Ultrastructural mechanical and material characterization of fossilized bone

Bone plays a key role in the paleontological and archeological records and can provide insight into the biology, ecology and the environment of ancient vertebrates. Examination of bone at the tissue level reveals a definitive relationship between nanomechanical properties and the local organic content, mineral content, and microstructural organization. However, it is unclear as to how these properties change following fossilization, or diagenesis, where the organic phase is rapidly removed and the remaining mineral phase is reinforced by the deposition of apatites, calcites, and other minerals. While the process of diagenesis is poorly understood, its outcome clearly results in the potential for dramatic alteration of the mechanical response of biological tissues. In this study, fossilized specimens of mammalian long bones, collected from Colorado and Wyoming, were studied for mechanical variations. Nanoindentation performed in both longitudinal and transverse directions revealed preservation of bone's natural anisotropy as transverse modulus values were consistently smaller than longitudinal values. Additionally, modulus values of fossilized bone from 35.0 to 89.1 GPa increased linearly with logarithm of the sample's age. Future studies will aim to clarify what mechanical and material elements of bone are retained during diagenesis as bone becomes part of the geologic milieu. © 2007 Materials Research Society.

Effects of gelatin on mechanical properties of hydroxyapatite-gelatin nano-composltes

A biomimetic reactor has been developed to synthesize hydroxyapatite- gelatin (HAP-GEL) nanocomposites that mimic ultra-structures of natural bone. We hypothesize that in the reactor, gelatin concentration controls morphology and packing structures of HAP crystals. To test the hypothesis, three types of mechanical tests were conducted, including nanoindentation, compression, and fracture tests. Nanoindentation tests in conjunction with computer modeling were used to assess effects on gelatin-induced microstructures of HAP. The results showed that increasing gelatin content increased both the plane strain modulus and the fracture toughness. The gelatin appeared to shorten the HAP crystal distance, which consolidated the internal structure of the composite and made the material more rigid. The fracture toughness KIC increased partially due to the effect of fiber bridging between gelatin molecules. The highest fracture toughness (1.12 MPa·1/2) was equivalent to that of pure hydroxyapatite. The compressive strength of the HAP-GEL (107.7±26.8 MPa) was, however, less sensitive to microstructural changes and was within the range of natural cortical bone (human 170 MPa, pig: 100 MPa). The compression strength was dominated by void inclusions while the nanoindentation response reflected ultra-structural arrangement of the crystals. The gelatin concentration is likely to modify crystal arrangement as demonstrated in TEM experiments but not void distribution at macroscopic levels. © 2006 Materials Research Society.

Adaptation to stable and unstable dynamics achieved by combined impedance control and inverse dynamics model.

This study compared adaptation in novel force fields where trajectories were initially either stable or unstable to elucidate the processes of learning novel skills and adapting to new environments. Subjects learned to move in a null force field (NF), which was unexpectedly changed either to a velocity-dependent force field (VF), which resulted in perturbed but stable hand trajectories, or a position-dependent divergent force field (DF), which resulted in unstable trajectories. With practice, subjects learned to compensate for the perturbations produced by both force fields. Adaptation was characterized by an initial increase in the activation of all muscles followed by a gradual reduction. The time course of the increase in activation was correlated with a reduction in hand-path error for the DF but not for the VF. Adaptation to the VF could have been achieved solely by formation of an inverse dynamics model and adaptation to the DF solely by impedance control. However, indices of learning, such as hand-path error, joint torque, and electromyographic activation and deactivation suggest that the CNS combined these processes during adaptation to both force fields. Our results suggest that during the early phase of learning there is an increase in endpoint stiffness that serves to reduce hand-path error and provides additional stability, regardless of whether the dynamics are stable or unstable. We suggest that the motor control system utilizes an inverse dynamics model to learn the mean dynamics and an impedance controller to assist in the formation of the inverse dynamics model and to generate needed stability.

Impedance control balances stability with metabolically costly muscle activation.

Humans are able to stabilize their movements in environments with unstable dynamics by selectively modifying arm impedance independently of force and torque. We further investigated adaptation to unstable dynamics to determine whether the CNS maintains a constant overall level of stability as the instability of the environmental dynamics is varied. Subjects performed reaching movements in unstable force fields of varying strength, generated by a robotic manipulator. Although the force fields disrupted the initial movements, subjects were able to adapt to the novel dynamics and learned to produce straight trajectories. After adaptation, the endpoint stiffness of the arm was measured at the midpoint of the movement. The stiffness had been selectively modified in the direction of the instability. The stiffness in the stable direction was relatively unchanged from that measured during movements in a null force field prior to exposure to the unstable force field. This impedance modification was achieved without changes in force and torque. The overall stiffness of the arm and environment in the direction of instability was adapted to the force field strength such that it remained equivalent to that of the null force field. This suggests that the CNS attempts both to maintain a minimum level of stability and minimize energy expenditure.

Impedance control and internal model use during the initial stage of adaptation to novel dynamics in humans.

This study investigated the neuromuscular mechanisms underlying the initial stage of adaptation to novel dynamics. A destabilizing velocity-dependent force field (VF) was introduced for sets of three consecutive trials. Between sets a random number of 4-8 null field trials were interposed, where the VF was inactivated. This prevented subjects from learning the novel dynamics, making it possible to repeatedly recreate the initial adaptive response. We were able to investigate detailed changes in neural control between the first, second and third VF trials. We identified two feedforward control mechanisms, which were initiated on the second VF trial and resulted in a 50% reduction in the hand path error. Responses to disturbances encountered on the first VF trial were feedback in nature, i.e. reflexes and voluntary correction of errors. However, on the second VF trial, muscle activation patterns were modified in anticipation of the effects of the force field. Feedforward cocontraction of all muscles was used to increase the viscoelastic impedance of the arm. While stiffening the arm, subjects also exerted a lateral force to counteract the perturbing effect of the force field. These anticipatory actions indicate that the central nervous system responds rapidly to counteract hitherto unfamiliar disturbances by a combination of increased viscoelastic impedance and formation of a crude internal dynamics model.

Impedance control is tuned to multiple directions of movement

Humans are able to learn tool-handling tasks, such as carving, demonstrating their competency to make and vary the direction of movements in unstable environments. It has been shown that when a single reaching movement is repeated in unstable dynamics, the central nervous system (CNS) learns an impedance internal model to compensate for the environment instability. However, there is still no explanation for how humans can learn to move in various directions in such environments. In this study, we investigated whether and how humans compensate for instability while learning two different reaching movements simultaneously. Results show that when performing movements in two different directions, separated by a 35° angle, the CNS was able to compensate for the unstable dynamics. After adaptation, the force was found to be similar to the free movement condition, but stiffness increased in the direction of instability, specifically for each direction of movement. Our findings suggest that the CNS either learned an internal model generalizing over different movements, or alternatively that it was able to switch between specific models acquired simultaneously. © 2008 IEEE.