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

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计时。这些神经元具有独特的放电特性。当一个稳定的刺激被呈现时，它们只在刺激开始时放电一次；许多其他类型的神经元将表现出强直的行为，在整个估计神经元呈现期间都被放电。这种相位性被认为对MSO细胞在精确的时间处理中的作用至关重要。相比之下，强直细胞被认为跟踪快速变化的信号的能力较差。MSO细胞有一种特殊的钾电流IK-LT，这是它们时相行为的基础。研究人员和他的同事系统地研究了随着神经元从时相模式转换到紧张期模式，神经元的临时处理能力是如何变化的，比如通过逐渐调整IK-LT的强度(使用药物阻滞剂和重新引入阻断电流的电子方法)。当ACell处于相位模式时，它是比处于主音模式时更好地跟踪时变信号，还是执行更好的符合检测？这项研究结合了实验和理论两种方法。这些实验包括对单个MSO神经元进行电记录，同时用周期性和其他时变信号刺激它们。采用不同的量化标准来评估时间加工的质量。在理论方面，开发了基于生物物理学的数学模型来模拟MSO神经元，包括IK-LT的术语。该模型的时间处理性能的评估就像真实细胞一样。此外，为了揭示和理解潜在的数学结构，我们还应用了非线性动力系统的概念。这种数学理解将有助于阐明相位性在其他神经系统中的重要性，在这些神经系统中，机制可能不涉及IK-LT。这个项目还探索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，被认为在功能上是重要的。如果没有可变性来源，这些非线性神经系统往往会锁相得太好，从而削弱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细胞和音调细胞的时间处理能力以及理论模型的影响。这项工作试图检验普遍接受的概念，即阶段性增强临时处理能力，是否通过了一套量化标准，如果是这样的话，就建立了支持这一概念的理论基础，并扩展到其他神经系统，可能还有一些化学和物理系统。一个相关的子项目是开发计算模型，帮助解释在实验中看到的耳间相位(或幅度或频率)动态变化的动态效应。对一些突起效应的深入理解，如在听觉中脑中看到的，应该有助于发展一种理论，即如何在大脑中分析声源运动。据信，一些神经计算涉及细胞和电路特性，这些特性使编码和解码能够基于动作电位的精确定时。听觉系统中的声音定位提供了一个令人信服的例子。它作为这项研究的案例研究，寻求与精确的时间处理相关的细胞属性的更高质量的特征。听觉脑干中的许多细胞有助于该系统检测耳间信号的重合。这些神经元具有独特的激发特性。当出现稳定的刺激时，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。这种阶段性被认为是精确的时间处理的关键。相反，强直细胞被认为跟踪快速变化的信号的能力较差。在生物物理学的基础上，一种特殊的钾电流，IK-LT，似乎在脑干神经元中表现出低肾性。本课题系统地研究了神经元的时间处理能力是如何随着神经元从时相模式向紧张期模式的转变而变化的，比如通过逐渐调整IK-LT的强度。当细胞处于同相模式时，它是比处于调频模式时更好地跟踪时变信号，还是执行更好的符合检测？这项研究结合了实验和理论两种方法。这些实验包括在体外对单个神经元进行电记录，同时用周期性和其他时变信号(包括随机成分)来刺激它们。在理论方面，开发了基于生物物理学的数学模型来模拟神经元，包括一个术语IK-LT。计算机和细胞模型采用了各种方法来评估处理的可靠性和精确度。此外，还应用了非线性动力系统的概念，以揭示和理解潜在的数学结构。这一理解将使我们能够将相变的意义推广到其他神经系统，在这些神经系统中，这种机制可能不涉及IK-LT。一个相关的子项目是开发计算模型，帮助解释当耳间相位(或幅度或频率)动态变化时的动态效应。更深入地了解这些令人惊讶的效应，就像在听觉中脑看到的那样，应该有助于发展一种理论，即如何在大脑中分析声源的运动。该项目得到了应用数学和计算数学计划以及MPS多学科活动办公室和生物计算神经科学计划的支持。

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.