Zhao Xue, Wu Meiyun, Liu Haotian, Wang Yuyang, Zhang Zhikai, Liu Yuhe, Zhang Yu-Xuan
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
Department of Otolaryngology Head and Neck Surgery, West China Hospital of Sichuan University, Chengdu, 610041, China.
Adv Sci (Weinh). 2025 May;12(20):e2309194. doi: 10.1002/advs.202309194. Epub 2025 Mar 31.
How the lateralized language network and its functions emerge with early auditory experiences remains largely unknown. Here, early auditory development is examined using repeated optical imaging for cochlear implanted (CI) toddlers with congenital deafness from onset of restored hearing to around one year of CI hearing experiences. Machine learning models are constructed to resolve how functional organization of the bilateral language network and its sound processing support the CI children's post-implantation development of auditory and verbal communication skills. Behavioral improvement is predictable by cortical processing as well as by network organization changes, with the highest classification accuracy of 81.57%. For cortical processing, behavioral prediction is better for the left than the right hemisphere and for speech than non-speech processing. For network organization, the best prediction is obtained for resting state, with greater contribution from inter-hemisphere connections between non-homologous regions than from within-hemisphere connections. Most interestingly, systematic connectivity-to-activity models reveal that speech processing of the left language network is developmentally supported largely by global network organization, particularly asymmetric inter-hemisphere communication, rather than functional segregation of local network. These findings collectively confirm the importance of asymmetric inter-hemisphere communication in formation of the lateralized language network and its functional development with early auditory experiences.
侧化语言网络及其功能如何随着早期听觉经验而出现，在很大程度上仍然未知。在这里，我们使用重复光学成像技术，对先天性耳聋的人工耳蜗（CI）植入幼儿从恢复听力开始到大约一年的CI听力经验进行早期听觉发育研究。构建机器学习模型以解析双侧语言网络的功能组织及其声音处理如何支持CI儿童植入后听觉和言语交流技能的发展。行为改善可通过皮层处理以及网络组织变化来预测，最高分类准确率为81.57%。对于皮层处理，行为预测在左半球比右半球更好，在语音处理方面比非语音处理更好。对于网络组织，静息状态下的预测效果最佳，非同源区域之间的半球间连接比半球内连接的贡献更大。最有趣的是，系统的连接性到活性模型表明，左语言网络的语音处理在发育上很大程度上受到全局网络组织的支持，特别是不对称的半球间通信，而不是局部网络的功能分离。这些发现共同证实了不对称半球间通信在侧化语言网络形成及其早期听觉经验功能发展中的重要性。
