The ventral striatum is believed to encode the subjective value of cost–benefit options; however, this effect has notably been absent during choices that involve physical effort. Previous work in freely moving animals has revealed opposing striatal signals, with greater response to increasing effort demands and reduced responses to rewards requiring effort. Yet, the relationship between these conflicting signals remains unknown. Using functional magnetic resonance imaging with a naturalistic maze-navigation paradigm, we identified functionally segregated regions within the ventral striatum that separately encoded effort activation, movement initiation and effort discounting of rewards. In addition, activity in regions associated with effort activation and discounting oppositely predicted striatal encoding of effort during effort-based decision-making. Our results suggest that the dorsomedial region hitherto associated with action may instead represent the cost of effort and raise fundamental questions regarding the interpretation of striatal ‘reward’ signals in the context of effort demands. This has implications for uncovering the neural architecture underlying motivated behaviour.
This is a preview of subscription content, access via your institution
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$119.00 per year
only $9.92 per issue
Rent or buy this article
Prices vary by article type
Prices may be subject to local taxes which are calculated during checkout
Contrast maps of fMRI data that support the findings of this study are available on NeuroVault (https://neurovault.org/collections/LLQYKRMV/). Other data are available from the corresponding author upon request.
Custom code that supports the findings of this study is available from the corresponding author upon request.
Bartra, O., McGuire, J. T. & Kable, J. W. The valuation system: a coordinate-based meta-analysis of BOLD fMRI experiments examining neural correlates of subjective value. Neuroimage 76, 412–427 (2013).
Mogenson, G. J., Jones, D. L. & Yim, C. Y. From motivation to action: functional interface between the limbic system and the motor system. Prog. Neurobiol. 14, 69–97 (1980).
Knutson, B., Delgado, M. R. & Phillips, P. E. in Neuroeconomics: Decision Making and the Brain (eds Glimcher, P. W., Fehr, E., Camerer, C., & Poldrack, R. A.) 389–406 (Academic Press, 2009).
Berke, J. D. What does dopamine mean? Nat. Neurosci. 21, 787–793 (2018).
Berridge, K. C. & Robinson, T. E. What is the role of dopamine in reward: hedonic impact, reward learning, or incentive salience? Brain Res. Rev. 28, 309–369 (1998).
Schultz, W., Carelli, R. M. & Wightman, R. M. Phasic dopamine signals: from subjective reward value to formal economic utility. Curr. Opin. Behav. Sci. 5, 147–154 (2015).
Salamone, J. D., Correa, M., Farrar, A. & Mingote, S. M. Effort-related functions of nucleus accumbens dopamine and associated forebrain circuits. Psychopharmacology 191, 461–482 (2007).
Wise, R. A. Dopamine, learning and motivation. Nat. Rev. Neurosci. 5, 483–494 (2004).
McClure, S. M., Laibson, D. I., Loewenstein, G. & Cohen, J. D. Separate neural systems value immediate and delayed monetary rewards. Science 306, 503–507 (2004).
Wittmann, M., Leland, D. S. & Paulus, M. P. Time and decision making: differential contribution of the posterior insular cortex and the striatum during a delay discounting task. Exp. Brain Res. 179, 643–653 (2007).
Gregorios-Pippas, L., Tobler, P. N. & Schultz, W. Short term temporal discounting of reward value in human ventral striatum. J. Neurophysiol. 101, 1507–1523 (2009).
Kable, J. W. & Glimcher, P. W. The neural correlates of subjective value during intertemporal choice. Nat. Neurosci. 10, 1625–1633 (2007).
Peters, J. & Büchel, C. Overlapping and distinct neural systems code for subjective value during intertemporal and risky decision making. J. Neurosci. 29, 15727–15734 (2009).
Prévost, C., Pessiglione, M., Météreau, E., Cléry-Melin, M.-L. & Dreher, J.-C. Separate valuation subsystems for delay and effort decision costs. J. Neurosci. 30, 14080–14090 (2010).
Abler, B., Walter, H., Erk, S., Kammerer, H. & Spitzer, M. Prediction error as a linear function of reward probability is coded in human nucleus accumbens. Neuroimage 31, 790–795 (2006).
Yacubian, J. et al. Dissociable systems for gain-and loss-related value predictions and errors of prediction in the human brain. J. Neurosci. 26, 9530–9537 (2006).
Levy, D. J. & Glimcher, P. W. The root of all value: a neural common currency for choice. Curr. Opin. Neurobiol. 22, 1027–1038 (2012).
Croxson, P. L., Walton, M. E., O’Reilly, J. X., Behrens, T. E. & Rushworth, M. F. Effort-based cost–benefit valuation and the human brain. J. Neurosci. 29, 4531–4541 (2009).
Kurniawan, I. T. et al. Choosing to make an effort: the role of striatum in signaling physical effort of a chosen action. J. Neurophysiol. 104, 313–321 (2010).
Schmidt, L., Lebreton, M., Cléry-Melin, M.-L., Daunizeau, J. & Pessiglione, M. Neural mechanisms underlying motivation of mental versus physical effort. PLoS Biol. 10, e1001266 (2012).
Burke, C. J., Brünger, C., Kahnt, T., Park, S. Q. & Tobler, P. N. Neural integration of risk and effort costs by the frontal pole: only upon request. J. Neurosci. 33, 1706–1713 (2013).
Kurniawan, I. T., Guitart-Masip, M., Dayan, P. & Dolan, R. J. Effort and valuation in the brain: the effects of anticipation and execution. J. Neurosci. 33, 6160–6169 (2013).
Skvortsova, V., Palminteri, S. & Pessiglione, M. Learning to minimize efforts versus maximizing rewards: computational principles and neural correlates. J. Neurosci. 34, 15621–15630 (2014).
Massar, S. A., Libedinsky, C., Weiyan, C., Huettel, S. A. & Chee, M. W. Separate and overlapping brain areas encode subjective value during delay and effort discounting. Neuroimage 120, 104–113 (2015).
Scholl, J. et al. The good, the bad, and the irrelevant: neural mechanisms of learning real and hypothetical rewards and effort. J. Neurosci. 35, 11233–11251 (2015).
Bonnelle, V., Manohar, S., Behrens, T. & Husain, M. Individual differences in premotor brain systems underlie behavioral apathy. Cereb. Cortex 26, 807–819 (2015).
Klein-Flügge, M. C., Kennerley, S. W., Friston, K. & Bestmann, S. Neural signatures of value comparison in human cingulate cortex during decisions requiring an effort-reward trade-off. J. Neurosci. 36, 10002–10015 (2016).
Chong, T. T.-J. et al. Neurocomputational mechanisms underlying subjective valuation of effort costs. PLoS Biol. 15, e1002598 (2017).
Hauser, T. U., Eldar, E. & Dolan, R. J. Separate mesocortical and mesolimbic pathways encode effort and reward learning signals. Proc. Natl Acad. Sci. USA 114, E7395–E7404 (2017).
Arulpragasam, A. R., Cooper, J. A., Nuutinen, M. R. & Treadway, M. T. Corticoinsular circuits encode subjective value expectation and violation for effortful goal-directed behavior. Proc. Natl Acad. Sci. USA 115, E5233–E5242 (2018).
Aridan, N., Malecek, N. J., Poldrack, R. A. & Schonberg, T. Neural correlates of effort-based valuation with prospective choices. Neuroimage 185, 446–454 (2019).
Endepols, H. et al. Effort-based decision making in the rat: an [18F]fluorodeoxyglucose micro positron emission tomography study. J. Neurosci. 30, 9708–9714 (2010).
Cousins, M. S. & Salamone, J. D. Nucleus accumbens dopamine depletions in rats affect relative response allocation in a novel cost/benefit procedure. Pharmacol. Biochem. Behav. 49, 85–91 (1994).
Floresco, S. B. The nucleus accumbens: an interface between cognition, emotion, and action. Annu. Rev. Psychol. 66, 25–52 (2015).
da Silva, J. A., Tecuapetla, F., Paixão, V. & Costa, R. M. Dopamine neuron activity before action initiation gates and invigorates future movements. Nature 554, 244–248 (2018).
Day, J. J., Jones, J. L., Wightman, R. M. & Carelli, R. M. Phasic nucleus accumbens dopamine release encodes effort-and delay-related costs. Biol. Psychiatry 68, 306–309 (2010).
Hamid, A. A. et al. Mesolimbic dopamine signals the value of work. Nat. Neurosci. 19, 117–126 (2016).
Syed, E. C. et al. Action initiation shapes mesolimbic dopamine encoding of future rewards. Nat. Neurosci. 19, 34–39 (2016).
Lau, B. & Glimcher, P. W. Action and outcome encoding in the primate caudate nucleus. J. Neurosci. 27, 14502–14514 (2007).
Samejima, K., Ueda, Y., Doya, K. & Kimura, M. Representation of action-specific reward values in the striatum. Science 310, 1337–1340 (2005).
Zaborszky, L. et al. Cholecystokinin innervation of the ventral striatum: a morphological and radioimmunological study. Neuroscience 14, 427–453 (1985).
Penner, M. R. & Mizumori, S. J. Neural systems analysis of decision making during goal-directed navigation. Prog. Neurobiol. 96, 96–135 (2012).
Di Chiara, G. et al. Dopamine and drug addiction: the nucleus accumbens shell connection. Neuropharmacology 47, 227–241 (2004).
Van Der Plasse, G., Schrama, R., Van Seters, S. P., Vanderschuren, L. J. & Westenberg, H. G. Deep brain stimulation reveals a dissociation of consummatory and motivated behaviour in the medial and lateral nucleus accumbens shell of the rat. PLoS ONE 7, e33455 (2012).
Parkinson, J. A., Willoughby, P. J., Robbins, T. W. & Everitt, B. J. Disconnection of the anterior cingulate cortex and nucleus accumbens core impairs Pavlovian approach behavior: further evidence for limbic cortical–ventral striatopallidal systems. Behav. Neurosci. 114, 42–63 (2000).
Ko, D. & Wanat, M. J. Phasic dopamine transmission reflects initiation vigor and exerted effort in an action-and region-specific manner. J. Neurosci. 36, 2202–2211 (2016).
Choi, E. Y., Yeo, B. T. & Buckner, R. L. The organization of the human striatum estimated by intrinsic functional connectivity. J. Neurophysiol. 108, 2242–2263 (2012).
Haber, S. N. & Knutson, B. The reward circuit: linking primate anatomy and human imaging. Neuropsychopharmacology 35, 4–26 (2010).
Haber, S. N., Kim, K.-S., Mailly, P. & Calzavara, R. Reward-related cortical inputs define a large striatal region in primates that interface with associative cortical connections, providing a substrate for incentive-based learning. J. Neurosci. 26, 8368–8376 (2006).
Engelhard, B. et al. Specialized coding of sensory, motor and cognitive variables in VTA dopamine neurons. Nature 570, 509–513 (2019).
Gorgolewski, K. J. et al. A high resolution 7-Tesla resting-state fMRI test-retest dataset with cognitive and physiological measures. Sci. Data 2, 140054 (2015).
Howe, M. W., Tierney, P. L., Sandberg, S. G., Phillips, P. E. & Graybiel, A. M. Prolonged dopamine signalling in striatum signals proximity and value of distant rewards. Nature 500, 575–579 (2013).
Roesch, M. R., Singh, T., Brown, P. L., Mullins, S. E. & Schoenbaum, G. Ventral striatal neurons encode the value of the chosen action in rats deciding between differently delayed or sized rewards. J. Neurosci. 29, 13365–13376 (2009).
Hall, J., Parkinson, J. A., Connor, T. M., Dickinson, A. & Everitt, B. J. Involvement of the central nucleus of the amygdala and nucleus accumbens core in mediating Pavlovian influences on instrumental behaviour. Eur. J. Neurosci. 13, 1984–1992 (2001).
Sonkusare, S., Breakspear, M. & Guo, C. Naturalistic stimuli in neuroscience: critically acclaimed. Trends Cogn. Sci. 23, 699–714 (2019).
Van Essen, D. C. et al. The WU-Minn human connectome project: an overview. Neuroimage 80, 62–79 (2013).
Esterman, M., Tamber-Rosenau, B. J., Chiu, Y.-C. & Yantis, S. Avoiding non-independence in fMRI data analysis: leave one subject out. Neuroimage 50, 572–576 (2010).
Pedregosa, F. et al. Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825–2830 (2011).
Ojala, M. & Garriga, G. C. Permutation tests for studying classifier performance. J. Mach. Learn. Res. 11, 1833–1863 (2010).
This work was supported by funding from the NIMH R00 MH102355 and R01 MH108605 to M.T.T. and F32 MH115692 to J.A.C. and the National Science Foundation Graduate Research Fellowship Program DGE- 1444932 to A.R.A. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. We thank J. Buckholtz and D. Dilks for helpful discussion and commentary. We also thank B. DeVries, M. Nuutinen, E. Hahn, D. Harrison, A. Lu, M. Rehman, J. Yang, K. Kwok, S. Han and N. Ahad for their assistance in data collection.
The authors report no conflicts of interest, financial or otherwise. In the past three years, M.T.T. has served as a paid consultant to Blackthorn Therapeutics and Avanir Pharmaceuticals. None of these entities supported the current work, and all views expressed herein are solely those of the authors.
Peer review information Primary Handling Editor: Jamie Horder.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Suzuki, S., Lawlor, V.M., Cooper, J.A. et al. Distinct regions of the striatum underlying effort, movement initiation and effort discounting. Nat Hum Behav 5, 378–388 (2021). https://doi.org/10.1038/s41562-020-00972-y
This article is cited by
Nature Reviews Psychology (2022)
Molecular Psychiatry (2022)