A methodological checklist for fMRI drug cue reactivity studies: development and expert consensus

Qiang Li, Hamed Ekhtiari, Mohsen Ebrahimi, Arshiya Sangchooli, Mehran Zare-Bidoky, Xiaochu Zhang, Amy C. Janes, Marc J. Kaufman, Jason A. Oliver, James J. Prisciandaro, Torsten Wüstenberg, Raymond F. Anton, Patrick Bach, Alex Baldacchino, Anne Beck, James M. Bjork, Judson Brewer, Anna Rose Childress, Eric D. Claus, Kelly E. Courtney, Francesca M. Filbey, Dara G. Ghahremani, Peyman Ghobadi Azbari, Rita Z. Goldstein, Anna E. Goudriaan, Erica N. Grodin, J. Paul Hamilton, Colleen A. Hanlon, Peyman Hassani-Abharian, Andreas Heinz, Jane E. Joseph, Falk Kiefer, Arash Khojasteh Zonoozi, Hedy Kober, Rayus Kuplicki, Edythe D. London, Joseph McClernon, Hamid R. Noori, Max M. Owens, Martin P. Paulus, Irene Perini, Marc Potenza, Stéphane Potvin, Lara Ray, Joseph P. Schacht, Dongju Seo, Rajita Sinha, Michael N. Smolka, Rainer Spanagel, Vaughn R. Steele, Elliot A. Stein, Sabine Steins-Loeber, Susan F. Tapert, Antonio Verdejo-Garcia, Sabine Vollstädt-Klein, Reagan R. Wetherill, Stephen J. Wilson, Katie Witkiewitz, Kai Yuan, Anna Zilverstand

Published: 2022-02-03 DOI: 10.1038/s41596-021-00649-4

Co-fractionation–mass spectrometry to characterize native mitochondrial protein assemblies in mammalian neurons and brain

Simultaneously measuring the methylation of parent and daughter strands of replicated DNA at the single-molecule level by Hammer-seq

The Nodewalk assay to quantitate chromatin fiber interactomes in very small cell populations

Nondestructive production of exosomes loaded with ultrathin palladium nanosheets for targeted bio-orthogonal catalysis

An optimized culture system for efficient derivation of porcine expanded potential stem cells from preimplantation embryos and by reprogramming somatic cells

References

Cue reactivity is one of the most frequently used paradigms in functional magnetic resonance imaging (fMRI) studies ofsubstance use disorders (SUDs). Although there have been promising results elucidating the neurocognitive mechanisms of SUDs and SUD tre
Introduction
Methods
Results
Discussion
Conclusion and future directions
References
ACKNOWLEDGMENTS
ACKNOWLEDGMENTS

Hasson, F., Keeney, S. & McKenna, H. Research guidelines for the Delphi survey technique. J. Adv. Nurs 32, 1008–1015 (2000).
Ekhtiari, H. Methodological Checklist for fMRI Drug Cue Reactivity Studies: Development and Consensus. Accessed 27 Jan 2020. https://osf.io/gwrh6/ (2020).
Degenhardt, L. et al. The global burden of disease attributable to alcohol and drug use in 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Psychiatry 5, 987–1012 (2018).
Ekhtiari, H. et al. Functional neuroimaging for addiction medicine: from mechanisms to practical considerations. Prog. Brain Res 224, 129–153 (2016).
Moeller, S. J. & Paulus, M. P. Toward biomarkers of the addicted human brain: using neuroimaging to predict relapse and sustained abstinence in substance use disorder. Prog. Neuropsychopharmacol. Biol. Psychiatry 80, 143–154 (2018).
Ekhtiari, H. et al. Neuroscience of drug craving for addiction medicine: from circuits to therapies. Prog. Brain Res 223, 115–141 (2016).
Ekhtiari, H. & ACRI Secretariat. A systematic review on fMRI drug cue reactivity studies (OSF, 2020). https://osf.io/eb972/ (2020).
Bough, K. J. et al. Biomarkers for the development of new medications for cocaine dependence. Neuropsychopharmacology 39, 202–219 (2014).
Carmichael, O. et al. The role of fMRI in drug development. Drug Discov. Today 23, 333–348 (2018).
Zilverstand, A. et al. Neuroimaging impaired response inhibition and salience attribution in human drug addiction: a systematic review. Neuron 98, 886–903 (2018).
Cremers, H. R., Wager, T. D. & Yarkoni, T. The relation between statistical power and inference in fMRI. PloS One 12, e0184923 (2017).
Turner, B. O. et al. Small sample sizes reduce the replicability of task-based fMRI studies. Commun. Biol 1, 62 (2018).
Liu, T. T. Noise contributions to the fMRI signal: An overview. Neuroimage 143, 141–151 (2016).
Elliott, M. L. et al. What Is the test-retest reliability of common task-functional MRI measures? New empirical evidence and a meta-analysis. Psychol. Sci 31, 792–806 (2020).
Korucuoglu, O. et al. Test-retest reliability of fMRI-measured brain activity during decision making under risk. NeuroImage 214, 116759 (2020).
Kragel, P. et al. Functional MRI can be highly reliable, but it depends on what you measure: a commentary on Elliott et al. (2020). Psychol. Sci. 32, 622–626 (2021).
Casey, B. et al. The Adolescent Brain Cognitive Development (ABCD) study: imaging acquisition across 21 sites. Dev. Cogn. Neurosci. 32, 43–54 (2018).
Jasinska, A. J. et al. Factors modulating neural reactivity to drug cues in addiction: a survey of human neuroimaging studies. Neurosci. Biobehav. Rev 38, 1–16 (2014).
Billieux, J. et al. The Geneva Appetitive Alcohol Pictures (GAAP): development and preliminary validation. Eur. Addict. Res. 17, 225–230 (2011).
Holla, B. et al. Visual image-induced craving for ethanol (VICE): development, validation, and a pilot fMRI study. Indian J. Psychol. Med. 36, 164–169 (2014).
Ekhtiari, H. et al. Methamphetamine and Opioid Cue Database (MOCD): development and validation. Drug Alcohol Depend. 209, 107941 (2020).
Khazaal, Y., Zullino, D. & Billieux, J. The Geneva Smoking Pictures: development and preliminary validation. Eur. Addict. Res 18, 103–109 (2012).
Lang, P. J., Bradley, M. M. & Cuthbert, B. N. International Affective Picture System (IAPS): Affective Ratings of Pictures and Instruction Manual. (NIMH, Center for the Study of Emotion & Attention, 2005).
Lindquist, M. Neuroimaging results altered by varying analysis pipelines. Nature 582, 36–37 (2020).
Nichols, T. E. et al. Best practices in data analysis and sharing in neuroimaging using MRI. Nat. Neurosci 20, 299–303 (2017).
Esteban, O. et al. Analysis of task-based functional MRI data preprocessed with fMRIPrep. Nat. Protoc 15, 2186–2202 (2020).
Bossuyt, P. M. et al. STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies. BMJ 351, h5527 (2015).
Collins, G. S. et al. Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD): The TRIPOD Statement. Circulation 131, 211–219 (2015).
Gagnier, J. J. et al. The CARE guidelines: consensus-based clinical case reporting guideline development. J. Med. Case Rep 7, 223 (2013).
Moher, D. et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med 6, e1000097 (2009).
Bossuyt, P. M. et al. STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies. Clin. Chem 61, 1446–1452 (2015).
Collins, G. S., Reitsma, J. B., Altman, D. G. & Moons, K. G. Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): the TRIPOD statement. Br. J. Surg 102, 148–158 (2015).
Moher, D. et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Int. J. Surg 8, 336–341 (2010).
O’Brien, B. C. et al. Standards for reporting qualitative research: a synthesis of recommendations. Acad. Med. 89, 1245–1251 (2014).
Schulz, K. F., Altman, D. G. & Moher, D. CONSORT 2010 statement: updated guidelines for reporting parallel group randomised trials. Trials 11, 32 (2010).
Tong, A., Sainsbury, P. & Craig, J. Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int. J. Qual. Health Care 19, 349–357 (2007).
Von Elm, E. et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Bull. World Health Organ 85, 867–872 (2007).
Hsu, C.-C. & Sandford, B. A. The Delphi technique: making sense of consensus. Pract. Assess. Res. Eval 12, 10 (2007).
Jorm, A. F. Using the Delphi expert consensus method in mental health research. Aust. N. Z. J. Psychiatry 49, 887–897 (2015).
Yucel, M. et al. A transdiagnostic dimensional approach towards a neuropsychological assessment for addiction: an international Delphi consensus study. Addiction 114, 1095–1109 (2019).
Diamond, I. R. et al. Defining consensus: a systematic review recommends methodologic criteria for reporting of Delphi studies. J. Clin. Epidemiol 67, 401–409 (2014).
Forsman, A. K. et al. Research priorities for public mental health in Europe: recommendations of the ROAMER project. Eur. J. Public Health 25, 249–254 (2015).
Chipchase, L. et al. A checklist for assessing the methodological quality of studies using transcranial magnetic stimulation to study the motor system: an international consensus study. Clin. Neurophysiol 123, 1698–1704 (2012).
Karoly, H. C. et al. Investigating a novel fMRI cannabis cue reactivity task in youth. Addict. Behav 89, 20–28 (2019).
Rubinstein, M. L. et al. Smoking-related cue-induced brain activation in adolescent light smokers. J. Adolesc. Health 48, 7–12 (2011).
Claus, E. D. et al. Association between nicotine dependence severity, BOLD response to smoking cues, and functional connectivity. Neuropsychopharmacology 38, 2363–2372 (2013).
Filbey, F. M. et al. Marijuana craving in the brain. Proc. Natl. Acad. Sci. U. S. A. 106, 13016–13021 (2009).
Casey, B. J., Jones, R. M. & Hare, T. A. The adolescent brain. Ann. N. Y. Acad. Sci 1124, 111–126 (2008).
Prisciandaro, J. J. et al. The relationship between years of cocaine use and brain activation to cocaine and response inhibition cues. Addiction 109, 2062–2070 (2014).
Cheng, G. L. F. et al. Heroin abuse accelerates biological aging: a novel insight from telomerase and brain imaging interaction. Transl. Psychiatry 3, e260 (2013).
McClernon, F. J., Kozink, R. V. & Rose, J. E. Individual differences in nicotine dependence, withdrawal symptoms, and sex predict transient fMRI-BOLD responses to smoking cues. Neuropsychopharmacology 33, 2148–2157 (2008).
Wetherill, R. R. et al. The impact of sex on brain responses to smoking cues: a perfusion fMRI study. Biol. Sex Differ 4, 9 (2013).
Joseph, J. E. et al. Neural correlates of oxytocin and cue reactivity in cocaine-dependent men and women with and without childhood trauma. Psychopharmacology (Berl.) https://doi.org/10.1007/s00213-019-05360-7 (2019).
Potenza, M. N. et al. Neural correlates of stress-induced and cue-induced drug craving: influences of sex and cocaine dependence. Am. J. Psychiatry 169, 406–414 (2012).
Kober, H. et al. Brain activity during cocaine craving and gambling urges: an fMRI study. Neuropsychopharmacology 41, 628–637 (2016).
Dong, G. et al. Gender-related differences in cue-elicited cravings in Internet gaming disorder: the effects of deprivation. J. Behav. Addict 7, 953–964 (2018).
Dong, G. et al. Gender-related differences in neural responses to gaming cues before and after gaming: implications for gender-specific vulnerabilities to Internet gaming disorder. Soc. Cogn. Affect. Neurosci. 13, 1203–1214 (2018).
Dong, G. et al. Gender-related functional connectivity and craving during gaming and immediate abstinence during a mandatory break: implications for development and progression of internet gaming disorder. Prog. Neuropsychopharmacol. Biol. Psychiatry 88, 1–10 (2019).
Franklin, T. R. et al. Menstrual cycle phase modulates responses to smoking cues in the putamen: preliminary evidence for a novel target. Drug Alcohol Depend 198, 100–104 (2019).
van Duijvenbode, N. et al. Problematic alcohol use and mild intellectual disability: standardization of pictorial stimuli for an alcohol cue reactivity task. Res. Dev. Disabil 33, 1095–1102 (2012).
Cuzzocreo, J. L. et al. Effect of handedness on fMRI activation in the medial temporal lobe during an auditory verbal memory task. Hum. Brain Mapp 30, 1271–1278 (2009).
Moriguchi, Y. et al. Specific brain activation in Japanese and Caucasian people to fearful faces. Neuroreport 16, 133–136 (2005).
Greer, T. M., Vendemia, J. M. & Stancil, M. Neural correlates of race-related social evaluations for African Americans and white Americans. Neuropsychology 26, 704–712 (2012).
Volkow, N. D. et al. Cocaine cues and dopamine in dorsal striatum: mechanism of craving in cocaine addiction. J. Neurosci 26, 6583–6588 (2006).
Kosten, T. R. et al. Cue-induced brain activity changes and relapse in cocaine-dependent patients. Neuropsychopharmacology 31, 644–650 (2006).
Prisciandaro, J. J. et al. Prospective associations between brain activation to cocaine and no-go cues and cocaine relapse. Drug Alcohol Depend 131, 44–49 (2013).
Chase, H. W. et al. The neural basis of drug stimulus processing and craving: an activation likelihood estimation meta-analysis. Biol. Psychiatry 70, 785–793 (2011).
Wertz, J. M. & Sayette, M. A. Effects of smoking opportunity on attentional bias in smokers. Psychol. Addict. Behav 15, 268–271 (2001).
Wilson, S. J. et al. Carry-over effects of smoking cue exposure on working memory performance. Nicotine Tob. Res. 9, 613–619 (2007).
Engelmann, J. M. et al. Neural substrates of smoking cue reactivity: a meta-analysis of fMRI studies. Neuroimage 60, 252–262 (2012).
Moeller, S. J. et al. Neural correlates of drug-biased choice in currently using and abstinent individuals with cocaine use disorder. Biol. Psychiatry Cogn. Neurosci. Neuroimaging 3, 485–494 (2018).
Coffey, S. F. et al. Craving and physiological reactivity to trauma and alcohol cues in posttraumatic stress disorder and alcohol dependence. Exp. Clin. Psychopharmacol 18, 340–349 (2010).
Potvin, S. et al. Increased ventro-medial prefrontal activations in schizophrenia smokers during cigarette cravings. Schizophr. Res 173, 30–36 (2016).
Wiers, C. E. et al. Effects of depressive symptoms and peripheral DAT methylation on neural reactivity to alcohol cues in alcoholism. Transl. Psychiatry 5, e648 (2015).
Goudriaan, A. E. et al. Neurophysiological effects of modafinil on cue-exposure in cocaine dependence: a randomized placebo-controlled cross-over study using pharmacological fMRI. Addict. Behav. 38, 1509–1517 (2013).
McHugh, R. K. et al. Cue-induced craving to paraphernalia and drug images in opioid dependence. Am. J. Addict. 25, 105–109 (2016).
Clayton, R. B., Bailey, R. L. & Liu, J. Conditioned “cross fading”: the incentive motivational effects of mediated-polysubstance pairings on alcohol, marijuana, and junk food craving. J. Health Commun 24, 319–327 (2019).
Bach, P. et al. The effects of single nucleotide polymorphisms in glutamatergic neurotransmission genes on neural response to alcohol cues and craving. Addict. Biol 20, 1022–1032 (2015).
Blaine, S. et al. TACR1 genotypes predict fMRI response to alcohol cues and level of alcohol dependence. Alcohol Clin. Exp. Res 37, E125–E130 (2013).
Chen, J. et al. CREB-BDNF pathway influences alcohol cue-elicited activation in drinkers. Hum. Brain Mapp 36, 3007–3019 (2015).
Filbey, F. M. et al. Differential neural response to alcohol priming and alcohol taste cues is associated with DRD4 VNTR and OPRM1 genotypes. Alcohol Clin. Exp. Res 32, 1113–1123 (2008).
Janes, A. C. et al. Association between CHRNA5 genetic variation at rs16969968 and brain reactivity to smoking images in nicotine dependent women. Drug Alcohol Depend 120, 7–13 (2012).
Jorde, A. et al. Genetic variation in the atrial natriuretic peptide transcription factor GATA4 modulates amygdala responsiveness in alcohol dependence. Biol. Psychiatry 75, 790–797 (2014).
Kareken, D. A. et al. A polymorphism in GABRA2 is associated with the medial frontal response to alcohol cues in an fMRI study. Alcohol Clin. Exp. Res 34, 2169–2178 (2010).
Kuhn, A. B. et al. FTO gene variant modulates the neural correlates of visual food perception. Neuroimage 128, 21–31 (2016).
McClernon, F. J. et al. DRD4 VNTR polymorphism is associated with transient fMRI-BOLD responses to smoking cues. Psychopharmacology (Berl.) 194, 433–441 (2007).
Moeller, S. J. et al. Gene x abstinence effects on drug cue reactivity in addiction: multimodal evidence. J. Neurosci 33, 10027–10036 (2013).
Schacht, J. P. et al. Predictors of naltrexone response in a randomized trial: reward-related brain activation, OPRM1 genotype, and smoking status. Neuropsychopharmacology 42, 2640–2653 (2017).
Schacht, J. P. et al. Dopaminergic genetic variation influences aripiprazole effects on alcohol self-administration and the neural response to alcohol cues in a randomized trial. Neuropsychopharmacology 43, 1247–1256 (2018).
Xu, K. et al. A variant on the kappa opioid receptor gene (OPRK1) is associated with stress response and related drug craving, limbic brain activation and cocaine relapse risk. Transl. Psychiatry 3, e292 (2013).
Yang, B. Z. et al. A preliminary study of DBH (encoding dopamine beta-hydroxylase) genetic variation and neural correlates of emotional and motivational processing in individuals with and without pathological gambling. J. Behav. Addict 5, 282–292 (2016).
Poldrack, R. A. et al. Guidelines for reporting an fMRI study. Neuroimage 40, 409–414 (2008).
Albrecht, J. et al. Potential impact of a 32-channel receiving head coil technology on the results of a functional MRI paradigm. Clin. Neuroradiol 20, 223–229 (2010).
Panman, J. L. et al. Bias introduced by multiple head coils in MRI research: an 8 channel and 32 channel coil comparison. Front. Neurosci 13, 729 (2019).
Colizoli, O. et al. Comparing fMRI responses measured at 3 versus 7 Tesla across human cortex, striatum, and brainstem. Preprint at https://www.biorxiv.org/content/10.1101/2020.05.12.090175v1 (2020).
Sacchet, M. D. & Knutson, B. Spatial smoothing systematically biases the localization of reward-related brain activity. Neuroimage 66, 270–277 (2013).
Mayer, A. R. et al. A comparison of denoising pipelines in high temporal resolution task-based functional magnetic resonance imaging data. Hum. Brain Mapp 40, 3843–3859 (2019).
Poldrack, R. A. et al. Scanning the horizon: towards transparent and reproducible neuroimaging research. Nat. Rev. Neurosci 18, 115–126 (2017).
Lorenz, R. C. et al. Cue reactivity and its inhibition in pathological computer game players. Addict. Biol 18, 134–146 (2013).
Dale, A. M. Optimal experimental design for event-related fMRI. Hum. Brain Mapp 8, 109–114 (1999).
Josephs, O. & Henson, R. N. Event-related functional magnetic resonance imaging: modelling, inference and optimization. Philos. Trans. R Soc. Lond. B Biol. Sci 354, 1215–1228 (1999).
Holla, B. et al. Brain functional magnetic resonance imaging cue-reactivity can predict baclofen response in alcohol use disorders. Clin. Psychopharmacol. Neurosci 16, 290–301 (2018).
Vollstädt-Klein, S. et al. Initial, habitual and compulsive alcohol use is characterized by a shift of cue processing from ventral to dorsal striatum. Addiction 105, 1741–1749 (2010).
Li, X. et al. The neural mechanisms of immediate and follow-up of the treatment effect of hypnosis on smoking craving. Brain Imaging Behav 14, 1487–1497 (2020).
Gusnard, D. A., Raichle, M. E. & Raichle, M. E. Searching for a baseline: functional imaging and the resting human brain. Nat. Rev. Neurosci 2, 685–694 (2001).
Janes, A. C. et al. Quitting starts in the brain: a randomized controlled trial of app-based mindfulness shows decreases in neural responses to smoking cues that predict reductions in smoking. Neuropsychopharmacology 44, 1631–1638 (2019).
Dean, A. C. et al. No effect of attentional bias modification training in methamphetamine users receiving residential treatment. Psychopharmacology 236, 709–721 (2019).
Kang, O.-S. et al. Individual differences in smoking-related cue reactivity in smokers: an eye-tracking and fMRI study. Prog. Neuropsychopharmacol. Biol. Psychiatry 38, 285–293 (2012).
Hanlon, C. A. et al. Cortical substrates of cue-reactivity in multiple substance dependent populations: transdiagnostic relevance of the medial prefrontal cortex. Transl. Psychiatry 8, 186 (2018).
Mondino, M. et al. Effects of repeated transcranial direct current stimulation on smoking, craving and brain reactivity to smoking cues. Sci. Rep 8, 8724 (2018).
Yalachkov, Y. et al. Sensory modality of smoking cues modulates neural cue reactivity. Psychopharmacology (Berl.) 225, 461–471 (2013).
Manoliu, A. et al. SmoCuDa: a validated smoking cue database to reliably induce craving in tobacco use disorder. Eur. Addict. Res 27, 107–114 (2021).
Macatee, R. J. et al. Development and validation of a cannabis cue stimulus set. Addict. Behav 112, 106643 (2021).
Stritzke, W. G. et al. Assessment of substance cue reactivity: advances in reliability, specificity, and validity. Psychol. Addict. Behav 18, 148–159 (2004).
Zeng, H. et al. The action representation elicited by different types of drug-related cues in heroin-abstinent individuals. Front. Behav. Neurosci 12, 123 (2018).
Lindsey, K. P. et al. Nicotine content and abstinence state have different effects on subjective ratings of positive versus negative reinforcement from smoking. Pharmacol. Biochem. Behav 103, 710–716 (2013).
Schacht, J. P., Anton, R. F. & Myrick, H. Functional neuroimaging studies of alcohol cue reactivity: a quantitative meta-analysis and systematic review. Addict. Biol 18, 121–133 (2013).
Wall, M. B. et al. Investigating the neural correlates of smoking: feasibility and results of combining electronic cigarettes with fMRI. Sci. Rep 7, 1–8 (2017).
Ekhtiari, H. et al. It is never as good the second time around: brain areas involved in salience processing habituate during repeated drug cue exposure in treatment engaged abstinent methamphetamine and opioid users. Neuroimage 238, 118180 (2021).
Seo, D. et al. Disrupted ventromedial prefrontal function, alcohol craving, and subsequent relapse risk. JAMA Psychiatry 70, 727–739 (2013).
Chua, H. F. et al. Self-related neural response to tailored smoking-cessation messages predicts quitting. Nat. Neurosci 14, 426–427 (2011).
McClernon, F. J. et al. Hippocampal and insular response to smoking-related environments: neuroimaging evidence for drug-context effects in nicotine dependence. Neuropsychopharmacology 41, 877–885 (2016).
McClernon, F. J. et al. Abstinence-induced changes in self-report craving correlate with event-related FMRI responses to smoking cues. Neuropsychopharmacology 30, 1940–1947 (2005).
Li, Q. et al. Craving correlates with mesolimbic responses to heroin-related cues in short-term abstinence from heroin: an event-related fMRI study. Brain Res 1469, 63–72 (2012).
Kleykamp, B. A. et al. Craving and opioid use disorder: a scoping review. Drug Alcohol Depend 205, 107639 (2019).
Ekhtiari, H. Craving as an Outcome Measure in Clinical Trials: A Systematic Review on Craving Assessment Instruments in Clinical Trials for Substance Use Disorders. Accessed 25 Aug 2021. https://osf.io/vk9ug/ (2021).
Heishman, S. J. et al. Prolonged duration of craving, mood, and autonomic responses elicited by cues and imagery in smokers: effects of tobacco deprivation and sex. Exp. Clin. Psychopharmacol. 18, 245 (2010).
Heishman, S. J., Saha, S. & Singleton, E. G. Imagery-induced tobacco craving: duration and lack of assessment reactivity bias. Psychol. Addict. Behav 18, 284–288 (2004).
Franken, I. H., Hendriks, V. M. & Van den Brink, W. Initial validation of two opiate craving questionnaires: The Obsessive Compulsive Drug Use Scale and the Desires for Drug Questionnaire. Addict. Behav 27, 675–685 (2002).
Heishman, S. J., Singleton, E. G. & Liguori, A. Marijuana Craving Questionnaire: development and initial validation of a self-report instrument. Addiction 96, 1023–1034 (2001).
Tiffany, S. T. & Drobes, D. J. The development and initial validation of a questionnaire on smoking urges. Br. J. Addict. 86, 1467–1476 (1991).
Kozlowski, L. T. et al. “Cravings” are amibiguous: ask about urges or desires. Addict. Behav 14, 443–445 (1989).
Kozlowski, L. T. & Wilkinson, D. A. Use and misuse of the concept of craving by alcohol, tobacco, and drug researchers. Br. J. Addict 82, 31–36 (1987).
Wilson, S. J. & Sayette, M. A. Neuroimaging craving: urge intensity matters. Addiction 110, 195–203 (2015).
Plant, R. R., Hammond, N. & Whitehouse, T. How choice of mouse may affect response timing in psychological studies. Behav. Res. Methods Instrum. Comput 35, 276–284 (2003).
Plant, R. R. & Turner, G. Millisecond precision psychological research in a world of commodity computers: new hardware, new problems? Behav. Res. Methods 41, 598–614 (2009).
Segalowitz, S. J. & Graves, R. E. Suitability of the IBM XT, AT, and PS/2 keyboard, mouse, and game port as response devices in reaction time paradigms. Behav. Res. Methods Instrum. Comput 22, 283–289 (1990).
Schwarz, A. J. et al. A procedural framework for good imaging practice in pharmacological fMRI studies applied to drug development #1: processes and requirements. Drug Discov. Today 16, 583–593 (2011).
Sutton, B. P. et al. Investigation and validation of intersite fMRI studies using the same imaging hardware. J. Magn. Reson. Imaging 28, 21–28 (2008).
Carter, B. L. & Tiffany, S. T. Meta-analysis of cue-reactivity in addiction research. Addiction 94, 327–340 (1999).
Chang, C., Cunningham, J. P. & Glover, G. H. Influence of heart rate on the BOLD signal: the cardiac response function. Neuroimage 44, 857–869 (2009).
Gloria, R. et al. An fMRI investigation of the impact of withdrawal on regional brain activity during nicotine anticipation. Psychophysiology 46, 681–693 (2009).
Janes, A. C. et al. Brain fMRI reactivity to smoking-related images before and during extended smoking abstinence. Exp. Clin. Psychopharmacol 17, 365–373 (2009).
Lou, M. et al. Cue-elicited craving in heroin addicts at different abstinent time: an fMRI pilot study. Subst. Use Misuse 47, 631–639 (2012).
McClernon, F. J. et al. 24-h smoking abstinence potentiates fMRI-BOLD activation to smoking cues in cerebral cortex and dorsal striatum. Psychopharmacology (Berl.) 204, 25–35 (2009).
Parvaz, M. A., Moeller, S. J. & Goldstein, R. Z. Incubation of cue-induced craving in adults addicted to cocaine measured by electroencephalography. JAMA Psychiatry 73, 1127–1134 (2016).
Lu, L. et al. Incubation of cocaine craving after withdrawal: a review of preclinical data. Neuropharmacology 47, 214–226 (2004).
Bailey, S. R., Goedeker, K. C. & Tiffany, S. T. The impact of cigarette deprivation and cigarette availability on cue-reactivity in smokers. Addiction 105, 364–372 (2010).
Fischer, H. et al. Brain habituation during repeated exposure to fearful and neutral faces: a functional MRI study. Brain Res. Bull 59, 387–392 (2003).
Siegle, G. J. et al. Can’t shake that feeling: event-related fMRI assessment of sustained amygdala activity in response to emotional information in depressed individuals. Biol. Psychiatry 51, 693–707 (2002).
Franklin, T. et al. Effects of varenicline on smoking cue-triggered neural and craving responses. Arch. Gen. Psychiatry 68, 516–526 (2011).
LaRowe, S. D. et al. Reactivity to nicotine cues over repeated cue reactivity sessions. Addict. Behav 32, 2888–2899 (2007).
Schacht, J. P. et al. Stability of fMRI striatal response to alcohol cues: a hierarchical linear modeling approach. Neuroimage 56, 61–68 (2011).
McBride, D. et al. Effects of expectancy and abstinence on the neural response to smoking cues in cigarette smokers: an fMRI study. Neuropsychopharmacology 31, 2728–2738 (2006).
Perry, R. N. et al. The impacts of actual and perceived nicotine administration on insula functional connectivity with the anterior cingulate cortex and nucleus accumbens. J. Psychopharmacol 33, 1600–1609 (2019).
Gu, X. et al. Belief about nicotine modulates subjective craving and insula activity in deprived smokers. Front. Psychiatry 7, 126 (2016).

A methodological checklist for fMRI drug cue reactivity studies: development and expert consensus

Extended

Supplementary information

推荐阅读