Pathway to Independence Award, Independent

人类和其他哺乳动物能够识别和区分声音，即使在被掩盖的情况下。 大量不相关的噪音。虽然这一过程往往是毫不费力的动物，共同来源 环境噪声的严重干扰自动语音处理器和失真的输出 助听器和假肢。了解中央处理复杂嘈杂声音的方式 大脑区域可以为如何应对这些持续的挑战提供重要的见解。的目标 本项目旨在研究大脑皮层对自然噪声听觉刺激的反应， 神经生理学机制的噪声信号的鲁棒感知。初步实验将 研究在被动听力过程中神经表征中自然信号的自动增强。 这些实验将特别关注环境噪声， 听觉处理系统进一步的实验将研究神经机制如何促进 当选择性注意力指向听觉和多感官视听特征时，这一过程。 计算分析将用于理解单个神经元所采用的算法， 神经群体来增强重要信号的表示。除了揭示 感觉处理的基本神经机制，这些实验将提供洞察如何 可以为听力受损的患者改进声音处理器。

Humans and other mammals are able to recognize and discriminate sounds even when masked by substantial irrelevant noise. Although this process is often effortless for animals, common sources of environmental noise severely confound automatic speech processors and distort the output of hearing aids and prosthetics. Understanding how complex noisy sounds are processed in central brain areas can provide critical insights into how to address these ongoing challenges. The goal of this project is to study cortical responses to naturalistic noisy auditory stimuli in order to understand neurophysiological mechanisms for the robust perception of noisy signals. Initial experiments will study automatic enhancement of natural signals in neural representations during passive listening. These experiments will focus specifically on environmental noise that challenges engineered auditory processing systems. Further experiments will study how neuronal mechanisms facilitate this process when selective attention is directed to auditory and multisensory audio-visual features. Computational analysis will be used to understand the algorithms employed by single neurons and neural populations to enhance the representation of important signals. In addition to revealing basic neural mechanisms of sensory processing, these experiments will provide insight into how sound processors can be improved for hearing-impaired patients.