TY - JOUR
T1 - Atypical Resting-State and Task-Evoked EEG Signatures in Children with Developmental Language Disorder
AU - Liang, Aimin
AU - Cui, Zhijun
AU - Shi, Yang
AU - Qu, Chunyan
AU - Wei, Zhuang
AU - Wang, Hanxiao
AU - Zhang, Xu
AU - Ning, Xiaolin
AU - Ni, Xin
AU - Fang, Jiancheng
N1 - Publisher Copyright:
© 2026 by the authors.
PY - 2026/1
Y1 - 2026/1
N2 - Developmental Language Disorder (DLD) is associated with abnormalities in both intrinsic resting-state brain networks and task-evoked neural responses, yet direct electrophysiological evidence linking these levels remains limited. This study examined multi-level EEG markers in 21 typically developing children and 15 children with DLD across resting-state, a semantic matching task, and an auditory oddball task. Resting-state analyses revealed frequency-specific connectivity imbalances, reduced stability of intrinsic microstate dynamics, and atypical transitions between microstates in the DLD group. During the semantic matching task, DLD children showed weaker occipital P1 and N2 responses (100–300 ms) and lacked the right fronto-central difference wave (500–700 ms) observed in TD children. In the auditory oddball task, DLD children exhibited high-theta/low-alpha event-related desynchronization at left frontal electrodes (400–500 ms), in contrast to TD children. A machine learning framework integrating resting-state and task-based features discriminated DLD from TD children (test-set F1 = 70.3–80.0%) but showed limited generalizability, highlighting the constraints of small clinical samples. These findings support a translational neurophysiological signature for DLD, in which atypical intrinsic network organization constrains emergent neural computations, providing a foundation for future biomarker development and targeted intervention strategies.
AB - Developmental Language Disorder (DLD) is associated with abnormalities in both intrinsic resting-state brain networks and task-evoked neural responses, yet direct electrophysiological evidence linking these levels remains limited. This study examined multi-level EEG markers in 21 typically developing children and 15 children with DLD across resting-state, a semantic matching task, and an auditory oddball task. Resting-state analyses revealed frequency-specific connectivity imbalances, reduced stability of intrinsic microstate dynamics, and atypical transitions between microstates in the DLD group. During the semantic matching task, DLD children showed weaker occipital P1 and N2 responses (100–300 ms) and lacked the right fronto-central difference wave (500–700 ms) observed in TD children. In the auditory oddball task, DLD children exhibited high-theta/low-alpha event-related desynchronization at left frontal electrodes (400–500 ms), in contrast to TD children. A machine learning framework integrating resting-state and task-based features discriminated DLD from TD children (test-set F1 = 70.3–80.0%) but showed limited generalizability, highlighting the constraints of small clinical samples. These findings support a translational neurophysiological signature for DLD, in which atypical intrinsic network organization constrains emergent neural computations, providing a foundation for future biomarker development and targeted intervention strategies.
KW - developmental language disorder (DLD)
KW - electroencephalography (EEG)
KW - event-related potentials (ERPs)
KW - neural biomarkers
KW - resting-state networks
UR - https://www.scopus.com/pages/publications/105032487351
U2 - 10.3390/bioengineering13010119
DO - 10.3390/bioengineering13010119
M3 - 文章
AN - SCOPUS:105032487351
SN - 2306-5354
VL - 13
JO - Bioengineering
JF - Bioengineering
IS - 1
M1 - 119
ER -