Gender differences in vulnerability for cocaine addiction have been reported. Though the mechanisms are not understood, here we hypothesize that gender differences in reactivity to conditioned-cues, which contributes to relapse, are involved.
To test this we compared brain metabolism (using PET and 18FDG) between female (n = 10) and male (n = 16) active cocaine abusers when they watched a neutral video (nature scenes) versus a cocaine-cues video.
Self-reports of craving increased with the cocaine-cue video but responses did not differ between genders. In contrast, changes in whole brain metabolism with cocaine-cues differed by gender (p<0.05); females significantly decreased metabolism (−8.6%±10) whereas males tended to increase it (+5.5%±18). SPM analysis (Cocaine-cues vs Neutral) in females revealed decreases in frontal, cingulate and parietal cortices, thalamus and midbrain (p<0.001) whereas males showed increases in right inferior frontal gyrus (BA 44/45) (only at p<0.005). The gender-cue interaction showed greater decrements with Cocaine-cues in females than males (p<0.001) in frontal (BA 8, 9, 10), anterior cingulate (BA 24, 32), posterior cingulate (BA 23, 31), inferior parietal (BA 40) and thalamus (dorsomedial nucleus).
Females showed greater brain reactivity to cocaine-cues than males but no differences in craving, suggesting that there may be gender differences in response to cues that are not linked with craving but could affect subsequent drug use. Specifically deactivation of brain regions from “control networks” (prefrontal, cingulate, inferior parietal, thalamus) in females could increase their vulnerability to relapse since it would interfere with executive function (cognitive inhibition). This highlights the importance of gender tailored interventions for cocaine addiction.
Citation: Volkow ND, Tomasi D, Wang G-J, Fowler JS, Telang F, Goldstein RZ, et al. (2011) Reduced Metabolism in Brain “Control Networks” following Cocaine-Cues Exposure in Female Cocaine Abusers. PLoS ONE 6(2): e16573. doi:10.1371/journal.pone.0016573
Editor: Kenji Hashimoto, Chiba University Center for Forensic Mental Health, Japan
Received: October 29, 2010; Accepted: December 23, 2010; Published: February 23, 2011
This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
Funding: This research was supported by NIH's Intramural Research Program (NIAAA), and by DOE (DE-AC01-76CH00016). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: Dr. Volkow reports no competing interests; Dr. Tomasi reports no competing interests; Dr. Wang reports no competing interests; Dr. Fowler reports no competing interests; Dr. Telang reports no competing interests; Dr. Goldstein received consultation fee from Medical Directions, Inc. and honoraria fee from Federal Judicial Center and the Gruter Institute for Law and Behavioral Research; Dr. Klein reports no competing interests; Mr. Wong reports no competing interests. This does not alter the authors' adherence to all the PLoS ONE policies on sharing data and materials.
Gender differences in the vulnerability for substance use disorders including cocaine dependence have been reported –. For example, females are 3–4 times more likely than males to become addicted within 24 months of first cocaine use . Also clinical studies report that women seek treatment for substance use disorders earlier than men – and that they don't recover as quickly from cocaine abstinence as their male counterparts . In turn, others have reported that male cocaine abusers appear to transition from abstinence to relapse and viceversa at a significantly greater rate than females .
The mechanisms underlying the reported gender differences in the vulnerability for cocaine use disorders are likely to be multiple including differences in pharmacological sensitivity to cocaine  and in reactivity to cocaine-cues and to stress . The differences in reactivity to cocaine-cues are particularly relevant since they drive continued cocaine use . However, few studies have evaluated gender differences in cocaine-cue reactivity and the results are inconclusive. At least two studies have reported greater reactivity in women than in men ,  one showed the opposite , one showed no differences  and one showed differential sensitivity to different cue-induced measures . The reasons for the discrepancies are likely to be multiple including heterogeneity of cocaine abusing populations, methods used to elicit craving and the period during the menstrual cycle when the measurements were done. Specifically, imaging studies have shown greater reactivity to reward during the follicular than the luteal phase of the menstrual cycle . Also subjective reports may not necessarily reflect brain reactivity in all subjects since deficits in interoception in cocaine abusers may interfere with awareness of craving . Here we test the hypothesis that the brain of female cocaine abusers when tested in the midfollicular phase of the menstrual cycle is more reactive to cocaine-cues than that of male cocaine abusers.
To test this hypothesis we compared the regional brain metabolic changes induced by cocaine-cues between female and male cocaine abusers. We used Positron Emission Tomography (PET) and 2-deoxy-2[18F]fluoro-D-glucose (18FDG) to measure brain glucose metabolism (marker of brain function)  in 16 males and 10 female active cocaine abusers that were part of two studies that assessed the effects of stimulant drugs and cognitive strategies to control craving , . Subjects were tested twice; once while watching a neutral video (nature scenes) and once while watching a video of cocaine-cues (repeating scenes of people taking cocaine). The cocaine-cues video used was one we had previously shown induced significant increases in striatal DA, which was an effect associated with increases in drug craving . Cocaine craving was measured using analog self-reports of craving and a brief version of the Cocaine Craving Questionnaire (CCQ) that evaluates current cocaine craving .
Self-reports of craving were increased by the cocaine-cues video; the repeated factorial ANOVA showed a significant condition effect (F = 5, df 1, 24; p<0.03) but the interaction was not significant (F = 2, p<0.17). Females tended to show larger increases (3.4±2 vs 5.8±3) than males (3.0±3 vs 3.7±3) but the gender difference was not significant. Similarly the cocaine-cues increased the scores on the CCQ both in females (29±9 vs 38±12) and males (30±12 vs 34±15) but the gender difference was not significant.
Absolute brain metabolism
Whole brain metabolism showed a significant cue by gender interaction effect (df 1, 24 p<0.05). In females whole brain metabolism significantly decreased (−8.6%±10; p<0.03) with the cocaine-cues video exposure (35.6±4 µmol/100 g/min) as compared to neutral (32.3±3 µmol/100 g/min); whereas in males whole brain metabolism tended to increase (+5.5%±18) with cocaine-cues exposure (36.2±5 µmol/100 g/min) as compared to neutral (34.9±5 µmol/100 g/min) but in the males this effect was not significant.
The SPM analysis on the absolute metabolic images in the females showed significant differences for the uncorrected threshold pu<0.005 for decreases in right midbrain (MNI coordinates for x (left to right), y (anterior to posterior) and z (top to bottom) of 3, −9, 15), left anterior cingulate (BA 24; MNI coordinates −14, 13, 30) and left lateral orbitofrontal cortex (BA 47; MNI coordinates −51, 24, −5). In males SPM did not detect any significant difference in absolute metabolism even when the threshold was reduced to pu<0.05. The cue by gender interaction showed that the differences were significant for pu<0.005 for greater cues-induced decreases in the females in anterior cingulate gyrus (BA 24; MNI coordinates −14, 13, 30 and BA 32 −18, 16, 38) and in left inferior frontal gyrus (BA 47, MNI coordinates −45, 39, −11).
Normalized metabolic measures
The SPM results were very similar when daily cocaine use was entered as a covariate than when it was not. Here we present the results for the analysis after adjusting for the amount of cocaine used (daily cocaine use) since this was higher for the males than for the females.
In the females SPM analysis on the normalized metabolic images (pu<0.001) showed decreases in anterior cingulate (BA 24, BA 32), frontal (BA 4, BA 8), posterior cingulate (BA 23,), inferior parietal (BA 40), thalamus (ventro lateral) and midbrain. There were no regions that showed increases in metabolism (Figure 1A, Table 1).
Comparison correspond to Neutral > Cocaine-cues for uncorrected threshold pu<0.001 cluster >200 voxels. There were no regions where metabolism was higher during the Cocaine-cues than the Neutral conditions. B. SPM results for the “normalized” metabolic images for Neutral vs Cocaine-cues video conditions in the Males. Comparison correspond to Neutral > Cocaine-cues for uncorrected threshold pu<0.005 cluster >200 voxels; we used this lower threshold since there were no significant differences for pu<0.001. There were no regions where metabolism was higher during the Cocaine-cues than the Neutral conditions.
In the males SPM analysis on the normalized metabolic images (pu<0.001) showed no significant differences. Reducing the threshold of pu<0.005 identified an area that showed increases in the right inferior frontal gyrus (BA 44/45) but this region did not survive the cluster correction for multiple comparison (Figure 1B).
SPM analysis to assess the gender by condition interaction showed that the genders differed significantly (pu<0.001). Females had significantly greater decreases than males during the cocaine-cues when compared with neutral in frontal regions (BA 4, BA 6, BA 8, BA 9), in anterior cingulate (BA 24), posterior cingulate (BA 23, 31) and inferior parietal (BA 40) (Figure 2, Table 2).
Comparison correspond to Females > Males for uncorrected threshold pu<0.001 cluster >200 voxels. There were no regions where males had larger changes than females.
Correlations with craving
SPM voxel wise correlation between changes in craving and changes in normalized metabolism were not significant in females or males for pu<0.001. Reducing the threshold to pu<0.005 showed in males a significant negative correlation in a cluster region (5403 voxels) located in the posterior cerebellum (uvula and culmen); centered at MNI x,y,z coordinates of −36, −65, 24. There were no significant correlations in the females with craving.
The results from this study corroborate our hypothesis of greater brain reactivity to conditioned cocaine-cues in female than in male cocaine abusers even though the self-reported craving responses did not differ between the genders. Females when compared with males showed enhanced brain reactivity (as assessed by changes in brain glucose metabolism) to the cocaine-cues when compared with the neutral condition. The responses were also qualitatively different between genders; whereas in females the cocaine-cues significantly decreased whole brain metabolism in males it was associated with non-significant increases. In addition, the analysis of the normalized metabolic images, which increases the sensitivity to detect regional effects, showed that in the females the cocaine-cues elicited relative decreases in prefrontal cortex, anterior and posterior cingulate gyrus, inferior parietal lobe, thalamus and midbrain whereas in males the only significant difference was an increase in the right inferior frontal cortex (BA 44, 45) that did not survive cluster correction for multiple comparison. The fact that the gender differences in brain reactivity were significant after covarying for the doses of cocaine used indicates that the gender differences were not driven by differences in severity of drug use between the genders.
Traditionally executive control has been ascribed to prefrontal regions, mainly the dorsolateral prefrontal cortex, dorsal anterior cingulate cortex/medial superior frontal cortex and inferior frontal cortex . However studies with functional connectivity have started to identify a more complex set of regions that in addition to prefrontal and cingulate gyrus, include other regions of the frontal cortex, the parietal cortex and the thalamus. Moreover, it has been proposed that these regions are functionally connected into two networks involved with top-down control . Specifically a fronto-parietal network comprised of the dorsolateral prefrontal cortex, inferior parietal lobe, dorsal frontal cortex, intraparietal sulcus, precuneus and middle cingulate cortex and a cingulo-opercular network comprised of the anterior prefrontal cortex, anterior insula/medial frontal operculum, dorsal anterior cingulate/medial superior frontal cortex and thalamus. It is noteworthy that the gender differences in the brain reactivity to cocaine-cues were all located within one of these two control networks. Thus the deactivation of regions involved with cognitive control with cue-exposure would suggest that top down control may be impaired after exposure to cocaine cues in female cocaine abusers. Indeed, there is evidence of impairment in executive function in cocaine abusers when exposed to conditioned-cues ; though to our knowledge no study has as of yet evaluated gender differences in cognitive function following exposure to drug-cues.
In a prior brain imaging study done in healthy controls in whom we exposed participants to food cues and asked them to cognitively inhibit craving we showed that whereas males were able to inhibit limbic brain activation by food-cues, females were unable to do so . If our current findings of metabolic decreases in regions that are part of top-down control networks in female cocaine abusers when exposed to cocaine-cues, generalize to appetitive cues in healthy controls, they could help explain gender differences in the ability to cognitively inhibit limbic activation with exposure to food cues.
In the current study females tended to show greater craving than males when exposed to cocaine-cues but this difference was not significant. Using a similar cocaine-cues video a prior study reported higher levels of craving in females than in male cocaine abusers . Thus in our study we can not rule out the possibility that a larger sample size may have enabled us to document gender differences in craving responses. Regardless, the lack of a correlation between the changes in metabolism induced by the cocaine-cues video and the changes in craving suggest to us that the regional brain responses that we observed with exposure to cues are not the ones underlying the conscious experience of craving but may reflect changes in brain activity that follow the exposure of highly salient stimuli for the cocaine abuser. In this respect it is noteworthy that most research done to understand responses to cues has focused on the experience of craving without recognizing that other processes (mood, executive function) are also likely to be influenced by exposure to conditioned cues.
Our findings differ from prior imaging studies (using fMRI and PET CBF measures) that showed activation of limbic brain regions with exposure to cocaine-cues (scripts constructed to evoke craving or cocaine-cues videos) –. This is very likely to reflect the different temporal sensitivity between the fMRI (measures activity over 5–10 seconds) and PET CBF measures (measures activity over 60 seconds) and that of the PET glucose metabolic measures (measures activity over 30 minutes). Thus the deactivation of regions involved with cognitive control observed with the cocaine-cues video in the females could reflect a long lasting effect that follows the exposure to conditioned-cues in contrast to the fast and short lasting limbic activation from cues exposure.
Most clinical studies have focused on the effects of therapeutic interventions to reduce craving , . However, therapeutic interventions to weaken the link between craving and drug use have also been shown to be beneficial in cocaine abusers . Indeed, the desire for a drug can be controlled to a greater or lesser extent among drug users and treatment interventions have been shown to decrease cocaine use despite persistent craving . Using imaging we showed in a group of cocaine abusers (predominantly male) that when primed to cognitively inhibit craving in response to the same cocaine-cue video used in this study (but compared to a baseline condition with no stimulation) many of the cocaine abusers were able to decrease subjective experience of craving and to reduce activity in limbic brain regions . Moreover, activity in left inferior frontal cortex (BA 44), which is a brain region implicated in cognitive control , predicted the ability to inhibit limbic activity with cue exposures.
In this respect, therapeutic interventions to increase executive function including impulse control may help patients develop coping skills to abstain from using drugs when exposed to cocaine-cues. The findings from this study suggest that these strategies may also benefit by considering gender differences since the mechanism leading to relapse may differ for men and women . Our findings also suggest that there may be gender differences in response to cues that are not necessarily linked with the conscious experience of craving that may nonetheless affect subsequent drug use (i.e., impairing executive function following cues exposures). Indeed a recent study that used real time electronic diary reports showed that in cocaine abusers cue exposures were more frequently associated with drug use than with craving .
We recently showed that in cocaine abusers the stimulant medication methylphenidate (MP) interfered with the reduction in metabolism triggered by cocaine cues in cocaine abusers  and in a separate study done with fMRI we showed that MP improved executive function and brain activation patterns in cocaine abusers . Also a recent study reported that MP improved stop signal reaction time (SSRT), an index of improved control, in cocaine abusers . Though stimulant medications have not been shown to improve abstinence in cocaine abusers  they may be beneficial when coupled with psychotherapeutic interventions that aim to improve executive function and control impulsivity in cocaine abusers.
A limitation for this study is the use of conscious awareness of craving as the dependent variable. However, our study does not enable us to assess if genders differ in unconscious responses to conditioned-cues. The studies were done in the midfollicular phase, which is a time at which there may be a greater reactivity to reward and prediction of reward and this reactivity in turn appears to be modulated by estradiol . Indeed, cocaine abusing women when tested in the luteal phase (when sex hormones are higher) have attenuated responses to drug conditioned cues, which were interpreted to suggest that sex hormones have significant effects in regulating brain reactivity to drugs and drug cues , . Thus it would have been desirable to quantify the concentration of sex hormones in plasma not only for estrogen and progesterone in the females but also for testosterone in the males. This is relevant since exposure to cocaine could modify the concentration of sex hormones , . Moreover, preclinical studies have shown that sex hormones modify the responses to stimulant drugs including cocaine (reviewed ) and female cocaine abusers report attenuated subjective responses and less desire to smoke cocaine during the luteal than during the follicular phase of the menstrual cycle , . Also the extent to which the greater reactivity to cues extends to other phases of the menstrual cycle and to postmenopausal women requires further evaluation. Moreover though we predict that decreases in metabolic activity in control networks would be associated with impairments in executive functions we did not perform cognitive tests to assess if this was the case (since this was not an a priori hypothesis). Thus studies that evaluate executive function (including impulsivity) after exposure to cocaine cues are necessary to test this. In addition another limitation is the small sample size; yet we were able to detect significant gender differences, which points to the sexual dimorphism in the responses to drug cues in cocaine abusers.
This study provides evidence of greater brain reactivity to cocaine cues in female than in male cocaine abusers but no differences in craving responses. Females, but not males showed decreased metabolic activity in brain regions implicated in top-down control network when exposed to cocaine-cues. Further studies to evaluate the cognitive consequences of these responses to cues are necessary to determine if they interfere with inhibitory control and to help guide gender tailored treatment interventions in cocaine use disorders.
This study was carried out at Brookhaven National Laboratory and approved by the local Institutional Review Board (IRB of record: Committee on Research Involving Human Subjects (CORIHS); Study #: IRBnet #91581; CORIHS ID #2007-4835; BNL IRB #404) and written informed consent was obtained from all participants.
Twenty six active cocaine abusers (16 M and 10 F) who responded to an advertisement were studied. Subjects fulfilled DSM-IV criteria for cocaine dependence and were active users for at least the prior 6 months (free-base or crack). Exclusion criteria included current or past psychiatric disease other than cocaine or nicotine dependence; past or present history of neurological, cardiovascular or endocrinological disease; history of head trauma with loss of consciousness greater than 30 minutes; and current medical illness. Written informed consent was obtained from all subjects. Table 3 provides demographic and clinical characteristics of participants. Females were studied during the mid follicular phase (7–10 days post last menstrual period).
To assess the subjective experience of craving we used an analog scale (1–10) for self-reports of “cocaine craving” and the brief version of the CCQ , which evaluates current cocaine craving on a seven-point visual analog scale. The behavioral measures were obtained prior to (pre) and 30 minutes after (post) initiation of the video. We compared the pre versus the post measures and the corresponding time period for the baseline condition using repeated measures ANOVA.
PET scans were conducted with a whole-body, high-resolution positron emission tomograph (Siemens/CTI ECAT HR+, with 4.6×4.6×4.2 mm NEMA (National Electrical Manufacturers Association) using 18FDG. Details about the methods for scanning have been published . Briefly, a 20 minutes emission scan was started 35 minutes after injection of 4–6 mCi of 18FDG. Arterialized blood sampling was used to measure 18FDG in plasma. Subjects were scanned on separate days, once while watching a video of nature scenes (neutral video) and once while watching a video that portrayed subjects smoking cocaine (cocaine-cues video). Videos were started 15 minutes prior to injection of 18FDG and continued for 25 minutes after 18FDG injection for a total video exposure of 40 minutes. The neutral video featured non-repeating segments of nature stories and the cocaine-cues video featured non-repeating segments portraying scenes that simulated purchase, preparation, and smoking of cocaine . The order of the videos was randomized such that on the first day, half of the subjects were shown the cocaine video whereas the other half were shown the neutral video.
Image and data Analysis
The data were analyzed using Statistical Parametric Mapping (SPM2) . The SPM analyses were performed both on the absolute metabolic images and on metabolic images that were normalized to whole brain metabolism, which increases the sensitivity to regional effects. The images were then spatially normalized using the PET template provided in SPM and subsequently smoothed with a 16 mm isotropic Gaussian kernel. We used a repeated (neutral vs cocaine-cues) factorial (male vs female) contrast ANOVA analysis for comparison. Since the groups differed in the amount of cocaine used (daily doses of cocaine), which was greater for the males than the females we entered daily cocaine daily use as a covariate in the SPM analyses. Voxel wise correlations were performed to assess the relationship between changes in metabolism and changes in craving separately for the males and females. Significance was set at p<0.001 (uncorrected, >200 voxels) and only regions that survive corrections for multiple comparisons (pc<0.05) are reported as significant unless otherwise specified. This was because for the comparisons of the absolute metabolic images there were no significant differences at p<0.001 so we lowered the threshold to p<0.005. Similarly for the comparisons on the normalized metabolic measures in the males there were no significant differences at p<0.001 so we lowered the threshold to p<0.005. Statistical maps were overlaid on an MRI structural image.
We thank David Schlyer, David Alexoff, Don Warner, Paul Vaska, Colleen Shea, Youwen Xu, Lisa Muench, Barbara Hubbard, Pauline Carter, Karen Apelskog and Linda Thomas for their contributions.
Conceived and designed the experiments: NDV GJW. Performed the experiments: FT GJW RZG NAK. Analyzed the data: NDV DT CW. Contributed reagents/materials/analysis tools: JSF DT. Wrote the paper: NDV JSF.
- 1. Evans SM (2007) The role of estradiol and progesterone in modulating the subjective effects of stimulants in humans. Exp Clin Psychopharmacol 15(5): 418–426.
- 2. Zilberman M, Tavares H, el-Guebaly N (2003) Gender similarities and differences: the prevalence and course of alcohol- and other substance-related disorders. J Addict Dis 22(4): 61–74.
- 3. Hernandez-Avila CA, Rounsaville BJ, Kranzler HR (2004) Opioid-, cannabis- and alcohol-dependent women show more rapid progression to substance abuse treatment. Drug Alcohol Depend 74(3): 265–272.
- 4. O'Brien MS, Anthony JC (2005) Risk of becoming cocaine dependent: Epidemiological estimates for the United States, 2000–2001. Neuropsychopharmacology 30: 1006–1018.
- 5. Anglin MD, Hser YI, McGlothlin WH (1987) Sex differences in addict careers. 2. Becoming addicted. Am J Drug Alcohol Abuse 13(1–2): 59–71.
- 6. Griffin ML, Weiss RD, Mirin SM, Lange U (1989) A comparison of male and female cocaine abusers. Arch Gen Psychiatry 46(2): 122–126.
- 7. Westermeyer J, Boedicker AE (2000) Course, severity, and treatment of substance abuse among women versus men. Am J Drug Alcohol Abuse 26(4): 523–535.
- 8. Brecht ML, O'Brien A, von Mayrhauser C, Anglin MD (2004) Methamphetamine use behaviors and gender differences. Addict Behav 29(1): 89–106.
- 9. Gallop RJ, Crits-Christoph P, Ten Have TR, Barber JP, Frank A, et al. (2007) Differential transitions between cocaine use and abstinence for men and women. J Consult Clin Psychol 75(1): 95–103.
- 10. Waldrop AE, Price KL, Desantis SM, Simpson AN, Back SE, et al. (2010) Community-dwelling cocaine-dependent men and women respond differently to social stressors versus cocaine cues. Psychoneuroendocrinology 35: 798–806.
- 11. O'Brien CP, Childress AR, McLellan T, Ehrman R (1990) Integrating systemic cue exposure with standard treatment in recovering drug dependent patients. Addict Behav 15(4): 355–365.
- 12. Robbins SJ, Ehrman RN, Childress AR, O'Brien CP (1999) Comparing levels of cocaine cue reactivity in male and female outpatients. Drug Alcohol Depend 53(3): 223–230.
- 13. Elman I, Karlsgodt KH, Gastfriend DR (2001) Gender differences in cocaine craving among non-treatment-seeking individuals with cocaine dependence. Am J Drug Alcohol Abuse 27(2): 193–202.
- 14. Sterling RC, Dean J, Weinstein SP, Murphy J, Gottheil E (2004) Gender differences in cue exposure reactivity and 9-month outcome. J Subst Abuse Treat 27(1): 39–44.
- 15. Avants SK, Margolin A, Kosten TR, Cooney NL (1995) Differences between responders and nonresponders to cocaine cues in the laboratory. Addict Behav 20(2): 215–224.
- 16. Fox HC, Hong KI, Siedlarz KM, Bergquist K, Anderson G, et al. (2009) Sex-specific dissociations in autonomic and HPA responses to stress and cues in alcohol-dependent patients with cocaine abuse. Alcohol Alcohol 44(6): 575–585.
- 17. Dreher JC, Schmidt PJ, Kohn P, Furman D, Rubinow D, et al. (2007) Menstrual cycle phase modulates reward-related neural function in women. Proc Natl Acad Sci USA 104(7): 2465–2470.
- 18. Goldstein RZ, Craig AD, Bechara A, Garavan H, Childress AR, et al. (2009) The neurocircuitry of impaired insight in drug addiction. Trends Cogn Sci 13(9): 372–380.
- 19. Sokoloff L, Reivich M, Kennedy C, Des Rosiers MH, Patlak CS, et al. (1977) The [14C]deoxyglucose method for the measurement of local cerebral glucose utilization: theory, procedure, and normal values in the conscious and anesthetized albino rat. Neurochem 28(5): 897–916.
- 20. Volkow ND, Wang G-J, Tomasi D, Telang F, Fowler JS, et al. (2010) Methylphenidate attenuates limbic brain inhibition after cocaine-cues exposure in cocaine abusers. PLoS One 5(7): e11509.
- 21. Volkow ND, Fowler JS, Wang GJ, Telang F, Logan J, et al. (2010) Cognitive control of drug craving inhibits brain reward regions in cocaine abusers. Neuroimage 49(3): 2536–2543.
- 22. Volkow ND, Wang G-J, Telang F, Fowler JS, Logan J, et al. (2006) Cocaine cues and dopamine in dorsal striatum: mechanism of craving in cocaine addiction. J Neurosci 26(24): 6583–6588.
- 23. Tiffany ST, Singleton E, Haertzen CA, Henningfield JE (1993) The development of a cocaine craving questionnaire. Drug Alcohol Depend 34(1): 19–28.
- 24. Wang GJ, Volkow ND, Roque CT, Cestaro VL, Hitzemann RJ, et al. (1993) Functional importance of ventricular enlargement and cortical atrophy in healthy subjects and alcoholics as assessed with PET, MRI imaging and neuropsychological testing. Radiology 186(1): 59–65.
- 25. Friston KJ, Holmes AP, Worsley KJ, Poline J-P, Frith CD, et al. (1994) Statistical Parametric Maps in functional imaging: A general linear approach. Hum Brain Mapp 2(4): 189–210.
- 26. MacDonald AW, Cohen JD, Stenger A, Carter CS (2000) Dissociating the role of the dorsolateral prefrontal and anterior cingulate cortex in cognitive control. Science 288: 1835–1838.
- 27. Dosenbach NU, Fair DA, Cohen AL, Schlaggar BL, Petersen SE (2008) A dual-networks architecture of top-down control. Trends Cogn Sci 12(3): 99–105.
- 28. Vadhan NP, Carpenter KM, Copersino ML, Hart CL, Foltin RW, et al. (2007) Attentional bias towards cocaine-related stimuli: relationship to treatment-seeking for cocaine dependence. Am J Drug Alcohol Abuse 33: 727–736.
- 29. Wang GJ, Volkow ND, Telang F, Jayne M, Ma Y, et al. (2009) Evidence of gender differences in the ability to inhibit brain activation elicited by food stimulation. Proc Natl Acad Sci USA 106(4): 1249–1254.
- 30. Duncan E, Boshoven W, Harenski K, Fiallos A, Tracy H, et al. (2007) An fMRI study of the interaction of stress and cocaine cues on cocaine craving in cocaine-dependent men. Am J Addict 16(3): 174–182.
- 31. Garavan H, Pankiewicz J, Bloom A, Cho JK, Sperry L, et al. (2000) Cue-induced cocaine craving: neuroanatomical specificity for drug users and drug stimuli. Am J Psychiatry 157: 1789–1798.
- 32. Childress AR, Mozley PD, McElgin W, Fitzgerald J, Reivich M, et al. (1999) Limbic Activation during cue-induced cocaine craving. Am J Psychiatry 156(1): 11–18.
- 33. Kilts CD, Schweitzer JB, Quinn CK, Gross RE, Faber TL, et al. (2001) Neural activity related to drug craving in cocaine addiction. Arch Gen Psychiatry 58: 334–341.
- 34. Kosten TR (1992) Can cocaine craving be a medication development outcome? drug craving and relapse in opioid and cocaine dependence. Am J Addict 1: 230–239.
- 35. Renshaw P, Daniels S, Lundahl L, Rogers V, Lukas S (1999) Short-term treatment with citicoline (CDP-choline) attenuates some measures of craving in cocaine-dependent subjects: a preliminary report. Psychopharmacology (Berl) 142: 132–138.
- 36. Weiss RD, Griffin ML, Mazurick C, Berkman B, Gastfriend DR, et al. (2003) The relationship between cocaine craving, psychosocial treatment, and subsequent cocaine use. Am J Psychiatry 160(7): 1320–1325.
- 37. Aron AR, Robbins TW, Poldrack RA (2004) Inhibition and the right inferior frontal cortex. Trends Cogn Sci 8(4): 170–177.
- 38. Epstein DH, Willner-Reid J, Vahabzadeh M, Mezghanni M, Lin JL, et al. (2009) Real-time electronic diary reports of cue exposure and mood in the hours before cocaine and heroin craving and use. Arch Gen Psychiatry 66(1): 88–94.
- 39. Goldstein RZ, Woicik PA, Maloney T, Tomasi D, Alia-Klein N, et al. (2010) Oral methylphenidate normalizes cingulate activity in cocaine addiction during a salient cognitive task. Proc Natl Acad Sci U S A 107(38): 16667–16672.
- 40. Li CS, Morgan PT, Matuskey D, Abdelghany O, Luo X, et al. (2010) Biological markers of the effects of intravenous methylphenidate on improving inhibitory control in cocaine-dependent patients. Proc Natl Acad Sci U S A. Jul 26. [Epub ahead of print].
- 41. Castells X, Casas M, Vidal X, Bosch R, Roncero C, et al. (2007) Efficacy of central nervous system stimulant treatment for cocaine dependence: a systematic review and meta-analysis of randomized controlled clinical trials. Addiction 102(12): 1871–1887.
- 42. Sinha R, Fox H, Hong KI, Sofuoglu M, Morgan PT, et al. (2007) Sex steroid hormones, stress response, and drug craving in cocaine-dependent women: implications for relapse and susceptibility. Exp Clin Psychopharmacol 15: 445–452.
- 43. Turner JM, de Wit H (2006) Menstrual cycle phase and response to drugs of abuse in humans. Drug Alcohol Depend 84: 1–13.
- 44. Heesch CM, Negus BH, Bost JE, Keffer JH, Snyder RW 2nd, et al. (1996) Effects of cocaine on anterior pituitary and gonadal hormones. J Pharmacol Exp Ther 278(3): 1195–1200.
- 45. Quinones-Jenab V, Minerly AC, Niyomchia T, Akahvan A, Jenab S, et al. (2008) Progesterone and allopregnanolone are induced by cocaine in serum and brain tissues of male and female rats. Pharmacol Biochem Behav 89: 292–297.
- 46. Kohtz AS, Paris JJ, Frye CA (2010) Low doses of cocaine decrease, and high doses increase, anxiety-like behavior and brain progestogen levels among intact rats. Horm Behav 57(4–5): 474–480.
- 47. Evans SM, Haney M, Foltin RW (2002) The effects of smoked cocaine during the follicular and luteal phases of the menstrual cycle. Psychopharmacology (Berl) 159: 397–406.
- 48. Sofuoglu M, Babb DA, Hatsukami DK (2002) Effects of progesterone treatment on smoked cocaine response in women. Pharmacol Biochem Behav 72: 431–435.