Brain Connectivity Unveils New Insights into Autism

Image showing brain scans with highlighted areas indicating neurological differences in individuals with autism.
Neuroimaging study reveals brain connectivity differences in autism spectrum disorder.

Because autism spectrum disease symptoms can vary greatly in intensity, no single cause has been identified. A study by researchers at the University of Virginia, however, points to a potentially fruitful new avenue for research that may increase our understanding of various neurological illnesses and disorders, particularly in the context of brain connectivity.

Using methods like functional magnetic resonance imaging, which maps the brain’s responses to input and activity, current approaches to autism research observe and understand the disorder through the study of its behavioral consequences. However, little work has been done to understand the causes of these responses.

Through the use of Diffusion MRI, a technique that measures molecular diffusion in biological tissue, researchers from UVA’s College and Graduate School of Arts & Sciences have been able to gain a better understanding of the physiological differences between the brain structures of individuals with autism and those without, particularly in terms of brain connectivity. Specifically, they have been able to look into how water moves throughout the brain and interacts with cellular membranes. The method has assisted the UVA group in creating mathematical representations of brain microstructures that have aided in identifying anatomical variations between the brains of individuals with autism and those without.

“It hasn’t been well understood what those differences might be,” said Benjamin Newman, a postdoctoral researcher with UVA’s Department of Psychology, a recent graduate of UVA School of Medicine’s neuroscience graduate program, and lead author of a paper published this month in PLOS: One. “This new approach looks at the neuronal differences contributing to the etiology of autism spectrum disorder.”

Using the most recent neuroimaging data and computational techniques, Newman and his co-authors built on the work of Alan Hodgkin and Andrew Huxley, who were awarded the 1963 Nobel Prize in Medicine for characterizing the electrochemical conductivity characteristics of neurons. This allowed them to understand how conductivity varies between individuals with and without autism. As a result, a novel method for determining neuronal axon conductivity and information-carrying ability has been developed. Additionally, the study provides proof that the participants’ scores on the Social Communication Questionnaire, a widely used clinical instrument for autism diagnosis, are directly correlated with those microstructural changes.

“What we’re seeing is that there’s a difference in the diameter of the microstructural components in the brains of autistic people that can cause them to conduct electricity slower. It’s the structure that constrains how the function of the brain works.” Benjamin Newman, a postdoctoral researcher with UVA’s Department of Psychology

John Darrell Van Horn, a psychology and data science professor at UVA and one of Newman’s co-authors, stated that we frequently attempt to comprehend autism through a set of behavioral patterns that may be odd or appear distinct.

“But understanding those behaviors can be a bit subjective, depending on who’s doing the observing,” Van Horn said. “We need greater fidelity in terms of the physiological metrics that we have so that we can better understand where those behaviors coming from. This is the first time this kind of metric has been applied in a clinical population, and it sheds some interesting light on the origins of ASD.”

Although functional magnetic resonance imaging has been used extensively to examine blood oxygen-related signal alterations in autistic people, Van Horn noted that this research “Goes a little bit deeper.” 

“It’s asking not if there’s a particular cognitive functional activation difference; it’s asking how the brain conducts information around itself through these dynamic networks,” Van Horn said. “And I think that we’ve been successful showing that there’s something uniquely different about autistic-spectrum-disorder-diagnosed individuals relative to otherwise typically developing control subjects.”

Newman and Van Horn, associated with the National Institutes of Health’s Autism Center of Excellence (ACE), which funds extensive multidisciplinary and multi-institutional research on autism spectrum disorder (ASD) to identify its causes and possible treatments, are also focused on studying brain connectivity. The other co-authors, Jason Druzgal and Kevin Pelphrey from the UVA School of Medicine, contribute to this collaborative effort.

The primary investigator of the study, Pelphrey, is a neuroscientist with expertise in brain development. The main goal of the ACE project is to set the standard for the development of a precision medicine approach to autism. 

“This study provides the foundation for a biological target to measure treatment response and allows us to identify avenues for future treatments to be developed,” he said.

According to Van Horn, there might be ramifications for the investigation, diagnosis, and management of several neurological conditions, such as Parkinson’s and Alzheimer’s.

“This is a new tool for measuring the properties of neurons which we are particularly excited about. We are still exploring what we might be able to detect with it,” Van Horn said.

For more information: Conduction velocity, G-ratio, and extracellular water as microstructural characteristics of autism spectrum disorder, PLOS ONE, https://doi.org/10.1371/journal.pone.0301964h

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