The latest research:
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Autism diagnosis currently relies on clinical evaluation, but a new
study suggests it may be possible to detect the disorder with near
perfect accuracy using brain scans.
Researchers say they were able to identify “thought-markers” — or
differences in the way the brain responds to certain thoughts — specific
to those with autism. The method was successful in identifying whether
or not a person had autism with 97 percent accuracy, according to
findings published Tuesday in the journal PLOS ONE.
For the study, researchers used functional magnetic resonance imaging
to perform brain scans on 17 adults with high-functioning autism and 17
typically-developing controls. During the scans, the individuals were
asked to think about various social interactions like “persuade,”
“adore” and “hug.”
The researchers then used a machine-learning technique to assess
patterns in brain activity and decode how the thoughts were processed.
They found a clear distinction between those who were and were not on
the spectrum.
Among the typically-developing controls, thoughts of a hug, for
example, activated an area of the brain associated with a representation
of one’s self, but this was largely absent in individuals with autism.
“We found that we could tell whether a person has autism or not by
their brain activation patterns when they think about social concepts,”
said Marcel Just of Carnegie Mellon University who led the study. “We’ve
shown not just that the brains of people with autism may be different,
or that their activation is different, but that the way social thoughts
are formed is different. We have discovered a biological thought-marker
for autism.”
Researchers said their approach could lead to quicker and more
certain diagnosis and allow for therapies that are more targeted to
specific areas of the brain.
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