EEGs predicting Autism
New research that looked at brain wave patterns of babies and toddlers showed the answer is likely yes.
A research group in Boston crunched data on brain activity from a group of 188 infants, between 3 months and 3 years old, to see if the reports showed what lead investigator Dr. William J. Bosl described as a "pattern of numbers that distinguished children who would develop autism from those who did not."
The goal was to find a way to help diagnose autism spectrum disorders much earlier, by using simple and available tools to look at the electrical signals of the brain.
What is autism spectrum disorder?Autism spectrum disorder (ASD) is a developmental disorder that affects a child’s language, behavior, and social skills. Recent data from the Centers for Disease Control (CDC), estimates that 1 in 59 children have autism.
https://abcnews.com/Health/predicting-autism-brain-wave-patterns-study-shows/story?id=54852771
Elderly eeg
Two Different Populations within the Healthy Elderly: Lack of Conflict Detection in Those at Risk of Cognitive Decline
During healthy aging, inhibitory processing is affected at the sensorial, perceptual, and cognitive levels. The assessment of event-related potentials (ERPs) during the Stroop task has been used to study age-related decline in the efficiency of inhibitory processes. Studies using ERPs have found that the P300 amplitude increases and the N500 amplitude is attenuated in healthy elderly adults compared to those in young adults. On the other hand, it has been reported that theta excess in resting EEG with eyes closed is a good predictor of cognitive decline during aging 7 years later, while a normal EEG increases the probability of not developing cognitive decline. The behavioral and ERP responses during a Counting-Stroop task were compared between 22 healthy elderly subjects with normal EEG (Normal-EEG group) and 22 healthy elderly subjects with an excess of EEG theta activity (Theta-EEG group). Behaviorally, the Normal-EEG group showed a higher behavioral interference effect than the Theta-EEG group. ERP patterns were different between the groups, and two facts are highlighted: (a) the P300 amplitude was higher in the Theta-EEG group, with both groups showing a P300 effect in almost all electrodes, and (b) the Theta-EEG group did not show an N500 effect. These results suggest that the diminishment in inhibitory control observed in the Theta-EEG group may be compensated by different processes in earlier stages, which would allow them to perform the task with similar efficiency to that of participants with a normal EEG. This study is the first to show that healthy elderly subjects with an excess of theta EEG activity not only are at risk of developing cognitive decline but already have a cognitive impairment.
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