Energy flow accounts for the adaptive property of functional synapses

Wu, FuQiang; Guo, YiTong; Ma, Jun

doi:10.1007/s11431-023-2441-5

Cited by 36 publications

(2 citation statements)

References 78 publications

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“…As suggested in the recent works [44,45], membrane parameters or memristive parameters can be controlled by the energy flow to induce a mode transition when the inner energy level is beyond a threshold. To investigate the selfadaption in the dual memristive map, it requires that parameter a for the dual memristive map can be controlled by the energy flux in an adaptive way as follows…”

Section: Model and Schemementioning

confidence: 99%

An adaptive energy regulation in a memristive map linearized from a circuit with two memristive channels

Yang,

Zhou,

2024

Commun. Theor. Phys.

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The nonlinear circuits can show multistability when magnetic flux-dependent memristor (MFDM) or charge-sensitive memristor (CSM) is incorporated into one branch circuit, which is helpful for estimating magnetic or electric field effects. In this paper, two different kinds of memristors are incorporated into two branch circuits composed of a capacitor and a nonlinear resistor, thus a memristive circuit with double memristive channels is designed. The circuit equations are presented, and the dynamics in this oscillator with two memristive terms are discussed. Then the memristive oscillator is converted into a memristive map by applying linear transformation on the sampled time series for memristive oscillator. The Hamilton energy function for the memristive oscillator is obtained by using the Helmholtz theorem, and it can be mapped from the field energy of the memristive circuit. An energy function for the dual memristive map is suggested by imposing suitable weights on the discrete energy function. The dynamical behaviors of the new memristive map are investigated, and an adaptive law is proposed to regulate the firing mode in the memristive map. This work will provide theoretical basis and experimental guidance for oscillator-to-map transformation and discrete map energy calculation.

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Section: Model and Schemementioning

confidence: 99%

An adaptive energy regulation in a memristive map linearized from a circuit with two memristive channels

Yang,

Zhou,

2024

Commun. Theor. Phys.

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“…Biological neurons show distinct self-adaptive property and inner parameter adjustment or synaptic controllability are crucial for selecting suitable firing modes in fast way. Two recent works [32] claimed that the mode selection has close relation to energy level of the neuron, and then the shift in the energy level accounts for the mode selection in neural activities. When more neurons are clustered in the same region, continuous energy collection [33][34][35][36][37] or release will develop heterogeneity or defects in the local area of the neural network, and energy diversity enables parameter shift for keeping desynchronization between neurons [38][39][40].…”

Section: Introductionmentioning

confidence: 99%

Dynamics in a light-sensitive neuron with two capacitive variables

Wang,

Lv,

Zhang

et al. 2024

Phys. Scr.

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Involvement of two capacitive variables into neuron models provides better description of the cell membrane property and then the diversity effect of electromagnetic field inner and outer of the cell membrane can be estimated in clear way. Specific electric components can be combined to build equivalent neural circuits for reproducing similar neural activities under some self-adaptive control schemes. A phototube converts external light into electric stimuli and the injected energy is encoded to excite the cell membranes for presenting suitable firing patterns. Two capacitors are connected via a linear resistor for mimicking the energy exchange and changes of membrane potentials. Combination of memristor into an additive branch circuit of the neural circuit can estimate the effect of electromagnetic induction and energy absorption. The energy function H for this light-sensitive and memristive neuron is calculated in theoretical way, and the average energy function <H> can predict the occurrence of stochastic resonance, which can be confirmed by estimating the distribution of signal to noise ratios. The firing mode is relative to the energy value of the neuron, and a control law is suggested to control the mode transition in neural activities in an adaptive way.

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A discrete memristive neuron and its adaptive dynamics

Li,

Lv,

et al. 2024

Nonlinear Dyn

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Energy flow accounts for the adaptive property of functional synapses

Cited by 36 publications

References 78 publications

An adaptive energy regulation in a memristive map linearized from a circuit with two memristive channels

An adaptive energy regulation in a memristive map linearized from a circuit with two memristive channels

Dynamics in a light-sensitive neuron with two capacitive variables

A discrete memristive neuron and its adaptive dynamics

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