Emerging of the physiome project provides various influences on the medical, biological and pharmaceutical development. In this paper, as an example of physiome research, neural network model analysis providing the conduction mechanisms of pain and tactile sensations was presented, and the functional relations between neural activities of the network cells and stimulus intensity applied on the peripheral receptive fields were described. The modeling presented here is based on the various assumptions made by the results of physiological and anatomical studies reported in the literature. The functional activities of spinothalamic and thalamocortical cells show a good agreement with the physiological and psychophysical functions of somatosensory system that are very instructive for covering the gap between physiologically and psychophysically aspects of pain and tactile sensation.

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Physiome inherently investigates hierarchical layers of biological system. In the post genome era, the number of layers should increase because possible mechanisms at molecular level are always referred to. However, biological modeling in the post genome era has to face unavoidable uncertainties in biological measurements and explosion of degree of freedom. An exhaustive modeling seems to be necessary to understand possible mechanisms underlying biological phenomena at every hierarchical level. However, simultaneously it looks like an impossible or reckless trial. In order to get rid of them, we propose a novel modeling strategy that integrates the top-down retrospection and bottom-up reduction modeling. Here, our strategy is applied to modeling of biological rhythms which is an appropriate system to study because of the penetration of rhythmic dynamics through all of the hierarchical layers.

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The integration of knowledge from many disciplines and vast amount of biological data in the post-genome era together with mathematical and information sciences is moving the world towards a new generation of life science where physiological and pathological information from the living human body can be quantitatively described in silico across multiple scales of time and size and through diverse hierarchies of organization. The Physiome Project represents such emerging sciences. The challenge is to understand and quantitatively integrate not only structure and function of biological entities such as ion channel proteins and enzymes on a single spatio-temporal scale, but also functional relationships between entities across multiple scales. This integrative approach is in stark contrast to the linear approach of reductionist life science, and it will allow us to understand the mechanisms underlying biological functions that will emerge through the dynamics of each element and large aggregations of the elements. This article discusses several points of the challenge that are expected to be resolved through the Physiome Project.

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We investigated the sensitivity of ATP detection based on bioluminescence at an optical fiber end where luciferase molecules were immobilized via silica-binding protein molecules. Luminescence was detected by an avalanche photo diode (APD), with coupling optics to make full use of the merit of compactness, high quantum efficiency and low noise of the APD. The core diameter and the numerical aperture of the optical fiber, as well as the design of the coupling optics, were optimized so as to realize high photon-collection efficiency. A detection limit of about 10^-10 M was obtained, which corresponds to 10^-15 mol of ATP. A rough estimation shows that the photon count rate is still two orders of magnitude lower than that limited by diffusion or reaction processes, implying a possibility of further improvement of the sensitivity.

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This paper describes a technique for controlling the shape of filamentous motor proteins for bio-nano driving units in MEMS devices. In this experiment, we have used actin, a protein to construct cytoskeleton. Actin monomers (G-actin) polymerize in high salt condition and form filaments (F-actin); the filaments move when they bind with the motor protein (myosin) in ATP (adenosine tri-phosphate) solution. Fascin, a putative bundling protein, tightly bundles several F-actins together to form tight bundles of actin and polymerized in the polydimethylsiloxane (PDMS) or parylene micro chambers, and then formed several shapes, such as circles, rods, triangles or squares. Since the bundled actins still have motility, we believe this technique is useful for forming a desired pattern of bio-molecular motors toward the actuation of MEMS/NEMS devices.

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Microarray chip technology such as DNA chips, peptide chips and protein chips is one of the promising approaches for achieving high-throughput screening (HTS) of biomolecule function since it has great advantages in feasibility of automated information processing due to one-to-one indexing between array position and molecular function as well as massively parallel sample analysis as a benefit of down-sizing and large-scale integration. Mostly, however, the function that can be evaluated by such microarray chips is limited to affinity of target molecules. In this paper, we propose a new HTS system of enzymatic activity based on microreactor array chip technology. A prototype of the automated and massively parallel measurement system for fluorometric assay of enzymatic reactions was developed by the combination of microreactor array chips and a highly-sensitive fluorescence microscope. Design strategy of microreactor array chips and an optical measurement platform for the high-throughput enzyme assay are discussed.

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We aimed to study the validity of a new analytical approach that reflected the phase from platelet activation to the formation of small platelet aggregates. We hoped that this new approach would enable us to use the particle-counting method with laser-light scattering to measure platelet aggregation in healthy controls and in diabetic patients without complications. We measured agonist-induced platelet aggregation for 10 min. Agonist was added to the platelet-rich plasma 1 min after measurement started. We compared the total scattered light intensity from small aggregates over a 10-min period (established analytical approach) and that over a 2-min period from 1 to 3 min after measurement started (new analytical approach). Consequently platelet aggregation in diabetics with HbA_1c ≥ 6.5% was significantly greater than in healthy controls by both analytical approaches. However, platelet aggregation in diabetics with HbA_1c < 6.5%, i.e. patients in the early stages of diabetes, was significantly greater than in healthy controls only by the new analytical approach, not by the established analytical approach. These results suggest that platelet aggregation as detected by the particle-counting method using laser-light scattering could be applied in clinical examinations by our new analytical approach.

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As photochemical reaction (PR) is used in photodynamic therapy (PDT), high reactive oxygen speacies (ROS) concentration often induces cell and tissue injury. In this study, we focused on the mechanism of endothelial cell injury caused by PR. Human umbilical vein endothelial cells (HUVEC) were incubated with delta-aminolevulinic acid and were irradiated by LED light in 630 nm wavelength for 10 min. In vitro cell viability by MTT ssay did not change after PR, while in 3D-cultures of HUVEC in collagen that induces tube formation, PDT reduced the capillary-like structures and increase in endothelial permeability. ROS by PR leaded to shrinkage of endothelial cells, suppressed increase in subendothelial area after PR. Furthermore, F-actin was formed into stress fibers. These results suggest that oxidative stress by PDT strongly affects on endothelial permeability and morphological change of endothelial cells in which generation of stress fibers.

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A multi-photonic imaging system was proposed for measuring blood flow velocity, vessel diameter and blood oxygen tension pO₂ simultaneously with high spatio-temporal resolution in the parenchymatous organ microcirculation, such as pial tissue, by using a closed cranial window and two light sources. FITC-stained erythrocytes was used to visualize the microcirculation, and the fluorescent image was recorded by a high-speed video camera for measuring blood flow velocity. Oxygen tension pO₂ was measured by oxygen-dependent quenching of phosphorescent molecules, Pd-TCPP, in the microvessels after irradiation of second harmonic light of Nd:YAG pulse laser (532nm). Animal experiments were performed for investigation of blood flow dynamics and oxygen diffusion phenomenon during acute cerebral ischemia using photochemical thrombus formation in the closed cranial window of male Wistar rats. Experimental results showed specific and significant blood flow and oxygen diffusion phenomena related to the abnormal organ tissues, from those the proposed technique would contribute to the trasnlational research for the clinical medicine, concerned in the ischemic dysfunction, angiogenisis, tumorgenisis and so on.

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A less-invasive recording technique capable of simultaneously monitoring the activity of significant number (10³ ∼ 10⁴) of neurons is a vital step in developing an effective brain-machine interface. Although there are many excellent techniques for recording activities of a single neuron or a group of neurons, there is no methodology for accessing large number of cells in a behaving experimental animal or human individual. Brain vascular parenchyma offers the promising candidate to solve this problem. We have proposed the use of myriad of nano-wire-electrodes that are introduced into the Central Nervous System through the vascular system to address any brain area. In this study we design a microcatheter for ex vivo experiments. Using a Wollaston platinum wire we design a submicron-scale electrode, and develop the fabrication method. We then evaluate the mechanical property of the electrode to flow into the intricacies of the capillary bed in ex vivo Xenopus laevis. Furthermore, we demonstrate the feasibility of intravascular recording in the spinal cord of Xenopus laevis.

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Neural interface devices that will allow signals from the human nervous system to control external equipment are extremely important for the next generation of prosthetic systems. A novel multichannel regeneration-type nerve electrode designed to record from and stimulate peripheral nerves has been developed to allow the control of artificial hands and to generate artificial sensations. In this study a novel flexible regeneration microelectrode based on the nerve regeneration principle was designed and fabricated using MEMS technologies. The electrode, which was fabricated on a 25-μm-thick Parylene C substrate, has multiple fluidic channels. Each fluidic channel was 100 μm wide × 30 μm high × 1500 μm long and featured multiple electrodes inside them as recording and stimulating sites. They also served as guidance channels for the regenerating axons.

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This paper proposes a penetration-type tungsten microelectrode array on a flexible silicone rubber substrate for neural recording from a desired cortical layer. Our evaluation experiments confirmed that the flexible substrate keeps the penetration depth of each electrode constant and allows simultaneous multipoint recording of spike potentials from a desired neocortical layer. Penetration of the stiff and flexible arrays into agarose, which has the curvature comparable to that of the rat brain, revealed that the electrodes at the edge of the stiff array had up to 150 μm error in its penetration depth, while the penetration depth of the flexible array was approximately constant across the electrodes (ANOVA, p=0.835). Electrophysiological experiments in the rat auditory cortex demonstrated that the simultaneous multipoint recording of the acoustically evoked spike potentials was feasible with the flexible array. A series of penetration trials and characteristic frequency estimations successfully identified the primary auditory cortex by assuring a gradual increase in the characteristic frequencies from caudal to rostral. This result suggests that the proposed electrode is suitable for acute experiments requiring repeated penetration and precision positioning of penetration sites.

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There have recently been many studies concerning the control of robot movements using neural signals recorded from the brain (usually called the Brain-Machine interface (BMI)). We fabricated implantable multi-electrode arrays to obtain neural signals from the rat cerebral cortex. As any multi-electrode array should have electrode alignment that minimizes invasion, it is necessary to customize the recording site. We designed three types of 22-channel multi-electrode arrays, i.e., 1) wide, 2) three-layered, and 3) separate. The first extensively covers the cerebral cortex. The second has a length of 2 mm, which can cover the area of the primary motor cortex. The third array has a separate structure, which corresponds to the position of the forelimb and hindlimb areas of the primary motor cortex. These arrays were implanted into the cerebral cortex of a rat. We estimated the walking speed from neural signals using our fabricated three-layered array to investigate its feasibility for BMI research. The neural signal of the rat and its walking speed were simultaneously recorded. The results revealed that evaluation using either the anterior electrode group or posterior group provided accurate estimates. However, two electrode groups around the center yielded poor estimates although it was possible to record neural signals.

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In order to precisely grasp the self-organization process of functional neuronal circuits from individual immature neurons, electrical activity of neuronal circuits should be continuously recorded with their well-defined inner structures and boundary conditions. Standing on this viewpoint, we have developed a series of practical experimental methods for the non-invasive recording of electrical activity from cultured small neuronal circuits by combining a simple micropatterning method of cultured neurons and a site-selective extracellular recording method. The micropatterning was demonstrated with a commercially available spray, and thousands of small neuronal circuits were formed in a 35-mm polystyrene dish by spraying PDL (poly-D-lysine) solution onto the BSA (bovine serum albumin)-coated culture surface. These small neuronal circuits consisted of several neurons and kept well-patterned for more than two weeks. The site-selective recording was demonstrated by means of a handmade mobile microelectrode, and spontaneous firings were detected at multiple recording sites in a small neuronal circuit. This series of experimental methods can be directly applicable to the investigation into the developmental process of the morphology and the functions of various electrically excitable multicellular organisms.

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Formation of simple neuronal networks in vitro is one of the promising methods to study biological information processing. Agarose microchambers have several advantages to form and maintain simple network structures. Here, in this work, a novel method for fabricating microwells in an agarose-layer is reported. Chaotropic effects of sodium iodide (NaI) is applied for etching agarose films. A conventional glass micropipette filled with NaI solution was aligned and a small amount of NaI was ejected to surface of the film. The agarose was denatured by the soaked NaI. The denatured agarose was washed out by distilled water. The size of the well was determined by the quantity of ejected NaI solution and its diffusion time. Conditions for fabricating wells of 100 to 600 μm diameters were established. Multiple wells up to 100 were formed on a single surface sequentially by programmed movement of the microscope stage. Rat hippocampal neurons were successfully cultured in the wells. Combining this method with microelectrode-array substrates will enable us of recording neuronal activity from simple neuronal networks as well as co-culture systems of heterogeneous tissues.

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This paper describes a new type of MCA (Micro Channel Array) for simultaneous multipoint measurement of cellular network. Presented MCA employing the measurement principles of the patch-clamp technique is designed for advanced neural network analysis which has been studied by co-authors using 64ch MEA (Micro Electrode Arrays) system. First of all, sucking and clamping of cells through channels of developed MCA is expected to improve electrophysiological signal detections. Electrophysiological sensing electrodes integrated around individual channels of MCA by using MEMS (Micro Electro Mechanical System) technologies are electrically isolated for simultaneous multipoint measurement. In this study, we tested the developed MCA using the non-cultured rat's cerebral cortical slice and the hippocampal neurons. We could measure the spontaneous action potential of the slice simultaneously at multiple points and culture the neurons on developed MCA. Herein, we describe the experimental results together with the design and fabrication of the electrophysiological MEMS device with MCA for cellular network analysis.

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Conventional microelectrode arrays (MEAs) cannot always access desired neurons due to low electrode density and small electrode number. To overcome this problem, we have proposed and developed a light-addressable planar electrode on a glass substrate. The electrode has a 3-layer structure, namely a transparent SnO₂ layer, an hydrogenated amorphous silicon (a-Si:H) layer, and a low-conductive passivation layer. Illumination to the a-Si:H layer increases the conductivity of a-Si:H and generates a virtual electrode at the surface of the illuminated site. In the present study, we evaluated the photoelectric property of the developed electrode and estimated the spatial resolution of the light-addressed stimulation. Illumination to the electrode increased stimulus intensity by up to 60-folds. This illumination-induced intensity change sufficiently followed high-frequency illumination switching. The simultaneous fluo-4 Ca²⁺-imaging, thus, successfully monitored post-stimulus fluorescence transients by instantaneously shutting out the excitation light during stimulus pulse application. By monitoring stimulus induced responses of cell aggregations, we estimated the spatial resolution of the light-addressed stimulation at 10 μm or more with an addressing illumination spot of 70 μm in diameter.

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A CMOS LSI-based neural stimulator was developed for retinal prosthesis. The stimulator was designed with “multi-chip” architecture. Small LSI neural stimulators named “Unit Chip” were assembled on a flexible substrate into a flexible, multi-site retinal stimulator. An experimental system equipped with the fabricated LSI-based flexible stimulator was configured and current injection functionality was demonstrated in saline solution. Materials for improved charge injection were also discussed.

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To develop a retinal prosthesis for blind patients using an implanted multielectrode array, it is important to study the response properties of retinal ganglion cells and of the visual cortex to localized retinal electrical stimulation.
Optical imaging can reveal the spatio-temporal properties of neuronal activity. Therefore, we conducted a calcium imaging study to investigate response properties to local current stimulation in frog retinas, and a membrane potential imaging study to explore the visual cortical responses to retinal stimulation in guinea pigs.
In the retina, local current stimuli evoked transient responses in the ganglion cells located near the stimulus electrode. The spatial pattern of the responding area was altered by changing the location of the stimulation.
Local electrical stimulation to the retina also caused transient responses in the visual cortex. The responding cortical areas in the primary visual cortex were localized. A spatially different cortical response was observed to stimulation of a different position on the retina.
These results suggest that the imaging study has great potential in revealing the spatio-temporal properties of the neuronal response for the retinal prosthesis.

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The neuromorphic device, which implements the functions of biological neural circuits by means of VLSI technology, has been collecting much attention in the engineering fields in the last decade. Concurrently, progress in neuroscience research has revealed the nonlinear computation in single neuron levels, suggesting that individual neurons are not merely the circuit elements but computational units. Thus, elucidating the properties of neuronal signal processing is thought to be an essential step for developing the next generation of neuromorphic devices. In the present study, we developed a method for dissociating single neurons from specific sublayers of mammalian retinas with using no proteolytic enzymes but rather combining tissue incubation in a low-Ca²⁺ medium and the vibro-dissociation technique developed for the slices of brains and spinal cords previously. Our method took shorter time of the procedure, and required less elaborated skill, than the conventional enzymatic method did; nevertheless it yielded enough number of the cells available for acute electrophysiological experiments. The isolated retinal neurons were useful for measuring the nonlinear membrane conductances as well as the spike firing properties under the perforated-patch whole-cell configuration. These neurons also enabled us to examine the effects of proteolytic enzymes on the membrane excitability in those cells.

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Activity-dependent plasticity probably plays a key role in learning and memory in biological information processing systems. Though long-term potentiation and depression have been extensively studied in the filed of neuroscience, little is known on the mechanisms for integrating these modifications on network-wide activity changes. In this report, we studied effects of spatio-temporally correlated stimuli on the neuronal network activity. Rat cortical neurons were cultured on substrates with 64 embedded micro-electrodes and the evoked responses were extracellularly recorded and analyzed. We compared spatio-temporal patterns of the responses between before and after repetitive application of correlated stimuli. After the correlated stimuli, the networks showed significantly different responses from those in the initial states. The modified activity reflected structures of the repeatedly applied correlated stimuli. The results suggested that spatiotemporally correlated inputs systematically induced modification of synaptic strengths in neuronal networks, which could serve as an underlying mechanism of associative memory.

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Intrinsic plastic properties in the auditory cortex can cause dynamic remodeling of the functional organization according to trainings. Neurorehabilitation will therefore potentially benefit from electrical stimulation that can modify synaptic strength as desired. Here we show that the auditory cortex of rats can be modified by intracortical microstimulation (ICMS) associated with tone stimuli on the basis of the spike time-dependent plasticity (STDP). Two kinds of ICMS were applied; a pairing ICMS following a tone-induced excitatory synaptic input and an anti-paring ICMS preceding a tone-induced input. The pairing and anti-pairing ICMS produced potentiation and depression, respectively, in responses to the paired tones with a particular test frequency, and thereby modified the tuning property of the auditory cortical neurons. In addition, we demonstrated that our experimental setup has a potential to directly measure how anesthetic agents and pharmacological manipulation affect ICMS-induced plasticity, and thus will serve as a powerful platform to investigate the neural basis of the plasticity.

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The artificial neural network (ANN) can reconstruct spatio-temporal neural activities into the corresponding test stimuli. ANN with a simple structure and generalization ability has a potential to reflect a prominent feature of the mechanism of neural computation in the brain. In the present work, we test this hypothesis and propose a novel analysis by investigating input-output relationships of hidden layer neurons. We made ANN with neural activities in the primary auditory cortex serving as the inputs and time-series changes of test frequencies of tones serving as the targets. We then investigated the hidden layer neurons that played important roles in the reconstruction. Neurons that tuned the frequency preference by excitatory inputs had positive contribution from all frequency regions. On the other hand, neurons responsible for inhibitory frequency tuning had negative contribution from a low frequency region. These results suggest that neural activities in the primary auditory cortex form a frequency preference with excitatory inputs from all frequency pathways and inhibitory inputs from a low frequency pathway. This suggestion is consistent with physiological facts that pyramidal cells in the auditory cortex have widely tuned excitatory response area and inhibitory input domains that flank the excitatory areas, supporting our hypothesis and proving the feasibility of the proposed analysis.

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A multiple independent component analysis (ICA) method based on the noisy time-delayed decorrelation algorithm is described that overcomes the problems and improves the usefulness of conventional ICA, which is commonly used for extracting the actual neural activity from data measured using optical recording with a voltage-sensitive dye to visualize neural activities in cortical areas as two-dimensional images. The problems with conventional ICA extraction include the lack of an a priori guarantee that the solution will be appropriate, the linear mixing of mutually independent random variables although the mixtures are not random variables but time signals in many applications, and the general requirement for repetitive calculation of large matrices. Application of multiple ICA to the extraction of neural activities in the guinea pig auditory cortex evoked by both click sounds and pure tones from optical recordings made using a voltage sensitive dye demonstrated that it effectively removes pulsatile and respiratory components from the measurement data and extracts neural activities from the optical recordings.

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It is known that the posterior parietal cortex (PPC) plays a dominant role in spatial processing during visual search. However, the temporal aspect of the PPC is unclear. In the present study, to investigate the temporal aspects of the PPC in feature search, we applied Transcranial Magnetic Stimulation (TMS) over the right PPC with the TMS stimulus onset asynchronies (SOAs) set at 100, 150, 200 and 250 ms after visual search stimulation. We found that when SOA was set at 150 ms, compared to the sham TMS condition, there was a significant elevation in response time when TMS pulses were applied. However, there was no significant difference between the TMS and sham TMS conditions for the other SOA settings. Therefore, we suggest that the spatial processing of feature search is probably processed in the posterior parietal cortex at about 150-170 ms after visual search stimuli presentation.

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Neural prostheses for restoring lost functions can benefit from selective activation of nerves. We had previously proposed a multiple gating stimulation, which can selectively activate a desired portion of nerve bundle, irrespective of a density of the electrode. In this paper, we discuss the design of electrode array and effective strategies to determine the stimulus parameters. A large electrode was less affected by the relative location of electrodes and the node of Ranvier, suggesting that a rectangular electrode, whose long side along a nerve bundle is longer than the internodal distance, i.e., on the order of 1 mm, would be more effective rather than a disk electrode. We could estimate an appropriate current at each electrode was a blocking threshold. For the lateral gating stimulation, the gate current should be set above the threshold, while, for depth-wise gating stimulation, the gate current should be set below the threshold. The spatial resolution of lateral gating stimulation is theoretically estimated at least at 50 μm when the grid of array was 1.2 mm, and that of depth-wise gating stimulation at 50 μm.

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The rise of the threshold of electric current stimulation to generate compound action potential of nerve conduction study is considered to have a relationship to malfunctions of the nerve. The effect of the decrease of the resistivity of the external tissue and the thickness of myelin sheaths was investigated by computer simulation. A myelinated human nerve fiber dipped in the homogeneous conductor was stimulated with a monopolar cathode located outside the axon. As a result, the rise of the threshold by demyelination was comparable to the effect of the decrease of the resistivity of the external tissue by a few Ωm when the external resistivity is about 10 Ωm. Actually the reduction of the thickness of the myelin sheaths also reduces the resistivity of the external tissue. Therefore the contribution of both effects in case of demyelination was estimated. As a result, the contributions of each effect were antagonized. As one of the causes of the rise of the threshold of nerve activation, the decrease of the resistivity of the external tissue is considerable.

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In past studies on the neural transfer function, some researchers have taken both excitation and inhibition factors into consideration. However, these past models were based on the diffusion of substances between neighboring cells. Therefore, they are not suitable for considering excitation and inhibition factors in individual cells. In the present study, based on the physiological characteristics of synaptic transmission, we propose a new model in which facilitation and fatigue can be both considered in individual cells. Using the proposed model, the simulations of short-term memory, afterimage effect, motion aftereffect, Game of Life, and image feature detections were performed. We suggest that the proposed model is a valid and widely applicable neural model.

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The present study introduces an approach to detect and classify extracellularly recorded action potentials of neurons, usually termed as spike sorting. Our approach is based on template matching, which is an optimal filter under Gaussian noise; however, this approach is usually expensive in computational time.
To speed up the filter, it is important to curtail the matching process when the distance between template and waveform exceeds some threshold. We approach this aspect of the problem using the frame of similarity detection algorithms (SSDA) and Davies-Bouldin validation indices (DBVI). Windowing pair of the filter was selected in DBVI based order and a signal which has rapidly increasing error was discarded to reduce the computational time. DBVI is a function of the ratio of the sum of within-cluster scatter to between-cluster separation, thus using this order we can expect to separate a signal and a noise in fewer window point calculation than full point matching. This matching process performed well, with a shorter computational time and fewer incorrect classifications than other ordering methods such as time based or amplitude based order.

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We are developing a brain-machine interface (BMI) called “RatCar," a small vehicle controlled by the neural signals of a rat's brain. An unconfined adult rat with a set of bundled neural electrodes in the brain rides on the vehicle. Each bundle consists of four tungsten wires isolated with parylene polymer. These bundles were implanted in the primary motor and premotor cortices in both hemispheres of the brain. In this paper, methods and results for estimating locomotion speed and directional changes are described. Neural signals were recorded as the rat moved in a straight line and as it changed direction in a curve. Spike-like waveforms were then detected and classified into several clusters to calculate a firing rate for each neuron. The actual locomotion velocity and directional changes of the rat were recorded concurrently. Finally, the locomotion states were correlated with the neural firing rates using a simple linear model. As a result, the abstract estimation of the locomotion velocity and directional changes were achieved.

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We have analyzed time series data of sound on interactive calling behavior of two male Japanese tree frogs (Hyla japonica; Nihon-Ama-Gaeru). First, we have extracted two time series data mainly corresponding to respective frogs from the single time series data of calls of two frogs by the free and cross-platform sound editor Audacity. Then, we have quantitatively analyzed timing and inter-call intervals of respective frogs. Finally, we have characterized nonstationarily temporal change of the interactive calling behavior of two frogs by analysis of the cross recurrence plot. The results have shown that a pair of male frogs called in almost anti-phase synchronization after a short-term period of nearly in-phase synchronization, which implies existence of complex interactive calling behavior of two male frogs.

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We proposed a novel retinal model capable of simulating Mach-effect, which is known as an optical illusion emphasizing edges of an object. The model was constructed by a rod cell layer, a bipolar cell layer, and a ganglion cell layer. Lateral inhibition and perceptive field networks were introduced between the layers, respectively. Photoelectric conversion for a single photon incidence at each rod cell was defined as an equation, and the input to the model was simulated as a distribution of transmitted photons through the input image for consecutive incidences by Monte Carlo method. Since this model successfully simulated not only Mach-effect illusion, but also DOG-like (Difference of Gaussian like) profile for a spot light incidence, the model was considered to form functionally the perceptive field of the retinal ganglion cell.

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Modeling and simulation based on mechanisms is important in order to design and control mechatronic systems. In particular, in-depth understanding and realistic modeling of biological systems is indispensable for biomechatronics. This paper presents open brain simulator, which estimates the neural state of human through external measurement for the purpose of improving motor and social skills. Macroscopic anatomical nervous systems model was built which can be connected to the musculoskeletal model. Microscopic anatomical and physiological neural models were interfaced to the macroscopic model. Neural activities of somatosensory area and Purkinje cell were calculated from motion capture data. The simulator provides technical infrastructure for human biomechatronics, which is promising for the novel diagnosis of neurological disorders and their treatments through medication and movement therapy, and for motor learning support system supporting acquisition of motor skill considering neural mechanism.

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Various clustering methods are applied to characterizing gene expression data from DNA microarrays. However, to elucidate functional dependencies of genes analysis of their associations is important. The REVerse Engineering ALgorithm (REVEAL) was developed for analyzing the functional dependencies. Although the algorithm has been tested using binary models of genetic networks, it remains unclear how the method or similar technology will operate with systems of continuous variables. In this study, first, the REVEAL was examined using noisy, continuous data and the results suggested that its application to such data required considerable refinement of the algorithm. Then a new implementation method of REVEAL was proposed. This implementation method was tested through numerical experiments. The results of the simulations demonstrated the potential of the proposed method for extracting gene associations.

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Understanding the shape of an organ is important because it is representative of the condition of an organ in case of diseases affecting it. The intensity and the phase distribution in MRI image are influenced by the system and the object. The influences in the distribution could be changed by the type of the organ. In this paper, we discuss a method that was developed to evaluate the shape of organs in MR images based on the anisotropy in the intensity or phase distribution. First, the entire intensity range or the phase is divided into intervals. The bounding rectangle for the particle, comprising neighboring points in each divided range, is used to recognize the object based on the elongation direction of the rectangle. This method can be applied to images obtained by phase-contrast, gradient-echo, and spin-echo methods. All the results demonstrate the efficiency of this method in recognizing the outline of the object. Moreover, the distribution anisotropy in the object differed from that in its outside. The result would make the method better.

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The purpose is to remove the speckle noise and to emphasize the boundary of a tumor by filtering based on the intensity difference in the medical ultrasound images. The proposed method is evaluated using numerical phantom simulating ultrasound B-mode images, and the effect is confirmed by applying to medical ultrasound images. Therefore, some important features such as tissue boundaries and small tumors may be overlooked. A CNN (cellular neural networks) for the speckle reduction and the edge enhancement are proposed in this paper. A CNN which is a kind of recurrent neural network can deal with images by the weight of neurons called a cell. It could be obtained more detail images recognition compared with the previous studies. A determination template parameters of the CNN for ultrasound image processing is discussed. The experimental results show effectiveness of applying the proposed method to boundary enhancement and the speckle reduction of medical ultrasound image.

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Accurate assessment of local myocardial contraction is important for diagnosis of ischemic heart disease, because decreases of myocardial motion often appear in the early stages of the disease. Three-dimensional (3-D) assessment of the stiffness distribution is required for accurate diagnosis of ischemic heart disease. Since myocardium motion occurs radially within the left ventricle wall and the ultrasound beam propagates axially, conventional approaches, such as tissue Doppler imaging and strain-rate imaging techniques, cannot provide us with enough quantitative information about local myocardial contraction. In order to resolve this problem, we propose a novel myocardial contraction imaging system which utilizes the weighted phase gradient method, the extended combined autocorrelation method, and the dynamic grid interpolation (DGI) method. From the simulation results, we conclude that the strain image's accuracy and contrast have been improved by the proposed method.

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3D reconstruction from ordinary X-ray equipment which is not CT or MRI is required in clinical veterinary medicine. Authors have already proposed a 3D reconstruction technique from X-ray photograph to present bone structure. Although the reconstruction is useful for veterinary medicine, the thechnique has two problems. One is about exposure of X-ray and the other is about data acquisition process. An x-ray equipment which is not special one but can solve the problems is X-ray fluoroscopy. Therefore, in this paper, we propose a method for 3D-reconstruction from X-ray fluoroscopy for clinical veterinary medicine. Fluoroscopy is usually used to observe a movement of organ or to identify a position of organ for surgery by weak X-ray intensity. Since fluoroscopy can output a observed result as movie, the previous two problems which are caused by use of X-ray photograph can be solved. However, a new problem arises due to weak X-ray intensity. Although fluoroscopy can present information of not only bone structure but soft tissues, the contrast is very low and it is very difficult to recognize some soft tissues. It is very useful to be able to observe not only bone structure but soft tissues clearly by ordinary X-ray equipment in the field of clinical veterinary medicine. To solve this problem, this paper proposes a new method to determine opacity in volume rendering process. The opacity is determined according to 3D differential coefficient of 3D reconstruction. This differential volume rendering can present a 3D structure image of multiple organs volumetrically and clearly for clinical veterinary medicine. This paper shows results of simulation and experimental investigation of small dog and evaluation by veterinarians.

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The skin is unique as an organ that is highly accessible to direct visual inspection with light. Visual inspection of cutaneous morphology is the mainstay of clinical dermatology, but relies heavily on subjective assessment by the skilled dermatologists. We present an imaging colorimeter of non-contact skin color measuring system and some experimented results using such instrument. The system is comprised by a video camera, light source, a real-time image processing board, magneto optics disk and personal computer which controls the entire system. The CIE-L*a*b* uniform color space is used. This system is used for monitoring of some clinical diagnosis. The instrument is non-contact, easy to operate, and has a high precision unlike the conventional colorimeters. This instrument is useful for clinical diagnoses, monitoring and evaluating the effectiveness of treatment.

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There is human error as a common factor of many traffic accidents. This study is aimed at evaluate from a nasal skin thermogram measured with an infrared thermography device about a change of physiology psychological condition of a driver. We measured a time change of difference of temperature of frontlet skin temperature and nasal skin temperature that can measure condition of sympathetic system / parasympathetic system indirectly with the infrared thermography device which can measure in non-contact, low restraint, easily. The experiment measured quantity of physiology from brain waves, a heartbeat, an nasal skin thermogram with the driving simulation problem which made a limit for a driver in time. By performing comparison with quantity of subjectivity, quantity of meandering and driving action quantity and steerage corners to acquire at the same time, we evaluate physiology psychological condition of a driver at the time of driving under the time pressure situation. As a result, by giving time pressure, difference of temperature of frontlet skin temperature and nasal skin temperature showed a change. Greatest temperature displacement became big when raised a degree of difficulty of time pressure.

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Autonomic nervous system is important to maintain homeostasis, and respiratory sinus arrhythmia (RSA) is known as a selective index of cardiac vagal activity. In this paper, we evaluated errors in the amplitude of RSA under the condition of body motion (keyboard typing and mental arithmetic with touching panel) and proposed a method for reducing them. It was found that elastic chest band is suitable under the quiet condition, while thermistor is suitable under the condition of body motion. It was also found that Berger's interpolation method was the best for detecting instantaneous heartbeat intervals in real-time signal processing. Furthermore, we proposed a error reduction algorithm by mixing the data of thermistor and elastic chest band , and applied it for interactive CG (Computer Graphics) system that reflected the amplitude of RSA estimated in real-time.

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The authors have been studying psychophysiological workload of human interface (HI) with physiological measurements and analysis. In this study, we investigated a kind of mental workload produced by user's unexpected waiting period from the request input to the termination of data processing during personal computer (PC) operation. As the experimental setting of HI, we used interactive software containing easy questions with unexpected time interval between each question. The effects of progress indicator (PI) indicating during waiting period on psychophysiological status of users were analyzed by using respiration, finger plethysmogram (PTG), heart rate (HR) and electroencephalogram (EEG) measurements. Results showed that the theta wave component of the EEG increased in the non-PI condition, even though autonomic nervous system parameters showed no significant change. Negative correlation between preference score for HI and integrated theta component percentage was observed only in non-PI condition. It is supposed that the PI was controlling theta activity coused by waiting stress in experimental condition. Utilizing physiological indices for HI assessment, this experimental method could be available to waiting stress estimation.

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To quantify the neural dynamics of the brain responsible for gustatory recognition and discrimination, fractal dimensions (FDs) of electroencephalograms (EEGs), which were measured under resting and three gustatory stimulation states, were investigated. The seven normal subjects sat on a chair with the chin resting on a frame made of plaster bandage and eyes closed. Distilled water (DW), high concentrated taste (HCT) solution (300 mM NaCl, 1 mM quinine-HCl, 40 mM acetic acid and 500 mM sucrose) and low concentrated taste (LCT) solution (51 mM NaCl, 0.026 mM quinine-HCl, 3 mM acetic acid and 14 mM sucrose) were randomly delivered to the anterior region of the tongue which was protruded slightly out of the mouth. FDs of EEGs from Cz in the resting and in the DW stimulation state were 5.43±1.01 and 4.94±1.03, respectively. In the HCT stimulation state, FD significantly decreased to 4.20±1.08 as compared with that in the resting (P<0.001). While, in the LCT stimulation state, FD significantly increased to 5.77±1.02 as compared with that in the HCT stimulation state (P<0.001). These results suggest that information processing of the brain is relatively simple when easily recognized tastes are applied.

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Recently, people of advanced age is increasing rapidly and following this the number of dementia is also increasing. The present study aimed to examine whether working memory task (1 back task) is available for an early diagnosis of dementia and to develop the early diagnostic method of dementia, by noticing that the prefrontal cortex is related to dementia and working memory. There was positive significant correlation between a number of right answer for working memory task and score of Hasegawa Dementia Rating Scale (HDS-R). In EEG coherent results, there was significant correlation between coherence of EEG and the score of HDS-R, especially in beta wave. The present results suggested that diagnosis using working memory task might be effective in detecting the presence of pre-stage of dementia.

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A system for monitoring electrocardiogram (ECG) through clothes inserted between the measuring electrodes and the body surface of a subject when lying on a mattress has been proposed. The principle of the system is based on capacitive coupling involving the electrode, the clothes, and the skin. Validation of the system revealed the following: (1) In spite of the gain attenuation in the pass band of the system, distortion of the detected signal was subtle even when clothes thicker than 1mm were inserted, (2) The system was able to yield a stable ECG from a subject particularly during sound sleep, (3) The system succeeded in detecting ECG after changing the posture into any of supine, right lateral, or left lateral positions by adopting a newly devised electrode configuration. Therefore, the proposed system appears promising for application to bedding as a non-invasive and awareness-free system for ECG monitoring during sleep.

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Previous studies have reported gaze influences on body sway direction in response to neck-dorsal-muscles stimulation (NS). In this study, we analyzed effects of gaze and auditory stimulation using tibialis anterior stimulation (TAS), gastrocnemius stimulation (GAS) or NS. From 21 subjects, the centre of pressure was measured and then the body sway direction during the stimulation was calculated. Each subject performed two trials in each of six gaze orientations. Nine subjects whose sway direction was markedly changed by the stimulation performed additional four trials. A comparison of the influences induced by the three methods revealed no statistical difference between NS and TAS. Three out of the nine subjects and another four took part in the auditory experiment. The three subjects showed significant changes in the sway direction. These results suggest that inconsistency among the sensory inputs around head plays only a minor role for reorienting the direction of postural sway and that a higher brain function is possibly involved in the mechanism for the sway direction change.

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The system and the alarm were designed as the operator operates properly it. However, the operator sometimes disregards consciously the alarms. In this paper, we discuss the new method of the estimation of accident rate, using the operator-machine-alarm model. If the operater always did right operation, the reliability of the alarm imformation was 1 and the accident rate was decided by the alarm failure rate and the machine failure rate. However, If the reliability of the alarm information wasn't 1,the accident rate was varied. For example, if the alarm failure rate was set to 0.1 and the machine failure rate was set to 0.9 and the reliability of alarm information was set to 1, then the accident rate was 0.09. However, when the reliability of alarm information was set to 0.1, the accident rate increased to 0.73.

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In present, personal identfication system have been used to input identification-numbers and passwords by keyboards and touch panels. When a user enters their identification-numbers and passwords an observer could easily see the user's secret details. In this report, new personal identification, which system constitutes tactile sense information using tactile stimuli and based on the cardinal trait of the tactile sense, is proposed.

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The subjective understanding on oral language understanding task is quantitatively evaluated by the fluctuation of oxygenated hemoglobin concentration measured by the near-infrared spectroscopy. The English listening comprehension test wihch consists of two difficulty level was executed by 4 subjects during the measurement. A significant correlation was found between the subjective understanding and the fluctuation of oxygenated hemoglobin concentration.

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