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“…'t was ten to one; And yet we ventured…” 1 : P300 and Decision Making
Author(s) -
Karis Demetrios,
Chesney Gregory L.,
Donchin Emanuel
Publication year - 1983
Publication title -
psychophysiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.661
H-Index - 156
eISSN - 1469-8986
pISSN - 0048-5772
DOI - 10.1111/j.1469-8986.1983.tb02153.x
Subject(s) - psychology , salience (neuroscience) , stochastic game , expectancy theory , set (abstract data type) , statistics , cognitive psychology , function (biology) , task (project management) , social psychology , audiology , mathematics , mathematical economics , computer science , management , evolutionary biology , economics , biology , programming language , medicine
In some situations subjects' predictions of future events do not accurately reflect the subjective probability associated with these events. We set up such a situation by manipulating the payoff structure in a prediction paradigm, and found that P300 provides an index of the processes responsible for subjective probability, or expectancy, not obtainable from overt predictions. Sixteen subjects were required to predict, on each trial, whether a 1, 2, or 3 would appear on a display. The numbers appeared randomly with probabilities .45, .10, and .45, respectively. In one condition subjects were given bonuses according to an all‐or‐none payoff function in which they received one cent if they predicted correctly, and nothing if they were incorrect. In a second condition bonuses were determined by a linear payoff function in which subjects were paid one cent if they predicted correctly, and one‐half cent if they were off by one (e.g., predict 1 and 2 appears). After each condition subjects estimated the actual number of stimuli presented. These estimates were the same for both conditions, although predictions differed radically, with 2 predicted much more frequently in the linear condition. P300 area was largest for the rare event (2), and the relationship between P300 and probability was unaffected by payoffs. Our design did introduce differences between conditions in the overall “riskiness’ of predictions, and the strategies adopted by most subjects also resulted in differences in the salience, or task relevance, of the feedback stimuli. These differences resulted in an overall increase in P300 in the all‐or‐none condition. A relationship also emerged between the subjects' strategies and their ERPs. Subjects who adopted more effective strategies responded differentially to feedback from high and low risk predictions, whereas the others did not.