Research Objectives

We will reveal 1) Nonlinear dynamics governing adaptation behaviour in living creatures, 2) Closed loop of brain and body (neural networks and sensory-motor systems), and 3) Mathematical structure underlying behaviour and neural networks. The significant investigation methods range over behavioural experiments, EEG measurement and analysis, robotic systems, mathematical modeling, and their combination.

Our aim is to reveal how the self-organization of the closed loop system gives rise to awareness or cognition in the interaction with changing environment, or with the other members in the society.

- Bioelectric Engineering

Functions of human such as memory, motor coordination, emotion ultimately relies on neuronal networks in brain. Information processing is embedded into spatial and temporal dynamics of the networks, i.e., how electric pulses propagate across a whole network. All of those amazing function originates from excitable nature of the individual neuronal cells, i.e., stimulated by the electric pulse, the cell itself can generate the electric pulse. In this study, we found elementally, for the first time, bacteria cells can respond electronically when applied electric shock. More surprisingly, healthy bacteria cells and affected cells by antibiotics and UV light showed completely different electric reactions.

Using the widely used mathematical model in Neuroscience, we revealed a common mechanism of excitable cells, neuron or bacteria cells, and the extended neuronal model could explain two distinct electric reactions of healthy and unhealthy bacteria cells. Surprisingly, a single parameter representing the degree of non-equilibrium across membrane was sufficient to explain these distinct responses of the cells.

Stratford, J. P., Edwards, C. L. A., Ghanshyam, M. J., Malyshev, D., Delise, M. A., Hayashi, Y. and Asally, M. (2019) Electrically induced bacterial membrane-potential dynamics correspond to cellular proliferation capacity. Proceedings of the National Academy of Sciences of the United States of America, 116 (19). pp. 9552-9557. ISSN 1091-6490 doi:

- Nonlinear Physics

Anticipating synchronization has been recently proposed as a mechanism of interaction in dy- namical systems which are able to bring about predictions of future states of a driver system. We suggest that an interesting insight into the anticipating synchronization can be obtained by the renormalization of the time scale in the driven system. Our approach directly links the feedback delay of the driven system with the renormalized time scale of the driven system, identifying the main component in the anticipating synchronization paradigm and suggesting an alternative method to generate the anticipating and the lagging synchronization.

Hayashi, Y., Nasuto, S. J. and Eberle, H. (2016) Renormalized time scale for anticipating and lagging synchronization. Physical Review E , 93 (5). 052229. ISSN 2470-0053 doi:

- Nonlinear Physics of living systems

DNA compaction can be caused by multivalent ions as condensing agents. Both discontinuous (all-or-none) and continuous (pearl-necklace structure) transitions have been observed in experiments as the concentration of the condensing agent was increased. We have investigated the DNA transition by analytical calculations in the infinite-chain limit. A mechanism for pearl-necklace structures could be a combinatorial entropy term, which favours a mixture of globules and coils in a single chain. However, when a surface term is taken into account, it gives rise to a discontinuous transition. We also consider the role of surface charges on the globule.

- Behaviour of micro-orgnisms

We investigate the behavior of a single-cell protozoan in a narrow tubular ring. This environment forces them to swim under a one-dimensional periodic boundary condition. Above a critical density, single-cell protozoa aggregate spontaneously without external stimulation. The high-density zone of swimming cells exhibits a characteristic collective dynamics including translation and boundary fluctuation. We analyzed the velocity distribution and turn rate of swimming cells and found that the regulation of the turing rate leads to a stable aggregation and that acceleration of velocity triggers instability of aggregation. These two opposing effects may help to explain the spontaneous dynamics of collective behavior. We also propose a stochastic model for the mechanism underlying the collective behavior of swimming cells.

- Behaviour of social insects

Revealing evolution of the well-organized social behavior requires understanding of the mechanism by which collective behavior is produced. We aim to link universal behavior in individual with the emerged collective behavior. To this end, the coupling of the internal dynamics via mutual interactions has been investigated, i.e., temporal pattern of interchangeable components in the pair condition was examined in contrast to that in the isolated condition.

We found; 1. A poisson process was discovered in durations of active and inactive states. 2. A transition probability from inactive to active state is affected by pair interactions. The fact that the transition probability is regulated by pair interactions leads to a control of the population of active and inactive workers.

- Behavioural Sciences

We performed mutual tapping experiments between two humans to investigate the conditions required for synchronized motion. A transition from an alternative mode to a synchronization mode was discovered under the same conditions as when a subject changed from a reactive mode to an anticipation mode in single tapping experiments. The experimental results suggest that the cycle time for each tapping motion is tuned by a proportional control that is based on synchronization errors and cycle time errors. As the tapping frequency increases, a mathematical model based on feedback control in the sensory-motor closed loop predicts a discrete transition of the mode as the gain factors of the proportional control decrease. The conditions for synchronization are shown as a consequence of the coupled dynamics based on the next feedback loop in the sensory-motor system.

- Brain Computer Interface

Our aim is to reconstruct the brain-body loop of stroke patients via an EEG-driven robotic system.

After the detection of motor command generation, the robotic arm should assist patient's movement at the correct moment and in a natural way. In this study we performed EEG measurements from healthy subjects performing discrete spontaneous motion. An EEG analysis based on the temporal correlation of the brain activity was employed to determine the onset of single motion motor command generation.

- Soft Robotics

We demonstrated the design, production, and functional properties of the Exoskeleton Actuated by the Soft Modules (EAsoftM). Integrating the 3D printed exoskeleton with passive joints to compensate gravity and with active joints to rotate the shoulder and elbow joints resulted in ultra-light system that could assist planar reaching motion by using the vision-based control law.

The EAsoftM can support the reaching motion with compliance realized by the soft materials and pneumatic actuation. In addition, the vision- based control law has been proposed for the precise control over the target reaching motion within the millimeter scale. Aiming at rehabilitation exercise for individuals, typically soft actuators have been developed for relatively small motions, such as grasping motion, and one of the challenges has been to extend their use for a wider range reaching motion. The proposed EAsoftM presented one possible solution for this challenge by transmitting the torque effectively along the anatomically aligned with a human body exoskeleton. The proposed integrated systems will be an ideal solution for neurorehabilitation where affordable, wearable, and portable systems are required to be customized for individuals with specific motor impairments.

Oguntosin, V. W., Mori, Y., Kim, H., Nasuto, S. J., Kawamura, S. and Hayashi, Y. (2017) Design and validation of exoskeleton actuated by soft modules towards neurorehabilitation - vision-based control for precise reaching motion of upper limb. Frontiers in Neuroscience, 11. 352. ISSN 1662-453X doi:

- Vision-based control for invariance of kinematics

A new dynamics-driven control law was developed for a robot arm, based on the feedback control law which uses the linear transformation directly from work space to joint space. This was validated using a simulation of a two-joint planar robot arm and an optimisation algorithm was used to nd the optimum matrix to generate straight trajectories of the end-e ector in the work space.

We found that this linear matrix can be decomposed into the rotation matrix representing the orientation of the goal direction and the joint relation matrix (MJRM) representing the joint response to errors in the Cartesian work space.

The decomposition of the linear matrix indicates the separation of path planning in terms of the direction of the reaching motion and the synergies of joint coordination. Once the MJRM is numerically obtained, the feedfoward planning of reaching direction allows us to provide asymptotically stable, linear trajectories in the entire work space through rotational transformation, completely avoiding the use of inverse kinematics. Our dynamics-driven control law suggests an interesting framework for interpreting human reaching motion control alternative to the dominant inverse method based explanations, avoiding expensive computation of the inverse kinematics and the point-to-point control along the desired trajectories.