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Functional characteristics of speech perception decline in healthy aging based on resting-state EEG-fNIRS

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机构: [1]School of Biomedical Engineering, Capital Medical University, Beijing 100069, China [2]Laboratory for Clinical Medicine, Capital Medical University, Beijing 100069, China [3]Beijing Key Laboratory of Fundamicationental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing 100069, China [4]Beijing Institute of Otolaryngology, Otolaryngology-Head and Neck Surgery, Key Laboratory of Otolaryngology Head and Neck Surgery (Capital Medical University), Ministry of Education, Beijing Tongren Hospital, Capital Medical University, Beijing 100005, China [5]Xinjiang International Medical Center (Xinjiang International Hospital), Urumqi 830017, China
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关键词: Aging Electroencephalography Functional near-infrared spectroscopy Microstates Speech recognition

摘要:
Older adults frequently struggle with speech perception in noisy environments, a challenge influenced by age-related changes in brain function. Resting-state brain activity has emerged as a crucial area of research for understanding alterations in functional connectivity associated with aging. We herein used a multimodal approach, integrating electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), to examine how aging affects the resting-state auditory network. Additionally, we assessed speech perception across three age groups-youth group (YG), middle-aged group (MG), and older group (OG)-under varying signal-to-noise ratio (SNR) conditions: speech in quiet (SIQ), moderate noise (SNR = 5 dB), and high noise (SNR = -5 dB). The results indicate that aging is linked to heightened functional connectivity in key brain regions responsible for speech processing and cognitive control, including the dorsolateral prefrontal cortex, Broca's area, Wernicke's area, and both the primary auditory cortex and auditory association cortices. However, despite this heightened connectivity, critical network properties-such as small-worldness, local efficiency, and nodal efficiency-show a decline, particularly in speech-related regions such as the left superior temporal gyrus. EEG microstate analysis further highlights a shift in brain dynamics with aging, demonstrating a transition from microstate C to microstate D. This shift suggests a compensatory reliance on executive functions, likely reflecting an adaptive mechanism to counteract age-related declines in auditory processing efficiency. Notably, higher small-worldness and local efficiency correlate with better speech recognition in noisy environments, while specific microstate features are associated with improved speech perception performance. These findings indicate that aging alters brain network dynamics, leading to compensatory neural adaptations that support auditory processing. By integrating EEG and fNIRS, this study provides a comprehensive analysis of the neural mechanisms underlying age-related changes in speech perception and cognitive control. The results underscore the importance of functional connectivity and network efficiency in maintaining speech comprehension in older adults, provide exploratory evidence on neural features underlying age-related auditory decline, which may inform future intervention research.Copyright © 2025. Published by Elsevier B.V.

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出版当年[2025]版:
大类 | 2 区 医学
小类 | 2 区 听力学与言语病理学 2 区 耳鼻喉科学 3 区 神经科学
最新[2025]版:
大类 | 2 区 医学
小类 | 2 区 听力学与言语病理学 2 区 耳鼻喉科学 3 区 神经科学
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第一作者机构: [1]School of Biomedical Engineering, Capital Medical University, Beijing 100069, China [2]Laboratory for Clinical Medicine, Capital Medical University, Beijing 100069, China [3]Beijing Key Laboratory of Fundamicationental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing 100069, China
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通讯机构: [1]School of Biomedical Engineering, Capital Medical University, Beijing 100069, China [2]Laboratory for Clinical Medicine, Capital Medical University, Beijing 100069, China [3]Beijing Key Laboratory of Fundamicationental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing 100069, China [5]Xinjiang International Medical Center (Xinjiang International Hospital), Urumqi 830017, China
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