Frequency-Dependent Changes in Resting State Electroencephalogram Functional Networks after Traumatic Brain Injury in Piglets.

Traumatic brain injury (TBI) is a major health concern in children, as it can cause chronic cognitive and behavioral deficits. The lack of objective involuntary metrics for the diagnosis of TBI makes prognosis more challenging, especially in the pediatric context, in which children are often unable to articulate their symptoms. Resting state electroencephalograms (EEG), which are inexpensive and non-invasive, and do not require subjects to perform cognitive tasks, have not yet been used to create functional brain networks in relation to TBI in children or non-human animals; here we report the first such study. We recorded resting state EEG in awake piglets before and after TBI, from which we generated EEG functional networks from the alpha (8-12 Hz), beta (16.5-25 Hz), broad (1-35 Hz), delta (1-3.5 Hz), gamma (30-35 Hz), sigma (13-16 Hz), and theta (4-7.5 Hz) frequency bands. We hypothesize that mild TBI will induce persistent frequency-dependent changes in the 4-week-old piglet at acute and chronic time points. Hyperconnectivity was found in several frequency band networks after TBI. This study serves as proof of concept that the study of EEG functional networks in awake piglets may be useful for the development of diagnostic metrics for TBI in children.

Changes in event-related potential functional networks predict traumatic brain injury in piglets.

BACKGROUND: Traumatic brain injury is a leading cause of cognitive and behavioral deficits in children in the US each year. None of the current diagnostic tools, such as quantitative cognitive and balance tests, have been validated to identify mild traumatic brain injury in infants, adults and animals. In this preliminary study, we report a novel, quantitative tool that has the potential to quickly and reliably diagnose traumatic brain injury and which can track the state of the brain during recovery across multiple ages and species. METHODS: Using 32 scalp electrodes, we recorded involuntary auditory event-related potentials from 22 awake four-week-old piglets one day before and one, four, and seven days after two different injury types (diffuse and focal) or sham. From these recordings, we generated event-related potential functional networks and assessed whether the patterns of the observed changes in these networks could distinguish brain-injured piglets from non-injured. FINDINGS: Piglet brains exhibited significant changes after injury, as evaluated by five network metrics. The injury prediction algorithm developed from our analysis of the changes in the event-related potentials functional networks ultimately produced a tool with 82% predictive accuracy. INTERPRETATION: This novel approach is the first application of auditory event-related potential functional networks to the prediction of traumatic brain injury. The resulting tool is a robust, objective and predictive method that offers promise for detecting mild traumatic brain injury, in particular because collecting event-related potentials data is noninvasive and inexpensive.

Improved prediction of direction-dependent, acute axonal injury in piglets.

To guide development of safety equipment that reduces sports-related head injuries, we sought to enhance predictive relationships between head movement and acute axonal injury severity. The severity of traumatic brain injury (TBI) is influenced by the magnitude and direction of head kinematics. Previous studies have demonstrated correlation between rotational head kinematics and symptom severity in the adult. More recent studies have demonstrated brain injury age- and direction-dependence, relating head kinematics to white matter tract-oriented strains. We have recently developed and assessed novel rotational head kinematic parameters as predictors of white matter damage in the female immature piglet. We show that many previously published rotational kinematic injury predictor metrics poorly predict acute axonal pathology induced by rapid, non-impact head rotations and that inclusion of cerebral moments of inertia (MOI) in rotational head injury metrics refines prediction of diffuse axonal injury following rapid head rotations for two immature age groups. Rotational Work (RotWork) was the best significant predictor of traumatic axonal injury in both newborn and pre-adolescent piglets following head rotations in the axial, coronal, and sagittal planes. An improvement over current metrics, we find that RotWork, which incorporates head rotation rate, direction, and brain shape, significantly enhanced acute traumatic axonal injury prediction. For similar injury extent, the RotWork threshold is lower for the newborn piglet than the pre-adolescent.

Full-field bulge test for planar anisotropic tissues: part I--experimental methods applied to human skin tissue.

The nonlinear anisotropic properties of human skin tissue were investigated using bulge testing. Full-field displacement data were obtained during testing of human skin tissues procured from the lower back of post-mortem human subjects using 3-D digital image correlation. To measure anisotropy, the dominant fiber direction of the tissue was determined from the deformed geometry of the specimen. Local strains and stress resultants were calculated along both the dominant fiber direction and the perpendicular direction. Variation in anisotropy and stiffness was observed between specimens. The use of stress resultants rather than the membrane stress approximation accounted for bending effects, which are significant for a thick nonlinear tissue. Of the six specimens tested, it was observed that specimens from older donors exhibited a stiffer and more isotropic response than those from younger donors. It was seen that the mechanical response of the tissue was negligibly impacted by preconditioning or the ambient humidity. The methods presented in this work for skin tissue are sufficiently general to be applied to other planar tissues, such as pericardium, gastrointestinal tissue, and fetal membranes. The stress resultant-stretch relations will be used in a companion paper to obtain material parameters for a nonlinear anisotropic hyperelastic model.