Michiyo Suzuki

A model of motor control of the nematode C. elegans with neuronal circuits

OBJECTIVE Living organisms have mechanisms to adapt to various conditions of external environments. If we can realize these mechanisms on the computer, it may be possible to apply methods of biological and biomimetic adaptation to the engineering of artificial machines. This paper focuses on the nematode Caenorhabditis elegans (C. elegans), which has a relatively simple structure and is one of the most studied multicellular organisms. We aim to develop its computer model, artificial C. elegans, to analyze control mechanisms with respect to motion. Although C. elegans processes many kinds of external stimuli, we focused on gentle touch stimulation. METHODS The proposed model consists of a neuronal circuit model for motor control that responds to gentle touch stimuli and a kinematic model of the body for movement. All parameters included in the neuronal circuit model are adjusted by using the real-coded genetic algorithm. Also, the neuronal oscillator model is employed in the body model to generate the sinusoidal movement. The motion velocity of the body model is controlled by the neuronal circuit model so as to correspond to the touch stimuli that are received in sensory neurons. CONCLUSION The computer simulations confirmed that the proposed model is capable of realizing motor control similar to that of the actual organism qualitatively. By using the artificial organism it may be possible to clarify or predict some characteristics that cannot be measured in actual experiments. With the recent development of computer technology, such a computational analysis becomes a real possibility. The artificial C. elegans will contribute for studies in experimental biology in future, although it is still developing at present.

A Dynamic Body Model of the Nematode C. elegans with Neural Oscillators

The nematode Caenorhabditis elegans (C. elegans), a relatively simple organism in structure, is one of the most well-studied multicellular organisms. We developed a virtual C. elegans based on the actual organism to analyze motor control. We propose a dynamic body model, including muscles, controlled by a neural circuit model based on the actual nematode. The model uses neural oscillators to generate rhythmic movement. Computer simulation confirmed that the virtual C. elegans realizes motor control similar qualitatively to that of the actual organism. Specified classes of neurons are killed in the neural circuit model corresponding to actual unc mutants, demonstrating that resulting movement of the virtual C. elegans resembles that of actual mutants.

Modulatory effect of ionizing radiation on food-NaCl associative learning: the role of γ subunit of G protein in Caenorhabditis elegans

Ionizing radiation (IR) is known to impair learning by suppressing adult neurogenesis in the hippocampus. However, in a mature nervous system, IR‐induced functional alterations that are independent of neurogenesis remain largely unknown. In the present study, we analyzed the effects of IR on a food‐NaCl associative learning paradigm of adult Caenorhabditis elegans that does not undergo neurogenesis. We observed that a decrease in chemotaxis toward NaCl occurs only after combined starvation and exposure to NaCl. Exposure to IR induced an additional decrease in chemotaxis immediately after an acute dose in the transition stage of the food‐NaCl associative learning. Strikingly, chronic irradiation induced negative chemo‐taxis in the exposed animals, i.e., the primary avoidance response. IR‐induced additional decreases in chemo‐taxis after acute and chronic irradiation were significantly suppressed in the gpc‐1 mutant, which was defective in GPC‐1 (one of the two y subunits of the heterotrimeric G‐protein). Chemotaxis to cAMP, but not to lysine and benzaldehyde, was influenced by IR during the food‐NaCl associative learning. Our novel findings suggest that IR behaves as a modulator in the food‐NaCl associative learning via C. elegans GPC‐1 and a specific neuronal network and may shed light on the modulatory effect of IR on learning.—Sakashita, T., Hamada, N., Ikeda, D. D., Yanase, S., Suzuki, M., Ishii, N., Kobayashi, Y. Modulatory effect of ionizing radiation on food‐NaCl associative learning: the role of γ subunit of G protein in Caenorhabditis elegans. FASEB J. 22, 713–720 (2008)

A dynamic body model of the nematode C. elegans with a touch-response circuit

The nematode Caenorhabditis elegans (C elegans), a relatively simple organism in structure, is one of the most well-studied multicellular organisms. In this study, we develop a virtual C. elegans based on the actual nematode to analyze motor control which uses neuronal circuits and muscles. Although C. elegans processes many kinds of external stimuli, we focus on gentle touch stimulation. Virtual C. elegans consists of both a neuronal circuit model for touch-response and a dynamic body model, and is capable of reproducing a series of information processing from stimulation reception to generation of movement. The effectiveness of our model is discussed through simulation results

A Motor Control Model of the Nematode C. e1egaans

This paper focuses on the nematode C. elegans which has a relatively simple structure, and is one of the most analyzed organisms among multicellular ones. We aim to develop a mathematical model of this organism to analyze control mechanisms with respect to locomotion. First, a new motor control model of the C. elegans is proposed, which includes both of the neuronal circuit model and the dynamic model of the body. Then, the effectiveness of the proposed model is verified through a series of computer simulations

Theoretical and evolutionary parameter tuning of neural oscillators with a double-chain structure for generating rhythmic signals

A neural oscillator with a double-chain structure is one of the central pattern generator models used to simulate and understand rhythmic movements in living organisms. However, it is difficult to reproduce desired rhythmic signals by tuning an enormous number of parameters of neural oscillators. In this study, we propose an automatic tuning method consisting of two parts. The first involves tuning rules for both the time constants and the amplitude of the oscillatory outputs based on theoretical analyses of the relationship between parameters and outputs of the neural oscillators. The second involves an evolutionary tuning method with a two-step genetic algorithm (GA), consisting of a global GA and a local GA, for tuning parameters such as neural connection weights that have no exact tuning rule. Using numerical experiments, we confirmed that the proposed tuning method could successfully tune all parameters and generate sinusoidal waves. The tuning performance of the proposed method was less affected by factors such as the number of excitatory oscillators or the desired outputs. Furthermore, the proposed method was applied to the parameter-tuning problem of some types of artificial and biological wave reproduction and yielded optimal parameter values that generated complex rhythmic signals in Caenorhabditis elegans without trial and error.

Biomimetic control based on a model of chemotaxis in escherichia coli

In the field of molecular biology, extending now to the more comprehensive area of systems biology, the development of computer models for synthetic cell simulation has accelerated extensively and has begun to be used for various purposes, such as biochemical analysis. These models, describing the highly efficient environmental searching mechanisms and adaptability of living organisms, can be used as machine-control algorithms in the field of systems engineering. To realize this biomimetic intelligent control, we require a stripped-down model that expresses a series of information-processing tasks from stimulation input to movement. Here we selected the bacterium Escherichia coli as a target organism because it has a relatively simple molecular and organizational structure, which can be characterized using biochemical and genetic analyses. We particularly focused on a motility response known as chemotaxis and developed a computer model that includes not only intracellular information processing but also motor control. After confirming the effectiveness and validity of the proposed model by a series of computer simulations, we applied it to a mobile robot control problem. This is probably the first study showing that a bacterial model can be used as an autonomous control algorithm. Our results suggest that many excellent models proposed thus far for biochemical purposes can be applied to problems in other fields.

In vivo 3D analysis of systemic effects after local heavy-ion beam irradiation in an animal model

Radiotherapy is widely used in cancer treatment. In addition to inducing effects in the irradiated area, irradiation may induce effects on tissues close to and distant from the irradiated area. Japanese medaka, Oryzias latipes, is a small teleost fish and a model organism for evaluating the environmental effects of radiation. In this study, we applied low-energy carbon-ion (26.7 MeV/u) irradiation to adult medaka to a depth of approximately 2.2 mm from the body surface using an irradiation system at the National Institutes for Quantum and Radiological Science and Technology. We histologically evaluated the systemic alterations induced by irradiation using serial sections of the whole body, and conducted a heart rate analysis. Tissues from the irradiated side showed signs of serious injury that corresponded with the radiation dose. A 3D reconstruction analysis of the kidney sections showed reductions in the kidney volume and blood cell mass along the irradiated area, reflecting the precise localization of the injuries caused by carbon-beam irradiation. Capillary aneurysms were observed in the gill in both ventrally and dorsally irradiated fish, suggesting systemic irradiation effects. The present study provides an in vivo model for further investigation of the effects of irradiation beyond the locally irradiated area.

A mathematical model of radiation-induced responses in a cellular population including cell-to-cell communications

Cell-to-cell communication is an important factor for understanding the mechanisms of radiation-induced responses such as bystander effects. In this study, a new mathematical model of intercellular signalling between individual cells in a cellular population is proposed. The authors considered two types of transmission of signals: via culture medium and via gap junction. They focus on the effects that radiation and intercellular signalling have on cell-cycle modification. The cell cycle is represented as a virtual clock that includes several checkpoint pathways within a cyclic process. They also develop a grid model and set up diffusion equations to model the propagation of signals to and from spatially located cells. The authors have also considered the role that DNA damage plays in the cycle of cells which can progress through the cell cycle or stop at the G1, S, G2 or M-phase checkpoints. Results of testing show that the proposed model can simulate intercellular signalling and cell-cycle progression in individual cells during and after irradiation.

A novel tuning method for neural oscillators with a ladder-like structure based on oscillation analysis

Neural oscillators with a ladder-like structure is one of the central pattern generator (CPG) model that is used to simulate rhythmic movements in living organisms. However, it is not easy to realize rhythmical cycles by tuning many parameters of neural oscillators. In this study, we propose an automatic tuning method. We derive the tuning rules for both the time constants and the coefficients of amplitude by linearizing the nonlinear equations of the neural oscillators. Other parameters such as neural connection weights are tuned using a genetic algorithm (GA). Through numerical experiments, we confirmed that the proposed tuning method can successfully tune all parameters.