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Brain trace can identify autism

26th June 2012

Researchers in Boston have developed a brain imaging analysis technique that could be used to detect autism in children as young as two.

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The team at the Boston Children's Hospital has carried out the largest, most rigorous study so far into the use of electroencephalography (EEG) as a tool for the diagnosis of autism.

To do so, they needed to find a way of eliminating "noise" from the readings that caused body movements; one of the reasons using EEG to diagnose toddlers has been ruled out in the past.

The developed a computer algorithm to isolate the brain reading from the "noise", producing a usable image.

Now, researchers Frank Duffy of the Department of Neurology and Heidelise Als of the Department of Psychiatry at Boston Children's Hospital say that EEG testing can be used to distinguish children with autism from neurotypical children as early as age 2.

When they looked at raw EEG data from 430 children with autism and 554 control subjects, all aged between 2 and 12, Duffy and Als found that those with autism had consistent EEG patterns indicating different connectivity between the regions of the brain compared with the neurotypical control group.

In the children with autism, there was altered connectivity throughout the brain compared with the control group, but especially in the left-hemisphere language areas.

Writing in the online open-access journal BMC Medicine, the researchers said they had achieved their result by focusing on children with "classic" autism, and excluding high-functioning autism and Asperger's syndrome cases.

The children in this group had been referred for EEGs by neurologists, psychiatrists or developmental paediatricians to rule out seizure disorders, and any children diagnosed with seizures were also ruled out of the autistic study group.

They said that high-functioning individuals with an autistic spectrum disorder (ASD), and those with a diagnosis of Asperger's, dominate the existing literature on ASDs because they are easier to study.

Children with genetic syndromes linked to autism (such as Fragile X or Rett syndrome), children being treated for other major illnesses, those with sensory disorders like blindness and deafness and those taking medications were all also excluded from the autistic group for the purposes of the study.

According to Duffy, the group they ended up with were typical of autistic children who might be referred to a behaviour specialist, and were the hardest group to study.

He said that no previous extensive studies had looked at large samples of these children with EEGs, partly because of the technical difficulty of getting reliable recordings from them.

The children were allowed to take breaks during scanning, using techniques developed at Boston Children's Hospital to get clean waking EEG recordings from children with autism.

Then, their readings were processed using computer algorithms to adjust for the children's body and eye movements and muscle activity, all of which can obscure EEG readings.

Connectivity in the brain was measured using coherence patterns, in which two or more waves rise or fall together over time.

Brain regions that are connected to each other are more likely to synchonise in this way.

Duffy and Als then looked for the readings, taken from more than 4,000 unique combinations of electrode signals, that seemed to vary the most from child to child.

They found 33 patterns indicative of coherence across all age groups in the children with autism, which were not found in the control group.

They then repeated their analysis 10 times, using patterns found in half the autistic group to analyse the readings of the other half, and vice versa.

Duffy and Als repeated their analysis 10 times, splitting their study population in half different ways and using half to identify the factors, and the other half to test and validate them. Each time, the classification scheme was validated.

Duffy said they had narrowed down their analysis to a single rule that was found across all the children, and which was repeatable again and again among the study subjects.

The narrowing down process was done through computers, eliminating the need for human judgement in the selection of coherence patterns, he said.

Behaviour-based diagnosis of autism is unreliable in very young children, and Duffy said he hoped that the team's findings could form the basis for a future objective diagnostic test of autism, particularly at a young age.

His team now plans to repeat their study in children with Asperger's syndrome and see if its EEG patterns are similar to or different from autism.

Children whose autism is associated with conditions such as tuberous sclerosis, fragile X syndrome and extremely premature birth will also, eventually, be evaluated in the same way.


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Article Information

Title: Brain trace can identify autism
Author: Luisetta Mudie
Article Id: 22210
Date Added: 26th Jun 2012

Sources

BBC News
Science Daily

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