Monday, July 29th, 2013
The diagnosis and treatment of autism spectrum disorders (ASD) could be improved by a new technique that takes advantage of the disrupted motor skills that autistic children commonly have. Time.com reports on the new technique, which was developed by researchers at Rutgers University and Indiana University:
Elizabeth Torres, a computational neuroscientist at Rutgers University, explores how movements reflect the way people interact with and sense their environments. Patterns in these movements can reflect brain processes and connections, and that could be helpful in understanding autism.
“The way that we study the brain is quite disembodied. We pay attention to the central nervous system—brain and spinal chord–and we don’t pay attention to the peripheral nervous system,” says Torres, referring to the network of nerves involved in relaying sensory information such as touch, sight and smell. “This plays a pretty important function in self-regulation and autonomy, and it is not often considered in autism and in much of brain research.”
Movement can influences our perception of the world around us, and our ability to sense the environment can also change our movements. “Movement is a form of sensory input that travels back to the brain as a form of feedback, continuously,” she says.
The central nervous system constantly receives and processes this feedback in order to produce the appropriate actions. During normal development, this system learns to anticipate sensory consequences, like how a baby learns to suction its mouth for feeding. But this process may not mature in the same way in autistic children, the researchers discovered.
In two papers published in the journal Frontiers in Neuroscience, Torres, working with a computer scientist and physicist, described a way to both diagnose autism via movement patterns, and potentially treat the condition using similar action-based strategies. They developed a method that focuses on the spontaneous movements that autistic children, even infants, make unintentionally. The research team measured tiny fluctuations of movement among autistic patients, and compared these movements to those of normally developing subjects.
This strategy was able to diagnose autism among children aged three to 25, but even more exciting was the fact that the movement profiles were unique enough to distinguish how severely affected children were by the developmental disorder. All the autistic participants — regardless of their age — were essentially stunted in their ability to process movement by age three. By age four, these patterns in normally developed youngsters should be predictive and reliable. By college age, they are highly predictive, and adults can anticipate how their actions impact their environment and vice versa. But kids with autism are not successfully forming these connections.
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