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

项目摘要 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 与生俱来的感官暗示。一种方法是大脑学习哪些线索在不同背景下是可靠的，并依赖于 在未来的这些线索上。此前的研究表明，感官系统能够主动 了解球杆可靠性背后的最新统计数据，并适应短期变化。然而，相对较少的是 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 成为永久的。虽然人类基于感觉线索统计的长期模式表现出偏见，但神经 这背后的机制尚不清楚。为了解决这些知识差距，这项提案将调查 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。 谷仓猫头鹰计算耳间时间差(ITD)来确定方位位置。先前的工作表明 ITD的信噪比以与位置相关的方式随频率变化，基于 头部的声学特性。因此，某些频率为来自一个语音的声音传递了更可靠的ITD提示 在给定的位置，中脑的神经调谐被优化以反映这种模式。这提供了一种系统 在表示自然声学提示的可靠性的情况下，允许调查 预测感知辨别能力的感官统计数据以及它是如何学习的。我们小组最近的工作 已经表明人类的听觉也受ITD统计数据的影响，潜在地允许 本项目研究了神经编码的特性，以解释这些发现的基础。整体而言 假设是谷仓猫头鹰在幼年关键时期学习预测线索可靠性，导致 神经和行为处理方面的偏见。行为和电生理方法以及 计算方法将被用来检验这一假设。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。目标2将 研究神经群体是否以及如何显示ITD-频率调谐模式 中脑解释了空间辨别能力。活体中脑的新的多单位记录 计算技术将被用来解决这个问题。目标3将阐明谷仓猫头鹰的学习能力 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 发展。总之，这项建议将提供对用于处理Long的机制的理解 球杆可靠性的术语模式。这些数据将提供对听觉系统如何学习自然的洞察力 感官噪音的统计数据，以优化感知，以及其适应意外情况的能力 改变。

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.