Iowa Gambling Task Description

• Iowa Gambling Task Igt
• Iowa Gambling Task Online
• Iowa Gambling Task Description Example

The Iowa gambling task (IGT) is a psychological task thought to simulate real-life decision making.It was introduced by Antoine Bechara, Antonio Damasio, Hanna Damasio and Steven Anderson,^[1] then researchers at the University of Iowa. It has been brought to popular attention by Antonio Damasio (proponent of the somatic marker hypothesis) in his best-selling book Descartes' Error.^[2]

In this case, the task is something called the Iowa Gambling Task (IGT). The IGT is a simple game where you win or lose money, and different people play the game with different strategies. I'm going to talk briefly about how the game works, what it tells us about how people make decisions and evaluate risk, and how the strategy you use might. And one of the ways this can be tested is with the Iowa Gambling Task. First designed by Antoine Bechara and others in 1994, the test was originally used to measure decision-making abilities. This decision-making required that the participants simply select a card from one of four decks – hardly a tricky bet.

The task was originally presented simply as the Gambling Task, or the 'OGT'. Later, it has been referred to as the Iowa gambling task and, less frequently, as Bechara's Gambling Task.^[3] The Iowa gambling task is widely used in research of cognition and emotion. A recent review listed more than 400 papers that made use of this paradigm.^[4]

Iowa Gambling Task Igt

Task structure[edit]

Participants are presented with four virtual decks of cards on a computer screen. They are told that each deck holds cards that will either reward or penalize them, using game money. The goal of the game is to win as much money as possible. The decks differ from each other in the balance of reward versus penalty cards. Thus, some decks are 'bad decks', and other decks are 'good decks', because some decks will tend to reward the player more often than other decks.

Common findings[edit]

Most healthy participants sample cards from each deck, and after about 40 or 50 selections are fairly good at sticking to the good decks. Patients with orbitofrontal cortex (OFC) dysfunction, however, continue to persevere with the bad decks, sometimes even though they know that they are losing money overall. Concurrent measurement of galvanic skin response shows that healthy participants show a 'stress' reaction to hovering over the bad decks after only 10 trials, long before conscious sensation that the decks are bad.^[5] By contrast, patients with amygdala lesions never develop this physiological reaction to impending punishment. In another test, patients with ventromedial prefrontal cortex (vmPFC) dysfunction were shown to choose outcomes that yield high immediate gains in spite of higher losses in the future.^[6] Bechara and his colleagues explain these findings in terms of the somatic marker hypothesis.

The Iowa gambling task is currently being used by a number of research groups using fMRI to investigate which brain regions are activated by the task in healthy volunteers^[7] as well as clinical groups with conditions such as schizophrenia and obsessive compulsive disorder.

Critiques[edit]

Iowa Gambling Task Online

Although the IGT has achieved prominence, it is not without its critics. Criticisms have been raised over both its design and its interpretation. Published critiques include:

• A paper by Dunn, Dalgliesh and Lawrence^[4]
• Research by Lin, Chiu, Lee and Hsieh,^[8] who argue that a common result (the 'prominent deck B' phenomenon) argues against some of the interpretations that the IGT has been claimed to support.
• Research by Chiu and Lin,^[9] the 'sunken deck C' phenomenon was identified, which confirmed a serious confound embedded in the original design of IGT, this confound makes IGT serial studies misinterpret the effect of gain-loss frequency as final-outcome for somatic marker hypothesis.
• A research group in Taiwan utilized an IGT-modified and relatively symmetrical gamble for gain-loss frequency and long-term outcome, namely the Soochow gambling task (SGT) demonstrated a reverse finding of Iowa gambling task.^[10] Normal decision makers in SGT were mostly occupied by the immediate perspective of gain-loss and inability to hunch the long-term outcome in the standard procedure of IGT (100 trials under uncertainty). In his book, Inside the investor's brain,^[11]Richard L. Peterson considered the serial findings of SGT may be congruent with the Nassim Taleb's^[12] suggestion on some fooled choices in investment.

References[edit]

Iowa Gambling Task Description Example

1. ^Bechara, A., Damasio, A. R., Damasio, H., Anderson, S. W. (1994). 'Insensitivity to future consequences following damage to human prefrontal cortex'. Cognition. 50 (1–3): 7–15. doi:10.1016/0010-0277(94)90018-3. PMID8039375.CS1 maint: multiple names: authors list (link)
2. ^Damasio, António R. (2008) [1994]. Descartes' Error: Emotion, Reason and the Human Brain. Random House. ISBN978-1-4070-7206-7.CS1 maint: ref=harv (link)Descartes' Error
3. ^Busemeyer JR, Stout JC (2002). 'A contribution of cognitive decision models to clinical assessment: Decomposing performance on the Bechara gambling task'. Psychological Assessment. 14 (3): 253–262. doi:10.1037/1040-3590.14.3.253.
4. ^ ^abDunn BD, Dalgleish T, Lawrence AD (2006). 'The somatic marker hypothesis: a critical evaluation'. Neurosci Biobehav Rev. 30 (2): 239–71. doi:10.1016/j.neubiorev.2005.07.001. PMID16197997.
5. ^Bechara A, Damasio H, Tranel D, Damasio AR (1997). 'Deciding advantageously before knowing the advantageous strategy'. Science. 275 (5304): 1293–5. doi:10.1126/science.275.5304.1293. PMID9036851.
6. ^Bechara A, Damasio H, Tranel D, Damasio AR (2000). 'Characterization of the decision-making deficit of patients with ventromedial prefrontal cortex lesions'. Brain. 123 (11): 2189–2202. doi:10.1093/brain/123.11.2189. PMID11050020.
7. ^Fukui H, Murai T, Fukuyama H, Hayashi T, Hanakawa T (2005). 'Functional activity related to risk anticipation during performance of the Iowa Gambling Task'. NeuroImage. 24 (1): 253–9. doi:10.1016/j.neuroimage.2004.08.028. PMID15588617.
8. ^Lin CH, Chiu YC, Lee PL, Hsieh JC (2007). 'Is deck B a disadvantageous deck in the Iowa Gambling Task?'. Behav Brain Funct. 3: 16. doi:10.1186/1744-9081-3-16. PMC1839101. PMID17362508.
9. ^Chiu, Yao-Chu; Lin, Ching-Hung (August 2007). 'Is deck C an advantageous deck in the Iowa Gambling Task?'. Behavioral and Brain Functions. 3 (1): 37. doi:10.1186/1744-9081-3-37. PMC1995208. PMID17683599.
10. ^Chiu, Yao-Chu; Lin, Ching-Hung; Huang, Jong-Tsun; Lin, Shuyeu; Lee, Po-Lei; Hsieh, Jen-Chuen (March 2008). 'Immediate gain is long-term loss: Are there foresighted decision makers in the Iowa Gambling Task?'. Behavioral and Brain Functions. 4 (1): 13. doi:10.1186/1744-9081-4-13. PMC2324107. PMID18353176.
11. ^Richard L. Peterson (9 July 2007). Inside the Investor's Brain: The Power of Mind Over Money. Wiley. ISBN978-0-470-06737-6.
12. ^'Nassim Nicholas Taleb Home & Professional Page'. www.fooledbyrandomness.com.

External links[edit]

• A free implementation of the Iowa Gambling task is available as part of the PEBL Project. For free, you will need to contribute to the WIKI, financially, software development, or publish and cite the program.
• A customizable version of the web implementation that works with Google Spreadsheets (your own spreadsheet) is here.
• A free implementation for Android and iPad.

Sample

Table 1 describes the data pool. All included studies used (a variant of) the traditional IGT payoff scheme 1 or the payoff scheme introduced by Bechara & Damasio 2. A detailed description of the payoff schemes can be found in the Supplemental Text 1.

Table 1

Overview of the studies included in the data pool. See text for a description of the different payoff schemes.

^aInformation that was provided in the original articles. This information consists of the mean age and the standard deviation in brackets, or alternatively the occupation of the participants. In addition, the number of female participants is provided for most datasets.

Most healthy participants sample cards from each deck, and after about 40 or 50 selections are fairly good at sticking to the good decks. Patients with orbitofrontal cortex (OFC) dysfunction, however, continue to persevere with the bad decks, sometimes even though they know that they are losing money overall. Concurrent measurement of galvanic skin response shows that healthy participants show a 'stress' reaction to hovering over the bad decks after only 10 trials, long before conscious sensation that the decks are bad.^[5] By contrast, patients with amygdala lesions never develop this physiological reaction to impending punishment. In another test, patients with ventromedial prefrontal cortex (vmPFC) dysfunction were shown to choose outcomes that yield high immediate gains in spite of higher losses in the future.^[6] Bechara and his colleagues explain these findings in terms of the somatic marker hypothesis.

The Iowa gambling task is currently being used by a number of research groups using fMRI to investigate which brain regions are activated by the task in healthy volunteers^[7] as well as clinical groups with conditions such as schizophrenia and obsessive compulsive disorder.

Critiques[edit]

Iowa Gambling Task Online

Although the IGT has achieved prominence, it is not without its critics. Criticisms have been raised over both its design and its interpretation. Published critiques include:

• A paper by Dunn, Dalgliesh and Lawrence^[4]
• Research by Lin, Chiu, Lee and Hsieh,^[8] who argue that a common result (the 'prominent deck B' phenomenon) argues against some of the interpretations that the IGT has been claimed to support.
• Research by Chiu and Lin,^[9] the 'sunken deck C' phenomenon was identified, which confirmed a serious confound embedded in the original design of IGT, this confound makes IGT serial studies misinterpret the effect of gain-loss frequency as final-outcome for somatic marker hypothesis.
• A research group in Taiwan utilized an IGT-modified and relatively symmetrical gamble for gain-loss frequency and long-term outcome, namely the Soochow gambling task (SGT) demonstrated a reverse finding of Iowa gambling task.^[10] Normal decision makers in SGT were mostly occupied by the immediate perspective of gain-loss and inability to hunch the long-term outcome in the standard procedure of IGT (100 trials under uncertainty). In his book, Inside the investor's brain,^[11]Richard L. Peterson considered the serial findings of SGT may be congruent with the Nassim Taleb's^[12] suggestion on some fooled choices in investment.

References[edit]

Iowa Gambling Task Description Example

1. ^Bechara, A., Damasio, A. R., Damasio, H., Anderson, S. W. (1994). 'Insensitivity to future consequences following damage to human prefrontal cortex'. Cognition. 50 (1–3): 7–15. doi:10.1016/0010-0277(94)90018-3. PMID8039375.CS1 maint: multiple names: authors list (link)
2. ^Damasio, António R. (2008) [1994]. Descartes' Error: Emotion, Reason and the Human Brain. Random House. ISBN978-1-4070-7206-7.CS1 maint: ref=harv (link)Descartes' Error
3. ^Busemeyer JR, Stout JC (2002). 'A contribution of cognitive decision models to clinical assessment: Decomposing performance on the Bechara gambling task'. Psychological Assessment. 14 (3): 253–262. doi:10.1037/1040-3590.14.3.253.
4. ^ ^abDunn BD, Dalgleish T, Lawrence AD (2006). 'The somatic marker hypothesis: a critical evaluation'. Neurosci Biobehav Rev. 30 (2): 239–71. doi:10.1016/j.neubiorev.2005.07.001. PMID16197997.
5. ^Bechara A, Damasio H, Tranel D, Damasio AR (1997). 'Deciding advantageously before knowing the advantageous strategy'. Science. 275 (5304): 1293–5. doi:10.1126/science.275.5304.1293. PMID9036851.
6. ^Bechara A, Damasio H, Tranel D, Damasio AR (2000). 'Characterization of the decision-making deficit of patients with ventromedial prefrontal cortex lesions'. Brain. 123 (11): 2189–2202. doi:10.1093/brain/123.11.2189. PMID11050020.
7. ^Fukui H, Murai T, Fukuyama H, Hayashi T, Hanakawa T (2005). 'Functional activity related to risk anticipation during performance of the Iowa Gambling Task'. NeuroImage. 24 (1): 253–9. doi:10.1016/j.neuroimage.2004.08.028. PMID15588617.
8. ^Lin CH, Chiu YC, Lee PL, Hsieh JC (2007). 'Is deck B a disadvantageous deck in the Iowa Gambling Task?'. Behav Brain Funct. 3: 16. doi:10.1186/1744-9081-3-16. PMC1839101. PMID17362508.
9. ^Chiu, Yao-Chu; Lin, Ching-Hung (August 2007). 'Is deck C an advantageous deck in the Iowa Gambling Task?'. Behavioral and Brain Functions. 3 (1): 37. doi:10.1186/1744-9081-3-37. PMC1995208. PMID17683599.
10. ^Chiu, Yao-Chu; Lin, Ching-Hung; Huang, Jong-Tsun; Lin, Shuyeu; Lee, Po-Lei; Hsieh, Jen-Chuen (March 2008). 'Immediate gain is long-term loss: Are there foresighted decision makers in the Iowa Gambling Task?'. Behavioral and Brain Functions. 4 (1): 13. doi:10.1186/1744-9081-4-13. PMC2324107. PMID18353176.
11. ^Richard L. Peterson (9 July 2007). Inside the Investor's Brain: The Power of Mind Over Money. Wiley. ISBN978-0-470-06737-6.
12. ^'Nassim Nicholas Taleb Home & Professional Page'. www.fooledbyrandomness.com.

External links[edit]

• A free implementation of the Iowa Gambling task is available as part of the PEBL Project. For free, you will need to contribute to the WIKI, financially, software development, or publish and cite the program.
• A customizable version of the web implementation that works with Google Spreadsheets (your own spreadsheet) is here.
• A free implementation for Android and iPad.

Sample

Table 1 describes the data pool. All included studies used (a variant of) the traditional IGT payoff scheme 1 or the payoff scheme introduced by Bechara & Damasio 2. A detailed description of the payoff schemes can be found in the Supplemental Text 1.

Table 1

Overview of the studies included in the data pool. See text for a description of the different payoff schemes.

^aInformation that was provided in the original articles. This information consists of the mean age and the standard deviation in brackets, or alternatively the occupation of the participants. In addition, the number of female participants is provided for most datasets.

^bData collected by Annette Horstmann. These data were first published in Steingroever et al. 10. A subset of this dataset is published in Horstmann, Villringer, and Neumann 4.

^cData of the standard condition. Data of three other conditions can be downloaded here: http://www.ruudwetzels.com/data/EV_data.zip.

^dThe first 90 participants of this dataset are between 18–40 years old (M = 23.04, SD = 5.88), and participants 91–153 are between 61 and 88 years old (M = 76.98, SD = 5.20).

In the traditional payoff scheme, the net outcome of 10 cards from the bad decks (i.e., decks A and B) is −250, and +250 in the case of the good decks (i.e., decks C and D). In addition, there are two decks with frequent losses (decks A and C), and two decks with infrequent losses (decks B and D). In the traditional payoff scheme, there is a variable loss in deck C (i.e., either −25, −50, or −75; classified here as payoff scheme 1). However, some of the included studies used a variant of this payoff scheme in which the loss in deck C was held constant (i.e., −50; classified here as payoff scheme 2). A second difference between payoff scheme 1 and 2 is that payoff scheme 1 uses a fixed sequence of rewards and losses, whereas payoff scheme 2 uses a randomly shuffled sequence.

The payoff scheme introduced by Bechara & Damasio 2 (classified here as payoff scheme 3) also consists of two good decks (decks C and D), and two bad decks (decks A and B), that vary in either having frequent losses (decks A and C) or infrequent losses (decks B and D). However, in contrast to payoff schemes 1 and 2, the schedules of rewards and losses in payoff scheme 3 are structured in such a way that the discrepancy between rewards and losses in the bad decks (decks A and B) changes such that the net outcome decreases by 150 every block of 10 cards (i.e., in the first block, the net outcome is −250, but in the sixth block, it is −1000). By contrast, the net outcome of the good decks (decks C and D) increases by 25 every block of 10 cards (i.e., in the first block, the net outcome is 250, but in the sixth block, it is 375). Thus, the good decks become gradually better, whereas the bad decks become gradually worse. In addition, in contrast to payoff schemes 1 and 2, the wins differ within each deck in payoff scheme 3. Just as payoff scheme 1, payoff scheme 3 uses a fixed sequence of wins and losses.