Selective Attention: How does Neural Response Modulation in Auditory Cortex Enable Auditory Scene Analysis?

选择性注意：听觉皮层中的神经反应调制如何实现听觉场景分析？

• 批准号: BB/N001818/1
• 负责人: Jennifer Bizley
• 金额: $ 67.2万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FN001818%2F1
• 关键词: Selective; Attention; How; does; Neural

Listening to conversation in a crowded room is one of the greatest challenges that the auditory system faces, and the most common cause of complaint for many of the 10 million people in the UK who suffer hearing loss. For example, to fully appreciate the piece of gossip that your friend is telling you in a restaurant, you must be able to separate his voice from the voices of other people, the clatter of glasses, and the music playing in the background. Your brain is able to 'select' the voice of your friend over all these other sounds - perhaps on the basis of where he is standing, or the pitch of his voice. Normal hearing listeners achieve this feat effortlessly, although engineers have yet to create a machine that can successfully match such signal separation in noisy backgrounds. In this proposal we try to understand how the neural machinery of the brain is able to extract sounds of interest while ignoring others. Our work focuses on a brain area called the auditory cortex; an area that is thought to be necessary for listening in complex situations like the one described above. Our goal is to understand how the responses of neurons in auditory cortex represent multiple competing sounds, and how the neural responses can be shaped in order to best represent sounds according to the listener's current demands.In this proposal we train animals in a series of listening tasks that will enable us to impose different demands on auditory cortex. Animals will listen for a target word amongst a series of non-target words. In some cases they will do this in silence, in others in the presence of background noise. In further variations they will listen to two streams of speech, each from a different talker, and from different locations, and be asked to selectively attend to one talker over the other (equivalent to trying to listen to your friend while ignoring the loud man behind her). We will record from neurons in auditory cortex while animals perform these tasks in order to understand how the different task requirements change the way in which sounds evoke neural activity. Auditory cortex is made of multiple, hierarchically organised areas that are thought to perform different functions. We will determine whether areas early in this hierarchy are affected by attention differently from those in higher areas.In the second part of this project we will use a technique called optogenetics to selectively silence neural activity in particular regions of auditory cortex. We will test the hypothesis that different areas of Auditory Cortex facilitate different sorts of attention - for example separating sounds according to their location in space, as opposed to the pitch or timbre or a particular talker's voice. Finally we will determine whether feedback from higher auditory areas to primary auditory areas is essential for active listening. This work would represent a fundamental advance in our knowledge of the role of these 'feedback' projections and the role that they play in active listening.Our work has the potential to enable the development of more sophisticated, biologically inspired, signal processing devices for hearing aids and cochlear implants - both of which perform poorly in many real-world listening conditions. Listeners whose hearing is assessed via an audiogram as normal can still struggle with listening in noisy situations - this problem is particularly acute in aged listeners. Problems in processing complex sounds underlie Central Auditory Processing Disorder, and disorders of attention are thought to underpin a variety of developmental disorders including autism, attention related hyperactivity disorder, as well as dementia and other neuropsychiatric conditions. Understanding the neural mechanisms in the healthy brain responsible for engaging attention to select sources in a sound scene will lay the foundation for understanding, and potentially treating, conditions in which these mechanisms are impaired.

在拥挤的房间里听谈话是听觉系统面临的最大挑战之一，也是英国1000万听力损失患者中许多人抱怨的最常见原因。例如，要充分欣赏你的朋友在餐厅告诉你的八卦，你必须能够将他的声音与其他人的声音、玻璃杯的叮当声和背景音乐分开。你的大脑能够在所有其他声音中“选择”你朋友的声音--也许是基于他站在哪里，或者他的声音的音高。正常听力的听众可以毫不费力地实现这一壮举，尽管工程师们还没有创造出一种机器，可以在嘈杂的背景下成功地匹配这种信号分离。在这个建议中，我们试图了解大脑的神经机制如何能够提取感兴趣的声音，而忽略其他声音。我们的工作集中在一个叫做听觉皮层的大脑区域，这个区域被认为是在复杂的情况下倾听所必需的，就像上面描述的那样。我们的目标是了解听觉皮层神经元的反应如何代表多种竞争的声音，以及如何根据听者的当前需求来塑造神经反应，以便最好地代表声音。在这个提议中，我们训练动物进行一系列的听力任务，这将使我们能够对听觉皮层施加不同的要求。动物会在一系列非目标词中寻找目标词。在某些情况下，他们会在沉默中这样做，在其他情况下，在存在背景噪音的情况下。在进一步的变化中，他们将听取两个语音流，每个语音流来自不同的说话者，来自不同的位置，并被要求选择性地关注一个说话者而不是另一个（相当于试图倾听你的朋友，而忽略她身后大声说话的人）。我们将记录动物执行这些任务时听觉皮层中的神经元，以了解不同的任务要求如何改变声音引起神经活动的方式。听觉皮层是由多个分层组织的区域组成的，这些区域被认为执行不同的功能。我们将确定这个层次中的早期区域是否与高级区域不同地受到注意力的影响，在这个项目的第二部分，我们将使用一种称为光遗传学的技术来选择性地沉默听觉皮层特定区域的神经活动。我们将测试这样一个假设，即听觉皮层的不同区域促进了不同类型的注意力--例如，根据声音在空间中的位置来区分声音，而不是音高、音色或特定说话者的声音。最后，我们将确定是否从高级听觉区反馈到初级听觉区是必不可少的积极倾听。这项工作将代表我们对这些“反馈”投射的作用以及它们在主动听力中所起作用的认识的根本性进步。我们的工作有可能使助听器和人工耳蜗植入物的更复杂的、受生物启发的信号处理设备的开发成为可能--这两种设备在许多现实世界的听力条件下表现不佳。通过听力图评估听力正常的听众仍然可以在嘈杂的情况下努力倾听-这个问题在老年听众中特别严重。处理复杂声音的问题是中枢听觉处理障碍的基础，注意力障碍被认为是各种发育障碍的基础，包括自闭症，注意力相关的多动症，以及痴呆和其他神经精神疾病。了解健康大脑中负责将注意力吸引到声音场景中的选择源的神经机制将为理解和潜在治疗这些机制受损的情况奠定基础。

项目成果

The role of temporal coherence and temporal predictability in the build-up of auditory grouping

时间连贯性和时间可预测性在听觉分组建立中的作用

• DOI: 10.1101/2021.06.27.449898
• 发表时间: 2021
• 作者: Sollini J

The role of temporal coherence and temporal predictability in the build-up of auditory grouping.

• DOI: 10.1038/s41598-022-18583-0
• 发表时间: 2022-08-25
• 期刊: SCIENTIFIC REPORTS
• 影响因子: 4.6
• 作者: Sollini, Joseph;Poole, Katarina C.;Blauth-Muszkowski, Dominic;Bizley, Jennifer K.
• 通讯作者: Bizley, Jennifer K.

Gradient boosted decision trees reveal nuances of auditory discrimination behavior

• DOI: 10.1101/2023.06.16.545302
• 发表时间: 2024-02
• 期刊: PLOS Computational Biology
• 影响因子: 4.3
• 作者: Carla Griffiths;Jules Lebert;J. Sollini;J. Bizley