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Increased Marijuana Use and Gender Predict Poorer Cognitive Functioning in Adolescents and Emerging Adults

Published online by Cambridge University Press:  22 May 2012

Krista M. Lisdahl  and
Jenessa S. Price
Krista M. Lisdahl*
Affiliation:
Department of Psychology, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin Clinical & Translational Science Institute, Medical College of Wisconsin, Milwaukee, Wisconsin
Jenessa S. Price
Affiliation:
Department of Psychology, University of Cincinnati, Cincinnati, Ohio
*
Correspondence and reprint requests to: Krista M. Lisdahl, University of Wisconsin-Milwaukee, 2241 E. Hartford Avenue, Milwaukee, WI 53211. E-mail: krista.medina@gmail.com
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Abstract

This study sought to characterize neuropsychological functioning in MJ-using adolescents and emerging adults (ages 18–26) and to investigate whether gender moderated these effects. Data were collected from 59 teens and emerging adults including MJ users (n = 23, 56% female) and controls (n = 35, 50% female) aged 18–26 (M = 21 years). Exclusionary criteria included independent Axis I disorders (besides SUD), and medical and neurologic disorders. After controlling for reading ability, gender, subclinical depressive symptoms, body mass index, and alcohol and other drug use, increased MJ use was associated with slower psychomotor speed/sequencing ability (p < .01), less efficient sustained attention (p < .05), and increased cognitive inhibition errors (p < .03). Gender significantly moderated the effects of MJ on psychomotor speed/sequencing ability (p < .003) in that males had a more robust negative relationship. The current study demonstrated that MJ exposure was associated with poorer psychomotor speed, sustained attention and cognitive inhibition in a dose-dependent manner in young adults, findings that are consistent with other samples of adolescent MJ users. Male MJ users demonstrated greater cognitive slowing than females. Future studies need to examine the neural substrates underlying with these cognitive deficits and whether cognitive rehabilitation or exercise interventions may serve as a viable treatments of cognitive deficits in emerging adult MJ users. (JINS, 2012, 18, 1–11)

Keywords

AdolescentsYoung adultsNeuropsychologyCognitionMarijuanaDrug effectsGender
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 18 , Issue 4 , July 2012 , pp. 678 - 688
Copyright
Copyright © The International Neuropsychological Society 2012

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References

Arnone, D., Barrick, T.R., Chengappa, S., Mackay, C.E., Clark, C.A., Abou-Saleh, M.T. (2008). Corpus callosum damage in heavy marijuana use: Preliminary evidence from diffusion tensor tractography and tract-based spatial statistics. Neuroimage, 41(3), 1067–1074.CrossRefGoogle ScholarPubMed
Aronowitz, B., Liebowitz, M.R., Hollander, E., Fazzini, E., Durlach-Misteli, C., Frenkel, M., DelBene, D. (1994). Neuropsychiatric and neuropsychological findings in conduct disorder and attention-deficit hyperactivity disorder. Journal of Neuropsychiatry & Clinical Neurosciences, 6, 245–249.Google ScholarPubMed
Ashtari, M., Cervellione, K., Cottone, J., Ardekani, B.A., Sevy, S., Kumra, S. (2009). Diffusion abnormalities in adolescents and young adults with a history of heavy cannabis use. Journal of Psychiatric Research, 43(3), 189–204.Google Scholar
Ashtari, M., Cervellione, K.L., Hasan, K.M., Wu, J., McIlree, C., Kester, H., Kumra, S. (2007). White matter development during late adolescence in healthy males: A cross-sectional diffusion tensor imaging study. Neuroimage, 35(2), 501–510.CrossRefGoogle Scholar
Barnea-Goraly, N., Menon, V., Eckert, M., Tamm, L., Bammer, R., Karchemskiy, A., Reiss, A.L. (2005). White matter development during childhood and adolescence: A cross-sectional diffusion tensor imaging study. Cerebral Cortex, 15(12), 1848–1854.Google Scholar
Bauer, L.O., Kaplan, R.F., Hesselbrock, V.M. (2010). P300 and the Stroop effect in overweight minority adolescents. Neuropsychobiology, 61(4), 180–187.CrossRefGoogle ScholarPubMed
Bava, S., Frank, L.R., McQueeny, T., Schweinsburg, B.C., Schweinsburg, A.D., Tapert, S.F. (2009). Altered white matter microstructure in adolescent substance users. Psychiatry Research, 173(3), 228–237.Google Scholar
Beck, A.T. (1996). Beck Depression Inventory-2nd edition. New York: Psychological Corporation.Google Scholar
Becker, B., Wagner, D., Gouzoulis-Mayfrank, E., Spuentrup, E., Daumann, J. (2010). The impact of early-onset marijuana use on functional brain correlates of working memory. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 34(6), 837–845.CrossRefGoogle ScholarPubMed
Belue, RC., Howlett, AC., Westlake, TM., Hutchings, DE. (1995). The ontogeny of cannabinoid receptors in the brain of postnatal and aging rats. Neurotoxicol Teratol, 17(1), 25–30.Google Scholar
Burston, J.J., Wiley, J.L., Craig, A.A., Selley, D.E., Sim-Selly, L.J. (2010). Regional enhancement of cannabinoid CB1 receptor desensitization in female adolescent rats following repeated delta9-tetrahydrocannabinol exposure. British Journal of Pharmacology, 161, 103–112.CrossRefGoogle Scholar
Cha, Y.M., White, A.M., Kuhn, C.M., Wilson, W.A., Swartzwelder, H.S. (2006). Differential effects of delta(9)-THC on learning in adolescent and adult rats. Pharmacology Biochemistry and Behavior, 83(3), 448–455.Google Scholar
Cohen-Zion, M., Drummong, S.P.A., Padula, C.B., Winward, J., Kanady, J., Medina, K.L., Tapert, S.F. (2009). Sleep Architecture in Adolescent marijuana and Alcohol Users during Acute and Extended Abstinence. Addictive Behaviors, 34(11), 967–969.CrossRefGoogle ScholarPubMed
Crews, F.T., Nixon, K., Wilkie, M.E. (2004). Exercise reverses ethanol inhibition of neural stem cell proliferation. Alcohol, 33(1), 63–71.CrossRefGoogle ScholarPubMed
Degenhardt, L., Chiu, W.T., Sampson, N., Kessler, R.C., Anthony, J.C., Angermeyer, M., Wells, J.E. (2008). Toward a global view of alcohol, tobacco, cannabis, and cocaine use: Findings from the WHO World Mental Health Surveys. PLoS Medicine, 5(7), e141.CrossRefGoogle Scholar
Delis, D.C., Jacobson, M., Bondi, M.W., Hamilton, J.M., Salmon, D.P. (2003). The myth of testing construct validity using factor analysis or correlations with normal or mixed clinical populations: Lessons from memory assessment. Journal of the International Neuropsychological Society, 9, 936–946.Google Scholar
Delis, D.C., Kaplan, E. (2000). Delis-Kaplan Executive Functioning Scale Manual. San Antonio, TX: Psychological Corporation.Google Scholar
Delis, D.C., Kramer, J.H., Kaplan, E., Ober, B.A. (2001). California Verbal Learning Test- Second edition. San Antonio, TX: The Psychological Corporation.Google Scholar
Delisi, L.E., Bertisch, H.C., Szulc, K.U., Majcher, M., Brown, K., Bappal, A., Ardekani, B.A. (2006). A preliminary DTI study showing no brain structural change associated with adolescent cannabis use. Harm Reduction Journal, 3, 17.CrossRefGoogle ScholarPubMed
Ehrenreich, H., Rinn, T., Kunert, H.J., Moeller, M.R., Poser, W., Schilling, L., Hoehe, M.R. (1999). Specific attentional dysfunction in adults following early start of marijuana use. Psychopharmacology, 142(3), 295–301.Google Scholar
Fals-Stewart, W., O'Farrell, T.J., Freitas, T.T., McFarlin, S.K., Rutligliano, P. (2000). The Timeline Followback reports of psychoactive substance use by drug-abusing patients: Psychometric properties. Journal of Consulting and Clinical Psychology, 68(1), 134–144.CrossRefGoogle ScholarPubMed
First Michael, B., Spitzer Robert, L., Gibbon Miriam, Williams Janet, B.W. Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Patient Edition. (SCID-I/P) New York: Biometrics Research, New York State Psychiatric Institute, November 2002.Google Scholar
Fried, P.A., Watkinson, B., Gray, R. (2005). Neurocognitive consequences of marihuana-a comparison with pre-drug performance. Neurotoxicology and Teratology, 27(2), 231–239.Google Scholar
Fried, P.A., Watkinson, B., Gray, R. (2006). Neurocognitive consequences of cigarette smoking in young adults-a comparison with pre-drug performance. Neurotoxicology and Teratology, 28(4), 517–525.Google Scholar
Giedd, J.N., Blumenthal, J., Jeffries, N.O., Castellanos, F.X., Liu, H., Zijdenbos, A., Rapoport, J.L. (1999). Brain development during childhood and adolescence: A longitudinal MRI study. Nature Neuroscience, 2, 861–863.CrossRefGoogle ScholarPubMed
Giedd, J.N., Snell, J.W., Lange, N., Rajapakse, J.C., Casey, B.J., Kozuch, P.L., Rapoport, J.L. (1996). Quantitative magnetic resonance imaging of human brain development: Ages 4–18. Cerebral Cortex, 6(4), 551–560.Google Scholar
Giedd, J.N., Vaituzis, A.C., Hamburger, S.D., Lange, N., Rajapakse, J.C., Kaysen, D., Rapoport, J.L. (1996). Quantitative MRI of the temporal lobe, amygdala, and hippocampus in normal human development: Ages 4-18 years. The Journal of Comparative Neurology, 366, 223–230.Google Scholar
Gogtay, N., Giedd, J.N., Lusk, L., Hayashi, K.M., Greenstein, D., Vaituzis, A.C., Thompson, P.M. (2004). Dynamic mapping of human cortical development during childhood through early adulthood. The Proceedings of the National Academy of Sciences of the United States of America, 101(21), 8174–8179.Google ScholarPubMed
Gunstad, J., Paul, R.H., Cohen, R.A., Tate, D.F., Spitznagel, M.B., Grieve, S., Gordon, E. (2008). Relationship between body mass index and brain volume in healthy adults. International Journal of Neuroscience, 118(11), 1582–1593.CrossRefGoogle ScholarPubMed
Hanson, K.L., Medina, K.L., Nagel, B.J., Spadoni, A.D., Gorlick, A., Tapert, S.F. (2010). Hippocampal volumes in adolescents with and without a family history of alcoholism. The American Journal of Drug and Alcohol Abuse, 36, 16–167.CrossRefGoogle ScholarPubMed
Hanson, K.L., Medina, K.L., Padula, C.B., Tapert, S.F., Brown, S.A. (2011). How does adolescent alcohol and drug use affect neuropsychological functioning in young adulthood?: 10-year outcomes. Journal of Child & Adolescent Substance Abuse, 20, 135–154.CrossRefGoogle Scholar
Hanson, K.L., Winward, J.L., Schweinsburg, A.D., Medina, K.L., Brown, S.A., Tapert, S.F. (2010). Longitudinal study of cognition among adolescent marijuana users over three weeks of abstinence. Addictive Behaviors, 35(11), 970–976.CrossRefGoogle ScholarPubMed
Harvey, M.A., Sellman, J.D., Porter, R.J., Frampton, C.M. (2007). The relationship between non-acute adolescent marijuana use and cognition. Drug and Alcohol Review, 26(3), 309–319.CrossRefGoogle ScholarPubMed
Hill, S.Y., Kostelnik, B., Holmes, B., Goradia, D., McDermott, M., Diwadkar, V., Keshavan, M. (2007). fMRI BOLD response to the eyes task in offspring from multiplex alcohol dependence families. Alcoholism, Clinical and Experimental Research, 31(12), 2028–2035.CrossRefGoogle Scholar
Hill, S.Y., Muddasani, S., Prasad, K., Nutche, J., Steinhauer, S.R., Scanlon, J., Keshavan, M. (2007). Cerebellar volume in offspring from multiplex alcohol dependence families. Biological Psychiatry, 61(1), 41–47.Google Scholar
Ho, A.J., Raji, C.A., Becker, J.T., Lopez, O.L., Kuller, L.H., Hua, X., Thompson, P.M. (2011). The effects of physical activity, education, and body mass index on the aging brain. Human Brain Mapping, 32(9), 1371–1382.CrossRefGoogle ScholarPubMed
Howlett, A.C. (2002). The cannabinoid receptors. Prostaglandins Other Lipid Mediat, 68-69, 619–631.CrossRefGoogle ScholarPubMed
Jacobsen, L.K., Pugh, K.R., Constable, R.T., Westerveld, M., Mencl, W.E. (2007). Functional correlates of verbal memory deficits emerging during nicotine withdrawal in abstinent adolescent marijuana users. Biological Psychiatry, 61(1), 31–40.Google Scholar
Jager, G., Block, R.I., Luijten, M., Ramsey, N.F. (2010). Marijuana use and memory brain function in adolescent boys: A cross-sectional multicenter functional magnetic resonance imaging study. Journal of the American Academy of Child and Adolescent Psychiatry, 49(6), 561–572.Google Scholar
Jarvis, K., DelBello, M.P., Mills, N., Elman, I., Strakowski, S.M., Adler, C.M. (2008). Neuroanatomic comparison of bipolar adolescents with and without cannabis use disorders. Journal of Child and Adolescent Psychopharmacology, 18(6), 557–563.CrossRefGoogle ScholarPubMed
Jernigan, T., Gamst, A. (2005). Changes in volume with age: Consistency and interpretation of observed effects. Neurobiology of Aging, 26(9), 1271–1274.Google Scholar
Johnston, L.D., O'Malley, P.M., Bachman, J.G., Schulenberg, J.E. (2009). Monitoring the Future national survey results on drug use, 1975–2008. Volume II: College students and adults ages 19–50 (NIH Publication No. 09-7403). Bethesda, MD: National Institute on Drug Abuse, 306 pp.Google Scholar
Johnston, L.D., O'Malley, P.M., Bachman, J.G., Schulenberg, J.E. (2010). Monitoring the Future national results on adolescent drug use: Overview of key findings, 2009 (NIH Publication No. 10-7583). Bethesda, MD: National Institute on Drug Abuse.Google Scholar
Kang-Park, M.H., Wilson, W.A., Kuhn, C.M., Moore, S.D., Swartzwelder, H.S. (2007). Differential sensitivity of GABA A receptor-mediated IPSCs to cannabinoids in hippocampal slices from adolescent and adult rats. Journal of Neurophysiology, 98(3), 1223–1230.Google Scholar
Kloos, A., Weller, R.A., Chan, R., Weller, E.B. (2009). Gender differences in adolescent substance abuse. Current Psychiatry Reports, 11(2), 120–126.CrossRefGoogle ScholarPubMed
Lisdahl, K. M., Price, J. S. (under review). Greater body mass index is associated with poorer cognitive inhibition and sustained attention in healthy young adults.Google Scholar
Leasure, J.L., Nixon, K. (2010). Exercise neuroprotection in a rat model of binge alcohol consumption. Alcoholism, Clinical and Experimental Research, 34(3), 404–414.Google Scholar
Lenroot, R.K., Giedd, J.N. (2006). Brain development in children and adolescents: Insights from anatomical magnetic resonance imaging. Neuroscience and Biobehavioral Reviews, 30, 718–729.CrossRefGoogle ScholarPubMed
Lenroot, R.K., Giedd, J.N. (2010). Sex differences in the adolescent brain. Brain and Cognition, 72(1), 46–55.Google Scholar
Lenroot, R.K., Gogtay, N., Greenstein, D.K., Wells, E.M., Wallace, G.L., Clasen, L.S., Giedd, J.N. (2007). Sexual dimorphism of brain developmental trajectories during childhood and adolescence. Neuroimage, 36(4), 1065–1073.CrossRefGoogle ScholarPubMed
Lezak, M.D., Howieson, D.B., Loring, D.W. (2004). Neuropsychological assessment (4th ed.). New York: Oxford University Press.Google Scholar
Manly, J.J., Jacobs, D.M., Touradji, P. (2002). Reading level attenuates differences in neuropsychological test performance between African American and White elders. Journal of the International Neuropsychological Society, 8(3), 341–348.Google Scholar
McQueeny, T.M., Padula, C., Price, J., Medina, K.L., Logan, P., Tapert, S.F. (2011). Gender effects on amygdala morphometry in adolescent marijuana users. Behavioural Brain Research, 224(1), 128–134.Google Scholar
Medina, K.L., Hanson, K., Schweinsburg, A.D., Cohen-Zion, M., Nagel, B.J., Tapert, S.F. (2007). Neuropsychological functioning in adolescent marijuana users: Subtle deficits detectable after 30 days of abstinence. Journal of the International Neuropsychological Society, 13(5), 807–820.Google Scholar
Medina, K.L., McQueeny, T., Nagel, B.J., Hanson, K., Schweinsburg, A.D., Tapert, S.F. (2008). Prefrontal cortex volumes in adolescents with alcohol use disorders: Unique gender effects. Alcoholism, Clinical and Experimental Research, 32, 386–394.CrossRefGoogle ScholarPubMed
Medina, K.L., McQueeny, T., Nagel, B.J., Hanson, K.L., Yang, T., Tapert, S.F. (2009). Prefrontal morphometry in abstinent adolescent marijuana users: Subtle gender effects. Addiction Biology, 14(4), 457–468.CrossRefGoogle ScholarPubMed
Medina, K.L., Nagel, B.J., McQueeny, T., Park, A., Tapert, S.F. (2007). Depressive symptoms in adolescents: Associations with white matter volume and marijuana use. Journal of Child Psychology and Psychiatry, 48(6), 592–600.Google Scholar
Medina, K.L., Nagel, B.J., Tapert, S.F. (2010). Cerebellar vermis abnormality in adolescent marijuana users. Psychiatry Research: Neuroimaging, 182(2), 152–159.CrossRefGoogle ScholarPubMed
Medina, K.L., Shear, P.K., Corcoran, K. (2005). Ecstasy (MDMA) exposure and neuropsychological functioning: A polydrug perspective. Journal of the International Neuropsychological Society, 11(6), 1–13.CrossRefGoogle ScholarPubMed
Nagel, B.J., Medina, K.L., Yoshii, J., Schweinsburg, A.D., Moadab, I., Tapert, S.F. (2006). Age related changes in prefrontal white matter volume across adolescence. Neuroreport, 17(13), 1427–1431.Google Scholar
Nigg, J.T., Glass, J.M., Wong, M.M., Poon, E., Jester, J.M., Fitzgerald, H.E., Zucker, R.A. (2004). Neuropsychological executive functioning in children at elevated risk for alcoholism: Findings in early adolescence. Journal of Abnormal Psychology, 113(2), 302–314.CrossRefGoogle ScholarPubMed
Paus, T., Zijdenbos, A., Worsley, K., Collins, D.L., Blumenthal, J., Giedd, J.N., Evans, A.C. (1999). Structural maturation of neural pathways in children and adolescents: In vivo study. Science, 283(5409), 1908–1911.Google Scholar
Pereira, A.C., Huddleston, D.E., Brickman, A.M., Sosunov, A.A., Hen, R., McKhann, G.M., Small, S.A. (2007). An in vivo correlate of exercise-induced neurogenesis in the adult dentate gyrus. Proceedings of the National Academy of Sciences of the United States of America, 104(13), 5638–5643.Google Scholar
Quinn, H.R., Matsumoto, I., Callaghan, P.D., Long, L.E., Arnold, J.C., Gunasekaran, N., McGregor, I.S. (2008). Adolescent rats find repeated Delta(9)-THC less aversive than adult rats but display greater residual cognitive deficits and changes in hippocampal protein expression following exposure. Neuropsychopharmacology, 33(5), 1113–1126.CrossRefGoogle ScholarPubMed
Ridenour, T.A., Tarter, R.E., Reynolds, M., Mezzich, A., Kirisci, L., Vanyukov, M. (2009). Neurobehavior disinhibition, parental substance use disorder, neighborhood quality and development of cannabis use disorder in boys. Drug and Alcohol Dependence, 102(1–3), 71–77.Google Scholar
Rubino, T., Realini, N., Braida, D., Guidi, S., Capurro, V., Viganò, D., Parolaro, D. (2009). Changes in hippocampal morphology and neuroplasticity induced by adolescent THC treatment are associated with cognitive impairment in adulthood. Hippocampus, 19(8), 763–772.Google Scholar
Rubino, T., Vigano’, D., Realini, N., Guidali, C., Braida, D., Capurro, V., Parolaro, D. (2008). Chronic delta(9)-tetrahydrocannabinol during adolescence provokes sex-dependent changes in the emotional profile in adult rats: Behavioral and biochemical correlates. Neuropsychopharmacology, 33(11), 2760–2771.CrossRefGoogle ScholarPubMed
Ruff, R.M., Allen, C.C. (1996). Ruff 2 & 7 Selective Attention Test. Odessa, Florida: Psychological Assessment Resources, Inc.Google Scholar
Schneider, M., Koch, M. (2003). Chronic pubertal but not adult chronic cannabinoid treatment impairs sensorimotor gating, recognition memory and performance in a progressive ratio task in adult rats. Neuropsychopharmacology, 28, 1760–1790.CrossRefGoogle ScholarPubMed
Schwartz, R.H., Gruenewald, P.J., Klitzner, M., Fedio, P. (1989). Short-term memory impairment in cannabis-dependent adolescents. American Journal of Diseases in Children, 143(10), 1214–1219.Google Scholar
Schweinsburg, A.D., Nagel, B.J., Schweinsburg, B.C., Park, A., Theilmann, R.J., Tapert, S.F. (2008). Abstinent adolescent marijuana users show altered fMRI response during spatial working memory. Psychiatry Research, 163(1), 40–51.CrossRefGoogle ScholarPubMed
Schweinsburg, A.D., Paulus, M.P., Barlett, V.C., Killeen, L.A., Caldwell, L.C., Pulido, C., Tapert, S.F. (2004). An FMRI study of response inhibition in youths with a family history of alcoholism. Annals of the New York Academy of Sciences, 1021, 391–394.Google Scholar
Schweinsburg, A.D., Schweinsburg, B.C., Medina, K.L., McQueeny, T., Brown, S.A., Tapert, S.F. (2010). The influence of recency of use on fMRI response during spatial working memory in adolescent marijuana users. Journal of Psychoactive Drugs, 42(3), 401–412.CrossRefGoogle ScholarPubMed
Schweinsburg, A.D., Schweinsburg, B.C., Nagel, B.J., Eyler, L.T., Tapert, S.F. (2011). Neural correlates of verbal learning in adolescent alcohol and marijuana users. Addiction, 106(3), 564–573.CrossRefGoogle ScholarPubMed
Silveri, M.M., Jensen, J.E., Rosso, I.M., Sneider, J.T., Yurgelun-Todd, D.A. (2011). Preliminary evidence for white matter metabolite differences in marijuana-dependent young men using 2D J-resolved magnetic resonance spectroscopic imaging at 4 Tesla. Psychiatry Research, 191(3), 201–211.Google Scholar
Sobell, L.C., Maisto, S.A., Sobell, M.B., Cooper, A.M. (1979). Reliability of alcohol abusers’ self-reports of drinking behavior. Behaviour Research and Therapy, 17(2), 157–160.Google Scholar
Sowell, E.R., Thompson, P.M., Holmes, C.J., Jernigan, T.L., Toga, A.W. (1999). In vivo evidence for post adolescent brain maturation in frontal and striatal regions. Nature Neuroscience, 2(10), 859–861.Google Scholar
Sowell, E.R., Thompson, P.M., Leonard, C.M., Welcome, S.E., Kan, E., Toga, A.W. (2004). Longitudinal mapping of cortical thickness and brain growth in normal children. The Journal of Neuroscience, 24(38), 8223–8231.Google Scholar
Sowell, E.R., Trauner, D.A., Gamst, A., Jernigan, T.L. (2002). Development of cortical and subcortical brain structures in childhood and adolescence: A structural MRI study. Developmental Medicine & Child Neurology, 44(1), 4–16.Google Scholar
Spadoni, A.D., Norman, A.L., Schweinsburg, A.D., Tapert, S.F. (2008). Effects of family history of alcohol use disorders on spatial working memory BOLD response in adolescents. Alcoholism, Clinical and Experimental Research, 32(7), 1135–1145.Google Scholar
Spear, L.P. (2010). The behavioral neuroscience of adolescence. Neuroscience and Biobehavioral Reviews, 24, 417–463.CrossRefGoogle Scholar
Tapert, S.F., Baratta, M.V., Abrantes, A.M., Brown, S.A. (2002). Attention dysfunction predicts substance involvement in community youths. Journal of the American Academy of Child and Adolescent Psychiatry, 41(6), 680–686.Google Scholar
Tapert, S.F., Brown, S.A. (2000). Substance dependence, family history of alcohol dependence, and neuropsychological functioning in adolescence. Addiction, 95, 1043–1053.CrossRefGoogle ScholarPubMed
Tapert, S.F., Granholm, E., Leedy, N.G., Brown, S.A. (2002). Substance use and withdrawal: Neuropsychological functioning over 8 years in youth. Journal of the International Neuropsychology Society, 8(7), 873–883.Google Scholar
Tapert, S.F., Schweinsburg, A.D., Drummond, S.P., Paulus, M.P., Brown, S.A., Yang, T.T., Frank, L.R. (2007). Functional MRI of inhibitory processing in abstinent adolescent marijuana users. Psychopharmacology (Berlin), 194, 173–183.Google Scholar
Viveros, M.P., Llorente, R., Moreno, E., Marco, E.M. (2005). Behavioural and neuroendocrine effects of cannabinoids in critical developmental periods. Behav Pharmacol, 16(5–6), 353–362.Google Scholar
Volkow, N.D., Wang, G.J., Telang, F., Fowler, J.S., Goldstein, R.Z., Alia-Klein, N., Pradhan, K. (2009). Inverse association between BMI and prefrontal metabolic activity in healthy adults. Obesity (Silver Spring), 17(1), 60–65.Google Scholar
Wilkinson, G. (1993). Wide Range Achievement Test, 3rd Edition (WRAT-3) Manual. Wilmington, DE: Wide Range, Inc.Google Scholar
Wilkinson, G. (2006). Wide Range Achievement Test, 4th edition (WRAT-4) manual. Wilmington, DE: Wide Range, Inc.Google Scholar
Wilson, W., Mathew, R., Turkington, T., Hawk, T., Coleman, R.E., Provenzale, J. (2000). Brain morphological changes and early marijuana use: A magnetic resonance and positron emission tomography study. Journal of Addictive Diseases, 19(1), 1–22.Google Scholar