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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.
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Dynamic neural coding of spectro-temporal sound features during free movement
Dissemination of tools and methods for modeling state-dependent neural sensory coding
Sound encoding by neural populations in auditory cortex during behavior
Top-down control of auditory processing in the cortico-collicular network (Administrative Supplement)
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