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

定位信号源是困难的，特别是当信号微弱和移动时。感官系统提取空间信息的能力已经在各种系统中进行了探索，但科学家们仍然不太了解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。为了确定一般机制，加强定位过程的感觉系统，一个独特的有机体将被检查。弱电鱼必须根据自己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，视觉系统在感觉系统的第一级创建地图，听觉系统通过比较两只耳朵的输入来计算位置。由于这些鱼类在移动时相互定位，它们非常适合解决这样一个问题：在困难和变化的条件下，是否存在通用的机制，在不同的模式下相似，以增强定位过程。表征这些鱼的空间相互作用的实验，识别神经机制的生理记录和建模研究，概括了所提出的神经动力学，将使我们更深入地了解这一定位过程。机器人界面将允许与实验鱼进行精确的互动，也将允许高中生参与该项目，让他们参与机器人组件的设计，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探测和定位。虽然对同视信号的时间编码已经完全了解，但对于如何提取同视的位置以及运动如何影响检测和定位过程，我们一无所知。这些实验将通过展示现实信号（包括运动）是如何被编码的，以及网络动态是如何适应典型运动的，从而支持对弱线索的有效提取，从而为感官处理提供新的见解。假设是，当发送者和接收者以现实的方式移动时，对同一对象的存在和位置的编码将得到增强。进一步假设反馈输入将锐化空间表征并增强运动信号的可检测性。为了验证假设，本项目分为三个方面：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。初级感觉区的神经记录将有助于阐明信号编码是如何受到运动影响的。最后，参与塑造感觉加工的网络机制将通过反馈通路的药理学操作和网络的大规模建模来确定。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值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.