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: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=648267
• 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.**

视觉被称为扫视的快速眼球运动不断增强，导致在短暂的稳定注视期间频繁出现时空中断。视觉特征跨扫视整合（TSI）是视觉感知的基础，是理解视觉系统中不同信号相互作用的理想模型系统。在我们之前由nserc资助的研究中，我们发现了一个与TSI有关的皮层区域网络，包括额叶和顶叶视野、背外侧前额叶皮层和早期视觉皮层。但是到目前为止，跨眼球特征存储和整合发生的关键位点仍然是难以捉摸的。***最近，我们使用fMRIa（适应）范式在边缘上回（SMG）中发现了一个区域，紧邻人类顶叶视野，似乎直接参与跨扫视的目标定向整合。SMG位于顶叶下小叶，位于顶叶上皮层和颞叶皮层之间，令人感兴趣，因为它与复杂的视觉行为有关，并且已经涉及到“背流”（空间/感觉运动）和“腹流”（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关注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和生理实验生成模拟预测；2)fmri适应协议来确认SMG在不同类型的特征整合、参考框架和眼动类型的整合中所起的作用；3)扩散张量成像来了解SMG与参与跨眼动整合的大脑其他区域的联系。4) fmri引导的经颅磁刺激（TMS）定位SMG信号在视觉空间整合中的因果作用，5)脑磁图（MEG）研究SMG与其他TSI部位的时间和同步性，以及6)动物神经生理学探索在执行类似TSI任务训练的猴子中SMG的详细细胞反应。***明确SMG在TSI中的具体机制和作用将为理解主动视觉提供重要的进展。此外，我们对SMG区域的战略关注可以回答神经科学中的一个基本问题：证明顶叶下小叶在认知和行为中整合背侧和腹侧流信号的关键作用。这个主题（TSI）在人机交互和计算机视觉领域有许多应用，从交通运输到机器人技术。最后，我们独特多样的技术组合将为学生和博士后提供一个强大的训练基地