Magnocellular neurones in the supraoptic nucleus and paraventricular nucleus express mRNA for nitric oxide synthase (NOS) and the expression becomes more prominent when the release of vasopressin or oxytocin is stimulated. It has also been reported that NO donors inhibit the electrical activity of supraoptic nucleus neurones, but the mechanism involved in the inhibition remains unclear. In the present study, to know whether modulation of synaptic inputs into supraoptic neurones is involved in the inhibitory effect of NO, we measured spontaneous excitatory and inhibitory postsynaptic currents (EPSCs and IPSCs) from rat supraoptic nucleus neurones in slice preparations identified under a microscope using the whole-cell mode of the slice-patch-clamp technique. The NO donor, S-nitroso-N-acetylpenicillamine (SNAP), reversibly increased the frequency of spontaneous IPSCs mediated by GABAA receptors, without affecting the amplitude, indicating that NO potentiated IPSCs via a presynaptic mechanism. The NO scavenger, haemoglobin, suppressed the potentiation of IPSCs by SNAP. On the other hand, SNAP did not cause significant effects on EPSCs mediated by non-NMDA glutamate receptors. The membrane permeable analogue of cGMP, 8-bromo cGMP, caused a significant reduction in the frequency and amplitude of both IPSCs and EPSCs. The results suggest that NO preferentially potentiates the inhibitory synaptic inputs into supraoptic nucleus neurones by acting on GABA terminals in the supraoptic nucleus, possibly via a cGMP-independent mechanism. The potentiation may, at least in part, account for the inhibitory action of NO on the neural activity of supraoptic neurones.
Investigation of adaptive control systems using neuronlike networks for the optimization of multitasking control of an unknown object has revealed that the identification of the unknown object should precede the main adaptation process. The Adaptive Neuronlike Network (ANN) is used for the simulation of an "inverted object model". In the result of the identification procedure a joined block composed of the unknown object and the ANN may be described by a matrix close to the identity matrix. This procedure considerably simplifies the optimization of multitasking control.A new model of neuronlike element with nonlinear presynaptic inhibition was introduced.Applying this model and a modified learning process makes it possible to simulate a broad class of nonlinear multidimensional objects. AbstractA new learning algorithm for multi-layered neural networks is presented. This algorithm, called minimal disturbance backpropagation, approximates a least mean squared error minimization of the error function while minimally disturbing the connection weights in the network. This means that the information previously trained into the network is disturbed to the smallest amount possible while achieving the desired error correction. Simulation results indicate that this algorithm is more robust and yields much faster convergence rates than the standard back-propagation algorithm. AbstractThis report presents a back-propagation algorithm that varies the number of hidden units. This algorithm i s expected t o escape l o c a l minima and.makes i t no longer necessary t o decide the number of hidden units. We e x p l a i n e x c l u s i v e OR t r a i n i n g and 8 x 8 d o t alphanumeric font training using t h i s algorithm. In exclusive OR t r a i n i n g , the p r o b a b i l i t y of being trapped i n local minima i s reduced. In alphanumeric font t r a i n i n g , the network converged two t o three times faster than the conventional back propagation algorithm. Abstract THE EFFECTS OF PRECISION CONSTRAINTS INA BACK-PROPAGATION LEARNING NETWORK Primacy and recency effects are analyzed mathematically for back propagation algorithms (generalized delta rule), which use momentum. Our results show that when the conventional momentum parameter is used, a primacy effect occurs: The current values of the weights are biased towards the first presentations in a sequence of training patterns. To produce a recency effect, we introduce a different momentum parameter. The current values of the weights depend more on recent presentations of training patterns under this recency effect. A method is provided for selecting a momentum parameter based on the effect desired : primacy or recency.ABSTRACT This paper presents a study of precision constraints imposed by a hybrid chip architecture with analog neurons and digital back-propagation calculations. Conversions between the analog and digital domains and weight storage restrictions impose precision limits on both analog and digital calculations. It is shown through simulations that a learning s...
I . H IR O NO , M . YA MA S HI TA A ND T. A OK I. 1998. Chitinase genes from Vibrio anguillarum KV9001 and V. parahaemolyticus ATCC17802 were cloned into Escherichia coli. Open reading frames of chitinase genes from V. anguillarum (vac) and V. parahaemolyticus (vpc) are 1755 bp and 1890 bp, respectively. The deduced amino acid sequences of these genes have 71·6% identity. There are two consensus sequence regions in the VAC and VPC proteins. The vac gene was highly prevalent in V. anguillarum, and the DNA probe of the vac gene hybridized to V. alginolyticus and Beneckea proteolytica DNA. The DNA probe of the vpc gene hybridized to V. alginolyticus, V. harveyi and V. ordalii DNA.
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