How Accumulated Real Life Stress Experience and Cognitive Speed Interact on Decision-Making Processes
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Rationale: Advances in neurocomputational modeling suggest that valuation systems for goal-directed (deliberative) on one side, and habitual (automatic) decision-making on the other side may rely on distinct computational strategies for reinforcement learning, namely model-free versus model-based learning. As a key theoretical difference, the model-based system strongly demands cognitive functions to plan actions prospectively based on an internal cognitive model of the environment, whereas valuation in the model-free system relies on rather simple learning rules from operant conditioning to retrospectively associate actions with their outcomes and is thus cognitively less demanding. Acute stress reactivity is known to impair model-based but not model-free choice behavior, with higher working memory capacity protecting the model-based system from acute stress. However, it is not clear which impact accumulated real life stress has on model-free and model-based decision systems and how this influence interacts with cognitive abilities. Methods: We used a sequential decision-making task distinguishing relative contributions of both learning strategies to choice behavior, the Social Readjustment Rating Scale questionnaire to assess accumulated real life stress, and the Digit Symbol Substitution Test to test cognitive speed in 95 healthy subjects. Results: Individuals reporting high stress exposure who had low cognitive speed showed reduced model-based but increased model-free behavioral control. In contrast, subjects exposed to accumulated real life stress with high cognitive speed displayed increased model-based performance but reduced model-free control. Conclusions: These findings suggest that accumulated real life stress exposure can enhance reliance on cognitive speed for model-based computations, which may ultimately protect the model-based system from the detrimental influences of accumulated real life stress. The combination of accumulated real life stress exposure and slower information processing capacities, however, might favor model-free strategies. Thus, the valence and preference of either system strongly depends on stressful experiences and individual cognitive capacities.
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Chronic stress tips the balance of behavioral control towards habit.
“Chronic stress tips the balance of behavioral control towards habit1–5.”
From A dual-pathway architecture for stress to disrupt agency and promote habit (2025) · cites this paper as [3]
After chronic stress, people become less able to adapt their behavior when its outcome has been devalued.
“Indeed, after chronic stress, people become less able to adapt their behavior when its outcome has been devalued1–5.”
From A dual-pathway architecture for stress to disrupt agency and promote habit (2025) · cites this paper as [3]
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- Authors
- Friedel, E.
- Affiliations
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE)
- Corresponding author
- Friedel, Eva
- ORCID
- Friedel, Eva
- Venue
- Frontiers in Human Neuroscience
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- Frontiers Media SA
- Published
- 2017
- Volume
- 11
- Pages
- 302-302
- ISSN
- 1662-5161 (ISSN-L)
- PMC
- PMC5462964
- OpenAlex
- W2624789916
- Cited by
- 29
- References
- 58
- Citations by year
- 2026: 4 · 2025: 3 · 2024: 4 · 2023: 3 · 2022: 4 · 2021: 3 · 2020: 2 · 2019: 3 · 2018: 3
- FWCI
- 1.25
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- journal article
- Language
- en
- Open access
- gold
- doi.org
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- cc-by
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- Zurich Open Repository and Archive (University of Zurich)
- Funders
- Deutsche Forschungsgemeinschaft (FOR1617, HE2597/14-2, WA1539/7-1, ZI1119/3-1, FR3572/1-1, WA 1539/7-1, HE2597/14-1, HE2597/14/-2, /14-1, HE 2597/14-1, FR3572/1-1)
- Berlin Institute of Health
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Keywords
- cognitive speed, model-based learning, model-free learning, decision-making, working memory capacity, sequential decision making, Social Readjustment Rating Scale, Digit Symbol Substitution Test, reinforcement learning
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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