CRCNS: Model-driven single-neuron studies of cortical mapping

描述（由申请人提供）：在自然视觉过程中，人类和非人类灵长类动物每秒进行几次眼球跳动，导致视网膜输入发生巨大变化。尽管经常有这些戏剧性的变化，但我们的视觉感知仍然非常稳定，我们可以很容易地注意到并指导我们对视觉环境中的物体的运动动作。该项目将使用模型驱动的方法来研究连接视觉、注意力和动眼肌规划的神经回路，这些神经回路在自然视觉过程中稳定知觉和注意力表征。实验数据将被收集并用于设计一个涉及扫视补偿的视觉和动眼区的详细计算模型。计算（DE）和实验神经生理学（US）实验室之间拟议的合作利用了两个学科的力量。Hamker实验室开发的视觉引导行为和跨眼球整合的生物学精确模型将指导从清醒的神经生理学实验中获得的数据的设计和解释，行为灵长类动物在Mazer实验室以迭代的方式进行，实验结果为模型修订提供信息，新模型预测改变实验设计。本研究将探讨背侧和腹侧流视觉区对稳定灵长类大脑视觉和注意力表征的贡献。从这些实验中获得的数据将确定负责整合动眼肌命令、自下而上的视觉输入和自上而下的注意信号的神经回路。这种方法将对自然视觉过程中背侧和腹侧流之间的相互作用产生新的见解，并促进我们对目标导向、主动视觉感知的理解，这是人类和非人类灵长类动物自然视觉的一个决定性特征。这个项目的一个关键组成部分是计划研究的高度协作性质。我们期望从这种跨学科的方法中获得巨大的好处，这种方法严格依赖于严格遵守已知生理和解剖学约束的计算模型来指导我们的神经生理学实验。

DESCRIPTION (provided by applicant): During natural vision humans and non-human primates make several saccadic eye movements each second that result in large changes in the retinal input. Despite these often dramatic changes, our visual percept remains remarkably stable and we can readily attend to and direct motor actions towards objects in our visual environment. This project will use a model-driven approach to investigate the neural circuits linking vision, attention and oculomotor planning that stabilize perceptual and attentional representations during natural vision. Experimental data will be collected and used to design a detailed computational model of the visual and oculomotor areas involved in saccade compensation. The proposed collaboration between a computational (DE) and experimental neurophysiological (US) laboratories leverages the power of both disciplines. Biologically accurate models of visually guided behavior and trans-saccadic integration developed in the Hamker lab will guide the design of and interpretation of data obtained from neurophysiological experiments in awake, behaving primates performed in the Mazer lab in an iterative fashion, with experimental results informing model revisions and new model predictions altering experimental designs. The proposed studies will characterize both dorsal and ventral stream visual area contributions to stabilizing visual and attentional representations in the primate brai. Data obtained from these experiments will identify the neural circuits responsible for integrating oculomotor commands, bottom-up visual inputs and top-down attention signals. This approach will yield novel insights into interactions between the dorsal and ventral streams during natural vision and facilitate our understanding of goal-directed, active visual perception, a defining feature of human and non-human primate natural vision. A critical component of this project is the highly collaborative nature of the planned research. We expect great benefits from this interdisciplinary approach, which depends critically on computational models that strictly adhere to the known physiological and anatomical constraints to guide our neurophysiological experiments. 1. Training. The proposal includes a detailed training plan intended to facilitate international training of future modelers and neurophysiologists. Specifically, we will train students and post-doctoral researchers to be experts in both experimental and theoretical approaches in order to advance the field using the hybrid approach outlined in the proposal. 2. Education and Outreach. We plan to organize two in-depth workshops on attention and eye movements. These events (one in Germany and one in the US) will bring together investigators from other institutions and related scientific disciplines to advance the field. In addition investigators will organize and chair 1-2 workshops/symposia at annual meetings (e.g., SFN and COSYNE) during the funding period. Finally, we will participate in science education for underrepresented groups through Yale's STARS program by providing training, research and mentoring opportunities in the Mazer lab. 3. Data Sharing. The software tools generated and behavioral and neurophysiological data collected during this project will be distributed to the neuroscience community to facilitate data mining and secondary analyses of experimental data. 4. Impact in other scientific fields. Efficient allocation of limited sensor resources is also a important problem faced by computer vision and robotics researchers. Understanding how the primate brain efficiently allocates visual resources using an active-sensing approach will guide development of biologically inspired computer vision algorithms and humanoid cognitive robots. 5. Translational Implications. Although the proposed research is not translational, there is a growing body of evidence suggesting that several clinically important conditions, including Autism Spectrum Disorder, Attention Deficit Hyperactivity Disorder and Schizophrenia, are associated with impaired behavioral links between saccade planning and visual attention. The proposed basic science studies could have significant implications for future translational research potentially leading to improved understanding disease etiology, development of early diagnostic tools and possible interventional strategies.