, Volume 231, Issue 7, pp 1351–1364 | Cite as

A new view of the effect of dopamine receptor antagonism on operant performance for rewarding brain stimulation in the rat

  • I. Trujillo-Pisanty
  • K. Conover
  • P. ShizgalEmail author
Original Investigation



Previous studies of neuroleptic challenges to intracranial self-stimulation (ICSS) employed two-dimensional (2D) measurements (curve shifts). Results so obtained are ambiguous with regard to the stage of neural processing at which the drug produces its performance-altering effect. We substituted a three-dimensional (3D) method that measures reward-seeking as a function of both the strength and cost of reward. This method reveals whether changes in reward seeking are due to drug action prior to the output of the circuitry that performs spatiotemporal integration of the stimulation-induced neural activity.


The aim of this study was to obtain new information about the stage of neural processing at which pimozide acts to alter pursuit of brain stimulation reward (BSR).


Following treatment with pimozide (0.1 mg/kg) or its vehicle, the proportion of trial time allocated to working for BSR was measured as a function of pulse frequency and opportunity cost. A surface defined by Shizgal's reward-mountain model was fitted to the drug and vehicle data.


Pimozide lowered the cost required to decrease performance for a maximal BSR to half its maximal level but did not alter the pulse-frequency required to produce a reward of half-maximal intensity.


Like indirect dopamine agonists, pimozide does not alter the sensitivity of brain reward circuity but changes reward-system gain, subjective effort costs, and/or the value of activities that compete with ICSS. The 3D method is more sensitive and informative than the 2D methods employed previously.


Pimozide Opportunity cost Neuroeconomics Reward mountain Intracranial self-stimulation ICSS Neuroleptics 



The research was supported by a grant to PS from the Canadian Institutes of Health Research (#MOP–74577), a group grant from the “Fonds de recherche Québec—santé” to the “Groupe de Recherche en Neurobiologie Comportementale”/Center for Studies in Behavioural Neurobiology (Shimon Amir, p.i.), support for PS from the Concordia University Research Chairs program, and scholarships to ITP from the “Consejo Nacional de Ciencia y Tecnologia” (CONACYT, #209314) and “le Ministère de l'Éducation, du Loisir et du Sport du Québec” (PBEEE-1M, #140498). David Munro built and maintained the computer-controlled equipment for experimental control and data acquisition. Software for experimental control and data acquisition was written and maintained by Steve Cabilio. The authors thank Brian Dunn for helpful comments on the manuscript.

Supplementary material


(MPG 102836 kb)


  1. Akaike H (1974) A new look at the statistical model identification. Autom Control IEEE Trans 19(6):716–723CrossRefGoogle Scholar
  2. Anderson RM, Fatigati MD, Rompré PP (1996) Estimates of the axonal refractory period of midbrain dopamine neurons: their relevance to brain stimulation reward. Brain Res 718(1–2):83–88PubMedCrossRefGoogle Scholar
  3. Anlezark GM et al (1974) Electrical self-stimulation in relation to cells of origin of catecholamine-containing neural systems ascending from the brain stem. J Physiol 237(2):31P–32PPubMedGoogle Scholar
  4. Arbuthnott GW et al (1970) Behavioural effects of stimulation in the region of the substantia nigra. J Pharmacol Sci 210:61P–62PGoogle Scholar
  5. Arvanitogiannis A, Shizgal P (2008) The reinforcement mountain: allocation of behavior as a function of the rate and intensity of rewarding brain stimulation. Behavioral Neuroscience 122(5):1126–1138.
  6. Atalay J, Wise RA (1983) Time course of pimozide effects on brain stimulation reward. Pharmacol Biochem Behav 18(4):655–658PubMedCrossRefGoogle Scholar
  7. Bauco P, Wang Y, Wise RA (1993) Lack of sensitization or tolerance to the facilitating effect of ventral tegmental area morphine on lateral hypothalamic brain stimulation reward. Brain Res 617(2):303–308PubMedCrossRefGoogle Scholar
  8. Baum W, Rachlin H (1969) Choice as time allocation. J Exp Anal Behav 12(6):861–874PubMedCentralPubMedCrossRefGoogle Scholar
  9. Bielajew C, Shizgal P (1982) Behaviorally derived measures of conduction velocity in the substrate for rewarding medial forebrain bundle stimulation. Brain Res 237(1):107–119PubMedCrossRefGoogle Scholar
  10. Bielajew C, Shizgal P (1986) Evidence implicating descending fibers in self-stimulation of the medial forebrain bundle. J Neurosci Off J Soc Neurosci 6(4):919–929Google Scholar
  11. Breton Y-A et al (2013) Validation and extension of the reward-mountain model. Front Behav Neurosci 7:125PubMedCentralPubMedCrossRefGoogle Scholar
  12. Breton Y-A, Marcus JC, Shizgal P (2009) Rattus psychologicus: construction of preferences by self-stimulating rats. Behav Brain Res 202(1):77–91PubMedCrossRefGoogle Scholar
  13. Corbett D, Wise RA (1980) Intracranial self-stimulation in relation to the ascending dopaminergic systems of the midbrain: a moveable electrode mapping study. Brain Res 185(1):1–15PubMedCrossRefGoogle Scholar
  14. Crow TJ (1972) A map of the rat mesencephalon for electrical self-stimulation. Brain Res 36(2):265–273PubMedCrossRefGoogle Scholar
  15. Crow TJ (1970) Enhancement by cocaine of intracranial self-stimulation in the rat. Life Sci 9(7):375–381PubMedCrossRefGoogle Scholar
  16. Edmonds DE, Gallistel CR (1974) Parametric analysis of brain stimulation reward in the rat: III. Effect of performance variables on the reward summation function. J Comp Physiol Psychol 87(5):876–883PubMedCrossRefGoogle Scholar
  17. Edmonds DE, Gallistel CR (1977) Reward versus performance in self-stimulation: electrode-specific effects of alpha-methyl-p-tyrosine on reward in the rat. J Comp Physiol Psychol 91(5):962–974PubMedCrossRefGoogle Scholar
  18. Efron B, Tibshirani RJ (1994) An Introduction to the Bootstrap 1st ed. Chapman and Hall/CRC, Boca RatonGoogle Scholar
  19. Esposito R, Kornetsky C (1977) Morphine lowering of self-stimulation thresholds: lack of tolerance with long-term administration. Science 195(4274):189–191 (New York, NY)PubMedCrossRefGoogle Scholar
  20. Fibiger HC et al (1987) The role of dopamine in intracranial self-stimulation of the ventral tegmental area. J Neurosci Off J Soc Neurosci 7(12):3888–3896Google Scholar
  21. Franklin KB (1978) Catecholamines and self-stimulation: reward and performances effects dissociated. Pharmacol Biochem Behav 9(6):813–820PubMedCrossRefGoogle Scholar
  22. Gallistel C, Shizgal P, Yeomans J (1981) A portrait of the substrate for self-stimulation. Psychol Rev 88(3):228–273PubMedCrossRefGoogle Scholar
  23. Gallistel CR, Freyd G (1987) Quantitative determination of the effects of catecholaminergic agonists and antagonists on the rewarding efficacy of brain stimulation. Pharmacol Biochem Behav 26(4):731–741PubMedCrossRefGoogle Scholar
  24. Gallistel CR, Leon M (1991) Measuring the subjective magnitude of brain stimulation reward by titration with rate of reward. Behav Neurosci 105(6):913–925PubMedCrossRefGoogle Scholar
  25. Gallistel CR et al (1991) Effect of current on the maximum possible reward. Behav Neurosci 105(6):901–912PubMedCrossRefGoogle Scholar
  26. Hernandez G et al (2010) At what stage of neural processing does cocaine act to boost pursuit of rewards? PLoS ONE 5(11)Google Scholar
  27. Hernandez G et al (2006) Prolonged rewarding stimulation of the rat medial forebrain bundle: neurochemical and behavioral consequences. Behav Neurosci 120(4):888–904PubMedCrossRefGoogle Scholar
  28. Hernandez G et al (2012) Role of dopamine tone in the pursuit of brain stimulation reward. J Neurosci Off J Soc Neurosci 32(32):11032–11041CrossRefGoogle Scholar
  29. Herrnstein R (1974) Formal properties of the matching law. J Exp Anal Behav 21(1):159–164PubMedCentralPubMedCrossRefGoogle Scholar
  30. Herrnstein R (1970) On the law of effect. J Exp Anal Behav 13(2):243–266PubMedCentralPubMedCrossRefGoogle Scholar
  31. Heyman GM, Beer B (1987) A new approach for evaluating the behavioral effects of antipsychotic drugs. Trends Pharmacol Sci 8(10):388–393CrossRefGoogle Scholar
  32. Jennings JH et al (2013) Distinct extended amygdala circuits for divergent motivational states. Nature 496(7444):224–228PubMedCentralPubMedCrossRefGoogle Scholar
  33. Kempadoo KA et al (2013) Hypothalamic neurotensin projections promote reward by enhancing glutamate transmission in the VTA. J Neurosci 33(18):7618–7626PubMedCentralPubMedCrossRefGoogle Scholar
  34. Killeen P (1972) The matching law. J Exp Anal Behav 17(3):489–495PubMedCentralPubMedCrossRefGoogle Scholar
  35. Leon M, Gallistel CR (1992) The function relating the subjective magnitude of brain stimulation reward to stimulation strength varies with site of stimulation. Behav Brain Res 52(2):183–193PubMedCrossRefGoogle Scholar
  36. Miliaressis E et al (1986) The curve-shift paradigm in self-stimulation. Physiol Behav 37(1):85–91PubMedCrossRefGoogle Scholar
  37. Moisan J, Rompré PP (1998) Electrophysiological evidence that a subset of midbrain dopamine neurons integrate the reward signal induced by electrical stimulation of the posterior mesencephalon. Brain Res 786(1–2):143–152PubMedCrossRefGoogle Scholar
  38. Niv Y et al (2007) Tonic dopamine: opportunity costs and the control of response vigor. Psychopharmacology (Berl) 191(3):507–520CrossRefGoogle Scholar
  39. Niv Y, Daw N, Dayan P (2006) How fast to work: response vigor, motivation, and tonic dopamine. Adv in Neural Inf Process syst 18:1019Google Scholar
  40. Olds J, Milner P (1954) Positive reinforcement produced by electrical stimulation of septal area and other regions of rat brain. J Comp Physiol Psychol 47(6):419–427PubMedCrossRefGoogle Scholar
  41. Paxinos G, Watson C (2007) The rat brain in stereotaxic coordinates 6 ed, Elsevier/Academic PressGoogle Scholar
  42. Petry N, Heyman G (1997) Rat toys, reinforcers, and response strength: an examination of the Re parameter in Herrnstein's. Behav Processes 39:39–52CrossRefGoogle Scholar
  43. Rachlin H (1971) On the tautology of the matching law. J Exp Anal Behav 15(2):249–251PubMedCentralPubMedCrossRefGoogle Scholar
  44. Rompré PP, Wise RA (1989) Behavioral evidence for midbrain dopamine depolarization inactivation. Brain Res 477(1–2):152–156PubMedCrossRefGoogle Scholar
  45. Salamone JD et al (2009) Dopamine, behavioral economics, and effort. Front Behav Neurosci 3:13PubMedCentralPubMedCrossRefGoogle Scholar
  46. Salamone JD et al (2007) Effort-related functions of nucleus accumbens dopamine and associated forebrain circuits. Psychopharmacology (Berl) 191(3):461–482CrossRefGoogle Scholar
  47. Salamone JD et al (2003) Nucleus accumbens dopamine and the regulation of effort in food-seeking behavior: implications for studies of natural motivation, psychiatry, and drug abuse. J Pharmacol Exp Ther 305(1):1–8PubMedCrossRefGoogle Scholar
  48. Shizgal P (1997) Neural basis of utility estimation. Curr Opin Neurobiol 7(2):198–208PubMedCrossRefGoogle Scholar
  49. Shizgal P (2012) Scarce means with alternative uses: Robbins' definition of economics and its extension to the behavioral and neurobiological study of animal decision making. Front Neurosci 6:20PubMedCentralPubMedCrossRefGoogle Scholar
  50. Shizgal P et al (1980) Behavioral methods for inferring anatomical linkage between rewarding brain stimulation sites. J Comp Physiol Psychol 94(2):227–237PubMedCrossRefGoogle Scholar
  51. Simmons JM, Gallistel CR (1994) Saturation of subjective reward magnitude as a function of current and pulse frequency. Behav Neurosci 108(1):151–160PubMedCrossRefGoogle Scholar
  52. Sonnenschein B, Conover K, Shizgal P (2003) Growth of brain stimulation reward as a function of duration and stimulation strength. Behav Neurosci 117(5):978–994PubMedCrossRefGoogle Scholar
  53. Stellar JR, Kelley AE, Corbett D (1983) Effects of peripheral and central dopamine blockade on lateral hypothalamic self-stimulation: evidence for both reward and motor deficits. Pharmacol Biochem Behav 18(3):433–442PubMedCrossRefGoogle Scholar
  54. Trujillo-Pisanty I et al (2011) Cannabinoid receptor blockade reduces the opportunity cost at which rats maintain operant performance for rewarding brain stimulation. J Neurosci Off J Soc Neurosci 31(14):5426–5435CrossRefGoogle Scholar
  55. Tsai H-C et al (2009) Phasic firing in dopaminergic neurons is sufficient for behavioral conditioning. Science 324(5930):1080–1084 (New York, NY)PubMedCrossRefGoogle Scholar
  56. Wise RA (1996) Addictive drugs and brain stimulation reward. Ann Rev Neurosci 19:319–340PubMedCrossRefGoogle Scholar
  57. Witten IB et al (2011) Recombinase-driver rat lines: tools, techniques, and optogenetic application to dopamine-mediated reinforcement. Neuron 72(5):721–733PubMedCentralPubMedCrossRefGoogle Scholar
  58. Yeomans JS, Maidment NT, Bunney BS (1988) Excitability properties of medial forebrain bundle axons of A9 and A10 dopamine cells. Brain Res 450(1–2):86–93PubMedCrossRefGoogle Scholar
  59. Yizhar O et al (2011) Optogenetics in neural systems. Neuron 71(1):9–34PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Center for Studies in Behavioural Neurobiology/Groupe de Recherche en Neurobiologie ComportementaleConcordia UniversityMontrealCanada

Personalised recommendations