SENSORY MECHANISMS OF BIOELECTRIC SIGNAL PROCESSING

神经科学家依靠动物模型来研究基本的 神经过程。 在这个广阔的领域内，神经行为学重点关注 对自然行为的分析，通常与感官相关 关键信号的处理。 我们对神经解剖学的理解 生理学和人类感觉系统的发展很大程度上来自于 脊椎动物模型系统研究。 Glymnotiform 电鱼已成为研究的主要模型 脊椎动物神经网络之间的并行处理和组织 感觉和运动系统。 神经科学家已经追踪到电感觉 从感觉周围，通过大脑，然后回到大脑的通路 电机输出。 Gymnotiform 电鱼使用相同的神经网络 三种不同的功能：电定位、通信和干扰 回避。 因此，gynotiform 电感觉系统是一个 探索并行处理灵活性的优秀模型 网络。 这三种感觉功能的行为研究形成了 研究相关大脑网络特性的基础。 本研究旨在揭示电的行为机制 社会交往中涉及的信号辨别。 进一步 对底层网络和神经机制的研究可以进行一次 我们知道电鱼用来区分的行为算法 信号波形之间。 裸状鱼类似乎可以控制它们的运动 输出（电信号）以增强其对信号的感觉处理 来自其他鱼。 组合信号相加以克服惯性 外周受体系统，但必须再次被中枢分开 网络。 这里提出的研究遵循合理的进展。 1. 已校准 一组来自室外鱼的自然信号将被数字化 繁殖群体在后续实验中用作刺激物。 2.下一个 步骤将是通过以下方式校准研究物种的感官阈值 获得两种类型的行为调整曲线：对纯粹的敏感性 信号以及接收器和信号器对组合信号的敏感度。 3. 信号运动模式将在实验中记录下来，从而引发 自然的歧视行为。 在这种情况下的运动行为将是 经过详细分析，准确记录何时以及如何 接收器将其信号与信号器的信号重叠（即，组合 信号）。 4. 本提案的最终实验将揭示 用于信号辨别和运动行为的显着特征 准确辨别信号所需的。

Neuroscientists rely on animal models for the investigation of basic neural processes. Within this broad field, neuroethology has focused on the analysis of natural behaviors, often those associated with sensory processing of critical signals. Our understanding of the neuroanatomy, physiology, and development of human sensory systems comes largely from study of vertebrate model system. Glymnotiform electric fish have become leading models for investigation of parallel processing and organization among neural networks in vertebrate sensory and motor systems. Neuroscientists have traced the electrosensory pathway from the sensory periphery, through the brain, and back to the motor output. Gymnotiform electric fish use the same neural networks for three different functions: electrolocation, communication, and jamming avoidance. The gymnotiform electrosensory system is therefore an excellent model for exploring the flexibility of parallel processing networks. Behavioral studies of these three sensory functions form the base for investigation of the properties of the brain networks involved. This study is designed to reveal the behavioral mechanism(s) of electric signal discrimination involved in social communication. Further investigation of underlying networks and neural mechanisms can follow once we know the behavioral algorithms that electric fish use to discriminate among signal waveforms. Gymnotiform fish appear to control their motor output (electric signals) to enhance their sensory processing of signals from other fish. Combined signals sum to overcome inertia of the peripheral receptor system but must be separated once again by the central networks. The study proposed here follows a rational progression. 1. A calibrated set of natural signals will be digitized from the fish in an outdoor breeding colony for use as stimuli in subsequent experiments. 2. The next step will be to calibrate the sensory thresholds of the study species by obtaining two types of behavioral tuning curves: sensitivity to pure signals and the sensitivity to combined signals of receiver and signaler. 3. Signal motor patterns will be recorded in experiments that elicit natural discrimination behavior. Motor behavior in this context will be subjected to detailed analysis to document precisely when and how the receiver overlaps its signal with that of the signaler (i.e., combines signals). 4. The final experiments in this proposal will reveal the salient features used for signal discrimination and the motor behaviors required for accurate discrimination of signals.