Sound encoding by neural populations in auditory cortex during behavior

项目摘要 在整个生命过程中，人类和其他动物都在调整自己的听觉，以感知声音的重要特征。 成功的行为决策。听力正常的人能够检测和区分重要的 在拥挤嘈杂的场景中发出声音，并在第一次见面时理解个人的讲话。 然而，患有外周听力损失或中央处理障碍的患者通常在听力方面存在问题。 这些具有挑战性的设置。即使他们能够准确地感知声音，额外的听力努力 对其他认知功能产生负面影响。更好地理解健康的听觉是如何 系统在认知挑战性环境中的运作将支持针对这些缺陷的新疗法。 这个项目将研究听觉系统如何代表声音信息，因为它在具有挑战性的操作 声学环境有三个具体目标。首先，高密度微电极阵列将用于 在需要检测的行为期间，记录听觉皮层中神经群的同时活动 声音被噪音掩盖或学习新的声音奖励协会。多个神经元的记录将 能够表征信息是如何被神经群体的同时活动编码的。这些 实验将检验这一假设，即听觉皮层中的群体活动产生表征， 不受无关的干扰声音的影响其次，光遗传学工具将用于识别不同的神经元。 皮质中的细胞类型（兴奋性与抑制性）。这项研究将检验这一假设，即紧张性激活 抑制性神经元可以解释行为过程中群体活动的变化。第三，机器学习工具将 用于模拟同时记录的神经活动。这些实验将检验这样一个假设， 听觉皮层中相同局部解剖回路中的神经元编码关于相对小的 在所有可能的听觉刺激的空间中的域。模型拟合实验数据也将描述如何 行为状态的变化改变了神经元编码声音的方式，并描述了相关的 影响行为过程中神经辨别力的群体活动。这些实验将共同建立 声音的神经表征和提取重要信息的认知过程之间的新联系 从声音中获取成功行为的信息。

Project Summary Throughout life, humans and other animals adapt their hearing to perceive features of sound that are important for successful behavioral decisions. Normal-hearing humans are able to detect and discriminate important sounds in crowded noisy scenes and to understand the speech of individuals the first time they meet. However, patients with peripheral hearing loss or central processing disorders often have problems hearing in these challenging settings. Even when they can perceive sounds accurately, the additional listening effort required negatively impacts other cognitive functions. A better understanding of how the healthy auditory system operates in cognitively challenging contexts will support new treatments for these deficits. This project will study how the auditory system represents sound information as it operates in challenging acoustic environments. There are three specific aims. First, high-density microelectrode arrays will be used to record the simultaneous activity of neural populations in auditory cortex during behaviors that require detecting sounds masked by noise or learning new sound-reward associations. Recording from multiple neurons will enable characterizing how information is encoded by the simultaneous activity of neural populations. These experiments will test the hypothesis that population activity in auditory cortex generates representations that are invariant to irrelevant distracting sounds. Second, optogenetic tools will be used to identify distinct neuronal cell types (excitatory versus inhibitory) in cortex. This study will test the hypothesis that tonic activation of inhibitory neurons can explain changes in population activity during behavior. Third, machine learning tools will be used to model the simultaneously recorded neural activity. These experiments will test the hypothesis that neurons in the same local anatomical circuit in auditory cortex encode information about a relatively small domain in the space of all possible auditory stimuli. Models fit to experimental data will also describe how changes in behavioral state shift the way neurons encode sounds and describe sources of correlated population activity that impact neural discriminability during behavior. Together these experiments will establish new links between neural representation of sound and the cognitive processes that extract important information from sound for successful behavior.