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.

A subject-specific human head finite element model with embedded axonal fiber tractography obtained from diffusion tensor imaging was developed. The axonal fiber tractography finite element model was coupled with the volumetric elements in the head model using the embedded element method. This technique enables the calculation of axonal strains and real-time tracking of the mechanical response of the axonal fiber tracts. The coupled model was then verified using pressure and relative displacement-based (between skull and brain) experimental studies and was employed to analyze a head impact, demonstrating the applicability of this method in studying axonal injury. Following this, a comparison study of different injury criteria was performed. This model was used to determine the influence of impact direction on the extent of the axonal injury. The results suggested that the lateral impact loading is more dangerous compared to loading in the sagittal plane, a finding in agreement with previous studies. Through this analysis, we demonstrated the viability of the embedded element method as an alternative numerical approach for studying axonal injury in patient-specific human head models.

Brain-computer interface and neuromodulation strategies relying on penetrating non-organic electrodes/optrodes are limited by an inflammatory foreign body response that ultimately diminishes performance. A novel "biohybrid" strategy is advanced, whereby living neurons, biomaterials, and microelectrode/optical technology are used together to provide a biologicallybased vehicle to probe and modulate nervous-system activity. Microtissue engineering techniques are employed to create axon-based "living electrodes", which are columnar microstructures comprised of neuronal population(s) projecting long axonal tracts within the lumen of a hydrogel designed to chaperone delivery into the brain. Upon microinjection, the axonal segment penetrates to prescribed depth for synaptic integration with local host neurons, with the perikaryal segment remaining externalized below conforming electrical-optical arrays. In this paradigm, only the biological component ultimately remains in the brain, potentially attenuating a chronic foreign-body This article is protected by copyright. All rights reserved. 4 response. Axon-based living electrodes are constructed using multiple neuronal subtypes, each with differential capacity to stimulate, inhibit, and/or modulate neural circuitry based on specificity uniquely afforded by synaptic integration, yet ultimately computer controlled by optical/electrical components on the brain surface. Current efforts are assessing the efficacy of this biohybrid interface for targeted, synaptic-based neuromodulation, and the specificity, spatial density and longterm fidelity versus conventional microelectronic or optical substrates alone.

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For implantable neural interfaces, functional/clinical outcomes are challenged by limitations in specificity and stability of inorganic microelectrodes. A biological intermediary between microelectrical devices and the brain may improve specificity and longevity through (i) natural synaptic integration with deep neural circuitry, (ii) accessibility on the brain surface, and (iii) optogenetic manipulation for targeted, light-based readout/control. Accordingly, we have developed implantable “living electrodes,” living cortical neurons, and axonal tracts protected within soft hydrogel cylinders, for optobiological monitoring/modulation of brain activity. Here, we demonstrate fabrication, rapid axonal outgrowth, reproducible cytoarchitecture, and simultaneous optical stimulation and recording of these tissue engineered constructs in vitro. We also present their transplantation, survival, integration, and optical recording in rat cortex as an in vivo proof of concept for this neural interface paradigm. The creation and characterization of these functional, optically controllable living electrodes are critical steps in developing a new class of optobiological tools for neural interfacing.

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The three methods of determining the quasi‐static Mode I fracture toughness (KIc) (surface crack in flexure—SC, single‐edge precracked beam—PB, and chevron‐notched beam—VB) found in ASTM C1421 were applied to a variety of advanced ceramic materials. All three methods produced valid and comparable KIc values for the Al2O3, SiC, Si3N4, and SiAlON ceramics examined. However, not all methods could successfully be applied to B4C, ZrO2, and WC ceramics due to a variety of material factors. The coarse‐grained microstructure of one B4C hindered the ability to observe and measure the precracks generated in the SC and PB methods while the transformation toughening in the ZrO2 prevented the formation of the SC and PB precracks and thus made it impossible to use either method on this ceramic. The high strength and elastic modulus of the WC made it impossible to achieve stable crack growth using the VB method because the specimen stored a tremendous amount of energy prior to fracture. Even though these methods have passed the rigors of the standardization process there are still some issues to be resolved when the methods are applied to certain classes of ceramics. It is recommended that, when appropriate, at least two of these methods be employed to determine the KIc, especially when a new or unfamiliar ceramic is being evaluated.