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MRI may play role in predicting language development among children with ASD

Functional magnetic resonance imaging may be able to predict future language development outcomes among toddlers with autism spectrum disorder even before they have been formally diagnosed.

“Autism is vastly heterogeneous, particularly in early language development. While [austism spectrum disorder] language trajectories in the first years of life are highly unstable, by early childhood these trajectories stabilize and are predictive of longer-term outcome. Early neural substrates that predict/precede such outcomes are largely unknown, but could have considerable translational and clinical impact,” study researcher Michael V. Lombardo, PhD, of the University of Cyprus, and colleagues wrote.

The study cohort included 60 children aged 12 to 48 months with ASD, 19 children with language or developmental delays but no ASD diagnosis and 24 children with typical development. Researchers combined functional magnetic resonance imaging (fMRI) measurements of neural systems response to speech at the earliest age when risk for ASD can be detected (approximately 1 to 2 years) with longitudinal diagnostic and clinical assessments of language skills at age 3 to 4 years.

Analysis indicated pre-diagnosis fMRI measurements of speech among children with ASD with relatively good language skills was comparable to that of children not diagnosed with ASD who had robust responses to language in superior temporal cortices.

Conversely, children with ASD and poor language outcomes had superior temporal cortices that indicated diminished or unusual inactivity to speech.

Further, fMRI imaging showed that the brains of children with ASD and poor language development processed speech differently and neural regions that manage emotion, memory and motor skills interacted differently.

“Our results suggest that information encoded in neural responses to speech at very young ages might provide important predictive information about a child’s likely later language capabilities. We found that early neural and behavioral information provide joint pieces of information that, when combined, provided a particularly strong classifier of poor versus improving language outcomes in ASD, and that such a multimodal classifier outperformed classifiers that used only clinical or fMRI information alone,” Lombardo and colleagues wrote. – by Amanda Oldt

Disclosure: The study was partly funded by grants from the National Institute of Mental Health. Please see the full study for a list of all other authors’ relevant financial disclosures.