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Quantitative evaluation of extrinsic factors influencing electrical excitability in neuronal networks: Voltage Threshold Measurement Method (VTMM)

摘要The electrical excitability of neural networks is influenced by different environmental factors.Effective and simple methods are required to objectively and quantitatively evaluate the influence of such factors,including variations in temperature and pharmaceutical dosage.The aim of this paper was to introduce ‘the voltage threshold measurement method',which is a new method using microelectrode arrays that can quantitatively evaluate the influence of different factors on the electrical excitability of neural networks.We sought to verify the feasibility and efficacy of the method by studying the effects of acetylcholine,ethanol,and temperature on hippocampal neuronal networks and hippocampal brain slices.First,we determined the voltage of the stimulation pulse signal that elicited action potentials in the two types of neural networks under normal conditions.Second,we obtained the voltage thresholds for the two types of neural networks under different concentrations of acetylcholine,ethanol,and different temperatures.Finally,we obtained the relationship between voltage threshold and the three influential factors.Our results indicated that the normal voltage thresholds of the hippocampal neuronal network and hippocampal slice preparation were 56 and 31 mV,respectively.The voltage thresholds of the two types of neural networks were inversely proportional to acetylcholine concentration,and had an exponential dependency on ethanol concentration.The curves of the voltage threshold and the temperature of the medium for the two types of neural networks were U-shaped.The hippocampal neuronal network and hippocampal slice preparations lost their excitability when the temperature of the medium decreased below 34 and 33℃ or increased above 42 and 43℃,respectively.These results demonstrate that the voltage threshold measurement method is effective and simple for examining the performance/excitability of neuronal networks.

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作者单位 State Key Laboratory of Bioelectronics, Southeast University, Nanjing, Jiangsu Province, China [1] State Key Laboratory of Bioelectronics, Southeast University, Nanjing, Jiangsu Province, China;Co-innovation Center of Neuroregeneration, Nantong University, Nantong, Jiangsu Province, China [2] Institute of RF-& OE-ICs, Southeast University, Nanjing, Jiangsu Province, China;Co-innovation Center of Neuroregeneration, Nantong University, Nantong, Jiangsu Province, China [3]
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DOI 10.4103/1673-5374.233446
发布时间 2018-10-12(万方平台首次上网日期,不代表论文的发表时间)
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中国神经再生研究(英文版)

中国神经再生研究(英文版)

2018年13卷6期

1026-1035页

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