Iowa Gambling Task The Iowa gambling task is a decision-making task that has been used in an fMRI study of binge drinkers and showed that heavy alcohol users make more disadvantageous decisions on the task than nonusers (Xiao et al., 2013). From: Progress in Brain Research, 2016. Iowa Gambling Task. A simulation of real life decision-making, the Iowa gambling task is widely used in cognition and emotion research. Participants are presented with four virtual decks of cards on a computer screen. They are told that each time they choose a card they stand to win some game money.

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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.

In my last post, I wrote that people who’re primed to think about free will tend to make riskier decisions. This is true, but like many things in psychology, it’s not quite as simple as it sounds at first.

The problem is that “risky decisions” aren’t a tangible thing that’s easy to quantify. When I say that people with free will are more likely to make risky decisions, what I mean is that they’re more likely to behave a certain way on a laboratory task.

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 say something about how you make decisions.

However, before I do this, you might want to try playing the game yourself. There’s an iOS app and an Android app available. If you want to try it firsthand, you should stop reading now and do it – I’m about to give away the secret to how the game works, after which point you won’t be able to play anymore.

OK, don’t say I didn’t warn you!

The IGT consists of four stacks of cards, and you play by turning over cards from any of the stacks. At any point, you choose which stack you want to pick a card from.

Some of the cards give you rewards, and you gain money. Other cards penalize you, and you lose money. The goal, of course, is to end up with as much money as possible.

When you flip over a given card, it’s up to chance whether that card’s going to reward you or penalize you. But there’s one thing you do know that makes the game work: the four decks are stacked differently, so some decks are better overall than others.

That’s all you know when you start. What you don’t know is the specific rules of how the decks are stacked (spoiler alert!):

• The cards in decks A and B have larger rewards than the cards in decks C and D
• The penalty cards in deck A are more frequent than the penalty cards in deck B, but the penalties in deck B are larger than in deck A. Likewise, the penalty cards in deck C are more frequent than the penalty cards in deck B, but the penalties in deck D are larger than in deck c.
• Altogether, the penalties in decks A and B outweigh the rewards, but the rewards in decks C and D outweigh the penalties. In other words, choosing cards from the decks with the higher rewards loses money over time, and choosing cards from the decks with the lower rewards gains it.

Therefore, the basic idea is that there’s a conflict between short-term and long-term rewards. If you keep picking the cards with the higher short-term rewards, you’ll lose money in the long term.

When researchers started having test subjects play the IGT, they found that people with damage to the prefrontal cortex, a part of the brain involved in decision making, don’t adapt to choose from the “good” decks that win money over time. They keep going for the decks that lose money but have larger immediate rewards.

The initial assumption was that most healthy people explore all the decks in the early stages of the game and grow to prefer decks C and D, learning to avoid the “bad” decks.

But it turns out that there’s actually quite a bit of variety in the approaches people take. Some people opt for the larger immediate rewards even if it means playing a suboptimal long-term strategy. Many people also develop a preference for the decks that have the most frequent rewards – these people choose more cards from deck B, which has very infrequent but very large penalties.

Overall, strategies that emphasize immediate rewards but tend to lose money over time are riskier. These strategies are linked with risk-taking and impulsivity although the exact nature of the connection isn’t clear.

So when I said in my last post that people who’re thinking about free will make riskier decisions, what I meant was that they play riskier strategies on the Iowa Gambling Task – that is, strategies that give larger short-term rewards but lose money in the long run.

Iowa Gambling Task

And these risky strategies correlate with a variety of risky real-world behaviors, including everything from reckless driving to getting tattoos. Stop and think for a minute about how what strategy you use on a simple game of chance predicts these other things about you.

More generally, the research that’s been done using the Iowa Gambling Task gives us some insight into how people make decisions. For example, it tells us:

• Sleep can improve decision making: Players who sleep between games choose deck B (the one with high, frequent rewards but occasional devastating losses) less often.
• Hunger can improve decision making: People who are hungry actually perform better on the IGT. Apparently being hungry doesn’t increase your appetite for risk.
• Too much and too little anxiety both lead to bad decisions: People with a moderate amount of anxiety are the only ones who win money on the IGT as a group. People with low levels of anxiety preferred deck B because they were overly focused on rewards while people with high levels of anxiety preferred deck A for reasons that aren’t entirely clear.
• Working memory helps decision making: People with high working memory (the kind of memory you use to hold things in your mind and, well, work with them) do better on the IGT than people with low working memory. One possibility is that making good decisions means being able to hold all the relevant factors in your mind and take them into consideration.

So this is one of the things that’s cool about psychology: something as simple as how someone plays this basic card game ties into all these other factors.

Iowa Gambling Task Professional Manual

But that’s one of the things that makes psychological studies so open to interpretation too. Going back to the study of free will, you could say that people who are thinking about free will make “riskier decisions.” But you could also say they have worse decision making abilities. Or they’re less sensitive to punishment. Or they’re just worse at math. Some of these things are related, but they’re different ways of framing the same data.

In fact, there’s still a lot of disagreement over how to interpret the way people play the IGT. After the IGT was introduced, it took a while before researchers realized just how often “normal” people prefer decks with frequent rewards that still lose over time (especially deck B, which turns out to be way more popular than it has any right to be!).

Iowa Gambling Task Description Template

Therefore, the IGT is probably a good example of how you should look at results from any psychology study: half with wonder at what well-designed experiments can reveal and half with skepticism over how the results are being interpreted.

Iowa Gambling Task Description Example

Dice image: FreeImages.com/J. Henning Buchholz

IGT image: Wikipedia/PaulWicks