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Neurochip based on light-addressable potentiometric sensor with wavelet transform de-noising

机译:基于光寻址电位传感器的小波变换去噪神经芯片

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摘要

Neurochip based on light-addressable potentiometric sensor (LAPS), whose sensing elements are excitable cells, can monitor electrophysiological properties of cultured neuron networks with cellular signals well analyzed. Here we report a kind of neurochip with rat pheochromocytoma (PC12) cells hybrid with LAPS and a method of de-noising signals based on wavelet transform. Cells were cultured on LAPS for several days to form networks, and we then used LAPS system to detect the extracellular potentials with signals de-noised according to decomposition in the time-frequency space. The signal was decomposed into various scales, and coefficients were processed based on the properties of each layer. At last, signal was reconstructed based on the new coefficients. The results show that after de-noising, baseline drift is removed and signal-to-noise ratio is increased. It suggests that the neurochip of PC12 cells coupled to LAPS is stable and suitable for long-term and non-invasive measurement of cell electrophysiological properties with wavelet transform, taking advantage of its time-frequency localization analysis to reduce noise.
机译:基于光寻址电位传感器(LAPS)的神经芯片,其传感元件是可激发细胞,可以通过分析得很好的细胞信号来监测培养的神经元网络的电生理特性。在这里,我们报告一种与LAPS混合的大鼠嗜铬细胞瘤(PC12)细胞的神经芯片,以及一种基于小波变换的信号去噪方法。将细胞在LAPS上培养数天以形成网络,然后使用LAPS系统检测细胞外电位,该信号根据在时频空间中的分解而消噪。信号被分解为各种比例,并根据每一层的属性处理系数。最后,基于新系数重建信号。结果表明,去噪后,基线漂移被消除,信噪比增加。这表明与LAPS偶联的PC12细胞的神经芯片是稳定的,适合利用小波变换进行细胞电生理特性的长期和非侵入性测量,并利用其时频定位分析来降低噪声。

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