The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Adaptation of Reward Sensitivity in Orbitofrontal Neurons
Open accessAbstract
Animals depend on a large variety of rewards but their brains have a limited dynamic coding range. When rewards are uncertain, neuronal coding needs to cover a wide range of possible rewards. However, when reward is likely to occur within a specific range, focusing the sensitivity on the predicted range would optimize the discrimination of small reward differences. One way to overcome the trade-off between wide coverage and optimal discrimination is to adapt reward sensitivity dynamically to the available rewards. We investigated how changes in reward distribution influenced the coding of reward in the orbitofrontal cortex. Animals performed an oculomotor task in which a fixation cue predicted the SD of the probability distribution of juice volumes, while the expected mean volume was kept constant. A subsequent cue specified the exact juice volume obtained for a correct saccade response. Population responses of orbitofrontal neurons that reflected the predicted juice volume showed adaptation to the reward distribution. Statistical tests on individual responses revealed that a quarter of value-coding neurons shifted the reward sensitivity slope significantly between two reward distributions, whereas the remaining neurons showed insignificant change or lack of adaptation. Adaptations became more prominent when reward distributions changed less frequently, indicating time constraints for assessing reward distributions and adjusting neuronal sensitivity. The observed neuronal adaptation would optimize discrimination and contribute to the efficient coding of a large variety of potential rewards by neurons with limited dynamic range.
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Citations
Cites
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
Self-citationNeurons in the orbitofrontal cortex encode economic value
Padoa-Schioppa, C., & Assad, J. A. (2006) · Nature · doi:10.1038/nature04676 · Cited by 1,598
Dissociation in prefrontal cortex of affective and attentional shifts
Dias, R., Robbins, T. W., & Roberts, A. C. (1996) · Nature · doi:10.1038/380069a0 · Cited by 1,527
Adaptive Coding of Reward Value by Dopamine Neurons
Tobler, P. N., Fiorillo, C. D., & Schultz, W. (2005) · Science · doi:10.1126/science.1105370 · Cited by 1,276 · cited 4×
“We used two reward distributions with different SDs, and each distribution consisted of three equiprobable juice volumes.”
InfluentialSelf-citationThe orbitofrontal cortex: Neuronal activity in the behaving monkey
Thorpe, S. J., Rolls, E. T., & Maddison, S. (1983) · Experimental Brain Research · doi:10.1007/bf00235545 · Cited by 836
Dynamic predictive coding by the retina
Hosoya, T., Baccus, S. A., & Meister, M. (2005) · Nature · doi:10.1038/nature03689 · Cited by 468
Range-adapting representation of economic value in the orbitofrontal cortex
Padoa-Schioppa, C. (2009) · The Journal of Neuroscience · doi:10.1523/jneurosci.3751-09.2009 · Cited by 276
Cited by
Neuronal Reward and Decision Signals: From Theories to Data
Schultz, W. (2015) · Physiological Reviews · doi:10.1152/physrev.00023.2014 · Cited by 1,126
Self-citationThe neurobiology of anhedonia and other reward-related deficits
Der-Avakian, A., & Markou, A. (2012) · Trends in Neurosciences · doi:10.1016/j.tins.2011.11.005 · Cited by 1,130
Value, pleasure and choice in the ventral prefrontal cortex
Grabenhorst, F., & Rolls, E. T. (2011) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2010.12.004 · Cited by 766
Neurobiology of economic choice: a good-based model
Padoa-Schioppa, C. (2011) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-061010-113648 · Cited by 600
Sterling, P., & Laughlin, S. (2015) · doi:10.7551/mitpress/9780262028707.001.0001 · Cited by 482
Metadata
- Authors
- Kobayashi, S., Pinto de Carvalho, O., & Schultz, W.
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2010-01-13
- Volume
- 30
- Issue
- 2
- Pages
- 534-544
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- OpenAlex
- W1988547834
- Cited by
- 206
- References
- 7
- FWCI
- 7.60
- Type
- journal article
- Language
- en
- Open access
- hybrid
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