Neural representation of mating partners by male C. elegans

雄性线虫对交配伙伴的神经表征

基本信息

批准号：
10685522
负责人：
Scott Warren Linderman
金额：
$ 65.68万
依托单位：
CALIFORNIA INSTITUTE OF TECHNOLOGY
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-08-15 至 2024-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10685522
关键词：
Ablation Acceleration Acute Affect Afferent Neurons Algorithms Anatomy Animal Behavior Animals Applied Genetics Behavior Behavior Control Behavioral Brain Brain imaging Caenorhabditis elegans Cells Chemicals Chronic Communities Complex Computer Models Coupled Coupling Data Data Analyses Databases Decision Making Dimensions Dissection Dorsal Environment Event Feedback Ganglia Genes Genetic Goals Head Hermaphroditism Image Insemination Interneurons Knowledge Laboratories Lead Learning Maps Measurement Methods Modeling Modernization Molecular Molecular Genetics Monitor Motor Motor Activity Motor Neurons Motor output Movement Nervous System Neurons Neurophysiology - biologic function Neurosciences Neurotransmitters Partner in relationship Pattern Penetration Perception Pheromone Policies Positioning Attribute Posture Property Psychological reinforcement Resolution Role Sensory Series Sex Behavior Shapes Side Specific qualifier value Stereotyping Stimulus Structure Synapses System Tail Technology Testing Texture Vulva automated segmentation connectome data modeling data-driven model experience experimental study genetic manipulation high dimensionality imaging platform male mating behavior mutant neural neural circuit neurogenetics neurophysiology neuroregulation optogenetics receptor response sensory input sexual dimorphism sperm cell temporal measurement tool

项目摘要

Project Summary Understanding how neural circuits create animal behavior requires knowing the system-wide activity patterns that connect sensory experience to motor activities, all within the full set of feedback loops by which actuated motor decisions modulate the animal's perceptions of itself and the outside world during naturally executed and unrestrained behaviors. Mechanistic understanding further requires interpretation of system-wide activity patterns in terms of the connectivity, synaptic, and cellular properties of all relevant neurons. Modeling requires comprehensive mapping of the salient dimensions of sensory input and motor output, as well as how high- dimensional neural activity patterns are properly projected, by decision-making and the internal constraints of the nervous system and motor system, into the fewer dimensions that characterize any animal's observed behavior. Such models are facilitated by using animals where entire brain and motor circuits can be mapped and interrogated with full molecular and cellular resolution. Here, we will use the mating behavior of the male C. elegans as such a paradigm. The mating behavior of C. elegans is a critically important and goal-directed task that occurs in natural environments and is robustly executed in the laboratory. Males use a specialized circuit of ~100 neurons – sensory neurons, interneurons, neuromodulatory, and motor neurons – all contained within the male tail ganglia to locate hermaphrodites, locate the vulva along the hermaphrodite's body, and initiate and complete insemination. A diverse set of mechanosensory, chemosensory, and pheromone sensing neurons are used to recognize the shape, texture, and chemical signature of the hermaphrodite body. Several neurons are specialized to detect fiducial points along the hermaphrodite body. The male implicitly uses an internal representation of the size, shape, and predictable behaviors of the hermaphrodite to positively recognize the hermaphrodite, infer its own position along the hermaphrodite, and execute an optimal movement strategy to maintain contact with the hermaphrodite and find and penetrate the vulva. It is now possible to record neural activity from the entire set of neurons in the male tail with high temporal resolution and complete cellular resolution. We will couple experiments, modern data analysis and modeling methods, and cellular and molecular genetic perturbations to elucidate the full set of sensorimotor events that organize the mating behavior. We will develop a realistic model of the circuit that integrates the observable behavioral algorithms with the connectivity and activity patterns of the male tail ganglion. We will apply genetic tools to identify and elucidate each sensory neuron type, and how it affects each aspect of decision-making by downstream interneurons and motor neurons. We will characterize key synaptic properties by molecular dissection of neurotransmitter and receptor types. We will store this comprehensive neurophysiological and neurogenetic data in online project databases connected to our computational models that will allow the wider community to view and probe our data-driven modeling eff ort.

项目概要了解神经回路如何产生动物行为需要了解整个系统的活动模式将感官体验与运动活动联系起来，所有这些都在由其驱动的全套反馈循环内运动决策在自然执行和执行过程中调节动物对自身和外部世界的感知。进一步理解机制需要对系统范围的活动进行解释。所有相关神经元的连接、突触和细胞特性的模式需要建模。感觉输入和运动输出的显着维度的全面映射，以及多高通过决策和内部约束，可以正确预测维度神经活动模式神经系统和运动系统，进入表征任何动物观察到的较少维度这种模型是通过使用可以绘制和绘制整个大脑和运动回路的动物来促进的。在这里，我们将使用雄性 C. 线虫作为这样的范例。线虫的交配行为是一项极其重要且有目标的任务。发生在自然环境中并在实验室中可靠地执行的男性使用专门的电路。约 100 个神经元——感觉神经元、中间神经元、神经调节神经元和运动神经元——全部包含在雄性尾部神经节定位雌雄同体，沿着雌雄同体的身体定位外阴，并启动完整的授精过程中具有多种机械感觉、化学感觉和信息素感应神经元。一些神经元用于识别雌雄体的形状、纹理和化学特征。专门用于检测雌雄同体身体上的基准点，男性隐式地使用内部的。表现雌雄同体的大小、形状和可预测的行为，以积极地识别雌雄同体，推断自己沿着雌雄同体的位置，并执行最优的移动策略与雌雄同体保持接触并找到并刺入外阴现在可以记录神经。雄性尾部整组神经元的活动，具有高时间分辨率和完整的细胞我们将结合实验、现代数据分析和建模方法以及细胞和分子。我们将利用遗传扰动来阐明组织交配行为的全套感觉运动事件。开发一个真实的电路模型，将可观察的行为算法与连接集成在一起我们将应用遗传工具来识别和阐明每种感觉。神经元类型，以及它如何影响下游中间神经元和运动神经元决策的各个方面。我们将通过神经递质和受体类型的分子解剖来表征关键的突触特性。将把这些全面的神经生理学和神经遗传学数据存储在连接的在线项目数据库中我们的计算模型将使更广泛的社区能够查看和探索我们的数据驱动模型努力。

项目成果

期刊论文数量（4）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

PEZO-1 and TRP-4 mechanosensors are involved in mating behavior in Caenorhabditis elegans.

PEZO-1 和 TRP-4 机械传感器参与秀丽隐杆线虫的交配行为。

DOI：
发表时间：
2022-11
期刊：
影响因子：
0
作者：
Brugman, Katherine I;Susoy, Vladislav;Whittaker, Allyson J;Palma, Wilber;Nava, Stephanie;Samuel, Aravinthan D T;Sternberg, Paul W
通讯作者：
Sternberg, Paul W

Statistical neuroscience in the single trial limit.

单次试验限制中的统计神经科学。