Neuronal Mechanisms of Multiplication and Invariance

乘法和不变性的神经机制

• 批准号: 8504032
• 负责人: FABRIZIO GABBIANI
• 金额: $ 39.13万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-06-01 至 2018-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8504032
• 关键词: Address; Animals; Attention; Biological Models; Biophysics; Calcium; Cell model; Cells; Complex; Data; Dendrites; Disease; Exhibits; Experimental Models; Generations; Goals; Image; Individual; Invertebrates; Membrane; Mental disorders; Modeling; Monitor; Motion; Motor; Movement; Nervous system structure; Neuraxis; Neurons; Output; Pathway interactions; Pattern; Perception; Photic Stimulation; Play; Preparation; Property; Research; Role; Sensory; Shapes; Signal Transduction; Stimulus; Synapses; System; Techniques; Texture; Time; Transfection; Trees; Viral; Visual Perception; Visual attention; Visual system structure; Work; avoidance behavior; base; compound eye; detector; information processing; insight; locust; neural information processing; operation; optogenetics; postsynaptic; presynaptic; public health relevance; reconstruction; relating to nervous system; response; sensory stimulus; simulation; two-dimensional; two-photon; visual information; visual stimulus

DESCRIPTION (provided by applicant): The long term objective of this research is to understand the biophysical mechanisms by which time-varying sensory stimuli are integrated in individual neurons. The immediate goal is to provide detailed biophysical explanations of how individual neurons multiply two inputs and how they implement invariance to certain stimulus attributes. Multiplication has been implicated in many neural computations, like the extraction of motion information from visual images, in both vertebrate and invertebrate nervous systems. Invariance is an attribute commonly found in higher order neurons that respond selectively to a stimulus feature independently of its context. Currently, there is little understanding of how thes computations are accomplished by neurons. These issues will be investigated in the visual system of the locust, which possesses a neuron, the lobula giant movement detector (LGMD), that responds to objects approaching on a collision course towards the animal and their two dimensional simulations on a video monitor, called looming stimuli. This neuron implements a multiplication operation between two distinct inputs impinging on its dendrites and exhibits responses that are invariant to many attributes of looming stimuli. Many features of the LGMD make it a favorable subject for biophysical studies. The specific aims of the project are to characterize the properties of synaptic inputs onto the LGMD, including the role played by background synaptic activity in shaping its responses to looming stimuli. In addition, the basic properties of several active membrane conductances and their role in the integration of synaptic inputs within the dendritic tree of the cell will be studied. The spatio-temporal activation patter of the LGMD's dendritic compartments during visual stimulation will also be assessed. These data will be used to build a model of the cell and its response to looming stimuli. The techniques employed will include stimulation of single facets on the compound eye of the locust - thus allowing to decompose complex visual stimuli in their elementary components - intracellular recordings, pharmacological manipulations, two-photon confocal calcium imaging, optogenetics and anatomical reconstructions based on viral transfections, as well as compartmental modeling at various levels of abstraction. The model and experimental data will be used to identify the biophysical mechanisms underlying multiplication and invariance in this neuron. Because very similar computations are found in vertebrate central nervous systems, this project is expected to advance the general understanding of how multiplication and invariance are implemented for neural information processing. Notably, multiplication and invariance have been shown to play an important role in visual perception and attention. Thus, characterizing the biophysical and cellular mechanisms of multiplication and invariance in this model system may also yield important insights in disorders involving perception and attention.

描述（由申请人提供）：本研究的长期目标是了解随时间变化的感觉刺激整合到单个神经元中的生物物理机制。近期目标是提供详细的生物物理学解释，说明单个神经元如何将两个输入相乘以及它们如何实现某些刺激属性的不变性。乘法涉及许多神经计算，例如在脊椎动物和无脊椎动物神经系统中从视觉图像中提取运动信息。不变性是高阶神经元中常见的一种属性，这些神经元能够选择性地响应刺激特征，而与其上下文无关。目前，人们对神经元如何完成这些计算知之甚少。这些问题将在蝗虫的视觉系统中进行研究，该系统拥有一个神经元，即小叶巨型运动探测器（LGMD），它对接近动物的碰撞过程中的物体做出反应，并在视频监视器上进行二维模拟，称为迫在眉睫的刺激。该神经元在影响其树突的两个不同输入之间实现乘法运算，并表现出对迫在眉睫的刺激的许多属性不变的响应。 LGMD 的许多特征使其成为生物物理学研究的热门课题。该项目的具体目标是表征 LGMD 突触输入的特性，包括背景突触活动在形成其对迫在眉睫的刺激的反应中所发挥的作用。此外，还将研究几种活性膜电导的基本特性及其在细胞树突树内突触输入整合中的作用。视觉刺激期间 LGMD 树突室的时空激活模式也将被评估。这些数据将用于构建细胞模型及其对迫在眉睫的刺激的反应。所采用的技术将包括刺激蝗虫复眼上的单个面，从而分解其基本成分中的复杂视觉刺激——细胞内记录、药理学操作、双光子共焦钙成像、光遗传学和基于病毒转染的解剖重建，以及不同抽象级别的分区建模。该模型和实验数据将用于识别该神经元倍增和不变性背后的生物物理机制。由于在脊椎动物中枢神经系统中发现了非常相似的计算，因此该项目有望促进对如何在神经信息处理中实现乘法和不变性的一般理解。值得注意的是，乘法和不变性已被证明在视觉感知和注意力中发挥着重要作用。因此，表征该模型系统中增殖和不变性的生物物理和细胞机制也可能对涉及感知和注意力的疾病产生重要的见解。