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Serotonin Selectively Modulates Reward Value in Human Decision-Making
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Establishing a function for the neuromodulator serotonin in human decision-making has proved remarkably difficult because if its complex role in reward and punishment processing. In a novel choice task where actions led concurrently and independently to the stochastic delivery of both money and pain, we studied the impact of decreased brain serotonin induced by acute dietary tryptophan depletion. Depletion selectively impaired both behavioral and neural representations of reward outcome value, and hence the effective exchange rate by which rewards and punishments were compared. This effect was computationally and anatomically distinct from a separate effect on increasing outcome-independent choice perseveration. Our results provide evidence for a surprising role for serotonin in reward processing, while illustrating its complex and multifarious effects.
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“ATD has been shown to affect measures of both ‘cold’ (rational and non-emotional), and ‘hot’ (social and emotional) cognition [13–18].”
From Chronic escitalopram in healthy volunteers has specific effects on reinforcement sensitivity: a double-blind, placebo-controlled semi-randomised study (2023) · cites this paper as [13]
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“Effects of ATD have also been seen on reinforcement behaviour [13], reversal learning [9, 14], learning and memory [15], affective and social cognition [9, 16, 17] and moral judgement [18].”
From Chronic escitalopram in healthy volunteers has specific effects on reinforcement sensitivity: a double-blind, placebo-controlled semi-randomised study (2023) · cites this paper as [13]
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“A previous study examining how reinforcement is influenced by serotonergic modulation showed that acute tryptophan depletion decreased reinforcement sensitivity, by impairing the representation of reward outcome value [13].”
From Chronic escitalopram in healthy volunteers has specific effects on reinforcement sensitivity: a double-blind, placebo-controlled semi-randomised study (2023) · cites this paper as [13]
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“However, three decision-making studies (Seymour et al., 2012; Roy et al., 2014; Eldar et al., 2016) that involved avoiding pain or shock examined prediction errors to successful and unsuccessful avoidance, and two found evidence for striatal prediction errors to successful avoidance of shock.”
From Active avoidance: Neural mechanisms and attenuation of pavlovian conditioned responding (2017) · cites this paper as Seymour et al., 2012
In the citing paper
“The vmPFC, rather than regions included in the NPS, correlates with spontaneous, clinical pain [52], and encodes the learned, behavioral avoidance value associated with painful stimulation [85],[86].”
From Distinct Brain Systems Mediate the Effects of Nociceptive Input and Self-Regulation on Pain (2015) · cites this paper as [85]
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“By contrast, vmPFC activity seems to reflect expected positive value in a variety of contexts and paradigms45, including reward learning, economic choice46, pain avoidance11, and extinction/extinction recall47.”
From Representation of aversive prediction errors in the human periaqueductal gray (2014) · cites this paper as [11]
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Citations
Cites
A neural substrate of prediction and reward
Schultz, W., Dayan, P., & Montague, P. R. (1997) · Science · doi:10.1126/science.275.5306.1593 · Cited by 9,388
Self-citationCortical substrates for exploratory decisions in humans
Daw, N. D., O'Doherty, J. P., Dayan, P., Seymour, B., & Dolan, R. J. (2006) · Nature · doi:10.1038/nature04766 · Cited by 2,224
Self-citationDissociable Roles of Ventral and Dorsal Striatum in Instrumental Conditioning
O'Doherty, J., Dayan, P., Schultz, J., Deichmann, R., Friston, K., & Dolan, R. J. (2004) · Science · doi:10.1126/science.1094285 · Cited by 2,088
Self-citationThe use of analogue scales in rating subjective feelings
BOND, A., & LADER, M. (1974) · British Journal of Medical Psychology · doi:10.1111/j.2044-8341.1974.tb02285.x · Cited by 1,972
Mowrer, O. H. (1960) · doi:10.1037/10802-000 · Cited by 1,670
Dopamine-dependent prediction errors underpin reward-seeking behaviour in humans
Pessiglione, M., Seymour, B., Flandin, G., Dolan, R. J., & Frith, C. D. (2006) · Nature · doi:10.1038/nature05051 · Cited by 1,584
Self-citationGonzalez, R. C., & Mowrer, O. H. (1962) · The American Journal of Psychology · doi:10.2307/1419634 · Cited by 1,584
Conditioning and Associative Learning
Hill, W. F., & Mackintosh, N. J. (1984) · The American Journal of Psychology · doi:10.2307/1422540 · Cited by 1,304
Midbrain dopamine neurons encode a quantitative reward prediction error signal
Bayer, H. M., & Glimcher, P. W. (2005) · Neuron · doi:10.1016/j.neuron.2005.05.020 · Cited by 1,304
Brain Serotonin Content: Physiological Regulation by Plasma Neutral Amino Acids
Fernstrom, J. D., & Wurtman, R. J. (1972) · Science · doi:10.1126/science.178.4059.414 · Cited by 1,166
Research works printed but not linked: 1
- Dickinson A Dearing MF (1979) in Mechanisms of learning and motivation: a memorial volume to Jerzy Konorski, Appetitive-aversive interactions and inhibitory processes, eds Dickinson A Boakes RA (Psychology Press, London), pp 203–231.
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Sorted by citations
Neuronal Reward and Decision Signals: From Theories to Data
Schultz, W. (2015) · Physiological Reviews · doi:10.1152/physrev.00023.2014 · Cited by 1,126
Serotonin and brain function: a tale of two receptors
Carhart-Harris, R., & Nutt, D. (2017) · Journal of Psychopharmacology · doi:10.1177/0269881117725915 · Cited by 739
Neuroscience of apathy and anhedonia: a transdiagnostic approach
Husain, M., & Roiser, J. P. (2018) · Nature reviews. Neuroscience · doi:10.1038/s41583-018-0029-9 · Cited by 682
Self-citationNeurophysiology of performance monitoring and adaptive behavior
Ullsperger, M., Danielmeier, C., & Jocham, G. (2014) · Physiological Reviews · doi:10.1152/physrev.00041.2012 · Cited by 634
Circuits and functions of the lateral habenula in health and in disease
Hu, H., Cui, Y., & Yang, Y. (2020) · Nature reviews. Neuroscience · doi:10.1038/s41583-020-0292-4 · Cited by 488
Dorsal raphe neurons signal reward through 5-HT and glutamate
Liu, Z., Zhou, J., Li, Y., Hu, F., Lu, Y., Ma, M., Feng, Q., Zhang, J.-E., Wang, D., Zeng, J., et al. (2014) · Neuron · doi:10.1016/j.neuron.2014.02.010 · Cited by 469
Reward processing by the lateral habenula in normal and depressive behaviors
Proulx, C. D., Hikosaka, O., & Malinow, R. (2014) · Nature Neuroscience · doi:10.1038/nn.3779 · Cited by 461
Reinforcement learning and episodic memory in humans and animals: an integrative framework
Gershman, S. J., & Daw, N. D. (2017) · Annual Review of Psychology · doi:10.1146/annurev-psych-122414-033625 · Cited by 446
Self-citationReduced Reward Learning Predicts Outcome in Major Depressive Disorder
Vrieze, E., Pizzagalli, D. A., Demyttenaere, K., Hompes, T., Sienaert, P. A., de Boer, P., Schmidt, M. E., & Claes, S. J. (2012) · Biological Psychiatry · doi:10.1016/j.biopsych.2012.10.014 · Cited by 463
LeDoux, J. E., & Daw, N. D. (2018) · Nature reviews. Neuroscience · doi:10.1038/nrn.2018.22 · Cited by 402
Self-citationReinforcement Learning in Multidimensional Environments Relies on Attention Mechanisms
Niv, Y., Daniel, R., Geana, A., Gershman, S. J., Leong, Y. C., Radulescu, A., & Wilson, R. C. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.2978-14.2015 · Cited by 362
Martinez, D. L., Brusoni, S., Canessa, N., & Zollo, M. (2013) · Strategic Management Journal · doi:10.1002/smj.2221 · Cited by 372
Beyond happiness: Building a science of discrete positive emotions.
Shiota, M. N., Campos, B., Oveis, C., Hertenstein, M. J., Simon-Thomas, E. R., & Keltner, D. J. (2017) · American Psychologist · doi:10.1037/a0040456 · Cited by 304
Hu, H. (2016) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-070815-014106 · Cited by 253
Distinct Brain Systems Mediate the Effects of Nociceptive Input and Self-Regulation on Pain
Woo, C.-W., Roy, M., Buhle, J. T., & Wager, T. D. (2015) · PLoS Biology · doi:10.1371/journal.pbio.1002036 · Cited by 263
Organization of monosynaptic inputs to the serotonin and dopamine neuromodulatory systems
Ogawa, S. K., Cohen, J. Y., Hwang, D., Uchida, N., & Watabe-Uchida, M. (2014) · Cell Reports · doi:10.1016/j.celrep.2014.06.042 · Cited by 249
Representation of aversive prediction errors in the human periaqueductal gray
Roy, M., Shohamy, D., Daw, N., Jepma, M., Wimmer, G. E., & Wager, T. D. (2014) · Nature Neuroscience · doi:10.1038/nn.3832 · Cited by 246
Self-citationNeuromodulatory Systems and Their Interactions: A Review of Models, Theories, and Experiments
Avery, M. C., & Krichmar, J. L. (2017) · Frontiers in Neural Circuits · doi:10.3389/fncir.2017.00108 · Cited by 250
Hauser, T. U., Iannaccone, R., Walitza, S., Brandeis, D., & Brem, S. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.09.018 · Cited by 203
How Dopamine Enhances an Optimism Bias in Humans
Sharot, T., Guitart‐Masip, M., Korn, C. W., Chowdhury, R., & Dolan, R. J. (2012) · Current Biology · doi:10.1016/j.cub.2012.05.053 · Cited by 227
Self-citationInterplay of approximate planning strategies
Huys, Q. J. M., Lally, N., Faulkner, P., Eshel, N., Seifritz, E., Gershman, S. J., Dayan, P., & Roiser, J. P. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1414219112 · Cited by 207
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Fonseca, M. S., Murakami, M., & Mainen, Z. F. (2015) · Current Biology · doi:10.1016/j.cub.2014.12.002 · Cited by 219
Pain, decisions, and actions: a motivational perspective
Wiech, K., & Tracey, I. (2013) · Frontiers in Neuroscience · doi:10.3389/fnins.2013.00046 · Cited by 188
An Update on the Role of Serotonin and its Interplay with Dopamine for Reward
Fischer, A. G., & Ullsperger, M. (2017) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2017.00484 · Cited by 189
Altered learning under uncertainty in unmedicated mood and anxiety disorders
Aylward, J., Valton, V., Ahn, W., Bond, R. L., Dayan, P., Roiser, J. P., & Robinson, O. J. (2019) · Nature Human Behaviour · doi:10.1038/s41562-019-0628-0 · Cited by 164
Self-citationModulating the Neuromodulators: Dopamine, Serotonin, and the Endocannabinoid System
Peters, K. Z., Cheer, J. F., & Tonini, R. (2021) · Trends in Neurosciences · doi:10.1016/j.tins.2021.02.001 · Cited by 180
Pain: A Precision Signal for Reinforcement Learning and Control
Seymour, B. (2019) · Neuron · doi:10.1016/j.neuron.2019.01.055 · Cited by 175
Self-citationSerotonin neurons modulate learning rate through uncertainty
Grossman, C. D., Bari, B. A., & Cohen, J. Y. (2022) · Current Biology · doi:10.1016/j.cub.2021.12.006 · Cited by 164
Wang, S., Leri, F., & Rizvi, S. J. (2021) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2021.110289 · Cited by 171
Chen, C., & Nakagawa, S. (2023) · Ageing Research Reviews · doi:10.1016/j.arr.2023.101868 · Cited by 172
Baliki, M. N., Mansour, A. R., Baria, A. T., Huang, L., Berger, S., Fields, H. L., & Apkarian, A. V. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.1731-13.2013 · Cited by 161
Separate mesocortical and mesolimbic pathways encode effort and reward learning signals
Hauser, T. U., Eldar, E., & Dolan, R. J. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1705643114 · Cited by 142
Self-citationActive avoidance: Neural mechanisms and attenuation of pavlovian conditioned responding
Boeke, E. A., Moscarello, J. M., LeDoux, J. E., Phelps, E. A., & Hartley, C. A. (2017) · The Journal of Neuroscience · doi:10.1523/jneurosci.3261-16.2017 · Cited by 131
“However, three decision-making studies (Seymour et al., 2012; Roy et al., 2014; Eldar et al., 2016) that involved avoiding pain or shock examined prediction errors to successful and unsuccessful avoidance, and two found evidence for striatal prediction errors to successful avoidance of shock.”
BackgroundSerotonin Modulates Striatal Responses to Fairness and Retaliation in Humans
Crockett, M. J., Apergis-Schoute, A., Herrmann, B., Lieberman, M. D., Müller, U., Robbins, T. W., & Clark, L. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.2761-12.2013 · Cited by 134
Worbe, Y., Savulich, G., Voon, V., Fernandez-Egea, E., & Robbins, T. W. (2014) · Neuropsychopharmacology · doi:10.1038/npp.2013.351 · Cited by 125
Iigaya, K., Fonseca, M. S., Murakami, M., Mainen, Z. F., & Dayan, P. (2018) · Nature Communications · doi:10.1038/s41467-018-04840-2 · Cited by 120
Self-citationReward processing by the dorsal raphe nucleus: 5-HT and beyondPreprint
Luo, M., Zhou, J., & Liu, Z. (2015) · Learning & Memory · doi:10.1101/lm.037317.114 · Cited by 131
Pelloux, Y., Dilleen, R., Economidou, D., Theobald, D. E. H., & Everitt, B. J. (2012) · Neuropsychopharmacology · doi:10.1038/npp.2012.111 · Cited by 115
Kanen, J. W., Ersche, K. D., Fineberg, N. A., Robbins, T. W., & Cardinal, R. N. (2019) · Psychopharmacology · doi:10.1007/s00213-019-05325-w · Cited by 101
Guitart‐Masip, M., Economides, M., Huys, Q. J. M., Frank, M. J., Chowdhury, R., Düzel, E., Dayan, P., & Dolan, R. J. (2013) · Psychopharmacology · doi:10.1007/s00213-013-3313-4 · Cited by 113
Self-citationReinforcement learning and human behavior
Shteingart, H., & Loewenstein, Y. (2014) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2013.12.004 · Cited by 107
Serotonin regulation of behavior via large-scale neuromodulation of serotonin receptor networks
Salvan, P., Fonseca, M., Winkler, A. M., Beauchamp, A., Lerch, J. P., & Johansen-Berg, H. (2023) · Nature Neuroscience · doi:10.1038/s41593-022-01213-3 · Cited by 101
How serotonin shapes moral judgment and behavior
Siegel, J. Z., & Crockett, M. J. (2013) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.12229 · Cited by 103
Origin of perseveration in the trade-off between reward and complexity
Gershman, S. J. (2020) · Cognition · doi:10.1016/j.cognition.2020.104394 · Cited by 97
Rygula, R., Clarke, H. F., Cardinal, R. N., Cockcroft, G. J., Xia, J., Dalley, J. W., Robbins, T. W., & Roberts, A. C. (2015) · Cerebral Cortex · doi:10.1093/cercor/bhu102 · Cited by 85
Hauser, T. U., Iannaccone, R., Dolan, R. J., Ball, J., Hättenschwiler, J., Drechsler, R., Rufer, M., Brandeis, D., Walitza, S., & Brem, S. (2017) · Psychological Medicine · doi:10.1017/s0033291716003305 · Cited by 86
Self-citationThe statistical structures of reinforcement learning with asymmetric value updates
Katahira, K. (2018) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2018.09.002 · Cited by 87
Value Learning through Reinforcement
Daw, N. D., & Tobler, P. N. (2013) · Elsevier eBooks · doi:10.1016/b978-0-12-416008-8.00015-2 · Cited by 109
Self-citationKatahira, K. (2015) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2015.03.006 · Cited by 84
Ottenhof, K., Sild, M., Lévesque, M. L., Ruhé, H. G., & Booij, L. (2018) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2018.05.018 · Cited by 87
Dissecting the functional organization of the C. elegans serotonergic system at whole-brain scale
Dag, U., Nwabudike, I., Kang, D., Gomes, M. A., Kim, J. S., Atanas, A. A., Bueno, E., Estrem, C., Pugliese, S. M., Wang, Z., et al. (2023) · Cell · doi:10.1016/j.cell.2023.04.023 · Cited by 96
Striatal structure and function predict individual biases in learning to avoid pain
Eldar, E., Hauser, T. U., Dayan, P., & Dolan, R. J. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1519829113 · Cited by 79
Self-citationFaulkner, P., & Deakin, J. F. W. (2014) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2014.07.024 · Cited by 75
Serotonin and Aversive Pavlovian Control of Instrumental Behavior in Humans
Geurts, D. E. M., Huys, Q. J. M., den Ouden, H. E. M., & Cools, R. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.2749-13.2013 · Cited by 83
Valence-dependent influence of serotonin depletion on model-based choice strategy
Worbe, Y., Palminteri, S., Savulich, G., Daw, N. D., Fernandez-Egea, E., Robbins, T. W., & Voon, V (2016) · Molecular Psychiatry · doi:10.1038/mp.2015.46 · Cited by 75
Self-citationGenetic factors in exercise adoption, adherence and obesity
Herring, M. P., Sailors, M. H., & Bray, M. S. (2013) · Obesity Reviews · doi:10.1111/obr.12089 · Cited by 71
Prakash, N., Stark, C. J., Keisler, M. N., Luo, L., Der‐Avakian, A., & Dulcis, D. (2019) · Journal of Neuroscience · doi:10.1523/jneurosci.1802-19.2019 · Cited by 72
Tryptophan Depletion Promotes Habitual over Goal-Directed Control of Appetitive Responding in Humans
Worbe, Y., Savulich, G., de Wit, S., Fernandez-Egea, E., & Robbins, T. W. (2015) · International Journal of Neuropsychopharmacology · doi:10.1093/ijnp/pyv013 · Cited by 64
Roberts, C., Sahakian, B. J., & Robbins, T. W. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.09.001 · Cited by 63
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Palminteri, S., & Pessiglione, M. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-805308-9.00023-3 · Cited by 71
Modular deep reinforcement learning from reward and punishment for robot navigation
Wang, J., Elfwing, S., & Uchibe, E. (2020) · Neural Networks · doi:10.1016/j.neunet.2020.12.001 · Cited by 62
Langley, C., Armand, S., Luo, Q., Savulich, G., Segerberg, T., Søndergaard, A., Pedersen, E. B., Svart, N., Overgaard-Hansen, O., Johansen, A., et al. (2023) · Neuropsychopharmacology · doi:10.1038/s41386-022-01523-x · Cited by 58
Hierarchical models of pain: Inference, information-seeking, and adaptive control.
Seymour, B., & Mancini, F. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117212 · Cited by 57
Self-citationMolle, R. D., Fatemi, H., Dagher, A., Levitan, R. D., Silveira, P. P., & Dubé, L. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.12.028 · Cited by 66
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Soder, H. E., Cooper, J. A., Lopez-Gamundi, P., Hoots, J. K., Nunez, C., Lawlor, V. M., Lane, S. D., Treadway, M. T., & Wardle, M. C. (2021) · Neuropsychopharmacology · doi:10.1038/s41386-020-0779-8 · Cited by 61
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Chekroud, A. M. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.00153 · Cited by 55
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Ranade, S., Pi, H.-J., & Kepecs, Á. (2014) · Current Biology · doi:10.1016/j.cub.2014.07.024 · Cited by 59
Relative Valuation of Pain in Human Orbitofrontal Cortex
Winston, J. S., Vlaev, I., Seymour, B., Chater, N., & Dolan, R. J. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.1706-14.2014 · Cited by 61
Self-citationThe origins of ‘5-HT and mechanisms of defence’ by Deakin and Graeff: A personal perspective
Deakin, J. F. W. (2013) · Journal of Psychopharmacology · doi:10.1177/0269881113503508 · Cited by 59
Scholl, J., Kolling, N., Nelissen, N., Browning, M., Rushworth, M. F. S., & Harmer, C. J. (2017) · PLOS Biology · doi:10.1371/journal.pbio.2000756 · Cited by 58
Bayesian Learning Models of Pain: A Call to Action
Tabor, A., & Burr, C. (2019) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2018.10.006 · Cited by 57
Clarke, H. F., Cardinal, R. N., Rygula, R., Hong, Y. T., Fryer, T. D., Sawiak, S. J., Ferrari, V., Cockcroft, G., Aigbirhio, F. I., Robbins, T. W., et al. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.0718-14.2014 · Cited by 54
Serotonergic modulation of reward and punishment: evidence from pharmacological fMRI studies
Macoveanu, J. (2014) · Brain Research · doi:10.1016/j.brainres.2014.02.003 · Cited by 55
Value generalization in human avoidance learning
Norbury, A., Robbins, T. W., & Seymour, B. (2018) · eLife · doi:10.7554/elife.34779 · Cited by 57
Self-citationMyers, C. E., Moustafa, A. A., Sheynin, J., VanMeenen, K. M., Gilbertson, M. W., Orr, S. P., Beck, K. D., Pang, K. C. H., & Servatius, R. J. (2013) · PLoS ONE · doi:10.1371/journal.pone.0072508 · Cited by 56
Aversive Motivation and Cognitive ControlPreprint
Yee, D. M., Leng, X., Shenhav, A., & Braver, T. S. (2021) · PsyArXiv (OSF Preprints) · doi:10.1016/j.neubiorev.2021.12.016 · Cited by 60
Model-free and model-based reward prediction errors in EEG
Sambrook, T. D., Hardwick, B., Wills, A. J., & Goslin, J. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.05.023 · Cited by 50
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Duerler, P., Vollenweider, F. X., & Preller, K. H. (2022) · Journal of Neurochemistry · doi:10.1111/jnc.15607 · Cited by 52
Transdiagnostic computations of uncertainty: towards a new lens on intolerance of uncertainty
Sandhu, T. R., Xiao, B., & Lawson, R. P. (2023) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2023.105123 · Cited by 51
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Mano, H., & Seymour, B. (2015) · PLoS Biology · doi:10.1371/journal.pbio.1002037 · Cited by 66
Self-citationBayer, J., Bandurski, P., & Sommer, T. (2013) · European Journal of Neuroscience · doi:10.1111/ejn.12347 · Cited by 49
Serotonergic regulation of the dopaminergic system: Implications for reward-related functions
Courtiol, E., Menezes, E. D. C., & Teixeira, C. M. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.06.022 · Cited by 50
Löffler, M., Levine, S. M., Usai, K., Desch, S., Mišić, M., Nees, F., & Flor, H. (2022) · Cell Reports Medicine · doi:10.1016/j.xcrm.2022.100677 · Cited by 45
Grünblatt, E., Hauser, T. U., & Walitza, S. (2014) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2014.07.003 · Cited by 44
Harm to self outweighs benefit to others in moral decision making
Volz, L. J., Welborn, B. L., Gobel, M. S., Gazzaniga, M. S., & Grafton, S. T. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1706693114 · Cited by 46
Stoltenberg, S. F., Christ, C. C., & Carlo, G. (2013) · Social Neuroscience · doi:10.1080/17470919.2013.807874 · Cited by 43
Boecker-Schlier, R., Holz, N. E., Buchmann, A. F., Blomeyer, D., Plichta, M. M., Jennen-Steinmetz, C., Wolf, I., Baumeister, S., Treutlein, J., Rietschel, M., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.02.006 · Cited by 42
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Self-citationThe Role of Tryptophan and Tyrosine in Executive Function and Reward Processing
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Self-citation
Metadata
- Authors
- Seymour, B., Daw, N. D., Roiser, J. P., Dayan, P., & Dolan, R.
- Affiliations
- Wellcome Centre for Human Neuroimaging (GB)
- Gatsby Computational Neuroscience Unit (GB)
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2012-04-25
- Volume
- 32
- Issue
- 17
- Pages
- 5833-5842
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC5321452
- OpenAlex
- W2083058253
- Cited by
- 252
- References
- 61
- Citations by year
- 2026: 8 · 2025: 16 · 2024: 20 · 2023: 25 · 2022: 15 · 2021: 17 · 2020: 19 · 2019: 13 · 2018: 20 · 2017: 17 · 2016: 17 · 2015: 17 · 2014: 22 · 2013: 19 · 2012: 7
- FWCI
- 8.57
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Max Planck Digital Library (submittedVersion, other-oa)
- Cambridge University Engineering Department Publications Database (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- Wellcome Trust (091593, 079866)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Keywords
- serotonin, decision-making, reward value, tryptophan depletion, monetary rewards, pain, punishment, reward processing, computational modeling of choice
- MeSH terms
- Brain, Brain Mapping, Conditioning, Operant, Decision Making, Double-Blind Method, Electric Stimulation, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Oxygen, Pain, Pain Measurement, Probability, Punishment, Surveys and Questionnaires, Reward, Serotonin, Statistics as Topic, Tryptophan, Dietary Supplements
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