COLLAB: From Structure to Information in Mechanosensory Systems. The role of Sensor Morphology in Detecting Fluid Signals.

协作：从机械感觉系统的结构到信息。

• 批准号: 0718506
• 负责人: Houshuo Jiang
• 金额: $ 17.91万
• 依托单位: Woods Hole Oceanographic Institution
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0718506&HistoricalAwards=false
• 关键词: COLLAB; Structure; Information; Mechanosensory; Systems.

ABSTRACT - Fields and JiangProposal Number: 0718832 - Collaborative Research: From structure to information in mechanosensory systems. The role of sensor morphology in detecting fluid signals.Copepods present a spectacular diversity of antennule and setal morphologies, orientations and degree of ornamentation. The causes and consequences of this diversity remain unexplored, but the staggering degree of morphological variation suggests structure-function relationships between mechanosensor properties and their sensory roles. Using copepods as a model system, this work will address the relationship between the shape of mechanosensory structures and their movement under non steady-state fluid conditions. Planktonic copepods provide a unique model system for mechanoreception because: 1) copepods show a variety of behavioral responses to fluid signals; 2) the basic properties of copepod's mechanosensory systems are easy to identify and are likely conserved across a diverse range of species; 3) because of their size, copepods operate at low Reynolds numbers where fluid motion remains comparatively coherent and easy to quantify and model. Also, one of the truly unique characteristics of copepods is their extremely rapid response times (milliseconds). Living at low Reynolds numbers, mechanical stimuli are attenuated quickly by viscous dampening causing fluid velocity (driven by steady swimming) to decrease with distance squared (Fields and Yen 2002). Consequently, copepods often do not detect other individuals (including predators) until they are within a few body lengths of each other. Because of the close proximity and their ability for rapid movement, behavioral latencies of milliseconds are required. Collecting enough information within this short latency period is an extraordinary challenge for the copepod and requires rapid firing rates and the spatial integration of numerous signals from their antennae.To determine the relationship between fluid motion, setal motion, nerve firing rates and behavior, the dynamics of all components must be simultaneously known. Using analytical solutions for monopole or dipole movement, previous studies have calculated what the fluid characteristics should be at the sensor under steady state conditions. However, the mechanical devises generating the fluid signals and the sensor responding to the signal require 100 - 1000 ms to reach steady state. Yet it is during these crucial first few milliseconds that copepods (or any other organism with short behavioral latency) gather the pertinent information. Therefore steady state solutions are appropriate for organisms that integrate information over long time periods but are not applicable for organisms such as copepods with short behavioral latencies. Numerical treatments for quantifying fluid motion are available but rarely applied. A second consideration is how the receptors are modeled. Due primarily to analytical tractability, most current models of setal motion characterize the hair as a rigid cylinder of uniform diameter and rely on spatially homogeneous-steady state flow over the entire hair to move it. However, anatomical features, such as non-uniform cuticular thickness, asymmetry in cross-sectional diameter, setal geniculations and fine hair-like projections from the setae differ between seta and likely affect the transduction of fluid motion to setal bending. Furthermore, mechanical features such as the degree of setal arcing may give rise to large changes in the relationship between angular deflection and fluid velocity. For setae immersed in water, as opposed to air (where many of the models have been applied) these effects may be even more pronounced.The goal of this project is to quantify the relationship between fluid motion and sensory morphology. SEM measurements of the size and width of different setae and TEM measurements of cuticular thickness and the extent of the dendritic penetration up the shaft of individual mechanoreceptors will be made for three species of copepods. The force required to bend the seta and the physiological response of individual hairs to the well described flows created in the lab will be quantified with respect to the physical characteristics of the receptor. The empirical data will be used to build two interacting models: Finite Element Method (FEM) and Computational Fluid Dynamics (CFD). The FEM will be used to model the motion of individual seta with known morphology and bending characteristics while the CFD will be used to calculate the hydrodynamic force and torque applied to each region of the seta and the influence of the seta on the surrounding flow. These data are fundamental to understanding how these small, neurologically simple organisms can distinguish from the myriad of biologically and physically induced fluid movements.

合作研究：从结构到信息的机械感觉系统。感受器形态在检测流体信号中的作用桡足类在触角和刚毛形态、方向和定向程度上呈现出惊人的多样性。这种多样性的原因和后果仍然未被探索，但形态变化的惊人程度表明机械传感器特性和它们的感觉作用之间的结构-功能关系。以桡足类为模型系统，研究非稳态流体条件下机械感觉结构的形状与运动之间的关系。浮游桡足类为机械感受提供了一个独特的模型系统，因为：1）桡足类对流体信号表现出多种行为反应; 2）桡足类机械感受系统的基本特性很容易识别，并且可能在不同的物种中保留; 3）由于它们的大小，桡足类在低雷诺数下运行，其中流体运动保持相对连贯，易于量化和建模。此外，桡足类真正独特的特征之一是它们极快的反应时间（毫秒）。生活在低雷诺数下，机械刺激通过粘性阻尼迅速衰减，导致流体速度（由稳定的游泳驱动）随距离的平方而减小（Fields和Yen 2002）。因此，桡足类通常不会发现其他个体（包括捕食者），直到它们彼此在几个身体长度内。由于它们的距离很近，而且能够快速移动，因此需要毫秒级的行为延迟。对于桡足类动物来说，在如此短的潜伏期内收集足够的信息是一个巨大的挑战，它需要快速的放电频率和对来自触角的大量信号的空间整合。为了确定流体运动、刚毛运动、神经放电频率和行为之间的关系，必须同时知道所有组件的动力学。使用偶极子或偶极子运动的解析解，以前的研究已经计算出在稳态条件下传感器处的流体特性。然而，产生流体信号的机械装置和响应于该信号的传感器需要100 - 1000 ms才能达到稳定状态。然而，桡足类动物（或任何其他行为潜伏期较短的生物）正是在这关键的最初几毫秒内收集相关信息。因此，稳态解适合于在长时间内整合信息的生物体，但不适用于具有短行为延迟的桡足类生物体。用于量化流体运动的数值处理是可用的，但很少应用。第二个考虑因素是受体是如何建模的。主要由于分析的易处理性，大多数当前的刚毛运动模型将毛发表征为均匀直径的刚性圆柱体，并且依赖于整个毛发上的空间稳态流动来移动毛发。刚毛膝状体和来自刚毛的细毛发状突起在刚毛之间不同，并且可能影响流体运动到刚毛弯曲的转换。此外，诸如刚毛电弧的程度的机械特征可能引起角偏转和流体速度之间的关系的大的变化。对于浸入水中的刚毛，而不是空气（许多模型已经应用），这些影响可能会更加明显。本项目的目标是量化流体运动和感觉形态之间的关系。SEM测量的大小和宽度不同的刚毛和TEM测量角质层厚度和树突的渗透程度的轴的个人mechanoreceptors将为三种桡足类。弯曲刚毛所需的力和个体毛发对实验室中产生的良好描述的流动的生理反应将相对于受体的物理特性进行量化。经验数据将用于建立两个相互作用的模型：有限元法（FEM）和计算流体动力学（CFD）。FEM将用于模拟具有已知形态和弯曲特性的单个刚毛的运动，而CFD将用于计算施加到刚毛每个区域的流体动力和扭矩以及刚毛对周围流动的影响。这些数据对于理解这些小的、神经学上简单的生物体如何区分无数的生物和物理诱导的流体运动至关重要。