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Cognitive deficits in people with stimulant use disorders

Verdejo-Garcia, Antonio, Rubenis, Adam J.·2020·Cognition and Addiction
DOI 10.1016/b978-0-12-815298-0.00011-3
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  1. Ben-Shahar, 2012, Extended access to cocaine self-administration results in reduced glutamate function within the medial prefrontal cortex, Addict. Biol., 17, 746, 10.1111/j.1369-1600.2011.00428.x · DOI
  2. Adinoff, 2016, Decision-making processes as predictors of relapse and subsequent use in stimulant-dependent patients, Am. J. Drug Alcohol Abuse, 42, 88, 10.3109/00952990.2015.1106550 · DOI
  3. Aharonovich, 2006, Cognitive deficits predict low treatment retention in cocaine dependent patients, Drug Alcohol Depend., 81, 313, 10.1016/j.drugalcdep.2005.08.003 · DOI · Paper page
  4. Almeida, 2017, Attention and memory deficits in crack-cocaine users persist over four weeks of abstinence, J. Subst. Abus. Treat., 81, 73, 10.1016/j.jsat.2017.08.002 · DOI
  5. Ashok, 2017, Association of stimulant use with dopaminergic alterations in users of cocaine, amphetamine, or methamphetamine: a systematic review and meta-analysis, JAMA Psychiatry, 74, 511, 10.1001/jamapsychiatry.2017.0135 · DOI · Paper page
  6. Ben-Shahar, 2013, Deficits in ventromedial prefrontal cortex group 1 metabotropic glutamate receptor function mediate resistance to extinction during protracted withdrawal from an extensive history of cocaine self-administration, J. Neurosci., 33, 495, 10.1523/JNEUROSCI.3710-12.2013 · DOI
  7. Bolla, 2004, Prefrontal cortical dysfunction in abstinent cocaine abusers, J. Neuropsychiatry Clin. Neurosci., 16, 456, 10.1176/jnp.16.4.456 · DOI
  8. Bonci, 2003, The dopamine-containing neuron: maestro or simple musician in the orchestra of addiction?, Trends Pharmacol. Sci., 24, 172, 10.1016/S0165-6147(03)00068-3 · DOI
  9. Briand, 2008, Persistent alterations in cognitive function and prefrontal dopamine D2 receptors following extended, but not limited, access to self-administered cocaine, Neuropsychopharmacology, 33, 2969, 10.1038/npp.2008.18 · DOI
  10. Cadet, 2013, Epigenetics of methamphetamine-induced changes in glutamate function, Neuropsychopharmacology, 38, 248, 10.1038/npp.2012.169 · DOI
  11. Carroll, 2011, Cognitive function and treatment response in a randomized clinical trial of computer-based training in cognitive-behavioral therapy, Subst. Use Misuse, 46, 23, 10.3109/10826084.2011.521069 · DOI
  12. Castellano, 2015, Facial emotion recognition in alcohol and substance use disorders: a meta-analysis, Neurosci. Biobehav. Rev., 59, 147, 10.1016/j.neubiorev.2015.11.001 · DOI
  13. Chang, 2007, Structural and metabolic brain changes in the striatum associated with methamphetamine abuse, Addiction, 102, 16, 10.1111/j.1360-0443.2006.01782.x · DOI
  14. Chen, 2015, Predictors of relapse and dropout during a 12-week relapse prevention program for methamphetamine users, J. Psychoact. Drugs, 47, 317, 10.1080/02791072.2015.1071447 · DOI
  15. Cherner, 2010, Methamphetamine use parameters do not predict neuropsychological impairment in currently abstinent dependent adults, Drug Alcohol Depend., 106, 154, 10.1016/j.drugalcdep.2009.08.010 · DOI
  16. Crocker, 2017, Enduring changes in brain metabolites and executive functioning in abstinent cocaine users, Drug Alcohol Depend., 178, 435, 10.1016/j.drugalcdep.2017.04.034 · DOI
  17. Czermainski, 2017, Assessment of inhibitory control in crack and/or cocaine users: a systematic review, Trends Psychiatry Psychother., 39, 216, 10.1590/2237-6089-2016-0043 · DOI
  18. Dean, 2009, Predicting adherence to treatment for methamphetamine dependence from neuropsychological and drug use variables, Drug Alcohol Depend., 105, 48, 10.1016/j.drugalcdep.2009.06.008 · DOI
  19. Dean, 2013, An evaluation of the evidence that methamphetamine abuse causes cognitive decline in humans, Neuropsychopharmacology, 38, 259, 10.1038/npp.2012.179 · DOI
  20. Degenhardt, 2014, The global epidemiology and burden of psychostimulant dependence: findings from the Global Burden of Disease Study 2010, Drug Alcohol Depend., 137, 36, 10.1016/j.drugalcdep.2013.12.025 · DOI
  21. Domínguez-Salas, 2016, Impact of general cognition and executive function deficits on addiction treatment outcomes: systematic review and discussion of neurocognitive pathways, Neurosci. Biobehav. Rev., 71, 772, 10.1016/j.neubiorev.2016.09.030 · DOI
  22. Donovan, 2012, Primary outcome indices in illicit drug dependence treatment research: systematic approach to selection and measurement of drug use end-points in clinical trials, Addiction, 107, 694, 10.1111/j.1360-0443.2011.03473.x · DOI
  23. Fagan, 2015, The effect of cognitive functioning on treatment attendance and adherence in comorbid bipolar disorder and cocaine dependence, J. Subst. Abus. Treat., 49, 15, 10.1016/j.jsat.2014.06.008 · DOI
  24. Fernandez-Serrano, 2010, Neuropsychological consequences of alcohol and drug abuse on different components of executive functions, J. Psychopharmacol., 24, 1317, 10.1177/0269881109349841 · DOI
  25. Fernández-Serrano, 2011, What are the specific vs. generalized effects of drugs of abuse on neuropsychological performance?, Neurosci. Biobehav. Rev., 35, 377, 10.1016/j.neubiorev.2010.04.008 · DOI · Paper page
  26. Fox, 2009, Elevated cortisol and learning and memory deficits in cocaine-dependent individuals: relationship to relapse outcomes, Psychoneuroendocrinology, 34, 1198, 10.1016/j.psyneuen.2009.03.007 · DOI
  27. Garavan, 2008, Acute effects of cocaine on the neurobiology of cognitive control, Phil. Trans. Biol. Sci., 363, 3267, 10.1098/rstb.2008.0106 · DOI
  28. Grant, 2016, Epidemiology of DSM-5 drug use disorder: results from the national epidemiologic survey on alcohol and related conditions–III, JAMA Psychiatry, 73, 39, 10.1001/jamapsychiatry.2015.2132 · DOI · Paper page
  29. Hall, 2017, Neuropsychological comparisons of cocaine versus methamphetamine users: a research synthesis and meta-analysis, Am. J. Drug Alcohol Abuse, 44, 1
  30. Harris, 2014, Dimensions of impulsive behavior and treatment outcomes for adolescent smokers, Exp. Clin. Psychopharmacol, 22, 57, 10.1037/a0034403 · DOI
  31. He, 2006, Consequences of paternal cocaine exposure in mice, Neurotoxicol. Teratol., 28, 198, 10.1016/j.ntt.2005.12.003 · DOI
  32. Iudicello, 2010, Longer term improvement in neurocognitive functioning and affective distress among methamphetamine users who achieve stable abstinence, J. Clin. Exp. Neuropsychol., 32, 704, 10.1080/13803390903512637 · DOI
  33. Jayanthi, 2014, Methamphetamine downregulates striatal glutamate receptors via diverse epigenetic mechanisms, Biol. Psychiatry, 76, 47, 10.1016/j.biopsych.2013.09.034 · DOI
  34. Jovanovski, 2005, Neurocognitive deficits in cocaine users: a quantitative review of the evidence, J. Clin. Exp. Neuropsychol., 27, 189, 10.1080/13803390490515694 · DOI
  35. Kasanetz, 2013, Prefrontal synaptic markers of cocaine addiction-like behavior in rats, Mol. Psychiatry, 18, 729, 10.1038/mp.2012.59 · DOI
  36. Kiluk, 2013, Smokers versus snorters: do treatment outcomes differ according to route of cocaine administration?, Exp. Clin. Psychopharmacol, 21, 490, 10.1037/a0034173 · DOI
  37. Kish, 2009, Brain serotonin transporter in human methamphetamine users, Psychopharmacology, 202, 649, 10.1007/s00213-008-1346-x · DOI
  38. Koob, 2007, Stress, dysregulation of drug reward pathways, and the transition to drug dependence, Am. J. Psychiatry, 164, 1149, 10.1176/appi.ajp.2007.05030503 · DOI · Paper page
  39. Koob, 2010, Neurocircuitry of addiction, Neuropsychopharmacology, 35, 217, 10.1038/npp.2009.110 · DOI · Paper page
  40. Li, 2015, Multiple faces of BDNF in cocaine addiction, Behav. Brain Res., 279, 240, 10.1016/j.bbr.2014.11.018 · DOI
  41. Lopes, 2017, Distinct cognitive performance and patterns of drug use among early and late onset cocaine users, Addict. Behav., 73, 41, 10.1016/j.addbeh.2017.04.013 · DOI
  42. Luscher, 2016, The emergence of a circuit model for addiction, Annu. Rev. Neurosci., 39, 257, 10.1146/annurev-neuro-070815-013920 · DOI
  43. McClure, 2014, A dual-systems perspective on addiction: contributions from neuroimaging and cognitive training, Ann. N. Y. Acad. Sci., 1327, 62, 10.1111/nyas.12561 · DOI
  44. McReynolds, 2014, Beta-2 adrenergic receptors mediate stress-evoked reinstatement of cocaine-induced conditioned place preference and increases in CRF mRNA in the bed nucleus of the stria terminalis in mice, Psychopharmacology, 231, 3953, 10.1007/s00213-014-3535-0 · DOI
  45. Mounteney, 2016, The drug situation in Europe: an overview of data available on illicit drugs and new psychoactive substances from European monitoring in 2015, Addiction, 111, 34, 10.1111/add.13056 · DOI
  46. Nejtek, 2013, Iowa Gambling Task scores predict future drug use in bipolar disorder outpatients with stimulant dependence, Psychiatr. Res., 210, 871, 10.1016/j.psychres.2013.08.021 · DOI
  47. Nestler, 2014, Epigenetic mechanisms of drug addiction, Neuropharmacology, 76, 259, 10.1016/j.neuropharm.2013.04.004 · DOI
  48. Noonan, 2010, Reduction of adult hippocampal neurogenesis confers vulnerability in an animal model of cocaine addiction, J. Neurosci., 30, 304, 10.1523/JNEUROSCI.4256-09.2010 · DOI
  49. Novikova, 2008, Maternal cocaine administration in mice alters DNA methylation and gene expression in hippocampal neurons of neonatal and prepubertal offspring, PLoS One, 3, 10.1371/journal.pone.0001919 · DOI
  50. Oh, 2005, Shape changes of the corpus callosum in abstinent methamphetamine users, Neurosci. Lett., 384, 76, 10.1016/j.neulet.2005.04.082 · DOI
  51. Panenka, 2013, Methamphetamine use: a comprehensive review of molecular, preclinical and clinical findings, Drug Alcohol Depend., 129, 167, 10.1016/j.drugalcdep.2012.11.016 · DOI · Paper page
  52. Patterson, 2010, Working memory deficits predict short-term smoking resumption following brief abstinence, Drug Alcohol Depend., 106, 61, 10.1016/j.drugalcdep.2009.07.020 · DOI
  53. Paus, 2008, Why do many psychiatric disorders emerge during adolescence?, Nat. Rev. Neurosci., 9, 947, 10.1038/nrn2513 · DOI · Paper page
  54. Peacock, 2018, Global statistics on alcohol, tobacco and illicit drug use: 2017 status report, Addiction, 10.1111/add.14234 · DOI
  55. Potvin, 2014, Cocaine and cognition: a systematic quantitative review, J. Addict. Med., 8, 368, 10.1097/ADM.0000000000000066 · DOI · Paper page
  56. Potvin, 2018, Cognitive deficits in individuals with methamphetamine use disorder: a meta-analysis, Addict. Behav., 80, 154, 10.1016/j.addbeh.2018.01.021 · DOI
  57. Powell, 2010, Relapse to smoking during unaided cessation: clinical, cognitive and motivational predictors, Psychopharmacology, 212, 537, 10.1007/s00213-010-1975-8 · DOI
  58. Preller, 2014, Functional changes of the reward system underlie blunted response to social gaze in cocaine users, Proc. Natl. Acad. Sci. U.S.A., 111, 2842, 10.1073/pnas.1317090111 · DOI · Paper page
  59. Robison, 2011, Transcriptional and epigenetic mechanisms of addiction, Nat. Rev. Neurosci., 12, 623, 10.1038/nrn3111 · DOI · Paper page
  60. Rubenis, 2017, Working memory predicts methamphetamine hair concentration over the course of treatment: moderating effect of impulsivity and implications for dual-systems model, Addict. Biol.
  61. Rubenis, 2018, Impulsivity predicts poorer improvement in quality of life during early treatment for people with methamphetamine dependence, Addiction, 113, 668, 10.1111/add.14058 · DOI
  62. Schulte, 2014, Recovery of neurocognitive functions following sustained abstinence after substance dependence and implications for treatment, Clin. Psychol. Rev., 34, 531, 10.1016/j.cpr.2014.08.002 · DOI
  63. Scott, 2007, Neurocognitive effects of methamphetamine: a critical review and meta-analysis, Neuropsychol. Rev., 17, 275, 10.1007/s11065-007-9031-0 · DOI
  64. Shibasaki, 2011, L-type voltage-dependent calcium channels facilitate acetylation of histone H3 through PKCγ phosphorylation in mice with methamphetamine-induced place preference, J. Neurochem., 118, 1056, 10.1111/j.1471-4159.2011.07387.x · DOI
  65. Shoptaw, 2014, Commentary on Gowin et al. (2014): brain is behavior—methamphetamine dependence and recovery, Addiction, 109, 248, 10.1111/add.12442 · DOI
  66. Smith, 2004, Cocaine-and amphetamine-regulated transcript activates the hypothalamic-pituitary-adrenal axis through a corticotropin-releasing factor receptor-dependent mechanism, Endocrinology, 145, 5202, 10.1210/en.2004-0708 · DOI
  67. Smith, 2014, Deficits in behavioural inhibition in substance abuse and addiction: a meta-analysis, Drug Alcohol Depend., 145, 1, 10.1016/j.drugalcdep.2014.08.009 · DOI · Paper page
  68. Spencer, 2016, The good and bad news about glutamate in drug addiction, J. Psychopharmacol., 30, 1095, 10.1177/0269881116655248 · DOI
  69. Stevens, 2014, Impulsivity as a vulnerability factor for poor addiction treatment outcomes: a review of neurocognitive findings among individuals with substance use disorders, J. Subst. Abus. Treat., 47, 58, 10.1016/j.jsat.2014.01.008 · DOI
  70. Streeter, 2008, Performance on the Stroop predicts treatment compliance in cocaine-dependent individuals, Neuropsychopharmacology, 33, 827, 10.1038/sj.npp.1301465 · DOI
  71. Sudai, 2011, High cocaine dosage decreases neurogenesis in the hippocampus and impairs working memory, Addict. Biol., 16, 251, 10.1111/j.1369-1600.2010.00241.x · DOI
  72. Tendilla-Beltrán, 2016, The effects of amphetamine exposure on juvenile rats on the neuronal morphology of the limbic system at prepubertal, pubertal and postpubertal ages, J. Chem. Neuroanat., 77, 68, 10.1016/j.jchemneu.2016.05.004 · DOI
  73. Thompson, 2004, Structural abnormalities in the brains of human subjects who use methamphetamine, J. Neurosci., 24, 6028, 10.1523/JNEUROSCI.0713-04.2004 · DOI
  74. Tobias, 2010, White-matter abnormalities in brain during early abstinence from methamphetamine abuse, Psychopharmacology, 209, 13, 10.1007/s00213-009-1761-7 · DOI
  75. Turner, 2009, Measures of cognitive functioning as predictors of treatment outcome for cocaine dependence, J. Subst. Abus. Treat., 37, 328, 10.1016/j.jsat.2009.03.009 · DOI
  76. Verdejo-Garcıa, 2005, Differential effects of MDMA, cocaine, and cannabis use severity on distinctive components of the executive functions in polysubstance users: a multiple regression analysis, Addict. Behav., 30, 89, 10.1016/j.addbeh.2004.04.015 · DOI
  77. Verdejo-Garcia, 2017, Neuroclinical assessment of addiction needs to incorporate decision-making measures and ecological validity, Biol. Psychiatry, 81, e53, 10.1016/j.biopsych.2016.07.015 · DOI
  78. Verdejo-Garcia, 2007, The differential relationship between cocaine use and marijuana use on decision-making performance over repeat testing with the Iowa Gambling Task, Drug Alcohol Depend., 90, 2, 10.1016/j.drugalcdep.2007.02.004 · DOI
  79. Verdejo-García, 2007, Strategic self-regulation, decision-making and emotion processing in poly-substance abusers in their first year of abstinence, Drug Alcohol Depend., 86, 139, 10.1016/j.drugalcdep.2006.05.024 · DOI
  80. Verdejo-Garcia, 2014, Decision-making impairment predicts 3-month hair-indexed cocaine relapse, Psychopharmacology, 231, 4179, 10.1007/s00213-014-3563-9 · DOI
  81. Vergara-Moragues, 2017, Association between executive function and outcome measure of treatment in therapeutic community among cocaine dependent individuals, J. Subst. Abus. Treat., 78, 48, 10.1016/j.jsat.2017.04.014 · DOI
  82. Vonmoos, 2013, Differences in self-reported and behavioral measures of impulsivity in recreational and dependent cocaine users, Drug Alcohol Depend., 133, 61, 10.1016/j.drugalcdep.2013.05.032 · DOI
  83. Vonmoos, 2014, Cognitive impairment in cocaine users is drug-induced but partially reversible: evidence from a longitudinal study, Neuropsychopharmacology, 39, 2200, 10.1038/npp.2014.71 · DOI
  84. Wang, 2000, Chronic methamphetamine exposure decreases high affinity uptake function in norepinephrine afferents in the cerebellar cortex: an electrophysiological and electrochemical study, Neuropharmacology, 39, 2112, 10.1016/S0028-3908(00)00021-6 · DOI
  85. Winstanley, 2009, ΔFosB induction in orbitofrontal cortex potentiates locomotor sensitization despite attenuating the cognitive dysfunction caused by cocaine, Pharmacol. Biochem. Behav., 93, 278, 10.1016/j.pbb.2008.12.007 · DOI
  86. Wolf, 2010, The Bermuda Triangle of cocaine-induced neuroadaptations, Trends Neurosci., 33, 391, 10.1016/j.tins.2010.06.003 · DOI
  87. Zhao, 2015, Prenatal cocaine exposure impairs cognitive function of progeny via insulin growth factor II epigenetic regulation, Neurobiol. Dis., 82, 54, 10.1016/j.nbd.2015.05.014 · DOI

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Authors
Verdejo-Garcia, A., & Rubenis, A. J.
ORCID
Rubenis, Adam J.
Venue
Cognition and Addiction
Publisher
Elsevier
Published
2020
Pages
155-163
DOI
10.1016/b978-0-12-815298-0.00011-3
OpenAlex
W2979040017
Cited by
9
References
7
Citations by year
2026: 1 · 2025: 3 · 2024: 2 · 2023: 2 · 2022: 1
FWCI
0.93
Type
book chapter
Language
en
Open access
closed
Licence
Locations
Elsevier eBooks (publishedVersion)
Topics
  • Health Sciences › Medicine › Epidemiology › Substance Abuse Treatment and Outcomes
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
  • Social Sciences › Psychology › Clinical Psychology › Historical and Modern Theater Studies
Keywords
stimulant use disorder, cocaine dependence, methamphetamine dependence, cognitive impairment, attention, verbal memory, working memory, impulsivity, executive function, social cognition, abstinence, treatment outcome prediction, cognitive behavioral therapy, drug relapse, decision-making

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