ABSTRACT A goal of computational psychiatry is to ground symptoms in basic mechanisms. Theory suggests that avoidance in anxiety disorders may reflect dysregulated mental simulation, a

process for evaluating candidate actions. If so, these covert processes should have observable consequences: choices reflecting increased and biased deliberation. In two online general

population samples, we examined how self-report symptoms of social anxiety disorder predict choices in a socially framed reinforcement learning task, the patent race, in which the pattern of

choices reflects the content of deliberation. Using a computational model to assess learning strategy, we found that self-report social anxiety was indeed associated with increased

neuro-computational mechanisms. Access through your institution Buy or subscribe This is a preview of subscription content, access via your institution ACCESS OPTIONS Access through your

institution Access Nature and 54 other Nature Portfolio journals Get Nature+, our best-value online-access subscription $29.99 / 30 days cancel any time Learn more Subscribe to this journal

Receive 12 digital issues and online access to articles $119.00 per year only $9.92 per issue Learn more Buy this article * Purchase on SpringerLink * Instant access to full article PDF Buy

now Prices may be subject to local taxes which are calculated during checkout ADDITIONAL ACCESS OPTIONS: * Log in * Learn about institutional subscriptions * Read our FAQs * Contact customer

support SIMILAR CONTENT BEING VIEWED BY OTHERS JUMPING TO ATTRIBUTIONS DURING SOCIAL EVALUATION Article Open access 04 July 2024 LACK OF OPTIMISTIC BIAS DURING SOCIAL EVALUATION LEARNING

REFLECTS REDUCED POSITIVE SELF-BELIEFS IN DEPRESSION AND SOCIAL ANXIETY, BUT VIA DISTINCT MECHANISMS Article Open access 28 September 2024 VALUE-FREE RANDOM EXPLORATION IS LINKED TO

IMPULSIVITY Article Open access 04 August 2022 DATA AVAILABILITY Processed data (per-participant estimated model parameters and covariates) supporting all of the statistical results of the

study, and the raw choice data from which the model parameters were estimated, are available at https://github.com/ndawlab/patentrace. Raw psychometric data (questionnaire responses) are

available from the corresponding authors upon request. CODE AVAILABILITY Custom MATLAB code to reproduce all statistical results and tables is available at

https://github.com/ndawlab/patentrace. Custom Julia code for estimating learning model parameters from raw choice data is available at https://github.com/ndawlab/em. Additional code (for

figures and analyses of psychometric data) is available from the corresponding authors upon request. REFERENCES * Maia, T. V. & Frank, M. J. From reinforcement learning models to

psychiatric and neurological disorders. _Nat. Neurosci._ 14, 154–162 (2011). Article  CAS  PubMed  PubMed Central  Google Scholar  * Huys, Q. J. M., Maia, T. V. & Frank, M. J.

Computational psychiatry as a bridge from neuroscience to clinical applications. _Nat. Neurosci._ 19, 404–413 (2016). Article  CAS  PubMed  PubMed Central  Google Scholar  * Huys, Q. J. M.

et al. Bonsai trees in your head: how the Pavlovian system sculpts goal-directed choices by pruning decision trees. _PLoS Comput. Biol._ 8, e1002410 (2012). Article  CAS  PubMed  PubMed

Central  Google Scholar  * Moutoussis, M., Eldar, E. & Dolan, R. J. Building a new field of computational psychiatry. _Biol. Psychiatry_ 82, 388–390 (2017). Article  PubMed  Google

Scholar  * Montague, P. R., Dolan, R. J. & Friston, K. J. Computational psychiatry. _Trends Cogn. Sci._ 16, 72–80 (2012). Article  PubMed  Google Scholar  * Daw, N. D., Niv, Y. &

Dayan, P. Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral control. _Nat. Neurosci._ 8, 1704–1711 (2005). Article  CAS  PubMed  Google

Scholar  * Johnson, A. & Redish, A. D. Neural ensembles in CA3 transiently encode paths forward of the animal at a decision point. _J. Neurosci._ 27, 12176–12189 (2007). Article  CAS 

PubMed  PubMed Central  Google Scholar  * Mattar, M. G. & Daw, N. D. Prioritized memory access explains planning and hippocampal replay. _Nat. Neurosci._ 21, 1609–1617 (2018). Article 

CAS  PubMed  PubMed Central  Google Scholar  * Schultz, W., Dayan, P. & Montague, P. R. A neural substrate of prediction and reward. _Science_ 275, 1593–1599 (1997). Article  CAS  PubMed

  Google Scholar  * Daw, N. D., Gershman, S. J., Seymour, B., Dayan, P. & Dolan, R. J. Model-based influences on humans’ choices and striatal prediction errors. _Neuron_ 69, 1204–15

(2011). Article  CAS  PubMed  PubMed Central  Google Scholar  * Otto, A. R., Gershman, S. J., Markman, A. B. & Daw, N. D. The curse of planning. _Psychol. Sci._ 24, 751–761 (2013).

Article  PubMed  Google Scholar  * Doll, B. B., Bath, K. G., Daw, N. D. & Frank, M. J. Variability in dopamine genes dissociates model-based and model-free reinforcement learning. _J.

Neurosci._ 36, 1211–22 (2016). Article  CAS  PubMed  PubMed Central  Google Scholar  * Everitt, B. J. & Robbins, T. W. Neural systems of reinforcement for drug addiction: from actions to

habits to compulsion. _Nat. Neurosci._ 8, 1481–1489 (2005). Article  CAS  PubMed  Google Scholar  * Gillan, C. M. et al. Disruption in the balance between goal-directed behavior and habit

learning in obsessive–compulsive disorder. _Am. J. Psychiatry_ 168, 718–726 (2011). Article  PubMed  PubMed Central  Google Scholar  * Gillan, C. M. et al. Counterfactual processing of

economic action–outcome alternatives in obsessive–compulsive disorder: further evidence of impaired goal-directed behavior. _Biol. Psychiatry_ 75, 639–646 (2014). Article  PubMed  PubMed

Central  Google Scholar  * Gillan, C. M., Kosinski, M., Whelan, R., Phelps, E. A. & Daw, N. D. Characterizing a psychiatric symptom dimension related to deficits in goal-directed

control. _eLife_ 5, e11305 (2016). Article  PubMed  PubMed Central  Google Scholar  * Reiter, A. M. F. et al. Behavioral and neural signatures of reduced updating of alternative options in

alcohol-dependent patients during flexible decision-making. _J. Neurosci._ 36, 10935–10948 (2016). Article  CAS  PubMed  PubMed Central  Google Scholar  * Voon, V. et al. Disorders of

compulsivity: a common bias towards learning habits. _Mol. Psychiatry_ 20, 345–52 (2015). Article  CAS  PubMed  Google Scholar  * Huys, Q. J. M., Daw, N. D. & Dayan, P. Depression: a

decision-theoretic analysis. _Annu. Rev. Neurosci._ 38, 1–23 (2015). Article  CAS  PubMed  Google Scholar  * Gagne, C., Dayan, P. & Bishop, S. J. When planning to survive goes wrong:

predicting the future and replaying the past in anxiety and PTSD. _Curr. Opin. Behav. Sci._ 24, 89–95 (2018). Article  Google Scholar  * Solway, A., Lohrenz, T. & Montague, P. R. Loss

aversion correlates with the propensity to deploy model-based control. _Front. Neurosci._ 13, 915 (2019). Article  PubMed  PubMed Central  Google Scholar  * Zorowitz, S., Momennejad, I.

& Daw, N. D. Anxiety, avoidance, and sequential evaluation. _Comput. Psychiatry_ 4, 1 (2020). Article  Google Scholar  * Faulkner, P. et al. A comparison of “pruning” during multi-step

planning in depressed and healthy individuals. _Psychol. Med._ https://doi.org/10.1017/S0033291721000799 (2021). * Shapiro, D. N., Chandler, J. & Mueller, P. A. Using Mechanical Turk to

study clinical populations. _Clin. Psychol. Sci._ 1, 213–220 (2013). Article  Google Scholar  * Norton, A. R. & Abbott, M. J. Self-focused cognition in social anxiety: a review of the

theoretical and empirical literature. _Behav. Change_ 33, 44–64 (2015). Article  Google Scholar  * Rapoport, A. & Amaldoss, W. Mixed strategies and iterative elimination of strongly

dominated strategies: an experimental investigation of states of knowledge. _J. Econ. Behav. Organ._ 42, 483–521 (2000). Article  Google Scholar  * Zhu, L., Mathewson, K. E. & Hsu, M.

Dissociable neural representations of reinforcement and belief prediction errors underlie strategic learning. _Proc. Natl Acad. Sci. USA_ 109, 1419–1424 (2012). Article  CAS  PubMed  PubMed

Central  Google Scholar  * Set, E. et al. Dissociable contribution of prefrontal and striatal dopaminergic genes to learning in economic games. _Proc. Natl Acad. Sci. USA_ 111, 9615–9620

(2014). Article  CAS  PubMed  PubMed Central  Google Scholar  * Camerer, C. & Ho, T. H. Experience-weighted attraction learning in normal form games. _Econometrica_ 67, 827–874 (1999).

Article  Google Scholar  * Cushman, F. & Morris, A. Habitual control of goal selection in humans. _Proc. Natl Acad. Sci. USA_ 112, 13817–13822 (2015). Article  CAS  PubMed  PubMed

Central  Google Scholar  * Liu, Y., Mattar, M. G., Behrens, T. E. J., Daw, N. D. & Dolan, R. J. Experience replay is associated with efficient nonlocal learning. _Science_ 372, eabf1357

(2021). Article  CAS  PubMed  PubMed Central  Google Scholar  * Kocovski, N. L., Fleming, J. E., Hawley, L. L., Ho, M. H. R. & Antony, M. M. Mindfulness and acceptance-based group

therapy and traditional cognitive behavioral group therapy for social anxiety disorder: mechanisms of change. _Behav. Res. Ther._ 70, 11–22 (2015). Article  PubMed  Google Scholar  *

Kocovski, N. L., Endler, N. S., Rector, N. A. & Flett, G. L. Ruminative coping and post-event processing in social anxiety. _Behav. Res. Ther._ 43, 971–984 (2005). Article  PubMed 

Google Scholar  * Crump, M. J. C., McDonnell, J. V. & Gureckis, T. M. Evaluating Amazon’s Mechanical Turk as a tool for experimental behavioral research. _PLoS ONE_ 8, e57410 (2013).

Article  CAS  PubMed  PubMed Central  Google Scholar  * Liebowitz, M. R. Social phobia. _Mod. Probl. Pharmacopsychiatry_ 22, 141–73 (1987). Article  CAS  PubMed  Google Scholar  * Mennin, D.

S. et al. Screening for social anxiety disorder in the clinical setting: using the Liebowitz Social Anxiety Scale. _J. Anxiety Disord._ 16, 661–673 (2002). Article  PubMed  Google Scholar 

* Bilker, W. B. et al. Development of abbreviated nine-item forms of the Raven’s standard progressive matrices test. _Assessment_ 19, 354–69 (2012). Article  PubMed  PubMed Central  Google

Scholar  * Brozovich, F. & Heimberg, R. G. An analysis of post-event processing in social anxiety disorder. _Clin. Psychol. Rev._ 28, 891–903 (2008). Article  PubMed  Google Scholar  *

Beck, A. T., Emery, G. & Greenberg, R. L. Anxiety disorders and phobias: a cognitive approach (Basic, 1985). * Clark, D. A. & Wells, A. in _Social Phobia: Diagnosis, Assessment, and

Treatment_ (eds Heimberg, R. G. et al.) (Guildford Press, 1995). * Hofmann, S. G., Carpenter, J. K. & Curtiss, J. in _Science and Practice in Cognitive Therapy: Foundations, Mechanisms,

and Applications_ (eds Leahy, R. L. et al.) 124–141 (Routledge, 2018). * Watkins, E. R. Constructive and unconstructive repetitive thought. _Psychol. Bull._ 134, 163–206 (2008). Article 

PubMed  PubMed Central  Google Scholar  * Keramati, M., Smittenaar, P., Dolan, R. J. & Dayan, P. Adaptive integration of habits into depth-limited planning defines a

habitual-goal-directed spectrum. _Proc. Natl Acad. Sci. USA_ 113, 12868–12873 (2016). Article  CAS  PubMed  PubMed Central  Google Scholar  * Icard, T., Cushman, F. & Knobe, J. On the

instrumental value of hypothetical and counterfactual thought. _Proceedings of the 40th Annual Conference of the Cognitive Science Society_ 517–522 (2018). * Caplin, A., Dean, M. &

Leahy, J. _Rationally Inattentive Behavior: Characterizing and Generalizing Shannon Entropy_ Working paper no. 23652 (NBER, 2017). * Kahneman, D. & Miller, D. T. Norm theory. Comparing

reality to its alternatives. _Psychol. Rev._ 93, 136–153 (1986). Article  Google Scholar  * McCloy, R. & Byrne, R. M. J. Counterfactual thinking about controllable events. _Mem. Cogn._

28, 1071–1078 (2000). Article  CAS  Google Scholar  * Loomes, G. & Sugden, R. Regret theory: an alternative theory of rational choice under uncertainty. _Econ. J._ 92, 805 (1982).

Article  Google Scholar  * Raven, J. The Raven’s progressive matrices: change and stability over culture and time. _Cogn. Psychol._ 41, 1–48 (2000). Article  CAS  PubMed  Google Scholar  *

Zhu, L., Jiang, Y., Scabini, D., Knight, R. T. & Hsu, M. Patients with basal ganglia damage show preserved learning in an economic game. _Nat. Commun._ 10, 802 (2019). Article  CAS 

PubMed  PubMed Central  Google Scholar  * Erev, I. & Roth, A. E. Predicting how people play games: reinforcement learning in experimental games with unique, mixed strategy equilibria.

_Am. Econ. Rev._ 88, 848–881 (1998). Google Scholar  * Cheung, Y. W. & Friedman, D. Individual learning in normal form games: some laboratory results. _Games Econ. Behav._ 19, 46–76

(1997). Article  Google Scholar  * Brown, G. W. Iterative solution of games by fictitious play. _Act. Anal. Prod. Allocation_ 13, 374–376 (1951). Google Scholar  * Sutton, R. S. Dyna, an

integrated architecture for learning, planning, and reacting. _ACM SIGART Bull._ 2, 160–163 (1991). Article  Google Scholar  * Amaldoss, W. & Jain, S. David vs. Goliath: an analysis of

asymmetric mixed-strategy games and experimental evidence. _Manag. Sci._ 48, 972–991 (2002). Article  Google Scholar  * Vikbladh, O. M. et al. Hippocampal contributions to model-based

planning and spatial memory. _Neuron_ 102, 683–693.e4 (2019). Article  CAS  PubMed  PubMed Central  Google Scholar  * Keramati, M., Dezfouli, A. & Piray, P. Speed/accuracy trade-off

between the habitual and the goal-directed processes. _PLoS Comput. Biol._ 7, e1002055 (2011). Article  CAS  PubMed  PubMed Central  Google Scholar  * Bezanson, J., Edelman, A., Karpinski,

S. & Shah, V. B. Julia: a fresh approach to numerical computing. _SIAM Rev._ 59, 65–98 (2017). Article  Google Scholar  Download references ACKNOWLEDGEMENTS The authors thank Q. Huys, M.

Paulus, M. Stein, A. Solway and S. Zorowitz for helpful conversations. This work was supported by NIMH grant R01MH121093, part of the CRNCS programme, and by a Scholar Award from the James

S. McDonnell Foundation. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. AUTHOR INFORMATION Author notes * Elana

A. Meer Present address: Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA AUTHORS AND AFFILIATIONS * Department of Psychology, Princeton University, Princeton,

NJ, USA Lindsay E. Hunter & Nathaniel D. Daw * Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA Elana A. Meer & Nathaniel D. Daw * School of Psychology,

Trinity College Dublin, Dublin, Ireland Claire M. Gillan * Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland Claire M. Gillan * Global Brain Health

Institute, Trinity College Dublin, Dublin, Ireland Claire M. Gillan * Haas School of Business, University of California, Berkeley, Berkeley, CA, USA Ming Hsu * Helen Wills Neuroscience

Institute, University of California, Berkeley, Berkeley, CA, USA Ming Hsu Authors * Lindsay E. Hunter View author publications You can also search for this author inPubMed Google Scholar *

Elana A. Meer View author publications You can also search for this author inPubMed Google Scholar * Claire M. Gillan View author publications You can also search for this author inPubMed 

Google Scholar * Ming Hsu View author publications You can also search for this author inPubMed Google Scholar * Nathaniel D. Daw View author publications You can also search for this author

inPubMed Google Scholar CONTRIBUTIONS L.E.H., E.A.M., C.M.G., M.H. and N.D.D. contributed to the conception and design of the experiment L.E.H. and E.A.M. collected the data. L.E.H., E.A.M.

and N.D.D. analysed the data. L.E.H. and N.D.D. prepared the initial draft of the manuscript, and all authors edited the manuscript and gave final approval of revisions. CORRESPONDING

AUTHORS Correspondence to Lindsay E. Hunter or Nathaniel D. Daw. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. ADDITIONAL INFORMATION PEER REVIEW

INFORMATION _Nature Human Behaviour_ thanks Camilla Nord and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. PUBLISHER’S NOTE Springer Nature

remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. SUPPLEMENTARY INFORMATION SUPPLEMENTARY INFORMATION Supplementary Tables 1–10 and Figs.

1–5. REPORTING SUMMARY RIGHTS AND PERMISSIONS Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Hunter, L.E., Meer, E.A., Gillan, C.M. _et al._ Increased and biased deliberation

in social anxiety. _Nat Hum Behav_ 6, 146–154 (2022). https://doi.org/10.1038/s41562-021-01180-y Download citation * Received: 16 January 2019 * Accepted: 08 July 2021 * Published: 16

August 2021 * Issue Date: January 2022 * DOI: https://doi.org/10.1038/s41562-021-01180-y SHARE THIS ARTICLE Anyone you share the following link with will be able to read this content: Get

shareable link Sorry, a shareable link is not currently available for this article. Copy to clipboard Provided by the Springer Nature SharedIt content-sharing initiative