Cortical Networks for Eye-Hand Coordination in the Human

人类神经成像已经成功地绘制了大脑皮层的功能解剖图，但我们还不清楚这些皮质区域是如何与现实世界的认知和行为相互作用的。例如，视觉皮质如何与其他感觉和运动区(即眼睛、头部、手臂和手)相互作用，产生构成大多数日常行为基础的“简单”眼手协调，这一点尚不清楚。为了研究这些基本问题，我们将利用各种神经成像和脑刺激技术，结合大规模的功能连通性分析来了解信号在皮质区域之间是如何共享的。在这一授权期内，我们将专注于以下科学问题：1.大脑皮质网络的局部着丝点编码与自我中心编码。在以前的研究中，我们确定了以眼睛为中心和以地标为中心的REACH目标记忆的皮质部位，以及它们的整合部位。在这里，我们将使用神经成像来研究这些功能的皮质“中枢”和网络，使用安全的大脑刺激技术来干扰它们，然后通过将神经成像与脑刺激相结合来将它们联系起来。2.REACH-GRAPH协调的大脑皮层网络大脑皮层的伸展和抓取区域已经确定，但还不知道它们是如何协调的。我们将使用线索分离范式(到达和抓取在时间上分开的指令)，结合解码和连通性分析来识别整合信号以进行协调抓取的枢纽和网络。3.REACH与Placement的皮质网络。许多研究已经研究了抓住物体的大脑皮层机制，但很少有人研究大脑如何控制这些物体的放置。我们将使用神经成像和功能连接分析来区分这些过程以及眼球运动的影响。我们假设，在这两个任务中，相同的伸展/抓取区域将被激活，但网络模块将发生变化，当眼球运动需要跨视野共享信息时，会有进一步的修改。4.将眼位整合到REACH计划中的皮质网络。在躯体感觉皮层中发现了一个“眼睛位置”区域，但这些信号在运动控制中的作用仍存在争议。我们将通过在凝视和触觉分离的任务中结合神经成像和脑刺激来测试这一点。我们假设对眼睛位置区域的刺激会影响运动区，导致视线相关的视距误差。这种全脑方法代表了人类神经科学的一个概念转折点。具体地说，为了了解不同的大脑区域如何共享/分离感觉运动信号，以形成跨越所有四个皮质叶的功能网络。这对加拿大医疗保健(因为这些网络受到许多疾病的影响)和工业(例如，用于激发自适应机器人控制系统的分布式模型)具有重要的应用。

Human neuroimaging has successfully mapped the functional anatomy of the cerebral cortex, but we do not yet understand how these cortical areas interact for real world cognition and behavior. For example, it is not known how visual cortex interacts with other sensory and motor areas (i.e., for the eyes, head, arm, & hands) to produce the `simple' eye-hand coordination that underlies most daily behaviors. To investigate these fundamental issues, we will utilize various neuroimaging and brain stimulation techniques, combined with large scale functional connectivity analysis to understand how signals are shared between cortical areas. For this grant period, we will focus on the following scientific issues: 1. Cortical Networks for Allocentric versus Egocentric Coding. In previous studies we identified cortical sites for eye-centred vs. landmark centered memory of reach goals, and sites for their integration. Here we will use neuroimaging to investigate the cortical `hubs' and networks for these functions, perturb them using safe brain stimulation techniques, and then link these by combining neuroimaging with brain stimulation. 2. Cortical Networks for Reach-Grasp Coordination. Cortical reach and grasp areas have been identified, but it is not known how they are coordinated. We will use a cue-separation paradigm (reach and grasp instructions separated in time), combined with decoding and connectivity analysis to identify the hubs and networks that integrate signals for coordinated grasp. 3. Cortical Networks for Reach vs. Placement. Numerous studies have investigated the cortical mechanisms for grasping objects, but few have investigated how the brain controls placement of those objects. We will differentiate these processes, and the influence of eye movements, using neuroimaging and functional connectivity analysis. We hypothesize that the same reach/grasp areas will be activated in both tasks but network modularity will change, with further modifications when eye movements necessitate sharing of information across visual fields. 4. Cortical Networks for Integration of Eye Position into the Reach Plan. An `eye position' region has been identified in somatosensory cortex, but the role of these signals in movement control remains controversial. We will test this by combining neuroimaging and brain stimulation during a task where gaze and reach are dissociated. We hypothesize that stimulation of the eye position area will influence the motor areas, causing gaze-dependent reach errors. This whole-brain approach represents a conceptual turning point for human neuroscience. Specifically, toward understanding how different brain areas share / segregate sensorimotor signals to form functional networks across all four cortical lobes. This has important applications for Canadian healthcare (since these networks are affected by many diseases) and industry (e.g., for inspiring distributed models for adaptive robotic control systems).