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Perceived goal instrumentality is associated with forgiveness: A test of the valuable relationships hypothesis
Three autobiographical studies tested the valuable relationships hypothesis of forgiveness. Although previous studies revealed that relationship value predicts interpersonal forgiveness, the measure of relationship value may be conflated with affective assessments of the relationship with the transgressor, which might have caused a criterion contamination problem. Therefore, we assessed the goal-related instrumentality of the transgressor (i.e., how useful the transgressor is for helping the victim to achieve his/her goals in fitness-relevant domains). Three studies, one involving a Japanese student sample (Study 1), a second involving Japanese community sample (Study 2), and a third involving U.S. community sample (Study 3), convergently showed that perceived goal instrumentality, as well as a latent relationship value variable estimated from multiple measures of relationship value, are associated with forgiveness. Moreover, this association could be explained in part by the intermediate association of perceived goal instrumentality with empathy both in Japan and the U.S
Postural dysfunction in spinocerebellar ataxia type 3 transgenic mice
学位の種別:課程博士University of Tokyo(東京大学
Dysfunction of postural adjustments associated with voluntary movements in a mouse model of spinocerebellar ataxia type 3
Abstract-We investigated kinematics of the hindlimb and electromyographic activities of the hindlimb muscles in the mouth reaching task needing postural adjustments in a mouse model of spinocerebellar ataxia type 3 (SCA3). The mouse model of SCA3 showed the dysfunction of the postural adjustments. The results indicate that the cerebellum play an important role in the postural adjustments associated with the intended movements
Superconductivity suppression of Ba0.5K0.5Fe2-2xM2xAs2 single crystals by substitution of transition-metal (M = Mn, Ru, Co, Ni, Cu, and Zn)
We investigated the doping effects of magnetic and nonmagnetic impurities on
the single-crystalline p-type Ba0.5K0.5Fe2-2xM2xAs2 (M = Mn, Ru, Co, Ni, Cu and
Zn) superconductors. The superconductivity indicates robustly against impurity
of Ru, while weakly against the impurities of Mn, Co, Ni, Cu, and Zn. However,
the present Tc suppression rate of both magnetic and nonmagnetic impurities
remains much lower than what was expected for the s\pm-wave model. The
temperature dependence of resistivity data is observed an obvious low-T upturn
for the crystals doped with high-level impurity, which is due to the occurrence
of localization. Thus, the relatively weak Tc suppression effect from Mn, Co,
Ni, Cu, and Zn are considered as a result of localization rather than
pair-breaking effect in s\pm-wave model.Comment: 8 pages, 9 figures, to be published in Phys. Rev.
Contributions of phase resetting and interlimb coordination to the adaptive control of hindlimb obstacle avoidance during locomotion in rats: a simulation study.
Obstacle avoidance during locomotion is essential for safe, smooth locomotion. Physiological studies regarding muscle synergy have shown that the combination of a small number of basic patterns produces the large part of muscle activities during locomotion and the addition of another pattern explains muscle activities for obstacle avoidance. Furthermore, central pattern generators in the spinal cord are thought to manage the timing to produce such basic patterns. In the present study, we investigated sensory-motor coordination for obstacle avoidance by the hindlimbs of the rat using a neuromusculoskeletal model. We constructed the musculoskeletal part of the model based on empirical anatomical data of the rat and the nervous system model based on the aforementioned physiological findings of central pattern generators and muscle synergy. To verify the dynamic simulation by the constructed model, we compared the simulation results with kinematic and electromyographic data measured during actual locomotion in rats. In addition, we incorporated sensory regulation models based on physiological evidence of phase resetting and interlimb coordination and examined their functional roles in stepping over an obstacle during locomotion. Our results show that the phase regulation based on interlimb coordination contributes to stepping over a higher obstacle and that based on phase resetting contributes to quick recovery after stepping over the obstacle. These results suggest the importance of sensory regulation in generating successful obstacle avoidance during locomotion
Deploying and Optimizing Embodied Simulations of Large-Scale Spiking Neural Networks on HPC Infrastructure
Simulating the brain-body-environment trinity in closed loop is an attractive proposal to investigate how perception, motor activity and interactions with the environment shape brain activity, and vice versa. The relevance of this embodied approach, however, hinges entirely on the modeled complexity of the various simulated phenomena. In this article, we introduce a software framework that is capable of simulating large-scale, biologically realistic networks of spiking neurons embodied in a biomechanically accurate musculoskeletal system that interacts with a physically realistic virtual environment. We deploy this framework on the high performance computing resources of the EBRAINS research infrastructure and we investigate the scaling performance by distributing computation across an increasing number of interconnected compute nodes. Our architecture is based on requested compute nodes as well as persistent virtual machines; this provides a high-performance simulation environment that is accessible to multi-domain users without expert knowledge, with a view to enable users to instantiate and control simulations at custom scale via a web-based graphical user interface. Our simulation environment, entirely open source, is based on the Neurorobotics Platform developed in the context of the Human Brain Project, and the NEST simulator. We characterize the capabilities of our parallelized architecture for large-scale embodied brain simulations through two benchmark experiments, by investigating the effects of scaling compute resources on performance defined in terms of experiment runtime, brain instantiation and simulation time. The first benchmark is based on a large-scale balanced network, while the second one is a multi-region embodied brain simulation consisting of more than a million neurons and a billion synapses. Both benchmarks clearly show how scaling compute resources improves the aforementioned performance metrics in a near-linear fashion. The second benchmark in particular is indicative of both the potential and limitations of a highly distributed simulation in terms of a trade-off between computation speed and resource cost. Our simulation architecture is being prepared to be accessible for everyone as an EBRAINS service, thereby offering a community-wide tool with a unique workflow that should provide momentum to the investigation of closed-loop embodiment within the computational neuroscience community.journal articl
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