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Performance of supercomputers has been steadily and exponentially increasing for the past 20 years, and is expected to increase further. This unprecedented computational power enables us to build and simulate large-scale neural network models composed of tens of billions of neurons and tens of trillions of synapses with detailed anatomical connections and realistic physiological parameters. Such “human-scale” brain simulation could be considered a milestone in computational neuroscience and even in general neuroscience. Towards this milestone, it is mandatory to introduce modern high-performance computing technology into neuroscience research. In this article, we provide an introductory landscape about large-scale brain simulation on supercomputers from the viewpoints of computational neuroscience and modern high-performance computing technology for specialists in experimental as well as computational neurosciences. This introduction to modeling and simulation methods is followed by a review of various representative large-scale simulation studies conducted to date. Then, we direct our attention to the cerebellum, with a review of more simulation studies specific to that region. Furthermore, we present recent simulation results of a human-scale cerebellar network model composed of 86 billion neurons on the Japanese flagship supercomputer K (now retired). Finally, we discuss the necessity and importance of human-scale brain simulation, and suggest future directions of such large-scale brain simulation research.

As friction couples tangential and lateral degrees-of-freedom of a structure at contact interfaces, the resulting asymmetric dynamic system is prone to dynamic instability. Using state-feedback control, such a frictional asymmetric system can be stabilized through assigning the system desirable eigenvalues; but uncertainties in system parameters can cause assigned eigenvalues to deviate from desired locations and thus stability may be lost. This study presents a robust stabilization method that assigns both desirable eigenvalues and their sensitivities and thus render assigned eigenvalues stable and insensitive to perturbations in uncertain contact parameters (the friction coefficient, contact damping, and contact stiffness). This method utilizes receptances of the corresponding symmetric part of the asymmetric system. The optimal control input location is first determined by minimizing the Frobenius norm of the normalized eigen-sensitivity matrix. The normalized eigen-sensitivities indicate that the friction coefficient and contact stiffness intrinsically have similar crucial effects on the stability of the system. To demonstrate the application of the proposed control method, the eigen-sensitivities with respect to only the friction coefficient are assigned. A constrained over-determined least-squares problem is solved to assign both required eigenvalues and eigen-sensitivities. Numerical examples validate the effectiveness of the proposed robust control scheme by Monte Carlo simulations.

During voluntary limb movements, humans exert anticipatory postural adjustments (APAs) to prevent any upcoming equilibrium disturbance that might be provoked by limb movements. Dysfunction in generation or control of APAs is associated with postural deficits in some human patients with cerebellar damage. To examine the role of the cerebellum in APAs, we investigated a conditional transgenic mouse of spinocerebellar ataxia type 3 (SCA3Tg) that has defective cerebellar Purkinje cells. Kinematic analyses and monitoring of electromyographic activities during quadrupedal standing showed that SCA3Tg mice exhibited greater hindlimb instability than wild-type (WT) mice. This instability increased during a reaching task that required postural adjustments associated with voluntary neck movements. Normally, the activities of the hindlimb muscles are synchronized with those in the neck that are the agonists for movement of the head in this reaching task; however, in SCA3Tg mice, activities in the hindlimbs were markedly delayed compared to the neck. These observations cannot simply be explained as a secondary outcome of the muscle atrophy that occurs in SCA3Tg mice. In WT mice with muscle atrophy induced by immobilization of the hindlimbs, we did not find impairment of APAs. These findings suggest that the deficits in APAs during the reaching task in SCA3Tg mice were not due to muscle atrophy in the hindlimbs, but were mainly caused by cerebellar degeneration. Therefore, we conclude that the cerebellum is critically involved in APAs.