臺灣博碩士論文加值系統

軀體標記假說已然成為探討交感神經活動(例如:膚電反應)，中央額葉功能與情感決策三者關係的重要理論。而愛荷華賭局作業則是建構軀體標記假說行為與生理論證的核心作業，此作業的結果指出:正常的決策者能夠逐漸預感到賭局裡各個牌的最終後果(有兩疊牌是好牌，另外兩疊是壞牌)，因而逐漸偏好好牌且避開壞牌。愛荷華賭局作業更驗證了中央腹側額葉損傷的病患會呈現與正常人相反的選擇模式。而此作業近來更被廣泛應用到許多神經與精神疾病的檢測與觀察正常人在不確定情境下的金錢決策行為。愛荷華賭局作業的影響力已經深入到情感的神經科學、神經與精神疾病的研究。愛荷華賭局作業也已經成為一個商品化的神經心理學測驗。膚觸電位反應則是一個軀體標記運作的關鍵指標。而基於臨床神經學的發現，軀體標記假說提供了一個神經網絡以解釋意識產生與決策的神經機制。軀體標記假說認為有五個腦部區域對日常生活的決策(就如同愛荷華賭局作業中的決策過程)具有關鍵作用。五個腦部區域包括: 中央腹側前額葉、杏仁核、腦島、主要體感覺皮質以及腦幹。

但是有一些證據顯示軀體標記假說在理論、行為與生理的層次上都有一些疑點待澄清。諸如Dunn等人回顧軀體標記假說與愛荷華賭局作業的許多研究發現:許多正常決策者與某些病人都偏好壞牌B，選壞牌B的次數比好牌C或D要來得高。Wilder等人曾經清楚的說明這個現象，後續，Chiu等人則以一個比愛荷華賭局作業簡單與對稱的改版作業(也就是東吳賭局作業)得出一個與愛荷華賭局作業完全相反的結果。東吳賭局作業的結果顯示: 正常決策者對期望值是不敏感的，而這與愛荷華賭局作業的最基本假設剛好牴觸。除此之外，Tomb等人則發現膚觸電位反應並未對應到好壞牌，而是對應到牌的輸贏大小。而Suzuki等人則指出膚觸電位反應的個別差異太大根本對應不到愛荷華賭局作業中特定的變項。而Dunn等人的研究回顧中更指出愛荷華賭局作業相關的腦造影研究並未得出與軀體標記大腦迴路一致的結果。

由此可知，愛荷華賭局作業、膚觸電位與軀體標記大腦迴路是支撐軀體標記假說三大基石。本文「背景」的部份將回顧愛荷華賭局作業的相關文獻中所呈現的「奇異B現象」。這部份的文獻回顧與整理主要根據兩條線索：(1)追蹤愛荷華團隊這歷年來的相關研究；(2)審視以愛荷華賭局作業為研究工具且有量測正常人的相關實驗。大部份愛荷華賭局作業的相關研究包括愛荷華團隊自己的研究絕大多數都用好(C+D)壞(A+B)牌的方式來呈現他們的資料。以致「奇異B現象」無法被觀察到。某些研究以「四疊牌」的方式呈現他們的資料，結果顯示，大部分都出現「奇異B現象」。此部份的文獻回顧指出愛荷華團隊應該考慮為愛荷華賭局作業的結果另闢一解釋之道。

第一個研究企圖去釐清「奇異B現象」是否存在。此部份以「兩階段簡單版」的愛荷華賭局進行實驗，也就是「AACC 和 BBDD」兩個版本。但是，每一個簡易版裡也都有好牌與壞牌，而且裡面的輸贏頻率也都完全對稱(牌A和C都是5贏5輸；牌B和D都是9贏1輸)，而兩階段是為了持續觀察受試者100次後的偏好狀況。實驗結果顯示「奇異B現象」的確存在愛荷華賭局作業中。甚至，受試者到了第二階段仍然無法抑制他們對壞牌B的偏好。雖然這個結果與愛荷華賭局作業的基本假設產生牴觸，但是愈來愈多的研究呈現出類似的結果。而且「AACC 和 BBDD」兩個版本的結果是可同時被輸贏頻率的文獻所解釋的。

第二個研究則主要在測試長期效益(也就是所謂的期望值) 。兩個實驗(愛荷華賭局作業與改版的愛荷華賭局作業)總共徵詢了48名大學生參與。第一個實驗是要確認的「奇異B現象」而第二個實驗則在檢定愛荷華賭局作業主要變項(長期效益)的穩定度。結果再度確認了「奇異B現象」存在愛荷華賭局作業與改版的愛荷華賭局作業中。這兩個實驗四疊牌雖然有不同的期望值，但是受試者卻有著類似的選牌模式。這個研究證明: 期望值在這類型動態賭局中可能不是最根本的變項。此研究與Wielder等人的發現都與愛荷華賭局作業的基本假設牴觸，但是此結果卻再度驗證「決策者對期望值是不敏感的」。

第三個研究主要欲解決愛荷華賭局作業在膚觸電位研究上的爭議。研究中包含兩個實驗。第一個實驗旨在驗證愛荷華賭局作業在膚觸電位實驗的可再現性。第二個實驗則是以較對稱而簡單的「東吳賭局」驗證: 在不確定的情境中，決策行為與膚觸電位反應之間是否存在穩定的相關。此研究發現以膚觸電位反應為指標的軀體標記，並未改善決策者在愛荷華賭局中預感的正確性。相反的，在兩組作業中，受試者在翻(特定)牌前要產生穩定的膚電反應似乎是有其困難。但是，膚觸電位卻在翻牌後明顯的反應了粗略的金錢值。

第四個研究主要是以「事件相關的功能性磁振造影」檢驗執行愛荷華賭局作業時的神經迴路，包括「預期(翻牌前)與經驗(翻牌後)」，「輸和贏」與各種不同牌的狀態。而行為結果顯示「輸贏頻率」影響決策的重要性。腦島與基底神經結在與預期階段是最活躍的腦部區域，而下頂葉則在經驗階段有最大強度與範圍的活動。而中央腹側額葉則在輸最大金額之後才被觀測到。依據目前資料推論:在不確定的情境中，正常決策者仍可能是短視的。腦島與基底神經結在導引長期的決策過程中可能扮演相當重要的角色。下頂葉則可能參與評估後果。而中央前額葉可能具有錯誤偵測的功能。

在行為的層面，「背景」與研究一證實了有愈來愈多的證據支持「奇異B現象」。而研究二的解析則指出大部份決策者在不確定的情境中是很難直覺到期望值的。而決策行為可能主要是受輸贏頻率所影響。受試者可能發展出一套「贏留輸跑」的策略來面對不確定的情境。在生理上，我們指出膚觸電位反應可能與翻牌後的覺醒程度(金錢值的大小)有關而非促使受試者對期望值的預感與頓悟。除此之外，中央腹側前額葉的功能是在偵測錯誤而非愛荷華團隊所推論的:整合軀體標記並誘導理性的決策。因此，高頻率的贏可能是主導決策的關鍵因素，而腦島與基底神經結的活動可能是對應輸贏頻率與驅動決策的神經機制所在。最後，下頂葉的部份負責在這種不確定的情境下對後果的評估。總之，愛荷華賭局作業如果要繼續成為有效的神經心理學測驗，應該要根據另外一個變項，也就是輸贏頻率進行修正與重新建構。此論文對愛荷華賭局作業在生理上的發現亦提供一個新的大腦圖譜以解釋不確定情境下的決策行為。

Somatic Marker Hypothesis (SMH) has been applied to explore the relationship between sympathetic activity, i.e., Skin Conductance Responses (SCRs), medial frontal function and affective decision-making. Additionally, Iowa Gambling Task (IGT), which is the core task for constructing behavioral and physiological aspects of SMH, indicates that normal decision makers can gradually hunch the final outcome of these decks (two good, two bad) and progressively approach the good decks and avoid the bad decks. The IGT has also demonstrated that ventromedial prefrontal patients exhibit inverse choice patterns. Recently, IGT has been used to assess neurological and psychiatric deficits as well as monetary decision-makers under uncertainty. The task has been influential in studies of affective neuroscience and neurological as well as psychiatric disorders. The IGT has been a commercialized neurological test for affective decision behavior. The SCRs are a critical index for somatic marker operation. Further, SMH based on neurological and clinical observations delineates neuronal networks for interpreting consciousness generation and decision-making. The SMH suggests that five brain areas, including the ventromedial prefrontal cortex (VMPFC), amygdala, insular cortex (IN), somatosensory cortex (SI) and brainstem nuclei, are also critical for real-life decision-making, as demonstrated in the IGT.

However, growing evidence reveals theoretical, behavioral and physiological flaws in the SMH. For example, a review for SMH and IGT by Dunn et al. showed that decision makers and some patients prefer bad final-outcome deck B to good final-outcome decks C or D. This phenomenon was clearly demonstrated by Wilder et al. In a subsequent study, Chiu et al. modified the IGT in another relatively simple and symmetric gamble, namely the Soochow Gambling Task (SGT), which demonstrated the opposite findings of IGT. The SGT results revealed that normal decision makers are insensitive to the final-outcome, which is contrary to the basic assumption of IGT. Further, Tomb et al. found that the SCRs in IGT respond to large-value decks, not just bad decks. Additionally, Suzuki et al. suggested that, because individual SCRs differ, these data are unsuitable for demonstrating stable trends in IGT. Further, Dunn et al. revealed incongruent IGT-related brain-imaging data for these somatic brain regions.

Clearly, IGT, SCRs and somatic brain loops are three cornerstones of SMH. This thesis explores five issues in IGT. The “Background” reviews the “prominent deck B phenomenon” in IGT-related studies. This evaluation reexamines this phenomenon via a literature review that (1) traces the findings of the Iowa group and (2) reviews other studies that have utilized the IGT as an experimental tool, particularly for control groups. Most IGT-related studies, including the Iowa group studies, subtracted bad decks from good decks when analyzing data; consequently, the incidence of the “prominent deck B phenomenon” cannot be assessed. Some studies have instead presented data in terms of a four-deck format, which provides a clear result for each deck and demonstrates the “prominent deck B phenomenon”. This literature review suggests that the Iowa group should consider alternative interpretations of the IGT to account for the inconsistent data.

First study describes attempts to verify the “prominent deck B phenomenon”. This study launched a two-stage simple version IGT, namely, an AACC and BBDD version, which possess balanced gain-loss structures between advantageous and disadvantageous decks (decks A and C each have five gains and five losses; decks B and D each have nine gains and one loss) and facilitates monitoring of participant preferences after the first 100 trials. The experimental results suggest that the “prominent deck B phenomenon” exists in the IGT. Moreover, participants cannot suppress their preference for bad deck B under uncertain conditions, even during the second stage of the game. Although this outcome is incongruent with the basic assumption of IGT, increasing studies reveal similar results. The AACC and BBDD versions are congruent with the literature in terms of gain-loss frequency.

Second study tests long-term outcomes (namely, expected value). Forty-eight college students were enrolled for two experiments (IGT and revised IGT). The first experiment identified the “prominent deck B phenomenon”, and the second experiment tested the stability of main guiding factor (long-term outcome) in IGT. This study confirmed that the “prominent deck B phenomenon” exists in the original and modified IGT. The two experiments revealed different long-term outcomes, even when the subjects had similar choice patterns. These findings demonstrate that long-term outcome might not be an essential factor in these dynamic games. This and other studies such as Wielder et al. may contradict the basic assumption of IGT whereas this study is congruent with studies indicating that decision makers are insensitive to long-term outcome (expected value).

Third study reconciles the argument over SCRs in IGT. Two experiments were performed in this study. First, the IGT-SCR experiment was elucidated the reproducibility of IGT. Second, the Soochow Gambling Task (SGT) examined the effect of decision-SCRs pairing under uncertainty. This study found that the indexical assistance of somatic markers represented by SCRs do not improve the accuracy of hunches by decision makers in IGT. Conversely, given these IGT and SGT conditions, subjects have difficulty generating stable anticipatory SCRs. However, SCRs apparently represent the approximate monetary value after card-turning.

Fourth study describes the use of event-related fMRI (functional Magnetic Resonance Imaging) to examine neural correlates of anticipation vs. outcome, wins vs. losses, and differential IGT contingencies between decks. The behavioral results reveal the importance of frequency in driving choices. The insula and basal ganglia were activated during the anticipation phase while the inferior parietal lobule was activated during the outcome phase. The medial prefrontal cortex was particularly activated during the high punishment contingencies. The data suggest that, under uncertainty, normal decision makers may become myopic. The insula and basal ganglia apparently have vital roles in long-term guidance of decision-making. The inferior parietal lobule may participate in evaluating consequences, and the medial prefrontal cortex may provide an error monitoring function.

On the behavioral level, the “Background” and study I review the growing evidence supporting the “prominent deck B phenomenon”. The analytical results of this study II indicate that most decision makers have difficulty hunching long-term outcomes under uncertainty. The choice behavior is mostly dominated by the gain-loss frequency. The subjects may develop a strategy, namely the “win-stay, loss-shift” to cope with the uncertain situation. Physiologically, SCRs are related to the arousal in response to the monetary value after card-turning rather than facilitating hunches of long-term outcome. Additionally, the function of VMPFC is identified for error detection or action monitoring rather than for somatic marker integration and guiding rational decisions as suggested by Iowa group. Consequently, the high-frequency gain could be an important guide for decision making, and the IN and basal ganglia could be essential for processing the gain-loss frequency and driving choice behavior. Finally, the inferior parietal cortex may correspond to outcome assessment under uncertainty. In conclusion, IGT has a need to be modified and reconstructed according to the alternative variable, gain-loss frequency before commercializing a neurological test. Accordingly, the present physiological finding with IGT provides a new brain circuitry for decision-making under uncertainty.

Content
1 Background 20
1.1 Somatic Marker Hypothesis Revisited 20
1.1.1 Introduction to Somatic Marker Hypothesis 20
1.1.2 SMH illustrated four mind-body issues 21
1.1.3 The query and criticism of SMH in a theoretical framework 24
1.2 Introduction of Iowa gambling task 27
1.3 Inconsistent behavioral evidences within Iowa group 30
1.4 Inconsistent behavioral evidences between Iowa and some other groups. 36
1.5 Incoherent SCRs evidences between Iowa and some other groups. 44
1.6 Incoherent evidences on the brain loops of IGT between Iowa group and some other groups 49
1.7 Hypothesis and prediction based on two variables (long-term outcome vs. gain-loss frequency) 53
2 Study I: Is deck B a disadvantageous deck in the Iowa Gambling Task? 56
2.1 Hypothesis 56
2.2 Methods 57
2.3 Results 59
2.4 Discussion 64
2.5 Conclusions 69
3 Study II: Decision maker is difficult to hunch the long-term outcome in the Iowa Gambling Task 71
3.1 Hypothesis 71
3.2 Methods 77
3.3 Results 77
3.4 Discussion 80
3.5 Conclusions 82
4 Study III: Does SCRs correlate to the anticipation of choice in the uncertain gambling tasks? 84
4.1 Hypothesis 84
4.2 Methods 84
4.3 Results 85
4.3.1 First experiment 85
4.3.2 Second experiment 88
4.4 Discussion 90
4.5 Conclusions 91
5 Study IV: Brain Maps of Iowa Gambling Task 93
5.1 Hypothesis 93
5.2 Methods 94
5.2.1 Participants 94
5.2.2 Paradigms 94
5.2.3 fMRI Data Acquisition 96
5.2.4 Data Processing and Analysis 96
5.3 Results 99
5.3.1 Behavior Data and Leaning Curve 99
5.3.2 Brain Activation during Anticipation and Experience 103
5.3.3 Brain Activation of Gain, Draw and Loss 106
5.3.4 Brain Activation of Decks (A, B, C, D) 107
5.3.5 Time courses of regional activity for 11 Monetary Values ($ +100, $ + 50, •••, $ - 350, $ -1150). 109
5.4 Discussion 112
5.4.1 The “prominent deck B phenomenon” 112
5.4.2 Brain activation for anticipation and experience 113
5.4.3 Brain activation for gain, loss and draw conditions 115
5.4.4 Brain activation for Decks 115
5.4.5 The role of medial prefrontal cortex in IGT 117
5.4.6 General Discussion 120
5.5 Conclusions 122
6 Questions and Future Works 123
6.1 Increased preference for bad deck B in normal decision makers 123
6.2 “Gain-loss frequency” effect revealed by the “prominent Deck B phenomenon” under uncertainty 124
6.3 Lack of stably anticipatory SCRs alerting decision makers to avoid the bad deck B? 125
6.4 Lack of stable medial prefrontal activity during the anticipatory period of choosing bad deck B 126
7 Summary 128

Figure content
Figure 1 1 Bechara et al. (1994) identified the choice pattern for four decks in a control group. 31
Figure 1 2 Prominent deck B phenomenon in two recent studies by the Iowa-related groups. 35
Figure 1 3 Prominent deck B phenomenon in some IGT-related studies using the four-deck format. 39
Figure 2 1 Counterbalance of deck position in the simplified IGT. 58
Figure 2 2 Mean number of cards selection. 59
Figure 2 3 Mean number of cards selection in blocks. 60
Figure 2 4 Mean number of cards selection. 61
Figure 2 5 Mean number of cards selection in blocks. 62
Figure 2 6 Participant memory assessments in the simplified IGT. 63
Figure 3 1 Mean of Card Selection in IGT. 78
Figure 3 2 Mean of Cards Selection in rIGT. 79
Figure 3 3 Percentage of Decks Preference in rIGT. 80
Figure 4 1 Mean number of cards chosen in IGT. 86
Figure 4 2 Mean amplitude of event-related SCRs for each card in IGT. 87
Figure 4 3 Mean amplitude of event-related SCRs for each value. 87
Figure 4 4 Mean number of cards chosen in SGT. 88
Figure 4 5 Mean amplitude of event-related SCRs for each card. 89
Figure 4 6 Mean amplitude of event-related SCRs for each value. 90
Figure 5 1 Computer version of IGT and event-related fMRI design. 95
Figure 5 2 Mean number of cards selection. 99
Figure 5 3 Mean number of cards selection in blocks. 100
Figure 5 4 Brain activation during anticipation and experience. 103
Figure 5 5 Brain activation for gain, draw and loss during anticipation and experience. 106
Figure 5 6 Brain activation for four decks during anticipation and experience. 108
Figure 5 7 BOLD response for each monetary value in anticipation and experience. 110
Figure 5 8 BOLD response of the medial prefrontal cortex under large loss ($ -1150) condition of deck B. 111
Figure 5 9 Mean of BOLD-response for each monetary value in specific brain region. 120


Table content
Table 1 1 The gain-loss structure in the original IGT. 28
Table 1 2 Data for normal control subjects in IGT serial studies by Iowa group. 33
Table 1 3 Data for normal control subjects in IGT-related studies using the four-deck format. 37
Table 1 4 Selected studies that provide a common explanation for the deck B phenomenon. 40
Table 1 5 Comparison of Gain-loss structure between IGT and SGT. 46
Table 1 6 Summary of functional brain imaging observations in IGT related studies. 50
Table 1 7 Summarization of hypotheses and prediction in each study. 54
Table 2 1 The final state of monetary gain-loss in the simplified IGT. 63
Table 2 2 The immediate net value of each trial in the original IGT. 66
Table 3 1 Comparison of the gamble structure of IGT and rIGT. 72
Table 3 2 The internal variables and prediction in IGT and rIGT. 76
Table 5 1 Statistical test for expected value, gain-loss frequency and blocks 101
Table 5 2 Pair-t test for between deck B and the other three decks in each block. 101
Table 5 3 Brain activation during anticipation period. 104
Table 5 4 Brain activation during experience phase. 105
Table 7 1 Experimental and predictive comparisons in each study. 129

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