Building momentum: A computational account of persistence toward long-term goals. - Sneha Aenugu; John P O'Doherty (PLoS Computational Biology)
Extended goals necessitate extended commitment. We address how humans select between multiple goals in a temporally extended setting. We probe whether humans engage in prospective valuation of goals by estimating which goals are likely to yield future success and choosing those, or whether they rely on a less optimal retrospective strategy, favoring goals with greater accumulated progress even if less likely to result in success. To address this, we introduce a novel task in which goals need to be persistently selected until a set target is reached to earn an overall reward. In a series of experiments, we show that human goal selection involves a mix of prospective and retrospective influences, with an undue bias in favor of retrospective valuation. We show that a goal valuation model utilizing the concept of 'momentum', where progress accrued toward a goal builds value and persists across trials, successfully explains human behavior better than alternative frameworks. Our findings thus suggest an important role for momentum in explaining the valuation process underpinning human goal selection.