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DOE OSTI2020

Assessment of Demographic, Genetic, and Imaging Variables Associated With Brain Resilience and Cognitive Resilience to Pathological Tau in Patients With Alzheimer Disease

Importance: Better understanding is needed of the degree to which individuals tolerate Alzheimer disease (AD)-like pathological tau with respect to brain structure (brain resilience) and cognition (cognitive resilience). Objective: To examine the demographic (age, sex, and educational level), genetic (APOE-ε4 status), and neuroimaging (white matter hyperintensities and cortical thickness) factors associated with interindividual differences in brain and cognitive resilience to tau positron emission tomography (PET) load and to changes in global cognition over time. Design, setting, an participants: In this cross-sectional, longitudinal study, tau PET was performed from June 1, 2014, to November 30, 2017, and global cognition monitored for a mean [SD] interval of 2.0 [1.8] years at 3 dementia centers in South Korea, Sweden, and the United States. The study included amyloid-β-positive participants with mild cognitive impairment or AD dementia. Data analysis was performed from October 26, 2018, to December 11, 2019. Exposures: Standard dementia screening, cognitive testing, brain magnetic resonance imaging, amyloid-β PET and cerebrospinal fluid analysis, and flortaucipir (tau) labeled with fluor-18 (18F) PET. Main outcomes and measures: Separate linear regression models were performed between whole cortex [18F]flortaucipir uptake and cortical thickness, and standardized residuals were used to obtain a measure of brain resilience. The same procedure was performed for whole cortex [18F]flortaucipir uptake vs Mini-Mental State Examination (MMSE) as a measure of cognitive resilience. Bivariate and multivariable linear regression models were conducted with age, sex, educational level, APOE-ε4 status, white matter hyperintensity volumes, and cortical thickness as independent variables and brain and cognitive resilience measures as dependent variables. Linear mixed models were performed to examine whether changes in MMSE scores over time differed as a function of a combined brain and cognitive resilience variable. Results: A total of 260 participants (145 [55.8%] female; mean [SD] age, 69.2 [9.5] years; mean [SD] MMSE score, 21.9 [5.5]) were included in the study. In multivariable models, women (standardized β = -0.15, P = .02) and young patients (standardized β = -0.20, P = .006) had greater brain resilience to pathological tau. Higher educational level (standardized β = 0.23, P < .001) and global cortical thickness (standardized β = 0.23, P < .001) were associated with greater cognitive resilience to pathological tau. Linear mixed models indicated a significant interaction of brain resilience × cognitive resilience × time on MMSE (β [SE] = -0.235 [0.111], P = .03), with steepest slopes for individuals with both low brain and cognitive resilience. Conclusions and relevance: Results of this study suggest that women and young patients with AD have relative preservation of brain structure when exposed to neocortical pathological tau. Interindividual differences in resilience to pathological tau may be important to disease progression because participants with both low brain and cognitive resilience had the most rapid cognitive decline over time.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1998

Fos Expression in Rat Brain During Depletion-Induced Thirst and Salt Appetite

The expression of Fos protein (Fos immunoreactivity, Fos-ir) was mapped in the brain of rats subjected to an angiotensin-dependent model of thirst and salt appetite. The physiological state associated with water and sodium ingestion was produced by the concurrent subcutaneous administration of the diuretic furosemide (10 mg/kg) and a low dose of the angiotensin-converting enzyme (ACE) inhibitor captopril (5 mg/kg; Furo/Cap treatment). The animals were killed 2 h posttreatment, and the brains were processed for Fos-ir to assess neural activation. Furo/Cap treatment significantly increased Fos-ir density above baseline levels both in structures of the lamina terminalis and hypothalamus known to mediate the actions of ANG 2 and in hindbrain regions associated with blood volume and pressure regulation. Furo/Cap treatment also typically increased Fos-ir density in these structures above levels observed after administration of furosemide or captopril separately. Fos-ir was reduced to a greater extent in forebrain than in hindbrain areas by a dose of captopril (100 mg/kg sc) known to block the actions of ACE in the brain. The present work provides further evidence that areas of lamina terminalis subserve angiotensin-dependent thirst and salt appetite.

Thunhorst, R. L.↗

NASA NTRSDate not supplied

Seamless Integration of Multibody and Orbital Dynamics to Support Human Spaceflight Simulations

At the NASA Johnson Space Center (JSC), modeling capability requirements are often driven by the need to simulate upcoming mission scenarios for analysis, procedures development, and training. In preparation for free-flyer vehicle capture, maneuvers, and release, it was determined that the multibody dynamics capabilities provided by MBDyn and the orbital dynamics capabilities supplied by JEOD needed to be merged to properly simulate the dynamic behaviors expected on-orbit. After initial attempts to combine the two packages proved cumbersome, it was decided that a more refined solution was required to facilitate the interface between these two packages. The resulting interface software package was named MBJEOD. The primary design goals for this new package were to leave MBDyn and JEOD untouched, to simplify and clarify simulation initialization for users, and to support any topology or on-orbit operational scenario that future missions might require. This paper provides a detailed overview of MBJEOD and the approach taken to seamlessly integrate the multibody dynamics of MBDyn with the orbital dynamics of JEOD. Additional attention is given to the numerical considerations required for MBJEOD and the simplifying assumptions leveraged to provide for real-time simulation needs. Verification and validation are addressed and current MBJEOD applications at the NASA JSC are discussed.

modeling↗

NASA NTRSDate not supplied

Seamless Integration of Multibody and Orbital Dynamics to Support Human Spaceflight Simulations

modeling↗

DOE OSTI2024

Bulk reconstruction and non-isometry in the backwards-forwards holographic black hole map

The backwards-forwards map, introduced as a generalization of the non-isometric holographic maps of the black hole interior of Akers, Engelhardt, Harlow, Penington, and Vardhan to include non-trivial dynamics in the effective description, has two possible formulations differing in when the post-selection is performed. While these two forms are equivalent on the set of dynamically generated states — states formed from unitary time evolution acting on well-defined initial configurations of infalling matter — they differ on the generic set of states necessary to describe the apparent world of the infalling observer. We show that while both versions successfully reproduce the Page curve, the version involving post-selection as the final step, dubbed the backwards-forwards-post-selection (BFP) map, has the desirable properties of being non-isometric but isometric on average and providing state-dependent reconstruction of bulk operators, while the other version does not. Thus the BFP map is a suitable non-isometric code describing the black hole interior including interior interactions.

3-D Image Reconstruction↗

DOE OSTI2020

Biofidelic Digital Head Model Software

Researchers at Los Alamos have extensive capabilities in biofidelic modeling, simulation and software development for predicting traumatic brain injury (TBI). Since injury-causing experiments cannot be performed on live humans, and head dummies are incapable of predicting brain deformations/strain, our approach uses magnetic resonance imaging (MRI) data for the brain combined with advanced computational methods and substructure constitutive properties to identify harmful accelerations that may develop diffused axonal injury in the brain. The goal is to develop this capability to analyze the effectiveness of personal protective equipment (PPE) such as, helmets and the advanced energy-absorbing materials used in PPE to mitigate brain injury. Los Alamos is seeking a collaborative partner (through a cooperative research and development agreement) to develop this capability toward a potential technology that will have commercial viability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Lowering the computational barrier: Partially Bayesian neural networks for transparency in medical imaging AI

Deep Neural Networks (DNNs) can provide clinicians with fast and accurate predictions that are highly valuable for high-stakes medical decision-making, such as in brain tumor segmentation and treatment planning. However, these models largely lack transparency about the uncertainty in their predictions, potentially giving clinicians a false sense of reliability that may lead to grave consequences in patient care. Growing calls for Transparent and Responsible AI have promoted Uncertainty Quantification (UQ) to capture and communicate uncertainty in a systematic and principled manner. However, traditional Bayesian UQ methods remain prohibitively costly for large, million-dimensional tumor segmentation DNNs such as the U-Net. In this work, we discuss a computationally-efficient UQ approach via the partially Bayesian neural networks (pBNN). In pBNN, only a single layer, strategically selected based on gradient-based sensitivity analysis, is targeted for Bayesian inference. We illustrate the effectiveness of pBNN in capturing the full uncertainty for a 7.8-million parameter U-Net. We also demonstrate how practitioners and model developers can use the pBNN's predictions to better understand the model's capabilities and behavior.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Tyramine and its Amtyr1 receptor modulate attention in honey bees (Apis mellifera)

Animals must learn to ignore stimuli that are irrelevant to survival and attend to ones that enhance survival. When a stimulus regularly fails to be associated with an important consequence, subsequent excitatory learning about that stimulus can be delayed, which is a form of nonassociative conditioning called ‘latent inhibition’. Honey bees show latent inhibition toward an odor they have experienced without association with food reinforcement. Moreover, individual honey bees from the same colony differ in the degree to which they show latent inhibition, and these individual differences have a genetic basis. To investigate the mechanisms that underly individual differences in latent inhibition, we selected two honey bee lines for high and low latent inhibition, respectively. We crossed those lines and mapped a Quantitative Trait Locus for latent inhibition to a region of the genome that contains the tyramine receptor gene Amtyr1 [We use Amtyr1 to denote the gene and AmTYR1 the receptor throughout the text.]. We then show that disruption of Amtyr1 signaling either pharmacologically or through RNAi qualitatively changes the expression of latent inhibition but has little or slight effects on appetitive conditioning, and these results suggest that AmTYR1 modulates inhibitory processing in the CNS. Electrophysiological recordings from the brain during pharmacological blockade are consistent with a model that AmTYR1 indirectly regulates at inhibitory synapses in the CNS. Our results therefore identify a distinct Amtyr1 -based modulatory pathway for this type of nonassociative learning, and we propose a model for how Amtyr1 acts as a gain control to modulate hebbian plasticity at defined synapses in the CNS. We have shown elsewhere how this modulation also underlies potentially adaptive intracolonial learning differences among individuals that benefit colony survival. Finally, our neural model suggests a mechanism for the broad pleiotropy this gene has on several different behaviors.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1989

Receptive fields and visual representations

Efficient representation of images for human use requires an understanding of how the brain processes and represents visual information. Spatial imagery is represented in the brain in the receptive fields of visual neurons. Models of these neurons lead to models of image fidelity, and to digital implementations of these neural codes. This approach will be illustrated by two example codes. The advantages and difficulties of this approach will be discussed.

Watson, Andrew B.↗

NASA NTRS1996

Computerized mappings of the cerebral cortex: a multiresolution flattening method and a surface-based coordinate system

We present a new method for generating two-dimensional maps of the cerebral cortex. Our computerized, two-stage flattening method takes as its input any well-defined representation of a surface within the three-dimensional cortex. The first stage rapidly converts this surface to a topologically correct two-dimensional map, without regard for the amount of distortion introduced. The second stage reduces distortions using a multiresolution strategy that makes gross shape changes on a coarsely sampled map and further shape refinements on progressively finer resolution maps. We demonstrate the utility of this approach by creating flat maps of the entire cerebral cortex in the macaque monkey and by displaying various types of experimental data on such maps. We also introduce a surface-based coordinate system that has advantages over conventional stereotaxic coordinates and is relevant to studies of cortical organization in humans as well as non-human primates. Together, these methods provide an improved basis for quantitative studies of individual variability in cortical organization.

Non-NASA Center↗

NASA NTRS2010

Human Perception of Ambiguous Inertial Motion Cues

Human daily activities on Earth involve motions that elicit both tilt and translation components of the head (i.e. gazing and locomotion). With otolith cues alone, tilt and translation can be ambiguous since both motions can potentially displace the otolithic membrane by the same magnitude and direction. Transitions between gravity environments (i.e. Earth, microgravity and lunar) have demonstrated to alter the functions of the vestibular system and exacerbate the ambiguity between tilt and translational motion cues. Symptoms of motion sickness and spatial disorientation can impair human performances during critical mission phases. Specifically, Space Shuttle landing records show that particular cases of tilt-translation illusions have impaired the performance of seasoned commanders. This sensorimotor condition is one of many operational risks that may have dire implications on future human space exploration missions. The neural strategy with which the human central nervous system distinguishes ambiguous inertial motion cues remains the subject of intense research. A prevailing theory in the neuroscience field proposes that the human brain is able to formulate a neural internal model of ambiguous motion cues such that tilt and translation components can be perceptually decomposed in order to elicit the appropriate bodily response. The present work uses this theory, known as the GIF resolution hypothesis, as the framework for experimental hypothesis. Specifically, two novel motion paradigms are employed to validate the neural capacity of ambiguous inertial motion decomposition in ground-based human subjects. The experimental setup involves the Tilt-Translation Sled at Neuroscience Laboratory of NASA JSC. This two degree-of-freedom motion system is able to tilt subjects in the pitch plane and translate the subject along the fore-aft axis. Perception data will be gathered through subject verbal reports. Preliminary analysis of perceptual data does not indicate that the GIF resolution hypothesis is completely valid for non-rotational periodic motions. Additionally, human perception of translation is impaired without visual or spatial reference. The performance of ground-base subjects in estimating tilt after brief training is comparable with that of crewmembers without training.

Zhang, Guan-Lu↗

NASA NTRS1972

Organization of brain tissue - Is the brain a noisy processor.

This paper presents some thoughts on functional organization in cerebral tissue. 'Spontaneous' wave and unit firing are considered as essential phenomena in the handling of information. Various models are discussed which have been suggested to describe the pseudorandom behavior of brain cells, leading to a view of the brain as an information processor and its role in learning, memory, remembering and forgetting.

Adey, W. R.↗

NASA NTRS2016

Behavioral, Brain Imaging and Genomic Measures to Predict Functional Outcomes Post - Bed Rest and Spaceflight

Astronauts experience sensorimotor disturbances during their initial exposure to microgravity and during the re-adaptation phase following a return to an Earth-gravitational environment. These alterations may disrupt crewmembers' ability to perform mission critical functional tasks requiring ambulation, manual control and gaze stability. Interestingly, astronauts who return from spaceflight show substantial differences in their abilities to readapt to a gravitational environment. The ability to predict the manner and degree to which individual astronauts would be affected would improve the effectiveness of countermeasure training programs designed to enhance sensorimotor adaptability. For such an approach to succeed, we must develop predictive measures of sensorimotor adaptability that will allow us to foresee, before actual spaceflight, which crewmembers are likely to experience the greatest challenges to their adaptive capacities. The goals of this project are to identify and characterize this set of predictive measures. Our approach includes: 1) behavioral tests to assess sensory bias and adaptability quantified using both strategic and plastic-adaptive responses; 2) imaging to determine individual brain morphological and functional features, using structural magnetic resonance imaging (MRI), diffusion tensor imaging, resting state functional connectivity MRI, and sensorimotor adaptation task-related functional brain activation; and 3) assessment of genotypic markers of genetic polymorphisms in the catechol-O-methyl transferase, dopamine receptor D2, and brain-derived neurotrophic factor genes and genetic polymorphisms of alpha2-adrenergic receptors that play a role in the neural pathways underlying sensorimotor adaptation. We anticipate that these predictive measures will be significantly correlated with individual differences in sensorimotor adaptability after long-duration spaceflight and exposure to an analog bed rest environment. We will be conducting a retrospective study, leveraging data already collected from relevant ongoing or completed bed rest and spaceflight studies. These data will be combined with predictor metrics that will be collected prospectively (as described for behavioral, brain imaging and genomic measures) from these returning subjects to build models for predicting post-mission (bed rest - non-astronauts or space flight - astronauts) adaptive capability as manifested in their outcome measures. To date we have completed a study on 15 normal subjects with all of the above measures. In this presentation we will discuss the optimized set of tests for predictive metrics to be used for evaluating post mission adaptive capability as manifested in their outcome measures. Comparisons of model performance will allow us to better design and implement sensorimotor adaptability training countermeasures against decrements in post-mission adaptive capability that are customized for each crewmember's sensory biases, adaptive capacity, brain structure and functional capacities, and genetic predispositions. The ability to customize adaptability training will allow more efficient use of crew time during training and will optimize training prescriptions for astronauts to ensure expected outcomes.

Mulavara, A. P.↗

NASA NTRS2017

Behavioral, Brain Imaging and Genomic Measures to Predict Functional Outcomes Post-Bed Rest and Space Flight

Astronauts experience sensorimotor disturbances during their initial exposure to microgravity and during the re-adaptation phase following a return to an Earth-gravitational environment. These alterations may disrupt crewmembers' ability to perform mission critical functional tasks requiring ambulation, manual control and gaze stability. Interestingly, astronauts who return from spaceflight show substantial differences in their abilities to readapt to a gravitational environment. The ability to predict the manner and degree to which individual astronauts are affected will improve the effectiveness of countermeasure training programs designed to enhance sensorimotor adaptability. For such an approach to succeed, we must develop predictive measures of sensorimotor adaptability that will allow us to foresee, before actual spaceflight, which crewmembers are likely to experience greater challenges to their adaptive capacities. The goals of this project are to identify and characterize this set of predictive measures. Our approach includes: 1) behavioral tests to assess sensory bias and adaptability quantified using both strategic and plastic-adaptive responses; 2) imaging to determine individual brain morphological and functional features, using structural magnetic resonance imaging (MRI), diffusion tensor imaging, resting state functional connectivity MRI, and sensorimotor adaptation task-related functional brain activation; and 3) assessment of genetic polymorphisms in the catechol-O-methyl transferase, dopamine receptor D2, and brain-derived neurotrophic factor genes and genetic polymorphisms of alpha2-adrenergic receptors that play a role in the neural pathways underlying sensorimotor adaptation. We anticipate that these predictive measures will be significantly correlated with individual differences in sensorimotor adaptability after long-duration spaceflight and exposure to an analog bed rest environment. We will be conducting a retrospective study, leveraging data already collected from relevant ongoing or completed bed rest and spaceflight studies. This data will be combined with predictor metrics that will be collected prospectively (as described for behavioral, brain imaging and genomic measures) from these returning subjects to build models for predicting post spaceflight and bed rest adaptive capability. In this presentation we will discuss the optimized set of tests for predictive metrics to be used for evaluating post mission adaptive capability as manifested in their outcome measures. Comparisons of model performance will allow us to better design and implement sensorimotor adaptability training countermeasures against decrements in post-mission adaptive capability that are customized for each crewmember's sensory biases, adaptive ability, brain structure, brain function, and genetic predispositions. The ability to customize adaptability training will allow more efficient use of crew time during training and will optimize training prescriptions for astronauts to mitigate the deleterious effects of spaceflight.

Mulavara, A. P.↗

DOE OSTI2024

Adaptive optical third-harmonic generation microscopy for in vivo imaging of tissues

Third-harmonic generation microscopy is a powerful label-free nonlinear imaging technique, providing essential information about structural characteristics of cells and tissues without requiring external labelling agents. In this work, we integrated a recently developed compact adaptive optics module into a third-harmonic generation microscope, to measure and correct for optical aberrations in complex tissues. Taking advantage of the high sensitivity of the third-harmonic generation process to material interfaces and thin membranes, along with the 1,300-nm excitation wavelength used here, our adaptive optical third-harmonic generation microscope enabled high-resolution in vivo imaging within highly scattering biological model systems. Examples include imaging of myelinated axons and vascular structures within the mouse spinal cord and deep cortical layers of the mouse brain, along with imaging of key anatomical features in the roots of the model plant Brachypodium distachyon. In all instances, aberration correction led to enhancements in image quality.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2016

Holodeck Testbed Project

The main objective of the Holodeck Testbed is to create a cost effective, realistic, and highly immersive environment that can be used to train astronauts, carry out engineering analysis, develop procedures, and support various operations tasks. Currently, the Holodeck testbed allows to step into a simulated ISS (International Space Station) and interact with objects; as well as, perform Extra Vehicular Activities (EVA) on the surface of the Moon or Mars. The Holodeck Testbed is using the products being developed in the Hybrid Reality Lab (HRL). The HRL is combining technologies related to merging physical models with photo-realistic visuals to create a realistic and highly immersive environment. The lab also investigates technologies and concepts that are needed to allow it to be integrated with other testbeds; such as, the gravity offload capability provided by the Active Response Gravity Offload System (ARGOS). My main two duties were to develop and animate models for use in the HRL environments and work on a new way to interface with computers using Brain Computer Interface (BCI) technology. On my first task, I was able to create precise computer virtual tool models (accurate down to the thousandths or hundredths of an inch). To make these tools even more realistic, I produced animations for these tools so they would have the same mechanical features as the tools in real life. The computer models were also used to create 3D printed replicas that will be outfitted with tracking sensors. The sensor will allow the 3D printed models to align precisely with the computer models in the physical world and provide people with haptic/tactile feedback while wearing a VR (Virtual Reality) headset and interacting with the tools. Getting close to the end of my internship the lab bought a professional grade 3D Scanner. With this, I was able to replicate more intricate tools at a much more time-effective rate. The second task was to investigate the use of BCI to control objects inside the hybrid reality ISS environment. This task looked at using an Electroencephalogram (EEG) headset to collect brain state data that could be mapped to commands that a computer could execute. On this Task, I had a setback with the hardware, which stopped working and was returned to the vendor for repair. However, I was still able to collect some data, was able to process it, and started to create correlation algorithms between the electrical patterns in the brain and the commands we wanted the computer to carry out. I also carried out a test to investigate the comfort of the headset if it is worn for a long time. The knowledge gained will benefit me in my future career. I learned how to use various modeling and programming tools that included Blender, Maya, Substance Painter, Artec Studio, Github, and Unreal Engine 4. I learned how to use a professional grade 3D scanner and 3D printer. On the BCI Project I learned about data mining and how to create correlation algorithms. I also supported various demos including a live demo of the hybrid reality lab capabilities at ComicPalooza. This internship has given me a good look into engineering at NASA. I developed a more thorough understanding of engineering and my overall confidence has grown. I have also realized that any problem can be fixed, if you try hard enough, and as an engineer it is your job to not only fix problems but to embrace coming up with solutions to those problems.

Arias, Adriel↗

DOE OSTI2024

Antiviral Effect of Antimicrobial Peptoid TM9 and Murine Model of Respiratory Coronavirus Infection

New antiviral agents are essential to improving treatment and control of SARS-CoV-2 infections that can lead to the disease COVID-19. Antimicrobial peptoids are sequence-specific oligo-N-substituted glycine peptidomimetics that emulate the structure and function of natural antimicrobial peptides but are resistant to proteases. We demonstrate antiviral activity of a new peptoid (TM9) against the coronavirus, murine hepatitis virus (MHV), as a closely related model for the structure and antiviral susceptibility profile of SARS-CoV-2. This peptoid mimics the human cathelicidin LL-37, which has also been shown to have antimicrobial and antiviral activity. In this study, TM9 was effective against three murine coronavirus strains, demonstrating that the therapeutic window is large enough to allow the use of TM9 for treatment. All three isolates of MHV generated infection in mice after 15 min of exposure by aerosol using the Madison aerosol chamber, and all three viral strains could be isolated from the lungs throughout the 5-day observation period post-infection, with the peak titers on day 2. MHV-A59 and MHV-A59-GFP were also isolated from the liver, heart, spleen, olfactory bulbs, and brain. These data demonstrate that MHV serves as a valuable natural murine model of coronavirus pathogenesis in multiple organs, including the brain.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2023

Numerical Investigation of Occupant Injury Risks During A Realistic Transport Aircraft Crash Conditions

Researchers at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) have conducted a full-scale crash test of a Fokker F28 MK1000 aircraft to investigate the performance of transport aircraft under realistic crash conditions. This crash test was computationally recreated using finite element (FE) human body models (HBMs) to further explore potential injury risks to occupants and analyze the utilization of HBMs in the aerospace crash environment. The Global Human Body Model Consortium (GHBMC) male 50th percentile occupant detailed model (v6.0) and the Toyota Human Model for Safety (THUMS) male 50th percentile occupant model (v6.1) were selected to be used in the crash simulations. The HBMs were simulated in conditions matching those of anthropomorphic test device (ATD) experiments included within the aircraft cabin during the crash test. Seven occupant locations within the cabin were simulated utilizing each of the models. The models were positioned in a neutral upright posture with hands resting on the legs and the feet contacting the floor. Head, brain, neck, and lumbar vertebra injury metrics were calculated for all trials. Both HBM models required minor modifications to stabilize these simulations. The GHBMC model required added erosion for six parts while the THUMS model only required one in order to complete the full simulation. The THUMS model, however, required a much smaller timestep for stability and therefore took significantly more computational time. In addition the GHBMC model includes integrated instrumentation while the THUMS model requires development and implementation of instrumentation. Both models predicted 100% injury risk for lumbar vertebra fracture in all test conditions. This prediction was in family with high lumbar load values measured by the ATDs during the crash test. The THUMS model consistently predicted lower injury risks than the GHBMC model in all three other metrics varying depending on the crash pulse. Overall, the THUMS model required less modifications to allow for this study. However, the GHBMC models significantly faster run time and integrated instrumentation make it a more intuitive model for this research.

Crashworthiness↗