Temporal Processing in the Auditory System: A Nonlinear Dynamics Approach with Theory and Experiment

听觉系统中的时间处理：理论与实验的非线性动力学方法

• 批准号: 0078420
• 负责人: John Rinzel
• 金额: $ 10.16万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-08-15 至 2006-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0078420&HistoricalAwards=false
• 关键词: Temporal; Processing; Auditory; System; Nonlinear

Rinzel0078420 The neural computation by the mammalian auditory system tolocalize low frequency sound sources relies on processing in thebrain stem. Neurons and circuits there, in the medial superiorolive (MSO), have specialized biophysical properties forprocessing and preserving precise timings. These neurons havedistinctive firing properties. When a steady stimulus ispresented they fire only once, at stimulus onset; many othertypes of neurons would behave tonically, firing throughout thestimulus presentation. This property of phasicness is believedcrucial for the MSO cell's role in precise temporal processing.In contrast, tonic cells are assumed to be less capable oftracking rapidly changing signals. The MSO cells have a specialpotassium current, IK-LT, that underlies their phasic behavior.The investigator and his colleagues systematically study how thetemporal processing ability of a neuron changes as the neuron istransformed from phasic to tonic mode, say by gradually adjustingthe strength of IK-LT (using pharmacological blockers andelectronic methods of re-introducing the blocked current). When acell is in phasic mode does it track a time-varying signalbetter, or does it perform better coincidence detection, thanwhen it is in tonic mode? The research combines both experimentaland theoretical approaches. The experiments involve electricalrecording from individual MSO neurons while stimulating them withperiodic and other time-varying signals. Various quantitativecriteria are applied to assess the quality of temporalprocessing. From the theoretical side, biophysically-basedmathematical models are developed that mimic the MSO neurons,including a term for IK-LT. The model's performance for temporalprocessing is evaluated just like the real cells. In addition,concepts from nonlinear dynamical systems are applied in order toreveal and understand the underlying mathematical structure.This mathematical understanding will shed light on thesignificance of phasicness in other neural systems where themechanism might not involve IK-LT. This project also explores theinfluence of randomness on the temporal processing abilities.Some randomness is intrinsic to the auditory nervous system, andit is believed to be functionally important. Without sources ofvariability, these nonlinear neuronal systems tend to phase-locktoo well, impairing a system's ability to perform discriminationtasks. The investigator therefore also assesses the effects ofrandomness on the temporal processing power of phasic and toniccells and on the theoretical models. This work seeks to testwhether the commonly accepted notion, that phasicness enhancestemporal processing power, passes a set of quantitative criteriaand, if so, to develop a theoretical foundation that supports thenotion and that extends to other neural and possibly somechemical and physical systems as well. A related subproject is todevelop computational models that help explain the dynamiceffects seen experimentally as interaural phase (or amplitude orfrequency) is varied dynamically. A deeper understanding of somesurprising effects, as seen in the auditory mid-brain, shouldcontribute to developing a theory for how motion of sound sourcesis analyzed in the brain. It is believed that some neural computations involvecellular and circuit properties that enable encoding and decodingbased on precise timing of action potentials. Sound localizationin the auditory system offers a compelling example. It serves asthe case study for this research, that seeks a more qualitativecharacterization of cellular properties that correlate withprecise temporal processing. Many cells in the auditory brainstem contribute to the system's ability to detect coincidence ofinteraural signals. These neurons have distinctive firingproperties. When a steady stimulus is presented they fire onlyonce, at stimulus onset, while neurons of many other types willcontinue to fire until the stimulus is turned off. This propertyof phasicness is believed crucial for precise temporalprocessing. In contrast, tonic cells are assumed to be lesscapable of tracking rapidly changing signals. The biophysicalbasis, a special potassium current, IK-LT, appears to underliephasicness in the brain stem neurons. This project systematicallyaddresses how the temporal processing ability of a neuron changesas the neuron is transformed from phasic to tonic mode, say bygradually adjusting the strength of IK-LT. When a cell is inphasic mode does it track a time-varying signal better, or doesit perform better coincidence detection, than when it is in tonicmode? The research combines both experimental and theoreticalapproaches. The experiments involve electrical recording fromindividual neurons in vitro while stimulating them with periodicand other time-varying signals, including random components. Fromthe theoretical side, biophysically-based mathematical models aredeveloped that mimic the neurons, including a term for IK-LT.Various measures are applied to the computer and cellular modelsto assess reliability and precision of processing. In addition,concepts from nonlinear dynamical systems are applied in order toreveal and understand the underlying mathematical structure. Thisunderstanding will enable us to generalize about the significanceof phasicness to other neural systems where the mechanism mightnot involve IK-LT. A related subproject is to developcomputational models that help explain the dynamic effects seenexperimentally as interaural phase (or amplitude or frequency) isvaried dynamically. A deeper understanding of these surprisingeffects, as seen in the auditory mid-brain, should contribute todeveloping a theory for how motion of sound sources is analyzedin the brain. This project is supported by the AppliedMathematics and Computational Mathematics programs and the Officeof Multidisciplinary Activities in MPS and by the ComputationalNeuroscience program in BIO.

Rinzel0078420 哺乳动物听觉系统定位低频声源的神经计算依赖于脑干的处理。 内侧上橄榄核（MSO）的神经元和回路具有特殊的生物物理特性，可以处理和保存精确的时间。 这些神经元具有独特的放电特性。 当一个稳定的刺激呈现时，它们只在刺激开始时放电一次;许多其他类型的神经元会表现出紧张性，在整个耳蜗呈现过程中放电。 相性的这种特性被认为是MSO细胞在精确的时间处理中的关键作用。相反，紧张性细胞被认为跟踪快速变化的信号的能力较低。 MSO细胞有一种特殊的钾电流IK-LT，它是其相位行为的基础。研究者和他的同事们系统地研究了神经元的时间处理能力如何随着神经元从相位模式转变为强直模式而变化，比如通过逐渐调整IK-LT的强度（使用药物阻断剂和重新引入阻断电流的电子方法）。 当一个细胞处于相位模式时，它是否能更好地跟踪时变信号，或者它是否能比处于紧张模式时更好地执行重合检测？本研究采用实验和理论相结合的方法。 这些实验包括用周期性和其他时变信号刺激单个MSO神经元时的电记录。 各种量化标准被用来评估时间加工的质量。 从理论上讲，我们开发了基于生物药理学的数学模型，模拟MSO神经元，包括IK-LT术语。 此外，非线性动力学系统的概念被应用于揭示和理解潜在的数学结构。这种数学理解将揭示相位在其他神经系统中的意义，其中机制可能不涉及IK-LT。本项目还探讨了随机性对时间处理能力的影响。一些随机性是听觉神经系统固有的，并且它被认为在功能上是重要的。 如果没有可变性的来源，这些非线性神经元系统往往相位锁定得太好，削弱了系统执行辨别任务的能力。 因此，研究人员还评估了随机性对相位和张力细胞的时间处理能力以及理论模型的影响。 这项工作旨在测试普遍接受的概念，即相位增强时间处理能力，是否通过了一套定量标准，如果是这样，发展一个理论基础，支持这一概念，并扩展到其他神经系统和可能的一些化学和物理系统。 一个相关的子项目是开发计算模型，帮助解释实验中看到的耳间相位（或振幅或频率）动态变化的动态效应。 更深入地了解一些令人惊讶的影响，如在听觉中脑中看到的，应该有助于发展一个理论，解释声源的运动如何在大脑中分析。 据信，一些神经计算涉及细胞和电路特性，这些特性使得能够基于动作电位的精确定时进行编码和解码。 听觉系统中的声音定位提供了一个令人信服的例子。 它作为本研究的案例研究，寻求与精确的时间处理相关的细胞特性的更定性的特征。 听觉脑干中的许多细胞有助于系统检测听觉信号的一致性。 这些神经元具有独特的放电特性。 当一个稳定的刺激出现时，它们只在刺激开始时放电一次，而许多其他类型的神经元将继续放电，直到刺激关闭。 这种相位性被认为对精确的时间处理至关重要。 相反，紧张性细胞被认为是不太能够跟踪快速变化的信号。 脑干神经元内一种特殊的钾电流（IK-LT）似乎是引起该现象的生物药理学基础。 这个项目系统地阐述了神经元的时间处理能力如何随着神经元从相位模式转变为强直模式而变化，比如通过逐渐调整IK-LT的强度。当细胞处于非相位模式时，它是否比处于强直模式时更好地跟踪时变信号，或者执行更好的重合检测？ 本研究采用实验和理论相结合的方法。 这些实验包括在体外对单个神经元进行电记录，同时用电信号和其他随时间变化的信号（包括随机成分）刺激它们。 从理论上讲，基于生物药理学的数学模型被开发出来，模拟神经元，包括IK-LT的术语。各种措施被应用到计算机和细胞模型中，以评估处理的可靠性和精度。 此外，从非线性动力系统的概念应用，以揭示和理解底层的数学结构。 这种理解将使我们能够将相位性的重要性推广到其他神经系统，其中机制可能不涉及IK-LT。一个相关的子项目是开发计算模型，以帮助解释实验中看到的耳间相位（或振幅或频率）动态变化的动态效应。 更深入地了解这些听觉中脑的听觉效应，应该有助于发展一个关于声源在大脑中如何运动的理论。 该项目得到了MPS的数学和计算数学计划以及多学科活动计划的支持，并得到了BIO的计算神经科学计划的支持。