Neural circuits for visual feature detection

用于视觉特征检测的神经电路

基本信息

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
项目类别：
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

项目摘要

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，很大一部分人因外伤、中风或退行性疾病而患有残疾，导致视觉感知缺陷，因此，需要了解基本回路神经生物学和特征的神经调节。基于视觉感知的视觉注意力将加深我们对视觉处理机制的理解，并有助于开发针对这些障碍的治疗方法。将特征与杂乱的视觉环境区分开的时空差异如何发生的细胞回路机制尚不清楚，该项目将利用果蝇的显着实验优势来探索产生这种现象的神经回路。基于特征的视觉注意力的基本类似物，苍蝇有一个数字上简单的神经系统，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。。果蝇还表现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，类似的过程也被定位于人类和非人类灵长类动物的皮层通路，并具有集成的专门电路。具有并行高阶时空差异的一阶基本运动信号，每个信号都是由抑制性神经递质的作用塑造的，PI将对候选者执行双光子 Ca2+ 成像。 PI发现，在虚拟现实飞行模拟器中，果蝇响应刺激的细胞通路能够引发强大的高阶特征检测，PI将检查在主动飞行行为期间观察到的特征感知如何受到光遗传学沉默的干扰。这些电路并使用系统识别技术测试其效果，该技术从完整的行为果蝇中提取一阶和高阶特征视觉的输入输出函数。最后，PI 将研究特定抑制剂神经递质的作用。 GABA 和谷氨酸塑造特征编码神经元的生理学和特征注意力行为。