Dopamine dependence in aggregate feedback learning: A computational cognitive neuroscience approach.
Procedural learning of skills depends on dopamine-mediated striatal plasticity. Most prior work investigated single stimulus-response procedural learning followed by feedback. However, many skills include several actions that must be performed before feedback is available. A new procedural-learning task is developed in which three independent and successive unsupervised categorization responses receive aggregate feedback indicating either that all three responses were correct, or at least one response was incorrect. Experiment 1 showed superior learning of stimuli in position 3, and that learning in the first two positions was initially compromised, and then recovered. An extensive theoretical analysis that used parameter space partitioning found that a large class of procedural-learning models, which predict propagation of dopamine release from feedback to stimuli, and/or an eligibility trace, fail to fully account for these data. The analysis also suggested that any dopamine released to the second or third stimulus impaired categorization learning in the first and second positions. A second experiment tested and confirmed a novel prediction of this large class of procedural-learning models that if the to-be-learned actions are introduced one-by-one in succession then learning is much better if training begins with the first action (and works forwards) than if it begins with the last action (and works backwards).
Department of Psychological & Brain Sciences, University of California, Santa Barbara, United States. Electronic address: valentin@psych.ucsb.edu.
Vivian V
VV
Valentin
Department of Psychology, University of Texas, 108 E. Dean Keeton, Stop A8000, Austin, TX 78712-1043, United States. Electronic address: wtoddmaddox@gmail.com.
W Todd
WT
Maddox
Department of Psychological & Brain Sciences, University of California, Santa Barbara, United States. Electronic address: ashby@psych.ucsb.edu.
F Gregory
FG
Ashby
D000328:Adult; D000066494:Cognitive Neuroscience / Q000379:methods*; D003210:Concept Formation / Q000502:physiology*; D004298:Dopamine / Q000502:physiology*; D030141:Feedback, Psychological / Q000502:physiology*; D006801:Humans; D007858:Learning / Q000502:physiology*; D008962:Models, Theoretical; D055815:Young Adult
D004298:Dopamine
Computational cognitive neuroscience; Dopamine; Parameter space partitioning; Skill learning; Striatal plasticity