An influential neurocomputational theory of the biological mechanisms of decision making, the “basal ganglia go/no-go model,” holds that individual variability in decision making is determined by differences in the makeup of a striatal system for approach and avoidance learning. The model has been tested empirically with the probabilistic selection task (PST), which determines whether individuals learn better from positive or negative feedback. In accordance with the model, in the present study we examined whether an individual’s ability to learn from positive and negative reinforcement can be predicted by genetic factors related to the midbrain dopamine system. We also asked whether psychiatric and personality factors related to substance dependence and dopamine affect PST performance. Although we found characteristics that predicted individual differences in approach versus avoidance learning, these observations were qualified by additional findings that appear inconsistent with the predictions of the go/no-go model. These results highlight a need for future research to validate the PST as a measure of basal ganglia reward learning.
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We also collected data for a gene that regulates the expression of the catechol-O-methyltransferase (COMT) enzyme, the primary mechanism for dopamine inactivation in prefrontal cortex, but these data were not analyzed.
Because the PPP1R1B polymorphisms displayed no deviation from Hardy–Weinberg equilibrium when minority subgroups were excluded, we used only data from Caucasians for this genetic association analysis.
Following Baker and colleagues (2011), we also examined test phase accuracy by running separate ANOVAs on negative or positive learners by dependence group. A significant interaction was detected for positive learners, F(3, 158) = 3.3, p < .05, but not for negative learners. Post hoc analysis indicated that positive learners tended to choose the good stimulus about equally often across groups, p > .05, but ND participants tended to avoid choosing the bad stimulus more often (66 %) than did the SDTx (57 %, p < .05), MD (56 %, p < .05), and SD (58 %, p = .07) participants. However, this result was not statistically significant following the B–H correction (p < .025).
A two-way ANOVA with repeated measures on PST accuracy and reaction time with Time (Time 1, Time 2), Test Condition (approach, avoid), and Dependence Group (SDTx, SD, MD, ND) as factors revealed only a main effect of group, F(1, 105) = 8.5, p < .005. No other main effects or interactions were detected.
Antonucci, A. S., Gansler, D. A., Tan, S., Bhadelia, R., Patz, S., & Fulwiler, C. (2006). Orbitofrontal correlates of aggression and impulsivity in psychiatric patients. Psychiatry Research, 147, 213–220.
Baker, T. E., Stockwell, T., Barnes, G., Haesevoets, R., Macleod, P., & Holroyd, C. B. (2010). Genetics, drugs, and cognitive control: Individual differences underlying substance dependence. Poster presented at the Symposium on. Oxford, UK: Motivational & Cognitive Control.
Baker, T. E., Stockwell, T., Barnes, G., & Holroyd, C. B. (2011). Individual differences in substance dependence: At the intersection of brain, behaviour and cognition. Addiction Biology, 16, 458–466.
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society, Series B, 57, 289–300.
Beste, C., Saft, C., Andrich, J., Gold, R., & Falkenstein, M. (2006). Error processing in Huntington’s disease. PLoS One, 1, e86. doi:10.1371/journal.pone.0000086
Bilder, R. M., Volavka, J., Lachman, H. M., & Grace, A. A. (2004). The catechol-O-methyltransferase polymorphism: Relations to the tonic-phasic dopamine hypothesis and neuropsychiatric phenotypes. Neuropsychopharmacology, 29, 1943–1961.
Bornovalova, M. A., Cashman-Rolls, A., O’Donnell, J. M., Ettinger, K., Richards, J. B., deWit, H., & Lejuez, C. W. (2009). Risk taking differences on a behavioral task as a function of potential reward/loss magnitude and individual differences in impulsivity and sensation seeking. Pharmacology Biochemistry and Behavior, 93, 258–262. doi:10.1016/j.pbb.2008.10.023
Calabresi, P., Gubellini, P., Centonze, D., Picconi, B., Bernardi, G., Chergui, K., . . . Greengard, P. (2000). Dopamine and cAMP-regulated phosphoprotein 32 kDa controls both striatal long-term depression and long-term potentiation, opposing forms of synaptic plasticity. Journal of Neuroscience, 20, 8443–8451.
Cavanagh, J. F., Bismark, A. J., Frank, M. J., & Allen, J. J. (2011). Larger error signals in major depression are associated with better avoidance learning. Frontiers in Cognition, 2, 331. doi:10.3389/fpsyg.2011.00331
Chase, H. W., Frank, M. J., Michael, A., Bullmore, E. T., Sahakian, B. J., & Robbins, T. W. (2010). Approach and avoidance learning in patients with major depression and healthy controls: Relation to anhedonia. Psychological Medicine, 40, 433–440.
Chiew, K. S., & Braver, T. S. (2011). Monetary incentives improve performance, sometimes: Speed and accuracy matter, and so might preparation. Frontiers in Cognition, 2, 325. doi:10.3389/fpsyg.2011.00325
Cloninger, C. R., Svrakic, D. M., & Przybeck, T. R. (1993). A psychobiological model of temperament and character. Archives of General Psychiatry, 50, 975–990.
Cockburn, J., & Frank, M.J. (2011). Reinforcement learning, conflict monitoring, and cognitive control: An integrative model of cingulate-striatal interactions and the ERN. R. Mars, J. Sallet, M. Rushworth & N. Yeung (Eds.), Neural Basis of Motivational and Cognitive Control (311–331). Cambridge: The MIT Press.
Cohen, M. X., & Frank, M. J. (2008). Neurocomputational models of basal ganglia function in learning, memory and choice. Behavioural Brain Research, 199, 141–156.
Conrod, P. J., & Woicik, P. (2002). Validation of a four-factor model of personality risk for substance abuse and examination of a brief instrument for assessing personality risk. Addiction Biology, 7, 329.
Cook, D. A., & Beckman, T. J. (2006). Current concepts in validity and reliability for psychometric instruments: Theory and application. American Journal of Medicine, 119, 166, e7–16.
DeYoung, C. G., Hirsh, J. B., Shane, M. S., Papademetris, X., Rajeevan, N., & Gray, J. R. (2010). Testing predictions from personality neuroscience. Brain structure and the big five. Psychological Science, 21, 820–828.
Di Chiara, G., & Imperato, A. (1988). Drugs abused by humans preferentially increase synaptic dopamine concentrations in the mesolimbic system of freely moving rats. Proceedings of the National Academy of Sciences, 85, 5274–5278.
Doll, B.B., Hutchison, K.E., & Frank, M.J. (2011). Dopaminergic genes predict individual differences in susceptibility to confirmation bias. Journal of Neuroscience, 31, 6188–6198.
Duan, J., Wainwright, M. S., Comeron, J. M., Saitou, N., Sanders, A. R., Gelernter, J., & Gejman, P. V. (2003). Synonymous mutations in the human dopamine receptor D2 (DRD2) affect mRNA stability and synthesis of the receptor. Human Molecular Genetics, 12, 205–216.
Fan, J., Fossella, J., Sommer, T., Wu, Y., & Posner, M. I. (2003). Mapping the genetic variation of executive attention onto brain activity. Proceedings of the National Academy of Sciences, 100, 7406–7411.
Fossella, J., Sommer, T., Fan, J., Wu, Y., Swanson, J. M., Pfaff, D. W., & Posner, M. I. (2002). Assessing the molecular genetics of attention networks. BMC Neuroscience, 3, 14.
Frank, M. J. (2005). Dynamic dopamine modulation in the basal ganglia: A neurocomputational account of cognitive deficits in medicated and nonmedicated Parkinsonism. Journal of Cognitive Neuroscience, 17, 51–72.
Frank, M. J., & Claus, E. D. (2006). Anatomy of a decision: Striato–orbitofrontal interactions in reinforcement learning, decision making, and reversal. Psychological Review, 113, 300–326.
Frank, M.J., Woroch, B.S., & Curran, T. (2005). Error-related negativity predicts reinforcement learning and conflict biases. Neuron, 47, 495–501.
Frank, M. J., D’Lauro, C., & Curran, T. (2007a). Cross-task individual differences in error processing: Neural, electrophysiological, and genetic components. Cognitive, Affective, & Behavioral Neuroscience, 7, 297–308. doi:10.3758/CABN.7.4.297
Frank, M. J., Doll, B. B., Oas-Terpstra, J., & Moreno, F. (2009). Prefrontal and striatal dopaminergic genes predict individual differences in exploration and exploitation. Nature Neuroscience, 12, 1062–1068.
Frank, M. J., & Fossella, J. A. (2011). Neurogenetics and pharmacology of learning, motivation, and cognition. Neuropsychopharmacology, 36, 133–152.
Frank, M. J., & Hutchison, K. (2009). Genetic contributions to avoidance-based decisions: Striatal D2 receptor polymorphisms. Neuroscience, 164, 131–140.
Frank, M. J., & Kong, L. (2008). Learning to avoid in older age. Psychology and Aging, 23, 392–398.
Frank, M. J., Loughry, B., & O’Reilly, R. C. (2001). Interactions between frontal cortex and basal ganglia in working memory: A computational model. Cognitive, Affective, & Behavioral Neuroscience, 1, 137–160. doi:10.3758/CABN.1.2.137
Frank, M. J., Moustafa, A. A., Haughey, H. M., Curran, T., & Hutchison, K. E. (2007b). Genetic triple dissociation reveals multiple roles for dopamine in reinforcement learning. Proceedings of the National Academy of Sciences, 104, 16311–16316.
Frank, M. J., & O’Reilly, R. C. (2006). A mechanistic account of striatal dopamine function in human cognition: Psychopharmacological studies with cabergoline and haloperidol. Behavioral Neuroscience, 120, 497–517.
Frank, M. J., Samanta, J., Moustafa, A. A., & Sherman, S. J. (2007c). Hold your horses: Impulsivity, deep brain stimulation, and medication in parkinsonism. Science, 318, 1309–1312. doi:10.1126/science.1146157
Frank, M. J., Scheres, A., & Sherman, S. J. (2007d). Understanding decision-making deficits in neurological conditions: Insights from models of natural action selection. Philosophical Transactions of the Royal Society B, 362, 1641–1654.
Frank, M. J., Seeberger, L. C., & O’Reilly, R. C. (2004). By carrot or by stick: Cognitive reinforcement learning in Parkinsonism. Science, 306, 1940–1943. doi:10.1126/science.1102941
Hakyemez, H. S., Dagher, A., Smith, S. D., & Zald, D. H. (2008). Striatal dopamine transmission in healthy humans during a passive monetary reward task. NeuroImage, 39, 2058–2065.
Hamidovic, A., Dlugos, A., Skol, A., Palmer, A. A., & de Wit, H. (2009). Evaluation of genetic variability in the dopamine receptor D2 in relation to behavioral inhibition and impulsivity/sensation seeking: An exploratory study with d-amphetamine in healthy participants. Experimental and Clinical Psychopharmacology, 17, 374–383. doi:10.1037/a0017840
Hardy, G. H., (1908). Mendelian proportions in a mixed population. Science 28, 49–50
Hirvonen, M., Laakso, A., Någren, K., Rinne, J. O., Pohjalainen, T., & Hietala, J. (2004). C957T polymorphism of the dopamine D2 receptor (DRD2) gene affects striatal DRD2 availability in vivo. Molecular Psychiatry, 9, 1060–1061.
Hirvonen, M. M., Laakso, A., Nagren, K., Rinne, J. O., Pohjalainen, T., & Hietala, J. (2009a). C957T polymorphism of dopamine D2 receptor gene affects striatal DRD2 in vivo availability by changing the receptor affinity. Synapse, 63, 907–912.
Hirvonen, M. M., Lumme, V., Hirvonen, J., Pesonen, U., Någren, K., Vahlberg, T., . . . Hietala, J. (2009). C957T polymorphism of the human dopamine D2 receptor gene predicts extrastriatal dopamine receptor availability in vivo. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 33, 630–636. doi:10.1016/j.pnpbp.2009.02.021
Hooks, M. S., Juncos, J. L., Justice, J. B., Jr., Meiergerd, S. M., Povlock, S. L., Schenk, J. O., & Kalivas P. W.(1994). Individual locomotor response to novelty predicts selective alterations in D1 and D2 receptors and mRNAs. Journal of Neuroscience, 14, 6144–6152.
Humeniuk, R., Ali, R., Babor, T. F., Farrell, M., Formigoni, M. L., Jittiwutikarn, J., . . . Simon, S. (2008). Validation of the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST). Addiction, 103, 1039–1047. doi:10.1111/j.1360-0443.2007.02114.x
Hyman, S. E., Malenka, R. C., & Nestler, E. J. (2006). Neural mechanisms of addiction: The role of reward-related learning and memory. Annual Review of Neuroscience, 29, 565–598.
Jentsch, J. D., & Taylor, J. R. (1999). Impulsivity resulting from frontostriatal dysfunction in drug abuse: Implications for the control of behavior by reward-related stimuli. Psychopharmacology, 146, 373–390.
Jutras-Aswad, D., Jacobs, M. M., Yiannoulos, G., Roussos, P., Bitsios, P., Nomura, Y., . . . Hurd, Y. L. (2012). Cannabis-dependence risk relates to synergism between neuroticism and proenkephalin SNPs associated with amygdala gene expression: Case-control study. PLoS ONE, 7:e39243. doi:10.1371/journal.pone.0039243
Klein, T. A., Neumann, J., Reuter, M., Hennig, J., von Cramon, D. Y., & Ullsperger, M. (2007). Genetically determined differences in learning from errors. Science, 318, 1642–1645.
Koob, G. F. (1996). Hedonic valence, dopamine and motivation. Mol. Psychiatry, 1, 186–189.
Koob, G. F., & Le, M. M. (1997). Drug abuse: hedonic homeostatic dysregulation. Science, 278, 52–58.
Koob, G. F., & Le, M. M. (2008). Review. Neurobiological mechanisms for opponent motivational processes in addiction. Philos. Trans. R. Soc. Lond B Biol.Sci., 363, 3113-3123.
Krebs, R. M., Schott, B. H., & Duzel, E. (2009). Personality traits are differentially associated with patterns of reward and novelty processing in the human substantia nigra/ventral tegmental area. Biological Psychiatry, 65, 103–110.
Kuntsi, J., Stevenson, J., Oosterlaan, J.,. & Sonuga-Barke, E.J.S. (2001). Test-retest reliability of a new delay aversion task and executive function measures. British Journal of Developmental Psychology, 19(3), 339–348.
Laine, T. P., Ahonen, A., Rasanen, P., & Tiihonen, J. (2001). Dopamine transporter density and novelty seeking among alcoholics. Journal of Addictive Diseases, 20, 91–96.
Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33, 159–174.
Laruelle, M., Gelernter, J., & Innis, R. B. (1998). D2 receptors binding potential is not affected by Taq1 polymorphism at the D2 receptor gene. Molecular Psychiatry, 3, 261–265.
Lawford, B. R., Young, R., Noble, E. P., Kann, B., & Ritchie, T. (2006). The D2 dopamine receptor (DRD2) gene is associated with co-morbid depression, anxiety and social dysfunction in untreated veterans with post-traumatic stress disorder. European Psychiatry, 21, 180–185.
Leventhal, A. M., Chasson, G. S., Tapia, E., Miller, EK., & Pettit, J. W. (2006). Measuring hedonic capacity in depression : a psychometric analysis of three anhedonia scales. Journal of Clinical Psychology 62, 1545–1558.
Lindskog, M., Kim, M., Wikstrom, M. A., Blackwell, K. T., & Kotaleski, J. H. (2006). Transient calcium and dopamine increase PKA activity and DARPP-32 phosphorylation. PLoS Computational Biology, 2, e119.
Lucht, M., & Rosskopf, D. (2008). Comment on “Genetically determined differences in learning from errors. Science, 321, 200.
Maia, T. V., & Frank, M. J. (2011). From reinforcement learning models to psychiatric and neurological disorders. Nature Neuroscience, 14, 154–162.
Maner, J. K., & Schmidt, N. B. (2006). The role of risk avoidance in anxiety. Behavior Therapy, 37, 181–189.
McGraw, K. O., & Wong, S. P. (1996). Forming inferences about some intraclass correlation coefficients. Psychological Methods, 1, 30–46. doi:10.1037/1082-989X.1.1.30
Meyer-Lindenberg, A. (2010). Behavioural neuroscience: Genes and the anxious brain. Nature, 466, 827–828.
Meyer-Lindenberg, A., Straub, R. E., Lipska, B. K., Verchinski, B. A., Goldberg, T., Callicott, J. H., . . . Weinberger, D. R. (2007). Genetic evidence implicating DARPP-32 in human frontostriatal structure, function, and cognition. Journal of Clinical Investigation, 117, 672–682. doi:10.1172/JCI30413
Mitte, K. (2008). Memory bias for threatening information in anxiety and anxiety disorders: A meta-analytic review. Psychological Bulletin, 134, 886–911.
Montag, C., Buckholtz, J. W., Hartmann, P., Merz, M., Burk, C., Hennig, J., & Reuter, M. (2008). COMT genetic variation affects fear processing: Psychophysiological evidence. Behavioral Neuroscience, 122, 901–909. doi:10.1037/0735-7044.122.4.901
Moustafa, A. A., Cohen, M. X., Sherman, S. J., & Frank, M. J. (2008a). A role for dopamine in temporal decision making and reward maximization in parkinsonism. Journal of Neuroscience, 28, 12294–12304. doi:10.1523/JNEUROSCI.3116-08.2008
Moustafa, A. A., Sherman, S. J., & Frank, M. J. (2008b). A dopaminergic basis for working memory, learning and attentional shifting in Parkinsonism. Neuropsychologia, 46, 3144–3156. doi:10.1016/j.neuropsychologia.2008.07.011
Newcombe, D. A., Humeniuk, R. E., & Ali, R. (2005). Validation of the World Health Organization Alcohol, Smoking and Substance Involvement Screening Test (ASSIST): Report of results from the Australian site. Drug and Alcohol Review, 24, 217–226.
Noël, X., Brevers, D., Bechara, A., Hanak, C., Kornreich, C., Verbanck, P., & Le Bon, O. (2011). Neurocognitive determinants of novelty and sensation-seeking in individuals with alcoholism. Alcohol and Alcoholism, 46, 407–415. doi:10.1093/alcalc/agr048
Oak, J. N., Oldenhof, J., & Van Tol, H. H. (2000). The dopamine D(4) receptor: One decade of research. European Journal of Pharmacology, 405, 303–327.
Okuyama, Y., Ishiguro, H., Toru, M., & Arinami, T. (1999). A genetic polymorphism in the promoter region of DRD4 associated with expression and schizophrenia. Biochemical and Biophysical Research Communications, 258, 292–295.
Packard, M. G., & Knowlton, B. J. (2002). Learning and memory functions of the basal ganglia. Annual Review of Neuroscience, 25, 563–593.
Paulus, M. P., & Frank, L. R. (2006). Anterior cingulate activity modulates nonlinear decision weight function of uncertain prospects. NeuroImage, 30, 668–677.
Piazza, P. V., Rouge-Pont, F., Deminiere, J. M., Kharoubi, M., Le, M. M., & Simon, H. (1991). Dopaminergic activity is reduced in the prefrontal cortex and increased in the nucleus accumbens of rats predisposed to develop amphetamine self-administration. Brain Research, 567, 169–174.
Raghunathan, R., & Pham, M. T. (1999). All negative moods are not equal: Motivational influences of anxiety and sadness on decision making. Organizational Behavior and Human Decision Processes, 79, 56–77.
Ragland, J. D., Cohen, N. J., Cools, R., Frank, M. J., Hannula, D. E., & Ranganath, C. (2012). CNTRICS imaging biomarkers final task selection: Long-term memory and reinforcement learning. Schizophrenia Bulletin, 38, 62–72. doi:10.1093/schbul/sbr168
Ragland, J. D., Cools, R., Frank, M., Pizzagalli, D. A., Preston, A., Ranganath, C., & Wagner, A. D. (2009). CNTRICS final task selection: Long-term memory. Schizophrenia Bulletin, 35, 197–212. doi:10.1093/schbul/sbn134
Savine, A. C., Beck, S. M., Edwards, B. G., Chiew, K. S., & Braver, T. S. (2010). Enhancement of cognitive control by approach and avoidance motivational states. Cognition & Emotion, 24, 338–356.
Savine, A. C., & Braver, T. S. (2010). Motivated cognitive control: Reward incentives modulate preparatory neural activity during task-switching. Journal of Neuroscience, 30, 10294–10305.
Schimmack, H. (2012). The ironic effect of significant results on the credibility of multiple-study articles. Psychological Methods, 17, 551–566. doi:10.1037/a0029487
Seeman, P. et al. (2005). Dopamine supersensitivity correlates with D2High states, implying many paths to psychosis. Proc. Natl Acad. Sci. USA. 102, 3513–3518
Simon, J. J., Walther, S., Fiebach, C. J., Friederich, H. C., Stippich, C., Weisbrod, M., & Kaiser, S. (2010). Neural reward processing is modulated by approach- and avoidance-related personality traits. NeuroImage, 49, 1868–1874. doi:10.1016/j.neuroimage.2009.09.016
Solomon, M., Smith, A. C., Frank, M. J., Ly, S., & Carter, C. S. (2011). Probabilistic reinforcement learning in adults with autism spectrum disorders. Autism Research, 4, 109–120.
Steele, J. D., Kumar, P., & Ebmeier, K. P. (2007). Blunted response to feedback information in depressive illness. Brain, 130, 2367–2374.
Svenningsson, P., Nairn, A. C., & Greengard, P. (2005). DARPP-32 mediates the actions of multiple drugs of abuse. The AAPS Journal, 7, E353–E360. doi:10.1208/aapsj070235
Svenningsson, P., Nishi, A., Fisone, G., Girault, J. A., Nairn, A. C., & Greengard, P. (2004). DARPP-32: An integrator of neurotransmission. Annual Review of Pharmacology and Toxicology, 44, 269–296.
Svenningsson, P., Tzavara, E. T., Liu, F., Fienberg, A. A., Nomikos, G. G., & Greengard, P. (2002). DARPP-32 mediates serotonergic neurotransmission in the forebrain. Proceedings of the National Academy of Sciences, 99, 3188–3193. doi:10.1073/pnas.052712699
Thissen, D., Steinberg, L., & Kuang, D. (2002). Quick and easy implementation of the Benjamini–Hochberg procedure for controlling the false discovery rate in multiple comparisons. Journal of Educational and Behavioral Statistics, 27, 77–83.
Thompson, J., Thomas, N., Singleton, A., Piggott, M., Lloyd, S., Perry, E. K., . . . Court, J. A. (1997). D2 dopamine receptor gene (DRD2) Taq1 A polymorphism: Reduced dopamine D2 receptor binding in the human striatum associated with the A1 allele. Pharmacogenetics, 7, 479–484.
Trochim, W. M. K., & Donnelly, J. P. (2007). The research methods knowledge base. Mason, OH: Thomson.
Waltz, J. A., Frank, M. J., Robinson, B. M., & Gold, J. M. (2007). Selective reinforcement learning deficits in schizophrenia support predictions from computational models of striatal–cortical dysfunction. Biological Psychiatry, 62, 756–764.
Waltz, J. A., Frank, M. J., Wiecki, T. V., & Gold, J. M. (2011). Altered probabilistic learning and response biases in schizophrenia: Behavioral evidence and neurocomputational modeling. Neuropsychology, 25, 86–97.
Weinberg, W., (1908). Über den Nachweis der Vererbung beim Menschen. Jahresh. Ver. Vaterl. Naturkd. Württemb. 64, 369–382
Wheeler, E. Z., & Fellows, L. K. (2008). The human ventromedial frontal lobe is critical for learning from negative feedback. Brain, 131, 1323–1331.
Wiecki, T. V., & Frank, M. J. (2010). Neurocomputational models of motor and cognitive deficits in Parkinson’s disease. Progress in Brain Research, 183, 275–297.
Whitmer A. J., & Gotlib I. H., (2012) Depressive rumination and the C957T polymorphism of the DRD2 gene. Cogn Affect Behav Neurosci. 12, 741-747
Yong, E. (2012). In the wake of high profile controversies, pyschologists are facing up to problems with replication. Nature, 483, 298–300.
Zermatten, A., Van der Linden, M., d’Acremont, M., Jermann, F., & Bechara, A. (2005). Impulsivity and decision making. The Journal of Nervous and Mental Disease, 193, 647–650.
Zhang, Y., Bertolino, A., Fazio, L., Blasi, G., Rampino, A., Romano, R., . . . Sadée, W. (2007). Polymorphisms in human dopamine D2 receptor gene affect gene expression, splicing, and neuronal activity during working memory. Proceedings of the National Academy of Sciences, 104, 20552–20557. doi:10.1073/pnas.0707106104
Zuckerman, M. (1988). Sensation seeking and behavior disorders. Archives of General Psychiatry, 45, 502–504.
Zuckerman, M., & Kuhlman, D. M. (2000). Personality and risk-taking: Common biosocial factors. Journal of Personality, 68, 999–1029.
This research was supported by Canadian Institutes of Health Research Operating Grant No. 97750. The first author was supported by Doctoral Awards from the Integrated Mentor Program in Addictions Research Training (IMPART) and from the Canadian Institutes of Health Research (No. 195501). We are grateful to the board of directors and staff members of Edgewood Rehab Center, Nanaimo British Columbia, for their supportive collaboration on this research, Mike Hunter and Gordon Barnes for their consultation on this project, Roderick Haesevoets for his work on genetic analysis, as well as Marie Clipperton, Somayyeh Montazer-Hojat, and Elizabeth Plant, and the research assistants of the Learning and Cognitive Control Laboratory for help with data collection.
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Baker, T.E., Stockwell, T. & Holroyd, C.B. Constraints on decision making: Implications from genetics, personality, and addiction. Cogn Affect Behav Neurosci 13, 417–436 (2013). https://doi.org/10.3758/s13415-013-0164-8
- Individual differences
- Midbrain dopamine system
- Basal ganglia
- Reinforcement learning
- Decision making
- Probabilistic selection task