scholarly journals ONSET OF PHASE SYNCHRONIZATION IN NEURONS WITH CHEMICAL SYNAPSE

2007 ◽  
Vol 17 (10) ◽  
pp. 3545-3549 ◽  
Author(s):  
T. PEREIRA ◽  
M. S. BAPTISTA ◽  
J. KURTHS ◽  
M. B. REYES

We study the onset of synchronous states in realistic chaotic neurons coupled by mutually inhibitory chemical synapses. For the realistic parameters, namely the synaptic strength and the intrinsic current, this synapse introduces noncoherences in the neuronal dynamics, yet allowing for chaotic phase synchronization in a large range of parameters. As we increase the synaptic strength, the neurons reach a periodic state, and no chaotic complete synchronization is found.

2014 ◽  
Vol 519-520 ◽  
pp. 846-849
Author(s):  
Rui Xue Li ◽  
Yan Qiu Che ◽  
Ping Hao ◽  
Xiao Qin Li

Inhibitory chemical coupling connections are ubiquitous in neuronal system. In this paper, we first reduce the complex neuronal dynamics to a simple phase model by means of phase-model reduction method. Then we examine the roles of time delays extensively on the synchronization properties by bifurcation analysis and numerical simulation. Finally, we identify the existence and the stability of various phase-locked states. Along with the expected phase and anti-phase synchronization regimes, we find the emergent phenomena that significantly influence the synchronization behavior.


1995 ◽  
Vol 74 (1) ◽  
pp. 437-452 ◽  
Author(s):  
B. R. Johnson ◽  
J. H. Peck ◽  
R. M. Harris-Warrick

1. In the pyloric network of the lobster stomatogastric ganglion, graded synapses organize the network output. The amines dopamine (DA), serotonin, and octopamine each elicit a distinctive motor pattern from a quiescent pyloric network. We have examined the effects of these amines on the graded synaptic strengths between the six major types of neurons of this network to understand how amine modulation of synaptic strength contributes to the amine-induced motor patterns. Here we tested amine affects at 10 different graded chemical synapses of the pyloric network. We show that each amine has a statistically different spectrum of distributed effects across the network synapses. 2. Under our control conditions (isolated pairs of neurons, removal of modulatory input), most of the graded chemical synapses were weak and some synapses were nonfunctional. The output synapses of the ventricular dilator (VD) neuron were significantly stronger than the other synapses. 3. DA altered the synaptic strength of every graded chemical synapse. This amine strengthened the weak chemical output synapses of the anterior burster (AB), lateral pyloric (LP), and pyloric constrictor (PY) neurons and weakened (and in some cases abolished) the strong chemical output synapses of the VD neuron. The AB-->inferior cardiac neuron (IC) and PY-->IC graded chemical synapses were nonfunctional under our control conditions; DA activated these silent synapses. 4. Serotonin enhanced the AB's output chemical synapses but weakened all the other graded chemical synapses examined. Octopamine's effects were much weaker than those of the other two amines. It enhanced the AB-->LP synapse and the LP's output synapses and weakly strengthened the AB-->PY, VD-->LP, and VD-->PY synapses. 5. The amines alter the input resistance of many of the pyloric neurons, and this could contribute to the observed changes in synaptic strength by altering passive current flow between input and output sites in the cells. However, the input resistance changes were relatively small compared with the changes in synaptic strength and cannot alone account for the synaptic modulation. In some cases the sign of the input resistance change was inconsistent with the change in synaptic strength. Thus the amines appear to modify synaptic transmission directly in this system. 6. This study completes our description of amine effects on all the graded synapses of the pyloric network. We summarize our present and earlier work to show that modulators can reconfigure the entire synaptic organization of a neural network by acting at many distributed synaptic sites.(ABSTRACT TRUNCATED AT 400 WORDS)


2020 ◽  
Vol 16 (12) ◽  
pp. e1007974
Author(s):  
Bánk G. Fenyves ◽  
Gábor S. Szilágyi ◽  
Zsolt Vassy ◽  
Csaba Sőti ◽  
Peter Csermely

Graph theoretical analyses of nervous systems usually omit the aspect of connection polarity, due to data insufficiency. The chemical synapse network of Caenorhabditis elegans is a well-reconstructed directed network, but the signs of its connections are yet to be elucidated. Here, we present the gene expression-based sign prediction of the ionotropic chemical synapse connectome of C. elegans (3,638 connections and 20,589 synapses total), incorporating available presynaptic neurotransmitter and postsynaptic receptor gene expression data for three major neurotransmitter systems. We made predictions for more than two-thirds of these chemical synapses and observed an excitatory-inhibitory (E:I) ratio close to 4:1 which was found similar to that observed in many real-world networks. Our open source tool (http://EleganSign.linkgroup.hu) is simple but efficient in predicting polarities by integrating neuronal connectome and gene expression data.


2003 ◽  
Vol 28 (12) ◽  
pp. 1013 ◽  
Author(s):  
Muhan Choi ◽  
K. V. Volodchenko ◽  
Sunghwan Rim ◽  
Won-Ho Kye ◽  
Chil-Min Kim ◽  
...  

2002 ◽  
Vol 66 (1) ◽  
Author(s):  
Sunghwan Rim ◽  
Inbo Kim ◽  
Pilshik Kang ◽  
Young-Jai Park ◽  
Chil-Min Kim

2018 ◽  
Vol 16 (04) ◽  
pp. 525-563 ◽  
Author(s):  
Seung-Yeal Ha ◽  
Hwa Kil Kim ◽  
Jinyeong Park

The synchronous dynamics of many limit-cycle oscillators can be described by phase models. The Kuramoto model serves as a prototype model for phase synchronization and has been extensively studied in the last 40 years. In this paper, we deal with the complete synchronization problem of the Kuramoto model with frustrations on a complete graph. We study the robustness of complete synchronization with respect to the network structure and the interaction frustrations, and provide sufficient frameworks leading to the complete synchronization, in which all frequency differences of oscillators tend to zero asymptotically. For a uniform frustration and unit capacity, we extend the applicable range of initial configurations for the complete synchronization to be distributed on larger arcs than a half circle by analyzing the detailed dynamics of the order parameters. This improves the earlier results [S.-Y. Ha, H. Kim and J. Park, Remarks on the complete frequency synchronization of Kuramoto oscillators, Nonlinearity 28 (2015) 1441–1462; Z. Li and S.-Y. Ha, Uniqueness and well-ordering of emergent phase-locked states for the Kuramoto model with frustration and inertia, Math. Models Methods Appl. Sci. 26 (2016) 357–382.] which can be applicable only for initial configurations confined in a half circle.


2021 ◽  
Vol 16 (2) ◽  
Author(s):  
H. Shameem Banu ◽  
P.S. Sheik Uduman

This paper seeks to address the phase synchronization phenomenon using the drive-response concept, in our proposed model, State Controlled Cellular Neural Network (SC-CNN) based on variant of MuraliLakshmanan-Chua (MLCV) circuit. Using this unidirectionally coupled chaotic non autonomous circuits, we described the transition of unsynchronous to synchronous state, by numerical simulation method as well as the results are confirmed by solving explicit analytical solution. In this aspect, the system undergoes the new effect of phase synchronization (PS) phenomenon have been observed before complete synchronization (CS) state. To characterize these phenomena by the phase portraits and the time series plots. Also particularly characterize for PS by the method of partial Poincare section map using phase difference versus time, numerically and analytically. The study of dynamics involved in SC-CNN circuit systems, mainly applicable in the field of neurosciences and in telecommunication fields.


Electronics ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 153
Author(s):  
Balamurali Ramakrishnan ◽  
Mahtab Mehrabbeik ◽  
Fatemeh Parastesh ◽  
Karthikeyan Rajagopal ◽  
Sajad Jafari

A memristor is a vital circuit element that can mimic biological synapses. This paper proposes the memristive version of a recently proposed map neuron model based on the phase space. The dynamic of the memristive map model is investigated by using bifurcation and Lyapunov exponents’ diagrams. The results prove that the memristive map can present different behaviors such as spiking, periodic bursting, and chaotic bursting. Then, a ring network is constructed by hybrid electrical and chemical synapses, and the memristive neuron models are used to describe the nodes. The collective behavior of the network is studied. It is observed that chemical coupling plays a crucial role in synchronization. Different kinds of synchronization, such as imperfect synchronization, complete synchronization, solitary state, two-cluster synchronization, chimera, and nonstationary chimera, are identified by varying the coupling strengths.


2009 ◽  
Vol 3 (2) ◽  
Author(s):  
S. Thuvvakkadan ◽  
V. J. Nair

Silicon eye can be otherwise called as a complete eye implant. The project overview is given in brief by the description of main components. Here in the silicon eye, a biconcave gel lens is used in connection with a micro controller. A porous silicon nano photodiode is placed before the gel lens. This specially designed transparent diode will help in identifying the intensity of light receiving in the beginning of the processing chain. An effective drainage system (with the help of two valves) will control the working of gel lens. All these components together form the primary circuit to enable the process of auto focusing. The micro controller is connected with all components of the system. The primary circuit is connected to a secondary circuit which consists of an artificial silicon retina and a chemical synapse. By the combined and co-ordinate working of both these will enable vision. The power supply, which all the electrical components here need is given by a series of nano paper batteries placed beneath the retinal layer (carbon nano tubes can also be implemented instead or along with it). The converted electrical impulses (from intensity of light received) will be carried to the visual area of brain through optic nerve by the effective interaction with a number of artificial chemical synapses. Finally this silicon eye will be an effective implant for the damaged eye. And we are sure that this will be a great breakthrough in the modern medicine.


Author(s):  
Liang Guo ◽  
Shuai Zhang ◽  
Jiankang Wu ◽  
Xinyu Gao ◽  
Mingkang Zhao ◽  
...  

Transcranial magnetic-acoustic electrical stimulation (TMAES) is a new technology with ultrasonic waves and a static magnetic field to generate an electric current in nerve tissues to modulate neuronal firing activities. The existing neuron models only simulate a single neuron, and there are few studies on coupled neurons models about TMAES. Most of the neurons in the cerebral cortex are not isolated but are coupled to each other. It is necessary to study the information transmission of coupled neurons. The types of neuron coupled synapses include electrical synapse and chemical synapse. A neuron model without considering chemical synapses is not comprehensive. Here, we modified the Hindmarsh-Rose (HR) model to simulate the smallest nervous system—two neurons coupled electrical synapses and chemical synapses under TMAES. And the environmental variables describing the synaptic coupling between two neurons and the nonlinearity of the nervous system are also taken into account. The firing behavior of the nervous system can be modulated by changing the intensity or the modulation frequency. The results show that within a certain range of parameters, the discharge frequency of coupled neurons could be increased by altering the modulation frequency, and intensity of stimulation, modulating the excitability of neurons, reducing the response time of chemical postsynaptic neurons, and accelerating the information transferring. Moreover, the discharge frequency of neurons was selective to stimulus parameters. These results demonstrate the possible theoretical regulatory mechanism of the neurons' firing frequency characteristics by TMAES. The study establishes the foundation for large-scale neural network modeling and can be taken as the theoretical basis for TMAES experimental and clinical application.


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