Researchers Discover New Metric For Diagnosing Autism

A recent study conducted by researchers at the University of Virginia offers a promising new approach to understanding autism spectrum disorder (ASD) and potentially other neurological conditions.

While the exact cause of ASD remains elusive due to its wide range of symptoms and severity, the study sheds light on the physiological differences in the brain structures of individuals with and without autism.

Using Diffusion MRI, a technique that measures water movement in the brain and its interaction with cellular membranes, the researchers were able to develop mathematical models of brain microstructures. These models revealed structural disparities between autistic and non-autistic brains, providing insights into the underlying neuronal differences contributing to ASD.

Lead author Benjamin Newman explained that the study focuses on understanding the conductivity of neural axons and their ability to transmit information through the brain. By applying concepts from Nobel laureates Alan Hodgkin and Andrew Huxley's work on neuron conductivity, the researchers identified slower electrical conductivity in the brains of autistic individuals, attributed to differences in microstructural components.

The study, published in PLOS One, also demonstrated a correlation between these microstructural differences and scores on the Social Communication Questionnaire, a common diagnostic tool for autism. Professor John Darrell Van Horn emphasized the importance of physiological metrics in understanding autism beyond behavioral observations, noting that the study provides a deeper understanding of how the brain processes information in ASD.

The researchers, affiliated with the National Institute of Health's Autism Center of Excellence, aim to develop a precision medicine approach to autism treatment. Principal investigator Kevin Pelphrey highlighted the study's potential to identify biological targets for treatment response and future therapies.

Moreover, the study's findings may have implications for the examination, diagnosis, and treatment of other neurological disorders such as Parkinson's and Alzheimer's. Van Horn emphasized the significance of the new tool for measuring neuron properties and its potential for detecting various neurological conditions.

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