This WebMD story tipped me off to a new study published in BMC Medicine: “EEG complexity as a biomarker for autism spectrum disorder risk.” If the results hold up in further experimentation, it’ll mean a great deal to parents of children with ASD.
While intervention techniques can do a lot of remedy the effects of ASD, the most important element in successful intervention is getting to work on it early as possible, while the brain is still organizing itself. With diagnoses that rely purely on behavioral indicators, the correct diagnosis can come fairly far along in early childhood, at 2 or 3 years of age.
Mean differences between control and risk-of-ASD groups
In contrast, this study collected data from infants at 6 to 24 months of age. 46 were at high risk for ASD because they had older siblings with ASD, and 33 were controls. Analysis of EEG data revealed a significant difference in brain activity patterns at just 9 months of age. Researchers were able to sort the high-risk group from the controls with up to 80 percent accuracy.
And, EEG offers a reasonably noninvasive way to test babies. “Infants were seated on their mothers’ laps in a dimly lit room while a research assistant engaged the infants’ attention by blowing bubbles,” report the study authors. The infants wore the 64-channel Sensor Net System (made by EGI, Inc., down in Eugene), making them look like they were enduring a barnacle infestation.
Since the mid-2000s, researchers have been exploring the uses of modified multiscale entropy on physiological signals to determine things like cardiac health. If it sounds complicated, it is, and my having researched the topic for an hour on Google has not left me with confidence that I can explain it for you. Suffice to say that the analysis involves using “computers” to run “algorithms” that look for fairly minute differences in the signals being recorded, looking to measure what’s known as signal complexity. This is all fairly meta, but the upshot (learned from studying patients admitted with heart problems) is that a lack of randomness in the data indicates deterioration of a physiological system.
Now, explains researcher William Bosl, PhD, of Children’s Hospital Boston, they’re using the same technique to look at electrical activity in the brain, via EEG. Surprisingly, the study also uncovered a sex-based difference: “Classification accuracy for boys was close to 100 percent at age 9 months and remains high (70 to 90 percent) at ages 12 and 18 months. For girls, classification accuracy was highest at age 6 months, but declines thereafter.” That earlier classification accuracy may turn out to be very good news for girls with ASD, as they can compensate and remain undiagnosed for longer than boys.