Palabras clave
dificultades de aprendizaje
trastorno específico de aprendizaje
dislexia
discalculia
neuroimagen
genética
trastorno específico de aprendizaje
dislexia
discalculia
neuroimagen
genética
Cómo citar
Dislexia y discalculia: una revisión sistemática actual desde la neurogenética. (2018). Universitas Psychologica, 17(3), 1-11. https://doi.org/10.11144/Javeriana.upsy17-3.ddrs
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Resumen
Los Trastornos Específicos del Aprendizaje constituyen un grupo heterogéneo de alteraciones frecuentes que pueden generar problemas importantes no solo durante la etapa escolar, sino a lo largo de toda la vida. Las dificultades persistentes en lectura (dislexia) y en matemáticas (discalculia) son, por su relevancia y prevalencia, los dos Trastornos de Aprendizaje más importantes en la práctica educativa y clínica. El objetivo del estudio es realizar una síntesis de los descubrimientos científicos de los últimos diez años sobre las bases neuroanatómicas y genéticas de la dislexia y la discalculia. Se realizó un análisis exhaustivo bibliográfico desde 2006 hasta enero de 2017 en inglés y español centrados en neuroimagen y genética de dislexia y discalculia mediante las bases de datos Medline, PsyInfo, Scopus, Web of Science y Dialnet. Se incluyeron 38 artículos de los cuales se extrajeronn las aportaciones desde la neuroimagen y la genética tanto para la dislexia como de discalculia. Estos datos facilitaron herramientas para orientar al contexto psicológico y educativo, a su vez proporcionando respuestas definitivas.
American Psychiatric Association (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington DC: APA.
Anthoni, H., Zucchelli, M., Matsson, H., Müller-Myhsok, B., Fransson, I., .. Peyrard-Janvid, M. (2007). A locus on 2p12 containing the coregulated MRPL19 and C2ORF3 genes is associated to dyslexia. Hum Mol Genet, 16(6), 667—77. https://doi.org/10.1093/hmg/ddm009
Artigas-Pallarés, J. (2009). Dislexia: enfermedad, trastorno o algo distinto. Rev Neurol, 48(Supl 2), S63-S69. Recuperado de https://www.neurologia.com/articulo/2009007
Ashkenazi, S., Rosenberg-Lee, M., Tenison, C., & Menon, V. (2012). Weak task-related modulation and stimulus representations during arithmetic problem solving in children with developmental dyscalculia. Developmental Cognitive Neuroscience, 2(1), S1, S152–S166. https://doi.org/10.1016/j.dcn.2011.09.006
Bates, T., Luciano, M., Medland, S., Montgomery, G., Wright, M. & Martin, N. (2011). Genetic variance in a component of the language acquisition device: ROBO1 polymorphisms associated with phonological buffer deficits. Behav Genet, 41(1), 50—57. https://doi.org/10.1007/s10519-010-9402-9
Benítez-Burraco, A. (2007). Bases moleculares de la Dislexia. Rev Neurol, 45(8), 491-502. Recuperado de https://www.uma.es/media/files/BASES_MOLECULARES_DE_LA_DISLEXIA.pdf
Benítez-Burraco, A. (2008). FOXP2 y la biología molecular del lenguaje: nuevas evidencias. II. Aspectos moleculares e implicaciones para la ontogenia y la filogenia del lenguaje. Neurología, 46(6), 351-359. Recuperado de https://www.unioviedo.es/biolang/pdf/FOXP2nuevasevidenciasII.pdf
Benítez-Burraco, A. (2010). Neurobiología y neurogenética de la dislexia. Neurología, 25(9), 563-81. Recuperado de https://doi.org/10.1016/j.nrl.2009.12.010
Benítez-Burraco, A. (2012). Aspectos problemáticos del análisis genético de los trastornos específicos del lenguaje, FOXP2 como paradigma. Neurología, 27(4), 225-33. https://doi.org/10.1016/j.nrl.2011.04.008
Berteletti, I., Prado, J. & Booth, J. R. (2014). Children with mathematical learning disability fail in recruiting verbal and numerical brain regions when solving simple multiplication problems. Cortex, 57, 43–55. https://doi.org/10.1016/j.cortex.2014.04.001
Bugden, S., & Ansari, D. (2015). How can cognitive developmental neuroscience constrain our understanding of developmental dyscalculia? In S. Chinn (Ed.), International handbook of dyscalculia and mathematical learning difficulties (pp. 18–43). London: Routledge. https://doi.org/10.4324/9781315740713
Cantlon, J., Davis, S., Libertus, M., Kahane, J., Brannon, E. & Pelphrey, K. (2011). Intra-parietal white matter development predicts numerical performance in children. Learn individ Differ, 21(6), 672–680. https://doi.org/10.1016/j.lindif.2011.09.003
Carboni-Román, A., Del Río Grande, D., Capilla, A., Maestú, F. & Ortiz, T. (2006). Bases neurobiológicas de las dificultades de aprendizaje. Neurología, 42(S2), S171-175. Recuperado de https://www.uma.es/media/files/BASES_NEUROLOGICAS_DE_LAS_DA.pdf
Cuadrado, P., Ho, J. & Vernes, S. (2014). Shining a light on CNTNAP2: complex functions to complex disorders. European Journal of Human Genetics, 22, 171-1788. https://doi.org/10.1038/ejhg.2013.100
Currier, T., Etchegaray, M., Haight, J., Galaburda, A. & Rosen, G. (2011). The effects of embryonic knockdown of the candidate dislexia susceptibility gene homologue Dyx1c1 on the distribution of GABAergic neurons in the cerebral cortex. Neuroscience, 172(13), 535 – 46. Recuperado de https://doi.org/10.1016/j.neuroscience.2010.11.002
Cutini, S., Szűcs, D., Mead, N., Huss, M. & Goswami, U. (2016). Atypical right hemisphere response to slow temporal modulations in children with developmental dyslexia. Neuroimage, 143, 40–49. https://doi.org/10.1016/j.neuroimage.2016.08.012
De la Peña, C. (2012). La dislexia desde la neuropsicología infantil. Madrid: Sanz y Torres.
Dehaene, S. & Cohen, L. (1995). Towards an anatomical and functional model for number processing. Math Cogn 1, 83-120. Recuperado de http://www.unicog.org/publications/DehaeneCohen_TripleCodeModelNumberProcessing_MathCognition1995.pdf
Díaz, B., Hintz, F., Kiebel, S. & Von Kriegstein, K. (2012). Dysfunction of the auditory thalamus in developmental dyslexia. Proc Natl Acad Sci U S A, 109, 13841—6. https://doi.org/10.1073/pnas.1119828109
Etchepareborda, M., Mulas, F., Gandía, R., Abad-Mas, L., Moreno-Madrid, F. & Díaz-Lucero, A. (2006). Técnica de evaluación funcional de los trastornos del neurodesarrollo. Neurología, 42(S2), S71-81. Recuperado de https://www.ncbi.nlm.nih.gov/pubmed/16555221?dopt=Abstract
Gavin, R., Price, R., Wilkey, E., Yeoa, D. & Cutting, L. (2015) The relation between 1st grade grey matter volume and 2nd grade math competence. Neuroimage, 124(Part A), 232–237. https://doi.org/10.1016/j.neuroimage.2015.08.046
Gersten, R., Clarke, B. & Mazzocco, M. (2007). Historical and contemporary perspectives on mathematical learning disabilities. In Berch D.B. & Mazzocco M.M (Eds). Why Is Math So Hard for Some Children? The nature and origins of mathematics learning difficulties and disabilities (pp. 7-27). Baltimore: Brookes Publishing.
Jolles, D., Ashkenazi, S., Kochalka, J., Evans, T., Richardson, J., … Menon, V. (2016). Parietal hyper-connectivity, aberrant brain organization, and circuit-based biomarkers in children with mathematical disabilities. Developmental Science 19(4), 613–631. https://doi.org/10.1111/desc.12399
Kadosh, R. & Walsh, V.(2007). Dyscalculia. Current Biology, 17(22) 946 – 947. https://doi.org/10.1016/j.cub.2007.08.038
Kanzafarova, R., Kazantseva, A. & Khusnutdinova, E. (2015). Genetic and environmental aspects of mathematical disabilities. Genetika, 51(3), 223-230. https://doi.org/10.1134/S1022795415010032
Klein, E., Moeller, K. & Willmes, K. (2013). A neural disconnection hypothesis on impaired numerical processing. Frontiers in Human Neuroscience,. 7, 663. https://doi.org/10.3389/fnhum.2013.00663
Kraft, I., Schreiber, J., Cafiero, R., Metere, R., Schaadt, G., … Skeide, M.A. (2016). Predicting early signs of dyslexia at a preliterate age by combining behavioral assessment with structural MRI. Neuroimage, 143, 378-386. https://doi.org/10.1016/j.neuroimage.2016.09.004
Krueger, F., Landgraf, S., Van der Meer, E., Deshpande, G. & Hu. X. (2011). Effective connectivity of the multiplication network: a functional MRI and multivariate granger causality mapping study. Human Brain Mapping, 32(9), 1419–1431. https://doi.org/10.1002/hbm.21119
Kucian, K., Ashkenazi, S., Hänggi, J., Rotzer, S., Jäncke, L., Martin, E. & Von Aster, M. (2013). Developmental dyscalculia: a dysconnection syndrome? Brain Structure & Function, 219(5), 1721-1733. https://doi.org/10.1007/s00429-013-0597-4
Kucian, K., Loenneker, T., Dietrich, T., Dosch, M., Martin, E. & Von Aster, M. (2006). Impaired neural networks for approximate calculation in dyscalculic children: a functional MRI study. Behavioral and Brain Functions, 2(31), 1-17. https://doi.org/10.1186/1744-9081-2-31
Lagae, L. (2008). Learning Disabilities: Definitions, Epidemiology, Diagnosis and Intervention Strategies. Pediatr Clin N Am, 55(6), 1259-1268. https://10.1016/j.pcl.2008.08.001
Lebel, C., Shaywitz, B., Holahan, J., Shaywitz, S., Marchione, K. & Beaulieu, C. (2013). Diffusion tensor imaging correlates of reading ability in disfluent and non-impaired readers. Brain Lang, 125(2), 215-22. https://doi.org/10.1016/j.bandl.2012.10.009
Lehongre, K., Ramus, F., Villiermet, N., Schwartz, D., Giraud, A. (2011). Altered low-gamma sampling in auditory cortex accounts for the three main facets of dyslexia. Neuron, 72(6), 1080-90. https://doi.org/10.1016/j.neuron.2011.11.002
Ludwig, K., Saman, P., Alexander, M., Becker, J., Bruder, …. Czamara, D. (2013). A common variant in myosin-18B contributes to mathematical abilities in children with dyslexia and intraparietal sulcus variability in adults. Transl Psychiatry 3(e229), 11-8. https://doi.org/10.1038/tp.2012.148
Marino, C., Mascheretti, S., Riva, V., Cattaneo, F., Rigoletto, C., …. Molteni, M. (2011). Pleiotropic effects of DCDC2 and DYX1C1 genes on language and mathematics traits in nuclear families of developmental dyslexia. Behavioral Genet, 41(1), 67-76. https://doi.org/10.1007/s10519-010-9412-7
Millá, G. (2006). Atención temprana de las dificultades de aprendizaje. Rev Neurol, 42(Supl 2), 153-156. Recuperado de http://www.mdp.edu.ar/psicologia/psico/sec-academica/asignaturas/aprendizaje/Materiales_2014/TAAtencion_temprana_de_las_dificultades_aprendizaje.pdf
Morken, F., Helland, T., Hugdahl, K. & Specht, K. (2017). Reading in dyslexia across literacy development: A longitudinal study of effective connectivity. Neuroimage,144, 92–100. https://doi.org/10.1016/j.neuroimage.2016.09.060
National Institute of Neurological Disorder and Stroke. (2016). Dyslexia Information Page. Recuperado de https://www.ninds.nih.gov/Disorders/All-Disorders/Dyslexia-Information-Page
Newbury, D., Fisher, S. & Monaco, A. (2010). Recent advances in the genetics of language impairment. Genome Med., 2, 6. https://doi.org/10.1186/gm127
Pagnamenta, A., Bacchelli, E., de Jonge, M., Mirza, G., Scerri, T., Minopoli, F., …. Moncao, A. P. (2010). Characterization of a family with rare deletions in CNTNAP5 and DOCK4 suggests novel risk loci for autism and dyslexia. Biol Psychiatry, 68(4), 320—8. https://doi.org/10.1016/j.biopsych.2010.02.002
Parachini, S., Steer, C., Buckingham, L., Morris, A., Ring, S., …. Monaco, A. P. (2008). Association of the KIAA0319 dyslexia susceptibility gene with reading skills in the general population. American Journal of Psychiatriy, 165(12), 1576-1584. https://doi.org/10.1176/appi.ajp.2008.07121872
Pernet, C., Anderson, J., Paulessu, E. & Demonet, J. (2009). When all hypotheses are right: A multifocal account of dyslexia. [Abstract]. Human Brain Imaging, 30(7), 2278-92. https://doi.org/10.1002/hbm.20670
Pernet, C., Pauline, J., Demonet, J. & Rousselet, G. (2009). Brain classification reveals the right cerebellum as the best biomarker of dyslexia. BMC Neurosci, 10, 67. https://doi.org/10.1186/1471-2202-10-67
Pettigrew, K., Fajutrao Valles, S., Moll, K., Northstone, K., Ring, S., … Paracchini, S. (2015). Lack of replication for the myosin-18B association with mathematical ability in independent cohorts. Genes Brain Behavior, 14(4), 369-76. https://10.1111/gbb.12213
Peyrin, C., Lallier, M., Démonet, J., Pernet, C., Baciu, M., Le Bas, J., et al. (2012). Neural dissociation of phonological and visual attention span disorders in developmental dyslexia: FMRI evidence from two case reports. Brain and Language, 120(3), 381-94. https://doi.org/10.1016/j.bandl.2011.12.015
Price, R. & Ansari, D. (2013). Dyscalculia: Characteristics, Causes, and Treatments. Numeracy, 6(1), 2. https:// http://scholarcommons.usf.edu/cgi/viewcontent.cgi?article=1112&context=numeracy
Pugh, K., Landi, N., Preston, J., Mencl, W.E., Austin, A. … Frost, S.J. (2013). The relationship between phonological and auditory processing and brain organization in beginning readers. Brain and Language, 125(2), 173-183.
Rimrodt, S., Peterson, D., Denckla, M., Kaufmann, W., Cutting, L. (2010). White matter microstructural differences linked to left perisylvian language network in children with dyslexia. Cortex, 46(6), 739-49. https://doi.org/10.1016/j.cortex.2009.07.008
Rotzer, S., Kucian, K., Martin, E., Von Aster, M., Klaver, P. & Loenneker, T. (2008). Optimized voxel-based morphometry in children with developmental dyscalculia. NeuroImage, 39(1), 417–422. https://doi.org/10.1016/j.neuroimage.2007.08.045
Rubinsten, O. & Henik, A. (2005). Automatic activation of internal magnitudes: A study of developmental dyscalculia. Neuropsychology, 19(5), 641–648. https://doi.org/10.1037/0894-4105.19.5.641
Rykhlevskaia, E., Uddin, L. Q., Kondos, L. & Menon, V. (2009). Neuroanatomical correlates of developmental dyscalculia: combined evidence from morphometry and tractography. Frontiers in Human Neuroscience, 3(51), 1-13. https://doi.org/10.3389/neuro.09.051.2009
Steinbrink, C., Groth, K., Lachmann, T. & Riecker, A. (2012). Neural correlates of temporal auditory processing in developmental dyslexia during German focal length discrimination: An fMRI study. Brain and Language, 121(1), 1-11. https://doi.org/10.1016/j.bandl.2011.12.003
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Szalkowski, C., Fiondella, C., Galaburda, A., Rosen, G., LoTurco, J. & Fitch, R. (2010). Neocortical disruption and behavioral impairments in rats following in utero RNAi of candidate dyslexia risk gene KIAA0319.International Journal of Developmental Neuroscience, 30(4), 293-302. https://doi.org/10.1016/j.ijdevneu.2012.01.009
Veerappa, A., Saldanha, A., Padakannaya, P. & Ramachandra, N. (2013). Genome-wide copy number scan identifies disruption of PCDH11X in developmental dyslexia. American Journal of Medical Genetics, 162(8), 889-97. https://doi.org/ 10.1002/ajmg.b.32199
Ziegler, J., Castle, C., Pech-Georgel, C., George, F., Alario, F-A. & Perry, C. (2008). Developmental dislexia and the dual route of Reading: Simulating individual differences and subtypes. Cognition, 107(1), 151-78. https://doi.org/10.1016/j.cognition.2007.09.004
Anthoni, H., Zucchelli, M., Matsson, H., Müller-Myhsok, B., Fransson, I., .. Peyrard-Janvid, M. (2007). A locus on 2p12 containing the coregulated MRPL19 and C2ORF3 genes is associated to dyslexia. Hum Mol Genet, 16(6), 667—77. https://doi.org/10.1093/hmg/ddm009
Artigas-Pallarés, J. (2009). Dislexia: enfermedad, trastorno o algo distinto. Rev Neurol, 48(Supl 2), S63-S69. Recuperado de https://www.neurologia.com/articulo/2009007
Ashkenazi, S., Rosenberg-Lee, M., Tenison, C., & Menon, V. (2012). Weak task-related modulation and stimulus representations during arithmetic problem solving in children with developmental dyscalculia. Developmental Cognitive Neuroscience, 2(1), S1, S152–S166. https://doi.org/10.1016/j.dcn.2011.09.006
Bates, T., Luciano, M., Medland, S., Montgomery, G., Wright, M. & Martin, N. (2011). Genetic variance in a component of the language acquisition device: ROBO1 polymorphisms associated with phonological buffer deficits. Behav Genet, 41(1), 50—57. https://doi.org/10.1007/s10519-010-9402-9
Benítez-Burraco, A. (2007). Bases moleculares de la Dislexia. Rev Neurol, 45(8), 491-502. Recuperado de https://www.uma.es/media/files/BASES_MOLECULARES_DE_LA_DISLEXIA.pdf
Benítez-Burraco, A. (2008). FOXP2 y la biología molecular del lenguaje: nuevas evidencias. II. Aspectos moleculares e implicaciones para la ontogenia y la filogenia del lenguaje. Neurología, 46(6), 351-359. Recuperado de https://www.unioviedo.es/biolang/pdf/FOXP2nuevasevidenciasII.pdf
Benítez-Burraco, A. (2010). Neurobiología y neurogenética de la dislexia. Neurología, 25(9), 563-81. Recuperado de https://doi.org/10.1016/j.nrl.2009.12.010
Benítez-Burraco, A. (2012). Aspectos problemáticos del análisis genético de los trastornos específicos del lenguaje, FOXP2 como paradigma. Neurología, 27(4), 225-33. https://doi.org/10.1016/j.nrl.2011.04.008
Berteletti, I., Prado, J. & Booth, J. R. (2014). Children with mathematical learning disability fail in recruiting verbal and numerical brain regions when solving simple multiplication problems. Cortex, 57, 43–55. https://doi.org/10.1016/j.cortex.2014.04.001
Bugden, S., & Ansari, D. (2015). How can cognitive developmental neuroscience constrain our understanding of developmental dyscalculia? In S. Chinn (Ed.), International handbook of dyscalculia and mathematical learning difficulties (pp. 18–43). London: Routledge. https://doi.org/10.4324/9781315740713
Cantlon, J., Davis, S., Libertus, M., Kahane, J., Brannon, E. & Pelphrey, K. (2011). Intra-parietal white matter development predicts numerical performance in children. Learn individ Differ, 21(6), 672–680. https://doi.org/10.1016/j.lindif.2011.09.003
Carboni-Román, A., Del Río Grande, D., Capilla, A., Maestú, F. & Ortiz, T. (2006). Bases neurobiológicas de las dificultades de aprendizaje. Neurología, 42(S2), S171-175. Recuperado de https://www.uma.es/media/files/BASES_NEUROLOGICAS_DE_LAS_DA.pdf
Cuadrado, P., Ho, J. & Vernes, S. (2014). Shining a light on CNTNAP2: complex functions to complex disorders. European Journal of Human Genetics, 22, 171-1788. https://doi.org/10.1038/ejhg.2013.100
Currier, T., Etchegaray, M., Haight, J., Galaburda, A. & Rosen, G. (2011). The effects of embryonic knockdown of the candidate dislexia susceptibility gene homologue Dyx1c1 on the distribution of GABAergic neurons in the cerebral cortex. Neuroscience, 172(13), 535 – 46. Recuperado de https://doi.org/10.1016/j.neuroscience.2010.11.002
Cutini, S., Szűcs, D., Mead, N., Huss, M. & Goswami, U. (2016). Atypical right hemisphere response to slow temporal modulations in children with developmental dyslexia. Neuroimage, 143, 40–49. https://doi.org/10.1016/j.neuroimage.2016.08.012
De la Peña, C. (2012). La dislexia desde la neuropsicología infantil. Madrid: Sanz y Torres.
Dehaene, S. & Cohen, L. (1995). Towards an anatomical and functional model for number processing. Math Cogn 1, 83-120. Recuperado de http://www.unicog.org/publications/DehaeneCohen_TripleCodeModelNumberProcessing_MathCognition1995.pdf
Díaz, B., Hintz, F., Kiebel, S. & Von Kriegstein, K. (2012). Dysfunction of the auditory thalamus in developmental dyslexia. Proc Natl Acad Sci U S A, 109, 13841—6. https://doi.org/10.1073/pnas.1119828109
Etchepareborda, M., Mulas, F., Gandía, R., Abad-Mas, L., Moreno-Madrid, F. & Díaz-Lucero, A. (2006). Técnica de evaluación funcional de los trastornos del neurodesarrollo. Neurología, 42(S2), S71-81. Recuperado de https://www.ncbi.nlm.nih.gov/pubmed/16555221?dopt=Abstract
Gavin, R., Price, R., Wilkey, E., Yeoa, D. & Cutting, L. (2015) The relation between 1st grade grey matter volume and 2nd grade math competence. Neuroimage, 124(Part A), 232–237. https://doi.org/10.1016/j.neuroimage.2015.08.046
Gersten, R., Clarke, B. & Mazzocco, M. (2007). Historical and contemporary perspectives on mathematical learning disabilities. In Berch D.B. & Mazzocco M.M (Eds). Why Is Math So Hard for Some Children? The nature and origins of mathematics learning difficulties and disabilities (pp. 7-27). Baltimore: Brookes Publishing.
Jolles, D., Ashkenazi, S., Kochalka, J., Evans, T., Richardson, J., … Menon, V. (2016). Parietal hyper-connectivity, aberrant brain organization, and circuit-based biomarkers in children with mathematical disabilities. Developmental Science 19(4), 613–631. https://doi.org/10.1111/desc.12399
Kadosh, R. & Walsh, V.(2007). Dyscalculia. Current Biology, 17(22) 946 – 947. https://doi.org/10.1016/j.cub.2007.08.038
Kanzafarova, R., Kazantseva, A. & Khusnutdinova, E. (2015). Genetic and environmental aspects of mathematical disabilities. Genetika, 51(3), 223-230. https://doi.org/10.1134/S1022795415010032
Klein, E., Moeller, K. & Willmes, K. (2013). A neural disconnection hypothesis on impaired numerical processing. Frontiers in Human Neuroscience,. 7, 663. https://doi.org/10.3389/fnhum.2013.00663
Kraft, I., Schreiber, J., Cafiero, R., Metere, R., Schaadt, G., … Skeide, M.A. (2016). Predicting early signs of dyslexia at a preliterate age by combining behavioral assessment with structural MRI. Neuroimage, 143, 378-386. https://doi.org/10.1016/j.neuroimage.2016.09.004
Krueger, F., Landgraf, S., Van der Meer, E., Deshpande, G. & Hu. X. (2011). Effective connectivity of the multiplication network: a functional MRI and multivariate granger causality mapping study. Human Brain Mapping, 32(9), 1419–1431. https://doi.org/10.1002/hbm.21119
Kucian, K., Ashkenazi, S., Hänggi, J., Rotzer, S., Jäncke, L., Martin, E. & Von Aster, M. (2013). Developmental dyscalculia: a dysconnection syndrome? Brain Structure & Function, 219(5), 1721-1733. https://doi.org/10.1007/s00429-013-0597-4
Kucian, K., Loenneker, T., Dietrich, T., Dosch, M., Martin, E. & Von Aster, M. (2006). Impaired neural networks for approximate calculation in dyscalculic children: a functional MRI study. Behavioral and Brain Functions, 2(31), 1-17. https://doi.org/10.1186/1744-9081-2-31
Lagae, L. (2008). Learning Disabilities: Definitions, Epidemiology, Diagnosis and Intervention Strategies. Pediatr Clin N Am, 55(6), 1259-1268. https://10.1016/j.pcl.2008.08.001
Lebel, C., Shaywitz, B., Holahan, J., Shaywitz, S., Marchione, K. & Beaulieu, C. (2013). Diffusion tensor imaging correlates of reading ability in disfluent and non-impaired readers. Brain Lang, 125(2), 215-22. https://doi.org/10.1016/j.bandl.2012.10.009
Lehongre, K., Ramus, F., Villiermet, N., Schwartz, D., Giraud, A. (2011). Altered low-gamma sampling in auditory cortex accounts for the three main facets of dyslexia. Neuron, 72(6), 1080-90. https://doi.org/10.1016/j.neuron.2011.11.002
Ludwig, K., Saman, P., Alexander, M., Becker, J., Bruder, …. Czamara, D. (2013). A common variant in myosin-18B contributes to mathematical abilities in children with dyslexia and intraparietal sulcus variability in adults. Transl Psychiatry 3(e229), 11-8. https://doi.org/10.1038/tp.2012.148
Marino, C., Mascheretti, S., Riva, V., Cattaneo, F., Rigoletto, C., …. Molteni, M. (2011). Pleiotropic effects of DCDC2 and DYX1C1 genes on language and mathematics traits in nuclear families of developmental dyslexia. Behavioral Genet, 41(1), 67-76. https://doi.org/10.1007/s10519-010-9412-7
Millá, G. (2006). Atención temprana de las dificultades de aprendizaje. Rev Neurol, 42(Supl 2), 153-156. Recuperado de http://www.mdp.edu.ar/psicologia/psico/sec-academica/asignaturas/aprendizaje/Materiales_2014/TAAtencion_temprana_de_las_dificultades_aprendizaje.pdf
Morken, F., Helland, T., Hugdahl, K. & Specht, K. (2017). Reading in dyslexia across literacy development: A longitudinal study of effective connectivity. Neuroimage,144, 92–100. https://doi.org/10.1016/j.neuroimage.2016.09.060
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