Studying EEG patterns as a potential diagnostic test for Autism
A study from Boston Children's Hospital published in BMC Medicine this week suggest a EEG coherence-based phenotype for childhood autism.
EEG coherence is a measure of the degree of association or coupling of frequency spectra between two EEG signals when compared over time.
The EEG coherence was studied by quantifying the degree to which any two EEG signals from multiple electrodes at different time points were synchronised.High coherence values for eg where two or more waves rise and fall together over time, are taken as a measure of strong connectivity between the brain regions that produce the compared EEG signals.
The investigators compared raw EEG data from 430 children with autism and 554 control subjects, ages 2 to 12, and found that those with autism had consistent EEG patterns indicating altered connectivity between brain regions.
Using computational techniques, the researchers generated coherence readings for more than 4,000 unique combinations of electrode signals, and looked for the ones that seemed to vary the most from child to child. From these, they identified 33 coherence "factors" that consistently distinguished the children with autism from the controls, across all age groups (2 to 4, 4 to 6, and 6 to 12 years).
The autistic children generally showing reduced connectivity compared to controls. The left hemisphere language areas in particular showed reduced connectivity in autistic children, consistent with neuroimaging findings suggesting altered connectivity in the arcuate fasciculus
There are several interesting aspects to the study methodology in that the researchers had included a mid-range cross section of childhood autism and pervasive developmental disorder while excluding the high functioning autism or Asperger's syndrome where the children are typically cooperative. The group at Boston children's also had at their disposal a large database of EEG data on typical neurologically normal children.
In addition they had also studied all the available scalp channels and spectral bands and using a technique called Principal Components Analysis the extensive spectral coherence data sets were reduced to a much small number of factors and these variables were studied among the cases and controls.
There are plans to repeat this study in children with Asperger's syndrome and also in autism associated with tuberous sclerosis, fragile x syndrome and extreme prematurity and see if its EEG patterns are similar to or different from that of classic autism.
The findings from this study are interesting since it explores potential diagnostic tests for autism particularly at younger ages when behavior-based measures are unreliable.
The full text of this study is available via open access at http://www.biomedcentral.com/1741-7015/10/64
Source: Children's Hospital Boston