Multiscale modeling of the cocktail party problem

鸡尾酒会问题的多尺度建模

基本信息

批准号：
10434784
负责人：
Mounya Elhilali
金额：
$ 44.35万
依托单位：
JOHNS HOPKINS UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-01 至 2024-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10434784
关键词：
Acoustics Adult Aging Animals Architecture Area Attention Auditory Auditory Perception Auditory area Brain Clutterings Cognitive Communication Complex Cues Data Databases Diagnosis Ear Electroencephalography Electrophysiology (science)Engineering Environment Face Failure Feedback Ferrets Goals Health Hearing Hearing Aids Human Impairment Individual Knowledge Life Light Linguistics Medical Memory Methods Modeling Monitor Nature Neuronal Plasticity Neurons Pattern Perception Personal Satisfaction Physiology Play Population Process Psychoacoustics Psychophysics Research Resolution Role Scheme Sensory Sensory Aids Sensory Process Shapes Short-Term Memory Speech Stimulus Structure System Techniques Technology Testing Time Training Translating Validation Work aging brain awake base brain shape cognitive control cognitive process communication aid dynamic system experimental study hearing impairment human subject improved innovation interest long term memory multi-scale modeling neural circuit neural correlate novel novel strategies perceptual organization predictive modeling preservation relating to nervous system response segregation sensory integration sensory mechanism sound speech recognition theories translational impact

项目摘要

Project summary At every instant of our lives, a cacophony of sounds impinges on our ears and challenges our brain to make sense of the complex acoustic environment in which we live – a phenomenon referred to as the cocktail party problem (CPP). Up till now, efforts to understand this phenomenon focused on the role of acoustic cues in shaping sensory encoding of auditory objects in the brain. Yet, listening is not the same as hearing. It engages both sensory and cognitive processes to enable the brain to adapt its computational primitives and neural encoding to the changing soundscape and shifting demands to attend to various sounds in the scene. The current proposal puts forth an adaptive theory of auditory perception which integrates the role of both sensory mechanisms and cognitive control in a unified multiscale theory that combines neural processes at the level of single neurons, neural populations and across brain areas. Central to this hypothesis is the role of rapid neural plasticity that reshapes brain responses to acoustic stimuli according to the statistical structure of the soundscape, guided by feedback mechanisms from memory and attention. The research plan translates this hypothesis into a unified multiscale model employing a distributed inference architecture (Aim 1). This scheme employs hierarchical dynamical systems that track the statistical structure of the stimulus at different resolutions and time-scales, and adapt their responses based on both memory and attentional priors. This architecture is used as springboard to predict the interaction between sensory and cognitive mechanisms at play during the CPP. It also affords a general solution to the scene analysis problem that will be interfaced with existing sound technologies (e.g. speech recognition, medical diagnosis, target tracking and surveillance). This computational effort is informed and validated with empirical data (Aim 2) from experiments in human subjects, using psychoacoustics and EEG; as well as single-unit electrophysiology in behaving ferrets. The experiments shed light of neural processes underlying the CPP using rich stimuli that manipulate the statistical structure as well as attentional focus of subjects (humans/animals). The final integrated theory is refined in perceptual studies in young and aging adults whose perception is highly challenged by complex listening soundscapes (Aim 3). This effort generates testable predictions about failures in auditory perception in multisource environments especially in aging adults and pinpoints possible malfunctions due to sensory or cognitive factors. By shedding light on the functional principles and neural underpinnings underlying the sensory and cognitive interaction during the CPP, the research will have a big impact on our understanding of auditory perception in cluttered scenes. In addition, it has direct relevance to health and wellbeing, particularly for improving communication aids for the sensory impaired and aging populations; as well as affording adaptive processing to sound technologies (e.g. speech recognition, audio analytics) which remain for the most part static and hard-wired. 1

项目概要在我们生命的每时每刻，都有刺耳的声音冲击着我们的耳朵，挑战着我们的大脑我们所生活的复杂声学环境的感觉——这种现象被称为鸡尾酒会到目前为止，理解这一现象的努力主要集中在声音线索的作用上。然而，聆听与听觉不同。感觉和认知过程使大脑能够适应其计算原语和神经元根据不断变化的音景和不断变化的需求进行编码，以适应当前场景中的各种声音。该提案提出了一种听觉感知的适应性理论，该理论整合了感觉和感官的作用统一的多尺度理论中的机制和认知控制，该理论结合了神经过程的水平这一假设的核心是快速神经元的作用。可塑性根据大脑的统计结构重塑大脑对声音刺激的反应该研究计划将这一点转化为由记忆和注意力反馈机制引导的音景。将假设转化为采用分布式推理架构的统一多尺度模型（目标 1）。采用分层动力系统来跟踪不同分辨率下刺激的统计结构和时间尺度，并根据记忆和注意力先验调整他们的反应。用作预测感觉和认知机制之间的相互作用的跳板 CPP 还提供了与现有声音交互的场景分析问题的通用解决方案。技术（例如语音识别、医疗诊断、目标跟踪和监视）。努力是通过人类受试者实验的经验数据（目标 2）来了解和验证的，使用心理声学和脑电图；以及雪貂行为的单单位电生理学。根据 CPP 的神经过程，使用丰富的刺激来操纵统计结构以及最终的综合理论在感知研究中得到完善。感知受到复杂聆听音景的高度挑战的年轻人和老年人（目标 3）。努力生成关于多源环境中听觉感知失败的可测试预测，尤其是通过阐明老年人的情况，并查明由于感觉或认知因素可能出现的功能障碍。 CPP 期间感觉和认知相互作用的功能原理和神经基础，这项研究将对我们对杂乱场景中听觉感知的理解产生重大影响。它与健康和福祉直接相关，特别是改善感官沟通辅助受损和老龄化人口；以及为声音技术（例如语音）提供自适应处理识别、音频分析），其中大部分仍然是静态的和硬连线的。 1