Multiscale modeling of the cocktail party problem

项目总结 在我们生命的每一刻，一种刺耳的声音冲击着我们的耳朵，挑战着我们的大脑 感受我们生活的复杂声环境--一种被称为鸡尾酒会的现象 问题(CPP)。到目前为止，理解这一现象的努力主要集中在声学线索在 在大脑中塑造听觉物体的感觉编码。然而，听和听不是一回事。它参与了 感觉和认知过程，使大脑能够适应其计算原语和神经 对不断变化的音景进行编码，并改变需求以注意场景中的各种声音。海流 Proposal提出了一种听觉感知的自适应理论，该理论整合了两种感觉的作用 在一个统一的多尺度理论中的机制和认知控制，该理论结合了 单个神经元、神经群和跨脑区。这一假说的核心是快速神经的作用 根据大脑的统计结构重塑大脑对声刺激的反应的可塑性 声音场景，由记忆和注意力的反馈机制引导。研究计划解释了这一点 将假设转化为采用分布式推理体系结构的统一多尺度模型(目标1)。这项计划 采用分层动态系统，跟踪不同分辨率下的刺激统计结构 和时间尺度，并根据记忆和注意力的先验来调整他们的反应。这个架构是 作为跳板，用来预测感觉和认知机制之间的相互作用 CPP。它还为将与现有声音交互的场景分析问题提供了一般解决方案 技术(例如语音识别、医疗诊断、目标跟踪和监视)。这是计算性的 使用来自人体受试者的实验的经验数据(目标2)来告知和验证努力 心理声学和脑电波；以及行为雪貂的单单位电生理学。实验搭建了 使用丰富的刺激来操纵统计结构以及 受试者(人/动物)的注意力焦点。最终的综合理论是在#年的感性研究中提炼出来的。 年轻人和老年人，他们的感知受到复杂的听音景的高度挑战(目标3)。这 努力产生关于多源环境中听觉感知故障的可测试预测，尤其是 并找出可能由感官或认知因素引起的功能障碍。通过将光线投射到 CPP过程中感觉和认知相互作用的功能原理和神经基础， 这项研究将对我们在杂乱场景中理解听觉产生重大影响。此外, 它与健康和幸福有直接的关系，特别是对于改善感官的交流辅助 受损和老龄化人口；以及对声音技术(例如语音)进行适应性处理 识别、音频分析)，大部分保持静态和硬连线。 1

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