A new study published in the Journal of Biological Psychiatric looked at the association between early neural activity and Autism Spectrum Disorder (ASD).
“We wanted to characterize early brain differences that can be detected before the behavioral signs of autism emerge,” study author Dr. Abigail Dickinson told us. “It’s important to map these patterns of early changes, as they could ultimately help identify infants showing neural risk for autism who may benefit from early intervention."
One in fifty-four children have autism according to 2020 data from the Center for Disease Control and Prevention. Boys are four times more likely to be diagnosed at an average of one in 34 while one in 144 girls are identified with autism.
“We thought that connectivity differences would be present at three months, as very early brain development is altered in ASD,” Dr. Dickinson told us. “However, we didn’t have any specific theories regarding the distribution or pattern of these changes across the scalp. That’s why we used a data-driven approach that studied all possible connections and didn’t pre-select connections or regions of interest.”
At age two, a child may be diagnosed with autism though most are diagnosed after age four. Along with autism, 31 per cent of children were also diagnosed with an intellectual disability. Autism does not discriminate as it affects all socioeconomic and ethnic groups.
“We studied infants who have an older sibling with autism, as these babies have increased risk for developing autism themselves,” Dr. Dickinson told us. “This research design allows us to study very early brain development in autism prospectively and how these patterns differ from typically developing children. We used electroencephalography, a non-invasive measure of brain function, to measure connectivity patterns while 3-month old infants were at rest. When these infants were 18 months, they underwent several behavioral assessments, including tests for autism symptoms.”
Researchers then tested if a machine learning algorithm could predict 18-month autism symptoms based on connectivity patterns at three months of age.
“We found that particular patterns of connectivity allowed the machine learning algorithm to predict later autism symptoms successfully,” Dr. Dickinson told us. “These results suggested that reduced long-range connectivity, and increased connectivity over right temporal and parietal regions, were associated with elevated autism symptoms.”
Children in minority groups are diagnosed with autism less often and later than children not in minority groups. Studies show that early intervention is key to providing children with opportunities in adulthood to thrive.
“Reduced long-range connectivity has been reported a lot in the autism literature, so it wasn’t too surprising that we see early differences for these connections,” Dr. Dickinson told us. “The increased connectivity over right temporal parietal regions was also interesting, as these brain areas are involved in social processing.”
While it is not known yet what causes autism, studies have shown genetics to be a factor. Also, children with older parents are more likely to develop autism. Families with one child with autism are two to 18 per cent more likely to have additional children also diagnosed with autism. In the case of identical twins, if one of the twins has autism, there’s up to a 95 per cent change the other twin will also develop autism. In the case of non-identical twins, the likelihood percentage rate of both twins having autism falls to just over 30 per cent.
“Going forward, we want to see if these early differences in brain activity are specific to children with a family history of autism,” Dr. Dickinson told us, “or if we see similar patterns infants who have other types of risk for ASD, such as specific genetic conditions.”
Patricia Tomasi is a mom, maternal mental health advocate, journalist, and speaker. She writes regularly for the Huffington Post Canada, focusing primarily on maternal mental health after suffering from severe postpartum anxiety twice. You can find her Huffington Post biography here. Patricia is also a Patient Expert Advisor for the North American-based, Maternal Mental Health Research Collective and is the founder of the online peer support group - Facebook Postpartum Depression & Anxiety Support Group - with over 1500 members worldwide. Blog: www.patriciatomasiblog.wordpress.com