Chronic electrical stimulation induces functional network changes in cortical neuron cultures

Wu, SongFang; Wang, Lu-Bin; Zhao, Yuwei; Sun, Honghao; Lang, Yiran; Wang, Changyong; Han, Jianming; Wang, Yan; Han, Yifeng

doi:10.1007/s11431-019-1442-2

Cited by 6 publications

(1 citation statement)

References 48 publications

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“…Experimental detection is crucial for model approach and improvement for biophysical neuron models. Generic neuron models in mathematical form provide an effective dynamical analysis and prediction of mode selection under external stimuli including electromagnetic radiation and mechanical excitation [6][7][8][9][10]. Indeed, complex physical effect should be considered into the neural activities during stochastic diffusion of intracellular ions and exchange between intracellular and extracellular ions across ion channels in the cell membrane.…”

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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