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Adaptive integration of habits into depth-limited planning defines a habitual-goal-directed spectrum.

ABSTRACT: Behavioral and neural evidence reveal a prospective goal-directed decision process that relies on mental simulation of the environment, and a retrospective habitual process that caches returns previously garnered from available choices. Artificial systems combine the two by simulating the environment up to some depth and then exploiting habitual values as proxies for consequences that may arise in the further future. Using a three-step task, we provide evidence that human subjects use such a normative plan-until-habit strategy, implying a spectrum of approaches that interpolates between habitual and goal-directed responding. We found that increasing time pressure led to shallower goal-directed planning, suggesting that a speed-accuracy tradeoff controls the depth of planning with deeper search leading to more accurate evaluation, at the cost of slower decision-making. We conclude that subjects integrate habit-based cached values directly into goal-directed evaluations in a normative manner.

SUBMITTER: Keramati M

PROVIDER: S-EPMC5111694 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Adaptive integration of habits into depth-limited planning defines a habitual-goal-directed spectrum.

Keramati Mehdi M Smittenaar Peter P Dolan Raymond J RJ Dayan Peter P

Proceedings of the National Academy of Sciences of the United States of America 20161024 45

Behavioral and neural evidence reveal a prospective goal-directed decision process that relies on mental simulation of the environment, and a retrospective habitual process that caches returns previously garnered from available choices. Artificial systems combine the two by simulating the environment up to some depth and then exploiting habitual values as proxies for consequences that may arise in the further future. Using a three-step task, we provide evidence that human subjects use such a nor ...[more]

PMID: 27791110

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Project description:Behavioral evidence suggests that instrumental conditioning is governed by two forms of action control: a goal-directed and a habit learning process. Model-based reinforcement learning (RL) has been argued to underlie the goal-directed process; however, the way in which it interacts with habits and the structure of the habitual process has remained unclear. According to a flat architecture, the habitual process corresponds to model-free RL, and its interaction with the goal-directed process is coordinated by an external arbitration mechanism. Alternatively, the interaction between these systems has recently been argued to be hierarchical, such that the formation of action sequences underlies habit learning and a goal-directed process selects between goal-directed actions and habitual sequences of actions to reach the goal. Here we used a two-stage decision-making task to test predictions from these accounts. The hierarchical account predicts that, because they are tied to each other as an action sequence, selecting a habitual action in the first stage will be followed by a habitual action in the second stage, whereas the flat account predicts that the statuses of the first and second stage actions are independent of each other. We found, based on subjects' choices and reaction times, that human subjects combined single actions to build action sequences and that the formation of such action sequences was sufficient to explain habitual actions. Furthermore, based on Bayesian model comparison, a family of hierarchical RL models, assuming a hierarchical interaction between habit and goal-directed processes, provided a better fit of the subjects' behavior than a family of flat models. Although these findings do not rule out all possible model-free accounts of instrumental conditioning, they do show such accounts are not necessary to explain habitual actions and provide a new basis for understanding how goal-directed and habitual action control interact.

Project description:IntroductionHarmful behavior such as smoking may reflect a disturbance in the balance of goal-directed and habitual control. Animal models suggest that habitual control develops after prolonged substance use. In this study, we investigated whether smokers (N = 49) differ from controls (N = 46) in the regulation of goal-directed and habitual behavior. It was also investigated whether individual differences in nicotine dependence levels were associated with habitual responding.MethodsWe used two different multistage instrumental learning tasks that consist of an instrumental learning phase, subsequent outcome devaluation, and a testing phase to measure the balance between goal-directed and habitual responding. The testing phases of these tasks occurred after either appetitive versus avoidance instrumental learning. The appetitive versus aversive instrumental learning stages in the two different tasks modeled positive versus negative reinforcement, respectively.ResultsSmokers and nonsmoking controls did not differ on habitual versus goal-directed control in either task. Individual differences in nicotine dependence within the group of smokers, however, were positively associated with habitual responding after appetitive instrumental learning. This effect seems to be due to impaired stimulus-outcome learning, thereby hampering goal-directed task performance and tipping the balance to habitual responding.ConclusionsThe current finding highlights the importance of individual differences within smokers. For future research, neuroimaging studies are suggested to further unravel the nature of the imbalance between goal-directed versus habitual control in severely dependent smokers by directly measuring activity in the corresponding brain systems.ImplicationsGoal-directed versus habitual behavior in substance use and addiction is highly debated. This study investigated goal-directed versus habitual control in smokers. The findings suggest that smokers do not differ from controls in goal-directed versus habitual control. Individual differences in nicotine dependence within smokers, however, were positively associated with habitual responding after appetitive instrumental learning. This effect seems to be due to impaired stimulus-outcome learning, thereby hampering goal-directed task performance and tipping the balance to habitual responding. These findings add to the ongoing debate on habitual versus goal-directed control in addiction and emphasize the importance of individual differences within smokers.

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Adaptive integration of habits into depth-limited planning defines a habitual-goal-directed spectrum.

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Adaptive integration of habits into depth-limited planning defines a habitual-goal-directed spectrum.

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