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M Kawato

Publications and source records attributed to M Kawato.

At least 73 records · Page 4Linked to original sources
PubMed1987

Simulation analysis of conduction of excitation in the atrioventricular node.

The excitation conduction in the atrioventricular node was simulated based on the spatially discrete model of the heart proposed in an earlier paper (Kawato et al., 1986). We constructed a model system composed of the atrium, the atrioventricular node and the Purkinje fiber. Coupling coefficients between these tissues were quantitatively estimated from experimental data on size and membrane capacitance of the three kinds of cardiac cells. We found the following three important features in the simulated excitation conduction along the atrioventricular node. First, shape of action potential was found to be different at different locations of the atrioventricular node although the membrane properties were assumed uniform through the atrioventricular node. Our analysis suggests that the difference in the action potential waveforms observed by Paes de Carvalho & De Almedia (1960) can be ascribed to the electrical influences of the atrium and the His bundle on the atrioventricular node. Second, when the excitation wavefront invaded the atrioventricular node from the atrium, a step was observed in the depolarization phase of the action potential at the atrioventricular node neighboring with the atrium. Janse found a similar step in the real experiment (1969). It is revealed that this step is caused by termination of the junctional current which flows from the atrium to the atrioventricular node. Finally, we found that the conduction velocity measured near the boundary between the atrium and the atrioventricular node was lower than that in the middle part of the atrioventricular node, which is in accordance with the experimental observation by Scher et al. (1959).

Action Potentials↗
PubMed1987

A hierarchical neural-network model for control and learning of voluntary movement.

In order to control voluntary movements, the central nervous system (CNS) must solve the following three computational problems at different levels: the determination of a desired trajectory in the visual coordinates, the transformation of its coordinates to the body coordinates and the generation of motor command. Based on physiological knowledge and previous models, we propose a hierarchical neural network model which accounts for the generation of motor command. In our model the association cortex provides the motor cortex with the desired trajectory in the body coordinates, where the motor command is then calculated by means of long-loop sensory feedback. Within the spinocerebellum--magnocellular red nucleus system, an internal neural model of the dynamics of the musculoskeletal system is acquired with practice, because of the heterosynaptic plasticity, while monitoring the motor command and the results of movement. Internal feedback control with this dynamical model updates the motor command by predicting a possible error of movement. Within the cerebrocerebellum--parvocellular red nucleus system, an internal neural model of the inverse-dynamics of the musculo-skeletal system is acquired while monitoring the desired trajectory and the motor command. The inverse-dynamics model substitutes for other brain regions in the complex computation of the motor command. The dynamics and the inverse-dynamics models are realized by a parallel distributed neural network, which comprises many sub-systems computing various nonlinear transformations of input signals and a neuron with heterosynaptic plasticity (that is, changes of synaptic weights are assumed proportional to a product of two kinds of synaptic inputs). Control and learning performance of the model was investigated by computer simulation, in which a robotic manipulator was used as a controlled system, with the following results: (1) Both the dynamics and the inverse-dynamics models were acquired during control of movements. (2) As motor learning proceeded, the inverse-dynamics model gradually took the place of external feedback as the main controller. Concomitantly, overall control performance became much better. (3) Once the neural network model learned to control some movement, it could control quite different and faster movements. (4) The neural network model worked well even when only very limited information about the fundamental dynamical structure of the controlled system was available.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗
PubMed1987

Immunohistochemical and ultrastructural study of subacute thyroiditis, with special reference to multinucleated giant cells.

Twenty-four cases of subacute thyroiditis were examined immunohistochemically and ultrastructurally, with special attention being directed to the multinucleated giant cells that characterize the lesions of this condition. Immunohistochemical study revealed that 99 per cent of the giant cells contained lysozyme, 82 per cent contained vimentin, 66 per cent contained alpha 1-antitrypsin, and 61 per cent contained thyroxine. Only 17 per cent contained thyroglobulin, 5 per cent contained keratin, 16 per cent contained epithelial membrane antigen, and 4 per cent contained leukocyte common antigen. Mononuclear cells infiltrating the follicular spaces showed a staining pattern similar to that of the multinucleated giant cells. Desquamated follicular epithelial cells were strongly positive for thyroglobulin and thyroxine, while regenerated epithelia that formed small follicles were positive for thyroglobulin but negative for thyroxine. Electron microscopic examination of cell ultrastructure revealed that most multinucleated giant cells had structures identical with those of infiltrating mononuclear cells, particularly with histiocytes, and that giant cells were formed by mononuclear cell fusion. These findings indicate the majority of multinucleated giant cells in subacute thyroiditis are derived from mononuclear-histiocyte cells.

Acute Disease↗
PubMed1986

Simulation analysis of excitation conduction in the heart: propagation of excitation in different tissues.

The normal excitation and conduction in the heart are maintained by the coordination between the dynamics of ionic conductance of each cell and the electrical coupling between cells. To examine functional roles of these two factors, we proposed a spatially-discrete model of conduction of excitation in which the individual cells were assumed isopotential. This approximation was reasoned by comparing the apparent space constant with the measured junctional resistance between myocardial cells. We used the four reconstruction models previously reported for five kinds of myocardial cells. Coupling coefficients between adjacent cells were determined quantitatively from the apparent space constants. We first investigated to what extent the pacemaker activity of the sinoatrial node depends on the number and the coupling coefficient of its cells, by using a one-dimensional model system composed of the sinoatrial node cells and the atrial cells. Extensive computer simulation revealed the following two conditions for the pacemaker activity of the sinoatrial node. The number of the sinoatrial node cells and their coupling coefficients must be large enough to provide the atrium with the sufficient electric current flow. The number of the sinoatrial node cells must be large so that the period of the compound system is close to the intrinsic period of the sinoatrial node cell. In this simulation the same sinoatrial node cells produced action potentials of different shapes depending on where they were located in the sinoatrial node. Therefore it seems premature to classify the myocardial cells only from their waveforms obtained by electrical recordings in the compound tissue. Second, we investigated the very slow conduction in the atrioventricular node compared to, for example, the ventricle. This was assumed to be due to the inherent property of the membrane dynamics of the atrioventricular node cell, or to the small value of the coupling coefficient (weak intercellular coupling), or to the electrical load imposed on the atrioventricular node by the Purkinje fibers, because the relatively small atrioventricular node must provide the Purkinje fibers with sufficient electric current flow. Relative contributions of these three factors to the slow conduction were evaluated using the model system composed of only the atrioventricular cells or that composed of the atrioventricular and Purkinje cells. We found that the weak coupling has the strongest effect. In the model system composed of the atrioventricular cells, the propagation failure was not observed even for very small values of the coupling coefficient.(ABSTRACT TRUNCATED AT 400 WORDS)

Atrioventricular Node↗
PubMed1986

[Responses of plasma bradykinin and the renin angiotensin axis to angiotensin II in hyperthyroid patients].

The present investigation was undertaken to elucidate the possible interplay between the circulating kinin(s) and the renin angiotensin axis in hyperthyroidism. The responsiveness of plasma aldosterone (p-Ald), kinin (p-BK), plasma renin activity (PRA) and serum angiotensin converting enzyme activity (ACEA) to infusion of angiotensin II at a dose of 4, 8 and 16 ng/kg.min. was asessed in 15 hyperthyroid patients and 10 euthyroid controls. There was impaired angiotensin II induced response of blood pressure in hyperthyroid patients, and basal concentrations of p-Ald were 7.7 +/- 3.8 ng/dl in euthyroid controls and 12.6 +/- 3.1 ng/dl in hyperthyroid patients (p less than 0.05). As compared to the euthyroid controls, the hyperthyroid patients showed a reduced response of plasma aldosterone to angiotensin II infusion. Angiotensin II infusion increased p-BK from basal levels of 19.1 +/- 8.2 pg/ml to 31.0 +/- 7.8 pg/ml (p less than 0.05) only in hyperthyroid patients and did not increase ACEA in either group. Next, the effects of a single administration of captopril (50 mg p.o.) on blood pressure and p-BK in hyperthyroid patients and euthyroid controls were studied. In the two groups blood pressure was not changed by captopril, but p-BK increased significantly. The present results do not support the view that there may be a direct linkage between the kallikrein kinin system and the renin angiotensin axis mediated by kininase II or angiotensin converting enzyme in human peripheral blood. Also it is unlikely that kinin may play a role in the mechanism of reduced responsiveness of aldosterone and blood pressure to angiotensin II in hyperthyroidism.

Adult↗
PubMed1986

Synaptic currents at interpositorubral and corticorubral excitatory synapses measured by a new iterative single-electrode voltage-clamp method.

A new iterative single-electrode voltage clamp method was applied to the measurement of synaptic currents in the red nucleus (RN) neuron of the cat. Voltage clamp was attained within 10 repetitions with great stability and the new algorithm was demonstrated to be superior to the original algorithm of iterative voltage clamp. With a conventional microelectrode, it was possible to measure the synaptic current with the time resolution of 50 microseconds. The synaptic currents evoked by stimulation of the contralateral interpositus nucleus (IP) had time-to-peak ranging from 200 to 540 microseconds and fitted well to alpha functions. Corticorubral (CR) synaptic current was also measured by making use of synaptic plasticity. The stimulation of the ipsilateral cerebral peduncle in cats with chronic lesion of the contralateral IP evoked fast rising EPSPs, as reported previously. The CR-EPSPs with times-to-peak less than 1 ms were subjected to voltage clamp. The CR synaptic currents had times-to-peak ranging from 350 to 880 microseconds. Since most of the interpositorubral (IR) synapses and a part of the CR synapses in IP-lesioned cats are situated on the somatic membrane of RN neurons and some of the CR synaptic currents were as rapid as the IR synaptic currents, the observed synaptic currents evoked by stimulation of the IP and those of the fast-rising CR-EPSPs were taken to originate from the synaptic membrane under space-clamp, i.e. soma. The present study provided additional evidence for the sprouting of the CR fibers as well as the time course of the synaptic current at the dendritic synapses remote from the soma, for the first time.

Animals↗
PubMed1986

ACTH secretory responsiveness of pituitary adrenotroph cell tumor to adrenocorticotropin-releasing factor in Cushing's disease and Nelson's syndrome.

ACTH-secretory responsiveness of the adrenotroph cell tumors to the exogenous CRF was evaluated in 4 cases of Cushing's disease and 3 cases of Nelson's syndrome. Significantly exaggerated ACTH release was evoked by the intravenous injection of CRF in all 3 cases of Nelson's syndrome, but in Cushing's disease there seemed to be an individual difference in the sensitivity of the pituitary to CRF, probably depending on the functional activity of hypothalamo-pituitary axis.

Adrenocorticotropic Hormone↗
PubMed1986

Reconstruction of electrocardiogram using ionic current models for heart muscles.

A digital computer model is presented for the simulation of the electrocardiogram during ventricular activation and repolarization (QRS-T waves). The part of the ventricular septum and the left ventricular free wall of the heart are represented by a two dimensional array of 730 homogeneous functional units. Ionic currents models are used to determine the spatial distribution of the electrical activities of these units at each instant of time during simulated cardiac cycle. In order to reconstruct the electrocardiogram, the model is expanded three-dimensionally with equipotential assumption along the third axis and then the surface potentials are calculated using solid angle method. Our digital computer model can be used to improve the understanding of the relationship between body surface potentials and intracellular electrical events.

Computer Simulation↗
PubMed1985

A new algorithm for voltage clamp by iteration: a learning control of a nonlinear neuronal system.

Voltage-clamp of excitable membrane allows the measurement of membrane currents associated with electrical potential changes across the membrane. However, it has been impossible in practice to apply the conventional analog feedback voltage-clamp circuits to single electrode voltage clamping in central neurons. The reason for this is that the feedback system becomes unstable because of the positive feedback required for compensation of capacitative loss through the wall of the microelectrode. Park et al. (1981) proposed a new iterative technique to solve this problem. It requires that the potential to be clamped repeats itself with little or no change. The amount of current needed to clamp the membrane potential is not determined at once, but in a step-wise, trial and error fashion in the course of a set of repetitions. Since the feedback loop is open in real time, the system has great stability, and this advantage can be exploited in single electrode preparations. The computation algorithm which calculates the current waveform based on the voltage deviation during the last trial is the central part of the iterative voltage-clamp system. In this paper, we propose a new algorithm, which has several theoretical and practical advantages over the original one proposed by Park et al. First, two parameters used in the new algorithm are predetermined by a current-clamp experiment. Second, the speed of convergence of the new algorithm is faster than that of the Park's original algorithm. This was shown by computer simulation of iterative voltage clamp of artificial membrane following Hodgkin-Huxley equations for squid axon membrane and Rall's compartment model for a neuron with dendrites. Finally, we offer proof that the new algorithm is certain to converge for the general cases of voltage-clamp experiments with active membrane properties, synaptic membranes, etc. Consequently, the new algorithm for iterative voltage clamp is very suitable for single electrode voltage clamp in the central neurons. The new algorithm has been successfully applied to voltage-clamp experiments on rubrospinal neurons of cats (Tsukahara, Murakami, Kawato, Oda, and Etoh, in preparation).

Animals↗
PubMed1984

Cable properties of a neuron model with non-uniform membrane resistivity.

We propose an exact, self-closed and simple method for simultaneous estimation of the electrotonic length of the equivalent dendritic cylinder, and the ratio of dendritic to somatic input conductance in the Rall's motoneuron model (1969), from a voltage transient at the soma in response to a current step applied to the soma. We prove the theoretical constraint in the Rall's motoneuron model that one half of the ratio of amplitudes of the first two peeled exponentials in a membrane voltage transient caused by a current step, must be smaller than the ratio of the corresponding first two time constants. This theoretical prediction is not satisfied for several types of neurons, and our method to estimate cable parameters is not applicable to these neurons. By extending the Rall's neuron model, we develop a neuron model, which contains two membrane resistance per unit area; one for somatic membrane and one for dendritic membrane. In this model we obtain the transient solution of membrane potential at the soma in response to a current step applied to the soma. It is shown that the amplitude ratio can be larger than double of the time constant ratio when the somatic resistance is lower than the dendritic resistance. Moreover, we give a purely electrophysiological method to estimate cable parameters of the extended model from soma transient in response to a current step.

Dendrites↗
PubMed1984

Quantitative analysis of electrical properties of dendritic spines.

Several suggestions have been made with regard to the functional significance of dendritic spines in connection with synaptic plasticity. We have shown that for a constant synaptic current, when the synaptic resistance is large compared to the spine-stem resistance, a morphological change in the spine does not produce a marked change in the postsynaptic potential (PSP). When the synaptic resistance is comparable to the spine-stem impedance a morphological change in the spine can induce changes in the synaptic current and the PSP due to the so-called nonlinear effect to the synapse (Kawato and Tsukahara, 1983, 1984). Consequently, in a study of the electrical properties of dendritic spines the input impedance of the parent dendrite, the spinestalk conductance and the conductance change associated with synaptic activity must be considered. We quantitatively estimated all three factors. By comparing electrophysiological data with morphological data, we estimated the synaptic conductance which causes corticorubral EPSP. Its maximum amplitude was 43 nS with a time-to-peak value of 0.3 ms. With this value, the effects of the spine were examined using an improved algorithm based on that of Butz and Cowan (1974). It uses a three-dimensional morphology of the rubrospinal (RS) neurons, which was reconstructed from serial sections containing HRP-filled RS cells. As the spine shortens, the amplitude of the EPSP becomes considerably larger, but its time-to-peak value does not markedly change. Moreover, if unitary EPSP in the RS cell is produced by the activation of several synaptic terminals a morphological change of the spine has a smaller effect on the EPSPs.

Animals↗
PubMed1984

Electrical properties of dendritic spines with bulbous end terminals.

Several suggestions have been made about the functional significance of dendritic spines in connection with synaptic plasticity. We investigated transient electrical behavior of spines with bulbous terminals in neurons with arbitrary dendritic geometries. It is shown that postsynaptic potential transform caused by a synapse on a spine can be resolved into a product of two transfer functions and the synaptic input current transform. The first transfer function was determined to be independent of the spine. The second transfer function represents the straightforward attenuation effect of the spine, which determines the effective synaptic current reaching the parent dendrite. Using what is known of the size and the shape of spines from histology, we conclude that almost all of the synaptic current flow into the parent dendrite, and that therefore the straightforward attenuation effect is negligible. Consequently, when the synaptic current remained unaltered, as was the case for a large synaptic resistance as compared with the spine stem resistance, a morphological change of the spine did not produce an effective change in the postsynaptic potential. On the other hand, when the synaptic resistance is compared with the spine stem impedance, the morphological change of the spine might induce changes of the synaptic current and the postsynaptic potential.

Animals↗
PubMed1983

Theoretical study on electrical properties of dendritic spines.

In most parts of mammalian central nervous system the majority of synapses are located on dendritic spines. Several suggestions have been made about the functional significance of the dendritic spines. We investigate electrical properties of dendritic spines in the neurons with arbitrary dendritic geometry. Following Butz & Cowan (1974), all dendritic branches, including spines, are treated as cylinders of uniform passive membrane. We show that the postsynaptic potential due to the synapse on the spine is represented as a convolution integral of the following two functions. The first is the postsynaptic potential caused by the same synapse on the branching point where the spine stalk is attached to the main dendritic trunk. The second function is determined mainly by the morphological and electrical properties of the spine and it represents the attenuation effect of the spine. On the assumption that the diameter of the spine stalk is sufficiently small compared to that of the parent dendrite to which the spine stem is attached, we obtain an approximation of the second function and conclude that morphological change of the spine does not produce an effective change of the postsynaptic potential, hence does not provide the neural basis for learning or memory simply by changing cable properties of dendrites. Moreover, we show that synapses on the dendritic spine are not effectively isolated from other synapses on the same assumption.

Animals↗