Slips of Action and Sequential Decisions: A Cross-Validation Study of Tasks Assessing Habitual and Goal-Directed Action Control

Sjoerds, Zsuzsika; Dietrich, Anja; Deserno, Lorenz; Wit, Sanne de; Villringer, Arno; Heinze, Hans-Joachim; Schlagenhauf, Florian; Horstmann, Annette

doi:10.3389/fnbeh.2016.00234

Cited by 44 publications

(47 citation statements)

References 76 publications

(155 reference statements)

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“…In the current study, we aimed to address the two issues raised above by including (1) more highly obese individuals to boost the contrast between groups, and (2) an intermediate overweight group for more sensitivity to detect the existence of potential linear or quadratic relationships between weight status and behavioural control. The original two-step task was implemented to disentangle and directly compare the reliance on model-based and model-free control 16 , 25 , 30 . We hypothesized that weight status relates to the degree to which individuals rely on model-based and model-free learning, and that it may do so in a linear or quadratic manner.…”

Section: Introductionmentioning

confidence: 99%

Reliance on model-based and model-free control in obesity

Janssen

Mahner

Schlagenhauf

et al. 2020

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Consuming more energy than is expended may reflect a failure of control over eating behaviour in obesity. Behavioural control arises from a balance between two dissociable strategies of reinforcement learning: model-free and model-based. We hypothesized that weight status relates to an imbalance in reliance on model-based and model-free control, and that it may do so in a linear or quadratic manner. To test this, 90 healthy participants in a wide BMI range [normal-weight (n = 31), overweight (n = 29), obese (n = 30)] performed a sequential decision-making task. The primary analysis indicated that obese participants relied less on model-based control than overweight and normal-weight participants, with no difference between overweight and normal-weight participants. In line, secondary continuous analyses revealed a negative linear, but not quadratic, relationship between BMI and model-based control. Computational modelling of choice behaviour suggested that a mixture of both strategies was shifted towards less model-based control in obese participants. Our findings suggest that obesity may indeed be related to an imbalance in behavioural control as expressed in a phenotype of less model-based control potentially resulting from enhanced reliance on model-free computations.

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Section: Introductionmentioning

confidence: 99%

Reliance on model-based and model-free control in obesity

Janssen

Mahner

Schlagenhauf

et al. 2020

Sci Rep

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“…Both studies found that model-based learning was a positive predictor of flexible adjustments based on a change in outcome value (i.e., goal-directedness), whereas model-free learning was unrelated to performance on the outcome-devaluation task. Relatedly, a recent study found that performance on the SOAT showed a moderately positive correlation with model-based learning on the two-step task, but once again, bore no relation with model-free learning ( Sjoerds et al, 2016 ). Taken together, these studies are consistent with the notion that model-based reinforcement learning is a good approximation of goal-directed control defined in terms of performance on outcome-devaluation tasks.…”

Section: Discussionmentioning

confidence: 99%

Shifting the balance between goals and habits: Five failures in experimental habit induction.

Wit¹,

Kindt²,

Knot³

et al. 2018

Journal of Experimental Psychology: General

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Habits are repetitive behaviors that become ingrained with practice, routine, and repetition. The more we repeat an action, the stronger our habits become. Behavioral and clinical neuroscientists have become increasingly interested in this topic because habits may contribute to aspects of maladaptive human behavior, such as compulsive behavior in psychiatry. Numerous studies have demonstrated that habits can be induced in otherwise healthy rats by simply overtraining stimulus–response behaviors. However, despite growing interest in this topic and its application to psychiatry, a similar body of work in humans is absent. Only a single study has been published in humans that shows the effect of extensive training on habit expression. Here, we report five failed attempts to demonstrate that overtraining instrumental behavior leads to the development of inflexible habits in humans, using variants of four previously published outcome devaluation paradigms. Extensive training did not lead to greater habits in two versions of an avoidance learning task, in an appetitive slips-of-action task, or in two independent attempts to replicate the original demonstration. The finding that these outcome devaluation procedures may be insensitive to duration of stimulus-response training in humans has implications for prior work in psychiatric populations. Specifically, it converges with the suggestion that the failures in outcome devaluation in compulsive individuals reflect dysfunction in goal-directed control, rather than overactive habit learning. We discuss why habits are difficult to experimentally induce in healthy humans, and the implications of this for future research in healthy and disordered populations.

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“…Second, there is some debate on whether – and to what extent – model-free learning maps on to traditional definitions of habitual control (Miller et al, 2019; see also Gillan et al, 2015; Sjoerds et al, 2016). Miller et al (2019) argue that traditional conceptualizations of habits reflect stimulus-response associations devoid of expected value representations (i.e., are value-free ), whereas model-free algorithms still depend on the expected value representations associated with a learner’s available actions (i.e., are value-based ).…”

Section: Discussionmentioning

confidence: 99%

Model-Based and Model-Free Social Cognition: Investigating the Role of Habit in Social Attitude Formation and Choice

et al. 2019

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Do habits play a role in our social impressions? To investigate the contribution of habits to the formation of social attitudes, we examined the roles of model-free and model-based reinforcement learning in social interactions – computations linked in past work to habit and planning, respectively. Participants in this study learned about novel individuals in a sequential reinforcement learning paradigm, choosing financial advisors who led them to high- or low-paying stocks. Results indicated that participants relied on both model-based and model-free learning, such that each type of learning was expressed in both advisor choices and post-task self-reported liking of advisors. Specifically, participants preferred advisors who could provide large future rewards as well as advisors who had provided them with large rewards in the past. Although participants relied more heavily on model-based learning overall, they varied in their use of model-based and model-free learning strategies, and this individual difference influenced the way in which learning related to self-reported attitudes: among participants who relied more on model-free learning, model-free social learning related more to post-task attitudes. We discuss implications for attitudes, trait impressions, and social behavior, as well as the role of habits in a memory systems model of social cognition.

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Slips of Action and Sequential Decisions: A Cross-Validation Study of Tasks Assessing Habitual and Goal-Directed Action Control

Cited by 44 publications

References 76 publications

Reliance on model-based and model-free control in obesity

Reliance on model-based and model-free control in obesity

Shifting the balance between goals and habits: Five failures in experimental habit induction.

Model-Based and Model-Free Social Cognition: Investigating the Role of Habit in Social Attitude Formation and Choice

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