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.

项目摘要了解神经回路如何创造动物行为需要了解系统范围的活动模式将感官体验与运动活动联系起来，所有这些都在整个反馈循环中运动决策调节动物在自然执行期间对自身和外界的看法不受约束的行为。机械理解进一步需要解释全系统范围的活动所有相关神经元的连通性，突触和细胞特性的模式。建模需要感觉输入和电机输出的显着尺寸的全面映射，以及高度通过决策和内部约束，适当地投影了维度神经活动模式神经系统和运动系统，变成较小的尺寸，表征了任何动物的观察到行为。通过使用可以映射整个大脑和运动电路的动物来制备此类模型通过全分子和细胞分辨率进行询问。在这里，我们将使用男性C的交配行为。秀丽隐杆人这样的范式。秀丽隐杆线虫的交配行为是一项至关重要的目标任务这发生在自然环境中，并在实验室中执行。男性使用专门的电路〜100个神经元 - 感觉神经元，中间神经元，神经调节性和运动神经元 - 全部包含雄性尾巴神经节定位雌雄同体，在雌雄同体的身体沿着外阴定位，并开始完全的授精。一组机制，化学感应和信息素传感神经元的一组用于识别雌雄同体体的形状，质地和化学特征。几个神经元专门用于检测雌雄同体体的基准点。男性隐式使用内部雌雄同体的大小，形状和可预测行为的表示，以积极认识雌雄同体，推断其沿雌雄同体的位置，并执行最佳运动策略保持与雌雄同体的接触，并找到并穿透外阴。现在可以记录中立高临时分辨率和完整细胞的雄性尾巴中整个神经元的活性解决。我们将对实验，现代数据分析和建模方法以及细胞和分子遗传扰动以阐明组织交配行为的全套感觉运动事件。我们将开发一个现实的电路模型，将可观察到的行为算法与连接性集成和雄性尾神经节的活动模式。我们将应用遗传工具来识别和阐明每个感觉神经元类型及其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突触特性。我们将在连接的在线项目数据库中存储这种全面的神经生理学和神经遗传数据对于我们的计算模型，该模型将使更广泛的社区能够查看和探究我们的数据驱动建模努力。

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.

DOI：
10.1093/pnasnexus/pgac213
发表时间：
2022-11
期刊：
PNAS NEXUS
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.

Generalized Shape Metrics on Neural Representations.

神经表示的广义形状度量。