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NOBEL PRIZE 2026

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NIHNATIONAL INSTITUTE ON DEAFNESS AND OTHER COMMUNICATION DISORDERSR01

Sound encoding by neural populations in auditory cortex during behavior

Completed
Institution
Oregon Health & Science University, OR
Principal investigator
Stephen V David
Funding
$325K
Duration
2016–2026
Open portfolio

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Abstract

Project Summary Throughout life, humans and other animals adapt their hearing to perceive features of sound that are important for successful behavioral decisions. Normal-hearing humans are able to detect and discriminate important sounds in crowded noisy scenes and to understand the speech of individuals the first time they meet. However, patients with peripheral hearing loss or central processing disorders often have problems hearing in these challenging settings. Even when they can perceive sounds accurately, the additional listening effort required negatively impacts other cognitive functions. A better understanding of how the healthy auditory system operates in cognitively challenging contexts will support new treatments for these deficits. This project will study how the auditory system represents sound information as it operates in challenging acoustic environments. There are three specific aims. First, high-density microelectrode arrays will be used to record the simultaneous activity of neural populations in auditory cortex during behaviors that require detecting sounds masked by noise or learning new sound-reward associations. Recording from multiple neurons will enable characterizing how information is encoded by the simultaneous activity of neural populations. These experiments will test the hypothesis that population activity in auditory cortex generates representations that are invariant to irrelevant distracting sounds. Second, optogenetic tools will be used to identify distinct neuronal cell types (excitatory versus inhibitory) in cortex. This study will test the hypothesis that tonic activation of inhibitory neurons can explain changes in population activity during behavior. Third, machine learning tools will be used to model the simultaneously recorded neural activity. These experiments will test the hypothesis that neurons in the same local anatomical circuit in auditory cortex encode information about a relatively small domain in the space of all possible auditory stimuli. Models fit to experimental data will also describe how changes in behavioral state shift the way neurons encode sounds and describe sources of correlated population activity that impact neural discriminability during behavior. Together these experiments will establish new links between neural representation of sound and the cognitive processes that extract important information from sound for successful behavior.

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R01NATIONAL INSTITUTE ON DEAFNESS AND OTHER COMMUNICATION DISORDERSAuditory System Study Section[AUD]cortexsoundauditory cortexsoundsexperiments testhearingauditorypopulation activity

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