噪音(视频)
计算机科学
听力损失
噪声性听力损失
计算机网络
语音识别
听力学
噪声暴露
医学
人工智能
图像(数学)
作者
Ranran Huang,Aijie Wang,Guowei Zhang
摘要
Motivation: Noise-induced hearing loss (NIHL) has become the most frequently recognized occupational disease worldwide, and to explore new functional neuroimaging biomarkers to guide its treatment. Goal(s): To explore the features of static/dynamic functional network connectivity (s/d FNC) in NIHL. Approach: NIHL and age- and education-matched healthy controls (HCs) were recruited, and scanned by T1WI-3DFSPGR, resting-state functional magnetic resonance imaging. The sFNC and dFNC analyses were performed based on independent component analysis. Results: Compared with HCs, NIHL patients had increased sFNC between the ventral attention network (VAN) and executive control network (ECN ); NIHL patients had specifically increased dFNC between the VAN and ECN in state-5. Impact: We provide neuroimaging evidence of sFNC to dFNC brain alterations in patients with NIHL. These methods may unravel the alterations among transmodal plasticity brain areas not involved in the hearing process, and identify new biomarkers to guide its treatment.
科研通智能强力驱动
Strongly Powered by AbleSci AI