Abstract
Children (n = 122) and adults (n = 200) with dyslexia completed rapid automatic naming (RAN) letters, rapid automatic switching (RAS) letters and numbers, executive function (inhibition, verbal fluency), and phonological working memory tasks. Typically developing 3rd (n = 117) and 5th (n = 103) graders completed the RAS task. Instead of analyzing RAN/RAS results the usual way (total time), growth mixture modeling assessed trajectories of successive times for naming 10 symbols in each of five rows. For all three samples and both RAN and RAS, two latent classes were identified. The “faster” class performed slowly on the first row and increased time by small increments on subsequent rows. The “slower” latent class performed more slowly on the first row, and children, but not adults, increased time by larger increments on subsequent rows. For children, both the initial row (automaticity index) and slope (sustained controlled processing index) of the trajectory differentiated the classes. For adults, only the initial row separated the classes. The longest time was on row 3 for RAN and row 4 for RAS. For the typically developing 5th graders, close in age to the children with dyslexia, the trajectories were flatter than for children with dyslexia and only the slower class (4%) showed the peak on row 4. For children with dyslexia, inhibition predicted RAN slope within the slower latent class and phonological working memory predicted RAS slope for both latent classes. For adults with dyslexia, inhibition and phonological working memory differentiated both latent classes on RAN intercept and RAS slope. Taken together, RAN, which may assess the phonological loop of working memory, and RAS, which may assess the central executive in working memory, may explain the timing deficit in dyslexia in sustaining coordinated orthographic-phonological processing over time.
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References
Abbott, R. D., Amtmann, D., & Munson, J. (2003). Exploratory and confirmatory methods in learning disabilities research. In H. L. Swanson, K. R. Harris, & J. W. Graham (Eds.), Handbood of learning disabilities (pp. 471–482). New York: Guilford Publications.
Amtmann, D., Abbott, R., & Berninger, V. (in press). Identifying and predicting classes of response to explicit, phonological spelling instruction during independent composing. Journal of Learning Disabilities.
Aylward, E., Richards, T., Berninger, V., Nagy, W., Field, K., Grimme, A., Richards, A., Thomson, J., & Cramer, S. (2003). Instructional treatment associated with changes in brain activation in children with dyslexia. Neurology, 61, 212–219.
Baddeley, A. (2002). Is working memory still working? European Psychologist, 7, 85–97.
Baddeley, A., Gathercole, S., & Papagno, C. (1998). The phonological loop as a language learning device. Psychological Review, 105, 158–173.
Berninger, V., Abbott, R., Thomson, J., & Raskind, W. (2001). Language phenotype for reading and writing disability: A family approach. Scientific Studies in Reading, 5, 59–105.
Berninger, V. (2006). A developmental approach to learning disabilities. In I. Siegel, & A.␣Renninger (Eds.), Handbook of Child Psychology, Vol. IV, Child Psychology and Practice (pp. 420–452). New York: John Wiley & Sons.
Berninger, V. (in press). Defining and differentiating dyslexia, dysgraphia, and language learning disability within a working memory model. To appear in E. Silliman, M. Mody (Eds.), Language impairment and reading disability-interactions among brain, behavior, and experience. Guilford Press.
Berninger, V., Abbott, R., Jones, J., Wolf, B., Gould, L., Anderson-Youngstrom, M., Shimada, S., & Apel, K. (2006). Early development of language by hand: Composing-, reading-, listening-, and speaking- connections, three letter writing modes, and fast mapping in spelling. Developmental Neuropsychology, 29, 61–92.
Berninger, V., Abbott, R., Thomson, J., Wagner, R., Swanson, H. L., Wijsman, E., & Raskind, W. (2006). Modeling developmental phonological core deficits within a working-memory architecture in children and adults with developmental dyslexia. Scientific Studies in Reading, 10, 165–198.
Berninger, V., Nagy, W., Richards, T., & Raskind, W. (in press). Developmental dyslexia: A developmental neurolinguistic approach. In G. Rickheit & Hans Strohner (Eds.), Communicative competence of the individual handbook of applied linguistics (HAL), 1st edn. de Gruyter Publishers.
Berninger, V., & O’Donnell, L. (2004). Research-supported differential diagnosis of specific learning disabilities. In A. Prifitera, D. Saklofske, L. Weiss, & E. Rolfhus (Eds.), WISC-IV Clinical use and interpretation (pp. 189–233). San Diego, CA: Academic Press. .
Booth, J., Burman, D., Van Sante, F., Hgarasaki, Y., Gitelman, D., Parrish, T., & Mesulam, M. (2001). The development of specialized brain systems in reading and oral language. Child Neuropsychology, 7, 119–141.
Bowers, P., & Wolf, M. (1993). Theoretical links between naming speed, precise timing mechanisms, and orthographic skill in dyslexia. Reading and Writing. An International Journal, 5, 69–85.
Breznitz, Z. (2002). Asynchrony of visual-orthographic and auditory-phonological word recognition processes: An underlying factor in dyslexia. Journal of Reading and Writing, 15, 15–42.
Butler, K. & Silliman, E. (Eds.) (2002). Speaking, reading, and writing in children with language learning disabilities. Mahwah, New Jersey: Lawrence Erlbaum Associates.
Byrne, B., Delaland, C., Fielding-Barnsley, R., Quain, P., Samuelsson, S., Høien, T., Corley, R., DeFries, J., Wadsworth, S., Willcutt, E., & Olson, R. (2002). Longitudinal twin study of early reading development in three countries: Preliminary results. Annals of Dylexia, 52, 4–73.
Cohen, L., Lehéricy, S., Chocon, F., Lemer, C., Rivaud, S., & Dehaene, S. (2002). Language-specific tuning of visual cortex? Functional properties of the visual word form area. Brain, 125, 1054–1069.
Compton, D. (2000a). Modeling the growth of decoding skills in first-grade children. Scientific Studies of Reading, 4, 219–259.
Compton, D. (2000b). Modeling the response of normally achieving and at-risk first grade children to word reading instruction. Annals of Dyslexia, 50, 53–84.
Compton, D. (2000c). Modeling the relationship between growth in rapid naming speed and growth in decoding skill in first grade children. Journal of Educational Psychology, 95, 225–239.
Compton, D. (2003). The influence of item composition on RAN letter performance in first-grade children. The Journal of Special Education, 37, 81–94.
Crosson B., Rao, S., Woodley, S., Rosen, A., Bobholz, J., Mayer, A., Cunningham, J., Hammeke, T., Fuller, S., Binder, J., Cox, R., & Stein, E. (1999). Mapping of semantic, phonological, and orthographic verbal working memory in normal adults with functional magnetic resonance imaging. Neuropsychology, 13, 171–187.
Delis, D. C., Kaplan, E., & Kramer, J. H. (2001). Delis–Kaplan executive function system. San Antonio, TX: Psychological Corporation.
Denckla, M., & Rudel, R. (1976). Rapid “automatized” naming (R.A.N.): Dyslexia differentiated from other learning disabilities. Neuropsychologia, 14, 471–479.
Greenblatt, E., Mattis, S., & Trad, P. (1990). Nature and prevalence of learning disabilities in a child psychiatric population. Developmental Neuropsychology, 6, 71–83.
Gunter, T., Wagner, S., & Friederici, A. (2003). Working memory and lexical ambiguity resolution as revealed by ERPS: A difficult case for activation theories. Journal of Cognitive Neuroscience, 15, 643–657.
Hitch, G. J. & Baddeley, A. (1976). Verbal reasoning and working memory. Quarterly Journal of Experimental Psychology, 28, 603–621.
Kail R. (1984). The development of memory in children, 2nd ed. New York: W. H. Freeman & Co.
Liederman, J., Kantrowitz L., & Flannery, K. (2005). Male vulnerability to reading disability is not likely to be a myth: A call for new data. Journal of Learning Disabilities, 38, 109–129.
Lubke, G. H. & Muthern, B. (2005). Investigating population heterogeneity with factor mixture models. Psychological Methods, 10(1), 21–39.
Lyon, G. R., Shaywitz, S., & Shaywitz, B. (2003). A definition of dyslexia. Annals of Dyslexia, 53, 1–14.
Manis, F., Seidenberg, M., & Doi, L. (1999). See Dick RAN: Rapid naming and the longitudinal prediction of reading subskills in first and second graders. Scientific Studies of Reading, 3, 129–157.
McCrory E., Frith, U., Brunswick, N., & Price, C. (2000). Abnormal functional activation during a simple word repetition task: A PET study of adult dyslexics. Journal of Cognitive Neuroscience, 12, 753–762.
McLachlam, G. & Peel, D. (2000). Finite mixture models. New York: Wiley.
Miyake, A., Friedman, N., Emerson, M., Witzki, A., Howerter, A., & Wager, T. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive Psychology, 41, 49–100.
Morris R., Stuebing, K., Fletcher, J., Shaywitz, S., Lyon, G. R., Shankweiler, D., Katz, L., Francis, D., & Shaywitz, S. (1998). Subtypes of reading disability: Variability around a phonological core. Journal of Educational Psychology, 90, 347–373.
Muthen, B. O. (2001). Second-generation structural equation modeling with a combination of categorical and continuous latent variables: New opportunities for latent class/latent growth modeling. In A. Sayer, & L. M. Collins (Eds.), New methods for the analysis of change (pp. 289–322). Washington, DC: American Psychological Association.
Muthen, B. O. (2003). Statistical and substantive checking in growth mixture modeling. Psychological Methods, 8, 369–377.
Muthen, B. O. (2004). Latent variable analysis: Growth mixture modeling and related techniques for longitudinal data. In D. Kaplan (Ed.), Handbook of quantitative methodology for the social sciences (pp. 345–368). Newbury Park, CA: Sage Publications.
Muthen, B. O., Brown, C. H., Masyn, K., Jo, B., Khoo, S. T., Yang, C. C., Wang, C. P., Kellam, S., Carlin, J., & Liao, J. (2002). General growth mixture modeling for randomized preventive interventions. Biostatistics, 3, 459–475.
Muthen, B. O., Khoo, S. T., Francis, D. J., & Boscardin, C. K. (2000). Analysis of reading skills development from kindergarten through first grade: An application of growth mixture modeling to sequential processes. In S. R. Reise & N. Duan (Eds.), Multilevel modeling: Methodological advances, issues, and applications. Mahaw, NJ: Lawrence Erlbaum Associates.
Muthen, B. O. & Muthen, L. K. (1998–2006). Mplus user’s guide, 4th ed. Los Angeles, CA: B.␣Muthen & L. Muthen.
Muthen, B. O. & Muthen, L. K. (2000). Integrating person-centered and variable-centered analyses: Growth mixture modeling with latent trajectory classes. Alcoholism Clinical and Experimental Research, 24(6), 882–891.
Muthen, B. & Shedden, K. (1999). Finite mixture modeling with mixture outcomes using the EM algorithm. Biometrics, 55, 463–469.
Nicolson, R. & Fawcett, A. (1990). Automaticity: A new framework for dyslexia research? Cognition, 35, 159–182.
Olson, R., Forsberg H., & Wise, B. (1994). Genes, environment, and the development of orthographic skills. In V. W. Berninger (Ed.) The varieties of orthographic knowledge I: Theoretical and developmental issues (pp. 27–71). Dordrecht, The Netherlands: Kluwer Academic Publishers.
Oxford, M. L., Gilchrist, L. D., Morrison, D. M., Gillmore, M. Rl, Lohr, M. J., & Lewis, S. M. (2003). Alcohol use among adolescent mothers: Heterogeneity in growth curves, predictors, and outcomes of alcohol use over time. Prevention Science, 4, 15–26.
Parrila, R., Aunola, K., Leskinen, E, Nurmi, J., & Kirby, J. R. (2005). Development of individuals differences in reading: Results from longitudinal studies in English and Finnish. Journal of Educational Psychology, 97(3), 299–319.
The Psychological Corporation (2002). Wechsler individual achievement test, 2nd ed. San Antonio, TX: Psychological Corporation. .
Ramaswamy, V., DeSarbo, W., Reibstein, D., & Robinson, W. (1993). An empirical pooling approach for estimating marketing mix elasticities with pims data. Marketing Science, 12, 103–124.
Richards, T., Aylward, E., Berninger V., Field, K., Parsons A., Richards, A., & Nagy W. (2006a). Individual fMRI activation in orthographic mapping and morpheme mapping after orthographic or morphological spelling treatment in child dyslexics. Journal of Neurolinguistics, 19, 56–86.
Richards, T., Aylward, E., Raskind, W., Abbott, R., Field, K., Parsons, A., Richards, A., Nagy, W., Eckert, M., Leonard, C., & Berninger, V. (2006b) Converging evidence for triple word form theory in child dyslexics. Developmental Neuropsychology, 30, 547–590.
Richards, T., Berninger, V., Nagy, W., Parsons, A., Field, K., & Richards, A. (2005). Dynamic assessment of child dyslexics’ brain response to alternative spelling treatments. Educational and Child Psychology, 22, 62–80.
Schneider, W. & Shiffrin, R. (1977). Controlled and automatic human information processing: 1. Detection, search, and attention. Psychological Review, 84, 1–66.
Shaeffer, C. M., Petras, H., Ialongo, N., Poduska, J., & Kellam S. (2003). Modeling growth in boy’s aggressive behavior across elementary school: Links to later criminal involvement, conduct disorder, and antisocial personality disorder. Developmental Psychology, 39, 1020–1035.
Schwartz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6, 461–464.
Swanson, H. L. (1993). Executive processing in learning disabled readers. Intelligence, 17, 117–149.
Swanson, H. L. (2000). Working memory, short-term memory, speech rate, word recognition and reading comprehension in learning disabled readers: Does the executive system have a role? Intelligence, 28, 1–30.
Swanson, H. L., Carson, C., & Sasche-Lee, C. (1996). A selective synthesis of intervention research for students with learning disabilities. School Psychology Review, 25, 370–391.
Torgesen, J. K., Wagner, R. K., & Rashotte, C. A. (1999). Test of word reading efficiency. Austin, TX: PRO-ED.
Vellutino, F., Scanlon, D., & Tanzman, M. (1991). Bridging the gap between cognitive and neuropsychological conceptualizations of reading disabilities. Learning and Individual Differences, 3, 181–203.
Waber, D. (2001). Aberrations in timing in children with impaired reading: Cause, effect, or correlate? In M. Wolf (Ed.), Dyslexia, fluency, and the brain (pp. 103–125). Extraordinary Brain Series. Baltimore: York Press.
Wadsworth, S., Olson, R., Pennington, B., & DeFries, J. (2000). Differential genetic etiology of reading disability as a function of IQ. Journal of Learning Disabilities, 33, 192–199.
Wagner, R. K., Torgesen, J. K., & Rashotte, C. A. (1999). The comprehensive test of phonological processing. Austin, TX: PRO-ED.
Wallach, G. & Butler, K. (Eds.) (1994). Language learning disabilities in school-age children and adolescents: Some principles and applications, 2nd ed. New York: Maxwell Macmillan International.
Wechsler, D. (1981). Wechsler adult intelligence scale—revised. San Antonio, TX: Psychological Corporation.
Wechsler, D. (1991). Wechsler intelligence scale for children, 3rd ed. San Antonio, TX: Psychological Corporation.
Wiederholt, J., & Bryant B. (1992). Gray oral reading test, 3rd ed. Odessa, FL: Psychological Assessment Resources. .
Wilkinson, G. (1993). Wide range achievement tests—revised. Wilmington, DE: Wide Range, Inc.
Wimmer, H. & Mayringer H. (2001). Is the reading-rate problem of German dyslexic children caused by slow visual processes? In M. Wolf (Ed.), Dyslexia, fluency, and the brain (pp. 93–102). Extraordinary Brain Series. Baltimore: York Press.
Wolf, M. (1986). Rapid alternating stimulus naming in the developmental dyslexias. Brain and Language, 27, 360–379.
Wolf, M. (1999). What time may tell: Towards a new conceptualization of dyslexia. Annals of Dyslexia, 49, 3–28.
Wolf, M. (Ed.) (2001). Dyslexia, fluency, and the brain. Extraordinary Brain Series. Baltimore: York Press.
Wolf, M., Bally, H., & Morris, R. (1986). Automaticity, retrieval processes, and reading: A longitudinal study in average and impaired reading. Child Development, 57, 988–1000.
Wolf, M., & Bowers P. (1999). The double-deficit hypothesis for the developmental dyslexias. Journal of Educational Psychology, 91, 415–438.
Wolf, M., Bowers, P., & Biddle, K. (2000). Naming-speed processes, timing, and reading: A conceptual review. Journal of Learning Disabilities, 33, 322–324.
Wolf, M., & Denckla, M. (2004). Test of rapid automatic naming. Austin, TXo: PRO-ED.
Wolff, P., Cohen, C., & Drake, C. (1984). Impaired motor timing control in specific reading retardation. Neuropsychologia, 22, 587–600.
Woodcock, R. (1987). Woodcock reading mastery tests—revised. Circle Pines, MN: American Guidance Service.
Woodcock, R. & Johnson, B. (1990). Woodcock–Johnson psycho-educational battery revised tests of achievement. Chicago: Riverside Publishing.
Acknowledgements
The authors thank Maryanne Wolf for giving us the prepublication versions of RAN letters and RAS letters and numbers to use in our research and Richard Wagner for his suggestion to analyze RAN times by row. They also thank Jon Organ for assistance in table formatting.
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This research was supported by Grant Ns. P50 33812 and R01 HD25858 from the National Institute of Child Health and Human Development, Virginia W. Berninger, PI.
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Amtmann, D., Abbott, R.D. & Berninger, V.W. Mixture growth models of RAN and RAS row by row: insight into the reading system at work over time. Read Writ 20, 785–813 (2007). https://doi.org/10.1007/s11145-006-9041-y
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DOI: https://doi.org/10.1007/s11145-006-9041-y