Home > Science > Innovative Technologies Help Identify Patterns and Reveal Solutions in Autism

Innovative Technologies Help Identify Patterns and Reveal Solutions in Autism

A recent study reports that a quick brain scan could be used to screen for autism.  The study, from senior author Declan Murphy, Ph.D., of Kings’ College London, has garnered considerable attention from the media for its potential to change the way we identify autism spectrum disorders (ASD).  There is, however, another interesting aspect to this story. The investigators borrowed methods from a field of computer science and engineering called machine learning.  These tools are most effective in finding patterns in sets of data that are large and heterogeneous for use in classification.  Using a set of five measurements that are based on structural features of the human brain, the authors found that different patterns emerged for adults with autism when compared with typically-developing adults and also adults with ADHD.  Importantly, no single brain region or feature alone was able to discriminate between the groups.  When considered together, however, these features were selective approximately 90% of the time.

Machine learning techniques are also being used to classify symptoms in the hope of identifying meaningful subtypes of autism that can lead to tailored effective treatments.  Curtis Jensen, a computer science engineer in San Diego has applied these techniques to the ARI database of symptoms from over 40,000 parent surveys. to identify symptom clusters that suggest possible relationships between symptoms that may be useful for identifying subtypes of autism.  According to Jensen, the clusters “make sense”.  For example, those subjects that score high in the fear or anxiety clusters tend to have lower intellectual disability. Similarly, although challenges with language communication are a defining feature of ASD, the obsessive-compulsive cluster seems to experience the least language difficulty.

Machine learning methods are not alone among the computer science tools used to benefit autism. For many years, the Interactive Technology for Autism (ITA) initiative from Autism Speaks, brought together researchers with expertise in computer science and engineering to seek solutions to problems faced in autism.  Now, through a $10 million initiative from the National Science Foundation, researchers will combine computer vision, speech analysis and wireless physiological measurements to assist with early diagnosis and behavioral shaping.  Collaborators at Georgia Tech, Carnegie Mellon University, University of Illinois at Urbana-Champaign, the University of Southern California and the Massachusetts Institute of Technology (MIT), will be aiming these powerful tools at social engagement and other behaviors.  By analyzing video collected in clinic visits, at schools and also at home, the group hopes to develop tools for screening autism and evaluating the effects of therapy.

Several of the principal investigators involved in the recently awarded NSF grant are long standing members of the ITA steering committee. According to ITA co-chair and Associate Director of the NSF grant, “Organizations like Autism Speaks play a vital role in funding pilot investigations needed to demonstrate scientific feasibility of innovative approaches that lead to larger-scale, federally-sponsored research programs”. Stay tuned as we learn more from the new field of Computational Behavioral Science.

  1. Debbie Ostle
    August 30, 2010 at 11:41 am

    We have not yet had a diagnosis for our son, he’s 8 now, and due to see the peadiatrician again in October, it’s been a bit of a roller-coaster ride since he was 3. Though I do feel now that a diagnosis would benefit him,to help support his education! I think that this new scan sounds amazing, and would like some more information about having one done for our son. HOW CAN I FIND OUT MORE…?

  2. Katie Wright
    August 30, 2010 at 5:24 pm

    We need the most practical and affordable technology now.

    Other than PECS and Dynavox there has been little to no movement in this field.

    We do not need such expensive technology to categorize subtypes. Most Moms can do this in a heartbeat. We need interventions for the 50% of kids whom Early Intervention fails. Rather than re-invent the wheel and create more diagnostic tests we need to work closely w/ families and focus on all forms of treatment. Autism is not just a brain or social disorder,

    We already have so many batteries of tests we don’t use. All the focus cannot be on the diagnosis. That is the easy part! 95% of the work comes afterwards!

    The real problem here is service delivery. We need to do something about the endless waiting lists for a diagnosis. The tools are all there- pediatricians and others need to better educate themselves and learn more about ASD. There learn so little about ASD in medical school- all too often it is up to the parents to educate the doctors. Unless a child is very, very HF, it is not hard to diagnose and should not take long.

    Database after database needs to = actual help. Technology has served HF kids very well but not nonverbal children. Time to see results asap.

  3. Thorton
    September 5, 2010 at 6:07 pm

    I thought the whole point of better identifying subtypes was for better treatments. As a simple case, high functioning kids shouldn’t be treated the same as low functioning kids. Those with OCD behaviors shouldn’t be treated the same as the non-verbal kids. Diagnosis is very important for treatments. That’s the whole point of diagnosis. Not all Autistic kids are the same.

    As for any mom being able to categorize kids in a heartbeat. That’s not true. I’m sure they can categorize their own kid just fine, and a different mother will categorize that kid completely different. We can’t even get trained psychologists to agree on a diagnosis for our kid. Almost no one agrees on diagnosis’s for these kids. Which is a big hindrance for getting treatments.

    Sorry, you’re not going to see results until there is more understanding. That doesn’t mean stop drying treatments, it just means that Autism needs to be studied more in all its facets. I wouldn’t stop anyone from studying what ever aspect of Autism they feel is important.

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