Coupling synchronization between photoelectric neurons by using memristive synapse

Guo, Yeye; Zhu, Zhigang; Ren, Guo-Dong

doi:10.1016/j.ijleo.2020.164993

Cited by 35 publications

(3 citation statements)

References 48 publications

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“…[21][22][23][24] Phototubes can convert optical signals into electrical signals. So neural circuits coupled with phototubes can be used as biophysical light-dependent neurons, [25][26][27][28] which have potential application value in the design of artificial eyes. Since the channel current through a Josephson junction depends on the external magnetic field, [29,30] the neuron circuit embedded in the Josephson junction can be used to sense the influence of the magnetic field.…”

Section: Introductionmentioning

confidence: 99%

Synchronization and firing mode transition of two neurons in a bilateral auditory system driven by a high–low frequency signal

Apata,

Tang 唐,

Zhou 周

et al. 2024

Chinese Phys. B

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The FitzHugh Nagumo neuron circuit integrates a piezoelectric ceramic to form a piezoelectric sensing neuron, which can capture external sound signals and simulate the auditory neuron system. Two piezoelectric sensing neurons are coupled by a parallel circuit consisting of a Josephson junction and a linear resistor, and a binaural auditory system is established. Considering the nonsingleness of external sound sources, the high-low frequency signal is used as input signal to study the firing mode transition and synchronization of this system. It is found that the angular frequency of the high-low frequency signal is a key factor in determining whether the dynamic behaviors of two coupled neurons are synchronous. When they are in synchronization at a specific angular frequency, the changes in physical parameters of the input signal and the coupling strength between them will not destroy their synchronization. In addition, the firing mode of two coupled auditory neurons in synchronization is affected by the characteristic parameters of high-low frequency signal, rather than the coupling strength. The asynchronous dynamic behavior and variations in firing modes will do harm to the auditory system. The findings will help determine the causes of hearing loss and devise functional assistive devices for patients.

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Section: Introductionmentioning

confidence: 99%

Synchronization and firing mode transition of two neurons in a bilateral auditory system driven by a high–low frequency signal

Apata,

Tang 唐,

Zhou 周

et al. 2024

Chinese Phys. B

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show abstract

“…Besides, adding special elements such as phototubes and thermistors will diversify the dynamics of the coupled system. Guo et al [43] testify that neurons exhibit multiple firing patterns under the influence of photocurrent and achieve complete synchronization. Fossi et al [44] couple two FHN neural circuits concurrently rely on light and temperature then find that the two neurons will showcase the same dynamics when the coupling channel parameters are selected with suitable values.…”

Section: Introductionmentioning

confidence: 99%

Switching motion analysis and synchronization control of a locally active memristive neuron model

Ren

Zhang

et al. 2023

Phys. Scr.

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In this paper, a new four-dimensional HR neuron model is developed by means of injecting external alternating current and introducing a locally active memristor to simulate the induced current in the synapse. Firstly, the stableness of the equilibrium points under alternating current injection is analyzed by using Matlab software, and it is found that the addition of alternating current makes the stableness distribution of equilibrium points vary between time intervals. Secondly, with the help of bifurcation diagrams and corresponding time response diagrams, the effect of induced current on the boundary dynamic behavior is investigated in detail, meanwhile, the conditions for switching motions on separated boundaries are revealed. Finally, the multi-neuron coupling synchronization is explored by setting the corresponding coupling model. The results are beneficial to understand the boundary dynamic mechanism of neurons.

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“…Some of them are hybrid synapse [16], Josephson junction synapse [17], memristive synapse [18], electrical synapse [19,20], and chemical synapse [21]. Following that, a large number of single neurons [22][23][24][25][26][27][28][29] and coupled neurons [27,[30][31][32][33][34][35][36][37][38][39][40][41][42] models have been introduced and addressed in the literature using the quoted artificial synapses.…”

Section: Introductionmentioning

confidence: 99%

Route to Chaos and Chimera States in a Network of Memristive Hindmarsh-Rose Neurons Model with External Excitation

Muni

Njitacke

Feudjio

et al. 2022

Chaos Theory and Applications

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In this paper we have introduced and investigated the collective behavior of a network of memristive Hindmarsh-Rose (HR) neurons. The proposed model was built considering the memristive autapse of the traditional 2D HR neuron. Using the one-parameter bifurcation diagram and its corresponding maximal Lyapunov exponent graph, we showed that the proposed model was able to exhibit a reverse period doubling route to chaos, phenomenon of interior and exterior crises. Three different configurations of the ring-star network of the memristive HR neuron model, including ring-star, ring, and star, have been considered. The study of those network configurations revealed incoherent, coherent , chimera and cluster state behaviors. Coherent behavior is characterized by synchronization of the neurons of the network, while incoherent behaviors are characterized by the absence of synchronization. Chimera states refer to a differet state where there is a coexistence of synchroniaed and asynchronized nodes of the network. One of the interesting result of the paper is the prevalence of double-well chimera states in both ring and ring-star network and has been first mentioned in the case of memrisitve HR neuron model.

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Coupling synchronization between photoelectric neurons by using memristive synapse

Cited by 35 publications

References 48 publications

Synchronization and firing mode transition of two neurons in a bilateral auditory system driven by a high–low frequency signal

Synchronization and firing mode transition of two neurons in a bilateral auditory system driven by a high–low frequency signal

Switching motion analysis and synchronization control of a locally active memristive neuron model

Route to Chaos and Chimera States in a Network of Memristive Hindmarsh-Rose Neurons Model with External Excitation

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