Study of neuronal spike-frequency adaptation with transcranial magneto-acoustical stimulation_Journal of Biomedical Engineering

Authors：

 YUAN Yi ¹ , PANG Na ¹ , CHEN Yudong ¹ , SUN Hongbao ¹ , LI Xiaoli ^2,3

1. Institute of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei 066004, P.R.China;
2. State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, P.R.China;
3. Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing 100875, P.R.China;

Corresponding author：

YUAN Yi, Email: yuanyi513@ysu.edu.cn

Keywords：

transcranial magneto-acoustical stimulation; spike-frequency adaption; Ermentrout model

DOI：

10.7507/1001-5515.201609042

Video：

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Abstract Full text Figures/Tables Video References Cited by

Transcranial magneto-acoustical stimulation (TMAS), utilizing focused ultrasound and a magnetostatic field to generate an electric current in tissue fluid to regulate the activities of neurons, has high spatial resolution and penetration depth. The neuronal spike-frequency adaptation plays an important role in the treatment of neural information. In this paper, we study the effects of ultrasonic intensity, magnetostatic field intensity and ultrasonic frequency on the neuronal spike-frequency adaptation based on the Ermentrout neuron model. The simulation results show that, the peak time interval becomes smaller, the interspike interval becomes shorter and the time of the firing of the neuron is shortened with the increasing of the magnetostatic field intensity. With the increase of the adaptive variables, the initial spike-frequency is shifted to the right with the magnetostatic field intensity, and the spike-frequency is linearly related to the increase of the magnetostatic field intensity in steady state. The simulation effect with change of the ultrasonic intensity is consistent with the change of magnetostatic field intensity. The change of the ultrasonic frequency has no effect on the neuronal spike-frequency adaptation. Under the different adaptive variables, with the increase of the adaptive variables, the initial spike-frequency amplitude decreased with the increasing of the ultrasonic frequency, and the spike-frequency is linearly related to the increase of the ultrasonic frequency in steady state. These results of the study can help us to reveal the mechanism of transcranial magneto-acoustical stimulation on the neuronal spike-frequency adaptation, and provide a theoretical basis for its application in the treatment of neurological disorders.

Citation： YUAN Yi, PANG Na, CHEN Yudong, SUN Hongbao, LI Xiaoli. Study of neuronal spike-frequency adaptation with transcranial magneto-acoustical stimulation. Journal of Biomedical Engineering, 2017, 34(6): 934-941. doi: 10.7507/1001-5515.201609042 Copy

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4.	Yuan Yi, Chen Yudong, Li Xiaoli. Theoretical analysis of transcranial Magneto-Acoustical stimulation with Hodgkin-Huxley neuron model. Front Comput Neurosci, 2016, 10: 35.
5.	王宝燕, 徐伟, 邢真慈. 外界电场激励下的耦合 FitzHugh-Nagumo 神经元系统的放电节律研究. 物理学报, 2009, 58(9): 6590-6595.
6.	杨卓琴. 神经元电活动不同节律模式的几种变化过程. 物理学报, 2010, 59(8): 5319-5324.
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8.	袁春华, 王江. 交流电场下神经元适应性的两种放电机制对比分析. 东北大学学报:自然科学版, 2014, 35(9): 1229-1233.
9.	马军, 苏文涛, 高加振. Hindmarsh-Rose 混沌神经元自适应同步和参数识别的优化研究. 物理学报, 2010, 59(3): 1554-1561.
10.	韩春晓, 王江, 常莉, 等. 外电场作用下改进的 Leaky Integrate-And-Fire 模型的峰放电频率适应性研究. 动力学与控制学报, 2013, 11(1): 46-52.
11.	Lancaster B, Nicoll R A. Properties of two calcium-activated hyperpolarizations in rat hippocampal neurones. J Physiol, 1987, 389(1): 187-203.
12.	Ahmed B, Anderson J C, Douglas R J, et al. Estimates of the net excitatory currents evoked by visual stimulation of identified neurons in cat visual cortex. Cereb Cortex, 1998, 8(5): 462-476.
13.	Lorenzon N M, Foehring R C. Relationship between repetitive firing and afterhyperpolarizations in human neocortical neurons. J Neurophysiol, 1992, 67(2): 350-363.
14.	Brown D A, Adams P R. Muscarinic suppression of a novel voltage-sensitive K⁺ current in a vertebrate neurone. Nature, 1980, 283(5748): 673-676.
15.	Sah P. Ca²⁺-activated K⁺ currents in neurones: types, physiological roles and modulation. Trends Neurosci, 1996, 19(4): 150-154.
16.	Wang Xiaojing, Liu Yinghui, Sanchez-Vives M V, et al. Adaptation and temporal decorrelation by single neurons in the primary visual cortex. J Neurophysiol, 2003, 89(6): 3279-3293.
17.	Norton S J. Can ultrasound be used to stimulate nerve tissue? Biomed Eng Online, 2003, 2(1): 1-9.
18.	Montalibet A, Jossinet J, Matias A, et al. Electric current generated by ultrasonically induced Lorentz force in biological media. Med Biol Eng Comput, 2001, 39(1): 15-20.
19.	Grasland-Mongrain P, Mari J M, Chapelon J Y, et al. Lorentz force electrical impedance tomography[J]. IRBM, 2013, 34(4): 357-360.
20.	常莉. 极低频外电场作用下神经元网络适应性的研究. 天津: 天津大学, 2012.

1. 金淇涛, 王江, 伊国胜, 等. 经颅磁刺激感应外电场作用下最小神经元模型放电起始动态机理分析. 物理学报, 2012, 61(11): 118701-1-118701-9.
2. Tufail Y, Yoshihiro A, Pati S, et al. Ultrasonic neuromodulation by brain stimulation with transcranial ultrasound. Nat Protoc, 2011, 6(9): 1453-1470.
3. Plaksin M, Shoham S, Kimmel E. Intramembrane cavitation as a predictive bio-piezoelectric mechanism for ultrasonic brain stimulation. Phys Rev X, 2014, 4(1): 011004.
4. Yuan Yi, Chen Yudong, Li Xiaoli. Theoretical analysis of transcranial Magneto-Acoustical stimulation with Hodgkin-Huxley neuron model. Front Comput Neurosci, 2016, 10: 35.
5. 王宝燕, 徐伟, 邢真慈. 外界电场激励下的耦合 FitzHugh-Nagumo 神经元系统的放电节律研究. 物理学报, 2009, 58(9): 6590-6595.
6. 杨卓琴. 神经元电活动不同节律模式的几种变化过程. 物理学报, 2010, 59(8): 5319-5324.
7. Song Yanli. Dynamical behaviour of FitzHugh-Nagumo neuron model driven by harmonic noise. Acta Physica Sinica, 2010, 59(4): 2334-2338.
8. 袁春华, 王江. 交流电场下神经元适应性的两种放电机制对比分析. 东北大学学报:自然科学版, 2014, 35(9): 1229-1233.
9. 马军, 苏文涛, 高加振. Hindmarsh-Rose 混沌神经元自适应同步和参数识别的优化研究. 物理学报, 2010, 59(3): 1554-1561.
10. 韩春晓, 王江, 常莉, 等. 外电场作用下改进的 Leaky Integrate-And-Fire 模型的峰放电频率适应性研究. 动力学与控制学报, 2013, 11(1): 46-52.
11. Lancaster B, Nicoll R A. Properties of two calcium-activated hyperpolarizations in rat hippocampal neurones. J Physiol, 1987, 389(1): 187-203.
12. Ahmed B, Anderson J C, Douglas R J, et al. Estimates of the net excitatory currents evoked by visual stimulation of identified neurons in cat visual cortex. Cereb Cortex, 1998, 8(5): 462-476.
13. Lorenzon N M, Foehring R C. Relationship between repetitive firing and afterhyperpolarizations in human neocortical neurons. J Neurophysiol, 1992, 67(2): 350-363.
14. Brown D A, Adams P R. Muscarinic suppression of a novel voltage-sensitive K⁺ current in a vertebrate neurone. Nature, 1980, 283(5748): 673-676.
15. Sah P. Ca²⁺-activated K⁺ currents in neurones: types, physiological roles and modulation. Trends Neurosci, 1996, 19(4): 150-154.
16. Wang Xiaojing, Liu Yinghui, Sanchez-Vives M V, et al. Adaptation and temporal decorrelation by single neurons in the primary visual cortex. J Neurophysiol, 2003, 89(6): 3279-3293.
17. Norton S J. Can ultrasound be used to stimulate nerve tissue? Biomed Eng Online, 2003, 2(1): 1-9.
18. Montalibet A, Jossinet J, Matias A, et al. Electric current generated by ultrasonically induced Lorentz force in biological media. Med Biol Eng Comput, 2001, 39(1): 15-20.
19. Grasland-Mongrain P, Mari J M, Chapelon J Y, et al. Lorentz force electrical impedance tomography[J]. IRBM, 2013, 34(4): 357-360.
20. 常莉. 极低频外电场作用下神经元网络适应性的研究. 天津: 天津大学, 2012.

Journal of Biomedical Engineering

Study of neuronal spike-frequency adaptation with transcranial magneto-acoustical stimulation

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