多細胞神經動作電位之分析:由單一細胞到神經群

Abstract

Ensemble recording是當代的趨勢，神經科學研究者可利用此記錄方法，來同時觀察大腦一個特定區域中所有的神經元的動作電位，進而了解一群神經元的功能。由ensemble recording所得的資料包含多個神經元的動作電位，並非肉眼可輕易辨識，而是必須經過電腦軟體的處理和分析。在神經電生理的研究上，本實驗室多年來皆以研究大鼠的體感覺所誘發的反應為重心。本篇論文主要探討對此種多細胞反應的分析及關於擷取此神經訊號的介面的開發。 由於訊號特性不同，分析誘發性的多細胞動作電位的技術迥異於分析自發性的動作電位。雖然動作電位的分析（稱為spike sorting）已經有很多相關文獻，但幾乎沒有提供適用於誘發性這種複雜的動作電位的分析方法。分析的第一個步驟是偵測，在此步驟本論文修改了一種已知的偵測方式(cumulative energy difference ,CED)，暫且稱為modified CED，並比較了修改前後所偵測到的棘波(spikes)在數量上和轉折數上有無顯著的差異，而其中的轉折次數也是本論文所提出的比較方法。後續的分析步驟本論文採用目前普遍流行的主成分分析法(principal component analysis, PCA)和k-means. 本論文所完成的訊號擷取介面可記錄多通道的神經動作電位和場電位，也可擷取記錄在錄音帶中的資料，並有計數器可直接計算神經細胞的放電頻率。在我們的實驗中，神經反應是由刺激器所誘發，而所有的訊號擷取功能皆可配合刺激器的觸發。 我們曾經使用過兩套具備記錄和分析的市售產品，並與本論文所開發的系統比較。結果顯示商業產品並不適合記錄和處理誘發性神經訊號，而自行開發的軟體較符合這項的需求。目前多神經細胞的動作電位分析軟體已經完成，我們仍不斷改進此軟體並引進新的分析方法。

The advance of ensemble recording makes it possible to simultaneously observe the neuronal activities of a specific brain area and has been a trend in neuroscience. The data from ensemble recording are multi-unit action potentials (APs), which need computer software to analyze before giving useful information. In our laboratory, we have focused on studying evoked responses. This thesis is mainly about developing software for the analysis of multi-unit APs, i.e. spike sorting. A data acquisition (DAQ) interface is also developed in this thesis. We found that evoked multi-unit analysis is very different from analyzing high SNR spontaneous neural signals. First, we finished the ordinary sorting methods and applied to our data. Principal component analysis (PCA) and k-means were used to identify units from the detected spikes. Then, we improved the spikes detection, which is the first step of spike sorting. By using modified cumulative energy difference (CED), the detection of multi-unit action potentials was refined to have better discrimination. Further, to see if this detection has significant differences to the original CED, we compared the numbers and the flips of spikes collected by these two detections. The DAQ interfaces we developed have functions of counters for firing rate counting, tape play back, and multi-channel acquisitions of action potentials and/or field potentials. All of these functions support triggers from the stimulators for synchronized responses. We compared our program to two commercial products, which records and analyzes spontaneous APs. They are less suitable for our experiments because they don’t support triggered recording. Our spike sorting was developed for evoked APs, which are usually overlapped with each other. Further, we are still improving our spike sorting program and trying to include new appropriate techniques.