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Common and distinct networks underlying reward valence and processing stages: A meta-analysis of functional neuroimaging studies
Open accessAbstract
To better understand the reward circuitry in human brain, we conducted activation likelihood estimation (ALE) and parametric voxel-based meta-analyses (PVM) on 142 neuroimaging studies that examined brain activation in reward-related tasks in healthy adults. We observed several core brain areas that participated in reward-related decision making, including the nucleus accumbens (NAcc), caudate, putamen, thalamus, orbitofrontal cortex (OFC), bilateral anterior insula, anterior cingulate cortex (ACC) and posterior cingulate cortex (PCC), as well as cognitive control regions in the inferior parietal lobule and prefrontal cortex (PFC). The NAcc was commonly activated by both positive and negative rewards across various stages of reward processing (e.g., anticipation, outcome, and evaluation). In addition, the medial OFC and PCC preferentially responded to positive rewards, whereas the ACC, bilateral anterior insula, and lateral PFC selectively responded to negative rewards. Reward anticipation activated the ACC, bilateral anterior insula, and brain stem, whereas reward outcome more significantly activated the NAcc, medial OFC, and amygdala. Neurobiological theories of reward-related decision making should therefore take distributed and interrelated representations of reward valuation and valence assessment into account.
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“Nevertheless, we are confident that the receipt-related effects reported here are robust and reliable based on the size of the sample we used as well as the clear main task effect of receipt (irrespective of group) that is in line with previous reports 47.”
From Increased neural responses to reward in adolescents and young adults with attention-deficit/hyperactivity disorder and their unaffected siblings (2015) · cites this paper as [47]
The cited source says what the claim attributes to it.
In the citing paper
“Indeed, striatal structures are known to show biphasic responses, making them capable of responding to positive (reward) as well as negative (punishment) stimulation.47”
From Increased neural responses to reward in adolescents and young adults with attention-deficit/hyperactivity disorder and their unaffected siblings (2015) · cites this paper as [47]
In the citing paper
“The ACC plays a central role in processing positively valenced emotions [239] and other rewards [240], and in coding value representations of anticipated rewards [241]”
From Reward circuitry dysfunction in psychiatric and neurodevelopmental disorders and genetic syndromes: animal models and clinical findings (2012) · cites this paper as [240]
In the citing paper
“Contrasting adolescent reward processing with the existing ALE of adult reward processing (Liu et al., 2011) reveals increased likelihood for activation in limbic, frontolimbic, and striatal regions in adolescents compared with adults.”
From Neural networks involved in adolescent reward processing: an activation likelihood estimation meta-analysis of functional neuroimaging studies (2015) · cites this paper as Liu et al., 2011
In the citing paper
“However, in support of our predictions, contrast analyses revealed an increased likelihood for activation in adolescents compared with adults in the bilateral ventral and dorsal striatum, insula, OFC, anterior cingulate cortex (ACC), PCC, frontal opercular regions, paracingulate gyrus, subcallosal cortex; right amygdala, right occipital pole; and left lateral occipital cortex.”
From Neural networks involved in adolescent reward processing: an activation likelihood estimation meta-analysis of functional neuroimaging studies (2015) · cites this paper as Liu et al. (2011)
In the citing paper
“These regions overlap the subcortical regions identified in similar ALEs of adult reward processing (Liu et al., 2011; Bartra et al., 2013) and include major dopaminergic projection regions”
From Neural networks involved in adolescent reward processing: an activation likelihood estimation meta-analysis of functional neuroimaging studies (2015) · cites this paper as Liu et al., 2011
In the citing paper
“A major finding of the current analysis is that adolescents and adults varied in activations during reward processing as supported by descriptive comparisons between our overall ALE and findings reported by Liu et al. (2011) as well as our contrast analysis.”
From Neural networks involved in adolescent reward processing: an activation likelihood estimation meta-analysis of functional neuroimaging studies (2015) · cites this paper as Liu et al. (2011)
In the citing paper
“it has not yet been confirmed that, across studies, adolescents reliably activate the same regions during reward based processing as do adults (McClure et al., 2004; Liu et al., 2011; Bartra et al., 2013).”
From Neural networks involved in adolescent reward processing: an activation likelihood estimation meta-analysis of functional neuroimaging studies (2015) · cites this paper as Liu et al., 2011
In the citing paper
“using the coordinates for the overall adult reward processing ALE provided by Liu and colleagues (2011) and the thresholding parameters outlined in their manuscript, we reproduced the findings reported in their study as a validation check of our procedures.”
From Neural networks involved in adolescent reward processing: an activation likelihood estimation meta-analysis of functional neuroimaging studies (2015) · cites this paper as Liu et al., 2011
In the citing paper
“No significant neural substrates were found in the contrast of negative greater than positive valence processing.”
From Neural networks involved in adolescent reward processing: an activation likelihood estimation meta-analysis of functional neuroimaging studies (2015) · cites this paper as Liu et al. (2011)
In the citing paper
“Notably, previous studies on adolescent reward processing have relied on studies of adult reward processing (Liu et al., 2011) for guiding hypothesis testing and ROI analyses (e.g., Lorenz et al., 2014).”
From Neural networks involved in adolescent reward processing: an activation likelihood estimation meta-analysis of functional neuroimaging studies (2015) · cites this paper as Liu et al., 2011
In the citing paper
“Notably, Liu et al. (2011) also reported strong activation likelihoods for numerous regions of the dorsal and ventral prefrontal cortex as well as superior and inferior parietal areas.”
From Neural networks involved in adolescent reward processing: an activation likelihood estimation meta-analysis of functional neuroimaging studies (2015) · cites this paper as Liu et al., 2011
In the citing paper
“Liu et al. (2011) found a significant likelihood of nucleus accumbens and OFC activation in adults’ processing of reward outcomes versus anticipation.”
From Neural networks involved in adolescent reward processing: an activation likelihood estimation meta-analysis of functional neuroimaging studies (2015) · cites this paper as Liu et al. (2011)
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Citations
Cites
A default mode of brain function
Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.2.676 · Cited by 12,190
The human brain is intrinsically organized into dynamic, anticorrelated functional networks
Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0504136102 · Cited by 8,553
How do you feel — now? The anterior insula and human awareness
(Bud) Craig, A. D. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2555 · Cited by 6,657 · cited 1×
“N IH -PA Author M anuscript N IH -PA Author M anuscript N IH -PA Author M anuscript interoception, emotion and empathy (Craig, 2002, 2009; Gu et al., 2010; Phan et al., 2002), and risk and uncertainty assessment (Critchley et al., 2001; Kuhnen and Knutson, 2005; Paulus et al., 2003), lending its…”
How do you feel? Interoception: The sense of the physiological condition of the body
Craig, A. D. (2002) · Nature Reviews Neuroscience · doi:10.1038/nrn894 · Cited by 6,006
The Neural Basis of Decision Making
Gold, J. I., & Shadlen, M. N. (2007) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.29.051605.113038 · Cited by 3,764
Functional neuroanatomy of emotion: A meta-analysis of emotion activation studies in PET and fMRI
Phan, K. L., Wager, T., Taylor, S. F., & Liberzon, I. (2002) · NeuroImage · doi:10.1006/nimg.2002.1087 · Cited by 3,502
The neural basis of economic decision-making in the Ultimatum Game.
Sanfey, A. G., Rilling, J. K., Aronson, J. A., Nystrom, L. E., & Cohen, J. D. (2003) · Science · doi:10.1126/science.1082976 · Cited by 3,375
Anticipation of Increasing Monetary Reward Selectively Recruits Nucleus Accumbens
Knutson, B., Adams, C. M., Fong, G. W., & Hommer, D. (2001) · The Journal of Neuroscience · doi:10.1523/jneurosci.21-16-j0002.2001 · Cited by 2,244
Cortical 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
The human orbitofrontal cortex: linking reward to hedonic experience
Kringelbach, M. L. (2005) · Nature Reviews Neuroscience · doi:10.1038/nrn1747 · Cited by 2,180
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Items 101–200 of 916
Disordered gambling: a behavioral addiction
Clark, L., & Limbrick‐Oldfield, E. H. (2013) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2013.01.004 · Cited by 115
Gregory, S., Blair, J., Ffytche, D. H., Simmons, A., Kumari, V., Hodgins, S., & Blackwood, N. (2015) · The Lancet Psychiatry · doi:10.1016/s2215-0366(14)00071-6 · Cited by 117
Cohen, M. S., Rissman, J., Suthana, N., Castel, A. D., & Knowlton, B. J. (2014) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/s13415-014-0275-x · Cited by 108
Dissociating contributions of ACC and vmPFC in reward prediction, outcome, and choice
Vassena, E., Krebs, R. M., Silvetti, M., Fias, W., & Verguts, T. (2014) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2014.04.019 · Cited by 111
Cao, Z., Bennett, M., Orr, C., Icke, I., Banaschewski, T., Barker, G. J., Bokde, A. L. W., Bromberg, U., Büchel, C., Quinlan, E. B., et al. (2018) · Human Brain Mapping · doi:10.1002/hbm.24370 · Cited by 109
Li, Y., Yuan, K., Cai, C., Feng, D., Yin, J., Bi, Y., Shi, S., Yu, D., Jin, C., von Deneen, K. M., et al. (2015) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2015.03.023 · Cited by 108
fMRI Functional Connectivity Applied to Adolescent Neurodevelopment
Ernst, M., Torrisi, S., Balderston, N. L., Grillon, C., & Hale, E. A. (2015) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-032814-112753 · Cited by 111
Cerebral interactions of pain and reward and their relevance for chronic pain
Becker, S., Gandhi, W., & Schweinhardt, P. (2012) · Neuroscience Letters · doi:10.1016/j.neulet.2012.03.013 · Cited by 103
Diederen, K. M. J., Spencer, T., Vestergaard, M. D., Fletcher, P. C., & Schultz, W. (2016) · Neuron · doi:10.1016/j.neuron.2016.04.019 · Cited by 102
Siebenthal, Z. V., Boucher, O., Lazzouni, L., Taylor, V. A., Martinu, K., Roy, M., Rainville, P., Leporé, F., & Nguyen, D. K. (2020) · Scientific Reports · doi:10.1038/s41598-020-68644-5 · Cited by 102
Andrzejewski, J. A., Greenberg, T., & Carlson, J. M. (2019) · Cognitive, Affective, & Behavioral Neuroscience · doi:10.3758/s13415-019-00747-7 · Cited by 100
Plichta, M. M., Wolf, I., Hohmann, S., Baumeister, S., Boecker, R., Schwarz, A. J., Zangl, M., Mier, D. U., Diener, C., Meyer, P., et al. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.0631-13.2013 · Cited by 109
Disentangling reward anticipation with simultaneous pupillometry / fMRI
Schneider, M., Leuchs, L., Czisch, M., Sämann, P. G., & Spoormaker, V. I. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.04.078 · Cited by 111
Altered brain response to reward and punishment in adolescents with Anorexia nervosa
Bischoff-Grethe, A., McCurdy, D., Grenesko-Stevens, E., (Zoe) Irvine, L. E., Wagner, A., Wendy Yau, W.-Y., Fennema-Notestine, C., Wierenga, C. E., Fudge, J. L., Delgado, M. R., et al. (2013) · Psychiatry Research: Neuroimaging · doi:10.1016/j.pscychresns.2013.07.004 · Cited by 99
Structural Connections of Functionally Defined Human Insular Subdivisions
Nomi, J. S., Schettini, E., Broce, I., Dick, A. S., & Uddin, L. Q. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx211 · Cited by 106
Video game training and the reward system
Lorenz, R. C., Gleich, T., Gallinat, J. ⁄. R., & Kühn, S. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2015.00040 · Cited by 114
Jauhar, S., Fortea, L., Solanes, A., Albajes‐Eizagirre, A., McKenna, P. J., & Raduà, J. (2021) · PLoS ONE · doi:10.1371/journal.pone.0255292 · Cited by 103
Effort increases sensitivity to reward and loss magnitude in the human brain
Hernandez-Lallement, J., Kuss, K., Trautner, P., Weber, B., Falk, A., & Fließbach, K. (2012) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nss147 · Cited by 97
Nakao, T., Ohira, H., & Northoff, G. (2012) · Frontiers in Neuroscience · doi:10.3389/fnins.2012.00031 · Cited by 102
Rybnicek, R., Bergner, S., & Gutschelhofer, A. (2017) · Review of Managerial Science · doi:10.1007/s11846-017-0252-1 · Cited by 133
Duncan, N. W., Wiebking, C., Tiret, B., Marjańska, M., Hayes, D. J., Lyttleton, O., Doyon, J., & Northoff, G. (2013) · PLoS ONE · doi:10.1371/journal.pone.0060312 · Cited by 95
Levy, I., & Schiller, D. (2021) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2020.11.007 · Cited by 95
Neural mechanisms for learning self and other ownership
Lockwood, P. L., Wittmann, M. K., Apps, M. A. J., Klein-Flügge, M. C., Crockett, M. J., Humphreys, G. W., & Rushworth, M. F. S. (2018) · Nature Communications · doi:10.1038/s41467-018-07231-9 · Cited by 98
Verdejo‐García, A., Lorenzetti, V., Manning, V., Piercy, H., Bruno, R., Hester, R., Pennington, D., Tolomeo, S., Arunogiri, S., Bates, M. E., et al. (2019) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2019.00877 · Cited by 95
Allostasis, action and affect in depression: Insights from the theory of constructed emotion
Shaffer, C., Westlin, C., Quigley, K. S., Whitfield-Gabrieli, S., & Barrett, L. F. (2022) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-081219-115627 · Cited by 94
Individualized real-time fMRI neurofeedback to attenuate craving in nicotine-dependent smokers
Hartwell, K. J., Hanlon, C. A., Li, X., Borckardt, J. J., Canterberry, M., Prisciandaro, J. J., Maria, M. M. M., LeMatty, T., George, M. S., & Brady, K. T. (2015) · Journal of Psychiatry and Neuroscience · doi:10.1503/jpn.140200 · Cited by 98
Schroeter, M. L., Laird, A. R., Chwiesko, C., Deuschl, C., Schneider, E., Bzdok, D., Eickhoff, S. B., & Neumann, J. (2014) · Cortex · doi:10.1016/j.cortex.2014.02.022 · Cited by 97
Prenatal Drug Exposure Affects Neonatal Brain Functional Connectivity
Salzwedel, A. P., Grewen, K. M., Vachet, C., Gerig, G., Lin, W., & Gao, W. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.4333-14.2015 · Cited by 93
Capacity and tendency: A neuroscientific framework for the study of emotion regulation
Silvers, J. A., & Moreira, J. F. G. (2017) · Neuroscience Letters · doi:10.1016/j.neulet.2017.09.017 · Cited by 101
Oumeziane, B. A., Jones, O., & Foti, D. (2019) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2019.00199 · Cited by 100
Bereczkei, T. (2015) · Brain and Cognition · doi:10.1016/j.bandc.2015.06.007 · Cited by 100
Psychosurgery Reduces Uncertainty and Increases Free Will? A Review
Ridder, D. D., Vanneste, S., Gillett, G. R., Manning, P. J., Glue, P., & Langguth, B. (2016) · Neuromodulation Technology at the Neural Interface · doi:10.1111/ner.12405 · Cited by 92
Zisner, A. R., & Beauchaine, T. P. (2016) · Development and Psychopathology · doi:10.1017/s0954579416000754 · Cited by 101
Orbitofrontal cortex mediates pain inhibition by monetary reward
Becker, S., Gandhi, W., Pomares, F. B., Wager, T. D., & Schweinhardt, P. (2017) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsw173 · Cited by 95
Anticipation of temporally structured events in the brain
Lee, C. S., Aly, M., & Baldassano, C. A. (2021) · eLife · doi:10.7554/elife.64972 · Cited by 91
Neural correlates of Machiavellian strategies in a social dilemma task
Bereczkei, T., Deák, A., Papp, P., Perlaki, G., & Orsi, G. (2013) · Brain and Cognition · doi:10.1016/j.bandc.2013.02.012 · Cited by 91
Abnormal striatal BOLD responses to reward anticipation and reward delivery in ADHD
Furukawa, E., Bado, P., Tripp, G., Mattos, P., Wickens, J. R., Bramati, I. E., Alsop, B., Ferreira, F. M., Lima, D., Tovar-Moll, F., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0089129 · Cited by 90
Mesbah, R., Koenders, M. A., van der Wee, N. J. A., Giltay, E. J., van Hemert, A. M., & de Leeuw, M. (2023) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2023.0131 · Cited by 97
Neural responses to monetary incentives among self-injuring adolescent girls
Sauder, C. L., Derbidge, C. M., & Beauchaine, T. P. (2016) · Development and Psychopathology · doi:10.1017/s0954579415000449 · Cited by 89
Common brain activations for painful and non-painful aversive stimuli
Hayes, D. J., & Northoff, G. (2012) · BMC Neuroscience · doi:10.1186/1471-2202-13-60 · Cited by 99
A Neural Signature of Affiliative Emotion in the Human Septohypothalamic Area
Moll, J., Bado, P., de Oliveira‐Souza, R., Bramati, I. E., Lima, D. O., Paiva, F. F., Sato, J. R., Tovar-Moll, F. F., & Zahn, R. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.6508-11.2012 · Cited by 87
Wang, D., Yan, X., Li, M., & Ma, Y. (2017) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsx085 · Cited by 86
Perinatal maternal depressive symptoms alter amygdala functional connectivity in girls
Soe, N. N., Wen, D. J., Poh, J. S., Chong, Y., Broekman, B. F., Chen, H., Shek, L. P., Tan, K. H., Gluckman, P. D., Fortier, M. V., et al. (2018) · Human Brain Mapping · doi:10.1002/hbm.23873 · Cited by 86
Pelowski, M. J., Gerger, G., Chetouani, Y., Markey, P. S., & Leder, H. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.01729 · Cited by 93
Spatial smoothing systematically biases the localization of reward-related brain activity
Sacchet, M. D., & Knutson, B. D. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.10.056 · Cited by 86
Fanning, J. R., Keedy, S., Berman, M. E., Lee, R., & Coccaro, E. F. (2017) · Current Behavioral Neuroscience Reports · doi:10.1007/s40473-017-0115-8 · Cited by 92
Aversive stimuli and loss in the mesocorticolimbic dopamine system
Brooks, A. M., & Berns, G. S. (2013) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2013.04.001 · Cited by 85
Hwang, J. W., Xin, S., Ou, Y., Zhang, W. Y., Liang, Y., Chen, J., Yang, X., Chen, X. Y., Guo, T., Yang, X., et al. (2016) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2016.02.005 · Cited by 85
Précis on The Cognitive-Emotional Brain
Pessoa, L. (2015) · Behavioral and Brain Sciences · doi:10.1017/s0140525x14000120 · Cited by 84
From Vivaldi to Beatles and back: Predicting lateralized brain responses to music
Alluri, V., Toiviainen, P., Lund, T. E., Wallentin, M., Vuust, P., Nandi, A. K., Ristaniemi, T., & Brattico, E. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.06.064 · Cited by 88
Pujara, M. S., Philippi, C. L., Motzkin, J. C., Başkaya, M. K., & Koenigs, M. R. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.4236-15.2016 · Cited by 87
Andreou, C., Frielinghaus, H., Rauh, J., Mußmann, M., Vauth, S., Braun, P., Leicht, G., & Mulert, C. (2017) · Translational Psychiatry · doi:10.1038/tp.2016.287 · Cited by 90
Fan, J., Liu, W., Xia, J., Li, S., Gao, F., Zhu, J., Han, Y., Zhou, H., Liao, H., Yi, J., et al. (2020) · Human Brain Mapping · doi:10.1002/hbm.25222 · Cited by 89
Self-citationReward, motivation and brain imaging in human healthy participants – A narrative review
Weinstein, A. M. (2023) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2023.1123733 · Cited by 95
Cheng, Y., Xu, J., Nie, B., Luo, C., Yang, T., Li, H., Lu, J., Xu, L., Shan, B., & Xu, X. (2013) · PLoS ONE · doi:10.1371/journal.pone.0067478 · Cited by 82
Medial prefrontal cortical activity reflects dynamic re-evaluation during voluntary persistence
McGuire, J. T., & Kable, J. W. (2015) · Nature Neuroscience · doi:10.1038/nn.3994 · Cited by 86
Li, C. R., Ide, J. S., Zhang, S., Hu, S., Chao, H. H., & Záborszky, L. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.04.019 · Cited by 83
The role of hedonics in the Human Affectome
Becker, S., Bräscher, A., Bannister, S., Bensafi, M., Calma‐Birling, D., Chan, R. C. K., Eerola, T., Ellingsen, D., Ferdenzi, C., Hanson, J. L., et al. (2019) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.05.003 · Cited by 93
Cortisol administration induces global down-regulation of the brain's reward circuitry
Montoya, E. R., Bos, P. A., Terburg, D., Rosenberger, L. A., & van Honk, J. (2014) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2014.04.022 · Cited by 80
Beauchaine, T. P., Hinshaw, S. P., & Bridge, J. A. (2019) · Clinical Psychological Science · doi:10.1177/2167702618818474 · Cited by 80
Zhang, D., Shen, J., Bi, R., Zhang, Y., Zhou, F., Feng, C., & Gu, R. (2020) · Psychological Medicine · doi:10.1017/s0033291720003967 · Cited by 82
Cohen, J. I., Yates, K. F., Duong, M. T., & Convit, A. J. (2011) · BMJ Open · doi:10.1136/bmjopen-2011-000175 · Cited by 83
Dopaminergic stimulation enhances confidence and accuracy in seeing rapidly presented words
LOU, H. C., Skewes, J., Thomsen, K. R., Overgaard, M. S., Lau, H. C., Mouridsen, K., & Roepstorff, A. (2011) · Journal of Vision · doi:10.1167/11.2.15 · Cited by 83
Forbes, E. E., Rodriguez, E. E., Musselman, S. C., & Narendran, R. (2014) · PLoS ONE · doi:10.1371/journal.pone.0094640 · Cited by 84
Temporal dynamics of reward anticipation in the human brain
Zhang, Y., Li, Q., Wang, Z., Liu, X., & Zheng, Y. (2017) · Biological Psychology · doi:10.1016/j.biopsycho.2017.07.011 · Cited by 83
Self-citationHerremans, S. C., Van Schuerbeek, P., De Raedt, R., Matthys, F., Buyl, R., De Mey, J., & Baeken, C. (2015) · PLOS ONE · doi:10.1371/journal.pone.0136182 · Cited by 78
Reward processing in gain versus loss context: An ERP study
Zheng, Y., Li, Q., Zhang, Y., Li, Q., Shen, H., Gao, Q., & Zhou, S.-Y. (2017) · Psychophysiology · doi:10.1111/psyp.12855 · Cited by 82
Better the devil you know than the devil you don't: Neural processing of risk and ambiguity
Wu, S., Sun, S., Camilleri, J. A., Eickhoff, S. B., & Yu, R. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118109 · Cited by 78
Greipl, S., Klein, E., Lindstedt, A., Kiili, K. J. M., Moeller, K., Karnath, H., Bahnmueller, J., Bloechle, J., & Ninaus, M. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2021.106946 · Cited by 88
Robert, G., Jeune, F. L., Dondaine, T., Drapier, S., Péron, J., Lozachmeur, C., Sauleau, P., Houvenaghel, J., Travers, D., Millet, B., et al. (2014) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp-2013-307025 · Cited by 78
Crone, E. A., Achterberg, M., Dobbelaar, S., Euser, S., van den Bulk, B. G., van der Meulen, M., van Drunen, L., Wierenga, L. M., Bakermans‐Kranenburg, M. J., & van IJzendoorn, M. H. (2020) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2020.100805 · Cited by 83
Silvers, J. A., Insel, C., Powers, A., Franz, P., Weber, J., Mischel, W., Casey, B. J., & Ochsner, K. N. (2014) · Psychological Science · doi:10.1177/0956797614546001 · Cited by 76
The Positive Valence Systems Scale: Development and Validation
Khazanov, G. K., Ruscio, A. M., & Forbes, C. N. (2019) · Assessment · doi:10.1177/1073191119869836 · Cited by 83
Cohn, M. D., Veltman, D. J., Pape, L. E., van Lith, K., Vermeiren, R. R. J. M., van den Brink, W., DORELEIJERS, T. A. H., & Popma, A. (2014) · Biological Psychiatry · doi:10.1016/j.biopsych.2014.08.017 · Cited by 79
Kujawa, A., Carroll, A., Mumper, E. E., Mukherjee, D., Kessel, E. M., Olino, T. M., Hajcak, G., & Klein, D. N. (2017) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2017.11.001 · Cited by 77
Luo, Y., Eickhoff, S. B., Hétu, S., & Feng, C. (2017) · Human Brain Mapping · doi:10.1002/hbm.23854 · Cited by 82
Ecstatic Epileptic Seizures: A Glimpse into the Multiple Roles of the Insula
Gschwind, M., & Picard, F. (2016) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2016.00021 · Cited by 78
Wang, Z., Fang, J., Liu, J. H., Rong, P., Jorgenson, K., Park, J., Lang, C., Yang, H., Zhu, B., & Kong, J. (2017) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2017.12.018 · Cited by 75
Intranasal oxytocin increases neural responses to social reward in post-traumatic stress disorder
Nawijn, L., van Zuiden, M., Koch, S. B. J., Frijling, J. L., Veltman, D. J., & Olff, M. (2016) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsw123 · Cited by 72
Trost, S., Diekhof, E. K., Zvonik, K., Lewandowski, M., Usher, J., Keil, M., Zilles‐Wegner, D., Falkai, P., Dechent, P., & Gruber, O. (2014) · Neuropsychopharmacology · doi:10.1038/npp.2014.39 · Cited by 73
The alcoholic brain: neural bases of impaired reward-based decision-making in alcohol use disorders
Galandra, C., Basso, G., Cappa, S. F., & Canessa, N. (2017) · Neurological Sciences · doi:10.1007/s10072-017-3205-1 · Cited by 76
Dugre, J. R., Raduà, J., Carignan-Allard, M., Dumais, A., Rubia, K., & Potvin, S. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.09.013 · Cited by 75
Neural bases of antisocial behavior: a voxel-based meta-analysis
Aoki, Y. Y., Inokuchi, R., Nakao, T., & Yamasue, H. (2013) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nst104 · Cited by 73
Bellis, M. D. D., Wang, L., Bergman, S. R., Yaxley, R. H., Hooper, S. R., & Huettel, S. A. (2013) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2013.05.020 · Cited by 76
Dolcos, S. M., Hu, Y., Iordan, A. D., Moore, M., & Dolcos, F. (2015) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsv106 · Cited by 79
Huang, F., Tang, S., Sun, P., & Luo, J. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.01.070 · Cited by 72
Neural correlates of processing “self-conscious” vs. “basic” emotions
Gilead, M., Katzir, M., Eyal, T., & Liberman, N. (2015) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2015.12.009 · Cited by 74
Role of Frontostriatal Connectivity in Adolescents With Excessive Smartphone Use
Chun, J.-W., Choi, J.-Y., Cho, H., Choi, M.-R., Ahn, K., Choi, J.-S., & Kim, D. (2018) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2018.00437 · Cited by 65
Ladouceur, C. D., Kerestes, R., Schlund, M. W., Shirtcliff, E. A., Lee, Y., & Dahl, R. E. (2018) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2018.12.016 · Cited by 76
The effects of age on reward magnitude processing in the monetary incentive delay task
Dhingra, I., Zhang, S., Zhornitsky, S., Le, T. M., Wang, W., Chao, H. H., Levy, I., & Li, C. R. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116368 · Cited by 77
Reward for food odors: an fMRI study of liking and wanting as a function of metabolic state and BMI
Jiang, T., Soussignan, R., Schaal, B., & Royet, J. (2014) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsu086 · Cited by 76
Oumeziane, B. A., Schryer-Praga, J., & Foti, D. (2017) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2017.11.001 · Cited by 75
Fatigue in inflammatory rheumatic disorders: pathophysiological mechanisms
Korte, S. M., & Straub, R. H. (2019) · Rheumatology · doi:10.1093/rheumatology/kez413 · Cited by 71
Gueguen, M. C. M., Lopez‐Persem, A., Billeke, P. B., Lachaux, J.-P., Rheims, S., Kahane, P., Minotti, L., Olivier David, A., Pessiglione, M., & Bastin, J. (2021) · Nature Communications · doi:10.1038/s41467-021-23704-w · Cited by 73
Modular structure of functional networks in olfactory memory
David Meunier, A., Fonlupt, P., Saive, A.-L., Plailly, J., Ravel, N., & Royet, J. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.03.041 · Cited by 70
Role of the Primate Ventral Tegmental Area in Reinforcement and Motivation
Arsenault, J. T., Rima, S., Stemmann, H., & Vanduffel, W. (2014) · Current Biology · doi:10.1016/j.cub.2014.04.044 · Cited by 70
Dugre, J. R., Dumais, A., Bitar, N., & Potvin, S. (2018) · PeerJ · doi:10.7717/peerj.4749 · Cited by 71
Loth, E., Poline, J.-B., Thyreau, B., Jia, T., Tao, C., Lourdusamy, A., Stacey, D., Cattrell, A., Desrivières, S., Ruggeri, B., et al. (2014) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.07.043 · Cited by 65
Baeken, C., Marinazzo, D., Schuerbeek, P. V., Wu, G., Mey, J. D., Luypaert, R., & Raedt, R. D. (2014) · PLoS ONE · doi:10.1371/journal.pone.0095740 · Cited by 68
Neural Population Decoding Reveals the Intrinsic Positivity of the Self
Chavez, R. S., Heatherton, T. F., & Wagner, D. D. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw302 · Cited by 68
Metadata
- Authors
- Liu, X., Hairston, J., Schrier, M., & Fan, J.
- Affiliations
- Chinese Academy of Sciences (CN)
- Icahn School of Medicine at Mount Sinai (US)
- Queens College, CUNY (US)
- Corresponding author
- Liu, Xun
- Venue
- Neuroscience & Biobehavioral Reviews
- Publisher
- Elsevier BV
- Published
- 2011-04
- Volume
- 35
- Issue
- 5
- Pages
- 1219-1236
- ISSN
- 0149-7634 (ISSN-L)
- PMC
- PMC3395003
- OpenAlex
- W2131675069
- Semantic Scholar
- 2ad686808fa437bceed156b160d64b167847da84
- Cited by
- 916
- References
- 196
- Citations by year
- 2026: 33 · 2025: 59 · 2024: 50 · 2023: 58 · 2022: 50 · 2021: 70 · 2020: 69 · 2019: 55 · 2018: 68 · 2017: 71 · 2016: 68 · 2015: 71 · 2014: 96 · 2013: 49 · 2012: 36
- FWCI
- 2.34
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Neuroscience & Biobehavioral Reviews (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Institutional Repository of Institute of Psychology, Chinese Academy of Sciences (Institute of Psychology, Chinese Academy of Sciences) (submittedVersion)
- Institutional Repository of Institute of Psychology, Chinese Academy of Sciences (Institute of Psychology, Chinese Academy of Sciences) (submittedVersion, cc-by-nc-sa)
- Funders
- National Institute of Mental Health (R21MH083164)
- 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 › Psychology › Clinical Psychology › Gambling Behavior and Treatments
- Keywords
- reward processing, reward valence, reward systems, nucleus accumbens, orbitofrontal cortex, anterior insula, anterior cingulate cortex, posterior cingulate cortex, thalamus, caudate and putamen, reward anticipation, reward outcome, amygdala, cognitive control
- MeSH terms
- Brain, Brain Mapping, Diagnostic Imaging, Humans, Functional Laterality, Neural Pathways, Reward, Likelihood Functions, Databases, Factual
About these checks
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