Article

Journal of Zhejiang University SCIENCE B

, Volume 11, Issue 5, pp 323-331

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

  • Qing-jun LiuAffiliated withBiosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, Zhejiang UniversityState Key Laboratory of Transducer Technology, Chinese Academy of Sciences
  • , Wei-wei YeAffiliated withBiosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, Zhejiang University
  • , Hui YuAffiliated withBiosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, Zhejiang University
  • , Ning HuAffiliated withBiosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, Zhejiang University
  • , Li-ping DuAffiliated withBiosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, Zhejiang University
  • , Ping WangAffiliated withBiosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, Zhejiang UniversityState Key Laboratory of Transducer Technology, Chinese Academy of Sciences Email author 

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Abstract

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.

Key words

Neurochip Light-addressable potentiometric sensor (LAPS) Wavelet transform Threshold De-noising

CLC number

Q27