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.