Neural circuits for visual feature detection

用于视觉特征检测的神经电路

• 批准号: 9265862
• 负责人: Mark Arthur Frye
• 金额: $ 37.67万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-05-01 至 2021-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9265862
• 关键词: Affect; Alpha Cell; Anatomy; Animals; Attention; Axon; Behavior; Biological Models; Brain; Brain region; Calcium; Cations; Cells; Clutterings; Code; Complex; Computer-Assisted Image Analysis; Cues; Databases; Degenerative Disorder; Dendrites; Detection; Dimensions; Disease; Drosophila genus; Ganglia; Genetic Models; Genetic Techniques; Glutamates; Human; Image; Individual; Insecta; Lead; Life; Light; Location; Mammals; Mathematics; Modeling; Molecular; Motion; Motion Perception; Nervous system structure; Neurobiology; Neurons; Neurotransmitters; Optics; Output; Pathway interactions; Perception; Performance; Perfusion; Pharmacology; Physiological; Physiology; Population; Preparation; Process; Property; Psychophysics; Research; Retina; Retinal; Role; Signal Transduction; Spottings; Stimulus; Stroke; System; Techniques; Testing; Transgenes; Traumatic injury; United States; Vision; Visual; Visual Perception; Visual attention; analog; avoidance behavior; base; detector; disability; experimental study; feeding; fly; gamma-Aminobutyric Acid; imaging system; in vivo calcium imaging; insight; luminance; member; membrane excitation; multi-photon; multiphoton imaging; neural circuit; neurogenetics; neuroregulation; neurotransmitter antagonist; nonhuman primate; novel; optogenetics; public health relevance; receptive field; response; selective attention; spatiotemporal; statistics; therapy development; two-dimensional; two-photon; virtual reality; visual processing

 DESCRIPTION (provided by applicant): A significant percentage of people in the US suffer from disabilities resulting from traumatic injury, stroke, or degenerative disease which result in deficits in visual perception. Therefore, an understanding of the basic circuit neurobiology and neuromodulation of feature-based visual perception will sharpen our understanding of the mechanism of visual processing, and should facilitate the development of treatments for these disabilities. One form of visual attention is targeted to salient features of the visual scene, durng which a subject detects spatio-temporal disparities that distinguish a feature from a cluttered visual surround. The cell-circuit mechanism for how this occurs is not well understood. This project will capitalize on the significant experimental advantages of the fruit fly Drosophila to explore the neural circuits that produce an elementary analogue of feature-based visual attention. The fly has a numerically simple nervous system, with which highly advanced genetic techniques can be used to identify, manipulate, and repeatedly record the activity of individual neurons, as well as their upstream and downstream network partners. The fly also displays robust feature-based visual perception, even under stimulus conditions that defeat classical models of motion vision, for which similar processes have been localized to cortical pathways in humans and non-human primates. The PI hypothesizes that flies detect and process these higher-order features with specialized circuits that integrate first-order elementary motion signals with parallel higher-order spatiotemporal disparities, each of which are sculpted by the action of inhibitory neurotransmitters. The PI will perform two-photon Ca2+ imaging of candidate cellular pathways in response to stimuli the PI has discovered to elicit robust higher-order feature detection by flies within a virtual reality flight simulator. Armed with physiological receptive fields, the PI will examine how feature perception observed during active flight behavior is perturbed by optogenetically silencing these circuits and testing the effects using a systems identification technique that extracts input-output functions of first-order and higher-order feature vision from an intact behaving fly. Finally, the PI will study how specific inhibitor neurotransmitters such as GABA and glutamate sculpt the physiology of feature coding neurons and feature attention behavior.

 描述（由申请人提供）：在美国，相当大比例的人患有由创伤性损伤、中风或退行性疾病导致的残疾，这些疾病导致视觉缺陷。因此，了解基于特征的视知觉的基本回路神经生物学和神经调制将提高我们对视觉处理机制的理解，并应促进这些残疾的治疗方法的发展。一种形式的视觉注意力针对视觉场景的显著特征，在此期间，受试者检测将特征与杂乱的视觉环境区分开的时空差异。这种情况如何发生的细胞回路机制还不清楚。本项目将利用果蝇的显著实验优势，探索产生基于特征的视觉注意的基本模拟的神经回路。果蝇的神经系统在数字上很简单，利用这种神经系统，可以使用高度先进的遗传技术来识别、操纵和重复记录单个神经元及其上游和下游网络伙伴的活动。果蝇还显示出强大的基于特征的视觉感知，即使在击败经典运动视觉模型的刺激条件下，类似的过程已经定位于人类和非人类灵长类动物的皮层通路。PI假设，苍蝇检测和处理这些高阶特征与专门的电路，集成一阶基本运动信号与并行高阶时空差异，其中每一个是由抑制性神经递质的作用雕刻。PI将对候选细胞通路进行双光子Ca 2+成像，以响应PI发现的刺激，从而在虚拟现实飞行模拟器内引起苍蝇的强大高阶特征检测。配备了生理感受野，PI将研究在主动飞行行为期间观察到的特征感知如何通过光遗传学沉默这些电路而受到干扰，并使用系统识别技术测试效果，该技术提取一阶和高阶特征视觉的输入-输出功能。最后，PI将研究特定的抑制剂神经递质，如GABA和谷氨酸如何塑造特征编码神经元和特征注意行为的生理学。