, Volume 236, Issue 2, pp 709–721 | Cite as

No effect of attentional bias modification training in methamphetamine users receiving residential treatment

  • Andy C. Dean
  • Erika L. Nurmi
  • Scott J. Moeller
  • Nader Amir
  • Michelle Rozenman
  • Dara G. Ghahremani
  • Maritza Johnson
  • Robert Berberyan
  • Gerhard Hellemann
  • Ziwei Zhang
  • Edythe D. LondonEmail author
Original Investigation



Attentional bias toward drug-related stimuli is a feature of drug addiction that is linked to craving and drug-seeking behavior.


An attentional bias modification (ABM) program was tested in 42 methamphetamine-dependent clients (DSM-IV criteria) receiving residential treatment for their drug use. Participants were randomly assigned to one of two groups (N = 21 each), receiving 12 sessions of either computerized ABM training (designed to train attention away from methamphetamine stimuli 100% of the time) or an attentional control condition (designed to train attention away from methamphetamine stimuli 50% of the time). Outcome measures included attentional bias to methamphetamine-related stimuli on a probe detection task, self-reported craving, and preferences to view methamphetamine-related images on a Simulated Drug Choice Task. A subset of participants (N = 17) also underwent fMRI in a cue-induced craving paradigm.


Poor split-half reliability was observed for the probe detection task. Using this task, attentional bias toward methamphetamine-related stimuli was greater after training than at baseline, irrespective of group (p = 0.037). Spontaneous and cue-induced methamphetamine craving diminished with time (ps < 0.01), but ABM training did not influence these effects (group by time interactions, ps > 0.05). ABM training did not influence selection of methamphetamine-related pictures in the Simulated Drug Choice task (p > 0.05). In the fMRI assessment, cue-induced activation in the ventromedial prefrontal cortex was reduced over time, without an effect of ABM training.


ABM training did not improve several clinically relevant variables in treatment-seeking methamphetamine users. Additional research is needed to improve the measurement of attentional bias.


Stimulant Substance abuse Attentional bias Craving 



This work was supported by a grant from the National Institute on Drug Abuse [R21DA040156 (EDL); K01DA037452 (SJM)], the Thomas P. and Katherine K. Pike Chair in Addiction Studies (EDL), and the Marjorie Greene Family Trust.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

213_2018_5100_MOESM1_ESM.png (242 kb)
Supplementary Figure 1. fMRI activation in response to MA vs. neutral cues before and after training across treatment groups (N = 12). Displayed are slices from the t-statistic image from a one-sample non-parametric t-test on difference images (pre-post training) for all voxels, overlaid on the mean anatomical image (MPRAGE) across participants. Results were cluster corrected at a cluster-determining threshold of t > 2.17 (i.e., P < 0.01). Suprathreshold clusters include those within ventromedial prefrontal cortex, including medial orbitofrontal cortex. No clusters reached significance with the threshold of P < 0.001. Images are in MNI space displayed in radiological orientation (right = left). (PNG 242 kb)


  1. Ahmed SH (2010) Validation crisis in animal models of drug addiction: beyond non-disordered drug use toward drug addiction. Neurosci Biobehav Rev 35(2):172–184. Google Scholar
  2. Amir N, Beard C, Taylor CT, Klumpp H, Elias J, Burns M, Chen X (2009) Attention training in individuals with generalized social phobia: a randomized controlled trial. J Consult Clin Psychol 77(5):961–973. Google Scholar
  3. Ataya AF, Adams S, Mullings E, Cooper RM, Attwood AS, Munafo MR (2012) Internal reliability of measures of substance-related cognitive bias. Drug Alcohol Depend 121(1–2):148–151. Google Scholar
  4. Attwood AS, O’Sullivan H, Leonards U, Mackintosh B, Munafo MR (2008) Attentional bias training and cue reactivity in cigarette smokers. Addiction 103(11):1875–1882. Google Scholar
  5. Ballester J, Valentine G, Sofuoglu M (2017) Pharmacological treatments for methamphetamine addiction: current status and future directions. Expert Rev Clin Pharmacol 10(3):305–314. Google Scholar
  6. Banks ML, Hutsell BA, Schwienteck KL, Negus SS (2015) Use of preclinical drug vs. food choice procedures to evaluate candidate medications for cocaine addiction. Curr Treat Options Psychiatry 2(2):136–150. Google Scholar
  7. Beck AT (1967) Depression: clinical, experimental, and theoretical aspects. Hoeber Medical Division, Harper & Row, New YorkGoogle Scholar
  8. Brecht ML, Herbeck D (2014) Time to relapse following treatment for methamphetamine use: a long-term perspective on patterns and predictors. Drug Alcohol Depend 139:18–25. Google Scholar
  9. Brorson HH, Ajo Arnevik E, Rand-Hendriksen K, Duckert F (2013) Drop-out from addiction treatment: a systematic review of risk factors. Clin Psychol Rev 33(8):1010–1024. Google Scholar
  10. Carpenter KM, Schreiber E, Church S, McDowell D (2006) Drug Stroop performance: relationships with primary substance of use and treatment outcome in a drug-dependent outpatient sample. Addict Behav 31(1):174–181. Google Scholar
  11. Chase HW, Eickhoff SB, Laird AR, Hogarth L (2011) The neural basis of drug stimulus processing and craving: an activation likelihood estimation meta-analysis. Biol Psychiatry 70(8):785–793. Google Scholar
  12. Chiang SC, Chan HY, Chen CH, Sun HJ, Chang HJ, Chen WJ et al (2006) Recidivism among male subjects incarcerated for illicit drug use in Taiwan. Psychiatry Clin Neurosci 60(4):444–451. Google Scholar
  13. Christiansen P, Schoenmakers TM, Field M (2015) Less than meets the eye: reappraising the clinical relevance of attentional bias in addiction. Addict Behav 44:43–50. Google Scholar
  14. Cook R, Quinn B, Heinzerling K, Shoptaw S (2017) Dropout in clinical trials of pharmacological treatment for methamphetamine dependence: the role of initial abstinence. Addiction 112(6):1077–1085. Google Scholar
  15. Cox WM, Fadardi JS, Intriligator JM, Klinger E (2014) Attentional bias modification for addictive behaviors: clinical implications. CNS Spectr 19(3):215–224. Google Scholar
  16. Cox WM, Fadardi JS, Pothos EM (2006) The addiction-stroop test: theoretical considerations and procedural recommendations. Psychol Bull 132(3):443–476. Google Scholar
  17. Cox WM, Hogan LM, Kristian MR, Race JH (2002) Alcohol attentional bias as a predictor of alcohol abusers’ treatment outcome. Drug Alcohol Depend 68(3):237–243Google Scholar
  18. Cristea IA, Kok RN, Cuijpers P (2016) The effectiveness of cognitive bias modification interventions for substance addictions: a meta-analysis. PLoS One 11(9):e0162226. Google Scholar
  19. DeVito EE, Kiluk BD, Nich C, Mouratidis M, Carroll KM (2018) Drug Stroop: mechanisms of response to computerized cognitive behavioral therapy for cocaine dependence in a randomized clinical trial. Drug Alcohol Depend 183:162–168. Google Scholar
  20. Diaz-Batanero C, Dominguez-Salas S, Moraleda E, Fernandez-Calderon F, Lozano OM (2018) Attentional bias toward alcohol stimuli as a predictor of treatment retention in cocaine dependence and alcohol user patients. Drug Alcohol Depend 182:40–47. Google Scholar
  21. Eklund A, Dufort P, Villani M, Laconte S (2014) BROCCOLI: software for fast fMRI analysis on many-core CPUs and GPUs. Front Neuroinform 8:24. Google Scholar
  22. Eklund A, Nichols TE, Knutsson H (2016) Cluster failure: why fMRI inferences for spatial extent have inflated false-positive rates. Proc Natl Acad Sci U S A 113(28):7900–7905. Google Scholar
  23. Fadardi JS, Cox WM (2009) Reversing the sequence: reducing alcohol consumption by overcoming alcohol attentional bias. Drug Alcohol Depend 101(3):137–145. Google Scholar
  24. Field M, Christiansen P (2012) Commentary on, 'Internal reliability of measures of substance-related cognitive bias. Drug Alcohol Depend 124(3):189–190. Google Scholar
  25. Field M, Cox WM (2008) Attentional bias in addictive behaviors: a review of its development, causes, and consequences. Drug Alcohol Depend 97(1–2):1–20. Google Scholar
  26. Field M, Duka T, Eastwood B, Child R, Santarcangelo M, Gayton M (2007) Experimental manipulation of attentional biases in heavy drinkers: do the effects generalise? Psychopharmacology 192(4):593–608. Google Scholar
  27. Field M, Duka T, Tyler E, Schoenmakers T (2009a) Attentional bias modification in tobacco smokers. Nicotine Tob Res 11(7):812–822. Google Scholar
  28. Field M, Eastwood B (2005) Experimental manipulation of attentional bias increases the motivation to drink alcohol. Psychopharmacology 183(3):350–357. Google Scholar
  29. Field M, Marhe R, Franken IH (2014) The clinical relevance of attentional bias in substance use disorders. CNS Spectr 19(3):225–230. Google Scholar
  30. Field M, Mogg K, Mann B, Bennett GA, Bradley BP (2013) Attentional biases in abstinent alcoholics and their association with craving. Psychol Addict Behav 27(1):71–80. Google Scholar
  31. Field M, Munafo MR, Franken IH (2009b) A meta-analytic investigation of the relationship between attentional bias and subjective craving in substance abuse. Psychol Bull 135(4):589–607. Google Scholar
  32. Field M, Werthmann J, Franken I, Hofmann W, Hogarth L, Roefs A (2016) The role of attentional bias in obesity and addiction. Health Psychol 35(8):767–780. Google Scholar
  33. Friese M, Bargas-Avila J, Hofmann W, Wiers RW (2010) Alcohol-related memory structures predict eye movements for social drinkers with low executive control. Soc Psychol Personal Sci 1(2):143–151Google Scholar
  34. Goldstein RZ, Volkow ND (2011) Dysfunction of the prefrontal cortex in addiction: neuroimaging findings and clinical implications. Nat Rev Neurosci 12(11):652–669. Google Scholar
  35. Hakamata Y, Lissek S, Bar-Haim Y, Britton JC, Fox NA, Leibenluft E et al (2010) Attention bias modification treatment: a meta-analysis toward the establishment of novel treatment for anxiety. Biol Psychiatry 68(11):982–990. Google Scholar
  36. Hallion LS, Ruscio AM (2011) A meta-analysis of the effect of cognitive bias modification on anxiety and depression. Psychol Bull 137(6):940–958. Google Scholar
  37. Heatherton TF, Kozlowski LT, Frecker RC, Fagerstrom KO (1991) The Fagerstrom test for nicotine dependence: a revision of the Fagerstrom Tolerance Questionnaire. Br J Addict 86(9):1119–1127Google Scholar
  38. Hester R, Lee N, Pennay A, Nielsen S, Ferris J (2010) The effects of modafinil treatment on neuropsychological and attentional bias performance during 7-day inpatient withdrawal from methamphetamine dependence. Exp Clin Psychopharmacol 18(6):489–497. Google Scholar
  39. Kappenman ES, Farrens JL, Luck SJ, Proudfit GH (2014) Behavioral and ERP measures of attentional bias to threat in the dot-probe task: poor reliability and lack of correlation with anxiety. Front Psychol 5:1368. Google Scholar
  40. Kennedy AP, Gross RE, Ely T, Drexler KP, Kilts CD (2014) Clinical correlates of attentional bias to drug cues associated with cocaine dependence. Am J Addict 23(5):478–484. Google Scholar
  41. Kerst WF, Waters AJ (2014) Attentional retraining administered in the field reduces smokers’ attentional bias and craving. Health Psychol 33(10):1232–1240. Google Scholar
  42. Koster EH, Crombez G, Verschuere B, Van Damme S, Wiersema JR (2006) Components of attentional bias to threat in high trait anxiety: facilitated engagement, impaired disengagement, and attentional avoidance. Behav Res Ther 44(12):1757–1771. Google Scholar
  43. Kuhn S, Gallinat J (2011) Common biology of craving across legal and illegal drugs—a quantitative meta-analysis of cue-reactivity brain response. Eur J Neurosci 33(7):1318–1326. Google Scholar
  44. Lang PJ (2005) International affective picture system (IAPS): affective ratings of pictures and instruction manual. In: Technical Report A-8. University of Florida, GainsvilleGoogle Scholar
  45. Lopes FM, Pires AV, Bizarro L (2014) Attentional bias modification in smokers trying to quit: a longitudinal study about the effects of number of sessions. J Subst Abus Treat 47(1):50–57. Google Scholar
  46. MacLeod C, Mathews A (1988) Anxiety and the allocation of attention to threat. Q J Exp Psychol A 40(4):653–670Google Scholar
  47. MacLeod C, Mathews A, Tata P (1986) Attentional bias in emotional disorders. J Abnorm Psychol 95(1):15–20Google Scholar
  48. Marhe R, Luijten M, van de Wetering BJ, Smits M, Franken IH (2013) Individual differences in anterior cingulate activation associated with attentional bias predict cocaine use after treatment. Neuropsychopharmacology 38(6):1085–1093. Google Scholar
  49. Marissen MA, Franken IH, Waters AJ, Blanken P, van den Brink W, Hendriks VM (2006) Attentional bias predicts heroin relapse following treatment. Addiction 101(9):1306–1312. Google Scholar
  50. Mayer AR, Wilcox CE, Dodd AB, Klimaj SD, Dekonenko CJ, Claus ED, Bogenschutz M (2016) The efficacy of attention bias modification therapy in cocaine use disorders. Am J Drug Alcohol Abuse 42(4):459–468. Google Scholar
  51. McGeary JE, Meadows SP, Amir N, Gibb BE (2014) Computer-delivered, home-based, attentional retraining reduces drinking behavior in heavy drinkers. Psychol Addict Behav 28(2):559–562. Google Scholar
  52. McKetin, R., Najman, J. M., Baker, A. L., Lubman, D. I., Dawe, S., Ali, R., . . . Mamun, A. (2012). Evaluating the impact of community-based treatment options on methamphetamine use: findings from the Methamphetamine Treatment Evaluation Study (MATES). Addiction, 107(11), 1998–2008. doi: Google Scholar
  53. Moeller SJ, Maloney T, Parvaz MA, Alia-Klein N, Woicik PA, Telang F et al (2010) Impaired insight in cocaine addiction: laboratory evidence and effects on cocaine-seeking behaviour. Brain 133(Pt 5):1484–1493. Google Scholar
  54. Moeller SJ, Maloney T, Parvaz MA, Dunning JP, Alia-Klein N, Woicik PA et al (2009) Enhanced choice for viewing cocaine pictures in cocaine addiction. Biol Psychiatry 66(2):169–176. Google Scholar
  55. Moeller SJ, Okita K, Robertson CL, Ballard ME, Konova AB, Goldstein RZ et al (2018) Low striatal dopamine D2-type receptor availability is linked to simulated drug choice in methamphetamine users. Neuropsychopharmacology 43(4):751–760. Google Scholar
  56. Moeller SJ, Stoops WW (2015) Cocaine choice procedures in animals, humans, and treatment-seekers: can we bridge the divide? Pharmacol Biochem Behav 138:133–141. Google Scholar
  57. Nichols TE, Holmes AP (2002) Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum Brain Mapp 15(1):1–25Google Scholar
  58. Powell J, Dawkins L, West R, Powell J, Pickering A (2010) Relapse to smoking during unaided cessation: clinical, cognitive and motivational predictors. Psychopharmacology 212(4):537–549. Google Scholar
  59. Schoenmakers T, Wiers RW, Jones BT, Bruce G, Jansen AT (2007) Attentional re-training decreases attentional bias in heavy drinkers without generalization. Addiction 102(3):399–405. Google Scholar
  60. Schoenmakers TM, de Bruin M, Lux IF, Goertz AG, Van Kerkhof DH, Wiers RW (2010) Clinical effectiveness of attentional bias modification training in abstinent alcoholic patients. Drug Alcohol Depend 109(1–3):30–36. Google Scholar
  61. 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. J Clin Psychiatry, 59 Suppl 20, 22–33;quiz 34–57Google Scholar
  62. Smith SM, Nichols TE (2009) Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference. Neuroimage 44(1):83–98. Google Scholar
  63. Snelleman M, Schoenmakers TM, van de Mheen D (2015) Attentional bias and approach/avoidance tendencies do not predict relapse or time to relapse in alcohol dependency. Alcohol Clin Exp Res 39(9):1734–1739. Google Scholar
  64. Substance Abuse and Mental Health Services Administration. (2013). Results from the 2012 National Survey on Drug Use and Health: summary of National Findings NSDUH Series H-46, HHS. . Rockville, MDGoogle Scholar
  65. Sussner BD, Smelson DA, Rodrigues S, Kline A, Losonczy M, Ziedonis D (2006) The validity and reliability of a brief measure of cocaine craving. Drug Alcohol Depend 83(3):233–237. Google Scholar
  66. UNODC (2017) World drug report. United Nations PublicationGoogle Scholar
  67. Waechter S, Nelson AL, Wright C, Hyatt A, Oakman J (2014) Measuring attentional bias to threat: reliability of dot probe and eye movement indices. Cogn Ther Res 38(3):313–333. Google Scholar
  68. Waters H, Green MW (2003) A demonstration of attentional bias, using a novel dual task paradigm, towards clinically salient material in recovering alcohol abuse patients? Psychol Med 33(3):491–498Google Scholar
  69. Wechsler, D. (2001). Wechsler test of adult reading: WTAR. The psychological corporation, San Antonio, TXGoogle Scholar
  70. Wiers RW, Boffo M, Field M (2018) What’s in a trial? On the importance of distinguishing between experimental lab studies and randomized controlled trials: the case of cognitive bias modification and alcohol use disorders. J Stud Alcohol Drugs 79(3):333–343Google Scholar
  71. Wiers RW, Gladwin TE, Hofmann W, Salemink E, Ridderinkhof RK (2013) Cognitive bias modification and cognitive control training in addiction and related psychopathology: mechanisms, clinical perspectives, and ways forward. Clin Psychol Sci 1(2):192–212Google Scholar
  72. Winkler AM, Ridgway GR, Webster MA, Smith SM, Nichols TE (2014) Permutation inference for the general linear model. Neuroimage 92:381–397. Google Scholar
  73. Woolrich MW, Ripley BD, Brady M, Smith SM (2001) Temporal autocorrelation in univariate linear modeling of FMRI data. Neuroimage 14(6):1370–1386Google Scholar
  74. Xu J, Moeller S, Auerbach EJ, Strupp J, Smith SM, Feinberg DA et al (2013) Evaluation of slice accelerations using multiband echo planar imaging at 3T. NeuroImage 83:991–1001. Google Scholar
  75. Zorick T, Sevak RJ, Miotto K, Shoptaw S, Swanson AN, Clement C et al (2009) Pilot safety evaluation of varenicline for the treatment of methamphetamine dependence. J Exp Pharmacol 2010(2):13–18Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Andy C. Dean
    • 1
    • 2
  • Erika L. Nurmi
    • 1
  • Scott J. Moeller
    • 3
  • Nader Amir
    • 4
  • Michelle Rozenman
    • 1
  • Dara G. Ghahremani
    • 1
  • Maritza Johnson
    • 1
  • Robert Berberyan
    • 1
  • Gerhard Hellemann
    • 1
  • Ziwei Zhang
    • 1
  • Edythe D. London
    • 1
    • 2
    • 5
    Email author
  1. 1.Department of Psychiatry and Biobehavioral Sciences, UCLA Semel Institute for NeuroscienceDavid Geffen School of MedicineLos AngelesUSA
  2. 2.Brain Research InstituteDavid Geffen School of MedicineLos AngelesUSA
  3. 3.Department of PsychiatryStony Brook University School of MedicineStony BrookUSA
  4. 4.Department of PsychologySan Diego State UniversitySan DiegoUSA
  5. 5.Department of Molecular and Medical PharmacologyDavid Geffen School of MedicineLos AngelesUSA

Personalised recommendations