Multisensory Integration and Cortical Plasticity in Cochlear Implant Users

人工耳蜗使用者的多感觉整合和皮质可塑性

• 批准号: 10683175
• 负责人: Ansley Kunnath
• 金额: $ 3.28万
• 依托单位: VANDERBILT UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10683175
• 关键词: Adult; Affect; Age; American; Auditory; Auditory area; Behavioral; Brain; Brain region; Clinical; Clinical Data; Cochlear Implants; Cochlear implant procedure; Complement; Comprehension; Cueing for speech; Cues; Data; Devices; Electrodes; Electroencephalography; Environment; Exhibits; Fellowship; Future; Hearing; Individual; Intervention; Laboratory Finding; Machine Learning; Magnetic Resonance Imaging; Measures; Modality; Modeling; Morphologic artifacts; Neurosciences; Operative Surgical Procedures; Otolaryngology; Outcome; Patients; Pattern; Perception; Performance; Persons; Phonetics; Physicians; Play; Positioning Attribute; Predictive Factor; Procedures; Research; Role; Scientist; Sensorineural Hearing Loss; Sensory; Sensory Process; Speech; Speech Perception; Standardization; Stimulus; Superior temporal gyrus; Time; Visual; Visual Cortex; audiovisual speech; deaf; deafness; disability; expectation; experimental study; functional near infrared spectroscopy; hearing impairment; hearing restoration; implantation; improved; innovation; insight; interest; machine learning model; machine learning prediction algorithm; multisensory; neural correlate; neuroimaging; neuroprosthesis; normal hearing; novel; predictive modeling; predictive tools; preimplantation; prognostic value; random forest; regression algorithm; response; sensory cortex; sensory integration; speech recognition; speech synthesis; success; support vector machine; surgery outcome; theories; visual performance; visual processing; visual speech

ABSTRACT Hearing loss is a major cause of disability that affects over 48 million Americans. Cochlear implants (CIs) are neuroprosthetic devices that allow people with profound hearing loss to recover hearing and speech comprehension. However, CI surgery outcomes are highly variable and difficult to predict, which creates a challenge for clinicians to guide patient decisions and expectations. Speech recognition is a multisensory process. Although it is known that visual speech cues can improve auditory speech recognition, the visual and audiovisual abilities of CI users have not been well characterized before and after cochlear implantation. In my preliminary data, I show that pre-implantation visual and audiovisual speech recognition predicts post- implantation auditory speech recognition, suggesting that multisensory integration may play an underappreciated role in CI outcomes. In the proposed experiments, I will explore changes in visual and audiovisual performance following CI surgery through a battery of sensory experiments (Aim 1). I will also assess the neural correlates of any behavioral changes using an innovative approach by simultaneously recording electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) responses over time (Aim 2). Finally, I will identify pre-implantation factors that predict post-implantation speech recognition and synthesize these data into a prediction model using machine learning (Aim 3). Through the experiments proposed in this fellowship application, I will comprehensively characterize the longitudinal changes in sensory perception and cortical organization following cochlear implantation. I will also use these findings to develop a novel clinical tool for predicting CI outcomes. The proposed plan integrates my research interests in auditory neuroscience with my clinical interests in otolaryngology, and it will set me up for success as a future physician-scientist.

摘要