The electrophysiological correlates of working memory-load effects in operation span task and symmetry span task

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：52

、訪客IP：3.137.175.166

姓名

莊凱淯(Kai-Yu Chuang) 查詢紙本館藏

畢業系所

認知與神經科學研究所

論文名稱

(The electrophysiological correlates of working memory-load effects in operation span task and symmetry span task)

相關論文

★ 時間及空間對注意力暫失的影響以及其可能的神經生理機制	★ 注意力分配及眼球運動準備歷程對於眼動潛伏時間與眼動軌跡的影響
★ 注意力暫失中的數字表徵: 數字距離對注意力暫失的影響	★ 利用跨顱磁刺激探討主動式注意力攫取的神經機制
★ 以數學模型及跨顱磁刺激探討注意力分配及眼球運動準備歷程	★ 學齡前兒童之視覺注意力發展及電腦化注意力訓練效果之探討
★ 以跨顱磁刺激探討左側下部頂葉以及左側上部頂葉的功能在中文處理中所扮演的角色	★ 性侵害犯的衝動行為表現-情緒狀態如何影響性侵害犯的抑制能力？
★ 學齡前階段孩童眼動抑制能力的發展和特性	★ 學齡前階段孩童衝突解決和動作反應抑制能力的發展
★ 6歲孩童與成人在數字和具體數量上的自動化處理	★ 期望效果之影響與可能的神經機制
★ Attentional reorienting: the dynamic interaction between goal-directed and stimulus-driven attentioinal control	★ 前額葉眼動區在視覺搜尋作業上對不同干擾物特徵與顯示時間扮演的角色
★ Roles of the Pre-supplementary Motor Area and Right Inferior Frontal Gyrus in Stimulus Selective Stop-signal task: A Theta Burst Transcranial!Magnetic! Stimulation!Study	★ Investigation of posterior parietal cortex visuospatial control over processing in near and far space using transcranial magnetic stimulation

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

複雜廣度測驗(complex span task)常被用於測量工作記憶容量，此測驗為複合式測驗，其中包含了干擾子測驗以及記憶子測驗，其特點在於干擾子測驗的作答時間長度會隨著不同的受試者而改變，進而達到更準確測量出每個人工作記憶容量的目的，然而，在進行測驗當下的過程與電生理訊號相關性仍不清楚。先前關於複雜廣度測驗的電生理訊號研究並沒有在不同的工作記憶負荷(working memory-load)下發現差異，本研究認為有兩項可能的因素導致此結果，首先為過去的研究固定了每位受試者干擾子測驗呈現的時間，這可能造成該測驗沒辦法準確的測量出每個人的工作記憶容量。第二，過去的研究所使用的分析方法主要用來分析線性的數據，用以分析非線性的腦波訊號可能不是那麼合適。因此本研究主要探討在使用希爾伯特-黃轉換(Hilbert-Huang Transform, HHT)的總體經驗模態分解法(ensemble empirical mode decomposition, EEMD)分析複雜廣度測驗在腦電波訊號上是否與其他工作記憶測驗一樣在工作記憶負荷上呈現差異。我們假設隨著工作記憶負荷的增加，在腦波訊號中會有較小的P300以及在alpha與beta頻率能量強度會下降。此結果指出隨著工作記憶負荷的增加，整體的P300會減小，時間頻率訊號在alpha與beta頻率的強度亦會隨著工作記憶負荷的增加而下降。本研究指出在腦波訊號上複雜廣度測驗亦能表現出工作記憶負荷差異。基於此結論，在複雜廣度測驗下以希爾伯特-黃轉換進行腦電波訊號的分析可以因為更好得訊雜比以及效果量而得到更加的結果。

摘要(英)

Complex span task is one among the commonly used cognitive tasks to evaluate individual working memory capacity (WMC). It is a dual task containing a distractor subtask and a memory subtask. The distractor subtask is equipped with varying time-limit across individual subjects which could provide a precise measure of individual WMC. However, the electrophysiological correlates of underlying processes of encoding and retrieval in working memory remain unclear. Previous complex span task study with EEG measure finds no significant difference between working memory-loads which a typical index is observed in other working memory tasks (e.g. n-back task and digital span task). There might be two potential problems that blur out the working memory-load difference. Firstly, the fixed-time distractor subtask may curtail in precisely assessing the individual WMC. Secondly, the method employed to analyze EEG data is favorable for linear systems, which may be inappropriate for a nonlinear system such as the human brain. Therefore, the present study seeks to investigate whether complex span tasks have similar or distinctive EEG patterns as other working memory tasks in terms of working memory-load by utilizing ensemble empirical mode decomposition (EEMD) of Hilbert-Huang Transform (HHT), a method for analyzing the nonlinear system. We expected an increase of working memory-load would lead to a decrement in the P300 component of event-related mode (ERM) and a decrease in the power of alpha and beta band frequency. This study found that low load condition had higher P300 amplitude than high load condition. The trend was widespread in many electrodes but only the C3 electrode reached statistical significance. In time-frequency analysis, a significant difference was observed between high and low load conditions at alpha and beta band in the frontal, central, and parietal channels. The results from our study demonstrate precise differences in EEG data pertaining to varied memory-load differences in the complex span task. Thus, by utilizing complex span tasks with the HHT-based analysis may aid in attaining a better signal to noise ratio and effect size for the results in working memory EEG studies.

關鍵字(中)

★ 複雜廣度測驗
★ 工作記憶容量
★ 工作記憶負荷
★ 腦電波

關鍵字(英)

★ Complex span task
★ working memory capacity
★ working memory-load,
★ EEG

論文目次

Table of Content
Chinese Abstract i
English Abstract iii
Table of Content v
Table of Figures vii
List of Tables ix
Chapter 1: Introduction 1
1.1 Working memory 2
1.2 Complex span task 5
1.3 EEG Analysis Method using Hilbert-Huang transform 7
1.3.1 ERP component of P300 7
1.3.2 Frequency band power of working memory load difference 9
1.3.3 Hilbert-Huang transform and event-related mode analysis 9
1.4 Purpose of study 14
Chapter 2: Method 17
2.1 Participants 17
2.2 Procedure 17
2.3 Tasks 18
2.3.1 Questionnaire 18
2.3.2 Raven Advanced Progressive Matrices (RAMP) task 19
2.3.3 Operation span task 20
2.3.4 Symmetry span task 22
2.4 EEG protocol 24
2.5 Event-related mode analysis 25
2.6 Time-frequency analysis 29
Chapter 3: Results 31
3.1 Behavioral data 31
3.1.1 Correlation 31
3.1.2 Operation span task 34
3.1.1 Symmetry span task 36
3.2 Event-related mode analysis 38
3.2.1 Operation span task 38
3.2.2 Symmetry span task 43
3.6 Time-frequency analysis 45
3.3.1 Operation span task 45
3.3.2 Symmetry span task 47
Chapter 4: Discussion 49
4.1 Complex span task in matlab version 49
4.2 Complex span task’s Load difference effect in P300 component and frequency band power 50
4.3 Ospan task’s difference between correct and incorrect conditions in P300 component and frequency band power 52
4.4 Limitations of the study 52
4.5 Conclusions 53
References 55
Appendix : Questionnaire 63

參考文獻

Al-subari, K., Al-baddai, S., Tome, A. M., Volberg, G., &Lang, E. W. (2015). Analysis of EEG Data Collected during a Contour Integration Task. Plos One, 10(4), 1–27. https://doi.org/10.1371/journal.pone.0119489
Atkinson, R. C., &Shiffrin, R. M. (1971). The Control of Short-Term Memory. Scientific American, 225, 82–90. https://doi.org/10.1038/ scientificamerican0871-82
Baddeley, A. (1992). Working memory. Science, 255(5044), 556–559. https://doi.org/10.1126/science.1736359
Baddeley, A. (2000). The episodic buffer: A new component of working memory? Trends in Cognitive Sciences, 4(11), 417–423. https://doi.org/10.1016/S1364-6613(00)01538-2
Baddeley, A. (2003). Working memory: Looking back and looking forward. Nature Reviews Neuroscience, 4(10), 829–839. https://doi.org/10.1038/nrn1201
Baddeley, A. (2007). Working Memory, Thought, and Action. Oxford, United Kingdom: Oxford University Press. Retrieved from http://0-www.oxfordscholarship.com.oasis.unisa.ac.za/view/10.1093/acprof:oso/9780198528012.001.0001/acprof-9780198528012
Baddeley, A., &Hitch, G. (1974). Working memory. Psychology of Learning and Motivation, 8, 47–89. https://doi.org/10.1016/j.cub.2009.12.014
Broadway, J. M., &Engle, R. W. (2011a). Individual Differences in Working Memory Capacity and Temporal Discrimination. PLoS ONE, 6(10). https://doi.org/10.1371/journal.pone.0025422
Broadway, J. M., &Engle, R. W. (2011b). Lapsed attention to elapsed time? Individual differences in working memory capacity and temporal reproduction. Acta Psychologica, 137(1), 115–126. https://doi.org/10.1016/j.actpsy.2011.03.008
Brown, K. W., &Ryan, R. M. (2003). The Benefits of Being Present: Mindfulness and Its Role in Psychological Well-Being. Journal of Personality and Social Psychology, 84(4), 822–848. https://doi.org/10.1037/0022-3514.84.4.822
Buzsaki, G., &Wang, X.-J. (2012). Mechanisms of Gamma Oscillations. Annual Review of Neuroscience, 35(1), 203–225. https://doi.org/10.1146/annurev-neuro-062111-150444
Carver, C. S., &White, T. L. (1994). Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: The BIS/BAS Scales. Journal of Personality and Social Psychology, 67(2), 319–333. https://doi.org/10.1037/0022-3514.67.2.319
Chang, C.-F., Liang, W.-K., Lai, C.-L., Hung, D. L., &Juan, C.-H. (2016). Theta Oscillation Reveals the Temporal Involvement of Different Attentional Networks in Contingent Reorienting. Frontiers in Human Neuroscience, 10(June), 1–11. https://doi.org/10.3389/fnhum.2016.00264
Cong, F., Sipola, T., Huttunen-Scott, T., Xu, X., Ristaniemi, T., &Lyytinen, H. (2009). Hilbert-Huang versus Morlet wavelet transformation on mismatch negativity of children in uninterrupted sound paradigm. Nonlinear Biomedical Physics, 3(1), 1–8. https://doi.org/10.1186/1753-4631-3-1
Conway, A. R. A., Kane, M. J., Bunting, M. F., Hambrick, Z. D., Wilhelm, O., &Engle, R. W. (2005). Working memory span tasks?: A methodological review and user’s guide. Psychonomic Bulletin & Review, 12(5), 769–786. https://doi.org/10.3758/BF03196772
Conway, A. R. A., Kane, M. J., &Engle, R. W. (2003). Working memory capacity and its relation to general intelligence. Trends in Cognitive Sciences, 7(12), 547–552. https://doi.org/10.1016/j.tics.2003.10.005
Crowne, D. P., &Marlowe, D. (1960). A new scale of social desirability independent of psychopathology. Journal of Consulting Psychology, 24(4), 349–354. https://doi.org/10.1037/h0047358
Daneman, M., &Carpenter, P. A. (1980). Individual differences in working memory and reading. Journal of Verbal Learning and Verbal Behavior, 19(4), 450–466. https://doi.org/10.1016/S0022-5371(80)90312-6
Dong, S., Reder, L. M., Yao, Y., Liu, Y., &Chen, F. (2015). Individual differences in working memory capacity are reflected in different ERP and EEG patterns to task difficulty. Brain Research, 1616, 146–156. https://doi.org/10.1016/j.brainres.2015.05.003
Foster, J. L., Shipstead, Z., Harrison, T. L., Hicks, K. L., Redick, T. S., &Engle, R. W. (2015). Shortened complex span tasks can reliably measure working memory capacity. Memory & Cognition, 43(2), 226–236. https://doi.org/10.3758/s13421-014-0461-7
Groppe, D. M., Urbach, T. P., &Kutas, M. (2011). Mass univariate analysis of event-related brain potentials/fields II: Simulation studies. Psychophysiology, 48(12), 1726–1737. https://doi.org/10.1111/j.1469-8986.2011.01272.x
Harrison, T. L., Shipstead, Z., Hicks, K. L., Hambrick, D. Z., Redick, T. S., &Engle, R. W. (2013). Working Memory Training May Increase Working Memory Capacity but Not Fluid Intelligence. Psychological Science, 24(12), 2409–2419. https://doi.org/10.1177/0956797613492984
Hsu, C.-H., Lee, C.-Y., &Liang, W.-K. (2016). An improved method for measuring mismatch negativity using ensemble empirical mode decomposition. Journal of Neuroscience Methods, 264, 78–85. https://doi.org/10.1016/j.jneumeth.2016.02.015
Huang, N. E., Shen, Z., Long, S. R., Wu, M. C., Shih, H. H., Zheng, Q., …Liu, H. H. (1998). The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 454(1971), 903–995. https://doi.org/10.1098/rspa.1998.0193
Jaeggi, S. M., Buschkuehl, M., Perrig, W. J., &Meier, B. (2010). The concurrent validity of the N -back task as a working memory measure. Memory, 18(4), 394–412. https://doi.org/10.1080/09658211003702171
Jensen, O. (2002). Oscillations in the Alpha Band (9-12 Hz) Increase with Memory Load during Retention in a Short-term Memory Task. Cerebral Cortex, 12(8), 877–882. https://doi.org/10.1093/cercor/12.8.877
Johnson, R. (1993). On the neural generators of the P300 component of the event-related potential. Psychophysiology, 30(1), 90–97. https://doi.org/10.1111/j.1469-8986.1993.tb03208.x
Kane, M. J., Conway, A. R. A., Miura, T. K., &Colflesh, G. J. H. (2007). Working memory, attention control, and the n-back task: A question of construct validity. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33(3), 615–622. https://doi.org/10.1037/0278-7393.33.3.615
Kane, M. J., Hambrick, D. Z., Tuholski, S. W., Wilhelm, O., Payne, T. W., &Engle, R. W. (2004). The Generality of Working Memory Capacity: A Latent-Variable Approach to Verbal and Visuospatial Memory Span and Reasoning. Journal of Experimental Psychology: General, 133(2), 189–217. https://doi.org/10.1037/0096-3445.133.2.189
Klimesch, W. (2012). Alpha-band oscillations, attention, and controlled access to stored information. Trends in Cognitive Sciences, 16(12), 606–617. https://doi.org/10.1016/j.tics.2012.10.007
Kok, A. (2001). On the utility of P3 amplitude as a measure of processing capacity. Psychophysiology, 38(3), 557–577. https://doi.org/10.1017/S0048577201990559
Maris, E., &Oostenveld, R. (2007). Nonparametric statistical testing of EEG- and MEG-data. Journal of Neuroscience Methods, 164(1), 177–190. https://doi.org/10.1016/j.jneumeth.2007.03.024
Miller, G. A. (1956). The Magic Number Seven, Plus or Minus Two: Some Limits on our Capcity for Processing Information. The Psychological Review, 63(2), 81–97.
Palomaki, J., Kivikangas, M., Alafuzoff, A., Hakala, T., &Krause, C. M. (2012). Brain oscillatory 4–35Hz EEG responses during an n-back task with complex visual stimuli. Neuroscience Letters, 516(1), 141–145. https://doi.org/10.1016/j.neulet.2012.03.076
Pesonen, M., Hamalainen, H., &Krause, C. M. (2007). Brain oscillatory 4–30 Hz responses during a visual n-back memory task with varying memory load. Brain Research, 1138(1), 171–177. https://doi.org/10.1016/j.brainres.2006.12.076
Picton, T. W. (1992). The P300 Wave of the Human Event-Related Potential. Journal of Clinical Neurophysiology, 9(4), 456–479. https://doi.org/10.1097/00004691-199210000-00002
Polich, J. (2007). Updating P300: An integrative theory of P3a and P3b. Clinical Neurophysiology, 118(10), 2128–2148. https://doi.org/10.1016/j.clinph.2007.04.019
Polich, J., &Criado, J. R. (2006). Neuropsychology and neuropharmacology of P3a and P3b. International Journal of Psychophysiology, 60(2), 172–185. https://doi.org/10.1016/j.ijpsycho.2005.12.012
Redick, T. S., &Lindsey, D. R. B. (2013). Complex span and n-back measures of working memory: A meta-analysis. Psychonomic Bulletin and Review, 20(6), 1102–1113. https://doi.org/10.3758/s13423-013-0453-9
Roberts, R., &Gibson, E. (2002). Individual Differences in Sentence Processing. Journal of Psycholinguistic Research, 31(6), 573–598.
Roux, F., Wibral, M., Mohr, H. M., Singer, W., &Uhlhaas, P. J. (2012). Gamma-Band Activity in Human Prefrontal Cortex Codes for the Number of Relevant Items Maintained in Working Memory. Journal of Neuroscience, 32(36), 12411–12420. https://doi.org/10.1523/JNEUROSCI.0421-12.2012
Scharinger, C., Soutschek, A., Schubert, T., &Gerjets, P. (2015). When flanker meets the n-back: What EEG and pupil dilation data reveal about the interplay between the two central-executive working memory functions inhibition and updating. Psychophysiology, 52, 1293–1304. https://doi.org/10.1111/psyp.12500
Scharinger, C., Soutschek, A., Schubert, T., &Gerjets, P. (2017). Comparison of the Working Memory Load in N-Back and Working Memory Span Tasks by Means of EEG Frequency Band Power and P300 Amplitude. Frontiers in Human Neuroscience, 11(6), 1–19. https://doi.org/10.3389/fnhum.2017.00006
Spielberger, C. D., Gorsuch, R. L., Lushene, P. R., Vagg, P. R., &Jacobs, A. G. (1983). Manual for the State-Trait Anxiety Inventory. Consulting Psychologists Press.
Squires, N. K., Squires, K. C., &Hillyard, S. A. (1975). Two varieties of long-latency positive waves evoked by unpredictable auditory stimuli in man. Electroencephalography and Clinical Neurophysiology, 38(4), 387–401. https://doi.org/10.1016/0013-4694(75)90263-1
Sutton, S., Braren, M., Zubin, J., &John, E. R. (1965). Evoked-Potential Correlates of Stimulus Uncertainty. Science, 150(3700), 1187–1188. https://doi.org/10.1126/science.150.3700.1187
Tsai, Y.-C., Lu, H.-J., Chang, C.-F., Liang, W.-K., Muggleton, N. G., &Juan, C.-H. (2017). Electrophysiological and behavioral evidence reveals the effects of trait anxiety on contingent attentional capture. Cognitive, Affective, & Behavioral Neuroscience, 17(5), 973–983. https://doi.org/10.3758/s13415-017-0526-8
Tseng, P., Chang, Y.-T., Chang, C.-F., Liang, W.-K., &Juan, C.-H. (2016). The critical role of phase difference in gamma oscillation within the temporoparietal network for binding visual working memory. Scientific Reports, 6(1), 32138. https://doi.org/10.1038/srep32138
Turner, M. L., &Engle, R. W. (1989). Is working memory capacity task dependent? Journal of Memory and Language, 28(2), 127–154. https://doi.org/10.1016/0749-596X(89)90040-5
Unsworth, N., &Engle, R. W. (2007). The nature of individual differences in working memory capacity: Active maintenance in primary memory and controlled search from secondary memory. Psychological Review, 114(1), 104–132. https://doi.org/10.1037/0033-295X.114.1.104
Unsworth, N., Heitz, R. P., Schrock, J. C., &Engle, R. W. (2005). An automated version of the operation span task. Behavior Research Methods, 37(3), 498–505. https://doi.org/10.3758/BF03192720
Unsworth, N., Redick, T. S., Heitz, R. P., Broadway, J. M., &Engle, R. W. (2009). Complex working memory span tasks and higher-order cognition: A latent-variable analysis of the relationship between processing and storage. Memory, 17(6), 635–654. https://doi.org/10.1080/09658210902998047
Watter, S., Geffen, G. M., &Geffen, L. B. (2001). The n-back as a dual-task: P300 morphology under divided attention. Psychophysiology, 38(6), 998–1003. https://doi.org/10.1111/1469-8986.3860998
Williams, N., Nasuto, S. J., &Saddy, J. D. (2011). Evaluation of Empirical Mode Decomposition for Event-Related Potential Analysis. EURASIP Journal on Advances in Signal Processing, 2011(1), 1–11. https://doi.org/10.1155/2011/965237
Wu, Z., &Huang, N. E. (2009). Ensemble empirical mode decomposition: a noise-assisted data analysis method. Advances in Adaptive Data Analysis, 1(1), 1–41. https://doi.org/10.1142/S1793536909000047

指導教授

阮啟弘

審核日期

2018-7-18

推文