Frontiers in Computational Neuroscience (Aug 2022)

Response of a neuronal network computational model to infrared neural stimulation

  • Jinzhao Wei,
  • Jinzhao Wei,
  • Licong Li,
  • Licong Li,
  • Hao Song,
  • Hao Song,
  • Zhaoning Du,
  • Zhaoning Du,
  • Jianli Yang,
  • Jianli Yang,
  • Mingsha Zhang,
  • Mingsha Zhang,
  • Mingsha Zhang,
  • Xiuling Liu,
  • Xiuling Liu

DOI
https://doi.org/10.3389/fncom.2022.933818
Journal volume & issue
Vol. 16

Abstract

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Infrared neural stimulation (INS), as a novel form of neuromodulation, allows modulating the activity of nerve cells through thermally induced capacitive currents and thermal sensitivity ion channels. However, fundamental questions remain about the exact mechanism of INS and how the photothermal effect influences the neural response. Computational neural modeling can provide a powerful methodology for understanding the law of action of INS. We developed a temperature-dependent model of ion channels and membrane capacitance based on the photothermal effect to quantify the effect of INS on the direct response of individual neurons and neuronal networks. The neurons were connected through excitatory and inhibitory synapses and constituted a complex neuronal network model. Our results showed that a slight increase in temperature promoted the neuronal spikes and enhanced network activity, whereas the ultra-temperature inhibited neuronal activity. This biophysically based simulation illustrated the optical dose-dependent biphasic cell response with capacitive current as the core change condition. The computational model provided a new sight to elucidate mechanisms and inform parameter selection of INS.

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