summary: Researchers have developed an innovative approach using diffusion MRI to investigate brain structure in individuals with autism spectrum disorder (ASD). This technology measures how water molecules move through the brain and reveals structural differences in neural pathways between autistic and non-autistic people.
By applying mathematical models, the research team linked these structural changes to functional implications, specifically how neurons conduct electricity and process information. Their findings correlating microstructural differences with autism diagnostic scores may deepen our understanding of ASD and lead to more precise treatments.
Important facts:
- The UVA study used diffusion MRI to identify microstructural differences between autistic and non-autistic brains, showing that electrical conductivity is slower in autistic brains due to changes in axonal diameter. It was revealed.
- These structural differences are directly linked to social communication questionnaire scores, increasing the likelihood of accurate diagnosis and treatment approaches.
- This research is part of the NIH’s Autism Center of Excellence Initiative, which aims to pioneer precision medicine approaches to understanding and treating autism.
sauce: University of Virginia
Autism spectrum disorders have not yet been linked to a single cause due to their wide range of symptoms and severity.
But a study by researchers at the University of Virginia suggests a promising new approach to finding answers that could lead to advances in research into other neurological diseases and disorders.
Current approaches to autism research include using techniques such as functional magnetic resonance imaging, which maps the brain’s response to input and activity, to observe and understand the disorder through the study of its behavioral effects. , but little research has been done to understand the causes of these reactions.
But by using diffusion MRI, a technique that measures the diffusion of molecules within living tissue, researchers in UVA’s College of Arts and Sciences and Graduate School have been able to determine the physiology of brain structures in autistic and non-autistic people. I was able to understand the differences better. Observe how water moves through the brain and interacts with cell membranes.
This approach helped the UVA team develop a mathematical model of brain microstructure that helps identify structural differences between the brains of people with autism and those without.
“We still don’t really understand what those differences are,” says Benjamin Newman, a postdoctoral fellow in the UVA Department of Psychology and recent graduate of the UVA School of Medicine’s neuroscience graduate program. Upvoted: 1.
“This new approach focuses on neuronal differences that contribute to the pathogenesis of autism spectrum disorders.”
Building on the work of Alan Hodgkin and Andrew Huxley, who won the Nobel Prize in Medicine in 1963 for their description of the electrochemical conduction properties of neurons, Newman and his coauthors applied those concepts to I understood how the conductivity differs between people with and without the disease. , using the latest neuroimaging data and computational techniques.
The result is a first-of-its-kind approach to calculating the conductivity of nerve axons and their ability to transmit information through the brain. This study also provides evidence that these microstructural differences are directly related to participants’ scores on the Social Communication Questionnaire, a common clinical tool for diagnosing autism. There is.
“What we’re seeing is that there are differences in the diameter of microstructural components in the brains of people with autism, which may slow the conduction of electricity,” Newman said. To tell. “It’s the structure of the brain that limits how it functions.”
John Darrell Van Horn, one of Newman’s co-authors and a professor of psychology and data science at UVA, says that we develop autism through a collection of behavioral patterns that appear abnormal or different. He said that he often tries to understand the disease.
“But understanding these behaviors can be a little subjective, depending on who is observing them,” Van Horn says.
“We need to increase the fidelity of physiological indicators so that we can better understand where these behaviors are coming from. This is the first time this type of indicator has been applied to a clinical population, and it is It sheds some interesting light on its origins.”
Van Horn said many studies have been done using functional magnetic resonance imaging to examine changes in blood oxygen-related signals in people with autism, but this study “goes a little deeper.” said.
“We’re not asking whether there are differences in the activation of specific cognitive functions; we’re asking how the brain actually communicates information through these dynamic networks,” says Van.・Mr. Horn said.
“And I think we’ve succeeded in showing that there is something uniquely different about people diagnosed with autism spectrum disorder compared to otherwise typically developing control subjects. .”
Newman and Van Horn are affiliated with the National Institutes of Health’s Autism Center of Excellence (ACE), along with co-authors Jason Druzgar and Kevin Pelfrey of the UVA School of Medicine. ACE is a large-scale, interdisciplinary, multi-institutional initiative to support autism treatment. His research on ASD aimed to determine its causes and potential treatments.
Pelfrey, a neuroscientist, brain development expert, and principal investigator on the study, said the overarching goal of the ACE project is to spearhead the development of precision medicine approaches to autism. .
“This study provides a basis for biological targets to measure therapeutic response and allows us to identify avenues for future therapeutic development,” he said.
Van Horn added that this research could also have implications for testing, diagnosis and treatment of other neurological diseases, such as Parkinson’s disease and Alzheimer’s disease.
“This is a new tool for measuring the properties of neurons that we are particularly excited about. We are still exploring what we can detect with it,” Van Horn said. .
About this autism research news
author: Russ Bahorsky
sauce: University of Virginia
contact: Russ Bahorsky – University of Virginia
image: Image credited to Neuroscience News
Original research: Open access.
“Conduction velocity, G ratio, and extracellular water as ultrastructural features of autism spectrum disordersWritten by Benjamin Newman et al. pro swan
abstract
Conduction velocity, G ratio, and extracellular water as ultrastructural features of autism spectrum disorders
The neuronal differences that contribute to the pathogenesis of autism spectrum disorders (ASD) are still poorly defined. Previous studies suggest that myelin and axons are destroyed during ASD development.
By combining structural and diffusion MRI techniques, we use a new approach to calculate axonal conduction velocity, called cohesive conduction velocity, which is related to extracellular water, cohesive g-ratio, and axonal information-carrying capacity, to investigate myelin and axons can be evaluated.
This study combines several innovative cellular ultrastructural methods measured with magnetic resonance imaging (MRI) to characterize differences between ASD and neurotypical adolescent participants in a large cohort.
First, we examine the relationship between each metric, including ultrastructural measurements of axonal and intracellular diffusion and the T1w/T2w ratio.
We then demonstrate the sensitivity of these metrics by characterizing differences between ASD and neurotypical participants, demonstrating widespread increases in cortical extracellular water and total g across the cortical, subcortical, and white matter skeleton. We found a decrease in the ratio and total conduction velocity.
We ultimately provide evidence that these microstructural differences are associated with higher scores on the Social Communication Questionnaire (SCQ), a commonly used diagnostic tool to assess ASD. Masu.
This study is the first to show that ASD is associated with symptoms that can be measured with MRI. in vivo Differences in myelin and axonal development influence neurological and behavioral functions.
We also present a new formulation for calculating aggregate conduction velocities that is highly sensitive to these changes. We conclude that ASD may be characterized by intact structural connectivity, whereas functional connectivity may be attenuated by network properties that influence neural conduction velocity. Masu.
This effect could explain the putative dependence on local connectivity, as opposed to more distal connectivity, observed in ASD.
