RT Journal Article
SR Electronic
T1 Precision weighting of cortical unsigned prediction errors is mediated by dopamine and benefits learning
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 288936
DO 10.1101/288936
A1 J. Haarsma
A1 P.C. Fletcher
A1 H. Ziauddeen
A1 T.J. Spencer
A1 K.M.J. Diederen
A1 G.K Murray
YR 2018
UL http://biorxiv.org/content/early/2018/05/10/288936.abstract
AB The predictive coding framework construes the brain as performing a specific form of hierarchical Bayesian inference. In this framework the precision of cortical unsigned prediction error (surprise) signals is proposed to play a key role in learning and decisionmaking, and to be controlled by dopamine. To test this hypothesis, we re-analysed an existing data-set from healthy individuals who received a dopamine agonist, antagonist or placebo and who performed an associative learning task under different levels of outcome precision. Computational reinforcement-learning modelling of behaviour provided support for precision-weighting of unsigned prediction errors. Functional MRI revealed coding of unsigned prediction errors relative to their precision in bilateral superior frontal gyri and dorsal anterior cingulate. Cortical precision-weighting was (i) perturbed by the dopamine antagonist sulpiride, and (ii) associated with task performance. These findings have important implications for understanding the role of dopamine in reinforcement learning and predictive coding in health and illness.