This article presents the integration of brain injury biomechanics and graph theoretical analysis of neuronal connections, or connectomics, to form a neurocomputational model that captures spatiotemporal characteristics of trauma. We relate localized mechanical brain damage predicted from biofidelic finite element simulations of the human head subjected to impact with degradation in the structural connectome for a single individual. The finite element model incorporates various length scales into the full head simulations by including anisotropic constitutive laws informed by diffusion tensor imaging. Coupling between the finite element analysis and network-based tools is established through experimentally-based cellular injury thresholds for white matter regions. Once edges are degraded, graph theoretical measures are computed on the “damaged” network. For a frontal impact, the simulations predict that the temporal and occipital regions undergo the most axonal strain and strain rate at short times (less than 24 hrs), which leads to cellular death initiation, which results in damage that shows dependence on angle of impact and underlying microstructure of brain tissue. The monotonic cellular death relationships predict a spatiotemporal change of structural damage. Interestingly, at 96 hrs post-impact, computations predict no network nodes were completely disconnected from the network, despite significant damage to network edges. At early times () network measures of global and local efficiency were degraded little; however, as time increased to 96 hrs the network properties were significantly reduced. In the future, this computational framework could help inform functional networks from physics-based structural brain biomechanics to obtain not only a biomechanics-based understanding of injury, but also neurophysiological insight.
Simulations show that extremely high-powered microwave pulses can cause potentially injurious intracranial stresses.
Recent wars have heightened the need to better protect dismounted soldiers against emerging blast and ballistic threats. Traumatic Brain Injury (TBI) due to blast and ballistic loading has been a subject of many recent studies. In this paper, we report a numerical study to understand the effects of load transmitted through a combat helmet and pad system to the head and eventually to the brain during a blast event. The ALE module in LS-DYNA was used to model the interactions between fluid (air) and the structure (helmet/head assembly). The geometry model for the head was generated from the MRI scan of a human head. For computational simplicity, four major components of the head are modeled: skin, bone, cerebrospinal fluid (CSF) and brain. A spherical shape blast wave was generated by using a spherical shell air zone surrounding the helmet/head structure. A numerical evaluation of boundary conditions and numerical algorithm to capture the wave transmission was carried out first in a simpler geometry. The ConWep function was used to apply blast pressure to the 3D model. The blast pressure amplitude was found to reduce as it propagated through the foam pads, indicating the latter’s utility in mitigating blast effects. It is also shown that the blast loads are only partially transmitted to the head. In the calculation where foam pads were not used, the pressure in the skin was found to be higher due to the underwash effect in the gap between the helmet and skin, which amplified the blast pressure.
Measurements of the mechanical response of biological cells are critical for understanding injury and disease, for developing diagnostic tools, and for computational models in mechanobiology. Although it is well known that cells are sensitive to the topography of their microenvironment, the current paradigm in mechanical testing of adherent cells is mostly limited to specimens grown on flat two-dimensional substrates. In this study, we introduce a technique in which cellular indentation via optical trapping is performed on cells at a high spatial resolution to obtain their regional mechanical properties while they exist in a more favorable three-dimensional microenvironment. We combine our approach with nonlinear contact mechanics theory to consider the effects of a large deformation. This allows us to probe length scales that are relevant for obtaining overall cell stiffness values. The experimental results herein provide the hyperelastic material properties at both high ($100 s À1 ) and low ($1-10 s À1 ) strain rates of murine central nervous system glial cells. The limitations due to possible misalignment of the indenter in the three-dimensional space are examined using a computational model.
Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing the burden, to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number.
Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing the burden, to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number.
Approved for public release; distribution unlimited. ii REPORT DOCUMENTATION PAGEForm Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing the burden, to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. REPORT DATE (DD-MM-YYYY)January 2012 ARL-TR-5893 SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR'S ACRONYM(S) SPONSOR/MONITOR'S REPORT NUMBER(S) DISTRIBUTION/AVAILABILITY STATEMENTApproved for public release; distribution unlimited. SUPPLEMENTARY NOTES ABSTRACTIn FY11, a collaborative team of researchers began a new Director's Strategic Initiative (DSI) to examine brain structurefunction couplings. The effort aims to develop a multidisciplinary, multiscale understanding of the relationship between the brain's physical structure, its dynamic electrochemical functioning, and human behavior. Here, brain structure refers to the architecture of the brain, namely, the grey matter regions in the brain and the white matter fiber tracts that connect them, and brain function indicates the neuron activity that enables communication between those regions. Combined, the individual variations in brain structure and function are thought to underlie and predict individual differences in task performance and human behavior. One of the broad, far-reaching goals of this initiative is to understand the set of circumstances under which individual differences in brain structure can be leveraged to account, predict, or enhance the measurement of brain function at varying time scales. The initiative has four main research areas-electrochemical modeling, biomechanical structural changes, electrochemical data collection and analysis, and time-evolving functional connectivity-and this year-end report captures some of the research highlights and accomplishments during the first year of the program. iii SUBJECT TERMS
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