The modelling of the process of image-sequence fixation and reproduction in a projective-associative network made up of excitatory neuron-like elements]

On mathematic model of several interconnected networks of excitatory neurone-like elements realized in the form of program on computer "Nord-100", a study of conditions of fixation and reproduction of symbols (words) succession was conducted. Connections between the receptive (C1 and C2) and associative (A1 and A2) networks were by the principle "one to one", connections between the networks A1 and A2 with reinforcing general activating network (GAN) were by the principle "all with all". Possibility was shown of restoration of images succession fixed in the network on the basis of the principle of chain conditioned reflexes provided a successive change of reinforcing GAN elements by means of the decrease of the threshold of their activation. It was found that contacts transferring the influences of the reinforcing network at learning by the Hebb principle, must either initially exert a subthreshold action or be "unlearning" for the elimination of the process of overexcitation.     

Homogeneous nets of neuron-like elements

Propagation and reverberation of excitation patterns are investigated for 1-dimensional and 2-dimensional homogeneous nets of neuron-like elements. A 1-dimensional net has a proper set of excitation patterns which only can be conducted in the net. Such a net has an ability of discriminating and shaping stimulus signals. Two types of self-reproducing reverberatory excitation patterns are shown for 2-dimensional homogeneous nets. An algebraic theory of general homogeneous nets is also developed.     

Modeling different regimes of bioelectrical activity in the brain in normal subjects and in "increased readiness" in a network of neuron-like elements

Desynchronous (low voltage fast activity), synchronous (high voltage slow waves) as well as convulsive brain activities were stimulated by a computer model of neuronal population. Network excitatory and inhibitory elements possessed fundamental dynamic properties of real neurones. Being independent both of the excitability of elements and of external influence efficacy, synchronous (desynchronous) network activity resulted from the increase (decrease) of the average power of "neuronal" interconnections which imitated mutual and recurrent excitation and inhibition. The inhibition efficacy being reduced as compared with excitation, synchronization of elements became intensified. As a consequence, the rhythmic activity amplitude increased and the appearance of self-sustained oscillations simulating convulsive activity was facilitated. The probable mechanism of EEG activation by virtue of the reduction of mutual and recurrent excitation and inhibition efficacy as well as the significance of inhibitory mechanism deficiency for epileptogenesis are discussed.     

Effect of deafferentation of the lateral geniculate body on its background activity

Elimination of reticular inputs to the lateral geniculate body (LGB) by sectioning of one half of the midbrain operculum, did not affect significantly the characteristics of the LGB evoked potential to light stimulus. At the same time LGB response to stimulation of the reticular formation by a single current impulse, though did not disappear completely, but changed greatly: its latency became twice as long, the negative component of the response was no more recorded. In conditions of LGB deafferentation, the characteristics of all rhythms of its electrical activity, besides the alpha-like one, considerably changed. At the same time, exactly this last rhythm underwent the greatest changes on the EEG of the visual cortex. On the basis of the obtained data it is suggested that the reticular formation takes a considerable and multiple part in generation of LGB rhythmic activity and that changes in its characteristics are clearly reflected in the ECoG rhythms formation. Retention of the LGB visual evoked potential and of the response to stimulation of the reticular formation after the section of one half of the midbrain operculum testifies to the presence of several reticular inputs to LGB.     

Molecular mechanisms of nerve excitation and conduction

In this paper we propose that the physical behavior of the electric dipoles at the membraneinterface is mainly responsible for the observed phenomena in nerve excitation and conduction. The underlying molecular mechanisms are conceived to be dipole reorientation, relaxation and flip-flops. It is suggested that quantum transitions of electric dipoles and a few first principles provide a real physical basis for the neural behavior as manifested macroscopically. This dipole theory gains a strong support from the most recent discoveries of negative fixed surface charge on axon membranes, infrared emission from stimulated nerve and the birefringence change which coincided with the action potential in squid axon. It can also offer an explanation for the heat production and absorption in excited nerves. A brief discussion will be given to the memory mechanism in terms of the field-dipole interaction during the RNA synthesis in nerve cells. Visiting the Research Institute of Electronics, Chiao-Tung University, Hsinchu, Formosa (Taiwan), September 1, 1968–June 1, 1969.     

Analysis of the effect of backward masking by means of a complex model of a net of neuron-like elements

According to the experiments with a projective-associative model of the neuronal net, the phenomenon of “backward masking” of the first stimulus of a pair of stimuli at a small time gap between the stimuli is caused by two events: (1) pre-excitation inhibition of the first stimulus-induced activation by the second stimulus and (2) disturbance of information processing connected with the deficiency of time needed to match the recalled symbol in memory to the symbol presented to the input subsystem and also to name it. Identification of the second stimulus may be impaired with a decreasing time interval due to: (1) superposition of the second (2) recurrent inhibition occurring in the neuronal net upon recognition of the first stimulus. It was found that in conditions of activity of neuron-like elements of the neuronal net, simulating the states of somnolence or slow-wave sleep, corresponding subsystems failed to learn, while time needed to identify already “learned” symbols substantially increased. The data obtained are in agreement with the hypothesis concerning the causes of backward masking and also with the facts on optimal conditions of learning and reproducing its results in living nervous system. It seems reasonable that discussed disturbances of information processing should be kept in mind in designing computers of a new generation, based on the use of principles of brain functioning, in order to increase the reliability and operation speed of technical systems.     

神经传导的新概念:无动作电位的兴奋传导

近年来研究揭示在神经传导中存在着无动作电位的兴奋传导机制,它主要涉及细胞膜中胞膜窖专门化脂筏内的分子转导作用,这对兴奋只能通过电现象沿神经进行传导的传统理念是一个重大的挑战.这一机制可能是神经科学基础领域研究的重要进展.     

Some properties of randomly connected networks of neuron-like elements with refractory

Dynamic properties of randomly connected networks consisting of neuron-like elements with refractory are investigated from a macroscopic point of view. Equations describing the transition of the activity level of the network — a macroscopic state — are derived under some hypotheses on the stochastic properties of the network. The equations are characterized by a set of parameters which are determined by distributions of the threshold values of elements and the weighting values of connection between elements. It is shown that a network behaves like a monostable, bistable or astable circuit when its refractory period is less than one time unit and that a network is monostable or bistable when its refractory period is longer than two time units. An oscillatory network, on the other hand, is always realized if the network has a feedback mechanism which decreases the excitability of neurons when high activity level is sustained. Some results of computer simulation of randomly connected neuron networks are also presented.     

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)     

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).