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Neuroimaging correlates of parent ratings of working memory in typically developing children

Published online by Cambridge University Press:  01 January 2009

E. MARK MAHONE ,
REBECCA MARTIN ,
WENDY R. KATES ,
TRISHA HAY  and
ALENA HORSKÁ
E. MARK MAHONE*
Affiliation:
Department of Neuropsychology, Kennedy Krieger Institute, Baltimore, Maryland Department of Psychiatry and Behavior Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
REBECCA MARTIN
Affiliation:
Department of Neuropsychology, Kennedy Krieger Institute, Baltimore, Maryland
WENDY R. KATES
Affiliation:
Department of Psychiatry and Behavior Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland Department of Psychiatry, SUNY Upstate Medical University, Syracuse, New York
TRISHA HAY
Affiliation:
Department of Psychology, University of Kansas, Lawrence, Kansas
ALENA HORSKÁ
Affiliation:
Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland
*
*Correspondence and reprint requests to: E. Mark Mahone, Department of Neuropsychology, Kennedy Krieger Institute, 1750 East Fairmount Avenue, Baltimore, MD 21231. E-mail: [email protected]
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Abstract

The purpose of the present study was to investigate construct validity of parent ratings of working memory in children, using a multi-trait/multi-method design including neuroimaging, rating scales, and performance-based measures. Thirty-five typically developing children completed performance-based tests of working memory and nonexecutive function (EF) skills, received volumetric MRI, and were rated by parents on both EF-specific and broad behavior rating scales. After controlling for total cerebral volume and age, parent ratings of working memory were significantly correlated with frontal gray, but not temporal, parietal, or occipital gray, or any lobar white matter volumes. Performance-based measures of working memory were also moderately correlated with frontal lobe gray matter volume; however, non-EF parent ratings and non-EF performance-based measures were not correlated with frontal lobe volumes. Results provide preliminary support for the convergent and discriminant validity of parent ratings of working memory, and emphasize their utility in exploring brain–behavior relationships in children. Rating scales that directly examine EF skills may potentially have ecological validity, not only for “everyday” function, but also as correlates of brain volume. (JINS, 2009, 15, 31–41.)

Keywords

Working memoryExecutive functionEcological validityRating scalesMRIBrain volumesNormal development
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 15 , Issue 1 , January 2009 , pp. 31 - 41
Copyright
Copyright © INS 2009

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References

REFERENCES

Achenbach, T.M. & Rescorla, L.A. (2000). Manual for the ASEBA preschool forms and profiles. Burlington, VT: University of Vermont, Research Center for Children, Youth, & Families.Google Scholar
American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders, Fourth Edition. Washington, DC: American Psychiatric Association.Google Scholar
Anderson, V.A., Anderson, P., Northam, E., Jacobs, R., & Mikiewicz, O. (2002). Relationships between cognitive and behavioral measures of executive function in children with brain disease. Child Neuropsychology, 8, 231–240.CrossRefGoogle ScholarPubMed
Andreasen, N.C., Cizadlo, T., Harris, G., Swayze, V. Jr. , O’Leary, D.S., Cohen, G., Ehrhardt, J., & Yuh, W.T. (1993). Voxel processing techniques for the antemortem study of neuroanatomy and neuropathology using magnetic resonance imaging. Journal of Neuropsychiatry and Clinical Neuroscience, 5, 121–130.Google ScholarPubMed
Antschel, K.M., Conchelos, J., Lanzetta, G., Fremont, W., & Kates, W.R. (2005). Behavior and corpus callosum morphology in velocardial facial syndrome (22q11.2 deletion syndrome). Psychiatry Research, 138, 235–245.CrossRefGoogle Scholar
Baldo, J.V. & Dronkers, N.F. (2006). The role of inferior parietal and inferior frontal cortex in working memory. Neuropsychology, 20, 529–538.CrossRefGoogle ScholarPubMed
Bearden, C.E., van Erp, T.G., Monterosso, J.R., Simon, T.J., Glahn, D.C., Saleh, P.A., Hill, N.M., McDonald-McGinn, D.M., Zakai, E., Emanual, B.S., & Cannon, T.D. (2004). Regional brain abnormalities in 22q11.2 deletion syndrome: Association with cognitive abilities and behavioral symptoms. Neurocase, 10, 198–206.CrossRefGoogle Scholar
Bernstein, J. & Waber, D. (1990). Developmental neuropsychological assessment: The systemic approach. In Boulton, A., Baker, G., & Hiscock, M. (Eds.), Neuromethods: Neuropsychology (pp. 311–371). Clifton, NJ: Humana Press.CrossRefGoogle Scholar
Bigler, E.D., Mortensen, S., Neeley, E.S., Ozonoff, S., Krasny, L., Johnson, M., Lu, J., Provencal, S.L., McMahon, W., & Lainhart, J.E. (2007). Superior temporal gyrus, language function, and autism. Developmental Neuropsychology, 31, 217–238.CrossRefGoogle ScholarPubMed
Bodnar, L.E., Prahme, M.C., Cutting, L.E., Denckla, M.B., & Mahone, E.M. (2007). Construct validity of parent ratings of inhibitory control. Child Neuropsychology, 13, 345–362.CrossRefGoogle ScholarPubMed
Carey, M.E., Haut, M.W., Reminger, S.L., Hutter, J.J., Theilman, R., & Kaemingk, K.L. (2008). Reduced frontal white matter volume in long-term childhood leukemia survivors: A voxel-based morphometry study. American Journal of Neuroradiology, 29, 792–797.CrossRefGoogle ScholarPubMed
Castellanos, F.X., Giedd, J.N., Berquin, P.C., Walter, J.M., Sharp, W., Tran, T., Vaituzis, A.C., Blumenthal, J.D., Nelson, J., Bastain, T.M., Zijdenbos, A., Evans, A.C., & Rapoport, J.L. (2001). Quantitative brain magnetic resonance imaging in girls with attention-deficit/hyperactivity disorder. Archives of General Psychiatry, 58, 289–295.CrossRefGoogle ScholarPubMed
Castellanos, F.X. & Tannock, R. (2002). Neuroscience of attention-deficit/hyperactivity disorder: The search for endophenotypes. Nature Reviews. Neuroscience, 3, 617–628.CrossRefGoogle ScholarPubMed
Chaytor, N., Schmitter-Edgecombe, M., Burr, R. (2006). Improving the ecological validity of executive function assessment. Archives of Clinical Neuropsychology, 21, 217–227.CrossRefGoogle Scholar
Conway, A.R., Kane, M.J., Bunting, M.F., Hambrick, D.Z., Wilhelm, O., & Engle, R.W. (2005). Working memory span tasks: A methodological review and user’s guide. Psychonomic Bulletin & Review, 12, 769–786.CrossRefGoogle ScholarPubMed
Courtney, S.M., Petit, L., Maisog, J.M., Ungerleider, L.G., & Haxby, J.V. (1998). An area specialized for spatial working memory in human frontal cortex. Science, 279, 1347–1351.CrossRefGoogle ScholarPubMed
Cripe, L.I. (1996). The MMPI in neuropsychological assessment: A murky measure. Applied Neuropsychology, 3, 97–103.CrossRefGoogle ScholarPubMed
Cummings, D.D., Singer, H.S., Krieger, M., Miller, T.L., & Mahone, E.M. (2002). Neuropsychiatric effects of guanfacine in children with mild Tourette syndrome: A pilot study. Clinical Neuropharmacology, 25, 325–332.CrossRefGoogle ScholarPubMed
D’Esposito, M., Postle, B.R., Ballard, D., & Lease, J. (1999). Maintenance versus manipulation of information held in working memory: An event-related fMRI study. Brain Cognition, 41, 66–86.CrossRefGoogle ScholarPubMed
D’Esposito, M., Postle, B.R., & Rypma, B. (2000). Prefrontal cortical contributions to working memory: Evidence from event-related fMRI studies. Experimental Brain Research, 133, 3–11.CrossRefGoogle ScholarPubMed
Donders, J. (2002). The Behavior Rating Inventory of Executive Function: Introduction. Child Neuropsychology, 4, 229–230.CrossRefGoogle Scholar
Dunn, L.M. & Dunn, L.M. (1997). Peabody Picture Vocabulary Test: Third Edition. Bloomington, MN: Pearson Assessments.Google Scholar
Fletcher, P.C. & Henson, R.N. (2001). Frontal lobes and human memory: Insights from functional imaging. Brain, 124, 849–881.CrossRefGoogle Scholar
Giedd, J.N., Castellanos, F.X., Casey, B.J., Kozuch, P., King, A.C., Hamburger, S.D., & Rapoport, J.L. (1994). Quantitative morphology of the corpus callosum in attention deficit hyperactivity disorder. American Journal of Psychiatry, 151, 665–669.Google ScholarPubMed
Gilotty, L., Kenworthy, L., Sirian, L., Black, D.O., & Wagner, A.E. (2002). Adaptive skills and executive function in autism spectrum disorders. Child Neuropsychology, 8, 241–248.CrossRefGoogle ScholarPubMed
Gioia, G.A., Isquith, P.K., Guy, S.C., & Kenworthy, L. (2000). Behavior rating inventory of executive function. Odessa, FL: Psychological Assessment Resources.Google Scholar
Goldberg, M.C., Mostofsky, S.H., Cutting, L.E., Mahone, E.M., Astor, B.C., Denckla, M.B., & Landa, R.J. (2005). Subtle executive impairment in children with autism and children with ADHD. Journal of Autism and Developmental Disorders, 35, 279–293.CrossRefGoogle ScholarPubMed
Harley, A.A. & Speer, N.K. (2000). Locating and fractionating working memory using functional neuroimaging: Storage, maintenance, and executive functions. Microscopy Research and Technique, 51, 45–53.3.0.CO;2-O>CrossRefGoogle Scholar
Hays, W.L. (1988). Statistics (4th ed.). Orlando, FL: Harcourt Brace Jovanovich, Inc.Google Scholar
Hollingshead, A.B. (1975). Four factor index of social status. New Haven, CT: Yale University, Department of Sociology.Google Scholar
Kaplan, D.M., Liu, A.M.C., Abrams, M.T., White, C.D., Warsofsky, I.S., & Reiss, A.L. (1997). Application of a rapid automated, Talairach-based parcellation method to the analysis of pediatric brain volumes. Psychiatry Research: Neuroimaging Section, 76, 15–27.CrossRefGoogle Scholar
Kates, W.R., Abrams, M.T., Kaufmann, W.E., Breiter, S.N., & Reiss, A.L. (1997). Reliability and validity of MRI measurement of the amygdala and hippocampus in children with fragile X syndrome. Psychiatry Research, 75, 31–48.CrossRefGoogle ScholarPubMed
Kates, W.R., Warsofsky, I.S., Patwardhan, A., Abrams, M.T., Liu, A.M.C., Naidu, S., Kaufmann, W. E., & Reiss, A.L. (1999). Automated Talairach atlas-based parcellation and measurement of cerebral lobes in children. Psychiatry Research Neuroimaging, 91, 11–30.CrossRefGoogle ScholarPubMed
Kibby, M.Y., Kroese, J.M., Morgan, A.E., Hiemenz, J.R., Cohen, M.J., & Hynd, G.W. (2004). The relationship between perisylvian morphology and verbal short-term memory functioning in children with neurodevelopmental disorders. Brain and Language, 89, 122–135.CrossRefGoogle ScholarPubMed
Konczak, J., Schoch, B., Dimitrova, A., Gizewski, E., & Timmann, D. (2005). Functional recovery of children and adolescents after cerebellar brain tumour resection. Brain, 128, 1428–1441.CrossRefGoogle Scholar
Kramer, J.H., Quitania, L., Dean, D., Neuhaus, J., Rosen, H.J., Halabi, C., Weiner, M.W., Magnotta, V.A., Delis, D.C., & Miller, B.L. (2007). Magnetic resonance imaging correlates of set shifting. Journal of the International Neuropsychological Society; JINS, 13, 386–392.CrossRefGoogle ScholarPubMed
Leffard, S.A., Miller, J.A., Bernstein, J., DeMann, J.J., Mangis, H.A., & McCoy, E.L. (2006). Substantive validity of working memory measures in major cognitive functioning test batteries for children. Applied Neuropsychology, 13, 230–241.CrossRefGoogle ScholarPubMed
Lenroot, R.K. & Giedd, J.N. (2006). Brain development in children and adolescents: Insights from anatomical magnetic resonance imaging. Neuroscience Biobehavioral Reviews, 30, 718–729.CrossRefGoogle ScholarPubMed
Mahone, E.M., Cirino, P.T., Cutting, L.E., Cerrone, P.M., Hagelthorn, K.M., Hiemenz, J.R., Singer, H.S., & Denckla, M.B. (2002b). Validity of the Behavior Rating Inventory of Executive Function in children with ADHD and/or Tourette syndrome. Archives of Clinical Neuropsychology, 17, 643–662.CrossRefGoogle ScholarPubMed
Mahone, E.M., Hagelthorn, K.M., Cutting, L.E., Schuerholz, L.J., Pelletier, S.F., Rawlins, C., Singer, H.S., & Denckla, M.B. (2002a). Effects of IQ on executive function measures in children with ADHD. Child Neuropsychology, 8, 52–65.CrossRefGoogle ScholarPubMed
Mahone, E.M. & Hoffman, J. (2007). Behavior ratings of executive function among preschoolers with ADHD. The Clinical Neuropsychologist, 21, 569–586.CrossRefGoogle ScholarPubMed
Mahone, E.M., Pillion, J.P., Hoffman, J., Hiemenz, J.R., & Denckla, M.B. (2005). Construct validity of the auditory continuous performance test for preschoolers. Developmental Neuropsychology, 27, 11–33.CrossRefGoogle ScholarPubMed
Mahone, E.M., Zabel, T.A., Levey, E., Verda, M., & Kinsman, S. (2002c). Parent and self-report ratings of executive function in adolescents with myelomeningocele and hydrocephalus. Child Neuropsychology, 8, 258–270.CrossRefGoogle ScholarPubMed
Mangeot, S., Armstrong, K., Colvin, A.N., Yeates, K.O., & Taylor, H.G. (2002). Long-term executive function deficits in children with traumatic brain injuries: Assessment using the Behavior Rating Inventory of Executive Function (BRIEF). Child Neuropsychology, 8, 271–284.CrossRefGoogle ScholarPubMed
Martinussen, R., Hayden, J., Hogg-Johnson, S., & Tannock, R. (2005). A meta-analysis of working memory impairments in children with attention-deficit/hyperactivity disorder. Journal of American Academy of Child and Adolescent Psychiatry, 44, 377–384.CrossRefGoogle ScholarPubMed
Mather, N. & Woodcock, R.W. (2001). Examiner’s manual: Woodcock-Johnson III tests of achievement. Itasca, IL: Riverside Publishing.Google Scholar
McGrew, K.S. & Woodcock, R.W. (2001). Technical Manual: Woodcock-Johnson III. Itasca, IL: Riverside Publishing.Google Scholar
Milner, B., Corsi, P. & Leonard, G. (1991). Frontal-lobe contribution to recency judgements. Neuropsychologia, 29, 601–618.CrossRefGoogle ScholarPubMed
Mohr, H.M., Goebel, R., & Linden, D.E. (2006). Content- and task-specific dissociations of frontal activity during maintenance and manipulation in visual working memory. Journal of Neuroscience, 26, 4465–4471.CrossRefGoogle ScholarPubMed
Mull, B.R. & Seyal, M. (2001). Transcranial magnetic stimulation of left prefrontal cortex impairs working memory. Clinical Neurophysiology, 112, 1672–1675.CrossRefGoogle ScholarPubMed
Niendam, T.A., Horwitz, J., Bearden, C.E., & Cannon, T.D. (2007). Ecological assessment of executive dysfunction in the psychosis prodrome: A pilot study. Schizophrenia Research, 93, 350–354.CrossRefGoogle ScholarPubMed
Nyden, A., Hjelmquist, E., & Gillberg, C. (2000). Autism spectrum and attention-deficit disorders in girls. Some neuropsychological aspects. European Child & Adolescent Psychiatry, 9, 180–185.Google ScholarPubMed
Ozonoff, S. & Jensen, J. (1999). Brief report: Specific executive function profiles in three neurodevelopmental disorders. Journal of Autism and Developmental Disorders, 29, 171–177.CrossRefGoogle ScholarPubMed
Pennington, B.F. & Ozonoff, S. (1996). Executive functions and developmental psychopathology. Journal of Child Psychology and Psychiatry, 37, 51–87.CrossRefGoogle ScholarPubMed
Rabin, L.A., Roth, R.M., Isquith, P.K., Wishart, H.A., Nutter-Upham, K.E., Pare, N., Flashman, L.A., & Saykin, A.J. (2006). Self- and informant reports of executive function on the BRIEF-A in MCI and older adults with cognitive complaints. Archives of Clinical Neuropsychology, 21, 721–732.CrossRefGoogle ScholarPubMed
Rama, P., Poremba, A., Sala, J.B., Yee, L., Malloy, M., Mishkin, M., & Courtney, S.M. (2004). Dissociable functional cortical topographies for working memory maintenance of voice identity and location. Cerebral Cortex, 14, 768–780.CrossRefGoogle ScholarPubMed
Reich, W., Welner, Z., & Herjanic, B. (1997). The Diagnostic Interview for Children and Adolescents-IV. North Tonawanda: Multi-Health Systems.Google Scholar
Reiss, A.L. (1999). BrainImage [computer software]. Stanford University, Department of Psychiatry.Google Scholar
Reiss, A.L., Hennessey, J.G., Rubin, M., Beach, L., Abrams, M.T., Warsofsky, I.S., Liu, A.M., & Links, J.M. (1998). Reliability and validity of an algorithm for fuzzy tissue segmentation of MRI. Journal of Computer Assisted Tomography, 22, 471–479.CrossRefGoogle ScholarPubMed
Ries, J., Zabel, T.A., & Mahone, E.M. (2003). Parent report of adaptive abilities and executive functions in children and adolescents with myelomengocele and hydrocephalus [Abstract]. Archives of Clinical Neuropsychology, 18, 762.Google Scholar
Robertson, I.H., Ward, T., Ridgeway, V., & Nimmo-Smith, I. (1994). The Test of Everyday Attention. Suffolk, UK: Thames Valley Test Co./Gaylord, MI: National Rehabilitation Services.Google Scholar
Roid, G.H. (2003). Stanford-Binet Intelligence Scales (5th ed.). Itasca, IL: Riverside Publishing.Google Scholar
Sbordone, R.J. (2000). Ecological validity issues in neuropsychological testing. Brain Injury Source, 4, 10–12.Google Scholar
Schatz, J., Kramer, J.H., Albin, A., & Mathay, K.K. (2000). Processing speed, working memory, and IQ: A developmental model of cognitive deficits following cranial radiation therapy. Neuropsychology, 14, 189–200.CrossRefGoogle ScholarPubMed
Schretlen, D. (1997). Brief Test of Attention. Odessa, FL: Psychological Assessment Resources.Google Scholar
Schrimsher, G.W., Billingsley, R.L., Jackson, E.F., & Moore, B.D. III (2002). Caudate nucleus volume asymmetry predicts attention-deficit hyperactivity disorder (ADHD) symptomatology in children. Journal of Child Neurology, 17, 877–884.CrossRefGoogle ScholarPubMed
Semrud-Clikeman, M., Steingard, R.J., Filipek, P., Biederman, J., Bekken, K., & Renshaw, P.F. (2000). Using MRI to examine brain behavior-relationships in males with Attention-Deficit Disorder with hyperactivity. Journal of the American Academy of Child and Adolescent Psychiatry, 39, 477–484.CrossRefGoogle ScholarPubMed
Sesma, H.W., Mahone, E.M., Levine, T.M., Eason, S.H., & Cutting, L.E. (2008). The contribution of executive skills to reading comprehension, language, and fluency to reading comprehension. Child Neuropsychology, 15, 1–15.Google Scholar
Sheridan, M.A., Hinshaw, S., & D’Esposito, M. (2007). Efficiency of the prefrontal cortex during working memory in attention-deficit/hyperactivity disorder. Journal of the American Academy of Child and Adolescent Psychiatry, 46, 1357–1366.CrossRefGoogle ScholarPubMed
Smith, E.E. & Jonides, J. (1999). Storage and executive processes in the frontal lobes. Science, 283, 1657–1661.CrossRefGoogle ScholarPubMed
Sowell, E.R., Mattson, S.N., Kan, E., Thompson, P.M., Riley, E.P., & Toga, A.W. (2008). Abnormal cortical thickness and brain–behavior correlation patterns in individuals with heavy prenatal alcohol exposure. Cerebral Cortex, 18, 136–144.CrossRefGoogle ScholarPubMed
Spooner, D.M. & Pachana, N.A. (2006). Ecological validity in neuropsychological assessment: A case for greater consideration in research with neurologically intact populations. Archives of Clinical Neuropsychology, 21, 327–337.CrossRefGoogle ScholarPubMed
Strauss, E., Sherman, E.M.S., & Spreen, O. (2006). Behavior rating inventory of executive function (BRIEF). In Strauss, E., Sherman, E.M.S., & Spreen, O. (Eds.), A compendium of neuropsychological tests: Administration, norms, and commentary (pp. 1090–1099). New York: Oxford University Press.Google Scholar
Subramaniam, B., Naidu, S., & Reiss, A.L. (1997). Neuroanatomy in Rett syndrome: Cerebral cortex and posterior fossa. Neurology, 48, 399–407.CrossRefGoogle ScholarPubMed
Swanson, H.L. & Alexander, J.E. (1997). Cognitive processes as predictors of word recognition and reading comprehension in learning-disabled and skilled readers: Revisiting the specificity hypothesis. Journal of Educational Psychology, 89, 128–158.CrossRefGoogle Scholar
Talairach, J. & Tournoux, P. (1988). Co-planar stereotaxic atlas of the human brain. New York: Thieme Medical Publishers, Inc.Google Scholar
Tarazi, R., Mahone, E.M., & Zabel, T.A. (2007). Self-care independence in children with neurological disorders: An interactional model of adaptive demands and executive dysfunction. Rehabilitation Psychology, 52, 196–205.CrossRefGoogle Scholar
Tarazi, R.A., Zabel, T.A., & Mahone, E.M. (2008). Age-related differences in executive function among children with spina bifida/hydrocephalus based on parent behavior ratings. The Clinical Neuropsychologist, 22, 585–602.CrossRefGoogle ScholarPubMed
Verte, S., Geurts, H.M., Roeyers, H., Oosterlaan, J., & Sergeant, J.A. (2006). The relationship of working memory, inhibition, and response variability in child psychopathology. Journal of Neuroscience Methods, 151, 5–14.CrossRefGoogle ScholarPubMed
Vriezen, E.R. & Pigott, S.E. (2002). The relationship between parental report on the BRIEF and performance-based measures of executive function in children with moderate to severe traumatic brain injury. Child Neuropsychology, 8, 296–303.CrossRefGoogle ScholarPubMed
Waber, D.P., Gerber, E.B., Turcios, V.Y., Wagner, E.R., & Forbes, P.W. (2006). Executive functions and performance on high-stakes testing in children from urban schools. Developmental Neuropsychology, 29, 459–477.CrossRefGoogle ScholarPubMed
Wechsler, D. (1991). Wechsler Intelligence Scale for Children, Third Edition (WISC-III). San Antonio, TX: Psychological Corporation.Google Scholar
Wechsler, D.L., Kaplan, E., Fein, D., Kramer, J.H., Morris, R., & Delis, D.C. (2004). Wechsler Intelligence Scale for Children - Fourth Edition - Integrated, technical and interpretive manual. San Antonio, TX: Harcourt Assessment, Inc.Google Scholar
Wells, C., Mahone, E.M., Matson, M.A., Kates, W., Hay, T., & Horska, A. (2008). Relationship of temporal lobe volumes to neuropsychological performance in healthy children. Brain and Cognition, 68, 171–179.CrossRefGoogle ScholarPubMed
Wilson, B.A., Cockburn, J., & Baddeley, A. (1985). The Rivermead Behavioral Memory Test. Reading, England: Thames Valley Test Co./Gaylord, MI: National Rehabilitation Services.Google Scholar
Wilson, B.A., Shiel, A., Foley, J., Emslie, H., Groot, Y., Hawkins, K., Groot, Y., & Evans, J.J. (2004). Cambridge Test of Prospective Memory. Bury St. Edmonds, England: Thames Valley Test Company.Google Scholar
Wodka, E.L., Loftis, C.W., Mostofsky, S.H., Prahme, C., Gidley Larson, J.C., Denckla, M.B., & Mahone, E.M. (2008). Prediction of ADHD in boys and girls using the D-KEFS. Archives of Clinical Neuropsychology, 23, 283–293.CrossRefGoogle ScholarPubMed
Woodcock, R.W., McGrew, K.S., & Mather, N. (2001). Woodcock-Johnson - III. Itasca, IL: Riverside Publishing.Google Scholar
Wozniak, J.R., Krach, L., Ward, E., Mueller, B.A., Muetzel, R., Schnoebelen, S., Kiragu, A., & Lim, K.O. (2007). Neurocognitive and neuroimaging correlates of pediatric traumatic brain injury: A diffusion tensor imaging (DTI) study. Archives of Clinical Neuropsychology, 22, 555–568.CrossRefGoogle ScholarPubMed