Individual differences in brain networks supporting speech understanding in patientswith cochlear implants

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Abstract Listeners with hearing impairment can often understand spoken language, but with increased effort, taking cognitive resources away from other processes such as attention and memory. An important challenge is therefore to understand how the brain copes with a degraded speech signal and the cognitive processes that are most critical to successful comprehension. Adult listeners with cochlear implants are a unique group in which to investigate effortful listening: They have typically adapted to auditory deprivation for a period of years of profound hearing loss, followed by some degree of hearing restoration following implantation. Following increased auditory input due to cochlear implantation, the degree to which individual listeners are able to successfully recognize speech, especially in the presence of background noise, is extremely variable. Previous attempts to explain this variability in the context of underlying patterns of brain activity have been unsuccessful, in large part because the technical challenges associated with neuroimaging in the presence of an implanted medical device have prevented adequate localization of neural responses to speech. The goal of our research is to understand the cognitive systems that support speech recognition in listeners with cochlear implants and to use knowledge about these systems to improve behavioral outcomes. We do so using converging evidence from behavioral measures and functional brain imaging. We make use of high-density diffuse optical tomography (HD-DOT), a form of optical brain imaging that produces anatomically-localized indices of regional cortical activity. We will map the brain networks supporting speech comprehension in listeners with cochlear implants, which we expect to differ from those engaged by listeners with good hearing. We will then evaluate the degree to which neural markers of effortful listening can predict individual differences in speech recognition success in the presence of background noise. Together the findings will help ground our understanding of cochlear implant-aided speech recognition in a neuroanatomically-constrained framework and develop more accurate outcome measures.