The interaction of acute and chronic stress impairs model-based behavioral control

Radenbach, Christoph; Reiter, Andrea; Engert, Veronika; Sjoerds, Zsuzsika; Villringer, Arno; Heinze, Hans‐Jochen; Deserno, Lorenz; Schlagenhauf, Florian

doi:10.1016/j.psyneuen.2014.12.017

Cited by 98 publications

(112 citation statements)

References 47 publications

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“…Model-fitting results showed a combination of both these strategies at the second stage, in both groups of subjects (with the weight of the habitual system being 0.37 ± 0.18 for the high-resource group, and 0.59 ± 0.23 for the low-resource group). This result confirms previous demonstrations of habitual and goal-directed strategies in depth-limited tasks (8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(20)(21)(22)(23). Furthermore, across subjects within both groups, the weight of using the plan-until-habit strategy at the first stage was correlated with the weight of using the pure habitual strategy at the second stage (Fig.…”

Section: Resultssupporting

confidence: 90%

“…Previous studies show distinct behavioral and neurobiological signatures of both systems (8-18). Furthermore, consistent with the theoretical strengths and weaknesses of each system (2, 19), different experimental conditions influence the relative contributions of the two systems in controlling behavior according to their respective competencies (20)(21)(22)(23).Here, we suggest that individuals, rather than simply showing greater reliance on the more competent system in each condition, combine the relative strengths of the two systems in a normative manner by integrating habit-based cached values directly into goaldirected evaluations. Specifically, we propose that given available resources (time, working memory, etc.…”

supporting

confidence: 72%

“…Previous studies show distinct behavioral and neurobiological signatures of both systems (8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18). Furthermore, consistent with the theoretical strengths and weaknesses of each system (2,19), different experimental conditions influence the relative contributions of the two systems in controlling behavior according to their respective competencies (20)(21)(22)(23).…”

supporting

confidence: 63%

“…Previous studies of planning have used shallow tasks (8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(20)(21)(22)(23) and have found evidence for the two extreme values of k. Rather than this dichotomous dependence on either goaldirected or habitual systems, we hypothesize that individuals use an integrative plan-until-habit system for decision making with intermediate values of k. We further hypothesize that the choice of k is a covert internal decision that is influenced by the availability of cognitive resources.…”

mentioning

confidence: 89%

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

Keramati

Smittenaar

Dolan

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

189

203

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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.planning | habit | reinforcement learning | speed/accuracy tradeoff | tree-based evaluation B ehavioral and neural evidence suggest that the brain uses distinct goal-directed and habitual systems for decisionmaking (1-5). A goal-directed system exploits an individual's model, i.e., their knowledge of environmental dynamics, to simulate the consequences that will likely follow a choice (6) (Fig. 1A). Such evaluations, which assess a decision-tree expanding into the future to estimate the total reward, adapt flexibly to changes in environmental dynamics or the values of outcomes. Evaluating deep trees, however, is computationally expensive (in terms of time, working memory, metabolic energy, etc.) and potentially error-prone. By contrast, the habitual system simply caches the rewards received on previous trials conditional on the choice (Fig. 1C) without a representational characterization of the environment (hence being called "model-free") (6, 7). This process hinders adaptation to changes in the environment, but has advantageous computational simplicity. Previous studies show distinct behavioral and neurobiological signatures of both systems (8-18). Furthermore, consistent with the theoretical strengths and weaknesses of each system (2, 19), different experimental conditions influence the relative contributions of the two systems in controlling behavior according to their respective competencies (20)(21)(22)(23).Here, we suggest that individuals, rather than simply showing greater reliance on the more competent system in each condition, combine the relative strengths of the two systems in a normative manner by integrating habit-based cached values directly into goaldirected evaluations. Specifically, we propose that given available resources (time, working memory, etc.), individuals decide the depth k up to which they can afford full forward simulations and use cached habitual values thereafter. That is, individuals compute the value of a choice by adding the first k rewards, predicted by the explicit simulation, to the value...

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Section: Resultssupporting

confidence: 90%

supporting

confidence: 72%

supporting

confidence: 63%

mentioning

confidence: 89%

See 2 more Smart Citations

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

Keramati

Smittenaar

Dolan

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

189

203

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“…However, factors commonly known to influence the shift from goaldirected to habitual behaviours appear to have a greater effect on the modelbased but not model-free measure. Thus, an acute stress challenge impaired model-based control in healthy controls, an effect mediated by working memory and stress (66,67). Model-based control also depends on individual cognitive capacity (e.g.…”

Section: Characteristics Of Multi-step Tasksmentioning

confidence: 99%

Model-Based Control in Dimensional Psychiatry

Voon

Reiter

Sebold

et al. 2017

Biological Psychiatry

102

105

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Comparison of the Association Between Goal-Directed Planning and Self-reported Compulsivity vs Obsessive-Compulsive Disorder Diagnosis

et al. 2020

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IMPORTANCE Dimensional definitions of transdiagnostic mental health problems have been suggested as an alternative to categorical diagnoses, having the advantage of capturing heterogeneity within diagnostic categories and similarity across them and bridging more naturally psychological and neural substrates. OBJECTIVE To examine whether a self-reported compulsivity dimension has a stronger association with goal-directed and related higher-order cognitive deficits compared with a diagnosis of obsessive-compulsive disorder (OCD). DESIGN, SETTING, AND PARTICIPANTSIn this cross-sectional study, patients with OCD and/or generalized anxiety disorder (GAD) from across the United States completed a telephone-based diagnostic interview by a trained rater, internet-based cognitive testing, and self-reported clinical assessments from October 8, 2015, to October 1, 2017. Follow-up data were collected to test for replicability. MAIN OUTCOMES AND MEASURESPerformance was measured on a test of goal-directed planning and cognitive flexibility (Wisconsin Card Sorting Test [WCST]) and a test of abstract reasoning. Clinical variables included DSM-5 diagnosis of OCD and GAD and 3 psychiatric symptom dimensions (general distress, compulsivity, and obsessionality) derived from a factor analysis. RESULTS Of 285 individuals in the analysis (mean [SD] age, 32 [12] years; age range, 18-77 years; 219 [76.8%] female), 111 had OCD; 82, GAD; and 92, OCD and GAD. A diagnosis of OCD was not associated with goal-directed performance compared with GAD at baseline (β [SE], −0.02 [0.02]; P = .18). In contrast, a compulsivity dimension was negatively associated with goal-directed performance (β [SE], −0.05 [0.02]; P = .003). Results for abstract reasoning task and WCST mirrored this pattern; the compulsivity dimension was associated with abstract reasoning (β [SE], 2.99 [0.63]; P < .001) and several indicators of WCST performance (eg, categories completed: β [SE], −0.57 [0.09]; P < .001), whereas OCD diagnosis was not (abstract reasoning: β [SE], 0.39 [0.66]; P = .56; categories completed: β [SE], −0.09 [0.10]; P = .38). Other symptom dimensions relevant to OCD, obsessionality, and general distress had no reliable association with goal-directed performance, WCST, or abstract reasoning. Obsessionality had a positive association with requiring more trials to reach the first category on the WCST at baseline (β [SE], 2.92 [1.39]; P = .04), and general distress was associated with impaired goal-directed performance at baseline (β [SE],−0.04 [0.02]; P = .01). However, unlike the key results of this study, neither survived correction for multiple comparisons or was replicated at follow-up testing.CONCLUSIONS AND RELEVANCE Deficits in goal-directed planning in OCD may be more strongly associated with a compulsivity dimension than with OCD diagnosis. This result may have implications for research assessing the association between brain mechanisms and clinical manifestations and for understanding the structure of mental illness.

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The interaction of acute and chronic stress impairs model-based behavioral control

Cited by 98 publications

References 47 publications

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

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

Model-Based Control in Dimensional Psychiatry

Comparison of the Association Between Goal-Directed Planning and Self-reported Compulsivity vs Obsessive-Compulsive Disorder Diagnosis

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