Striatal dopamine supports reward expectation and learning: A simultaneous PET/fMRI study.

Finnegan J Calabro, David F Montez, Bart Larsen, Charles M Laymon, William Foran, Michael N Hallquist, Julie C Price, Beatriz Luna
Author Information
  1. Finnegan J Calabro: Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA. Electronic address: fjc20@pitt.edu.
  2. David F Montez: Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA; Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.
  3. Bart Larsen: Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA.
  4. Charles M Laymon: Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA; Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA.
  5. William Foran: Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
  6. Michael N Hallquist: Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA; Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  7. Julie C Price: Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
  8. Beatriz Luna: Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA; Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA.

Abstract

Converging evidence from both human neuroimaging and animal studies has supported a model of mesolimbic processing underlying reward learning behaviors, based on the computation of reward prediction errors. However, competing evidence supports human dopamine signaling in the basal ganglia as also contributing to the generation of higher order learning heuristics. Here, we present data from a large (N = 81, 18-30yo), multi-modal neuroimaging study using simultaneously acquired task fMRI, affording temporal resolution of reward system function, and PET imaging with [C]Raclopride (RAC), assessing striatal dopamine (DA) D2/3 receptor binding, during performance of a probabilistic reward learning task. Both fMRI activation and PET DA measures showed ventral striatum involvement for signaling rewards. However, greater DA release was uniquely associated with learning strategies (i.e., learning rates) that were more task-optimal within the best fitting reinforcement learning model. This DA response was associated with BOLD activation of a network of regions including anterior cingulate cortex, medial prefrontal cortex, thalamus and posterior parietal cortex, primarily during expectation, rather than prediction error, task epochs. Together, these data provide novel, human in vivo evidence that striatal dopaminergic signaling interacts with a network of cortical regions to generate task-optimal learning strategies, rather than representing reward outcomes in isolation.

Keywords

References

  1. Prog Neurobiol. 2021 Jun;201:101997 [PMID: 33667595]
  2. J Neurophysiol. 1998 Jul;80(1):1-27 [PMID: 9658025]
  3. J Neurosci. 2003 May 15;23(10):3963-71 [PMID: 12764080]
  4. Neuroimage. 2013 Nov 15;82:208-25 [PMID: 23747457]
  5. J Neurosci. 2015 May 27;35(21):8145-57 [PMID: 26019331]
  6. Addict Biol. 2011 Oct;16(4):654-66 [PMID: 21790899]
  7. Behav Brain Funct. 2005 May 04;1:6 [PMID: 15953384]
  8. Brain Connect. 2017 Apr;7(3):152-171 [PMID: 28398812]
  9. Neuropsychopharmacology. 2018 Mar;43(4):820-827 [PMID: 28829051]
  10. Neuroimage. 2011 Jan 1;54(1):264-77 [PMID: 20600980]
  11. Cereb Cortex. 2007 Jul;17(7):1625-36 [PMID: 16963518]
  12. Annu Rev Neurosci. 2011;34:441-66 [PMID: 21469956]
  13. Neurosci Biobehav Rev. 2000 Jun;24(4):417-63 [PMID: 10817843]
  14. J Cereb Blood Flow Metab. 2001 Oct;21(10):1133-45 [PMID: 11598490]
  15. Proc Natl Acad Sci U S A. 2011 Sep 13;108 Suppl 3:15647-54 [PMID: 21389268]
  16. J Neurosci. 2006 Jan 4;26(1):217-22 [PMID: 16399690]
  17. Transl Psychiatry. 2018 Nov 30;8(1):264 [PMID: 30504860]
  18. Trends Cogn Sci. 2019 Mar;23(3):213-234 [PMID: 30711326]
  19. Neuroimage. 2017 Feb 1;146:701-714 [PMID: 27743899]
  20. Neuroimage. 2016 Nov 15;142:14-26 [PMID: 25944610]
  21. Neuroimage. 2013 Jul 15;75:46-57 [PMID: 23466936]
  22. J Clin Endocrinol Metab. 2021 Sep 27;106(10):2949-2961 [PMID: 34131733]
  23. J Neurosci. 2017 Jun 21;37(25):6087-6097 [PMID: 28539420]
  24. Psychol Sci. 2019 Nov;30(11):1561-1572 [PMID: 31652093]
  25. Hum Brain Mapp. 2006 Apr;27(4):306-13 [PMID: 16092133]
  26. Dialogues Clin Neurosci. 2016 Mar;18(1):23-32 [PMID: 27069377]
  27. Trends Cogn Sci. 2012 Feb;16(2):122-8 [PMID: 22226543]
  28. Behav Brain Res. 2009 Dec 7;204(2):396-409 [PMID: 19110006]
  29. Neuroimage. 2002 Aug;16(4):1015-27 [PMID: 12202089]
  30. J Neurosci. 2009 Oct 21;29(42):13365-76 [PMID: 19846724]
  31. J Neurosci. 2008 Mar 5;28(10):2435-46 [PMID: 18322089]
  32. Brain Res. 2010 Feb 8;1313:143-61 [PMID: 19961836]
  33. Behav Brain Res. 1991 Dec 13;46(1):17-29 [PMID: 1786111]
  34. PLoS Comput Biol. 2015 Jun 18;11(6):e1004237 [PMID: 26086934]
  35. Dev Cogn Neurosci. 2016 Feb;17:103-17 [PMID: 26774291]
  36. Science. 2014 Sep 26;345(6204):1616-20 [PMID: 25258080]
  37. Neuroimage. 2008 Feb 15;39(4):2058-65 [PMID: 18063390]
  38. Comput Biomed Res. 1996 Jun;29(3):162-73 [PMID: 8812068]
  39. J Neurophysiol. 1986 Nov;56(5):1439-61 [PMID: 3794777]
  40. Neuron. 2016 Jun 1;90(5):1127-38 [PMID: 27181060]
  41. Nat Commun. 2020 Feb 12;11(1):846 [PMID: 32051403]
  42. Nature. 2020 Apr;580(7802):239-244 [PMID: 32269346]
  43. J Neurosci. 1993 Mar;13(3):900-13 [PMID: 8441015]
  44. PLoS Comput Biol. 2014 Jan;10(1):e1003441 [PMID: 24465198]
  45. J Neurosci. 2004 Apr 28;24(17):4105-12 [PMID: 15115805]
  46. J Neurosci. 2007 Nov 21;27(47):12860-7 [PMID: 18032658]
  47. Psychiatry Res Neuroimaging. 2023 Aug;333:111660 [PMID: 37301129]
  48. Nature. 2019 Jun;570(7759):65-70 [PMID: 31118513]
  49. Nat Rev Neurosci. 2019 Nov;20(11):703-714 [PMID: 31570826]
  50. Nat Neurosci. 2018 Jun;21(6):787-793 [PMID: 29760524]
  51. Cereb Cortex. 2018 Dec 1;28(12):4281-4290 [PMID: 29121332]
  52. Psychol Med. 2010 Mar;40(3):433-40 [PMID: 19607754]
  53. PLoS Comput Biol. 2019 Jun 18;15(6):e1007043 [PMID: 31211783]
  54. J Neurosci. 2006 Mar 1;26(9):2449-57 [PMID: 16510723]
  55. Science. 2008 Aug 8;321(5890):848-51 [PMID: 18687967]
  56. Psychopharmacology (Berl). 2012 May;221(1):67-77 [PMID: 22052081]
  57. Annu Rev Neurosci. 2015 Jul 8;38:151-70 [PMID: 26154978]
  58. Annu Rev Neurosci. 1986;9:357-81 [PMID: 3085570]
  59. J Neurosci. 2001 Apr 15;21(8):2793-8 [PMID: 11306631]
  60. J Cereb Blood Flow Metab. 2022 Jul;42(7):1309-1321 [PMID: 35118904]
  61. J Neurosci. 2020 Jul 1;40(27):5273-5282 [PMID: 32457071]

Grants

  1. R01 MH080243/NIMH NIH HHS
  2. R37 MH080243/NIMH NIH HHS
  3. UL1 TR001857/NCATS NIH HHS

MeSH Term

Animals
Humans
Dopamine
Motivation
Magnetic Resonance Imaging
Corpus Striatum
Reward
Positron-Emission Tomography

Chemicals

Dopamine

Word Cloud

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