Iowa gambling task
The Iowa gambling task or (IGT) is a psychological task thought to simulate real-life decision making. It was introduced by Antoine Bechara, Antonio Damasio, Hanna Damásio and Steven Anderson,[1] then researchers at the University of Iowa. It has been brought to popular attention by António Damásio (proponent of the Somatic markers hypothesis) in his best-selling book Descartes' Error.[2]
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 100 papers that made use of this paradigm.[4]
Contents
Task structure
Participants are presented with 4 virtual decks of cards on a computer screen. They are told that each time they choose a card they will win some game money. Every so often, however, choosing a card causes them to lose some money. The goal of the game is to win as much money as possible. The decks differ from each other in the number of trials over which the losses are distributed. Thus, some decks are "bad decks", and other decks are "good decks", because some will lead to losses over the long run, and others will lead to gains.
Common findings
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 (VM) 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 of the Iowa Gambling Task
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] [1], 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.
External links
- 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.
Notes
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- ↑ http://www.fooledbyrandomness.com/
