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Total Activity Estimation of Hippocampal Slice Using Multi-Electrode Array

Multi-Electrode Array를 이용한 뇌 해마의 Total Activity 추산

  • Lee, Jeong-Chan (Department of Biomedical Engineering, Kyung Hee University) ;
  • Kim, Ji-Eun (Department of Biomedical Engineering, Kyung Hee University) ;
  • Cho, Chung-Yearn (Department of Medical Science, Graduate School of East-West Medical Science) ;
  • Son, Min-Sook (Department of Medical Science, Graduate School of East-West Medical Science) ;
  • Park, Kyung-Mo (Department of Biomedical Engineering, Kyung Hee University) ;
  • Park, Ji-Ho (Department of Medical Science, Graduate School of East-West Medical Science)
  • 이정찬 (경희대학교 동서의료공학과) ;
  • 김지은 (경희대학교 동서의료공학과) ;
  • 조정연 (경희대학교 동서의학대학원 의과학과) ;
  • 손민숙 (경희대학교 동서의학대학원 의과학과) ;
  • 박경모 (경희대학교 동서의료공학과) ;
  • 박지호 (경희대학교 동서의학대학원 의과학과)
  • Published : 2006.12.12

Abstract

Research on neural circuit is a difficult area due to complexity and inaccessibility. Due to recent developments, the research using multi-electrode array of cells or tissues has become an important research area. However, there are some difficulties to decode the submerged meaning from huge and complex neural data. Moreover, it needs a harmonic collaboration between informatics and bioscience. In this paper, we have developed a custom-designed signal processing technique for multi-electrode array measured neural responses induced by electrical stimuli to the hippocampal tissue slices of the rat brain. The raw data from hippocampal slice using the multi-electrode array system were saved in a computer. Then we estimated characteristic points in each channel and calculated the total activity. To estimate the points, we used the Polynomial Fitting Approximation Method. Using the calculated total activity, we could provide the histogram or pseudo-image matrix to help interpretation of results.

Keywords

References

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