The effect of encoding cue reliability on the function and development of the barn owl auditory system

编码线索可靠性对仓鸮听觉系统功能和发育的影响

• 批准号: 10388026
• 负责人: Keanu Shadron
• 金额: $ 4.6万
• 依托单位: ALBERT EINSTEIN COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-12-01 至 2025-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10388026
• 关键词: effect; encoding; cue; reliability; function

Project Summary In order to accurately perceive the world and respond accordingly, the brain has to deal with noise inherent in sensory cues. One method is for the brain to learn which cues are reliable across contexts and rely on these cues in the future. Previous studies have demonstrated that sensory systems are able to actively learn recent statistics underlying cue reliability and adapt to short term changes. However, relatively little is known about whether and how sensory systems adapt to natural statistics of sensory cues that are expected to be permanent. While humans display biases based on long term patterns of sensory cue statistics, the neural mechanisms underlying this are unknown. To address these knowledge gaps, this proposal will investigate whether and how anticipated reliability of binaural spatial cues determines sound localization of barn owls. Barn owls compute the interaural time difference (ITD) to determine azimuthal location. Previous work showed that the signal-to-noise ratio of ITD varies across frequencies in a location dependent manner, based on the acoustical properties of the head. Thus, certain frequencies convey more reliable ITD cues for sounds from a given location, and the neural tuning in the midbrain is optimized to reflect this pattern. This provides a system where the reliability of natural acoustic cues is represented, allowing for the investigation of the effect of anticipating sensory statistics on perceptual discriminability and how it is learned. Recent work by our group has shown evidence that human auditory perception is also shaped by ITD statistics, potentially allowing the properties of neural coding investigated in this project to explain the bases of these findings. The overall hypothesis is that barn owls learn to anticipate cue reliability during juvenile critical periods, leading to biases in neural and behavioral processing. Behavioral and electrophysiological approaches along with computational methodology will be used to test this hypothesis. Experiments outlined in Aim 1 will determine whether barn owls show better sound discrimination for frequencies anticipated to be reliable. Aim 2 will investigate whether and how the neural population displaying the pattern of ITD-frequency tuning described in the midbrain explains spatial discriminability. Novel multi-unit recordings in the midbrain in vivo along with computational techniques will be used to address this. Aim 3 will elucidate the capacity of the barn owl to learn altered forms of cue reliability, by changing the acoustical properties of the owl’s head at different stages of development. Altogether, this proposal will provide understanding on the mechanisms used to deal with long term patterns of cue reliability. The data will offer insight into how the auditory system learns the natural statistics underlying sensory noise to optimize perception, as well as its capacity to adapt to unanticipated changes.

项目概要 为了准确地感知世界并做出相应的反应，大脑必须处理噪音 一种方法是让大脑了解哪些线索在不同情境中是可靠的并依赖。 先前的研究表明，感觉系统能够主动地根据这些线索进行预测。 了解线索可靠性的最新统计数据并适应短期变化然而，相对较少。 了解感觉系统是否以及如何适应感觉线索的自然统计数据 虽然人类会根据感官线索统计的长期模式表现出偏见，但神经系统会表现出偏见。 其背后的机制尚不清楚，为了解决这些知识差距，本提案将进行调查。 双耳空间线索的预期可靠性是否以及如何决定谷仓猫头鹰的声音定位。 先前的研究表明，谷仓猫头鹰通过计算耳间时间差（ITD）来确定方位角位置。 ITD 的信噪比以位置相关的方式随频率变化，基于 因此，某些频率可以为来自头部的声音传达更可靠的 ITD 线索。 给定位置，并且中脑的神经调节被优化以反映这种模式，这提供了一个系统。 其中代表了自然声学线索的可靠性，允许研究 预测关于感知辨别力的感官统计数据以及我们小组最近的工作。 有证据表明人类听觉感知也受到 ITD 统计数据的影响，这可能允许 该项目研究了神经编码的特性，以解释这些发现的总体基础。 假设仓鸮在幼年关键时期学会预测线索的可靠性，从而导致 神经和行为处理的偏差以及行为和电生理学方法。 将使用计算方法来检验这一假设。目标 1 中概述的实验将确定。 谷仓猫头鹰是否对预期可靠的频率表现出更好的声音辨别能力。 研究神经群体是否以及如何表现出 ITD 频率调谐模式。 中脑解释了体内中脑的空间辨别能力。 计算技术将用于解决这个问题，目标 3 将阐明仓鸮的学习能力。 通过改变猫头鹰头部在不同阶段的声学特性来改变提示可靠性的形式 总而言之，该提案将提供对用于处理长期问题的机制的理解。 线索可靠性的术语模式将提供对听觉系统如何学习自然的洞察。 感官噪音的统计数据可以优化感知，以及适应意外情况的能力 变化。