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Saturday 24 February 2018
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Ground breaking autism research finds brain scans can diagnose autism

autism brain scan

Professor Marcel Just and team looking at brain scans at the Center for Cognitive Brain Imaging at Carnegie Mellon University

A new study by the Center for Cognitive Brain Imaging at Carnegie Mellon University has found that autism has a particular brain pattern different than that of non-autistic or neurotypical people.

Currently the diagnosis of autism relies on observation, interviews and behavioural analysis however this new approach using brain scans has an accuracy rate of 97% and also demonstrates not only that the brain scans of autistic people are different but in what way they are different.

To date, the Center for Cognitive Brain Imaging at Carnegie Mellon University has produced ground breaking research into how the brain works. Watch the clip below, from CBS Pittsburg, to see how they have developed a way of decoding the brain so that they can actually know what a person is thinking about by looking at the battery of brain activity the person displays while in a specially developed MRI scanner.

According to Marcel Just, PhD, professor of psychology and director of the Center for Cognitive Brain Imaging at Carnegie Mellon University, thinking is amazingly similar across people. He says:
“When you think about a house or a chair or a banana while you’re in the scanner, I can tell which one you’re thinking about.”

Applying their research to autism, and reported in PLoS One, the team at Carnigie Mellon have found that when given emotive words such as hug, humiliate, kick and adore the autistic people reacted very differently and had a very different perception of self to the non-autistic people studied.
According to the findings:
Many studies have characterized the behavior or the brain activation in autism as being altered, but often without specifying the nature of the alteration in terms that speak to its commonality across people with autism. The current results provide a possible core property, the neural representation of social interactions, that is altered similarly across participants with autism, namely in that the representation of self is largely absent.

The study measured 17 young adults with high functioning autism and 17 people without autism and  fMRI scans were performed on all the participants while they thought about the set of emotive words.

Looking at the fMRI activation patterns the difference between the two groups was so evident that the researchers could identify whether a brain was autistic or neurotypical in 33 out of 34 of the participants, giving an accuracy rate of 97%.

Professor Just, comments:

“There was an area associated with the representation of self that did not activate in people with autism. When they thought about hugging or adoring or persuading or hating, they thought about it like somebody watching a play or reading a dictionary definition. They didn’t think of it as it applied to them. This suggests that in autism, the representation of the self is altered, which researchers have known for many years, but this is the first time that anybody’s used that to diagnose autism looking at brain activation.”

The team believe that this research suggests there could be a new approach to how certain illnesses and disorders are diagnosed and understood.

According to their research paper:

One potential application of the current approach is to provide a biological measure of altered social processing in autism that can augment conventional structured-interview measures, as well as neuroanatomical and brain activity biomarkers of autism.

A second potential application is to provide a precise enough characterization of altered social representations in autism to allow the design of targeted therapies and neuropsychiatric diagnostic procedures.

Furthermore, both applications of this approach may be feasible with other psychiatric disorders which entail a systematic alteration of particular concepts, such as delusions. But the most far-reaching scientific significance is that psychiatric alterations of thought can begin to be biologically understood in light of their direct psychological consequences using brain imaging techniques in combination with machine learning analyses.

This is ground breaking research and may at last provide a way forwards to help understand autism and to find ways to enable autistic people to manage the stressors that frequently impact on their wellbeing.

Sources:  Just et al, (Dec 2 2014) Identifying Autism from Neural Representations of Social Interactions:  Neurocognitive Markers of Autism  http://www.plosone.org/article/info:doi/10.1371/journal.pone.0113879#abstract

 

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