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.

项目概要 在整个生命过程中，人类和其他动物都会调整听力以感知重要的声音特征 成功的行为决策。听力正常的人能够检测和区分重要的内容 在拥挤嘈杂的场景中发出声音并理解人们第一次见面时的讲话。 然而，患有周围性听力损失或中枢处理障碍的患者通常会出现听力问题。 这些具有挑战性的设置。即使他们能够准确地感知声音，额外的聆听努力 所需的负面影响其他认知功能。更好地了解如何保持健康的听觉 系统在认知挑战的环境中运行将支持针对这些缺陷的新疗法。 该项目将研究听觉系统在具有挑战性的情况下如何表示声音信息 声学环境。具体目标有三个。首先，高密度微电极阵列将用于 记录需要检测的行为期间听觉皮层神经群的同时活动 声音被噪音掩盖或学习新的声音奖励关联。来自多个神经元的记录将 能够表征神经群体的同时活动如何编码信息。这些 实验将检验听觉皮层中的群体活动产生的表征的假设 对于不相关的分散注意力的声音是不变的。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：强直激活 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。这些实验将检验以下假设： 听觉皮层中同一局部解剖回路中的神经元编码有关相对较小的信息 所有可能的听觉刺激的空间域。适合实验数据的模型还将描述如何 行为状态的变化改变了神经元编码声音和描述相关来源的方式 影响行为过程中神经辨别能力的群体活动。这些实验将共同建立 声音的神经表征与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。