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White matter integrity in alcohol-naive youth with a family history of alcohol use disorders

Published online by Cambridge University Press:  26 March 2014

L. M. Squeglia ,
J. Jacobus ,
T. Brumback ,
M. J. Meloy  and
S. F. Tapert
L. M. Squeglia
Affiliation:
University of California San Diego, Department of Psychiatry, La Jolla, CA, USA
J. Jacobus
Affiliation:
University of California San Diego, Department of Psychiatry, La Jolla, CA, USA VA San Diego Healthcare System, La Jolla, CA, USA
T. Brumback
Affiliation:
University of California San Diego, Department of Psychiatry, La Jolla, CA, USA
M. J. Meloy
Affiliation:
University of California San Diego, Department of Psychiatry, La Jolla, CA, USA
S. F. Tapert*
Affiliation:
University of California San Diego, Department of Psychiatry, La Jolla, CA, USA VA San Diego Healthcare System, La Jolla, CA, USA
*
* Address for correspondence: S. F. Tapert, Ph.D., VA San Diego Healthcare System, Psychology Service (116B), 3350 La Jolla Village Drive, San Diego, CA 92161, USA. (Email: [email protected])
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Abstract

Background

Understanding pre-existing neural vulnerabilities found in youth who are family history positive (FHP) for alcohol use disorders could help inform preventative interventions created to delay initiation age and escalation of heavy drinking. The goal of this study was to compare indices of white matter integrity using diffusion tensor imaging (DTI) between FHP and family history negative (FHN) youth using a sample of 94 alcohol-naive adolescents and to examine if differences were associated with global and domain-specific cognitive functioning.

Method

Participants were 48 FHP and 46 FHN demographically matched, healthy, substance-naive 12- to 14-year-olds (54% female) recruited from local middle schools. Participants completed a neuropsychological test battery and magnetic resonance imaging session, including DTI.

Results

FHP youth had higher fractional anisotropy and axial diffusivity, and lower radial and mean diffusivity, than FHN youth in 19 clusters spanning projection, association and interhemispheric white matter tracts. Findings were replicated after controlling for age, gender, socio-economic status, grade and pubertal development. Groups did not differ significantly on global or domain-specific neuropsychological test scores.

Conclusions

FHP teens showed higher white matter integrity, but similar cognitive functioning, to FHN youth. More mature neural features could be related to more precocious behaviors, such as substance use initiation, in FHP youth. Future research exploring white matter maturation before and after substance use initiation will help elucidate the neurodevelopmental trajectories in youth at risk for substance use disorders, to inform preventive efforts and better understand the sequelae of adolescent alcohol and drug use.

Keywords

Adolescencediffusion tensor imagingfamily historyneuropsychological functioningstructural connectivitysubstance use disorderswhite matter integrity
Type
Original Articles
Information
Psychological Medicine , Volume 44 , Issue 13 , October 2014 , pp. 2775 - 2786
Copyright
Copyright © Cambridge University Press 2014 

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References

Acheson, A, Vincent, AS, Sorocco, KH, Lovallo, WR (2011). Greater discounting of delayed rewards in young adults with family histories of alcohol and drug use disorders: studies from the Oklahoma family health patterns project. Alcoholism: Clinical and Experimental Research 35, 1607–1613.Google ScholarPubMed
Andersson, JL, Skare, S (2002). A model-based method for retrospective correction of geometric distortions in diffusion-weighted EPI. NeuroImage 16, 177–199.CrossRefGoogle ScholarPubMed
Andreasen, NC, Rice, J, Endicott, J, Reich, T, Coryell, W (1986). The family history approach to diagnosis. How useful is it? Archives of General Psychiatry 43, 421–429.CrossRefGoogle Scholar
APA (1994). Diagnostic and Statistical Manual of Mental Disorders, 4th edn (DSM-IV). American Psychiatric Association: Washington, DC.Google Scholar
Barnea-Goraly, N, Menon, V, Eckert, M, Tamm, L, Bammer, R, Karchemskiy, A, Dant, CC, Reiss, AL (2005). White matter development during childhood and adolescence: a cross-sectional diffusion tensor imaging study. Cerebral Cortex 15, 1848–1854.CrossRefGoogle ScholarPubMed
Basser, PJ, Pierpaoli, C (1996). Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. Journal of Magnetic Resonance, Series B 111, 209–219.CrossRefGoogle ScholarPubMed
Bava, S, Jacobus, J, Thayer, RE, Tapert, SF (2013). Longitudinal changes in white matter integrity among adolescent substance users. Alcoholism: Clinical and Experimental Research 37, E181–E189.CrossRefGoogle ScholarPubMed
Bava, S, Thayer, R, Jacobus, J, Ward, M, Jernigan, TL, Tapert, SF (2010). Longitudinal characterization of white matter maturation during adolescence. Brain Research 1327, 38–46.CrossRefGoogle ScholarPubMed
Behrens, TE, Woolrich, MW, Jenkinson, M, Johansen-Berg, H, Nunes, RG, Clare, S, Matthews, PM, Brady, JM, Smith, SM (2003). Characterization and propagation of uncertainty in diffusion-weighted MR imaging. Magnetic Resonance in Medicine 50, 1077–1088.CrossRefGoogle ScholarPubMed
Berns, GS, Moore, S, Capra, CM (2009). Adolescent engagement in dangerous behaviors is associated with increased white matter maturity of frontal cortex. PLoS ONE 4, e6773.CrossRefGoogle ScholarPubMed
Corral, M, Holguín, SR, Cadaveira, F (2003). Neuropsychological characteristics of young children from high-density alcoholism families: a three-year follow-up. Journal of Studies on Alcohol 64, 195–199.CrossRefGoogle ScholarPubMed
Corral, MM, Holguín, SR, Cadaveira, F (1999). Neuropsychological characteristics in children of alcoholics: familial density. Journal of Studies on Alcohol 60, 509–513.CrossRefGoogle ScholarPubMed
Cox, RW (1996). AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Computers and Biomedical Research 29, 162–173.CrossRefGoogle ScholarPubMed
Cservenka, A, Herting, MM, Nagel, BJ (2012). Atypical frontal lobe activity during verbal working memory in youth with a family history of alcoholism. Drug and Alcohol Dependence 123, 98–104.CrossRefGoogle ScholarPubMed
Cservenka, A, Nagel, BJ (2012). Risky decision-making: an fMRI study of youth at high risk for alcoholism. Alcoholism: Clinical and Experimental Research 36, 604–615.CrossRefGoogle ScholarPubMed
De Bellis, MD, Van Voorhees, E, Hooper, SR, Gibler, N, Nelson, L, Hege, SG, Payne, ME, MacFall, J (2008). Diffusion tensor measures of the corpus callosum in adolescents with adolescent onset alcohol use disorders. Alcoholism: Clinical and Experimental Research 32, 395–404.CrossRefGoogle ScholarPubMed
Delis, DC, Kaplan, E, Kramer, JH (2001). The Delis–Kaplan Executive Function System: Examiner's Manual. The Psychological Corporation: San Antonio, TX.Google Scholar
Delis, DC, Kramer, JH, Kaplan, E, Ober, BA (1994). Manual for the California Verbal Learning Test–Children's Version. The Psychological Corporation: San Antonio, TX.Google Scholar
Elliott, JC, Carey, KB, Bonafide, KE (2012). Does family history of alcohol problems influence college and university drinking or substance use? A meta-analytical review. Addiction 107, 1774–1785.CrossRefGoogle ScholarPubMed
Frank, LR (2001). Anisotropy in high angular resolution diffusion-weighted MRI. Magnetic Resonance in Medicine 45, 935–939.CrossRefGoogle ScholarPubMed
Giancola, PR, Peterson, JB, Pihl, RO (1993). Risk for alcoholism, antisocial behavior, and response perseveration. Journal of Clinical Psychology 49, 423–428.3.0.CO;2-1>CrossRefGoogle ScholarPubMed
Giedd, JN (2004). Structural magnetic resonance imaging of the adolescent brain. Annals of the New York Academy of Sciences 1021, 77–85.CrossRefGoogle ScholarPubMed
Giedd, JN, Lalonde, FM, Celano, MJ, White, SL, Wallace, GL, Lee, NR, Lenroot, RK (2009). Anatomical brain magnetic resonance imaging of typically developing children and adolescents. Journal of the American Academy of Child and Adolescent Psychiatry 48, 465–470.Google Scholar
Giorgio, A, Watkins, KE, Douaud, G, James, AC, James, S, De Stefano, N, Matthews, PM, Smith, SM, Johansen-Berg, H (2008). Changes in white matter microstructure during adolescence. NeuroImage 39, 52–61.CrossRefGoogle ScholarPubMed
Gogtay, N, Giedd, JN, Lusk, L, Hayashi, KM, Greenstein, D, Vaituzis, AC, Nugent, TF III, Herman, DH, Clasen, LS, Toga, AW, Rapoport, JL, Thompson, PM (2004). Dynamic mapping of human cortical development during childhood through early adulthood. Proceedings of the National Academy of Sciences USA 101, 8174–8179.CrossRefGoogle ScholarPubMed
Harden, PW, Pihl, RO (1995). Cognitive function, cardiovascular reactivity, and behavior in boys at high risk for alcoholism. Journal of Abnormal Psychology 104, 94–103.CrossRefGoogle ScholarPubMed
Herting, MM, Fair, D, Nagel, BJ (2011). Altered fronto-cerebellar connectivity in alcohol-naïve youth with a family history of alcoholism. NeuroImage 54, 2582–2589.CrossRefGoogle ScholarPubMed
Herting, MM, Schwartz, D, Mitchell, SH, Nagel, BJ (2010). Delay discounting behavior and white matter microstructure abnormalities in youth with a family history of alcoholism. Alcoholism: Clinical and Experimental Research 34, 1590–1602.CrossRefGoogle ScholarPubMed
Hill, SY, Terwilliger, R, McDermott, M (2013). White matter microstructure, alcohol exposure, and familial risk for alcohol dependence. Psychiatry Research 212, 43–53.CrossRefGoogle ScholarPubMed
Hill, SY, Yuan, H (1999). Familial density of alcoholism and onset of adolescent drinking. Journal of Studies on Alcohol 60, 7–17.CrossRefGoogle ScholarPubMed
Hollingshead, AB (1965). Two-Factor Index of Social Position. Yale University Press: New Haven, CT. Google Scholar
Hooper, HE (1958). The Hooper Visual Organization Test Manual. Western Psychological Services: Los Angeles.Google Scholar
Hüppi, PS, Dubois, J (2006). Diffusion tensor imaging of brain development. Seminars in Fetal and Neonatal Medicine 11, 489–497.CrossRefGoogle ScholarPubMed
Huttenlocher, PR (1990). Morphometric study of human cerebral cortex development. Neuropsychologia 28, 517–527.CrossRefGoogle ScholarPubMed
Jacobus, J, Squeglia, LM, Bava, S, Tapert, SF (2013 a). White matter characterization of adolescent binge drinking with and without co-occurring marijuana use: a 3-year investigation. Psychiatry Research 214, 374–381.CrossRefGoogle ScholarPubMed
Jacobus, J, Tapert, SF (2013). Neurotoxic effects of alcohol in adolescence. Annual Review of Clinical Psychology 9, 703–721.CrossRefGoogle ScholarPubMed
Jacobus, J, Thayer, RE, Trim, RS, Bava, S, Frank, LR, Tapert, SF (2013 b). White matter integrity, substance use, and risk taking in adolescence. Psychology of Addictive Behaviors 27, 431–442.CrossRefGoogle ScholarPubMed
Jellison, BJ, Field, AS, Medow, J, Lazar, M, Salamat, MS, Alexander, AL (2004). Diffusion tensor imaging of cerebral white matter: a pictorial review of physics, fiber tract anatomy, and tumor imaging patterns. American Journal of Neuroradiology 25, 356–369.Google ScholarPubMed
Jenkinson, M (2003). Fast, automated, N-dimensional phase-unwrapping algorithm. Magnetic Resonance in Medicine 49, 193–197.CrossRefGoogle ScholarPubMed
Jenkinson, M, Bannister, P, Brady, M, Smith, S (2002). Improved optimization for the robust and accurate linear registration and motion correction of brain images. NeuroImage 17, 825–841.CrossRefGoogle ScholarPubMed
Jenkinson, M, Smith, S (2001). A global optimisation method for robust affine registration of brain images. Medical Image Analysis 5, 143–156.CrossRefGoogle ScholarPubMed
Jernigan, TL, Gamst, AC (2005). Changes in volume with age–consistency and interpretation of observed effects. Neurobiology of Aging 26, 1271–1278.CrossRefGoogle ScholarPubMed
Jezzard, P, Balaban, RS (1995). Correction for geometric distortion in echo planar images from B0 field variations. Magnetic Resonance in Medicine 34, 65–73.CrossRefGoogle ScholarPubMed
Jones, DK, Horsfield, MA, Simmons, A (1999). Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging. Magnetic Resonance in Medicine 42, 515–525.3.0.CO;2-Q>CrossRefGoogle ScholarPubMed
Le Bihan, D, Mangin, JF, Poupon, C, Clark, CA, Pappata, S, Molko, N, Chabriat, H (2001). Diffusion tensor imaging: concepts and applications. Journal of Magnetic Resonance Imaging 13, 534–546.CrossRefGoogle ScholarPubMed
Lebel, C, Gee, M, Camicioli, R, Wieler, M, Martin, W, Beaulieu, C (2012). Diffusion tensor imaging of white matter tract evolution over the lifespan. NeuroImage 60, 340–352.CrossRefGoogle ScholarPubMed
Lenroot, RK, Giedd, JN (2006). Brain development in children and adolescents: insights from anatomical magnetic resonance imaging. Neuroscience and Biobehavioral Reviews 30, 718–729.CrossRefGoogle ScholarPubMed
Lewis, RF (1995). Digit Vigilance Test. Psychological Assessment Resources: Odessa, FL. Google Scholar
Li, Q, Sun, J, Guo, L, Zang, Y, Feng, Z, Huang, X, Yang, H, Lv, Y, Huang, M, Gong, Q (2010). Increased fractional anisotropy in white matter of the right frontal region in children with attention-deficit/hyperactivity disorder: a diffusion tensor imaging study. Neuroendocrinology Letters 31, 747–753.Google ScholarPubMed
Lovallo, WR, Yechiam, E, Sorocco, KH, Vincent, AS, Collins, FL (2006). Working memory and decision-making biases in young adults with a family history of alcoholism: studies from the Oklahoma Family Health Patterns Project. Alcoholism: Clinical and Experimental Research 30, 763–773.CrossRefGoogle ScholarPubMed
Luna, B, Sweeney, JA (2004). The emergence of collaborative brain function: fMRI studies of the development of response inhibition. Annals of the New York Academy of Sciences 1021, 296–309.CrossRefGoogle ScholarPubMed
Mackiewicz Seghete, KL, Cservenka, A, Herting, MM, Nagel, BJ (2013). Atypical spatial working memory and task-general brain activity in adolescents with a family history of alcoholism. Alcoholism: Clinical and Experimental Research 37, 390–398.CrossRefGoogle ScholarPubMed
McGue, M, Iacono, WG, Legrand, LN, Elkins, I (2001). Origins and consequences of age at first drink. II. Familial risk and heritability. Alcoholism: Clinical and Experimental Research 25, 1166–1173.CrossRefGoogle ScholarPubMed
McQueeny, T, Schweinsburg, BC, Schweinsburg, AD, Jacobus, J, Bava, S, Frank, LR, Tapert, SF (2009). Altered white matter integrity in adolescent binge drinkers. Alcoholism: Clinical and Experimental Research 33, 1278–1285.CrossRefGoogle ScholarPubMed
Milberger, S, Faraone, SV, Biederman, J, Chu, MP, Feighner, JA (1999). Substance use disorders in high-risk adolescent offspring. American Journal on Addiction 8, 211–219.CrossRefGoogle ScholarPubMed
Mori, S, Oishi, K, Jiang, H, Jiang, L, Li, X, Akhter, K, Hua, K, Faria, AV, Mahmood, A, Woods, R, Toga, AW, Pike, GB, Neto, PR, Evans, A, Zhang, J, Huang, H, Miller, MI, van Zijl, P, Mazziotta, J (2008). Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template. NeuroImage 40, 570–582.CrossRefGoogle Scholar
Ozkaragoz, T, Satz, P, Noble, EP (1997). Neuropsychological functioning in sons of active alcoholic, recovering alcoholic, and social drinking fathers. Alcohol 14, 31–37.CrossRefGoogle ScholarPubMed
Petersen, AC, Crockett, L, Richards, M, Boxer, A (1988). A self-report measure of pubertal status: reliability, validity, and initial norms. Journal of Youth and Adolescence 17, 117–133.CrossRefGoogle ScholarPubMed
Pfefferbaum, A, Adalsteinsson, E, Sullivan, EV (2006 a). Dysmorphology and microstructural degradation of the corpus callosum: interaction of age and alcoholism. Neurobiology of Aging 27, 994–1009.CrossRefGoogle ScholarPubMed
Pfefferbaum, A, Adalsteinsson, E, Sullivan, EV (2006 b). Supratentorial profile of white matter microstructural integrity in recovering alcoholic men and women. Biological Psychiatry 59, 364–372.CrossRefGoogle ScholarPubMed
Pfefferbaum, A, Mathalon, DH, Sullivan, EV, Rawles, JM, Zipursky, RB, Lim, KO (1994). A quantitative magnetic resonance imaging study of changes in brain morphology from infancy to late adulthood. Archives of Neurology 51, 874–887.CrossRefGoogle ScholarPubMed
Reese, TG, Heid, O, Weisskoff, RM, Wedeen, VJ (2003). Reduction of eddy-current-induced distortion in diffusion MRI using a twice-refocused spin echo. Magnetic Resonance in Medicine 49, 177–182.CrossRefGoogle ScholarPubMed
Rey, A, Osterrieth, PA (1993). Translations of excerpts from Andre Rey's “Psychological examination of traumatic encephalopathy” and P.A. Osterrieth's “The complex figure copy test” (J. Corwin & F. W. Bylsma, Trans.). Clinical Neuropsychologist 7, 3–21.Google Scholar
Rice, JP, Reich, T, Bucholz, KK, Neuman, RJ, Fishman, R, Rochberg, N, Hesselbrock, VM, Nurnberger, JIJ, Schuckit, MA, Begleiter, H (1995). Comparison of direct interview and family history diagnoses of alcohol dependence. Alcoholism: Clinical and Experimental Research 19, 1018–1023.CrossRefGoogle ScholarPubMed
Roberts, TP, Schwartz, ES (2007). Principles and implementation of diffusion-weighted and diffusion tensor imaging. Pediatric Radiology 37, 739–748.CrossRefGoogle ScholarPubMed
Sarkar, S, Craig, MC, Catani, M, Dell'acqua, F, Fahy, T, Deeley, Q, Murphy, DG (2013). Frontotemporal white-matter microstructural abnormalities in adolescents with conduct disorder: a diffusion tensor imaging study. Psychological Medicine 43, 401–411.CrossRefGoogle ScholarPubMed
Schmithorst, VJ, Wilke, M, Dardzinski, BJ, Holland, SK (2002). Correlation of white matter diffusivity and anisotropy with age during childhood and adolescence: a cross-sectional diffusion-tensor MR imaging study. Radiology 222, 212–218.CrossRefGoogle ScholarPubMed
Schmithorst, VJ, Yuan, W (2010). White matter development during adolescence as shown by diffusion MRI. Brain and Cognition 72, 16–25.CrossRefGoogle ScholarPubMed
Schweinsburg, AD, Paulus, MP, Barlett, VC, Killeen, LA, Caldwell, LC, Pulido, C, Brown, SA, Tapert, SF (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.CrossRefGoogle ScholarPubMed
Shaffer, D, Fisher, P, Lucas, CP, Dulcan, MK, Schwab-Stone, ME (2000). NIMH Diagnostic Interview Schedule for Children Version IV (NIMH DISC-IV): description, differences from previous versions, and reliability of some common diagnoses. Journal of the American Academy of Child and Adolescent Psychiatry 39, 28–38.CrossRefGoogle ScholarPubMed
Silveri, MM, Rogowska, J, McCaffrey, A, Yurgelun-Todd, DA (2011). Adolescents at risk for alcohol abuse demonstrate altered frontal lobe activation during Stroop performance. Alcoholism: Clinical and Experimental Research 35, 218–228.CrossRefGoogle ScholarPubMed
Smith, SM, Jenkinson, M, Johansen-Berg, H, Rueckert, D, Nichols, TE, Mackay, CE, Watkins, KE, Ciccarelli, O, Cader, MZ, Matthews, PM, Behrens, TE (2006). Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. NeuroImage 31, 1487–1505.CrossRefGoogle ScholarPubMed
Smith, SM, Jenkinson, M, Woolrich, MW, Beckmann, CF, Behrens, TE, Johansen-Berg, H, Bannister, PR, De Luca, M, Drobnjak, I, Flitney, DE, Niazy, RK, Saunders, J, Vickers, J, Zhang, Y, De Stefano, N, Brady, JM, Matthews, PM (2004). Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage 23, S208–S219.CrossRefGoogle ScholarPubMed
Smith, SM, Johansen-Berg, H, Jenkinson, M, Rueckert, D, Nichols, TE, Miller, KL, Robson, MD, Jones, DK, Klein, JC, Bartsch, AJ, Behrens, TE (2007). Acquisition and voxelwise analysis of multi-subject diffusion data with tract-based spatial statistics. Nature Protocols 2, 499–503.CrossRefGoogle ScholarPubMed
Sowell, ER, Thompson, PM, Holmes, CJ, Jernigan, TL, Toga, AW (1999). In vivo evidence for post adolescent brain maturation in frontal and striatal regions. Nature Neuroscience 2, 859–861.CrossRefGoogle ScholarPubMed
Sowell, ER, Thompson, PM, Leonard, CM, Welcome, SE, Kan, E, Toga, AW (2004). Longitudinal mapping of cortical thickness and brain growth in normal children. Journal of Neuroscience 24, 8223–8231.CrossRefGoogle ScholarPubMed
Spadoni, AD, Norman, AL, Schweinsburg, AD, Tapert, SF (2008). Effects of family history of alcohol use disorders on spatial working memory BOLD response in adolescents. Alcoholism: Clinical and Experimental Research 32, 1135–1145.CrossRefGoogle ScholarPubMed
Squeglia, LM, Jacobus, J, Brumback, T, Meloy, MJ, Tapert, SF (in press). White matter integrity in alcohol-naive youth with a family history of alcohol use disorders. Psychological Medicine.Google Scholar
Squeglia, LM, Jacobus, J, Sorg, SF, Jernigan, TL, Tapert, SF (2013 a). Early adolescent cortical thinning is related to better neuropsychological performance. Journal of the International Neuropsychological Society 19, 962–970.CrossRefGoogle ScholarPubMed
Squeglia, LM, Jacobus, J, Tapert, SF (2009 a). The influence of substance use on adolescent brain development. Clinical EEG and Neuroscience 40, 31–38.CrossRefGoogle ScholarPubMed
Squeglia, LM, McKenna, BS, Jacobus, J, Castro, N, Sorg, SF, Tapert, SF (2013 b). BOLD response to working memory not related to cortical thickness during early adolescence. Brain Research 1537, 59–68.CrossRefGoogle Scholar
Squeglia, LM, Pulido, C, Wetherill, RR, Jacobus, J, Brown, GG, Tapert, SF (2012). Brain response to working memory over three years of adolescence: influence of initiating heavy drinking. Journal of Studies on Alcohol and Drugs 73, 749–760.CrossRefGoogle ScholarPubMed
Squeglia, LM, Spadoni, AD, Infante, MA, Myers, MG, Tapert, SF (2009 b). Initiating moderate to heavy alcohol use predicts changes in neuropsychological functioning for adolescent girls and boys. Psychology of Addictive Behaviors 23, 715–722.CrossRefGoogle ScholarPubMed
Stiles, J, Jernigan, TL (2010). The basics of brain development. Neuropsychology Review 20, 327–348.CrossRefGoogle ScholarPubMed
Stoltenberg, SF, Mudd, SA, Blow, FC, Hill, EM (1988). Evaluating measures of family history of alcoholism: density versus dichotomy. Addiction 93, 1511–1520.CrossRefGoogle Scholar
Tamnes, CK, Ostby, Y, Fjell, AM, Westlye, LT, Due-Tønnessen, P, Walhovd, KB (2010). Brain maturation in adolescence and young adulthood: regional age-related changes in cortical thickness and white matter volume and microstructure. Cerebral Cortex 20, 534–548.CrossRefGoogle Scholar
Tarter, RE, Jacob, T, Bremer, DL (1989). Specific cognitive impairment in sons of early onset alcoholics. Alcoholism: Clinical and Experimental Research 13, 786–789.CrossRefGoogle ScholarPubMed
Wakana, S, Jiang, H, Nagae-Poetscher, LM, van Zijl, PC, Mori, S (2004). Fiber tract-based atlas of human white matter anatomy. Radiology 230, 77–87.CrossRefGoogle ScholarPubMed
Ward, BD (2000). Simultaneous inference for fMRI data (http://afni.nimh.nih.gov/afni/doc/manual/AlphaSim). Accessed 15 June 2013.Google Scholar
Wechsler, D (1991). Wechsler Intelligence Scale for Children, 3rd edn. Psychological Corporation: New York.Google Scholar
Wechsler, D (1999). Wechsler Abbreviated Scale of Intelligence. The Psychological Corporation: San Antonio, TX.Google Scholar
Wechsler, D (2008). Wechsler Adult Intelligence Scale, 4th edn. Pearson: San Antonio, TX.Google Scholar
Wetherill, RR, Bava, S, Thompson, WK, Boucquey, V, Pulido, C, Yang, TT, Tapert, SF (2012). Frontoparietal connectivity in substance-naïve youth with and without a family history of alcoholism. Brain Research 1432, 66–73.CrossRefGoogle ScholarPubMed
Wetherill, RR, Squeglia, LM, Yang, TT, Tapert, SF (2013). A longitudinal examination of adolescent response inhibition: neural differences before and after the initiation of heavy drinking. Psychopharmacology 230, 663–671.CrossRefGoogle ScholarPubMed
Yap, QJ, Teh, I, Fusar-Poli, P, Sum, MY, Kuswanto, C, Sim, K (2013). Tracking cerebral white matter changes across the lifespan: insights from diffusion tensor imaging studies. Journal of Neural Transmission 120, 1369–1395.CrossRefGoogle ScholarPubMed
Zucker, RA, Ellis, DA, Fitzgerald, HE (1994). Developmental evidence for at least two alcoholisms: I. Biopyschosocial variation among pathways into symptomatic difficulty. Annals of the New York Academy of Sciences 708, 134–146.CrossRefGoogle Scholar