本文關鍵詞： 膜片鉗技術 反卷積 系統(tǒng)辨識 白噪聲 互相關技術 子空間法 自動補償　出處：《華中科技大學》2012年博士論文　論文類型：學位論文

【摘要】：膜片鉗技術是細胞離子通道記錄方法的金標準。20年來，，神經科學的發(fā)展體現(xiàn)出與信息技術（計算機）越發(fā)緊密結合的趨勢，而膜片鉗技術中計算機的參與度相對較低。膜片鉗技術中的信號處理主要使用模擬電路中的概念，如濾波、檢波、補償?shù)�。為了適應神經科學發(fā)展的總體趨勢，本文致力于以膜片鉗系統(tǒng)的數(shù)學模型為基礎，為膜片鉗的信號處理引入正、逆問題的概念，以便經典的膜片鉗技術從現(xiàn)代信息技術的豐碩成果中獲益。 本文的工作主要有兩點：1）討論膜片鉗放大器、電極、細胞構成的統(tǒng)一電系統(tǒng)的數(shù)學模型，并總結膜片鉗電路設計及信號處理中的正問題和逆問題；2）對于膜片鉗系統(tǒng)中的逆問題用反卷積進行描述，并提出采用白噪聲驅動的時間序列分析及基于子空間的系統(tǒng)辨識法對反卷積問題進行求解。 用正、逆問題的概念對膜片鉗技術中信號處理問題進行分類，可使信號之間的關系更為清晰，使問題的描述更系統(tǒng)，使問題的求解有堅實的理論基礎和可借鑒的方法。 根據正、逆問題的基本概念，細胞通道電流記錄本質上是個逆問題（信號還原）。若細胞以單室模型建模，通道電流與膜電容被動響應電流相并聯(lián)。于是，通道電流的求解可看作加法問題的逆問題，即減法問題。待減去的膜電容電流，其大小與膜電容參數(shù)有關，從測量數(shù)據獲得膜電容參數(shù)信息是個逆問題（系統(tǒng)辨識）。 線性時不變系統(tǒng)中的逆問題就是反卷積。反卷積的求解以數(shù)學模型為基礎。本文討論了膜片鉗放大器和細胞構成的電系統(tǒng)的若干種數(shù)學模型，如微分方程模型、傳遞函數(shù)模型、卷積模型和狀態(tài)空間方程模型，以及它們之間的關系。文章從信號與系統(tǒng)的角度，討論了膜片鉗實驗中的幾個典型的反卷積問題，包括信號復原和系統(tǒng)辨識。 受基于ARMA模型的時間序列分析的啟發(fā)，可用白噪聲激勵膜片鉗系統(tǒng)，通過互相關技術求解系統(tǒng)的時域特性，即沖激響應（本文中稱為卷積核），并開發(fā)了基于卷積核的非迭代快電容自動補償算法——K-method；為了確定膜片鉗探頭反饋電阻的雜散電容，可采用子空間法對其進行系統(tǒng)辨識，并以此為基礎開發(fā)了高值串聯(lián)電阻估計方法和軟件高頻補償方法——SHB。本文詳細介紹了這些具體應用的原理和實現(xiàn)步驟。相比原迭代方法，K-method具有簡單、準確、抗飽和的優(yōu)點；SHB有利于減小膜片鉗體積、提高膜片鉗的集成度。 本文工作不但為膜片鉗技術結合現(xiàn)代信號處理技術打下了理論基礎，還提供了兩個具體范例展示了膜片鉗技術的發(fā)展方向。
[Abstract]:Patch clamp technology is the gold standard of cell ion channel recording. In the past 20 years, the development of neuroscience has shown a trend of closer integration with information technology (computer). The signal processing in patch clamp technology mainly uses the concept of analog circuit, such as filtering, detection, compensation, etc. In order to adapt to the general trend of neuroscience development. Based on the mathematical model of patch clamp system, this paper introduces the concepts of forward and inverse problems for the signal processing of patch clamp, so that the classical patch clamp technology can benefit from the fruitful results of modern information technology. In this paper, there are two points: 1) the mathematical model of the unified electrical system composed of patch clamp amplifier, electrode and cell is discussed, and the forward and inverse problems in the design of patch clamp circuit and signal processing are summarized. 2) the inverse problem in patch clamp system is described by deconvolution, and the white noise-driven time series analysis and system identification method based on subspace are proposed to solve the deconvolution problem. Using the concepts of positive and inverse problems to classify the signal processing problems in patch clamp technology can make the relationship between signals clearer and the description of problems more systematic. So that the solution of the problem has a solid theoretical basis and can be used for reference. According to the basic concepts of forward and inverse problems, the recording of cell channel current is essentially an inverse problem (signal reduction). If the cell is modeled by a single cell model, the channel current is parallel with the passive response current of membrane capacitance. The solution of channel current can be regarded as the inverse problem of the addition problem, that is, the subtraction problem. The magnitude of the membrane capacitance current to be subtracted is related to the parameters of the membrane capacitance. It is an inverse problem to obtain membrane capacitance parameter information from measurement data (system identification). The inverse problem in linear time-invariant system is deconvolution. The solution of deconvolution is based on mathematical model. In this paper, some mathematical models of electric system composed of patch clamp amplifier and cell are discussed. For example, differential equation model, transfer function model, convolution model and state space equation model, and their relations. Several typical deconvolution problems in patch clamp experiments, including signal recovery and system identification, are discussed. Inspired by the time series analysis based on ARMA model, white noise excited patch clamp system can be used to solve the time-domain characteristics of the system by cross-correlation technique, that is, impulse response (in this paper called convolution kernel). A non-iterative fast capacitor compensation algorithm based on convolution kernels is developed. In order to determine the stray capacitance of the feedback resistance of the patch clamp probe, the subspace method can be used to identify the system. On this basis, the high value series resistance estimation method and the software high frequency compensation method, SHB, are developed. The principle and implementation steps of these specific applications are introduced in detail, compared with the original iterative method. K-method has the advantages of simplicity, accuracy and anti-saturation. SHB can reduce the size of patch clamp and improve the integration of patch clamp. This work not only lays a theoretical foundation for patch clamp technology combined with modern signal processing technology, but also provides two concrete examples to show the development direction of patch clamp technology.
【學位授予單位】：華中科技大學
【學位級別】：博士
【學位授予年份】：2012
【分類號】：R329

【共引文獻】

相關期刊論文 前10條

1 趙剡,宗云花,張世軍,楊秋英;氣動光學效應降晰函數(shù)辨識與圖像復原[J];兵工學報;2005年02期

2 周宏潮;王正明;劉洋;;基于邊緣保護的正則化超分辨重構技術[J];兵工學報;2006年06期

3 宋義剛;肖亮;韋志輝;黃麗麗;;光學遙感圖像變量分裂迭代快速復原算法[J];兵工學報;2012年03期

4 趙剡;李東興;許東;;抑制復原圖像振鈴波紋的頻域循環(huán)邊界算法[J];北京航空航天大學學報;2006年11期

5 趙文哲;秦世引;;一種高精度視頻目標檢測與分割新方法[J];北京航空航天大學學報;2010年12期

6 劉揚陽,金偉其,蘇秉華;數(shù)字圖像去模糊處理算法的對比研究[J];北京理工大學學報;2004年10期

7 朱亞平;沈庭芝;王心一;;基于小波域分類隱馬爾可夫樹模型的圖像恢復[J];北京理工大學學報;2006年05期

8 韓曼;劉曉華;孫娜;杜劍青;;電刺激延髓外側網狀核對大鼠心臟-軀體運動反射的下行性抑制作用及其機制[J];吉林大學學報(醫(yī)學版);2012年03期

9 胡曉紅;陳大卿;;基于變分偏微分方程的雙參數(shù)圖像去噪模型[J];重慶郵電大學學報(自然科學版);2012年03期

10 宋海英;胡蓉;;勻速直線運動模糊圖像點擴展函數(shù)的識別方法[J];成都電子機械高等專科學校學報;2012年01期

相關會議論文 前10條

1 李e鹲

本文編號：1489299