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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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Smelling decides: fMRI evidence reveals the influence of olfactory stimuli on risky decision-making
Dakhili, A. H., Kamrava, S. K., & Sadeghi, A. Z. (2026) · Journal of Neuroradiology · doi:10.1016/j.neurad.2026.101529
Βases cérébrales du compromis coûts/bénéfices
Clairis, N. (2020) · theses.fr (ABES) · doi:10.70675/5e0e9c10z2c72z4ed2zb4caz900659cedbc0
Bases neuro-fonctionnelles des troubles de l’impulsivité dans la maladie de Parkinson
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Kawata, K., Buddenbaum, C. V., Huibregtse, M. E., Sweeney, S. H., Cheng, H., Rosenberg, M. S., Finn, D., Newman, S. D., Wetzel, G. M., Hohne, J. M., et al. (2026) · PLoS ONE · doi:10.1371/journal.pone.0344672
Wen, X., Fengge, Y., Han, B., Wei, G., Gao, Y., Chen, Y., Hao, Z., Li, H., & Dou, F. (2026) · Brain Structure and Function · doi:10.1007/s00429-026-03089-6
RETRACTED: Neural correlates of risky monetary decision-making impacting others
Fede, S. J., Jefferson, Y., & Romines, A. J. (2026) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2026.1813515
Retracted
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
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