4.7 Article

A Role Beyond Learning for NMDA Receptors in Reward-Based Decision-Making-a Pharmacological Study Using d-Cycloserine

Journal

NEUROPSYCHOPHARMACOLOGY
Volume 39, Issue 12, Pages 2900-2909

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/npp.2014.144

Keywords

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Funding

  1. Oxfordshire Health Services Research Committee [OHSRC 1021]
  2. Wellcome Trust [092759/Z/10/Z, 089280/Z/09/Z]
  3. Wellcome Trust (MFSR) [WT100973AIA]
  4. p1vital
  5. Servier
  6. Eli Lilly
  7. AstraZeneca
  8. Lundbeck
  9. Medical Research Council [G0902373] Funding Source: researchfish
  10. Wellcome Trust [100973/Z/13/Z] Funding Source: researchfish
  11. Wellcome Trust [092759/Z/10/Z, 100973/Z/13/Z, 089280/Z/09/Z] Funding Source: Wellcome Trust
  12. MRC [G0902373, MR/J011878/1] Funding Source: UKRI

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N-methyl-D-aspartate (NMDA) receptors are known to fulfill crucial functions in many forms of learning and plasticity. More recently, biophysical models, however, have suggested an additional role of NMDA receptors in evidence integration for decision-making, going beyond their role in learning. We designed a task to study the role of NMDA receptors in human reward-guided learning and decision-making. Human participants were assigned to receive either 250 mg of the partial NMDA agonist d-cycloserine (n = 20) or matching placebo capsules (n = 27). Reward-guided learning and decision-making were assessed using a task in which participants had to integrate learnt and explicitly shown value information to maximize their monetary wins and minimize their losses. To tease apart the effects of NMDA on learning and decision-making we used simple learning models. D-cycloserine shifted decision-making towards a more optimal integration of the learnt and the explicitly shown information, in the absence of a direct learning effect. In conclusion, our results reveal a distinct role for NMDA receptors in reward-guided decision-making. We discuss these findings in the context of NMDA's roles in neuronal super-additivity and as crucial for evidence integration for decisions.

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