Reuben Kraft, professor of mechanical engineering in the Penn State College of Engineering, is using computational tools — such as mouthguard sensors — to model and predict injury in the human brain. Here, a 3D visualization shows deformation in the brain caused by physical impact during a game of football. Credit: Kraft Lab.
Research team aims to better understand traumatic brain injuries
Oct 29, 2024
Editor's note: This article originally appeared on Penn State News.
By Mallorie McIlwain
UNIVERSITY PARK, Pa. — When the brain experiences an injury, it can be difficult to definitively diagnose a concussion as the trauma is often limited to inside the skull and cannot be accurately assessed, according Reuben Kraft, a professor of mechanical engineering at the Penn State College of Engineering.
Kraft, who is also a co-hire with the Penn State Institute for Computational and Data Sciences (ICDS), and his collaborators are using computational methods and tools — such as custom mouthguard sensors — to model and predict injury in the human brain.
Axonal fiber tracks, or bundles of neurons that transmit information between different regions of the brain, comprise a significant portion of the brain, explained Kraft.
These tracts form the brain’s white matter and are essential for communication across various neural networks.
“When a head acceleration, or rapid head motion, occurs due to impact, these axonal fiber tracts are stretched,” Kraft said. “We call this axonal fiber strain. When the strain exceeds a certain threshold, it might be an indicator of brain injury. Our simulations make a numerical prediction of the strain, which we then make a prediction of the risk of brain injury.”
The brain is a heavily networked system that allows for more than one communication pathway, which Kraft said is useful if one fiber track is ruptured — another can act as a detour. The brain may process information slower than usual, but it can still function.
“The understanding of the break in those pathways is the starting point,” Kraft said. “We don’t fully understand the brain yet. As an engineer, I think that structure plays a big role in better understanding the brain. If we can get a handle on what happens to those pathways, we can better understand the injury and possibly even predict the type and severity of injuries resulting from specific impacts.”
Kraft and his research team concluded a five-year, U.S. National Science Foundation-funded project in February building a computational platform that models the human brain after impact to predict injury.
“We have a very nice platform developed, and we are now trying to see if clinical collaborators can evaluate whether it is accurate or if it will be as useful as we hope,” Kraft said, explaining that other techniques — such as testing for biomarkers in blood or saliva and imaging — are used to gain insight into injuries. “In all of those other cases, there is no way to see what happens inside the skull during impact. Computational modeling is the only way you can do that right now.”
Called the “Brain Simulation Research Platform,” the computational model allows the research team to assess injury location, predict how the network was affected and how that might impact functional behavior. Kraft said the team plans to continue refining the platform and eventually test it clinically.
“I believe understanding concussion is the gateway to understanding neuroscience more broadly,” Kraft said. “The idea is that if someone were to get hit very hard, we would be able to predict that concussion and secondly, provide documentation to the clinicians saying exactly where the impact is in the brain — that this is the functional or structural region that was affected — and the doctor may be able to come up with a treatment plan based off of that.”
The work may also benefit athletes and military personnel who experience repetitive trauma to the head — a common occurrence in those fields, especially when initial injuries are considered minor, according to Kraft. 
Bundles of fiber called axonal tracts in the brain experience strain when injured. Credit: Kraft Lab.
In a research collaboration funded by The Chuck Noll Foundation, Kraft and his team tracked football players throughout their season at Western Carolina University.
The players were tracked via commercially available mouthguards equipped with sensors to collect impact data. The mouthguards, customized to the player, measure the force transmission to the head and capture rotational movements, and translational movements, such as forward/backward, up/down and side-to-side. These mouthguards allow for precise monitoring of head motion, even in cases where there is no direct head impact, such as during a body tackle that causes whiplash-like head motion.
The researchers process the data through their computational models, transforming it into meaningful information, such as how much the brain tissue strained due to the impact.
The researchers had one question: Is brain strain or stretch a predictor of cognitive change or decline?
All participating players took a baseline functional test to assess verbal and working memory and reaction time. Players who sustained a big impact — when the brain tissue was estimated to stretch 20% or more — repeated the test to measure changes in their cognitive function.
Although the research is ongoing, Kraft said they’re seeing significant changes in brain function after large impacts.
“We hope we can be predictive to some degree of accuracy, specificity and sensitivity,” Kraft said, noting that current assessment capabilities are more accurate with more severe injuries. “But in contact sports, impacts are smaller, and it’s a very difficult area to predict changes. We want to understand whether these models can predict strain accurately, and if strain predicts changes in cognition.”
Kraft’s team, which also includes graduate students, uses ICDS tools and facilities to work on their study.
“We couldn’t do this work without the right tools,” Kraft said. “The ICDS facilities creates a community of users — faculty, students and staff — who are gaining more information and knowledge and funneling that knowledge into the work. This process really helps us focus on the question of ‘why?’, which makes for more in-depth research and better answers.”
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