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12 - Multiple Memory Systems, Addiction, and Health Habits: New Routes for Translational Science

from Part III - Levels of Analysis and Etiology

Published online by Cambridge University Press:  13 July 2020

Steve Sussman
Affiliation:
University of Southern California
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Summary

Several decades of basic research support the neural basis of multiple memory systems. These systems are highly relevant to all health behaviors, since behaviors are learned from experience and require some form of memory process to retain learning and affect subsequent action. Research on the neuroscience of appetitive behaviors has rigorously studied motivational processes involved in behaviors such as drug use, diet, and sex. However, very little of this otherwise stellar research has attempted to integrate its findings with multiple memory system views that acknowledge the wide range of memory effects uncovered in several highly relevant basic research areas. Further, good explanatory theories of multiple memory systems studied mostly in addiction and in animal research have not yet been integrated with the vast knowledge base from human cognitive science. Moreover, most research on the epidemiology, prevention, or treatment of problems in appetitive behavior has not taken into account these basic research findings and has instead focused on theories and methods derived primarily from survey research. Yet, basic research areas from neuroscience and cognitive science are highly relevant to all areas of study of appetitive behavior, and the prevailing focus in prevention science on concepts derived from survey research may be channeled mostly by the training of investigators and disciplinary history. This chapter provides one example of how these disparate literatures from basic research might be integrated to advance our understanding of this class of behavior and derive new possibilities for intervention. It highlights examples of key findings supporting the need for a greater translational effort but also highlights large gaps in knowledge. Future research filling these gaps and others in the void between compelling research domains could substantially change and advance the study of addictions and all appetitive or habit-forming behaviors.

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Publisher: Cambridge University Press
Print publication year: 2020

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References

Albarracín, D., Johnson, B. T., Fishbein, M. & Muellerleile, P. A. (2001). Theories of reasoned action and planned behavior as models of condom use: A meta-analysis. Psychological Bulletin, 127(1), 142161.CrossRefGoogle ScholarPubMed
Ames, S. L., Grenard, J. L., He, Q., et al. (2014b). Functional imaging of an alcohol-Implicit Association Test (IAT). Addiction Biology, 19(3), 467481. doi:10.1111/adb.12071CrossRefGoogle ScholarPubMed
Ames, S. L., Grenard, J. L., Stacy, A. W., et al. (2013). Functional imaging of implicit marijuana associations during performance on an Implicit Association Test (IAT). Behavioural Brain Research, 256, 494502. doi:10.1016/j.bbr.2013.09.013Google Scholar
Ames, S. L., Wong, S. W., Bechara, A., et al. (2014a). Neural correlates of a Go/No Go task with alcohol stimuli in light and heavy young drinkers. Behavioural Brain Research, 274, 382389CrossRefGoogle Scholar
Ames, S. L., Xie, B., Aragon, J. & Stacy, A. W. (2020). Moderating effects of control functions on implicit cognitive processes in health behavior: A meta-analysis. Submitted for publication.Google Scholar
Ames, S. L., Xie, B., Shono, Y. & Stacy, A. W. (2017). Adolescents at risk for drug abuse: A 3-year dual-process analysis. Addiction, 112(5), 852863. doi:10.1111/add.13742CrossRefGoogle ScholarPubMed
Baddeley, A. D. (2001). Is working memory still working? American Psychologist, 11, 851864. doi:10.1037/0003-066X.56.11.851Google Scholar
Back, S. E., Gros, D. F., McCauley, J. L., et al. (2014). Laboratory-induced cue reactivity among individuals with prescription opioid dependence. Addictive Behaviors, 39(8), 12171223. doi:10.1016/j.addbeh.2014.04.007Google Scholar
Bargh, J. A., Chen, M. & Burrows, L. (1996). Automaticity of social behavior: Direct effects of trait construct and stereotype activation on action. Journal of Personality and Social Psychology, 71(2), 230244.Google Scholar
Bargh, J. A. & Morsella, E. (2008). The unconscious mind. Perspectives on Psychological Science, 3(1), 7379.CrossRefGoogle ScholarPubMed
Bazzaz, M. M., Fadardi, J. S. & Parkinson, J. (2017). Efficacy of the attention control training program on reducing attentional bias in obese and overweight dieters. Appetite, 108, 111. doi:10.1016/j.appet.2016.08.114CrossRefGoogle ScholarPubMed
Bechara, A. (2005). Decision making, impulse control and loss of willpower to resist drugs: A neurocognitive perspective. Nature Neuroscience, 8(11), 14581463. doi:10.1038/nn1584Google Scholar
Berridge, K. C. & Robinson, T. E. (2016). Liking, wanting, and the incentive-sensitization theory of addiction. American Psychologist, 71(8), 670679. doi:10.1037/amp0000059Google Scholar
Binder, J. R. & Desai, R. H. (2011). The neurobiology of semantic memory. Trends in Cognitive Sciences, 15(11), 527536. doi:10.1016/j.tics.2011.10.001CrossRefGoogle ScholarPubMed
Binder, J. R., Desai, R. H., Graves, W. W. & Conant, L. L. (2009). Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. Cerebral Cortex, 19(12), 27672796. doi:10.1093/cercor/bhp055CrossRefGoogle ScholarPubMed
Blanton, H., Burrows, C. N. & Jaccard, J. (2016). To accurately estimate implicit influences on health behavior, accurately estimate explicit influences. Health Psychology, 35(8), 856860. doi:10.1037/hea0000348; 10.1037/hea0000348.supp (Supplemental).Google Scholar
Bousfield, W. A., Whitmarsh, G. A. & Danick, J. J. (1958). Partial response identities in verbal generalization. Psychological Reports, 4(3), 703713.Google Scholar
Brewer, D. D., Catalano, R. F., Haggerty, K., Gainey, R. R. & Fleming, C. B. (1998). A meta-analysis of predictors of continued drug use during and after treatment for opiate addiction. Addiction, 93(1), 7392. doi:10.1046/j.1360-0443.1998.931738.xGoogle Scholar
Buckner, R. L., Koutstaal, W., Schacter, D. L. & Rosen, B. R. (2000). Functional MRI evidence for a role of frontal and inferior temporal cortex in amodal components of priming. Brain: A Journal of Neurology, 123(3), 620640.CrossRefGoogle ScholarPubMed
Burton, P. C. & Martin, R. C. (2006). Semantic retrieval versus selection in verb generation: An fMRI investigation. Paper presented at the 47th Annual Meeting of the Psychonomic Society, Houston, Texas.Google Scholar
Cabeza, R. & Lennartson, E. R. (2005). False memory across languages: Implicit associative response vs fuzzy trace views. Memory, 13(1), 15.CrossRefGoogle ScholarPubMed
Cabeza, R. & Nyberg, L. (2000). Imaging cognition II: An empirical review of 275 PET and fMRI studies. Journal of Cognitive Neuroscience, 12(1), 147.Google Scholar
Cacioppo, J. T. & Berntson, G. G. (1999). The affect system: Architecture and operating characteristics. Current Directions in Psychological Science, 8, 133137.Google Scholar
Cacioppo, J. T. & Gardner, W. L. (1999). Emotion. Annual Review of Psychology, 50, 191214.Google Scholar
Chassin, L., Presson, C. C., Sherman, S. J., Seo, D.-C. & Macy, J. T. (2010). Implicit and explicit attitudes predict smoking cessation: Moderating effects of experienced failure to control smoking and plans to quit. Psychology of Addictive Behaviors, 24(4), 670679. doi:10.1037/a0021722CrossRefGoogle ScholarPubMed
Chein, J. M. & Schneider, W. (2005). Neuroimaging studies of practice-related change: fMRI and meta-analytic evidence of a domain-general control network for learning. Cognitive Brain Research, 25(3), 607623.CrossRefGoogle ScholarPubMed
Coallier, É, Michelet, T. & Kalaska, J. F. (2015). Dorsal premotor cortex: Neural correlates of reach target decisions based on a color-location matching rule and conflicting sensory evidence. Journal of Neurophysiology, 113(10), 35433573. doi:10.1152/jn.00166.2014Google Scholar
Cousijn, J., Wiers, R. W., Ridderinkhof, K. R., et al. (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), 24702482. doi:10.1002/hbm.22342CrossRefGoogle ScholarPubMed
Cowan, N. (1988). Evolving conceptions of memory storage, selective attention, and their mutual constraints within the human information-processing system. Psychological Bulletin, 104(2), 163191. doi:10.1037/0033-2909.104.2.163Google Scholar
Cox, W. M., Fadardi, J. S. & Pothos, E. M. (2006). The addiction-Stroop test: Theoretical considerations and procedural recommendations. Psychological Bulletin, 132(3), 443476. doi:10.1037/0033-2909.132.3.443CrossRefGoogle ScholarPubMed
Cramer, P. (1970a). Associative strength as a determinant of mediated priming. Journal of Verbal Learning and Verbal Behavior, 9(6), 658664. doi:http://dx.doi.org/10.1016/S0022-5371(70)80029-9Google Scholar
Cramer, P. (1970b). Semantic generalization: Demonstration of an associative gradient. Journal of Experimental Psychology, 84(1), 164172. doi:10.1037/h0028935Google Scholar
Crescentini, C., Shallice, T. & Macaluso, E. (2010). Item retrieval and competition in noun and verb generation: An fMRI study. Journal of Cognitive Neuroscience, 22(6), 11401157. doi:10.1162/jocn.2009.21255.Google Scholar
Cristofori, I. & Grafman, J. (2017). Neural underpinnings of the human belief system. In Angel, H., Oviedo, L., Paloutzian, R. F., et al. (Eds.), Processes of Believing: The Acquisition, Maintenance, and Change in Creditions. Cham, Switzerland: Springer International Publishing, pp. 111123. doi:10.1007/978-3-319-50924-2_8CrossRefGoogle Scholar
de Jong, P. J., Wiers, R. W., van de Braak, M. & Huijding, J. (2007). Using the Extrinsic Affective Simon Test as a measure of implicit attitudes towards alcohol: Relationship with drinking behavior and alcohol problems. Addictive Behaviors, 32(4), 881887. doi:10.1016/j.addbeh.2006.06.017CrossRefGoogle ScholarPubMed
Deese, J. (1959). On the prediction of occurrence of particular verbal intrusions in immediate recall. Journal of Experimental Psychology, 58(1), 1722.Google Scholar
Deese, J. (1962). On the structure of associative meaning. Psychological Review, 69(3), 161175. doi:10.1037/h0045842CrossRefGoogle ScholarPubMed
Derzon, J. H. & Lipsey, M. W. (1999). Predicting tobacco use to age 18: A synthesis of longitudinal research. Addiction, 94(7), 9951006. doi:10.1046/j.1360-0443.1999.9479955.xGoogle Scholar
Eldridge, L. L., Masterman, D. & Knowlton, B. J. (2002). Intact implicit habit learning in Alzheimer’s disease. Behavioral Neuroscience, 116(4), 722726.Google Scholar
Eriksson, J., Vogel, E.K., Lansner, A., Bergström, F. & Nyberg, L. (2015). Neurocognitive architecture of working memory. Neuron, 88(1), 3346. doi:10.1016/j.neuron.2015.09.020CrossRefGoogle ScholarPubMed
Everitt, B. J. & Robbins, T. W. (2016). Drug addiction: Updating actions to habits to compulsions ten years on. Annual Review of Psychology, 67, 2350. doi:10.1146/annurev-psych-122414-033457Google Scholar
Fillmore, M. T., Vogel-Sprott, M. & Gavrilescu, D. (1999). Alcohol effects on intentional behavior: Dissociating controlled and automatic influences. Experimental and Clinical Psychopharmacology, 7(4), 372378.CrossRefGoogle ScholarPubMed
Fishbein, D. H., Ridenour, T. A., Stahl, M. & Sussman, S. (2016). The full translational spectrum of prevention science: Facilitating the transfer of knowledge to practices and policies that prevent behavioral health problems. Translational Behavioral Medicine, 6(1), 516. doi:10.1007/s13142-015-0376-2Google Scholar
Foerde, K., Knowlton, B. J. & Poldrack, R. A. (2006). Modulation of competing memory systems by distraction. PNAS Proceedings of the National Academy of Sciences of the United States of America, 103(31), 1177811783. doi:10.1073/pnas.0602659103Google Scholar
Frankland, L., Bradley, B. P. & Mogg, K. (2016). Time course of attentional bias to drug cues in opioid dependence. Psychology of Addictive Behaviors, 30(5), 601606. doi:10.1037/adb0000169; 10.1037/adb0000169.supp (Supplemental)CrossRefGoogle ScholarPubMed
Fuster, J. M. (2001). The prefrontal cortex – An update: Time is of the essence. Neuron, 30, 319333.Google Scholar
Gabrieli, J. D. E., Stebbins, G. T., Singh, J., Willingham, D. B. & Goetz, C.G. (1997). Intact mirror-tracing and impaired rotary-pursuit skill learning in patients with Huntington’s disease: Evidence for dissociable memory systems in skill learning. Neuropsychology, 11(2), 272281. doi:10.1037/0894-4105.11.2.272Google Scholar
Gardner, B., de Bruijn, G. & Lally, P. (2011). A systematic review and meta-analysis of applications of the Self-Report Habit Index to nutrition and physical activity behaviours. Annals of Behavioral Medicine, 42(2), 174187. doi:10.1007/s12160-011-9282-0CrossRefGoogle ScholarPubMed
Gardner, B., de Bruijn, G. & Lally, P. (2012). Habit, identity, and repetitive action: A prospective study of binge-drinking in UK students. British Journal of Health Psychology, 17(3), 565581. doi:10.1111/j.2044-8287.2011.02056.xCrossRefGoogle Scholar
Garland, E. L., Franken, I. H., Sheetz, J. J. & Howard, M. O. (2012). Alcohol attentional bias is associated with autonomic indices of stress-primed alcohol cue-reactivity in alcohol-dependent patients. Experimental and Clinical Psychopharmacology, 20(3), 225235. doi:10.1037/a0027199Google Scholar
Glenberg, A. M., Witt, J. K. & Metcalfe, J. (2013). From the revolution to embodiment: 25 years of cognitive psychology. Perspectives on Psychological Science, 8(5), 573585. doi:10.1177/1745691613498098Google Scholar
Glock, S., Klapproth, F. & Müller, B. C. N. (2015). Promoting responsible drinking? A mass media campaign affects implicit but not explicit alcohol-related cognitions and attitudes. British Journal of Health Psychology, 20(3), 482497. doi:10.1111/bjhp.12130Google Scholar
Graf, P. & Schacter, D. L. (1985). Implicit and explicit memory for new associations in normal and amnesic subjects. Journal of Experimental Psychology: Learning, Memory, and Cognition, 11(3), 501518.Google Scholar
Greenwald, A. G. & Banaji, M. R. (1995). Implicit social cognition: Attitudes, self-esteem, and stereotypes. Psychological Review, 102(1), 427.Google Scholar
Greenwald, A. G., McGhee, D. E. & Schwartz, J. L. K. (1998). Measuring individual differences in implicit cognition: The Implicit Association Test. Journal of Personality and Social Psychology, 74(6), 14641480.CrossRefGoogle ScholarPubMed
Greenwald, A. G., Nosek, B. A. & Banaji, M. R. (2003). Understanding and using the Implicit Association Test: I. An improved scoring algorithm. Journal of Personality and Social Psychology, 85(2), 197216.Google Scholar
Grenard, J. L., Ames, S. L., Wiers, R. W., et al. (2008). Working memory capacity moderates the predictive effects of drug-related associations on substance use. Psychology of Addictive Behaviors , 22(3), 426432. doi:10.1037/0893-164X.22.3.426Google Scholar
Hagger, M. S., Chan, D. K. C., Protogerou, C. & Chatzisarantis, N. L. D. (2016). Using meta-analytic path analysis to test theoretical predictions in health behavior: An illustration based on meta-analyses of the theory of planned behavior. Preventive Medicine, 89, 154161. doi:10.1016/j.ypmed.2016.05.020Google Scholar
Hanlon, C. A., Dowdle, L. T., Naselaris, T., Canterberry, M. & Cortese, B. M. (2014). Visual cortex activation to drug cues: A meta-analysis of functional neuroimaging papers in addiction and substance abuse literature. Drug and Alcohol Dependence, 143, 206212. doi:10.1016/j.drugalcdep.2014.07.028CrossRefGoogle ScholarPubMed
Hélie, S., Ell, S. W. & Ashby, F. G. (2015). Learning robust cortico-cortical associations with the basal ganglia: An integrative review. Cortex: A Journal Devoted to the Study of the Nervous System and Behavior, 64, 123135. doi:10.1016/j.cortex.2014.10.011Google Scholar
Henke, K. (2010). A model for memory systems based on processing modes rather than consciousness. Nature Reviews Neuroscience, 11(7), 523532. doi:10.1038/nrn2850CrossRefGoogle Scholar
Hintzman, D. L. (1986). “Schema abstraction” in a multiple-trace memory model. Psychological Review, 93(4), 411428.CrossRefGoogle Scholar
Hommel, B. & Wiers, R. W. (2017). Towards a unitary approach to human action control. Trends in Cognitive Sciences, 21(12), 940949. doi:10.1016/j.tics.2017.09.009CrossRefGoogle ScholarPubMed
Hoshi, E. & Tanji, J. (2007). Distinctions between dorsal and ventral premotor areas: Anatomical connectivity and functional properties. Current Opinion in Neurobiology, 17(2), 234242. doi:10.1016/j.conb.2007.02.003CrossRefGoogle ScholarPubMed
Hovington, C. L. & Brouwer, B. (2010). Guided motor imagery in healthy adults and stroke: Does strategy matter? Neurorehabilitation and Neural Repair, 24(9), 851857. doi:10.1177/1545968310374190CrossRefGoogle ScholarPubMed
Hutchison, K. A., Balota, D. A., Cortese, M. J. & Watson, J. M. (2008). Predicting semantic priming at the item level. The Quarterly Journal of Experimental Psychology, 61(7), 10361066. doi:10.1080/17470210701438111Google Scholar
Ishida, H., Inoue, K., Takada, M. & Hoshi, E. (2016). Origins of multisynaptic projections from the basal ganglia to the forelimb region of the ventral premotor cortex in macaque monkeys. European Journal of Neuroscience, 43(2), 258269. doi:10.1111/ejn.13127Google Scholar
Kahneman, D. (2003). A perspective on judgment and choice: Mapping bounded rationality. American Psychologist, 58(9), 697720.Google Scholar
Kahneman, D. (2011). Thinking, Fast and Slow (1st edition). New York, NY: Farrar, Straus and Giroux.Google Scholar
Kandel, E. R. & Kandel, D. B. (2014). A molecular basis for nicotine as a gateway drugThe New England Journal of Medicine371(10), 932943. doi:10.1056/NEJMsa1405092CrossRefGoogle ScholarPubMed
Kelly, A. B., Masterman, P. W. & Marlatt, G. A. (2005). Alcohol-related associative strength and drinking behaviours: Concurrent and prospective relationships. Drug and Alcohol Review, 24(6), 489498.Google Scholar
Kharitonova, M., Winter, W. & Sheridan, M. A. (2015). As working memory grows: A developmental account of neural bases of working memory capacity in 5- to 8-year old children and adults. Journal of Cognitive Neuroscience, 27(9), 17751788. doi:10.1162/jocn_a_00824Google Scholar
Khurana, A., Romer, D., Betancourt, L. M., et al. (2012). Working memory ability predicts trajectories of early alcohol use in adolescents: The mediational role of impulsivity. Addiction, 108, 506515.Google Scholar
Khurana, A., Romer, D., Betancourt, L. M., et al. (2015). Stronger working memory reduces sexual risk taking in adolescents, even after controlling for parental influences. Child Development, 86(4), 11251141. doi:10.1111/cdev.12383Google Scholar
Khurana, A., Romer, D., Betancourt, L. M. & Hurt, H. (2017). Working memory ability and early drug use progression as predictors of adolescent substance use disorders. Addiction, 112(7), 12201228. doi:10.1111/add.13792Google Scholar
Knowlton, B. J., Mangels, J. A. & Squire, L. R. (1996). A neostriatal habit learning system in humans. Science, 273(5280), 1399–402.Google Scholar
Koob, G. F. & Le Moal, M. (2008). Addiction and the brain antireward system. Annual Review of Psychology, 59, 2953. doi:10.1146/annurev.psych.59.103006.093548Google Scholar
Koob, G. F. & Volkow, N. D. (2016). Neurobiology of addiction: A neurocircuitry analysis. The Lancet Psychiatry, 3(8), 760773. doi:10.1016/S2215-0366(16)00104-8Google Scholar
Kosslyn, S. M., Ganis, G. & Thompson, W. L. (2001). Neural foundations of imagery. Nature Reviews Neuroscience, 2(9), 635642. doi:10.1038/35090055Google Scholar
Krank, M., Wall, A.-M., Stewart, S. H., Wiers, R. W. & Goldman, M. S. (2005). Context effects on alcohol cognitions. Alcoholism: Clinical & Experimental Research, 29(2), 196206. doi:10.1097/01.ALC.0000153545.36787.C8CrossRefGoogle ScholarPubMed
Landis, D., Triandis, H. C. & Adamopoulos, J. (1978). Habit and behavioral intentions as predictors of social behavior. The Journal of Social Psychology, 106(2), 227237. doi:10.1080/00224545.1978.9924174Google Scholar
Levy, D. A., Stark, C. E. L. & Squire, L. R. (2004). Intact conceptual priming in the absence of declarative memory. Psychological Science, 15(10), 680686. doi:10.1111/j.0956-7976.2004.00740.xGoogle Scholar
Lindgren, K. P., Neighbors, C., Gasser, M. L., Ramirez, J. J. & Cvencek, D. (2017). A review of implicit and explicit substance self-concept as a predictor of alcohol and tobacco use and misuse. The American Journal of Drug and Alcohol Abuse, 43(3), 237246. doi:10.1080/00952990.2016.1229324Google Scholar
Lindgren, K. P., Neighbors, C., Teachman, B. A., et al. (2016). Implicit alcohol associations, especially drinking identity, predict drinking over time. Health Psychology, 35(8), 908918. doi:10.1037/hea0000396; 10.1037/hea0000396.supp (Supplemental).Google Scholar
Luttrell, A., Stillman, P. E., Hasinski, A. E. & Cunningham, W. A. (2016). Neural dissociations in attitude strength: Distinct regions of cingulate cortex track ambivalence and certainty. Journal of Experimental Psychology: General, 145(4), 419433. doi:10.1037/xge0000141; 10.1037/xge0000141.supp (Supplemental).CrossRefGoogle ScholarPubMed
Mahler, S. V. & Berridge, K. C. (2012). What and when to “want”? Amygdala-based focusing of incentive salience upon sugar and sex. Psychopharmacology, 221(3), 407426. doi:10.1007/s00213-011-2588-6Google Scholar
Marins, T. F., Rodrigues, E. C., Engel, A., et al. (2015). Enhancing motor network activity using real-time functional MRI neurofeedback of left premotor cortex. Frontiers in Behavioral Neuroscience, 9. doi:10.3389/fnbeh.2015.00341Google Scholar
McEachan, R. R. C., Conner, M., Taylor, N. J. & Lawton, R. J. (2011). Prospective prediction of health-related behaviours with the Theory of Planned Behaviour: A meta-analysis. Health Psychology Review, 5(2), 97144. doi:10.1080/17437199.2010.521684CrossRefGoogle Scholar
Miller, K. J., Schalk, G., Fetz, E. E., et al. (2010). Cortical activity during motor execution, motor imagery, and imagery-based online feedback. Proceedings of the National Academy of Sciences of the United States of America, 107(9), 44304435. doi:10.1073/pnas.0913697107Google Scholar
Mirabella, G., Pani, P. & Ferraina, S. (2011). Neural correlates of cognitive control of reaching movements in the dorsal premotor cortex of rhesus monkeys. Journal of Neurophysiology, 106(3), 14541466. doi:10.1152/jn.00995.2010Google Scholar
Moore, P. J., Turner, R., Park, C. L. & Adler, N. E. (1996). The impact of behavior and addiction on psychological models of cigarette and alcohol use during pregnancy. Addictive Behaviors, 21(5), 645658. doi:10.1016/0306-4603(95)00100-XCrossRefGoogle ScholarPubMed
Moors, A., Spruyt, A. & De Houwer, J. (2010). In search of a measure that qualifies as implicit: Recommendations based on a decompositional view of automaticity. In Gawronski, B. & Payne, B. K. (Eds.), Handbook of Implicit Social Cognition: Measurement, Theory, and Applications. New York, NY: The Guilford Press, pp. 1937.Google Scholar
Neal, D. T., Wood, W. & Drolet, A. (2013). How do people adhere to goals when willpower is low? The profits (and pitfalls) of strong habits. Journal of Personality and Social Psychology, 104(6), 959975. doi:10.1037/a0032626Google Scholar
Nelson, D. L., McKinney, V. M., Gee, N. R. & Janczura, G. A. (1998). Interpreting the influence of implicitly activated memories on recall and recognition. Psychological Review, 105(2), 299324. doi:10.1037/0033-295X.105.2.299Google Scholar
Noël, X., Brevers, D. & Bechara, A. (2013). A neurocognitive approach to understanding the neurobiology of addiction. Current Opinion in Neurobiology, 23(4), 632638. doi:10.1016/j.conb.2013.01.018Google Scholar
Norman, P. (2011). The theory of planned behavior and binge drinking among undergraduate students: Assessing the impact of habit strength. Addictive Behaviors, 36(5), 502507. doi:10.1016/j.addbeh.2011.01.025CrossRefGoogle ScholarPubMed
Nosek, B. A., Greenwald, A. G. & Banaji, M. R. (2005). Understanding and using the Implicit Association Test: II. Method variables and construct validity. Personality and Social Psychology Bulletin, 31(2), 166180.Google Scholar
Nosek, B. A., Greenwald, A. G. & Banaji, M. R. (2007). The Implicit Association Test at age 7: A methodological and conceptual review. In Bargh, J. A. (Ed.), Automatic Processes in Social Thinking and Behavior. New York, NY: Psychology Press Ltd, pp. 265292.Google Scholar
Ntoumanis, N. D., Ng, J. Y. Y., Barkoukis, V. & Backhouse, S. (2014). Personal and psychosocial predictors of doping use in physical activity settings: A meta-analysis. Sports Medicine, 44(11), 16031624. doi:10.1007/s40279-014-0240-4Google Scholar
Oguri, T., Sawamoto, N., Tabu, H., et al. (2013). Overlapping connections within the motor cortico-basal ganglia circuit: fMRI-tractography analysis. Neuroimage, 78, 353362. doi:10.1016/j.neuroimage.2013.04.026Google Scholar
Oliver, J. A., Jentink, K. G., Drobes, D. J. & Evans, D. E. (2016). Smokers exhibit biased neural processing of smoking and affective images. Health Psychology, 35(8), 866869. doi:10.1037/hea0000350; 10.1037/hea0000350.supp (Supplemental).Google Scholar
Orbell, S. & Verplanken, B. (2010). The automatic component of habit in health behavior: Habit as cue-contingent automaticity. Health Psychology, 29(4), 374383. doi:10.1037/a0019596Google Scholar
Ouellette, J. & Wood, W. (1998). Habit and intention in everyday life: The multiple processes by which past behavior predicts future behavior. Psychological Bulletin, 124(1), 5474. doi:10.1037//0033-2909.124.1.54Google Scholar
Packard, M. G. & Goodman, J. (2013). Factors that influence the relative use of multiple memory systems. Hippocampus, 23(11), 10441052. doi:10.1002/hipo.22178Google Scholar
Packard, M. G. & Knowlton, B. J. (2002). Learning and memory functions of the basal ganglia. Annual Review of Neuroscience, 25(1), 563593. doi:10.1146/annurev.neuro.25.112701.142937Google Scholar
Palfai, T. P. & Ostafin, B. D. (2003). Alcohol-related motivational tendencies in hazardous drinkers: Assessing implicit response tendencies using the modified-IAT. Behaviour Research and Therapy, 41(10), 11491162.CrossRefGoogle ScholarPubMed
Patterson, K., Nestor, P. J. & Rogers, T. T. (2007). Where do you know what you know? The representation of semantic knowledge in the human brain. Nature Reviews Neuroscience, 8(12), 976987. doi:10.1038/nrn2277Google Scholar
Payne, B. K. & Gawronski, B. (2010). A history of implicit social cognition: Where is it coming from? Where is it now? Where is it going? In Gawronski, B. & Payne, B. K. (Eds.), Handbook of Implicit Social Cognition: Measurement, Theory, and Applications . New York, NY: The Guilford Press, pp. 115.Google Scholar
Payne, B. K., Lee, K. M., Giletta, M. & Prinstein, M. J. (2016). Implicit attitudes predict drinking onset in adolescents: Shaping by social norms. Health Psychology, 35(8), 829836. doi:10.1037/hea0000353; 10.1037/hea0000353.supp (Supplemental).Google Scholar
Peeters, M., Monshouwer, K., Janssen, T., Wiers, R. W. & Vollebergh, W. A. M. (2014). Working memory and alcohol use in at-risk adolescents: A 2-year follow-up. Alcoholism: Clinical & Experimental Research, 38(4), 11761183. doi:10.1111/acer.12339Google Scholar
Pilgramm, S., de Haas, B., Helm, F., et al. (2016). Motor imagery of hand actions: Decoding the content of motor imagery from brain activity in frontal and parietal motor areas. Human Brain Mapping, 37(1), 8193. doi:10.1002/hbm.23015Google Scholar
Raichle, M. E., Fiez, J. A., Videen, T. O., et al. (1994). Practice-related changes in human brain functional anatomy during nonmotor learning. Cerebral Cortex, 4(1), 826. doi:10.1093/cercor/4.1.8Google Scholar
Ray, S., Bates, M. E. & Ely, B. M. (2004). Alcohol's dissociation of implicit and explicit memory processes: Implications of a parallel distributed processing model of semantic priming. Experimental and Clinical Psychopharmacology, 12(2), 118125.CrossRefGoogle ScholarPubMed
Reder, L. M., Park, H. & Kieffaber, P. D. (2009). Memory systems do not divide on consciousness: Reinterpreting memory in terms of activation and binding. Psychological Bulletin, 135(1), 2349. doi:10.1037/a0013974Google Scholar
Reich, R. R., Goldman, M. S. & Noll, J. A. (2004). Using the false memory paradigm to test two key elements of alcohol expectancy theory. Experimental and Clinical Psychopharmacology, 12(2), 102110.Google Scholar
Robin, N., Dominique, L., Toussaint, L., et al. (2007). Effect of motor imagery training on service return accuracy in tennis: The role of imagery ability. International Journal of Sport and Exercise Psychology, 5(2), 175186.Google Scholar
Robinson, M. J. F., Anselme, P., Fischer, A. M. & Berridge, K. C. (2014). Initial uncertainty in Pavlovian reward prediction persistently elevates incentive salience and extends sign-tracking to normally unattractive cues. Behavioural Brain Research, 266, 119130. doi:10.1016/j.bbr.2014.03.004Google Scholar
Robinson, K. J. & Roediger, H. L. (1997). Associative processes in false recall and false recognition. Psychological Science, 8(3), 231237.Google Scholar
Roediger, H. L., Watson, J. M., McDermott, K. B. & Gallo, D. A. (2001). Factors that determine false recall: A multiple regression analysis. Psychonomic Bulletin & Review, 8(3), 385407.Google Scholar
Rolls, E. T. (2000). Memory systems in the brain. Annual Review of Psychology, 51, 599630. doi:10.1146/annurev.psych.51.1.599Google Scholar
Rotter, J. B. (1954). Social Learning and Clinical Psychology. Englewood Cliffs, NJ: Prentice-Hall, Inc. doi:10.1037/10788-000Google Scholar
Salemink, E. & Wiers, R. W. (2014). Alcohol-related memory associations in positive and negative affect situations: Drinking motives, working memory capacity, and prospective drinking. Psychology of Addictive Behaviors, 28(1), 105113. doi:10.1037/a0032806Google Scholar
Schacter, D. L. (1985). Priming of old and new knowledge in amnesic patients and normal subjects. Annals of the New York Academy of Sciences, 444, 4153.Google Scholar
Schneider, W. & Chein, J. M. (2003). Controlled & automatic processing: Behavior, theory, and biological mechanisms. Cognitive Science, 27(3), 525559. doi:10.1016/S0364-0213(03)00011-9Google Scholar
Schneider, W. & Shiffrin, R. M. (1977). Controlled and automatic human information processing: I. Detection, search, and attention. Psychological Review, 84(1), 166. doi:10.1037/0033-295X.84.1.1Google Scholar
Scoville, W. B. & Milner, B. (1957). Loss of recent memory after bilateral hippocampal lesions. Journal of Neurology, Neurosurgery & Psychiatry, 20(1), 1121. doi:10.1136/jnnp.20.1.11Google Scholar
Seger, C. A., Desmond, J. E., Glover, G. H. & Gabrieli, J. D. (2000). Functional magnetic resonance imaging evidence for right-hemisphere involvement in processing unusual semantic relationships. Neuropsychology, 14(3), 361369.Google Scholar
Seger, C. A., Rabin, L. A., Desmond, J. E. & Gabrieli, J. D. (1999). Verb generation priming involves conceptual implicit memory. Brain and Cognition, 41(2), 150177. doi:10.1006/brcg.1999.1116Google Scholar
Seger, C. A., Rabin, L. A., Zarella, M. M. & Gabrieli, J. D. E. (1997). Preserved verb generation priming in global amnesia. Neuropsychologia, 35(8), 10691074. doi:10.1097/OLQ.0b013e318214bb70Google Scholar
Sheldon, S., Romero, K. & Moscovitch, M. (2013). Medial temporal lobe amnesia impairs performance on a free association task. Hippocampus, 23(5), 405412. doi:10.1002/hipo.22099Google Scholar
Sherman, S. J., Chassin, L., Presson, C., Seo, D.-C. & Macy, J. T. (2009). The intergenerational transmission of implicit and explicit attitudes toward smoking: Predicting adolescent smoking initiation. Journal of Experimental Social Psychology, 45(2), 313319. doi:10.1016/j.jesp.2008.09.012CrossRefGoogle Scholar
Shiffrin, R. M. & Schneider, W. (1977). Controlled and automatic human information processing: II. Perceptual learning, automatic attending and a general theory. Psychological Review, 84(2), 127190. doi:10.1037/0033-295X.84.2.127Google Scholar
Shimamura, A. P. & Squire, L. R. (1984). Paired-associate learning and priming effects in amnesia: A neuropsychological study. Journal of Experimental Psychology: General, 113(4), 556570. doi:10.1037/0096-3445.113.4.556Google Scholar
Shono, Y., Ames, S. L. & Stacy, A. W. (2016). Evaluation of internal validity using modern test theory: Application to word association. Psychological Assessment, 28(2), 194204. doi:10.1037/pas0000175Google Scholar
Shono, Y., Edwards, M. C., Ames, S. L. & Stacy, A. W. (2018). Trajectories of cannabis-related associative memory among vulnerable adolescents: Psychometric and longitudinal evaluations. Developmental Psychology, 54(6), 11481158. doi:10.1037/dev0000510Google Scholar
Spruyt, A., Lemaigre, V., Salhi, B., et al. (2015). Implicit attitudes towards smoking predict long-term relapse in abstinent smokers. Psychopharmacology, 232(14), 25512561. doi:10.1007/s00213-015-3893-2Google Scholar
Squire, L. R. (2009). Memory and brain systems: 1969–2009. The Journal of Neuroscience, 29(41), 1271112716. doi:10.1523/JNEUROSCI.3575-09.2009Google Scholar
Squire, L. R. & Knowlton, B. J. (1995). Memory, hippocampus, & brain systems. In Gazzaniga, M. (Ed.), The Cognitive Neurosciences. Cambridge, MA: MIT Press, pp. 825837.Google Scholar
Squire, L. R., Knowlton, B. & Musen, G. (1993). The structure and organization of memory. Annual Review of Psychology, 44, 453495.Google Scholar
Stacy, A. W., Ames, S. L. & Knowlton, B. J. (2004). Neurologically plausible distinctions in cognition relevant to drug use etiology and prevention. Substance Use & Misuse, 39(10–12), 15711623.Google Scholar
Stacy, A. W., Bentler, P. M. & Flay, B. R. (1994). Attitudes and health behavior in diverse populations: Drunk driving, alcohol use, binge eating, marijuana use, and cigarette use. Health Psychology, 13(1), 7385. doi:10.1037/0278-6133.13.1.73Google Scholar
Stacy, A. W., Nydegger, L. A. & Shono, Y. (2019). Translation of basic research in cognitive science to HIV risk: A randomized controlled trial. Journal of Behavioral Medicine, 42, 440451.CrossRefGoogle ScholarPubMed
Stacy, A. W., Stein, J. A. & Longshore, D. (1999). Habit, intention, and drug use as interactive predictors of condom use among drug abusers. AIDS and Behavior, 3(3), 231241.Google Scholar
Sussman, S., Ames, S. L., Dent, C. W. & Stacy, A. W. (2001). Self-reported high-risk locations of drug use among drug offenders. American Journal of Drug and Alcohol Abuse, 27(2), 281299.Google Scholar
Szalay, L. B., Strohl, J. B. & Doherty, K. T. (1999). Psychoenvironmental Forces in Substance Abuse Prevention. Dordrecht, the Netherlands: Kluwer Academic Publishers.Google Scholar
Thompson-Schill, S. L., D'Esposito, M. & Kan, I. P. (1999). Effects of repetition and competition on activity of left prefrontal cortex during word generation. Neuron, 23(3), 513522.Google Scholar
Thush, C. & Wiers, R. W. (2007). Explicit and implicit alcohol-related cognitions and the prediction of future drinking in adolescents. Addictive Behaviors, 32(7), 13671383. doi:S0306-4603(06)00299-1 [pii] 10.1016/j.addbeh.2006.09.011Google Scholar
Thush, C., Wiers, R. W., Ames, S. L., et al. (2007). Apples and oranges? Comparing indirect measures of alcohol-related cognition predicting alcohol use in at-risk adolescents. Psychology of Addictive Behaviors, 21(4), 587591.Google Scholar
Thush, C., Wiers, R. W., Ames, S. L., et al. (2008). Interactions between implicit and explicit cognition and working memory capacity in the prediction of alcohol use in at-risk adolescents. Drug and Alcohol Dependence, 94(1–3), 116124. doi:S0376-8716(07)00432-2 [pii] 10.1016/j.drugalcdep.2007.10.019Google Scholar
Tversky, A. & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive Psychology, 5(2), 207232. doi:10.1016/0010-0285(73)90033-9Google Scholar
Underwood, B. J. (1965). False recognition produced by implicit verbal responses. Journal of Experimental Psychology, 70(1), 122129.Google Scholar
Underwood, B. J., Reichardt, C. S. & Malmi, R. A. (1975). Sources of facilitation in learning conceptually structured paired-associate lists. Journal of Experimental Psychology: Human Learning and Memory, 1(2), 160166. doi:10.1037/0278-7393.1.2.160Google Scholar
Vaidya, C. J., Gabrieli, J. D.E., Keane, M. M. & Monti, L. A. (1995). Perceptual and conceptual memory processes in global amnesia. Neuropsychology, 9(4), 580591.CrossRefGoogle Scholar
Vallet, G. T., Hudon, C., Bier, N., et al. (2017). A semantic and episodic memory test (SEMEP) developed within the embodied cognition framework: Application to normal aging, Alzheimer’s disease and semantic dementia. Frontiers in Psychology, 8. doi:10.3389/fpsyg.2017.01493Google Scholar
Van Der Vorst, H., Krank, M. D., Engels, R. C. M. E., et al. (2013). The mediating role of alcohol-related memory associations on the relation between perceived parental drinking and the onset of adolescents’ alcohol use. Addiction, 108(3), 526533. doi:10.1111/add.12042Google Scholar
Verplanken, B. & Orbell, S. (2003). Reflections on past behavior: A self-report index of habit strength. Journal of Applied Social Psychology, 33(6), 13131330. doi:10.1007/s12160-011-9305-xGoogle Scholar
Volkow, N. D., Koob, G. F. & McLellan, A. T. (2016). Neurobiologic advances from the brain disease model of addiction. The New England Journal of Medicine, 374(4), 363-371. doi:10.1056/NEJMra1511480Google Scholar
Wang, J., Johnson, L. A., Jensen, A. L., et al. (2017). Network-wide oscillations in the parkinsonian state: Alterations in neuronal activities occur in the premotor cortex in parkinsonian nonhuman primates. Journal of Neurophysiology, 117(6), 22422249. doi:10.1152/jn.00011.2017Google Scholar
Wei, G. & Luo, J. (2010). Sport expert's motor imagery: Functional imaging of professional motor skills and simple motor skills. Brain Research, 1341, 5262. doi:10.1016/j.brainres.2009.08.014CrossRefGoogle ScholarPubMed
Weingardt, K. R., Stacy, A. W. & Leigh, B. C. (1996). Automatic activation of alcohol concepts in response to positive outcomes of alcohol use. Alcoholism: Clinical and Experimental Research, 20(1), 2530.Google Scholar
White, N. M. & McDonald, R. J. (2002). Multiple parallel memory systems in the brain of the rat. Neurobiology of Learning and Memory, 77(2), 125184. doi:10.1006/nlme.2001.4008Google Scholar
White, N. M., Packard, M. G. & McDonald, R. J. (2013). Dissociation of memory systems: The story unfolds. Behavioral Neuroscience, 127(6), 813834. doi:10.1037/a0034859Google Scholar
Wiers, R. W., Rinck, M., Dictus, M. & van den Wildenberg, E. (2009). Relatively strong automatic appetitive action-tendencies in male carriers of the OPRM1 G-allele. Genes, Brain & Behavior, 8(1), 101106. doi:10.1111/j.1601-183X.2008.00454.xGoogle Scholar
Wiers, R. W. & Stacy, A. W. (2006). Implicit cognition and addiction. Current Directions in Psychological Science, 15(6), 292296.Google Scholar
Wiers, R. W., van de Luitgaarden, J., van den Wildenberg, E. & Smulders, F. T. Y. (2005). Challenging implicit and explicit alcohol-related cognitions in young heavy drinkers. Addiction, 100(6), 806819. doi:10.1111/j.1360-0443.2005.01064.xGoogle Scholar
Wing, E. A., Iyengar, V., Hess, T. M., et al. (2018). Neural mechanisms underlying subsequent memory for personal beliefs: An fMRI study. Cognitive, Affective & Behavioral Neuroscience, 18(2), 216231. doi:10.3758/s13415-018-0563-yGoogle Scholar
Wood, W. & Neal, D. T. (2007). A new look at habits and the habit-goal interface. Psychological Review, 114(4), 843863. doi:2007-13558-001 [pii] 10.1037/0033-295X.114.4.843Google Scholar
Wriessnegger, S. C., Steyrl, D., Koschutnig, K. & Müller-Putz, G. R. (2016). Cooperation in mind: Motor imagery of joint and single actions is represented in different brain areas. Brain and Cognition, 109, 1925. doi:10.1016/j.bandc.2016.08.008Google Scholar
Yalachkov, Y., Kaiser, J. & Naumer, M.J. (2015). The role of sensory and motor brain regions in drug-cue reactivity. In Wilson, S. J. (Ed.), The Wiley Handbook on the Cognitive Neuroscience of Addiction. Wiley-Blackwell, pp. 175194.Google Scholar
Yan, W., Li, Y., Xiao, L., et al. (2014). Working memory and affective decision- making in addiction: A neurocognitive comparison between heroin addicts, pathological gamblers and healthy controls. Drug and Alcohol Dependence, 134, 194200. doi:10.1016/j.drugalcdep.2013.09.027Google Scholar
Yin, H. H. & Knowlton, B. J. (2006a). Addiction and learning in the brain. In Wiers, R. W. & Stacy, A. W. (Eds.), Handbook of Implicit Cognition and Addiction. Thousand Oaks, CA: SAGE Publications, pp. 167184.Google Scholar
Yin, H. H. & Knowlton, B. J. (2006b). The role of the basal ganglia in habit formation. Nature Reviews Neuroscience, 7(6), 464476. doi:10.1038/nrn1919Google Scholar
Young, K. A., Franklin, T. R., Roberts, D. C. S., et al. (2014). Nipping cue reactivity in the bud: Baclofen prevents limbic activation elicited by subliminal drug cues. The Journal of Neuroscience, 34(14), 50385043. doi:10.1523/JNEUROSCI.4977-13.2014Google Scholar
Zabicki, A., de Haas, B., Zentgraf, K., et al. (2017). Imagined and executed actions in the human motor system: Testing neural similarity between execution and imagery of actions with a multivariate approach. Cerebral Cortex, 27(9), 45234536. doi:10.1093/cercor/bhw257Google Scholar
Zack, M., Poulos, C. X. & Woodford, T. M. (2006). Diazepam dose-dependently increases or decreases implicit priming of alcohol associations in problem drinkers. Alcohol and Alcoholism, 41(6), 604610. doi:10.1093/alcalc/agl076Google Scholar
Ziaee, S. S., Fadardi, J. S., Cox, W. M. & Yazdi, S. A. A. (2016). Effects of attention control training on drug abusers’ attentional bias and treatment outcome. Journal of Consulting and Clinical Psychology, 84(10), 861873. doi:10.1037/a0040290Google Scholar

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