用回歸方法分析文字與動詞文法辨認的腦電資料;Regression-based analysis of EEG activity elicited by orthographic and verb grammar recognition

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Title:	用回歸方法分析文字與動詞文法辨認的腦電資料;Regression-based analysis of EEG activity elicited by orthographic and verb grammar recognition
Authors:	伍禹丞;Wu, Yu-Chen
Contributors:	認知與神經科學研究所
Keywords:	腦電儀;視覺展頻誘發電位;回歸事件相關電位;詞彙效應;文法合理性;EEG;VESPA;ERP;rERP
Date:	2023-08-17
Issue Date:	2024-09-19 16:56:50 (UTC+8)
Publisher:	國立中央大學
Abstract:	本研究旨在探討腦電儀(electroencephalography, EEG)實驗的新流程:視覺展頻誘發電位(Visually-Evoked Spread Spectrum Response Potential, VESPA)以及新分析方法:回歸事件相關電位(regression Event-related Potential, rERP)應用於語言實驗的效果。傳統的事件相關電位(Event-related Potential, ERP)需要收集大量試題以進行平均法降噪，而且流程需要重複多次，這可能導致受試者感到無聊或疲倦。為了克服這些限制，本研究引入了VESPA和rERP方法，以減少實驗流程的時間，同時確保結果的可靠性。本研究採用了兩種不同類型的語言刺激，一種是真字、非字和符號辨認，一種是動詞文法辨認。神經語言學的研究已經顯示字形、語意、可預期性、表音一致性等現象影響事件關聯電位的振幅。這些現象可以用於解釋詞彙效應和文法合理性的大腦機制。因此，本研究觀察的依變項是N100、N170、P200以及N400這4個特徵區段。本研究為首次將VESPA和rERP應用於語言實驗中，並對比了這些方法之間與傳統ERP的差異。為了比較效果進行了相關性分析，結果顯示這些方法在數據分析方面具有高度相似性。這表明在減少流程時間的同時，仍能保持乾淨且與傳統流程相似的數據。此外，符號刺激具有最高的相關性，這意味著在使用VESPA方法時，越簡單且需要較少認知負荷的刺激更為適合。本研究的結果表明VESPA和rERP能成為更高效的流程與分析方法。這些方法的應用將使研究人員能夠進一步規劃更廣泛的實驗設計，同時有效地消除底噪，使顯著差異更加明顯。未來的研究可以基於這些發現進一步探索語言學習研究、臨床實踐和其他研究領域的議題。 ;This study aimed to investigate the effects of Visually-Evoked Spread Spectrum Response Potential (VESPA), a new procedure, and regression Event-related Potential (rERP), a analysis method, in language experiments using electroencephalography (EEG). Traditional Event-related Potentials (ERP) often require a large number of trials for averaging, resulting in time-consuming and potentially tedious procedures. To address these limitations, VESPA and rERP were introduced to streamline the experimental process while ensuring reliable outcomes. The study employed two contexts of language stimuli: orthographic forms (including symbols, nonwords and real words) and verbs with grammatical or ungrammatical suffixes. Dependent variables were mean amplitudes of four ERP components, including N100, N170, P200, and N400. Notably, the present study was the first one applying VESPA paradigm and rERP analyses to investigate language processes. It is essential to compare them with traditional ERP methods Correlation analysis was conducted to assess the effectiveness of these approaches, revealing a high degree of similarity in data analysis. These findings indicate that VESPA and rERP can yield clean and comparable data to traditional procedures, while also reducing the duration of the experiments. Moreover, symbol stimuli exhibited the strongest correlation, suggesting that simpler stimuli with lower cognitive load are particularly suitable when employing the VESPA method. The results of this study underscore the potential of VESPA and rERP as efficient procedures and analysis methods applicable to a wide range of domains, including language learning research and clinical practice. By implementing these methods, researchers can design more comprehensive experiments while effectively eliminating baseline noise, thereby making significant differences more discernible. Future research can build upon these findings to further refine visual stimulus procedures and analysis methods.
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