Resting-State Electroencephalogram (EEG) as a Biomarker of Learning Disabilities in Children-A Systematic Review.

Learning disabilities (LD) compromise academic achievement in approximately 5-10% of school-aged children, yet the neurophysiological signatures that could facilitate earlier detection or stratification remain poorly defined. Resting-state electroencephalography (rs-EEG) offers millisecond resolution and is cost-effective, but its findings have never been synthesized systematically across pediatric LD cohorts. Following a PROSPERO-registered protocol (CRD420251087821) and adhering to PRISMA 2020 guidelines, we searched PubMed, Embase, Web of Science, Scopus, and PsycINFO through 31 March 2025 for peer-reviewed studies that recorded eyes-open or eyes-closed rs-EEG using ≥ 4 scalp electrodes in children (≤18 years) formally diagnosed with LD, and compared the results with typically developing peers or normative databases. Four reviewers independently screened titles and abstracts, extracted data, and assessed the risk of bias using ROBINS-I. Seventeen studies (704 children with LD; 620 controls) met the inclusion criteria. The overall risk of bias was moderate, primarily due to small clinic-based samples and inconsistent control for confounding variables. Three consistent electrophysiological patterns emerged: (i) a 20-60% increase in delta/theta power over mesial-frontal, fronto-central and left peri-Sylvian cortices, resulting in markedly elevated θ/α and θ/β ratios; (ii) blunting or anterior displacement of the posterior alpha rhythm, particularly in language-critical temporo-parietal regions; and (iii) developmentally immature connectivity, characterized by widespread slow-band hypercoherence alongside hypo-connected upper-alpha networks linking left-hemisphere language hubs to posterior sensory areas. These abnormalities were correlated with reading, writing, and IQ scores and, in two longitudinal cohorts, they partially normalized in parallel with academic improvement. Furthermore, a link between reduced posterior/overall alpha and neuroinflammation has been found. Rs-EEG reveals a robust yet heterogeneous electrophysiological profile of pediatric LD, supporting a hybrid model that combines maturational delay with persistent circuit-level atypicalities in some children. While current evidence suggests that rs-EEG features show promise as potential biomarkers for LD detection and subtyping, these findings remain preliminary. Definitive clinical translation will require multi-site, dense-array longitudinal studies employing harmonized pipelines, integration with MRI and genetics, and the inclusion of EEG metrics in intervention trials.