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Residual Effects of Cannabis Use on Effort-Based Decision-Making

Published online by Cambridge University Press:  15 July 2021

Mackenzie B. Taylor Open the ORCID record for Mackenzie B. Taylor [Opens in a new window]  and
Francesca M. Filbey
Mackenzie B. Taylor
Affiliation:
Center for BrainHealth, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, USA
Francesca M. Filbey*
Affiliation:
Center for BrainHealth, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, USA
*
Correspondence and reprint requests to: Francesca M. Filbey, PhD, Center for Brain Health, School of Behavioral and Brain Sciences, The University of Texas at Dallas, 2200 West Mockingbird, Dallas, TX75235, USA. Email: Francesca.Filbey@utdallas.edu
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Abstract

Objective:

Acute Δ9-tetrahydrocannabinol (THC) administration in humans (Lawn etal., 2016) and rats (Silveira, Adams, Morena, Hill, & Winstanley, 2016) has been associated with decreased effort allocation that may explain amotivation during acute cannabis intoxication. To date, however, whether residual effects of cannabis use on effort-based decision-making are present and observable in humans have not yet been determined. The goal of this study was to test whether prolonged cannabis use has residual effects on effort-based decision-making in 24-hr abstinent cannabis using adults.

Method:

We evaluated performance on the Effort Expenditure for Reward Task (EEfRT) in 41 adult cannabis users (mean age = 24.63 years, 21 males) and 45 nonusers (mean age = 23.90 years, 19 males). A mixed 2x3x3 ANOVA with age as a covariate was performed to examine the effect of group, probability of winning, and reward amount on EEfRT performance. EEfRT performance was operationalized as % of trials for which the hard (vs. easy) condition was chosen. Pearson’s correlations were conducted to test the relationship between EEfRT performance and measures of cannabis use, anhedonia and motivation.

Results:

We found that cannabis users selected hard trials significantly more than nonusers regardless of win probability or reward level. Frequency of cannabis use was positively correlated with amount of % hard trials chosen. There were no significant correlations between % hard trials chosen, self-reported anhedonia, or motivation.

Conclusions:

These results suggest that unlike acute effects, residual effects of cannabis following 24 hrs of abstinence are associated with greater effort allocation during effort-based decision-making.

Keywords

Decision-makingPhysical effortMotivationExecutive functionCannabis use disorderAddictive behavior
Type
Regular Research
Information
Journal of the International Neuropsychological Society , Volume 27 , Special Issue 6: Clarifying the Complexities of Cannabis and Cognition , July 2021 , pp. 559 - 569
Copyright
Copyright © INS. Published by Cambridge University Press, 2021

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References

REFERENCES

Bailey, A.J., Gerst, K., & Finn, P.R. (2020). Intelligence moderates the relationship between delay discounting rate and problematic alcohol use. Psychology of Addictive Behaviors, 34(1), 175–181. https://doi.org/10.1037/adb0000471 CrossRefGoogle ScholarPubMed
Barch, D.M., Pagliaccio, D., & Luking, K.R. (2018). Motivational Impairments in psychotic and depressive pathology: Psychological and neural mechanisms. Neurobiology of Abnormal Emotion and Motivated Behaviors, 123, 278–304.CrossRefGoogle Scholar
Barch, D.M., Treadway, M.T., & Schoen, N. (2014). Effort, anhedonia, and function in schizophrenia: Reduced effort allocation predicts amotivation and functional impairment. Journal of Abnormal Psychology, 123(2), 387–397. https://doi.org/10.1037/a0036299 CrossRefGoogle ScholarPubMed
Beck, A.T., Epstein, N., Brown, G., & Steer, R.A. (1988). An inventory for measuring clinical anxiety: Psychometric properties. Journal of Consulting and Clinical Psychology, 56(6), 893–897. https://doi.org/10.1037//0022-006x.56.6.893 CrossRefGoogle ScholarPubMed
Beck, A.T., Ward, C.H., Mendelson, M., Mock, J., & Erbaugh, J. (1961). An inventory for measuring depression. Archives of General Psychiatry, 4, 561–571. https://doi.org/10.1001/archpsyc.1961.01710120031004 CrossRefGoogle ScholarPubMed
Behan, B., Connolly, C.G., Datwani, S., Doucet, M., Ivanovic, J., Morioka, R., … Garavan, H. (2014). Response inhibition and elevated parietal-cerebellar correlations in chronic adolescent cannabis users. Neuropharmacology, 84, 131–137. https://doi.org/10.1016/j.neuropharm.2013.05.027 CrossRefGoogle ScholarPubMed
Berridge, K.C. (2012). From prediction error to incentive salience: Mesolimbic computation of reward motivation. European Journal of Neuroscience, 35(7), 1124–1143. https://doi.org/10.1111/j.1460-9568.2012.07990.x CrossRefGoogle ScholarPubMed
Białaszek, W., Marcowski, P., & Ostaszewski, P. (2017). Physical and cognitive effort discounting across different reward magnitudes: Tests of discounting models. PLoS One, 12(7), e0182353. https://doi.org/10.1371/journal.pone.0182353 CrossRefGoogle ScholarPubMed
Bloomfield, M.A., Ashok, A.H., Volkow, N.D., & Howes, O.D. (2016). The effects of Delta(9)-tetrahydrocannabinol on the dopamine system. Nature, 539(7629), 369–377. doi: 10.1038/nature20153 CrossRefGoogle ScholarPubMed
Bond, A., & Lader, M. (1974). The use of analogue scales in rating subjective feelings. British Journal of Medical Psychology, 47(3), 211–218. https://doi.org/10.1111/j.2044-8341.1974.tb02285.x CrossRefGoogle Scholar
Byrne, K.A., & Ghaiumy Anaraky, R. (2019). Strive to win or not to lose? Age-related differences in framing effects on effort-based decision-making. The Journals of Gerontology: Series B. 75(10), 2095–2105. https://doi.org/10.1093/geronb/gbz136 CrossRefGoogle Scholar
Carver, C. S., & White, T. L. (1994). Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: The BIS/BAS scales. Journal of Personality and Social Psychology, 67(2), 319–333.CrossRefGoogle Scholar
Casey, J.L., & Cservenka, A. (2020). Effects of frequent marijuana use on risky decision-making in young adult college students. Addictive Behaviors Reports, 100253. https://doi.org/10.1016/j.abrep.2020.100253 CrossRefGoogle ScholarPubMed
Chang, W.C., Chu, A.O.K., Treadway, M.T., Strauss, G.P., Chan, S.K.W., Lee, E.H.M., … Chen, E.Y.H. (2019). Effort-based decision-making impairment in patients with clinically-stabilized first-episode psychosis and its relationship with amotivation and psychosocial functioning. European Neuropsychopharmacology, 29(5), 629–642. https://doi.org/10.1016/j.euroneuro.2019.03.006 CrossRefGoogle ScholarPubMed
Clithero, J.A. (2011). Neuroeconomics of Reward Information and Motivation (Ph.D., Duke University). Duke University, United States -- North Carolina. Retrieved from https://search.proquest.com/docview/874146592/abstract/66A6B01DD2684A3EPQ/1 Google Scholar
Cohen, J. (1957). A factor-analytically based rationale for the Wechsler Adult Intelligence Scale. Journal of Consulting Psychology, 21(6), 451–457. https://doi.org/10.1037/h0044203 CrossRefGoogle ScholarPubMed
Cousijn, J., Wiers, R.W., Ridderinkhof, K.R., Brink, W.vanden, Veltman, D.J., Porrino, L.J., & Goudriaan, A.E. (2012). Individual differences in decision making and reward processing predict changes in cannabis use: A prospective functional magnetic resonance imaging study. Addiction Biology, 18(6), 1013–1023. https://doi.org/10.1111/j.1369-1600.2012.00498.x CrossRefGoogle ScholarPubMed
Cousijn, J., Wiers, R.W., Ridderinkhof, K.R., van den Brink, W., Veltman, D.J., & Goudriaan, A.E. (2014). Effect of baseline cannabis use and working-memory network function on changes in cannabis use in heavy cannabis users: A prospective fMRI study. Human Brain Mapping, 35(5), 2470–2482. https://doi.org/10.1002/hbm.22342 CrossRefGoogle ScholarPubMed
Culbreth, A.J., Moran, E.K., & Barch, D.M. (2018). Effort-cost decision-making in psychosis and depression: Could a similar behavioral deficit arise from disparate psychological and neural mechanisms? Psychological Medicine, 48(6), 889–904. https://doi.org/10.1017/S0033291717002525 CrossRefGoogle ScholarPubMed
Deci, E. L., & Ryan, R. M. (1985). The general causality orientations scale: Self-Determination in personality. Journal of Research in Personality, 19,109–134.CrossRefGoogle Scholar
Fatahi, Z., Zeinaddini-Meymand, A., Karimi-Haghighi, S., Moradi, M., Khodagholi, F., & Haghparast, A. (2020). Naloxone-precipitated withdrawal ameliorates impairment of cost-benefit decision making in morphine-treated rats: Involvement of BDNF, p-GSK3-β, and p-CREB in the amygdala. Neurobiology of Learning and Memory, 167, 107138. https://doi.org/10.1016/j.nlm.2019.107138 CrossRefGoogle ScholarPubMed
Fatima, H., Howlett, A.C., & Whitlow, C.T. (2019). Reward, Control & Decision-Making in Cannabis Use Disorder: Insights from Functional MRI. The British Journal of Radiology, 92(1101), 20190165. https://doi.org/10.1259/bjr.20190165 CrossRefGoogle ScholarPubMed
Figueiredo, P.R., Tolomeo, S., Steele, J.D., & Baldacchino, A. (2020). Neurocognitive consequences of chronic cannabis use: A systematic review and meta-analysis. Neuroscience and Biobehavioral Reviews, 108, 358–369. https://doi.org/10.1016/j.neubiorev.2019.10.014 CrossRefGoogle ScholarPubMed
Filbey, F.M., Dunlop, J., Ketcherside, A., Baine, J., Rhinehardt, T., Kuhn, B., … Alvi, T. (2016). FMRI study of neural sensitization to hedonic stimuli in long-term, daily cannabis users. Human Brain Mapping, 37(10), 3431–3443. https://doi.org/10.1002/hbm.23250 CrossRefGoogle Scholar
Fridberg, D.J., Queller, S., Ahn, W.-Y., Kim, W., Bishara, A.J., Busemeyer, J.R., … Stout, J.C. (2010). Cognitive mechanisms underlying risky decision-making in chronic cannabis users. Journal of Mathematical Psychology, 54(1), 28–38. https://doi.org/10.1016/j.jmp.2009.10.002 CrossRefGoogle ScholarPubMed
Gonzalez, R. (2007). Acute and non-acute effects of cannabis on brain functioning and neuropsychological performance. Neuropsychology Review, 17(3), 347–361. https://doi.org/10.1007/s11065-007-9036-8 CrossRefGoogle ScholarPubMed
Grant, I., Gonzalez, R., Carey, C.L., Natarajan, L., & Wolfson, T. (2003). Non-acute (residual) neurocognitive effects of cannabis use: A meta-analytic study. Journal of the International Neuropsychological Society, 9(5), 679–689. https://doi.org/10.1017/S1355617703950016 CrossRefGoogle ScholarPubMed
Green, L., & Myerson, J. (2013). How many impulsivities? A discounting perspective. Journal of the Experimental Analysis of Behavior, 99(1), 3–13. https://doi.org/10.1002/jeab.1 CrossRefGoogle ScholarPubMed
Grodin, E.N., Steckler, L.E., & Momenan, R. (2016). Altered striatal response during effort-based valuation and motivation in alcohol-dependent individuals. Alcohol and Alcoholism, 51(6), 638–646. https://doi.org/10.1093/alcalc/agw003 CrossRefGoogle ScholarPubMed
Hammond, C.J., Chaney, A., Hendrickson, B., & Sharma, P. (2020). Cannabis use among U.S. adolescents in the era of marijuana legalization: A review of changing use patterns, comorbidity, and health correlates. International Review of Psychiatry, 32(3), 221–234. https://doi.org/10.1080/09540261.2020.1713056 CrossRefGoogle ScholarPubMed
Hayley, A.C., Stough, C., & Downey, L.A. (2017). DSM-5 cannabis use disorder, substance use and DSM-5 specific substance-use disorders: Evaluating comorbidity in a population-based sample. European Neuropsychopharmacology, 27(8), 732–743. https://doi.org/10.1016/j.euroneuro.2017.06.004 CrossRefGoogle Scholar
Imhoff, S., Harris, M., Weiser, J., & Reynolds, B. (2014). Delay discounting by depressed and non-depressed adolescent smokers and non-smokers. Drug and Alcohol Dependence, 135, 152–155. https://doi.org/10.1016/j.drugalcdep.2013.11.014 CrossRefGoogle ScholarPubMed
Johnson, S.L., Swerdlow, B.A., Treadway, M., Tharp, J.A., & Carver, C.S. (2017). Willingness to expend effort toward reward and extreme ambitions in Bipolar I disorder. Clinical Psychological Science, 5(6), 943–951. https://doi.org/10.1177/2167702617718181 CrossRefGoogle Scholar
Lawn, W., Freeman, T.P., Pope, R.A., Joye, A., Harvey, L., Hindocha, C., … Curran, H.V. (2016). Acute and chronic effects of cannabinoids on effort-related decision-making and reward learning: An evaluation of the cannabis ‘amotivational’ hypotheses. Psychopharmacology, 233(19), 3537–3552. https://doi.org/10.1007/s00213-016-4383-x CrossRefGoogle ScholarPubMed
Lee, J.Y., Brook, J.S., & Kim, W. (2018). Triple trajectories of alcohol use, tobacco use, and depressive symptoms as predictors of cannabis use disorders among urban adults. Psychology of Addictive Behaviors: Journal of the Society of Psychologists in Addictive Behaviors, 32(4), 466–474. https://doi.org/10.1037/adb0000373 CrossRefGoogle ScholarPubMed
Massar, S.A.A., Csathó, Á., & Van der Linden, D. (2018). Quantifying the motivational effects of cognitive fatigue through effort-based decision making. Frontiers in Psychology, 9. https://doi.org/10.3389/fpsyg.2018.00843 CrossRefGoogle ScholarPubMed
Massar, S.A.A., Libedinsky, C., Weiyan, C., Huettel, S.A., & Chee, M.W.L. (2015). Separate and overlapping brain areas encode subjective value during delay and effort discounting. NeuroImage, 120, 104–113. https://doi.org/10.1016/j.neuroimage.2015.06.080 CrossRefGoogle ScholarPubMed
McCarthy, J.M., Treadway, M.T., & Blanchard, J.J. (2015). Motivation and effort in individuals with social anhedonia. Schizophrenia Research, 165(1), 70–75. https://doi.org/10.1016/j.schres.2015.03.030 CrossRefGoogle ScholarPubMed
Meier, M.H., & White, M. (2018). Do young-adult cannabis users show amotivation? An analysis of informant reports. Translational Issues in Psychological Science, 4(1), 99–107. https://doi.org/10.1037/tps0000150 CrossRefGoogle Scholar
Mosner, M.G., Kinard, J.L., McWeeny, S., Shah, J.S., Markiewitz, N.D., Damiano-Goodwin, C.R., … Dichter, G.S. (2017). Vicarious effort-based decision-making in autism spectrum disorders. Journal of Autism and Developmental Disorders, 47(10), 2992–3006. https://doi.org/10.1007/s10803-017-3220-3 CrossRefGoogle ScholarPubMed
Oleson, E.B., & Cheer, J.F. (2012). A brain on cannabinoids: The role of dopamine release in reward seeking. Cold Spring Harbor Perspectives in Medicine, 2(8). https://doi.org/10.1101/cshperspect.a012229 CrossRefGoogle ScholarPubMed
Oudeyer, P.-Y., & Kaplan, F. (2009). What is intrinsic motivation? A typology of computational approaches. Frontiers in Neurorobotics, 1. https://doi.org/10.3389/neuro.12.006.2007 Google Scholar
Pacheco-Colón, I., Coxe, S., Musser, E.D., Duperrouzel, J.C., Ross, J.M., & Gonzalez, R. (2018). Is cannabis use associated with various indices of motivation among adolescents? Substance Use & Misuse, 53(7), 1158–1169. https://doi.org/10.1080/10826084.2017.1400566 CrossRefGoogle ScholarPubMed
Pacheco-Colón, I., Ramirez, A.R., & Gonzalez, R. (2019). Effects of adolescent cannabis use on motivation and depression: A systematic review. Current Addiction Reports, 6(4), 532–546. https://doi.org/10.1007/s40429-019-00274-y CrossRefGoogle ScholarPubMed
Pulcu, E., Trotter, P.D., Thomas, E.J., McFarquhar, M., Juhasz, G., Sahakian, B.J., … Elliott, R. (2014). Temporal discounting in major depressive disorder. Psychological Medicine, 44(9), 1825–1834. https://doi.org/10.1017/S0033291713002584 CrossRefGoogle ScholarPubMed
Reddy, L.F., Horan, W.P., Barch, D.M., Buchanan, R.W., Dunayevich, E., Gold, J.M., … Green, M.F. (2015). Effort-based decision-making paradigms for clinical trials in schizophrenia: Part 1—Psychometric characteristics of 5 paradigms. Schizophrenia Bulletin, 41(5), 1045–1054. https://doi.org/10.1093/schbul/sbv089 CrossRefGoogle ScholarPubMed
Robinson, S.M., Sobell, L.C., Sobell, M.B., & Leo, G.I. (2014). Reliability of the timeline followback for cocaine, cannabis, and cigarette use. Psychology of Addictive Behaviors, 28(1), 154–162. https://doi.org/10.1037/a0030992 CrossRefGoogle ScholarPubMed
Schmidt, L., Lebreton, M., Cléry-Melin, M.-L., Daunizeau, J., & Pessiglione, M. (2012). Neural mechanisms underlying motivation of mental versus physical effort. PLoS Biology, 10(2). https://doi.org/10.1371/journal.pbio.1001266 CrossRefGoogle ScholarPubMed
Shamosh, N.A., & Gray, J.R. (2008). Delay discounting and intelligence: A meta-analysis. Intelligence, 36(4), 289–305. https://doi.org/10.1016/j.intell.2007.09.004 CrossRefGoogle Scholar
Sheehan, D.V., Lecrubier, Y., Sheehan, K.H., Amorim, P., Janavs, J., Weiller, E., … Dunbar, G.C. (1998). The Mini-International Neuropsychiatric Interview (M.I.N.I.): The development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. The Journal of Clinical Psychiatry, 59(Suppl 20), 22–33;quiz 34–57.Google ScholarPubMed
Silveira, M.M., Adams, W.K., Morena, M., Hill, M.N., & Winstanley, C.A. (2016). Δ9-Tetrahydrocannabinol decreases willingness to exert cognitive effort in male rats. Journal of Psychiatry & Neuroscience: JPN, 41(6), 150363.Google ScholarPubMed
Snaith, R. P., Hamilton, M., Morley, S., Humayan, A., Hargreaves, D., & Trigwell, P. (1995). A scale for the assessment of hedonic tone the Snaith-Hamilton Pleasure Scale. The British Journal of Psychiatry: The Journal of Mental Science, 167(1), 99–103. https://doi.org/10.1192/bjp.167.1.99 CrossRefGoogle ScholarPubMed
Solowij, N., Stephens, R.S., Roffman, R.A., Babor, T., Kadden, R., Miller, M., … Vendetti, J. (2002). Cognitive functioning of long-term heavy cannabis users seeking treatment. JAMA, 287(9), 1123–1131. https://doi.org/10.1001/jama.287.9.1123 CrossRefGoogle ScholarPubMed
Treadway, M.T., Bossaller, N., Shelton, R.C., & Zald, D.H. (2012). Effort-based decision-making in major depressive disorder: A translational model of motivational anhedonia. Journal of Abnormal Psychology, 121(3), 553–558. https://doi.org/10.1037/a0028813 CrossRefGoogle ScholarPubMed
Treadway, M.T., Buckholtz, J.W., Schwartzman, A.N., Lambert, W.E., & Zald, D.H. (2009). Worth the ‘EEfRT’? The effort expenditure for rewards task as an objective measure of motivation and anhedonia. PLoS ONE, 4(8), e6598. https://doi.org/10.1371/journal.pone.0006598 CrossRefGoogle ScholarPubMed
Treadway, M.T., Peterman, J.S., Zald, D.H., & Park, S. (2015). Impaired effort allocation in patients with schizophrenia. Schizophrenia Research, 161(2), 382–385. https://doi.org/10.1016/j.schres.2014.11.024 CrossRefGoogle ScholarPubMed
Vaidya, J.G., Block, R.I., O’Leary, D.S., Ponto, L.B., Ghoneim, M.M., & Bechara, A. (2012). Effects of chronic marijuana use on brain activity during monetary decision-making. Neuropsychopharmacology, 37(3), 618–629. https://doi.org/10.1038/npp.2011.227 CrossRefGoogle ScholarPubMed
van Leeuwen, A.P., Creemers, H.E., Verhulst, F.C., Ormel, J., & Huizink, A.C. (2011). Are adolescents gambling with cannabis use? A longitudinal study of impulsivity measures and adolescent substance use: The TRAILS study. Journal of Studies on Alcohol and Drugs, 72(1), 70–78. https://doi.org/10.15288/jsad.2011.72.70 CrossRefGoogle Scholar
Vingerhoets, W., Koenders, L., van den Brink, W., Wiers, R., Goudriaan, A., van Amelsvoort, T., … Cousijn, J. (2016). Cue-induced striatal activity in frequent cannabis users independently predicts cannabis problem severity three years later. Journal of Psychopharmacology, 30(2), 152–158. https://doi.org/10.1177/0269881115620436 CrossRefGoogle ScholarPubMed
Vlachou, S., & Panagis, G. (2014). Regulation of brain reward by the endocannabinoid system: A critical review of behavioral studies in animals. Current Pharmaceutical Design, 20(13), 2072–2088. https://doi.org/10.2174/13816128113199990433 CrossRefGoogle ScholarPubMed
Wrege, J., Schmidt, A., Walter, A., Smieskova, R., Bendfeldt, K., Radue, E.-W., … Borgwardt, S. (2014). Effects of cannabis on impulsivity: A systematic review of neuroimaging findings. Current Pharmaceutical Design, 20(13), 2126–2137.CrossRefGoogle ScholarPubMed
Zilverstand, A., Huang, A.S., Alia-Klein, N., & Goldstein, R.Z. (2018). Neuroimaging impaired response inhibition and salience attribution in human drug addiction: A systematic review. Neuron, 98(5), 886–903. https://doi.org/10.1016/j.neuron.2018.03.048 CrossRefGoogle ScholarPubMed
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