There used to be no predicting whether babies less than two years old will develop autism or other developmental disorders later on. But an advanced MRI technique being studied by researchers from the University of North Carolina at Chapel Hill is showing promise in decoding how different regions of the brain interact in babies at high risk for autism.
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| Image source: Harvard.edu |
Functional connectivity MRI, or fcMRI, reveals a correlation between connections among certain areas of the brain and the likelihood of autism.The researchers focused on infants with siblings diagnosed with autism, as this set is assumed to be high-risk. The fcMRI, scanning 230 different regions of the brain associated with specific abilities such as language and social behavior, was conducted on them in their sleep when they were six months old. The scans were studied alongside other clinical information in the formation of predictions.
The study, published in the June 2017 issue of Science Translational Medicine, supports the idea that the brain undergoes changes before behavioral symptoms of autism manifest at two years. It then grouped neuroimaging results among a population of 59 six-month-old infants into autism and non-autism predictions. It also identified almost a thousand brain connections that are predictive of autism.
The confirmation of the study’s predictions was compelling. Eighty-two percent (9 out of 11) of infants predicted to develop the disorder went on to have autism. The study also correctly predicted all the infants who will not develop the disorder.
The predictive promise of neuroimaging in the early identification of neurodevelopmental disorders is seen to support recommendations for early intervention, which mitigates the behavioral symptoms of autism.
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| Image source: Psychneuro.wordpress.com |
Dr. Curtis Cripe is a neuroengineer with a diverse multidisciplinary background that includes software development, bioengineering, addiction recovery, psychophysiology, psychology, brain injury, and child neurodevelopment. To learn about the basics of neuroimaging and other neuroengineering techniques, visit this webpage.
