NONLINEAR DYNAMICS OF NEURONAL TEMPORAL PROCESSING

描述(改编自申请人的摘要)：相信有一些 神经计算涉及细胞和电路属性，使 基于动作电位的精确定时的编码和解码。声响 听觉系统的定位提供了一个令人信服的例子。它的作用是 这项研究的案例研究寻求更定性的描述 与精确的时间处理相关的细胞特性。 听觉脑干中的许多细胞有助于该系统的能力 检测耳间信号的重合度。这些神经元有独特的放电 属性。当提供稳定的刺激时，他们只发射一次，在 刺激开始，而许多其他类型的神经元将继续放电，直到 刺激计划被关闭了。这种阶段性的性质被认为对 精确的时间处理。相反，补血细胞被认为较少。 能够跟踪快速变化的信号。生物物理基础，一种特殊的 钾电流，IK-LT似乎是脑干相性的基础 神经元。 该项目将以一种系统的方式解决时间处理如何 神经元的能力随着神经元从相变到紧张期而变化 模式，例如，当细胞处于阶段时，逐渐调整IK-LT的强度 模式是更好地跟踪时变信号，还是执行得更好 符合检测，而不是当它处于紧张模式时？这项研究将结合 无论是实验方法还是理论方法。这些实验包括 刺激单个神经元时的体外电记录 具有周期性和其他时变信号，包括随机分量。从… 在理论方面，将开发基于生物物理学的数学模型 即模仿神经元，包括一个IK-LT术语，各种措施都会 应用于计算机和细胞模型以评估可靠性和精确度 在处理过程中。此外，来自非线性动力系统的概念将是 应用于揭示和理解潜在的数学结构 这一理解将使我们能够概括出 对机制可能不涉及IK-LT的其他神经系统的阶段性 一个相关的子项目是开发计算模型，以帮助解释 在实验上被视为耳间相位(或幅度或 频率)是动态变化的。对这些令人惊讶的事情有更深的了解 在听觉中脑所看到的影响，应该有助于形成一个 关于如何在大脑中分析声源运动的理论。

DESCRIPTION (Adapted from Applicant's abstract): It is believed that some neural computations involve cellular and circuit properties that enable encoding and decoding based on precise timing of action potentials. Sound localization in the auditory system offers a compelling example. It serves as the case study for this research that seeks a more qualitative characterization of cellular properties that correlate with precise temporal processing. Many cells in the auditory brain stem contribute to the system's ability to detect coincidence of interaural signals. These neurons have distinctive firing properties. When a steady stimulus is presented they fire only once, at stimulus onset, while neurons of many other types will continue to fire until the stimulus is turned off. This property of phasicness is believed crucial for precise temporal processing. In contrast, tonic cells are assumed to be less capable of tracking rapidly changing signals. The biophysical basis, a special potassium current, IK-LT appears to underlie phasicness in the brain stem neurons. This project will address in a systematic way how the temporal processing ability of a neuron changes as the neuron is transformed from phasic to tonic mode, say by gradually adjusting the strength of IK-LT When a cell is in phasic mode does it track a time-varying signal better, or does it perform better coincidence detection, than when it is in tonic mode? The research will combine both experimental and theoretical approaches. The experiments involve electrical recording from individual neurons in vitro while stimulating them with periodic and other time-varying signals, including random components. From the theoretical side, biophysically-based mathematical models will be developed that mimic the neurons, including a term for IK-LT Various measures will be applied to the computer and cellular models to assess reliability and precision of processing. In addition, concepts from nonlinear dynamical systems will be applied in order to reveal and understand the underlying mathematical structure This understanding will enable us to generalize about the significance of phasicness to other neural systems where the mechanism might not involve IK-LT A related subproject is to develop computational models that will help explain the dynamic effects seen experimentally as interaural phase (or amplitude or frequency) is varied dynamically. A deeper understanding of these surprising effects, as seen in the auditory mid-brain, should contribute to developing a theory for how motion of sound sources are analyzed in the brain.