Scientific article
Decomposing the effects of context valence and feedback information on speed and accuracy during reinforcement learning: a meta-analytical approach using diffusion decision modeling
ContributorsFontanesi, Laura; Palminteri, Stefano; Lebreton, Mael
Published inCognitive Affective and Behavioral Neuroscience, vol. 19, no. 3, p. 490-502
Publication date2019
Funding
- Swiss National Science Foundation - Integrating Neuropsychological Models of Learning and Decision Making [153616]
- Swiss National Science Foundation - The role of dopaminergic midbrain nuclei in predicting monetary gains and losses: who’s doing what? [172017]
- Swiss National Science Foundation - A neuro-computational investigation of value precision [174127]
Citation (ISO format)
FONTANESI, Laura, PALMINTERI, Stefano, LEBRETON, Mael. Decomposing the effects of context valence and feedback information on speed and accuracy during reinforcement learning: a meta-analytical approach using diffusion decision modeling. In: Cognitive Affective and Behavioral Neuroscience, 2019, vol. 19, n° 3, p. 490–502. doi: 10.3758/s13415-019-00723-1
Main files (1)
Article (Published version)
Identifiers
- PID : unige:121096
- DOI : 10.3758/s13415-019-00723-1
- PMID : 31175616
Additional URL for this publicationhttp://link.springer.com/10.3758/s13415-019-00723-1
Journal ISSN1530-7026
