The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Learning about pain: The neural substrate of the prediction error for aversive events
Open accessAbstract
Associative learning is thought to depend on detecting mismatches between actual and expected experiences. With functional magnetic resonance imaging (FMRI), we studied brain activity during different types of mismatch in a paradigm where contrasting-colored lights signaled the delivery of painful heat, nonpainful warmth, or no stimulation. When painful heat stimulation was unexpected, there was increased FMRI signal intensity in areas of the hippocampus, superior frontal gyrus, cerebellum, and superior parietal gyrus that was not found with mismatch between expectation and delivery of nonpainful warmth stimulation. When painful heat stimulation was unexpectedly omitted, the FMRI signal intensity decreased in the left superior parietal gyrus and increased in the other regions. These contrasting activation patterns correspond to two different mismatch concepts in theories of associative learning (Rescorla-Wagner, temporal difference vs. Pearce-Hall, Mackintosh). Searching for interventions to specifically modulate activation of these brain regions therefore offers an approach to identifying new treatments for chronic pain, which often has a substantial associative learning component.
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Cites
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Preferential activation of midbrain dopamine neurons by appetitive rather than aversive stimuli
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Is the short-latency dopamine response too short to signal reward error?
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Cited by
Human brain mechanisms of pain perception and regulation in health and disease
Apkarian, A. V., Bushnell, M. C., Treede, R., & Zubieta, J. (2005) · European Journal of Pain · doi:10.1016/j.ejpain.2004.11.001 · Cited by 3,126
The Cerebral Signature for Pain Perception and Its Modulation
Tracey, I., & Mantyh, P. W. (2007) · Neuron · doi:10.1016/j.neuron.2007.07.012 · Cited by 1,843
Self-citationGut feelings: the emerging biology of gut-brain communication
Mayer, E. A. (2011) · Nature Reviews Neuroscience · doi:10.1038/nrn3071 · Cited by 1,726
Temporal difference models and reward-related learning in the human brain
O'Doherty, J. P., Dayan, P., Friston, K., Critchley, H., & Dolan, R. J. (2003) · Neuron · doi:10.1016/s0896-6273(03)00169-7 · Cited by 1,522
Control of mental activities by internal models in the cerebellum
Ito, M. (2008) · Nature Reviews Neuroscience · doi:10.1038/nrn2332 · Cited by 1,356
Metadata
- Authors
- Ploghaus, A., Tracey, I., Clare, S., Gati, J. S., Rawlins, J. N. P., & Matthews, P. M.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2000-07-25
- Volume
- 97
- Issue
- 16
- Pages
- 9281-9286
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2005857607
- Cited by
- 248
- References
- 7
- FWCI
- 4.35
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.