scholarly journals Dynamic Threshold Neural P Systems with Multiple Channels and Inhibitory Rules

Processes ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1281
Author(s):  
Xiu Yin ◽  
Xiyu Liu
Keyword(s):  
Neural Networks ◽  
Parallel Computing ◽  
Ion Channels ◽  
Inhibitory Synapses ◽  
Dynamic Threshold ◽  
P System ◽  
Excitatory Synapses ◽  
Multiple Channels ◽  
Computing Model ◽  
Distributed Parallel Computing

In biological neural networks, neurons transmit chemical signals through synapses, and there are multiple ion channels during transmission. Moreover, synapses are divided into inhibitory synapses and excitatory synapses. The firing mechanism of previous spiking neural P (SNP) systems and their variants is basically the same as excitatory synapses, but the function of inhibitory synapses is rarely reflected in these systems. In order to more fully simulate the characteristics of neurons communicating through synapses, this paper proposes a dynamic threshold neural P system with inhibitory rules and multiple channels (DTNP-MCIR systems). DTNP-MCIR systems represent a distributed parallel computing model. We prove that DTNP-MCIR systems are Turing universal as number generating/accepting devices. In addition, we design a small universal DTNP-MCIR system with 73 neurons as function computing devices.

scholarly journals A Complex Chained P System Based on Evolutionary Mechanism for Image Segmentation

2020 ◽  
Vol 2020 ◽  
pp. 1-19 ◽  
Author(s):  
Xiyu Liu ◽  
Lin Wang ◽  
Jianhua Qu ◽  
Ning Wang
Keyword(s):  
Image Segmentation ◽  
Real Life ◽  
Membrane System ◽  
Global Search ◽  
P System ◽  
Evolutionary Mechanism ◽  
Modified Particle Swarm Optimization ◽  
Computing Model ◽  
Distributed Parallel Computing ◽  
Clustering Problems

A new clustering membrane system using a complex chained P system (CCP) based on evolutionary mechanism is designed, developed, implemented, and tested. The purpose of CCP is to solve clustering problems. In CCP, two kinds of evolution rules in different chained membranes are used to enhance the global search ability. The first kind of evolution rules using traditional and modified particle swarm optimization (PSO) clustering techniques are used to evolve the objects. Another based on differential evolution (DE) is introduced to further improve the global search ability. The communication rules are adopted to accelerate the convergence and avoid prematurity. Under the control of evolution-communication mechanism, the CCP can effectively search for the optimal partitioning and improve the clustering performance with the help of the distributed parallel computing model. This proposed CCP is compared with four existing PSO clustering approaches on eight real-life datasets to verify the validity. The computational results on tested images also clearly show the effectiveness of CCP in solving image segmentation problems.

Spiking Neural P Systems with Extended Channel Rules

2020 ◽  
Vol 31 (01) ◽  
pp. 2050049 ◽  
Author(s):  
Zeqiong Lv ◽  
Tingting Bao ◽  
Nan Zhou ◽  
Hong Peng ◽  
Xiangnian Huang ◽  
...  
Keyword(s):  
Parallel Computing ◽  
Control Mechanism ◽  
P Systems ◽  
Multiple Channels ◽  
Spiking Neural P Systems ◽  
Distributed Parallel Computing ◽  
New Variant ◽  
New Type ◽  
Turing Universality ◽  
Computing Models

This paper discusses a new variant of spiking neural P systems (in short, SNP systems), spiking neural P systems with extended channel rules (in short, SNP–ECR systems). SNP–ECR systems are a class of distributed parallel computing models. In SNP–ECR systems, a new type of spiking rule is introduced, called ECR. With an ECR, a neuron can send the different numbers of spikes to its subsequent neurons. Therefore, SNP–ECR systems can provide a stronger firing control mechanism compared with SNP systems and the variant with multiple channels. We discuss the Turing universality of SNP–ECR systems. It is proven that SNP–ECR systems as number generating/accepting devices are Turing universal. Moreover, we provide a small universal SNP–ECR system as function computing devices.

scholarly journals Universal Nonlinear Spiking Neural P Systems with Delays and Weights on Synapses

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Liping Wang ◽  
Xiyu Liu ◽  
Yuzhen Zhao
Keyword(s):  
Parallel Computing ◽  
P Systems ◽  
Real Numbers ◽  
Spiking Neural P Systems ◽  
Subset Sum Problem ◽  
Computing Model ◽  
Distributed Parallel Computing ◽  
Subset Sum ◽  
Computing Performance ◽  
Turing Universality

The nonlinear spiking neural P systems (NSNP systems) are new types of computation models, in which the state of neurons is represented by real numbers, and nonlinear spiking rules handle the neuron’s firing. In this work, in order to improve computing performance, the weights and delays are introduced to the NSNP system, and universal nonlinear spiking neural P systems with delays and weights on synapses (NSNP-DW) are proposed. Weights are treated as multiplicative constants by which the number of spikes is increased when transiting across synapses, and delays take into account the speed at which the synapses between neurons transmit information. As a distributed parallel computing model, the Turing universality of the NSNP-DW system as number generating and accepting devices is proven. 47 and 43 neurons are sufficient for constructing two small universal NSNP-DW systems. The NSNP-DW system solving the Subset Sum problem is also presented in this work.

scholarly journals A Novel Clustering Algorithm Inspired by Membrane Computing

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Hong Peng ◽  
Xiaohui Luo ◽  
Zhisheng Gao ◽  
Jun Wang ◽  
Zheng Pei
Keyword(s):  
Parallel Computing ◽  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Real Life ◽  
P System ◽  
Data Sets ◽  
Evolutionary Clustering ◽  
Distributed Parallel Computing ◽  
Real Life Data ◽  
Neighborhood Topology

P systems are a class of distributed parallel computing models; this paper presents a novel clustering algorithm, which is inspired from mechanism of a tissue-like P system with a loop structure of cells, called membrane clustering algorithm. The objects of the cells express the candidate centers of clusters and are evolved by the evolution rules. Based on the loop membrane structure, the communication rules realize a local neighborhood topology, which helps the coevolution of the objects and improves the diversity of objects in the system. The tissue-like P system can effectively search for the optimal partitioning with the help of its parallel computing advantage. The proposed clustering algorithm is evaluated on four artificial data sets and six real-life data sets. Experimental results show that the proposed clustering algorithm is superior or competitive tok-means algorithm and several evolutionary clustering algorithms recently reported in the literature.

Acid-Sensing Ion Channels

2020 ◽  
Author(s):  
Stefan Gründer
Keyword(s):  
Nervous System ◽  
Ion Channels ◽  
Excitatory Synapses ◽  
Detailed Characterization ◽  
High Affinity ◽  
Acid Sensing Ion Channels ◽  
Long Time ◽  
Pathological Pain

Acid-sensing ion channels (ASICs) are proton-gated Na+ channels. Being almost ubiquitously present in neurons of the vertebrate nervous system, their precise function remained obscure for a long time. Various animal toxins that bind to ASICs with high affinity and specificity have been tremendously helpful in uncovering the role of ASICs. We now know that they contribute to synaptic transmission at excitatory synapses as well as to sensing metabolic acidosis and nociception. Moreover, detailed characterization of mouse models uncovered an unanticipated role of ASICs in disorders of the nervous system like stroke, multiple sclerosis, and pathological pain. This review provides an overview on the expression, structure, and pharmacology of ASICs plus a summary of what is known and what is still unknown about their physiological functions and their roles in diseases.

Urban Railway Bridge Fast Evaluation Based on Cloud Computing

2011 ◽  
Vol 71-78 ◽  
pp. 4501-4505
Author(s):  
Ming Chen ◽  
Wan Zhou
Keyword(s):  
Neural Networks ◽  
Cloud Computing ◽  
Model Updating ◽  
Condition Assessment ◽  
Fe Model ◽  
Railway Bridge ◽  
Fast Evaluation ◽  
Railway Bridges ◽  
Computing Model ◽  
Bridge Condition Assessment

Although modern bridge are carefully designed and well constructed, damage may occur in them due to unexpected causes. Currently, many different techniques have been proposed and investigated in bridge condition assessment. However, evaluation efficiency of condition assessment has not been paid much attention by the researchers. A fast evaluation of the urban railway bridge condition based on the cloud computing is presented. In this paper dynamic FE model and Artificial neural networks technique is applied to model updating. The cloud computing model provides the basis for fast analyses. It was found that when applied to the actually railway bridges, the proposed method provided results similar to those obtained by experts, but can improve efficiency of bridge

scholarly journals Novel Numerical Spiking Neural P Systems with a Variable Consumption Strategy

Processes ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 549
Author(s):  
Xiu Yin ◽  
Xiyu Liu ◽  
Minghe Sun ◽  
Qianqian Ren
Keyword(s):  
Production Functions ◽  
P Systems ◽  
P System ◽  
Computing Device ◽  
Spiking Neural P Systems ◽  
Distributed Parallel Computing ◽  
Production Values ◽  
Novel Variant ◽  
Turing Universality ◽  
Variable Consumption

A novel variant of NSN P systems, called numerical spiking neural P systems with a variable consumption strategy (NSNVC P systems), is proposed. Like the spiking rules consuming spikes in spiking neural P systems, NSNVC P systems introduce a variable consumption strategy by modifying the form of the production functions used in NSN P systems. Similar to the delay feature of the spiking rules, NSNVC P systems introduce a postponement feature into the production functions. The execution of the production functions in NSNVC P systems is controlled by two, i.e., polarization and threshold, conditions. Multiple synaptic channels are used to transmit the charges and the production values in NSNVC P systems. The proposed NSNVC P systems are a type of distributed parallel computing models with a directed graphical structure. The Turing universality of the proposed NSNVC P systems is proved as number generating/accepting devices. Detailed descriptions are provided for NSNVC P systems as number generating/accepting devices. In addition, a universal NSNVC P system with 66 neurons is constructed as a function computing device.

Electrophysiological evidence from glutamate microapplications for local excitatory circuits in the CA1 area of rat hippocampal slices

1988 ◽  
Vol 59 (1) ◽  
pp. 110-123 ◽  
Author(s):  
E. P. Christian ◽  
F. E. Dudek
Keyword(s):  
Hippocampal Neurons ◽  
Hippocampal Slices ◽  
Pyramidal Cells ◽  
Inhibitory Synapses ◽  
Excitatory Synapses ◽  
Recording Site ◽  
Postsynaptic Potentials ◽  
Inhibitory Postsynaptic Potentials ◽  
Ca1 Area ◽  
Transverse Slice

1. Evidence for local excitatory synaptic connections in CA1 of the rat hippocampus was obtained by recording excitatory postsynaptic potentials (EPSPs) intracellularly from pyramidal cells during local microapplications of glutamate. 2. Experiments were performed in hippocampal slices cut parallel to (transverse slice) or perpendicular to (longitudinal slice) alvear fibers. In normal solutions, glutamate microdrops (10–20 mM, 10–20 micron diam) applied in CA1 within 400 micron of recorded cells sometimes increased the frequency of inhibitory postsynaptic potentials for 5–10 s in both transverse and longitudinal slices. Increases in EPSP frequency were also occasionally observed, but only in transverse slices. Tetrodotoxin (1 microgram/ml) blocked glutamate-induced increases in PSP frequency, thus indicating that they were not caused by subthreshold effects on presynaptic terminals. Increases in PSP frequency were interpreted to result from glutamate activation of hippocampal neurons with inhibitory and excitatory connections to recorded neurons. 3. In both slice orientations, local excitatory circuits were studied in more isolated conditions by surgically separating CA1 from CA3 (transverse slices) and by blocking GABAergic inhibitory synapses with picrotoxin (5–10 microM). Microdrops were systematically applied at 200 and 400 micron on each side of the recording site. Significant glutamate-induced increases in EPSP frequency were observed in neurons from both slice orientations to microdrops in at least one of the locations. This provided evidence that excitatory synapses are present in both transverse and longitudinal slices. 4. Substantial increases in EPSP frequency only occurred in neurons from longitudinal slices when glutamate was microapplied 200 micron or less from the recording site. In transverse slices, however, large increases in EPSP frequency were observed to glutamate microapplications at 200 or 400 micron. These data suggest that CA1 local excitatory connections project for longer distances in the transverse than in the longitudinal plane of section. 5. Increases in EPSP frequency, averaged across cells, did not differ significantly in the four microapplication sites in either transverse or longitudinal slices. Thus local excitation in CA1 does not appear to be asymmetrically arranged in the way suggested for CA3. 6. The densities of local excitatory circuits in CA1 versus CA3 were studied by quantitatively comparing glutamate-induced increases in EPSP frequency.(ABSTRACT TRUNCATED AT 400 WORDS)

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