Jie Chen, Xiaoxia Feng, Jia Zhang, Chan Tang, Linyan Liu, Siyi Fan, Ningxin Zhao, Yang Lei, Xiujie Yang, Xiangzhi Meng, Guosheng Ding
This study offers a macroscopic view of language comprehension research in MCI. Future work should pay more attention to stage-related changes, cross-linguistic variations, clearer distinctions among comprehension processes, and more reliable measures for clinical monitoring and intervention evaluation. Future reviews may also extend this work to language production and broader communicative functioning in MCI.
Understanding how multiple linguistic components are represented within the human language network, and how these representations change across development, remains an important open question. This study examines whether the language network integrates linguistic components through regions dedicated to single components (single-component coding) or through regions representing combined components (combination-based coding), and how these representational patterns differ across development. We recruited 64 participants (34 children and 30 adults) to complete a hierarchical reading task involving pseudowords, words, sentences, and stories, enabling assessment of neural substrates for individual language components (semantics, syntax, situation model) and their combinations. Based on this task structure, we constructed seven cognitive models targeting individual components and their combinations. Model-based multivariate regression revealed overlapping engagement of left frontal and temporal regions across all models in both groups, indicating multifunctional regions supporting combination-based coding. Compared to children, adults showed more spatially focal model correspondence within core language regions. Moreover, clustering based on model-fitting performance identified three functional clusters with marked developmental differences, broadly corresponding to right frontotemporal regions (Cluster 1), left anterior frontotemporal regions (Cluster 2), and left posterior frontotemporal regions (Cluster 3). Further statistical analyses showed that adults exhibited stronger Combination Code representations in Cluster 2, whereas children relied more on Single Code representations in Cluster 3, suggesting a developmental shift toward integrated coding in anterior networks. Together, these findings reveal that the language network supports combination-based coding through functionally organized clusters, and that the representational roles of anterior and posterior regions undergo reorganization from childhood to adulthood.