CAREER: Detection and localization of communication signals during motion in the electrosensory system.

定位信号源是很困难的，特别是当信号很微弱且在移动时。感官系统提取空间信息的能力已经在不同的系统中进行了探索，但科学家们仍然不太清楚允许这种定位过程在具有挑战性的条件下保持准确的机制，特别是当运动发生时。为了确定增强感官系统定位过程的通用机制，将检查一种独特的有机体。弱电鱼类必须根据它们发出的电信号来探测和定位其他个体。定位过程与视觉系统和听觉系统都有相似之处，视觉系统中的地图是在感觉系统的第一级创建的，而听觉系统中的位置是通过比较两只耳朵的输入来计算的。由于这些鱼在移动时彼此本地化，它们非常适合于解决这样一个问题：在困难和不断变化的条件下，是否存在类似的通用机制来加强本地化进程。描述这些鱼的空间相互作用的实验，识别神经机制的生理记录，以及概括所提出的神经动态的建模研究，将使我们能够更深入地理解这种本地化过程。机器人界面将允许与实验鱼进行精确的交互，还将允许高中生参与该项目，让他们参与机器人部件的设计，然后在实验期间参与其操作。该项目的目标是确定运动如何影响微弱电感觉信号的编码，以及网络动态如何适应现实的运动模式。这些鱼之间的社会互动依赖于对每条鱼产生的电场的检测和定位。虽然同种信号的时间编码被彻底理解，但关于同种信号的位置是如何提取的以及运动是如何影响检测和定位过程的，仍然一无所知。这些实验将通过展示现实信号--包括运动--是如何编码的，以及网络动态如何适应典型的动作，以支持有效地提取弱线索，从而为感觉加工提供新的见解。假设当发送者和接收者以现实的方式移动时，对同种生物的存在和位置的编码都将得到增强。进一步假设反馈输入将使空间表示更加清晰，并增强运动信号的可检测性。为了验证假设，项目分为三个方面：信号、编码精度和反馈的影响。动物所经历的感觉流将通过行为记录和感觉环境的3D建模来表征。主要感觉区域的神经记录将有助于阐明信号编码如何受到运动的影响。最后，将通过反馈路径的药理学操作和网络的大规模建模来确定与塑造感觉处理有关的网络机制。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Localizing the source of a signal is difficult, particularly when the signal is faint and moving. The ability of the sensory system to extract spatial information has been explored in various systems but scientists still do not understand well the mechanisms that allow this localization process to remain accurate in challenging conditions, particularly when movements occur. In order to identify generic mechanisms that enhance the localization process across sensory systems, a unique organism will be examined. Weakly electric fish must detect and localize other individuals based on the electric signal they emit. The localization process has similarities with both the visual system, where a map is created at the first level of the sensory system, and the auditory system where location is computed by comparing inputs at the two ears. Since these fish localize each other while moving, they are well suited to address the question: are there generic mechanisms, similar across modalities, that enhance the localization process in difficult and changing conditions. Experiments characterizing spatial interactions of these fish, physiological recordings that identify neural mechanisms and modelling studies recapitulating the proposed neural dynamic will allow a deeper understanding of this localization process. A robotic interface will allow a precise interaction with the experimental fish and will also permit to get high school students involved in the project by having them contribute to the design of the robotic component and then participate in its operation during experiments.The goal of this project is to determine how motion influences the coding of weak electrosensory signals and how network dynamic is adapted to realistic movement patterns. Social interactions among these fish rely on the detection and localization of the electric field each fish generates. Although temporal coding of conspecific signals is thoroughly understood, nothing is known about how the location of a conspecific is extracted and how motion affects the detection and localization process. The experiments will provide new insight into sensory processing by showing how realistic signals -that include movement- are encoded and how network dynamic is adapted to typical movements in order to support the efficient extraction of weak cues. The hypothesis is that the encoding of both the presence and location of a conspecific will be enhanced when sender and receiver move in a realistic manner. It is further hypothesized that feedback inputs will sharpen the spatial representation and enhance the detectability of moving signals. To test the hypotheses, the project is divided in 3 aspects: the signal, the coding accuracy and the influence of feedback. The sensory flow experienced by the animal will be characterized via behavioral recordings and 3D modelling of the sensory environment. Neural recordings in the primary sensory area will allow clarifying how signal coding is affected by motion. Finally, the network mechanisms involved in shaping sensory processing will be identified by pharmacological manipulation of feedback pathways and large-scale modelling of the network.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.