Kiyohito Iigaya 1 , * , Giles W Story 2 , 3 , Zeb Kurth-Nelson 2 , 3 , Raymond J Dolan 2 , 3 , Peter Dayan 1
21 April 2016
eLife Sciences Publications, Ltd
reward, anticipation, prediction error, decision-making, reinforcement-learning, Human, Rhesus macaque, Other
When people anticipate uncertain future outcomes, they often prefer to know their fate in advance. Inspired by an idea in behavioral economics that the anticipation of rewards is itself attractive, we hypothesized that this preference of advance information arises because reward prediction errors carried by such information can boost the level of anticipation. We designed new empirical behavioral studies to test this proposal, and confirmed that subjects preferred advance reward information more strongly when they had to wait for rewards for a longer time. We formulated our proposal in a reinforcement-learning model, and we showed that our model could account for a wide range of existing neuronal and behavioral data, without appealing to ambiguous notions such as an explicit value for information. We suggest that such boosted anticipation significantly drives risk-seeking behaviors, most pertinently in gambling.
People, pigeons and monkeys often want to know in advance whether they will receive a reward in the future. This behaviour is irrational when individuals pay for costly information that makes no difference to an eventual outcome. One explanation is that individuals seek information because anticipating reward has hedonic value (it produces a feeling of pleasure). Consistent with this, pigeons are more likely to seek information when they have to wait longer for the potential reward. However, existing models cannot account for why this anticipation of rewards leads to irrational information-seeking.
In many situations, animals are uncertain about what is going to happen. Providing new information can produce a “prediction error” that indexes a discrepancy between what is expected and what actually happens. Iigaya et al. have now developed a mathematical model of information-seeking in which anticipation is boosted by this prediction error.
The model accounts for a wide range of previously unexplained data from monkeys and pigeons. It also successfully explains the behaviour of a group of human volunteers from whom Iigaya et al. elicited informational and actual decisions concerning uncertain and delayed rewards. The longer that the participants had to wait for possible rewards, the more avidly they wanted to find out about them. Further research is now needed to investigate the neural underpinnings of anticipation and its boosting by prediction errors.
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