The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index.
The anticipation and outcome phases of reward and loss processing: A neuroimaging meta‐analysis of the monetary incentive delay task
Open accessAbstract
The processing of rewards and losses are crucial to everyday functioning. Considerable interest has been attached to investigating the anticipation and outcome phases of reward and loss processing, but results to date have been inconsistent. It is unclear if anticipation and outcome of a reward or loss recruit similar or distinct brain regions. In particular, while the striatum has widely been found to be active when anticipating a reward, whether it activates in response to the anticipation of losses as well remains ambiguous. Furthermore, concerning the orbitofrontal/ventromedial prefrontal regions, activation is often observed during reward receipt. However, it is unclear if this area is active during reward anticipation as well. We ran an Activation Likelihood Estimation meta‐analysis of 50 fMRI studies, which used the Monetary Incentive Delay Task (MIDT), to identify which brain regions are implicated in the anticipation of rewards, anticipation of losses, and the receipt of reward. Anticipating rewards and losses recruits overlapping areas including the striatum, insula, amygdala and thalamus, suggesting that a generalised neural system initiates motivational processes independent of valence. The orbitofrontal/ventromedial prefrontal regions were recruited only during the reward outcome, likely representing the value of the reward received. Our findings help to clarify the neural substrates of the different phases of reward and loss processing, and advance neurobiological models of these processes.
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Cites
The reward circuit: linking primate anatomy and human imaging
Haber, S. N., & Knutson, B. (2010) · Neuropsychopharmacology · doi:10.1038/npp.2009.129 · Cited by 3,718
Self-referential processing in our brain—A meta-analysis of imaging studies on the self
Northoff, G., Heinzel, A., de Greck, M., Bermpohl, F., Dobrowolny, H., & Panksepp, J. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2005.12.002 · Cited by 2,792
Remembering the past to imagine the future: the prospective brain
Schacter, D. L., Addis, D. R., & Buckner, R. L. (2007) · Nature Reviews Neuroscience · doi:10.1038/nrn2213 · Cited by 2,394
From motivation to action: Functional interface between the limbic system and the motor system
MOGENSON, G., JONES, D., & YIM, C. (1980) · Progress in Neurobiology · doi:10.1016/0301-0082(80)90018-0 · Cited by 2,331
Dissociable 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
Discrete coding of reward probability and uncertainty by dopamine neurons
Fiorillo, C. D., Tobler, P. N., & Schultz, W. (2003) · Science · doi:10.1126/science.1077349 · Cited by 2,085
KRINGELBACH, M. (2004) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2004.03.006 · Cited by 1,977
Bartra, O., McGuire, J. T., & Kable, J. W. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.02.063 · Cited by 1,927
The neural basis of loss aversion in decision-making under risk
Tom, S. M., Fox, C. R., Trepel, C., & Poldrack, R. A. (2007) · Science · doi:10.1126/science.1134239 · Cited by 1,733
Neuronal Coding of Prediction Errors
Schultz, W., & Dickinson, A. (2000) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.23.1.473 · Cited by 1,427
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Skumlien, M., Mokrysz, C., Freeman, T. P., Valton, V., Wall, M. B., Bloomfield, M., Lees, R., Borissova, A., Petrilli, K., Giugliano, M., et al. (2023) · International Journal of Neuropsychopharmacology · doi:10.1093/ijnp/pyac056 · Cited by 20
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Addressing altered anticipation as a transdiagnostic target through computational psychiatry
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Metadata
- Authors
- Oldham, S., Murawski, C., Fornito, A., Youssef, G., Yücel, M., & Lorenzetti, V.
- Venue
- Human Brain Mapping
- Publisher
- Wiley
- Published
- 2018-04-25
- Volume
- 39
- Issue
- 8
- Pages
- 3398-3418
- ISSN
- 1065-9471 (ISSN-L)
- 1097-0193
- OpenAlex
- W2800351030
- Cited by
- 425
- References
- 57
- FWCI
- 19.78
- Type
- journal article
- Language
- en
- Open access
- hybrid
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