基於碎形迭代法分析老鼠大腦運動區誘發電位的信號

Evoked Potential Analysis of Rat Motor Cortex Based on Iterated Function Systems

淩聖欽(Chuan Chin Lim)

指導教授 ： 駱榮欽

國立臺北科技大學/電資學院/電腦與通訊研究所/碩士(2014年)

https://doi.org/10.6841/NTUT.2014.00740

摘要

腦部神經信號一直以來是研究腦部功能的一項重要的訊息並持續了多達40年之久，目前有許多研究重點關於神經系統的傳輸，因此記錄與分析腦神經信號將助於了解腦部功能。本研究的目的是開發一套老鼠運動區誘發電位分析系統,藉以分析老鼠大腦運動區神經信號。本研究的實驗是先從老鼠腦部的運動區取得訊號，並利用獨立成份分析取得獨立訊號。假設大腦誘發各種動作的誘發電位都是由各種小動作的電位所組成，我們將訊號分成各種小動作訊號再以小波及迭代函數係統編碼各種動作的神經訊號。經由各種編碼方式與不同的動作結果分析運動區神經訊號與動作的關聯性。

關鍵字

碎形迭代法 ； 電訊號 ； 插值法 ； 獨立成分分析法

並列摘要

Brain research has been study for more than 40years and brain neurons signals is required for understanding brain functions. Motor cortex is the main part that controls actions. Therefore, recording and analyzing the brain neurons signals in the motor cortex will help to understand relationships between actions and brain neurons signals. In the study, we use multichannel electrode of micro-wire to obtain the neural signals from motor cortex of rats. Different kind of actions signals was classified and applied ICA for obtaining independent source signals. IFS were used to analyze relationships between neural signals and actions. Assume that an action is merged by neural signals that combined from different path and neuron signals of the nervous systems that produced by motor cortex, then we encode by inverse IFS . Different kind of actions is encoded by IFS. Analyze the results to understand the relationships between the neural signals and actions.

並列關鍵字

IFS ； Interpolation Functions ； ICA ； Electrophysiological signal

參考文獻

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