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Contextual influence of reinforcement learning performance of depression: evidence for a negativity bias?

Published online by Cambridge University Press:  21 June 2022

Henri Vandendriessche*
Affiliation:
Laboratoire de Neurosciences Cognitives Computationnelles, INSERM U960, Paris, France Département d'Etudes Cognitives, Ecole Normale Supérieure, PSL Research University, Paris, France
Amel Demmou
Affiliation:
Unité Psychiatrie Adultes, Hôpital Cochin Port Royal, Paris, France
Sophie Bavard
Affiliation:
Laboratoire de Neurosciences Cognitives Computationnelles, INSERM U960, Paris, France Département d'Etudes Cognitives, Ecole Normale Supérieure, PSL Research University, Paris, France Department of Psychology, University of Hamburg, Hamburg, Germany
Julien Yadak
Affiliation:
Unité Psychiatrie Adultes, Hôpital Cochin Port Royal, Paris, France
Cédric Lemogne
Affiliation:
Université Paris Cité, INSERM U1266, Institute de Psychiatrie et Neurosciences de Paris, Paris, France Service de Psychiatrie de l'adulte, AP-HP, Hôpital Hôtel-Dieu, Paris, France
Thomas Mauras
Affiliation:
Groupe Hospitalier Universitaire, GHU paris psychiatrie neurosciences, Paris, France
Stefano Palminteri*
Affiliation:
Laboratoire de Neurosciences Cognitives Computationnelles, INSERM U960, Paris, France Département d'Etudes Cognitives, Ecole Normale Supérieure, PSL Research University, Paris, France
*
Authors for correspondence: Stefano Palminteri, E-mail: stefano.palminteri@ens.fr; Henri Vandendriessche, E-mail: henri.vandendriessche@ens.fr
Authors for correspondence: Stefano Palminteri, E-mail: stefano.palminteri@ens.fr; Henri Vandendriessche, E-mail: henri.vandendriessche@ens.fr

Abstract

Backgrounds

Value-based decision-making impairment in depression is a complex phenomenon: while some studies did find evidence of blunted reward learning and reward-related signals in the brain, others indicate no effect. Here we test whether such reward sensitivity deficits are dependent on the overall value of the decision problem.

Methods

We used a two-armed bandit task with two different contexts: one ‘rich’, one ‘poor’ where both options were associated with an overall positive, negative expected value, respectively. We tested patients (N = 30) undergoing a major depressive episode and age, gender and socio-economically matched controls (N = 26). Learning performance followed by a transfer phase, without feedback, were analyzed to distangle between a decision or a value-update process mechanism. Finally, we used computational model simulation and fitting to link behavioral patterns to learning biases.

Results

Control subjects showed similar learning performance in the ‘rich’ and the ‘poor’ contexts, while patients displayed reduced learning in the ‘poor’ context. Analysis of the transfer phase showed that the context-dependent impairment in patients generalized, suggesting that the effect of depression has to be traced to the outcome encoding. Computational model-based results showed that patients displayed a higher learning rate for negative compared to positive outcomes (the opposite was true in controls).

Conclusions

Our results illustrate that reinforcement learning performances in depression depend on the value of the context. We show that depressive patients have a specific trouble in contexts with an overall negative state value, which in our task is consistent with a negativity bias at the learning rates level.

Type
Original Article
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

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Footnotes

*

Co-first author

References

Admon, R., & Pizzagalli, D. A. (2015). Dysfunctional reward processing in depression. Current Opinion in Psychology, 4, 114118. https://doi.org/10.1016/j.copsyc.2014.12.011.CrossRefGoogle ScholarPubMed
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (DSM-5®). Washington, DC: American Psychiatric Pub.Google Scholar
Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67, 148. https://doi.org/10.18637/jss.v067.i01.CrossRefGoogle Scholar
Bavard, S., Lebreton, M., Khamassi, M., Coricelli, G., & Palminteri, S. (2018). Reference-point centering and range-adaptation enhance human reinforcement learning at the cost of irrational preferences. Nature Communications, 9(1), 4503. https://doi.org/10.1038/s41467-018-06781-2.CrossRefGoogle ScholarPubMed
Bavard, S., & Théro, H. (2018). [Re] adaptive properties of differential learning rates for positive and negative outcomes. ReScience 4(1), 5. https://doi.org/10.5281/ZENODO.1289889.CrossRefGoogle Scholar
Beck, A T. (1987). Cognitive models of depression. Journal of Cognitive Psychotherapy, 1(1), 537.Google Scholar
Beck, A. T., Steer, R. A., Ball, R., & Ranieri, W. F. (1996). Comparison of beck depression inventories-IA and-II in psychiatric outpatients. Journal of Personality Assessment, 67(3), 588597. https://doi.org/10.1207/s15327752jpa6703_13.CrossRefGoogle ScholarPubMed
Brolsma, S. C. A., Vrijsen, J. N., Vassena, E., Kandroodi, M. R., Bergman, M. A., van Eijndhoven, P. F., … Cools, R. (2022). Challenging the negative learning bias hypothesis of depression: Reversal learning in a naturalistic psychiatric sample. Psychological Medicine, 52(2), 303313. https://doi.org/10.1017/S0033291720001956.CrossRefGoogle Scholar
Brolsma, S. C. A., Vassena, E., Vrijsen, J. N., Sescousse, G., Collard, R. M., van Eijndhoven, P. F., … Cools, R. (2021). Negative learning bias in depression revisited: Enhanced neural response to surprising reward across psychiatric disorders. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 6(3), 280289. https://doi.org/10.1016/j.bpsc.2020.08.011.Google ScholarPubMed
Byrne, D. G. (1976). Choice reaction times in depressive states. British Journal of Social and Clinical Psychology, 15(2), 149156. https://doi.org/10.1111/j.2044-8260.1976.tb00020.x.CrossRefGoogle ScholarPubMed
Cazé, R. D., & van der Meer, M. A. A. (2013). Adaptive properties of differential learning rates for positive and negative outcomes. Biological Cybernetics, 107(6), 711719. https://doi.org/10.1007/s00422-013-0571-5.CrossRefGoogle ScholarPubMed
Chambon, V., Théro, H., Vidal, M., Vandendriessche, H., Haggard, P., & Palminteri, S. (2020). Information about action outcomes differentially affects learning from self-determined versus imposed choices. Nature Human Behaviour, 4(10), 10671079. https://doi.org/10.1038/s41562-020-0919-5.CrossRefGoogle ScholarPubMed
Chase, H. W., Frank, M. J., Michael, A., Bullmore, E. T., Sahakian, B. J., & Robbins, T. W. (2010). Approach and avoidance learning in patients with major depression and healthy controls: Relation to anhedonia. Psychological Medicine, 40(3), 433440. https://doi.org/10.1017/S0033291709990468.CrossRefGoogle ScholarPubMed
Chen, C., Takahashi, T., Nakagawa, S., Inoue, T., & Kusumi, I. (2015). Reinforcement learning in depression: A review of computational research. Neuroscience & Biobehavioral Reviews, 55, 247267. https://doi.org/10.1016/j.neubiorev.2015.05.005.CrossRefGoogle ScholarPubMed
Chung, D., Kadlec, K., Aimone, J. A., McCurry, K., King-Casas, B., & Chiu, P. H. (2017). Valuation in major depression is intact and stable in a non-learning environment. Scientific Reports, 7, 44374. https://doi.org/10.1038/srep44374.CrossRefGoogle Scholar
Collins, A. G. E., & Frank, M. J. (2012). How much of reinforcement learning is working memory, not reinforcement learning? A behavioral, computational, and neurogenetic analysis. European Journal of Neuroscience, 35(7), 10241035. https://doi.org/10.1111/j.1460-9568.2011.07980.x.CrossRefGoogle Scholar
Daw, N. D., Gershman, S. J., Seymour, B., Dayan, P., & Dolan, R. J. (2011). Model-based influences on humans’ choices and striatal prediction errors. Neuron, 69(6), 12041215. https://doi.org/10.1016/j.neuron.2011.02.027.CrossRefGoogle ScholarPubMed
Douglas, K. M., Porter, R. J., Frampton, C. M., Gallagher, P., & Young, A. H. (2009). Abnormal response to failure in unmedicated major depression. Journal of Affective Disorders, 119(1), 9299. https://doi.org/10.1016/j.jad.2009.02.018.CrossRefGoogle ScholarPubMed
Elliott, R., Sahakian, B. J., Herrod, J. J., Robbins, T. W., & Paykel, E. S. (1997). Abnormal response to negative feedback in unipolar depression: Evidence for a diagnosis specific impairment. Journal of Neurology, Neurosurgery & Psychiatry, 63(1), 7482. https://doi.org/10.1136/jnnp.63.1.74.CrossRefGoogle ScholarPubMed
Elliott, R., Sahakian, B. J., McKay, A. P., Herrod, J. J., Robbins, T. W., & Paykel, E. S. (1996). Neuropsychological impairments in unipolar depression: The influence of perceived failure on subsequent performance. Psychological Medicine, 26(5), 975989. https://doi.org/10.1017/S0033291700035303.CrossRefGoogle ScholarPubMed
Eshel, N., & Roiser, J. P. (2010). Reward and punishment processing in depression. Biological Psychiatry, 68(2), 118124. https://doi.org/10.1016/j.biopsych.2010.01.027.CrossRefGoogle ScholarPubMed
Fontanesi, L., Gluth, S., Spektor, M. S., & Rieskamp, J. (2019a). A reinforcement learning diffusion decision model for value-based decisions. Psychonomic Bulletin & Review, 26(4), 10991121. https://doi.org/10.3758/s13423-018-1554-2.CrossRefGoogle ScholarPubMed
Fontanesi, L., Palminteri, S., & Lebreton, M. (2019b). Decomposing the effects of context valence and feedback information on speed and accuracy during reinforcement learning: A meta-analytical approach using diffusion decision modeling. Cognitive, Affective, & Behavioral Neuroscience, 19(3), 490502. https://doi.org/10.3758/s13415-019-00723-1.CrossRefGoogle ScholarPubMed
Forbes, E. E., & Dahl, R. E. (2012). Research review: Altered reward function in adolescent depression: What, when and how? Journal of Child Psychology and Psychiatry, 53(1), 315. https://doi.org/10.1111/j.1469-7610.2011.02477.x.CrossRefGoogle ScholarPubMed
Frank, M. J., Moustafa, A. A., Haughey, H. M., Curran, T., & Hutchison, K. E. (2007). Genetic triple dissociation reveals multiple roles for dopamine in reinforcement learning. Proceedings of the National Academy of Sciences, 104(41), 1631116316. https://doi.org/10.1073/pnas.0706111104.CrossRefGoogle ScholarPubMed
Frank, M. J., Seeberger, L. C., & O'Reilly, R. C. (2004). By carrot or by stick: Cognitive reinforcement learning in parkinsonism. Science (New York, N.Y.), 306(5703), 19401943. https://doi.org/10.1126/science.1102941.CrossRefGoogle ScholarPubMed
Gotlib, I. H., & Joormann, J. (2010). Cognition and depression: Current status and future directions. Annual Review of Clinical Psychology, 6(1), 285312. https://doi.org/10.1146/annurev.clinpsy.121208.131305.CrossRefGoogle ScholarPubMed
Gradin, V. B., Kumar, P., Waiter, G., Ahearn, T., Stickle, C., Milders, M., … Steele, J. D. (2011). Expected value and prediction error abnormalities in depression and schizophrenia. Brain: A Journal of Neurology, 134(Pt 6), 17511764. https://doi.org/10.1093/brain/awr059.CrossRefGoogle ScholarPubMed
Guitart-Masip, M., Huys, Q. J. M., Fuentemilla, L., Dayan, P., Duzel, E., & Dolan, R. J. (2012). Go and no-go learning in reward and punishment: Interactions between affect and effect. NeuroImage, 62(1), 154166. https://doi.org/10.1016/j.neuroimage.2012.04.024.CrossRefGoogle ScholarPubMed
Hägele, C., Schlagenhauf, F., Rapp, M., Sterzer, P., Beck, A., Bermpohl, F., … Heinz, A. (2015). Dimensional psychiatry: Reward dysfunction and depressive mood across psychiatric disorders. Psychopharmacology, 232(2), 331341. https://doi.org/10.1007/s00213-014-3662-7.CrossRefGoogle ScholarPubMed
Henriques, J. B., Glowacki, J. M., & Davidson, R. J. (1994). Reward fails to alter response bias in depression. Journal of Abnormal Psychology, 103(3), 460. https://psycnet.apa.org/buy/1994-45308-001.CrossRefGoogle Scholar
Henriques, J. B., & Davidson, R. J. (2000). Decreased responsiveness to reward in depression. Cognition and Emotion, 14(5), 711724. https://doi.org/10.1080/02699930050117684.CrossRefGoogle Scholar
Huys, Q. J., Pizzagalli, D. A., Bogdan, R., & Dayan, P. (2013). Mapping anhedonia onto reinforcement learning: A behavioural meta-analysis. Biology of Mood & Anxiety Disorders, 3(1), 12. https://doi.org/10.1186/2045-5380-3-12.CrossRefGoogle ScholarPubMed
Huys, Q. J. M., Gölzer, M., Friedel, E., Heinz, A., Cools, R., Dayan, P., & Dolan, R. J. (2016). The specificity of Pavlovian regulation is associated with recovery from depression. Psychological Medicine, 46(5), 10271035. https://doi.org/10.1017/S0033291715002597.CrossRefGoogle ScholarPubMed
Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Pine, D. S., Quinn, K., … Wang, P. (2010). Research domain criteria (RDoC): Toward a new classification framework for research on mental disorders. American Journal of Psychiatry, 167(7), 748751. https://doi.org/10.1176/appi.ajp.2010.09091379.CrossRefGoogle Scholar
Joormann, J., & Quinn, M. E. (2014). Cognitive processes and emotion regulation in depression. Depression and Anxiety, 31(4), 308315. https://doi.org/10.1002/da.22264.CrossRefGoogle ScholarPubMed
Katahira, K., Yuki, S., & Okanoya, K. (2017). Model-based estimation of subjective values using choice tasks with probabilistic feedback. Journal of Mathematical Psychology, 79, 2943. https://doi.org/10.1016/j.jmp.2017.05.005.CrossRefGoogle Scholar
Klein, T. A., Ullsperger, M., & Jocham, G. (2017). Learning relative values in the striatum induces violations of normative decision making. Nature Communications, 8(1), 16033. https://doi.org/10.1038/ncomms16033.CrossRefGoogle Scholar
Knutson, B., Bhanji, J. P., Cooney, R. E., Atlas, L. Y., & Gotlib, I. H. (2008). Neural responses to monetary incentives in major depression. Biological Psychiatry, 63(7), 686692. https://doi.org/10.1016/j.biopsych.2007.07.023.CrossRefGoogle ScholarPubMed
Kumar, P., Waiter, G., Ahearn, T., Milders, M., Reid, I., & Steele, J. D. (2008). Abnormal temporal difference reward-learning signals in major depression. Brain, 131(8), 20842093. https://doi.org/10.1093/brain/awn136.CrossRefGoogle ScholarPubMed
Moutoussis, M., Rutledge, R. B., Prabhu, G., Hrynkiewicz, L., Lam, J., Ousdal, O.-T., … Dolan, R. J. (2018). Neural activity and fundamental learning, motivated by monetary loss and reward, are intact in mild to moderate major depressive disorder. PLoS One, 13(8), e0201451. https://doi.org/10.1371/journal.pone.0201451.CrossRefGoogle ScholarPubMed
Murphy, F. C., Michael, A., Robbins, T. W., & Sahakian, B. J. (2003). Neuropsychological impairment in patients with major depressive disorder: The effects of feedback on task performance. Psychological Medicine, 33(3), 455467. https://doi.org/10.1017/S0033291702007018.CrossRefGoogle Scholar
Niv, Y., Edlund, J. A., Dayan, P., & O'Doherty, J. P. (2012). Neural prediction errors reveal a risk-sensitive reinforcement-learning process in the human brain. Journal of Neuroscience, 32(2), 551562. https://doi.org/10.1523/JNEUROSCI.5498-10.2012.CrossRefGoogle ScholarPubMed
Palminteri, S., Clair, A.-H., Mallet, L., & Pessiglione, M. (2012). Similar improvement of reward and punishment learning by serotonin reuptake inhibitors in obsessive-compulsive disorder. Biological Psychiatry, 72(3), 244250. https://doi.org/10.1016/j.biopsych.2011.12.028.CrossRefGoogle ScholarPubMed
Palminteri, S., Khamassi, M., Joffily, M., & Coricelli, G. (2015). Contextual modulation of value signals in reward and punishment learning. Nature Communications, 6(1), 8096. https://doi.org/10.1038/ncomms9096.CrossRefGoogle ScholarPubMed
Palminteri, S., & Lebreton, M. (2021). Context-dependent outcome encoding in human reinforcement learning. Current Opinion in Behavioral Sciences, 41, 144151. https://doi.org/10.1016/j.cobeha.2021.06.006.CrossRefGoogle Scholar
Palminteri, S., Lefebvre, G., Kilford, E. J., & Blakemore, S.-J. (2017). Confirmation bias in human reinforcement learning: Evidence from counterfactual feedback processing. PLOS Computational Biology, 13(8), e1005684. https://doi.org/10.1371/journal.pcbi.1005684.CrossRefGoogle ScholarPubMed
Palminteri, S., & Pessiglione, M. (2017). Chapter 23 – opponent brain systems for reward and punishment learning: Causal evidence from drug and lesion studies in humans. In Dreher, J.-C. & Tremblay, L. (Eds.), Decision neuroscience (pp. 291303). San Diego: Academic Press. Retrieved from https://doi.org/10.1016/B978-0-12-805308-9.00023-3.CrossRefGoogle Scholar
Pessiglione, M., Seymour, B., Flandin, G., Dolan, R., & Frith, C. (2006). Dopamine-dependent prediction errors underpin reward-seeking behaviour in humans. Nature, 442(7106), 1042–1045. https://doi.org/10.1038/nature05051.CrossRefGoogle ScholarPubMed
Pike, A. C., & Robinson, O. J. (2022). Reinforcement learning in patients with mood and anxiety disorders vs control individuals: A systematic review and meta-analysis. JAMA Psychiatry, 79(4), 313–322. https://doi.org/10.1001/jamapsychiatry.2022.0051.CrossRefGoogle ScholarPubMed
Pizzagalli, D. A. (2014). Depression, stress, and anhedonia: Toward a synthesis and integrated model. Annual Review of Clinical Psychology, 10, 393–423. https://doi.org/10.1146/annurev-clinpsy-050212-185606.CrossRefGoogle Scholar
Pizzagalli, D. A., Jahn, A. L., & O'Shea, J. P. (2005). Toward an objective characterization of an anhedonic phenotype: A signal-detection approach. Biological Psychiatry, 57(4), 319327. https://doi.org/10.1016/j.biopsych.2004.11.026.CrossRefGoogle ScholarPubMed
R Core Team. (2022). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.Google Scholar
Recorla, R. A., & Wagner, A. R. (1972). A theory of pavlovian conditioning: Variations in the effectiveness of reinforcement and nonreinforcement. In A. H. Black & W. F. Prokasy (Eds.), Classical conditioning II: Current research and theory (pp. 64–99). New York: Appleton- Century-Crofts.Google Scholar
Rothkirch, M., Tonn, J., Köhler, S., & Sterzer, P. (2017). Neural mechanisms of reinforcement learning in unmedicated patients with major depressive disorder. Brain, 140(4), 11471157. https://doi.org/10.1093/brain/awx025.CrossRefGoogle ScholarPubMed
Rupprechter, S., Stankevicius, A., Huys, Q. J. M., Steele, J. D., & Seriès, P. (2018). Major depression impairs the use of reward values for decision-making. Scientific Reports, 8(1), 13798. https://doi.org/10.1038/s41598-018-31730-w.CrossRefGoogle ScholarPubMed
Rutledge, R. B., Moutoussis, M., Smittenaar, P., Zeidman, P., Taylor, T., Hrynkiewicz, L., … Dolan, R. J. (2017). Association of neural and emotional impacts of reward prediction errors with major depression. JAMA Psychiatry, 74(8), 790797. https://doi.org/10.1001/jamapsychiatry.2017.1713.CrossRefGoogle ScholarPubMed
Safra, L., Chevallier, C., & Palminteri, S. (2019). Depressive symptoms are associated with blunted reward learning in social contexts. PLOS Computational Biology, 15(7), e1007224. https://doi.org/10.1371/journal.pcbi.1007224.CrossRefGoogle ScholarPubMed
Shah, P. J., O'carroll, R. E., Rogers, A., Moffoot, A. P. R., & Ebmeier, K. P. (1999). Abnormal response to negative feedback in depression. Psychological Medicine, 29(1), 6372. https://doi.org/10.1017/S0033291798007880.CrossRefGoogle ScholarPubMed
Sheehan, D. V., Lecrubier, Y., Sheehan, K. H., Amorim, P., Janavs, J., Weiller, E., … Dunbar, G. C. (1998). The mini-international neuropsychiatric interview (M.I.N.I.): The development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. The Journal of Clinical Psychiatry, 59(Suppl. 20), 2233; quiz 34–57.Google Scholar
Steele, J. D., Kumar, P., & Ebmeier, K. P. (2007). Blunted response to feedback information in depressive illness. Brain, 130(9), 23672374. https://doi.org/10.1093/brain/awm150.CrossRefGoogle ScholarPubMed
Sutton, R. S., & Barto, A. G. (2018). Reinforcement learning: An introduction (2nd ed.). Cambridge, MA: The MIT Press.Google Scholar
Ubl, B., Kuehner, C., Kirsch, P., Ruttorf, M., Diener, C., & Flor, H. (2015). Altered neural reward and loss processing and prediction error signalling in depression. Social Cognitive and Affective Neuroscience, 10(8), 11021112. https://doi.org/10.1093/scan/nsu158.CrossRefGoogle ScholarPubMed
Vrieze, E., Pizzagalli, D. A., Demyttenaere, K., Hompes, T., Sienaert, P., de Boer, P., … Claes, S. (2013). Reduced reward learning predicts outcome in major depressive disorder. Biological Psychiatry, 73(7), 639645. https://doi.org/10.1016/j.biopsych.2012.10.014.CrossRefGoogle ScholarPubMed
Whitton, A. E., Kakani, P., Foti, D., Van't Veer, A., Haile, A., Crowley, D. J., & Pizzagalli, D. A. (2016). Blunted neural responses to reward in remitted major depression: A high-density event-related potential study. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 1(1), 8795. https://doi.org/10.1016/j.bpsc.2015.09.007.Google ScholarPubMed
Whitton, A. E., Treadway, M. T., & Pizzagalli, D. A. (2015). Reward processing dysfunction in major depression, bipolar disorder and schizophrenia. Current Opinion in Psychiatry, 28(1), 712. https://doi.org/10.1097/YCO.0000000000000122.CrossRefGoogle ScholarPubMed
Wilson, R. C., & Collins, A. G. (2019). Ten simple rules for the computational modeling of behavioral data. ELife, 8, e49547. https://doi.org/10.7554/eLife.49547.CrossRefGoogle ScholarPubMed
World Health Organization, . (2017). Depression and other common mental disorders: Global health estimates (No. WHO/MSD/MER/2017.2). Retrieved from World Health Organization website: https://apps.who.int/iris/handle/10665/254610.Google Scholar
Yechiam, E., & Hochman, G. (2014). Loss attention in a dual-task setting. Psychological Science, 25(2), 494502. https://doi.org/10.1177/0956797613510725.CrossRefGoogle Scholar
Yu, Z., Guindani, M., Grieco, S. F., Chen, L., Holmes, T. C., & Xu, X. (2022). Beyond t test and ANOVA: Applications of mixed-effects models for more rigorous statistical analysis in neuroscience research. Neuron, 110(1), 2135. https://doi.org/10.1016/j.neuron.2021.10.030.CrossRefGoogle Scholar
Zhang, W.-N., Chang, S.-H., Guo, L.-Y., Zhang, K.-L., & Wang, J. (2013). The neural correlates of reward-related processing in major depressive disorder: A meta-analysis of functional magnetic resonance imaging studies. Journal of Affective Disorders, 151(2), 531539. https://doi.org/10.1016/j.jad.2013.06.039.CrossRefGoogle ScholarPubMed