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Modeling methods in understanding and ameliorating central nervous system injury
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Singh, Sagar. Modeling methods in understanding and ameliorating central nervous system injury. Retrieved from https://doi.org/doi:10.7282/T36D5WB7

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TitleModeling methods in understanding and ameliorating central nervous system injury
NameSingh, Sagar (author); Shreiber, David I (chair); Langrana, Noshir (internal member); Firestein, Bonnie (internal member); Kaplan, Hilton (internal member); Pelegri, ASSIMINA (outside member); Rutgers University; Graduate School - New Brunswick
Date Created2016
Other Date2016-10 (degree)
SubjectBiomedical Engineering, Central nervous system--Wounds and injuries, Spinal cord--Wounds and injuries
Extent1 online resource (xiv, 220 p. : ill.)
DescriptionTo improve the quality of life for victims of traumatic spinal cord and brain injury, a better understanding of how microstructural mechanical behavior influences bulk tissue and vice versa is necessary. Two aspects that warrant attention in this matter are primary injury and neural electrode-tissue interactions. While their respective biomechanics are measurable at the macroscopic level, it is difficult to measure microscopic deformations during injury in situ and in vivo experimentally. To overcome this limitation, we develop experimentally validated computational approaches to predict the multiscale translations involved in white matter tissue injury, and probe-tissue interfaces. In the first part of this dissertation, we developed approaches to model primary injury at the axon level. First we developed 3-D axon kinematic models to infer axonal strain as a function of tissue-level stretch. Embryonic chick spinal cord tissue was exposed to controlled stretch and axon tortuosity and kinematics were characterized in 3-dimensions. We determined that greater proportions of axons are predicted to behave with affine, composite-like kinematics. Next, we identified and evaluated contactin-associated protein (Caspr) for use as a fiducial marker in estimating axonal strain and axonal failure thresholds. Spinal cord tissue was exposed to controlled stretch, and displacements of immunostained Caspr proteins were measured. Changes in Caspr displacements reflected the applied macroscopic stretch directly at earlier stages of development but this trend deviated with further development. This shift in trend correlated with observations of axon failure at later stages of development, and we predicted axon failure thresholds to decrease with development. In the second part of this dissertation, we developed approaches to model multiscale mechanics in neural probe and tissue interactions. Finite element simulations were developed and experimentally validated to determine insertion and buckling forces for different coating and probe designs. Parameter sweeps of these features determined that probe length and coating thickness had the biggest impact on insertion forces. Next, we used the model to simulate the probe-tissue interface in order to correlate interfacial stress and tissue strain to chronic injury. Stress and strain predictions were made for a variety of probe designs and results were validated with parallel experiments using agarose tissue phantoms. We correlated predictions to gliosis through an in vitro model where astrocytes cultured in collagen gels were cast around a probe and exposed to micromotion. We determined that probe stiffness has a greater effect on chronic injury than size. We were also able to predict minimum strain thresholds for inducing astrocyte activation. The findings in this work help elucidate multiscale transfers in white matter injury and probe-tissue interfaces. These results can be applied to the design of better preventative measures for brain and spinal cord injury (sports and military equipment), as well as neural probes for long-term signal acquisition/stimulation in brain-to-computer interfaces.
NotePh.D.
NoteIncludes bibliographical references
Noteby Sagar Singh
Genretheses, ETD doctoral
Persistent URLhttps://doi.org/doi:10.7282/T36D5WB7
Languageeng
CollectionGraduate School - New Brunswick Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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