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Identifying selective visual attention mechanisms through high-dimensional analysis.

通过高维分析识别选择性视觉注意机制。

基本信息

批准号：
9127978
负责人：
Adam Christopher Snyder
金额：
$ 9.63万
依托单位：
CARNEGIE-MELLON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-09-01 至 2018-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9127978
关键词：
Achievement Affect Area Attention Attention Deficit Disorder Autistic Disorder Automobile Driving Basic Science Behavioral Brain Cerebral cortex Clinical Research Code Complex Data Data Set Disease Electric Stimulation Electrophysiology (science)Feedback Fire - disasters Foundations Future Goals Grant Health Individual Investigation K-Series Research Career Programs Knowledge Learning Life Linear Models Link Location Measures Memory Mentors Mentorship Methods Microelectrodes Modeling Monkeys Motor Motor Cortex Movement Nature Neurons Output Pattern Perception Population Preparation Primates Process Professional Practice Property Research Research Project Grants Schizophrenia Scientist Sensory Sensory Process Signal Transduction Site Source Stimulus Structure Techniques Testing Therapeutic Intervention Training Translating Universities Vision Disorders Visual Visual Cortex Visual attention area V4 base career cognitive ability dimensional analysis electrical microstimulation extrastriate visual cortex frontal eye fields frontal lobe inattention information processing innovation microstimulation neural prosthesis premature relating to nervous system research study retinotopic selective attention sensory cortex tool

项目摘要

DESCRIPTION (provided by applicant): The visual world contains more information than the brain can process. Fortunately, we have some ability to influence which sources of information receive processing priority through the mechanism of selective attention, and this ability is critical for daily life. While much research has focused on the effects of attention on information processing, relatively little remains known about how attention states are established. This is because clear effects of attention preparation at the level of single neurons have not been forthcoming. Recently, movement preparation has been linked to activity patterns that can be identified by analyzing dozens of neurons together. Such `high-dimensional' analyses have not been applied to sensory brain areas however, and we reasoned that a similar approach may overcome the barriers to progress in explaining attention preparation in sensory cortex. The goal of this research project is to apply high-dimensional analyses to the neuronal activity in sensory cortex in order to characterize how attention states are established. We have developed a carefully titrated research strategy that will achieve this overarching goal through three systematic and specific aims. We will begin by identifying the activity patterns in visual cortex that correlate with attention and inattention, both in the context of attention to spatial locations and in the context of attention to visual features. We will then add a layer of complexit by analyzing neuronal activity recorded from both visual cortex and frontal cortex -a presumed source of attention control signals -to identify the processes that drive these preparatory attention states. Finally, to test the causal nature of the neuronal correlates identified by the preceding two aims, we will use microstimulation in frontal cortex in an effort to mimic the neural and behavioral effects of attentional preparation. Since this is a career development award, another major goal of this project is the training of Dr. Adam C. Snyder in the high-dimensional analysis methods (under the mentorship of Dr. Byron Yu of Carnegie Mellon University) and experimental techniques (under the mentorship of Dr. Matthew Smith of the University of Pittsburgh) required for the achievement of the research aims, as well as the professional practices that will be needed throughout his career as an independent scientist. At the end of this project, Dr. Snyder will have received first-rate training in the analysis of high-dimensional datasets and practices of primate electrophysiology, strengthening his foundation as an innovative and successful neuroscientist. From a scientific perspective, we will have developed a new model of attention preparation that will overcome a long-standing barrier to progress in attention research. This advancement will not only benefit attention research itself, but will provide a framework for future investigations of other brain processes that involve feedback modulation of sensory processing, such as learning and memory. An understanding of the functioning of attention in health individuals is essential to guide potential therapeutic interventions in disorders involving deficits in attention, including autism, schizophrenia and attention deficit disorder.

描述（由申请人提供）：视觉世界包含的信息比大脑可以处理的更多。幸运的是，我们有能力通过选择性注意机制影响哪些信息源获得优先处理，这种能力对日常生活至关重要。虽然许多研究都集中在注意力对信息的影响上，在处理过程中，关于注意力状态是如何建立的知之甚少。这是因为在单个神经元水平上注意准备的明确效果尚未出现。最近，运动准备与活动模式有关，可以通过分析数十个神经元来识别。然而，这种“高维”分析尚未应用于感觉脑区，我们推断，类似的方法可能会克服在解释感觉皮层的注意准备方面的障碍。本研究的目标是应用高维分析的感觉皮层的神经元活动，以表征如何建立注意状态。我们已经制定了一个精心滴定的研究战略，将通过三个系统和具体的目标实现这一总体目标。我们将开始通过识别与注意力和注意力不集中相关的视觉皮层的活动模式，无论是在注意空间位置的背景下，还是在注意视觉特征的背景下。然后，我们将通过分析从视觉皮层和额叶皮层记录的神经元活动（注意力控制信号的假定来源）来添加一层复合物，以确定驱动这些预备注意力状态的过程。最后，为了测试由前两个目标确定的神经元相关性的因果性质，我们将在额叶皮层中使用微刺激来模拟神经元相关性。和注意力准备的行为效应。由于这是一个职业发展奖，这个项目的另一个主要目标是培养博士。斯奈德在高维分析方法（在卡内基梅隆大学的拜伦·余博士的指导下）和实验技术（在匹兹堡大学的马修·史密斯博士的指导下）需要实现研究目标，以及在整个职业生涯中需要作为一个独立的科学家的专业实践。在这个项目结束时，斯奈德博士将在高维分析方面接受一流的培训。灵长类动物电生理学的数据集和实践，加强了他作为创新和成功的神经科学家的基础。从科学的角度来看，我们将开发出一种新的注意力准备模型，它将克服长期以来阻碍注意力研究进展的障碍。这一进展不仅有利于注意力研究本身，而且将为未来研究其他涉及感觉处理反馈调节的大脑过程（如学习和记忆）提供一个框架。了解健康个体的注意力功能对于指导涉及注意力缺陷的疾病（包括自闭症、精神分裂症和注意力缺陷障碍）的潜在治疗干预至关重要。