Contribution of Phase Resetting to Adaptive Rhythm Control in Human Walking Based on the Phase Response Curves of a Neuromusculoskeletal Model.

Humans walk adaptively in varying environments by manipulating their complicated and redundant musculoskeletal system. Although the central pattern generators in the spinal cord are largely responsible for adaptive walking through sensory-motor coordination, it remains unclear what neural mechanisms determine walking adaptability. It has been reported that locomotor rhythm and phase are regulated by the production of phase shift and rhythm resetting (phase resetting) for periodic motor commands in response to sensory feedback and perturbation. While the phase resetting has been suggested to make a large contribution to adaptive walking, it has only been investigated based on fictive locomotion in decerebrate cats, and thus it remains unclear if human motor control has such a rhythm regulation mechanism during walking. In our previous work, we incorporated a phase resetting mechanism into a motor control model and demonstrated that it improves the stability and robustness of walking through forward dynamic simulations of a human musculoskeletal model. However, this did not necessarily verify that phase resetting plays a role in human motor control. In our other previous work, we used kinematic measurements of human walking to identify the phase response curve (PRC), which explains phase-dependent responses of a limit cycle oscillator to a perturbation. This revealed how human walking rhythm is regulated by perturbations. In this study, we integrated these two approaches using a physical model and identification of the PRC to examine the hypothesis that phase resetting plays a role in the control of walking rhythm in humans. More specifically, we calculated the PRC using our neuromusculoskeletal model in the same way as our previous human experiment. In particular, we compared the PRCs calculated from two different models with and without phase resetting while referring to the PRC for humans. As a result, although the PRC for the model without phase resetting did not show any characteristic shape, the PRC for the model with phase resetting showed a characteristic phase-dependent shape with trends similar to those of the PRC for humans. These results support our hypothesis and will improve our understanding of adaptive rhythm control in human walking.

Neuromusculoskeletal model that walks and runs across a speed range with a few motor control parameter changes based on the muscle synergy hypothesis.

Humans walk and run, as well as change their gait speed, through the control of their complicated and redundant musculoskeletal system. These gaits exhibit different locomotor behaviors, such as a double-stance phase in walking and flight phase in running. The complex and redundant nature of the musculoskeletal system and the wide variation in locomotion characteristics lead us to imagine that the motor control strategies for these gaits, which remain unclear, are extremely complex and differ from one another. It has been previously proposed that muscle activations may be generated by linearly combining a small set of basic pulses produced by central pattern generators (muscle synergy hypothesis). This control scheme is simple and thought to be shared between walking and running at different speeds. Demonstrating that this control scheme can generate walking and running and change the speed is critical, as bipedal locomotion is dynamically challenging. Here, we provide such a demonstration by using a motor control model with 69 parameters developed based on the muscle synergy hypothesis. Specifically, we show that it produces both walking and running of a human musculoskeletal model by changing only seven key motor control parameters. Furthermore, we show that the model can walk and run at different speeds by changing only the same seven parameters based on the desired speed. These findings will improve our understanding of human motor control in locomotion and provide guiding principles for the control design of wearable exoskeletons and prostheses.

Generation of an ICF syndrome model by efficient genome editing of human induced pluripotent stem cells using the CRISPR system.

Genome manipulation of human induced pluripotent stem (iPS) cells is essential to achieve their full potential as tools for regenerative medicine. To date, however, gene targeting in human pluripotent stem cells (hPSCs) has proven to be extremely difficult. Recently, an efficient genome manipulation technology using the RNA-guided DNase Cas9, the clustered regularly interspaced short palindromic repeats (CRISPR) system, has been developed. Here we report the efficient generation of an iPS cell model for immunodeficiency, centromeric region instability, facial anomalies syndrome (ICF) syndrome using the CRISPR system. We obtained iPS cells with mutations in both alleles of DNA methyltransferase 3B (DNMT3B) in 63% of transfected clones. Our data suggest that the CRISPR system is highly efficient and useful for genome engineering of human iPS cells.

Genome engineering of mammalian haploid embryonic stem cells using the Cas9/RNA system.

Haploid embryonic stem cells (ESCs) are useful for studying mammalian genes because disruption of only one allele can cause loss-of-function phenotypes. Here, we report the use of haploid ESCs and the CRISPR RNA-guided Cas9 nuclease gene-targeting system to manipulate mammalian genes. Co-transfection of haploid ESCs with vectors expressing Cas9 nuclease and single-guide RNAs (sgRNAs) targeting Tet1, Tet2, and Tet3 resulted in the complete disruption of all three genes and caused a loss-of-function phenotype with high efficiency (50%). Co-transfection of cells with vectors expressing Cas9 and sgRNAs targeting two loci on the same chromosome resulted in the creation of a large chromosomal deletion and a large inversion. Thus, the use of the CRISPR system in combination with haploid ESCs provides a powerful platform to manipulate the mammalian genome.