Abstract
Motivation for goal-directed behaviors depends on the hierarchical orchestration between brain systems of valuation and executive control. This integrative review synthesized evidence that dopamine, acting on the mesocorticolimbic axis, primarily signals reward prediction error and mobilizes the effort necessary for action, underpinning the motivational "wanting" component. This signal is integrated by corticostriatal circuits, in which the functional connectivity between the ventral striatum and the dorsolateral prefrontal cortex is essential for transforming valuation into persistent action plans capable of overcoming costs and distractions. Dysregulation of this system generates opposing psychopathologies: hypofunction and frontostriatal disconnection are associated with apathy and anhedonia in depression, while hypersensitization of the reward system to specific stimuli sustains compulsive seeking in addiction. It is concluded that adaptive motivation requires dynamic balance and effective communication within this network, offering an integrated model for the development of targeted interventions.
References
Salamone JD, Correa M. The mysterious motivational functions of mesolimbic dopamine. Neuron. 2012;76(3):470-85. https://doi.org/10.1016/j.neuron.2012.10.021
Berridge KC, Robinson TE. Liking, wanting, and the incentive-sensitization theory of addiction. Am Psychol. 2016;71(8):670-9. https://doi.org/10.1037/amp0000059
Pessoa L. On the relationship between emotion and cognition. Nat Rev Neurosci. 2008;9(2):148-58. https://doi.org/10.1038/nrn2317
Schultz W. Dopamine reward prediction-error signalling: a two-component response. Nat Rev Neurosci. 2016;17(3):183-95. https://doi.org/10.1038/nrn.2015.26
Wise RA. Dopamine, learning and motivation. Nat Rev Neurosci. 2004;5(6):483-94. https://doi.org/10.1038/nrn1406
Berridge KC. From prediction error to incentive salience: mesolimbic computation of reward motivation. Eur J Neurosci. 2012;35(7):1124-43. https://doi.org/10.1111/j.1460-9568.2012.07990.x
Schultz W. Neuronal reward and decision signals: from theories to data. Physiol Rev. 2015;95(3):853-951. https://doi.org/10.1152/physrev.00023.2014
Niv Y. Reinforcement learning in the brain. J Math Psychol. 2009;53(3):139-54. https://doi.org/10.1016/j.jmp.2008.12.005
Haber SN, Knutson B. The reward circuit: linking primate anatomy and human imaging. Neuropsychopharmacology. 2010;35(1):4-26. https://doi.org/10.1038/npp.2009.129
Balleine BW, O'Doherty JP. Human and rodent homologies in action control: corticostriatal determinants of goal-directed and habitual action. Neuropsychopharmacology. 2010;35(1):48-69. https://doi.org/10.1038/npp.2009.131
Der-Avakian A, Markou A. The neurobiology of anhedonia and other reward-related deficits. Trends Neurosci. 2012;35(1):68-77. https://doi.org/10.1016/j.tins.2011.11.005
Volkow ND, Wise RA, Baler R. The dopamine motive system: implications for drug and food addiction. Nat Rev Neurosci. 2017;18(11):741-52. https://doi.org/10.1038/nrn.2017.130
Botvinick M, Braver T. Motivation and cognitive control: from behavior to neural mechanism. Annu Rev Psychol. 2015;66:83-113. https://doi.org/10.1146/annurev-psych-010814-015044
Souza MT, Silva MD, Carvalho R. Revisão integrativa: o que é e como fazer. Einstein (São Paulo). 2010;8(1):102-6. https://doi.org/10.1590/s1679-45082010rw1134
Whittemore R, Knafl K. The integrative review: updated methodology. J Adv Nurs. 2005;52(5):546-53. https://doi.org/10.1111/j.1365-2648.2005.03621.x
Botelho LLR, Cunha CCA, Macedo M. O método da revisão integrativa nos estudos organizacionais. Gest Soc. 2011;5(11):121-36. https://doi.org/10.21171/ges.v5i11.1220
Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71. https://doi.org/10.1136/bmj.n71
Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. 2006;3(2):77-101. https://doi.org/10.1191/1478088706qp063oa
Papalini S, Beckers T, Vervliet B. Dopamine: from prediction error to psychotherapy. Transl Psychiatry. 2020;10:164. https://doi.org/10.1038/s41398-020-0814-x
Borsini A, St John Wallis A, Zunszain P, Pariante CM, Kempton MJ. Characterizing anhedonia: a systematic review of neuroimaging across the subtypes of reward processing deficits in depression. Cogn Affect Behav Neurosci. 2020;20(4):816-41. https://doi.org/10.3758/s13415-020-00804-6
Horne SJ, Topp ET, Quigley L. Depression and the willingness to expend cognitive and physical effort for rewards: a systematic review. Clin Psychol Rev. 2021;88:102065. https://doi.org/10.1016/j.cpr.2021.102065
Bailey MR, Chun E, Schipani E, Balsam PD, Simpson EH. Dissociating the effects of dopamine D2 receptors on effort-based versus value-based decision making using a novel behavioral approach. Behav Neurosci. 2020;134(2):101-18. https://doi.org/10.1037/bne0000361
Salamone JD, Correa M. The neurobiology of activational aspects of motivation: exertion of effort, effort-based decision making, and the role of dopamine. Annu Rev Psychol. 2024;75:1-32. https://doi.org/10.1146/annurev-psych-020223-012208
Salamone JD, Ecevitoglu A, Carratala-Ros C, Presby RE, Edelstein GA, Fleeher R, et al. Complexities and paradoxes in understanding the role of dopamine in incentive motivation and instrumental action: exertion of effort vs. anhedonia. Brain Res Bull. 2022;182:57-66. https://doi.org/10.1016/j.brainresbull.2022.01.019
Corlett PR, Mollick JA, Kober H. Meta-analysis of human prediction error for incentives, perception, cognition, and action. Neuropsychopharmacology. 2022;47(7):1339-49. https://doi.org/10.1038/s41386-021-01264-3
Kok A. Cognitive control, motivation and fatigue: a cognitive neuroscience perspective. Brain Cogn. 2022;160:105880. https://doi.org/10.1016/j.bandc.2022.105880
Wang S, et al. Anhedonia as a central factor in depression: neural mechanisms revealed from preclinical to clinical evidence. Prog Neuropsychopharmacol Biol Psychiatry. 2021;110:110289. https://doi.org/10.1016/j.pnpbp.2021.110289
Liang S, Wu Y, Li H, Greenshaw AJ, Li T. Anhedonia in depression and schizophrenia: brain reward and aversion circuits. Neuropsychiatr Dis Treat. 2022;18:1385-96. https://doi.org/10.2147/NDT.S367839
Ekhtiari H, Zare-Bidoky M, Sangchooli A, et al. A methodological checklist for fMRI drug cue reactivity studies: development and expert consensus. Nat Protoc. 2022;17(3):567-95. https://doi.org/10.1038/s41596-021-00649-4
Addiction Cue-Reactivity Initiative (ACRI) Network, et al. Parameter space and potential for biomarker development in 25 years of fMRI drug cue reactivity: a systematic review. JAMA Psychiatry. 2024;81(4):414-25. https://doi.org/10.1001/jamapsychiatry.2023.5483
Pollard AA, Hauson AO, Lackey NS, et al. Functional neuroanatomy of craving in heroin use disorder: voxel-based meta-analysis of functional magnetic resonance imaging (fMRI) drug cue reactivity studies. Am J Drug Alcohol Abuse. 2023;49(4):418-30. https://doi.org/10.1080/00952990.2023.2172423
Bore MC, Liu X, Gan X, et al. Distinct neurofunctional alterations during motivational and hedonic processing of natural and monetary rewards in depression: a neuroimaging meta-analysis. Psychol Med. 2024;54(4):639-51. https://doi.org/10.1017/S0033291723003410
Kieslich K, Valton V, Roiser JP. Pleasure, reward value, prediction error and anhedonia. Curr Top Behav Neurosci. 2022;58:281-304. https://doi.org/10.1007/7854_2021_295

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Copyright (c) 2026 Global Academic Nursing Journal
