Altered efficiency of white matter connections for language function in children with language disorder

To characterize structural white matter substrates associated with language functions in children with language disorders (LD), a psychometry-driven diffusion tractography network was investigated with canonical correlation analysis (CCA), which can reliably predict expressive and receptive language scores from the nodal efficiency (NE) of the obtained network. The CCA found that the NE values of six regions: left inferior-frontal-opercular, left insular, left angular gyrus, left superior-temporal-gyrus, right hippocampus, and right cerebellar-lobule were highly correlated with language scores (ρ_expressive/ρ_receptive = 0.609/0.528), yielding significant differentiation of LD from controls using new imaging predictors u_expressive (F = 15.024, p = .0003) and u_receptive (F = 7.421, p = .009). This study demonstrates the utility of intrinsic language network analyses in distinguishing and potentially subtyping the type and severity of language deficit, especially in very young children (≤3 years) with LD. The use of structural imaging to identify children with persisting language disorder could prove useful in understanding the etiology of language disorder.