Sound encoding by neural populations in auditory cortex during behavior

行为过程中听觉皮层神经群的声音编码

• 批准号: 10302718
• 负责人: Stephen V David
• 金额: $ 32.06万
• 依托单位: OREGON HEALTH & SCIENCE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-02-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10302718
• 关键词: Acoustics; Affect; Anatomy; Animals; Area; Arousal; Attention; Auditory; Auditory Perception; Auditory Perceptual Disorders; Auditory area; Auditory system; Behavior; Behavioral; Brain; Categories; Code; Cognitive; Complex; Computer Models; Crowding; Data; Dimensions; Discrimination; Electrophysiology (science); Enhancers; Environment; Ferrets; Frequencies; Hearing; Hearing problem; Human; Individual; Interneurons; Label; Lasers; Learning; Life; Link; Machine Learning; Masks; Measures; Mediating; Methods; Microelectrodes; Modeling; Monitor; Neurons; Noise; Operating System; Patients; Performance; Peripheral; Play; Population; Process; Property; Pupil; Reporting; Rewards; Role; Sensory; Shapes; Signal Transduction; Source; Speech; Stimulus; Testing; Time; Training; Virus; auditory processing; auditory stimulus; cell type; cognitive function; cognitive process; deep neural network; density; excitatory neuron; experimental study; flexibility; frontal lobe; hearing impairment; improved; indexing; inhibitory neuron; insight; machine learning method; nervous system disorder; neural model; neuromechanism; neurophysiology; new technology; normal hearing; novel; optogenetics; receptive field; relating to nervous system; sound; tool

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.

项目摘要 在一生中，人类和其他动物会适应他们的听力，以感知重要的声音特征 成功的行为决策。正常听觉的人能够检测并区分重要的 在拥挤的嘈杂场景中听起来，并在第一次见面时了解个人的讲话。 但是，外围听力损失或中央处理障碍的患者通常会出现听力的问题 这些具有挑战性的设置。即使他们能够准确地感知声音，额外的听力也 需要负面影响其他认知功能。更好地了解健康的听觉 系统在认知挑战性的环境中运作将支持这些缺陷的新疗法。 该项目将研究听觉系统在具有挑战性的过程中如何代表声音信息 声学环境。有三个特定的目标。首先，高密度微电极阵列将用于 在需要检测的行为中记录听觉皮层中神经种群的同时活动 听起来被噪音掩盖或学习新的声音奖励关联。来自多个神经元的录制 使信息如何通过神经种群的同时活动来表征信息。这些 实验将检验以下假设：听觉皮层中的种群活动会产生表示形式 与分散注意力无关的声音是不变的。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）。这项研究将检验以下假设 抑制性神经元可以解释行为过程中人群活动的变化。第三，机器学习工具将 用于对同时记录的神经活动进行建模。这些实验将检验以下假设 听觉皮层中同一局部解剖电路中的神经元编码有关相对较小的信息 在所有可能的听觉刺激的空间中的域。适合实验数据的模型还将描述 行为状态的变化改变神经元编码声音的方式并描述相关的来源 影响行为过程中神经可区分性的人群活动。这些实验将共同建立 声音的神经表示与提取重要的认知过程之间的新联系 来自声音的信息成功行为。