磁图（MEG），以研究SMG与其他TSI部位的定时和同步性，6）动物神经生理学，以探索SMG在训练执行类似TSI任务的猴子中的详细细胞反应。 明确SMG在TSI中的具体作用机制，将为进一步理解主动视觉提供重要的理论依据。但是，我们对SMG区域的战略重点可以回答神经科学中的一个基本问题：证明顶下小叶在整合认知和行为的背腹流信号中的关键作用。该主题（TSI）在从交通运输到机器人等领域的人机交互和计算机视觉方面有许多应用。最后，我们独特多样的技术组合将为学生和博士后研究员提供强大的培训基地。