Circuit Mechanisms of Sound Processing and Detection in the Auditory Pathway

听觉通路中声音处理和检测的电路机制 听觉感知依赖于对传入信号的预测统计，无论是识别一个人的语音 在拥挤的房间里与人交谈，或者认出森林里流淌的小溪的声音。人脑 检测声音中的统计规律作为预测的一个基本方面，从对 重复的声音模式和对意外声音的增强反应。多项研究表明，神经元 通过自适应减少对规则信号的响应，这有助于预测。然而，适应 迄今为止，仅凭这一点还不足以解释对动物细胞和神经元群体水平的预测和研究。 部分支持现有的预测编码理论。因此，电路级机制 对声音中音调频率以外的统计规律的预测，以及它们在行为中的作用，仍然未知。我们的 目标是弥合这一知识差距，并确定预测信号和检测统计规律性的电路 它在听觉行为中的违规行为。识别统计预测的前馈和反馈分量 声音在听觉系统中的规律性，我们结合了光遗传选择性微扰和大规模成像 清醒小鼠的电生理学和行为学方法。首先，我们测试兴奋性抑制是否以及如何抑制 听觉皮质(AC)内的相互作用为声音模式建立预测代码，检测统计规律，以及 帮助增强对意外声音的响应。其次，我们测试统计检测是否以及如何检测 神经元水平的规律性有助于行为检测声音规律性的变化。第三，我们测试是否 以及来自更高皮质区域的反馈如何提供有关规律性和违规性的信息。我们的结果将确定 编码统计规律的神经元回路及其在声音中的破坏及其在听觉中的作用 行为。

CIRCUIT MECHANISMS OF SOUND PROCESSING AND DETECTION IN THE AUDITORY PATHWAY Auditory perception relies on predicting statistics of incoming signals, be it identifying the speech of a conversation partner in a crowded room or recognizing the sound of a bubbling brook in a forest. The human brain detects statistical regularities in sounds as a fundamental aspect of prediction, evidenced by reduced responses to repeated sound patterns and enhanced responses to unexpected sounds. Multiple studies demonstrate that the neuronal responses to regular signals are reduced through adaptation, which can contribute to prediction. However, adaptation alone is not sufficient to account for prediction and studies at cellular and neuronal population level in animals thus far lend onto partial support to existing theories of predictive coding. As such, the circuit level mechanisms for the prediction of statistical regularities beyond tone frequency in sounds, and their role in behavior, remain unknown. Our goal is to close this gap in knowledge and to determine the circuits that predict signals and detect statistical regularity and its violation in auditory behavior. To identify feedforward and feedback components of prediction of statistical regularities in sounds in the auditory system, we combine optogenetic selective perturbation and large-scale imaging and electrophysiology with behavioral methods in awake mice. First, we test whether and how excitatory-inhibitory interactions within the auditory cortex (AC) establish predictive code for sound patterns, detect statistical regularities, and contribute to enhanced responses for unexpected sounds. Second, we test whether and how detection of statistical regularities at the neuronal level contributes to behavioral detection of change in sound regularity. Third, we test whether and how feedback from higher cortical areas provides information about regularity and violation. Our results will identify the neuronal circuits for encoding statistical regularity and its violation in sound and establish their role in auditory behavior.