From gifted to high potential and twice exceptional: A state-of-the-art meta-review

References

• Al-Dhamit, Y., & Kreishan, L. (2016). Gifted students’ intrinsic and extrinsic motivations and parental influence on their motivation: from the self-determination theory perspective. Journal of Research in Special Educational Needs, 16(1), 13–23. https://doi.org/10.1111/1471-3802.12048
   Web of Science ®Google Scholar
• Allen, E. A., Erhardt, E. B., Damaraju, E., Gruner, W., Segall, J. M., Silva, R. F., Havlicek, M., Rachakonda, S., Fries, J., Kalyanam, R., Michael, A. M., Caprihan, A., Turner, J. A., Eichele, T., Adelsheim, S., Bryan, A. D., Bustillo, J., Clark, V. P., Feldstein Ewing, S. W., … Calhoun, V. D. (2011). A baseline for the multivariate comparison of resting-state networks. Frontiers in Systems Neuroscience, 5, 2. https://doi.org/10.3389/fnsys.2011.00002
   PubMedGoogle Scholar
• Alloway, T. P., Rajendran, G., & Archibald, L. M. D. (2009). Working memory in children with developmental disorders. Journal of Learning Disabilities, 42(4), 372–382. https://doi.org/10.1177/0022219409335214
   PubMed Web of Science ®Google Scholar
• Alnæs, D., Kaufmann, T., Doan, N. T., Córdova-Palomera, A., Wang, Y., Bettella, F., Moberget, T., Andreassen, O. A., & Westlye, L. T. (2018). association of heritable cognitive ability and psychopathology with white matter properties in children and adolescents. JAMA Psychiatry, 75(3), 287–295. https://doi.org/10.1001/jamapsychiatry.2017.4277
   PubMed Web of Science ®Google Scholar
• Amat, J. A., Bansal, R., Whiteman, R., Haggerty, R., Royal, J., & Peterson, B. S. (2008). Correlates of intellectual ability with morphology of the hippocampus and amygdala in healthy adults. Brain and Cognition, 66(2), 105–114. https://doi.org/10.1016/j.bandc.2007.05.009
   PubMed Web of Science ®Google Scholar
• American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed.). American Psychiatric Association. https://doi.org/10.1176/appi.books.9780890423349
   Google Scholar
• Annevirta, T., & Vauras, M. (2006). Developmental changes of metacognitive skill in elementary school children. The Journal of Experimental Education, 74(3), 195–226. https://doi.org/10.3200/JEXE.74.3.195-226
   Web of Science ®Google Scholar
• Araújo, S., & Faísca, L. (2019). A meta-analytic review of naming-speed deficits in developmental dyslexia. Scientific Studies of Reading, 23(5), 349–368. https://doi.org/10.1080/10888438.2019.1572758
   Web of Science ®Google Scholar
• Assouline, S. G., Foley Nicpon, M., & Whiteman, C. (2010). Cognitive and psychosocial characteristics of gifted students with written language disability. Gifted Child Quarterly, 54(2), 102–115. https://doi.org/10.1177/0016986209355974
   Web of Science ®Google Scholar
• Au, J., Sheehan, E., Tsai, N., Duncan, G. J., Buschkuehl, M., & Jaeggi, S. M. (2015). Improving fluid intelligence with training on working memory: A meta-analysis. Psychonomic Bulletin & Review, 22(2), 366–377. https://doi.org/10.3758/s13423-014-0699-x
   PubMed Web of Science ®Google Scholar
• Bajaj, S., Raikes, A., Smith, R., Dailey, N. S., Alkozei, A., Vanuk, J. R., & Killgore, W. D. S. (2018). The relationship between general intelligence and cortical structure in healthy individuals. Neuroscience, 388, 36–44. https://doi.org/10.1016/j.neuroscience.2018.07.008
   PubMed Web of Science ®Google Scholar
• Barbey, A. K. (2018). Network neuroscience theory of human intelligence. Trends in Cognitive Sciences, 22(1), 8–20. https://doi.org/10.1016/j.tics.2017.10.001
   PubMed Web of Science ®Google Scholar
• Barbey, A. K., Colom, R., & Grafman, J. (2013). Dorsolateral prefrontal contributions to human intelligence. Neuropsychologia, 51(7), 1361–1369. https://doi.org/10.1016/j.neuropsychologia.2012.05.017
   PubMed Web of Science ®Google Scholar
• Barbey, A. K., Colom, R., Solomon, J., Krueger, F., Forbes, C., & Grafman, J. (2012). An integrative architecture for general intelligence and executive function revealed by lesion mapping. Brain, 135(Pt 4), 1154–1164. https://doi.org/10.1093/brain/aws021
   PubMed Web of Science ®Google Scholar
• Barfurth, M. A., Ritchie, K. C., Irving, J. A., & Shore, B. M. (2009). A metacognitive portrait of gifted learners. In International handbook on giftedness (pp. 397–417). Springer.
   Google Scholar
• Baron-Cohen, S., Ring, H. A., Bullmore, E. T., Wheelwright, S., Ashwin, C., & Williams, S. C. R. (2000). The amygdala theory of autism. Neuroscience and Biobehavioral Reviews, 24(3), 355–364. https://doi.org/10.1016/s0149-7634(00)00011-7
   PubMed Web of Science ®Google Scholar
• Basten, U., Hilger, K., & Fiebach, C. J. (2015). Where smart brains are different: A quantitative meta-analysis of functional and structural brain imaging studies on intelligence. Intelligence, 51, 10–27. https://doi.org/10.1016/j.intell.2015.04.009
   Web of Science ®Google Scholar
• Bates, T., & Stough, C. (1997). Processing speed, attention, and intelligence: Effects of spatial attention on decision time in high and low IQ subjects. Personality and Individual Differences, 23(5), 861–868. https://doi.org/10.1016/s0191-8869(97)00089-5
   Web of Science ®Google Scholar
• Berkowitz, E., & Cicchelli, T. (2004). Metacognitive strategy use in reading of gifted high achieving and gifted underachieving middle school students in New York City. Education and Urban Society, 37(1), 37–57. https://doi.org/10.1177/0013124504268072
   Web of Science ®Google Scholar
• Berninger, V. W., & Abbott, R. D. (2013). Differences between children with dyslexia who are and are not gifted in verbal reasoning. The Gifted Child Quarterly, 57(4), 223–233. https://doi.org/10.1177/0016986213500342
   Web of Science ®Google Scholar
• Bildiren, A. (2018). Developmental characteristics of gifted children aged 0–6 years: Parental observations. Early Child Development and Care, 188(8), 997–1011. https://doi.org/10.1080/03004430.2017.1389919
   Web of Science ®Google Scholar
• Biotteau, M., Danna, J., Baudou, E., Puyjarinet, F., Velay, J.-L., Albaret, J.-M., & Chaix, Y. (2019). Developmental coordination disorder and dysgraphia: Signs and symptoms, diagnosis, and rehabilitation. Neuropsychiatric Disease and Treatment, 15(15), 1873–1885. volume https://doi.org/10.2147/ndt.s120514
   PubMedGoogle Scholar
• Blaas, S. (2014). The relationship between social-emotional difficulties and underachievement of gifted students. Australian Journal of Guidance and Counselling, 24(2), 243–255. https://doi.org/10.1017/jgc.2014.1
   Google Scholar
• Blankenship, T. L., Slough, M. A., Calkins, S. D., Deater‐Deckard, K., Kim‐Spoon, J., & Bell, M. A. (2019). Attention and executive functioning in infancy: Links to childhood executive function and reading achievement. Developmental Science, 22(6), e12824. https://doi.org/10.1111/desc.12824
   PubMed Web of Science ®Google Scholar
• Boschi, A., Planche, P., Hemimou, C., Demily, C., & Vaivre-Douret, L. (2016). From High Intellectual potential to asperger syndrome: Evidence for differences and a fundamental overlap – A systematic review. Frontiers in Psychology, 7, 1605. https://doi.org/10.3389/fpsyg.2016.01605
   PubMed Web of Science ®Google Scholar
• Brock, L. L., Rimm-Kaufman, S. E., Nathanson, L., & Grimm, K. J. (2009). The contributions of “hot” and “cool” executive function to children’s academic achievement, learning-related behaviors, and engagement in kindergarten. Early Childhood Research Quarterly, 24(3), 337–349. https://doi.org/10.1016/j.ecresq.2009.06.001
   Web of Science ®Google Scholar
• Budding, D., & Chidekel, D. (2012). ADHD and giftedness: A neurocognitive consideration of twice exceptionality. Applied Neuropsychology, 1(2), 145–151. https://doi.org/10.1080/21622965.2012.699423
   Google Scholar
• Carlson, J. S., & Jensen, C. M. (1982). Reaction time, movement time, and intelligence: A replication and extension. Intelligence, 6(3), 265–274. https://doi.org/10.1016/0160-2896(82)90003-4
   Web of Science ®Google Scholar
• Carman, C. A. (2013). Comparing apples and oranges: Fifteen years of definitions of giftedness in research. Journal of Advanced Academics, 24(1), 52–70. https://doi.org/10.1177/1932202X12472602
   Google Scholar
• Carroll, J. B. (1995). On methodology in the study of cognitive abilities. Multivariate Behavioral Research, 30(3), 429–452. https://doi.org/10.1207/s15327906mbr3003_6
   PubMed Web of Science ®Google Scholar
• Casini, L., Pech-Georgel, C., & Ziegler, J. C. (2018). It’s about time: Revisiting temporal processing deficits in dyslexia. Developmental Science, 21(2), e12530. https://doi.org/10.1111/desc.12530
   Web of Science ®Google Scholar
• Choi, Y. Y., Shamosh, N. A., Cho, S. H., DeYoung, C. G., Lee, M. J., Lee, J.-M., Kim, S. I., Cho, Z.-H., Kim, K., Gray, J. R., & Lee, K. H. (2008). Multiple bases of human intelligence revealed by cortical thickness and neural activation. The Journal of Neuroscience, 28(41), 10323–10329. https://doi.org/10.1523/jneurosci.3259-08.2008
   PubMed Web of Science ®Google Scholar
• Chuderski, A. (2015). High intelligence prevents the negative impact of anxiety on working memory. Cognition & Emotion, 29(7), 1197–1209. https://doi.org/10.1080/02699931.2014.969683
   PubMed Web of Science ®Google Scholar
• Colom, R., Haier, R. J., Head, K., Álvarez-Linera, J., Quiroga, M. Á., Shih, P. C., & Jung, R. E. (2009). Gray matter correlates of fluid, crystallized, and spatial intelligence: Testing the P-FIT model. Intelligence, 37(2), 124–135. https://doi.org/10.1016/j.intell.2008.07.007
   Web of Science ®Google Scholar
• Conway, A. R. A., & Kovacs, K. (2015). New and emerging models of human intelligence. Wiley Interdisciplinary Reviews, 6(5), 419–426. https://doi.org/10.1002/wcs.1356
   PubMedGoogle Scholar
• Dąbrowski, K. (1967). Personality-shaping Through Positive Disintegration. J. & A. Churchill.
   Google Scholar
• Dai, X., Müller, H. G., Wang, J. L., & Deoni, S. C. (2019). Age-dynamic networks and functional correlation for early white matter myelination. Brain Structure & Function, 224(2), 535–551. https://doi.org/10.1007/s00429-018-1785-z
   PubMed Web of Science ®Google Scholar
• Deary, I. J., Penke, L., & Johnson, W. (2010). The neuroscience of human intelligence differences. Nature Reviews. Neuroscience, 11(3), 201–211. https://doi.org/10.1038/nrn2793
   PubMed Web of Science ®Google Scholar
• Dempsey, J., Ahmed, K., Simon, A. R., Hayutin, L. G., Monteiro, S., & Dempsey, A. G. (2021). Adaptive behavior profiles of intellectually gifted children with autism spectrum disorder. Journal of Developmental and Behavioral Pediatrics, 42(5), 374–379. https://doi.org/10.1097/dbp.0000000000000907
   PubMed Web of Science ®Google Scholar
• Deoni, S. C. L., O'Muircheartaigh, J., Elison, J. T., Walker, L., Doernberg, E., Waskiewicz, N., Dirks, H., Piryatinsky, I., Dean, D. C., & Jumbe, N. L. (2016). White matter maturation profiles through early childhood predict general cognitive ability. Brain Structure & Function, 221(2), 1189–1203. https://doi.org/10.1007/s00429-014-0947-x
   PubMed Web of Science ®Google Scholar
• Diamond, A. (2013). Executive functions. Annual Review of Psychology, 64(1), 135–168. https://doi.org/10.1146/annurev-psych-113011-143750
   PubMed Web of Science ®Google Scholar
• Dinehart, L. H. (2015). Handwriting in early childhood education: Current research and future implications. Journal of Early Childhood Literacy, 15(1), 97–118. https://doi.org/10.1177/1468798414522825
   Web of Science ®Google Scholar
• Dunn, W. (1999). Sensory profile: User’s manual. Psychological Corp.
   Google Scholar
• Fields, R. D. (2015). A new mechanism of nervous system plasticity: Activity-dependent myelination. Nature Reviews. Neuroscience, 16(12), 756–767. https://doi.org/10.1038/nrn4023
   PubMed Web of Science ®Google Scholar
• Fiske, A., & Holmboe, K. (2019). Neural substrates of early executive function development. Developmental Review, 52, 42–62. https://doi.org/10.1016/j.dr.2019.100866
   PubMed Web of Science ®Google Scholar
• Foley-Nicpon, M., Allmon, A., Sieck, B., & Stinson, R. D. (2010). Empirical investigation of twice-exceptionality: Where have we been and where are we going? Gifted Child Quarterly, 55(1), 3–17. https://doi.org/10.1177/0016986210382575
   Web of Science ®Google Scholar
• Foley-Nicpon, M., Assouline, S. G., & Colangelo, N. (2013). Twice-exceptional learners. Gifted Child Quarterly, 57(3), 169–180. https://doi.org/10.1177/0016986213490021
   Web of Science ®Google Scholar
• Foley-Nicpon, M., Assouline, S. G., & Stinson, R. D. (2012). Cognitive and academic distinctions between gifted students with autism and asperger syndrome. Gifted Child Quarterly, 56(2), 77–89. https://doi.org/10.1177/0016986211433199
   Web of Science ®Google Scholar
• Frischkorn, G., & Schubert, A.-L. (2018). Cognitive models in intelligence research: Advantages and recommendations for their application. Journal of Intelligence, 6(3), 34. https://doi.org/10.3390/jintelligence6030034
   PubMedGoogle Scholar
• Fuelscher, I., Caeyenberghs, K., Enticott, P. G., Williams, J., Lum, J., & Hyde, C. (2018). Differential activation of brain areas in children with developmental coordination disorder during tasks of manual dexterity: An ALE meta-analysis. Neuroscience and Biobehavioral Reviews, 86, 77–84. https://doi.org/10.1016/j.neubiorev.2018.01.002
   PubMed Web of Science ®Google Scholar
• Gagné, F. (1985). Giftedness and talent: Reexamining a reexamination of the definitions. Gifted Child Quarterly, 29(3), 103–112. https://doi.org/10.1177/001698628502900302
   Web of Science ®Google Scholar
• Gagné, F. (1995). From giftedness to talent: A developmental model and its impact on the language of the field. Roeper Review, 18(2), 103–111. https://doi.org/10.1080/02783199509553709
   Google Scholar
• Gagné, F. (2004). Transforming gifts into talents: The DMGT as a developmental theory. High Ability Studies, 15(2), 119–147. https://doi.org/10.1080/1359813042000314682
   Web of Science ®Google Scholar
• Gagné, F. (2010). Motivation within the DMGT 2.0 framework. High Ability Studies, 21(2), 81–99. https://doi.org/10.1080/13598139.2010.525341
   Web of Science ®Google Scholar
• Gagné, F. (2013). The DMGT: Changes within, beneath, and beyond. Talent Development & Excellence, 5(1), 5–19.
   Google Scholar
• Galton, F. (1869). Hereditary genius. 2nd Ed., 1892.
   Google Scholar
• Gardner, H. (1983). Frames of mind. Basic Books.
   Google Scholar
• Gardner, H. (1993). Multiple intelligences: The theory in practice. Basic Books.
   Google Scholar
• Gere, D. R., Capps, S. C., Mitchell, D. W., & Grubbs, E. (2009). Sensory sensitivities of gifted children. The American Journal of Occupational Therapy, 63(3), 288–295. https://doi.org/10.5014/ajot.63.3.288
   PubMed Web of Science ®Google Scholar
• Gilar-Corbi, R., Veas, A., Miñano, P., & Castejón, J.-L. (2019). Differences in personal, familial, social, and school factors between underachieving and non-underachieving gifted secondary students. Frontiers in Psychology, 10, 2367. https://doi.org/10.3389/fpsyg.2019.02367
   PubMed Web of Science ®Google Scholar
• Giraud, A.-L., & Poeppel, D. (2012). Cortical oscillations and speech processing: Emerging computational principles and operations. Nature Neuroscience, 15(4), 511–517. https://doi.org/10.1038/nn.3063
   PubMed Web of Science ®Google Scholar
• Girn, M., Mills, C., & Christoff, K. (2019). Linking brain network reconfiguration and intelligence: Are we there yet? Trends in Neuroscience and Education, 15, 62–70. https://doi.org/10.1016/j.tine.2019.04.001
   PubMed Web of Science ®Google Scholar
• Gläscher, J., Rudrauf, D., Colom, R., Paul, L. K., Tranel, D., Damasio, H., & Adolphs, R. (2010). Distributed neural system for general intelligence revealed by lesion mapping. Proceedings of the National Academy of Sciences of the United States of America, 107(10), 4705–4709. https://doi.org/10.1073/pnas.0910397107
   PubMed Web of Science ®Google Scholar
• Gomez, R., Stavropoulos, V., Vance, A., & Griffiths, M. D. (2020). Gifted children with ADHD: How are they different from non-gifted children with ADHD? International Journal of Mental Health and Addiction, 18(6), 1467–1481. https://doi.org/10.1007/s11469-019-00125-x
   Web of Science ®Google Scholar
• Gori, S., Cecchini, P., Bigoni, A., Molteni, M., & Facoetti, A. (2014). Magnocellular-dorsal pathway and sub-lexical route in developmental dyslexia. Frontiers in Human Neuroscience, 8, 460. https://doi.org/10.3389/fnhum.2014.00460
   PubMed Web of Science ®Google Scholar
• Gori, S., & Facoetti, A. (2015). How the visual aspects can be crucial in reading acquisition? The intriguing case of crowding and developmental dyslexia. Journal of Vision, 15(1), 15.1.8–8. https://doi.org/10.1167/15.1.8
   PubMed Web of Science ®Google Scholar
• Gori, S., Seitz, A. R., Ronconi, L., Franceschini, S., & Facoetti, A. (2016). Multiple causal links between magnocellular–dorsal pathway deficit and developmental dyslexia. Cerebral Cortex, 26(11), 4356–4369. https://doi.org/10.1093/cercor/bhv206
   PubMed Web of Science ®Google Scholar
• Goriounova, N. A., & Mansvelder, H. D. (2019). Genes, cells and brain areas of intelligence. Frontiers in Human Neuroscience, 13(44), 44. https://doi.org/10.3389/fnhum.2019.00044
   PubMedGoogle Scholar
• Goswami, U. (2011). A temporal sampling framework for developmental dyslexia. Trends in Cognitive Sciences, 15(1), 3–10. https://doi.org/10.1016/j.tics.2010.10.001
   PubMed Web of Science ®Google Scholar
• Goswami, U. (2022). Language acquisition and speech rhythm patterns: An auditory neuroscience perspective. Royal Society Open Science, 9(7), 211855. https://doi.org/10.1098/rsos.211855
   PubMed Web of Science ®Google Scholar
• Guénolé, F., Louis, J., Creveuil, C., Montlahuc, C., Baleyte, J.-M., Fourneret, P., & Revol, O. (2013). Étude transversale de l’anxiété trait dans un groupe de 111 enfants intellectuellement surdoués. L'Encephale, 39(4), 278–283. https://doi.org/10.1016/j.encep.2013.02.001
   PubMedGoogle Scholar
• Guénolé, F., Speranza, M., Louis, J., Fourneret, P., Revol, O., & Baleyte, J.-M. (2015). Wechsler profiles in referred children with intellectual giftedness: Associations with trait-anxiety, emotional dysregulation, and heterogeneity of Piaget-like reasoning processes. European Journal of Paediatric Neurology, 19(4), 402–410. https://doi.org/10.1016/j.ejpn.2015.03.006
   PubMed Web of Science ®Google Scholar
• He, J. L., Fuelscher, I., Coxon, J., Barhoun, P., Parmar, D., Enticott, P. G., & Hyde, C. (2018). Impaired motor inhibition in developmental coordination disorder. Brain and Cognition, 127, 23–33. https://doi.org/10.1016/j.bandc.2018.09.002
   PubMed Web of Science ®Google Scholar
• Hearne, L. J., Mattingley, J. B., & Cocchi, L. (2016). Functional brain networks related to individual differences in human intelligence at rest. Scientific Reports, 6(1), 32328. https://doi.org/10.1038/srep32328
   PubMedGoogle Scholar
• Hernández Finch, M. E., Speirs Neumeister, K. L., Burney, V. H., & Cook, A. L. (2014). The relationship of cognitive and executive functioning with achievement in gifted kindergarten children. Gifted Child Quarterly, 58(3), 167–182. https://doi.org/10.1177/0016986214534889
   Web of Science ®Google Scholar
• Heuser, B. L., Wang, K., & Shahid, S. (2017). Global dimensions of gifted and talented education: The influence of national perceptions on policies and practices. Global Education Review, 4(1), 4–21.
   Google Scholar
• Hilger, K., Ekman, M., Fiebach, C. J., & Basten, U. (2017). Intelligence is associated with the modular structure of intrinsic brain networks. Scientific Reports, 7(1), 7. https://doi.org/10.1038/s41598-017-15795-7
   PubMedGoogle Scholar
• Hill, A. C., Laird, A. R., & Robinson, J. L. (2014). Gender differences in working memory networks: A BrainMap meta-analysis. Biological Psychology, 102, 18–29. https://doi.org/10.1016/j.biopsycho.2014.06.008
   PubMed Web of Science ®Google Scholar
• Jensen, A. R., & Munro, E. (1979). Reaction time, movement time, and intelligence. Intelligence, 3(2), 121–126. https://doi.org/10.1016/0160-2896(79)90010-2
   Google Scholar
• Jiang, R., Calhoun, V. D., Fan, L., Zuo, N., Jung, R., Qi, S., Lin, D., Li, J., Zhuo, C., Song, M., Fu, Z., Jiang, T., & Sui, J. (2020). Gender differences in connectome-based predictions of individualized intelligence quotient and sub-domain scores. Cerebral Cortex, 30(3), 888–900. https://doi.org/10.1093/cercor/bhz134
   PubMed Web of Science ®Google Scholar
• Johnson, J., Im-Bolter, N., & Pascual-Leone, J. (2003). Development of mental attention in gifted and mainstream children: The role of mental capacity, inhibition, and speed of processing. Child Development, 74(6), 1594–1614. https://doi.org/10.1046/j.1467-8624.2003.00626.x
   PubMed Web of Science ®Google Scholar
• Jung, R. E., & Haier, R. J. (2007). The Parieto-Frontal Integration Theory (P-FIT) of intelligence: Converging neuroimaging evidence. The Behavioral and Brain Sciences, 30(2), 135–154. https://doi.org/10.1017/s0140525x07001185
   PubMed Web of Science ®Google Scholar
• Karras, H. C., Morin, D. N., Gill, K., Izadi-Najafabadi, S., & Zwicker, J. G. (2019). Health-related quality of life of children with Developmental Coordination Disorder. Research in Developmental Disabilities, 84, 85–95. https://doi.org/10.1016/j.ridd.2018.05.012
   PubMed Web of Science ®Google Scholar
• Kaur, M., Srinivasan, S. M., & Bhat, A. N. (2018). Comparing motor performance, praxis, coordination, and interpersonal synchrony between children with and without Autism Spectrum Disorder (ASD). Research in Developmental Disabilities, 72, 79–95. https://doi.org/10.1016/j.ridd.2017.10.025
   PubMed Web of Science ®Google Scholar
• Kent, P. (2017). Fluid intelligence: A brief history. Applied Neuropsychology. Child, 6(3), 193–203. https://doi.org/10.1080/21622965.2017.1317480
   PubMed Web of Science ®Google Scholar
• Kirby, A., Sugden, D., & Purcell, C. (2014). Diagnosing developmental coordination disorders. Archives of Disease in Childhood, 99(3), 292–296. https://doi.org/10.1136/archdischild-2012-303569
   PubMed Web of Science ®Google Scholar
• Kocevar, G., Suprano, I., Stamile, C., Hannoun, S., Fourneret, P., Revol, O., Nusbaum, F., & Sappey-Marinier, D. (2019). Brain structural connectivity correlates with fluid intelligence in children: A DTI graph analysis. Intelligence, 72, 67–75. https://doi.org/10.1016/j.intell.2018.12.003
   Web of Science ®Google Scholar
• Kong, D. T. (2014). Mayer–Salovey–Caruso Emotional Intelligence Test (MSCEIT/MEIS) and overall, verbal, and nonverbal intelligence: Meta-analytic evidence and critical contingencies. Personality and Individual Differences, 66, 171–175. https://doi.org/10.1016/j.paid.2014.03.028
   Web of Science ®Google Scholar
• Kovacs, K., & Conway, A. R. A. (2019a). A unified cognitive/differential approach to human intelligence: Implications for IQ testing. Journal of Applied Research in Memory and Cognition, 8(3), 255–272. https://doi.org/10.1016/j.jarmac.2019.05.003
   Web of Science ®Google Scholar
• Kovacs, K., & Conway, A. R. A. (2019b). What is iq? Life beyond “general intelligence”. Current Directions in Psychological Science, 28(2), 189–194. https://doi.org/10.1177/0963721419827275
   Web of Science ®Google Scholar
• Kovacs, K., & Conway, A. R. A. (2020). Process overlap theory, executive functions, and the interpretation of cognitive test scores: Reply to commentaries. Journal of Applied Research in Memory and Cognition, 9(3), 419–424. https://doi.org/10.1016/j.jarmac.2020.04.005
   Web of Science ®Google Scholar
• Langer, N., Pedroni, A., Gianotti, L. R. R., Hänggi, J., Knoch, D., & Jäncke, L. (2012). Functional brain network efficiency predicts intelligence. Human Brain Mapping, 33(6), 1393–1406. https://doi.org/10.1002/hbm.21297
   PubMed Web of Science ®Google Scholar
• Leong, V., & Goswami, U. (2014). Impaired extraction of speech rhythm from temporal modulation patterns in speech in developmental dyslexia. Frontiers in Human Neuroscience, 8, 96. https://doi.org/10.3389/fnhum.2014.00096
   PubMed Web of Science ®Google Scholar
• Luders, E., Narr, K. L., Bilder, R. M., Thompson, P. M., Szeszko, P. R., Hamilton, L., & Toga, A. W. (2007). Positive correlations between corpus callosum thickness and intelligence. NeuroImage, 37(4), 1457–1464. https://doi.org/10.1016/j.neuroimage.2007.06.028
   PubMed Web of Science ®Google Scholar
• MacCann, C. (2010). Further examination of emotional intelligence as a standard intelligence: A latent variable analysis of fluid intelligence, crystallized intelligence, and emotional intelligence. Personality and Individual Differences, 49(5), 490–496. https://doi.org/10.1016/j.paid.2010.05.010
   Web of Science ®Google Scholar
• Mayer, J. D., Salovey, P., Caruso, D. R., & Sitarenios, G. (2003). Measuring emotional intelligence with the MSCEIT V2.0. Emotion, 3(1), 97–105. https://doi.org/10.1037/1528-3542.3.1.97
   PubMed Web of Science ®Google Scholar
• Mayes, S. D., & Calhoun, S. L. (2008). WISC-IV and WIAT-II profiles in children with high-functioning autism. Journal of Autism and Developmental Disorders, 38(3), 428–439. https://doi.org/10.1007/s10803-007-0410-4
   PubMed Web of Science ®Google Scholar
• McClelland, M. M., & Cameron, C. E. (2019). Developing together: The role of executive function and motor skills in children’s early academic lives. Early Childhood Research Quarterly, 46, 142–151. https://doi.org/10.1016/j.ecresq.2018.03.014
   Web of Science ®Google Scholar
• Melnick, M. D., Harrison, B. R., Park, S., Bennetto, L., & Tadin, D. (2013). A strong interactive link between sensory discriminations and intelligence. Current Biology, 23(11), 1013–1017. https://doi.org/10.1016/j.cub.2013.04.053
   PubMed Web of Science ®Google Scholar
• Minahim, D., & Rohde, L. A. (2015). Attention deficit hyperactivity disorder and intellectual giftedness: A study of symptom frequency and minor physical anomalies. Revista Brasileira de Psiquiatria, 37(4), 289–295. https://doi.org/10.1590/1516-4446-2014-1489
   PubMed Web of Science ®Google Scholar
• Mullet, D. R., & Rinn, A. N. (2015). Giftedness and ADHD: Identification, misdiagnosis, and dual diagnosis. Roeper Review, 37(4), 195–207. https://doi.org/10.1080/02783193.2015.1077910
   Web of Science ®Google Scholar
• Murphy, A., & Janeke, H. C. (2009). The Relationship between Thinking Styles and Emotional Intelligence: An exploratory study. South African Journal of Psychology, 39(3), 357–375. https://doi.org/10.1177/008124630903900310
   Web of Science ®Google Scholar
• Nagy, Z., Westerberg, H., & Klingberg, T. (2004). Maturation of White matter is associated with the development of cognitive functions during childhood. Journal of Cognitive Neuroscience, 16(7), 1227–1233. https://doi.org/10.1162/0898929041920441
   PubMed Web of Science ®Google Scholar
• Navas-Sánchez, F. J., Alemán-Gómez, Y., Sánchez-Gonzalez, J., Guzmán-De-Villoria, J. A., Franco, C., Robles, O., Arango, C., & Desco, M. (2014). White matter microstructure correlates of mathematical giftedness and intelligence quotient. Human Brain Mapping, 35(6), 2619–2631. https://doi.org/10.1002/hbm.22355
   PubMed Web of Science ®Google Scholar
• Nijs, S., Gallardo-Gallardo, E., Dries, N., & Sels, L. (2014). A multidisciplinary review into the definition, operationalization, and measurement of talent. Journal of World Business, 49(2), 180–191. https://doi.org/10.1016/j.jwb.2013.11.002
   Web of Science ®Google Scholar
• Norton, E. S., & Wolf, M. (2012). Rapid Automatized Naming (RAN) and reading fluency: Implications for understanding and treatment of reading disabilities. Annual Review of Psychology, 63(1), 427–452. https://doi.org/10.1146/annurev-psych-120710-100431
   PubMed Web of Science ®Google Scholar
• Nusbaum, F., Hannoun, S., Kocevar, G., Stamile, C., Fourneret, P., Revol, O., & Sappey-Marinier, D. (2017). Hemispheric differences in white matter microstructure between two profiles of children with high intelligence quotient vs. controls: A tract-based spatial statistics study. Frontiers in Neuroscience, 11, 173. https://doi.org/10.3389/fnins.2017.00173
   PubMed Web of Science ®Google Scholar
• Ogurlu, U. (2021). A meta-analytic review of emotional intelligence in gifted individuals: A multilevel analysis. Personality and Individual Differences, 171, 110503. https://doi.org/10.1016/j.paid.2020.110503
   Web of Science ®Google Scholar
• Oppong, E., Shore, B. M., & Muis, K. R. (2019). Clarifying the connections among giftedness, metacognition, self-regulation, and self-regulated learning: Implications for theory and practice. Gifted Child Quarterly, 63(2), 102–119. https://doi.org/10.1177/0016986218814008
   Web of Science ®Google Scholar
• Peñuelas-Calvo, I., Sareen, A., Porras-Segovia, A., Cegla-Schvatzman, F. B., & Fernandez-Berrocal, P. (2021). The association between reading the mind in the eyes test performance and intelligence quotient in children and adolescents with Asperger syndrome. Frontiers in Psychiatry, 12, 642799. https://doi.org/10.3389/fpsyt.2021.642799
   PubMed Web of Science ®Google Scholar
• Peyre, H., Ramus, F., Melchior, M., Forhan, A., Heude, B., & Gauvrit, N. (2016). Emotional, behavioral and social difficulties among high-IQ children during the preschool period: Results of the EDEN mother–child cohort. Personality and Individual Differences, 94, 366–371. https://doi.org/10.1016/j.paid.2016.02.014
   Web of Science ®Google Scholar
• Pezoulas, V. C., Zervakis, M., Michelogiannis, S., & Klados, M. A. (2017). Resting-state functional connectivity and network analysis of cerebellum with respect to IQ and gender. Frontiers in Human Neuroscience, 11, 189. https://doi.org/10.3389/fnhum.2017.00189
   PubMed Web of Science ®Google Scholar
• Pfeiffer, S. I. (2012). Current perspectives on the identification and assessment of gifted students. Journal of Psychoeducational Assessment, 30(1), 3–9. https://doi.org/10.1177/0734282911428192
   Web of Science ®Google Scholar
• Pfeiffer, S. I. (2015). Gifted students with a coexisting disability: The twice exceptional. Estudos de Psicologia (Campinas), 32(4), 717–727. https://doi.org/10.1590/0103-166X2015000400015
   Google Scholar
• Pfeiffer, S. I., & Blei, S. (2008). Gifted Identification Beyond the IQ Test: Rating scales and other assessment procedures (pp. 177–198). Springer EBooks. https://doi.org/10.1007/978-0-387-74401-8_10
   Google Scholar
• Poeppel, D. (2003). The analysis of speech in different temporal integration windows: Cerebral lateralization as “asymmetric sampling in time. Speech Communication, 41(1), 245–255. https://doi.org/10.1016/s0167-6393(02)00107-3
   Web of Science ®Google Scholar
• Prescott, J., Gavrilescu, M., Cunnington, R., O’Boyle, M. W., & Egan, G. F. (2010). Enhanced brain connectivity in math-gifted adolescents: An fMRI study using mental rotation. Cognitive Neuroscience, 1(4), 277–288. https://doi.org/10.1080/17588928.2010.506951
   PubMed Web of Science ®Google Scholar
• Ramus, F., Rosen, S., Dakin, S. C., Day, B. L., Castellote, J. M., White, S., & Frith, U. (2003). Theories of developmental dyslexia: Insights from a multiple case study of dyslexic adults. Brain, 126(Pt 4), 841–865. https://doi.org/10.1093/brain/awg076
   PubMed Web of Science ®Google Scholar
• Reis, S. M., & Renzulli, J. S. (2004). Current research on the social and emotional development of gifted and talented students: Good news and future possibilities. Psychology in the Schools, 41(1), 119–130. https://doi.org/10.1002/pits.10144
   Web of Science ®Google Scholar
• Renzulli, J. S. (1988). A decade of dialogue on the three‐ring conception of giftedness. Roeper Review, 11(1), 18–25. https://doi.org/10.1080/02783198809553154
   Google Scholar
• Renzulli, J. S. (2011). What makes giftedness?: Reexamining a definition. Phi Delta Kappan, 92(8), 81–88. https://doi.org/10.1177/003172171109200821
   Google Scholar
• Renzulli, J. S. (2012). Reexamining the role of gifted education and talent development for the 21st Century. Gifted Child Quarterly, 56(3), 150–159. https://doi.org/10.1177/0016986212444901
   Web of Science ®Google Scholar
• Rodríguez-Naveiras, E., Verche, E., Hernández-Lastiri, P., Montero, R., & Borges, Á. (2019). Differences in working memory between gifted or talented students and community samples: A meta-analysis. Psicothema, 31(3), 255–262. https://doi.org/10.7334/psicothema2019.18
   PubMed Web of Science ®Google Scholar
• Ronksley-Pavia, M. (2015). A model of twice-exceptionality. Journal for the Education of the Gifted, 38(3), 318–340. https://doi.org/10.1177/0162353215592499
   Google Scholar
• Rose, S. A., Feldman, J. F., Jankowski, J. J., & Van Rossem, R. (2012). Information processing from infancy to 11years: Continuities and prediction of IQ. Intelligence, 40(5), 445–457. https://doi.org/10.1016/j.intell.2012.05.007
   PubMed Web of Science ®Google Scholar
• Ryman, S. G., Yeo, R. A., Witkiewitz, K., Vakhtin, A. A., van den Heuvel, M., de Reus, M., Flores, R. A., Wertz, C. R., & Jung, R. E. (2016). Fronto-Parietal gray matter and white matter efficiency differentially predict intelligence in males and females. Human Brain Mapping, 37(11), 4006–4016. https://doi.org/10.1002/hbm.23291
   PubMed Web of Science ®Google Scholar
• Santarnecchi, E., Emmendorfer, A., Tadayon, S., Rossi, S., Rossi, A., & Pascual-Leone, A. (2017). Network connectivity correlates of variability in fluid intelligence performance. Intelligence, 65, 35–47. https://doi.org/10.1016/j.intell.2017.10.002
   Web of Science ®Google Scholar
• Sayal, K., Prasad, V., Daley, D., Ford, T., & Coghill, D. (2018). ADHD in children and young people: Prevalence, care pathways, and service provision. The Lancet. Psychiatry, 5(2), 175–186. https://doi.org/10.1016/s2215-0366(17)30167-0
   PubMed Web of Science ®Google Scholar
• Schultz, D. H., & Cole, M. W. (2016). Higher intelligence is associated with less task-related brain network reconfiguration. The Journal of Neuroscience, 36(33), 8551–8561. https://doi.org/10.1523/JNEUROSCI.0358-16.2016
   PubMed Web of Science ®Google Scholar
• Shaw, P., Greenstein, D., Lerch, J., Clasen, L., Lenroot, R., Gogtay, N., Evans, A., Rapoport, J., & Giedd, J. (2006). Intellectual ability and cortical development in children and adolescents. Nature, 440(7084), 676–679. https://doi.org/10.1038/nature04513
   PubMed Web of Science ®Google Scholar
• Silverman, L. K. (2018). Assessment of giftedness. In Handbook of giftedness in children: Psychoeducational theory, research, and best practices (pp. 183–207). Springer Cham.
   Google Scholar
• Snyder, K. E., Nietfeld, J. L., & Linnenbrink-Garcia, L. (2011). Giftedness and metacognition. Gifted Child Quarterly, 55(3), 181–193. https://doi.org/10.1177/0016986211412769
   Web of Science ®Google Scholar
• Solé-Casals, J., Serra-Grabulosa, J. M., Romero-Garcia, R., Vilaseca, G., Adan, A., Vilaró, N., Bargalló, N., & Bullmore, E. T. (2019). Structural brain network of gifted children has a more integrated and versatile topology. Brain Structure & Function, 224(7), 2373–2383. https://doi.org/10.1007/s00429-019-01914-9
   PubMed Web of Science ®Google Scholar
• Spearman, C. (1904). “General Intelligence,” objectively determined and measured. The American Journal of Psychology, 15(2), 201–293. https://doi.org/10.2307/1412107
   Google Scholar
• Spit, S., & Rispens, J. (2019). On the relation between procedural learning and syntactic proficiency in gifted children. Journal of Psycholinguistic Research, 48(2), 417–429. https://doi.org/10.1007/s10936-018-9611-6
   PubMed Web of Science ®Google Scholar
• Steiner, H. H., & Carr, M. (2003). Cognitive development in gifted children: Toward a more precise understanding of emerging differences in intelligence. Educational Psychology Review, 15(3), 215–246. https://doi.org/10.1023/A:1024636317011
   Web of Science ®Google Scholar
• Sternberg, R. J. (1985). Beyond IQ: A triarchic theory of human intelligence. Cambridge University Press.
   Google Scholar
• Sternberg, R. J. (2003). A broad view of intelligence: The Theory Of Successful Intelligence. Consulting Psychology Journal, 55(3), 139–154. https://doi.org/10.1037/1061-4087.55.3.139
   Google Scholar
• Sternberg, R. J. (2016). ACCEL: A new model for identifying the gifted. Roeper Review, 2016, 1256739. https://doi.org/10.1080/02783193.2016.1256739
   Google Scholar
• Stoeger, H., Stoeger, D. P., & Ziegler, A. (2018). International perspectives and trends in research on giftedness and talent development. In APA handbook of giftedness and talent (pp. 25–37). American Psychological Association.
   Google Scholar
• Suprano, I., Delon-Martin, C., Kocevar, G., Stamile, C., Hannoun, S., Achard, S., Badhwar, A., Fourneret, P., Revol, O., Nusbaum, F., & Sappey-Marinier, D. (2019). Corrigendum: Topological modification of brain networks organization in children with high intelligence quotient: A resting-state fMRI study. Frontiers in Human Neuroscience, 13, 450. https://doi.org/10.3389/fnhum.2019.00450
   PubMed Web of Science ®Google Scholar
• Surgent, O. J., Walczak, M., Zarzycki, O., Ausderau, K., & Travers, B. G. (2021). IQ and sensory symptom severity best predict motor ability in children with and without autism spectrum disorder. Journal of Autism and Developmental Disorders, 51(1), 243–254. https://doi.org/10.1007/s10803-020-04536-x
   PubMed Web of Science ®Google Scholar
• Szalkai, B., Varga, B., & Grolmusz, V. (2015). Graph theoretical analysis reveals: Women’s brains are better connected than men. PLoS One, 10(7), e0130045. https://doi.org/10.1371/journal.pone.0130045
   PubMed Web of Science ®Google Scholar
• Takeuchi, H., Taki, Y., Sassa, Y., Hashizume, H., Sekiguchi, A., Fukushima, A., & Kawashima, R. (2011). Working memory training using mental calculation impacts regional gray matter of the frontal and parietal regions. PloS One, 6(8), e23175. https://doi.org/10.1371/journal.pone.0023175
   PubMed Web of Science ®Google Scholar
• Tallal, P. (1980). Auditory temporal perception, phonics, and reading disabilities in children. Brain and Language, 9(2), 182–198. https://doi.org/10.1016/0093-934x(80)90139-x
   PubMed Web of Science ®Google Scholar
• Tanaka, H., Black, J. M., Hulme, C., Stanley, L. M., Kesler, S. R., Whitfield-Gabrieli, S., Reiss, A. L., Gabrieli, J. D. E., & Hoeft, F. (2011). The brain basis of the phonological deficit in dyslexia is independent of IQ. Psychological Science, 22(11), 1442–1451. https://doi.org/10.1177/0956797611419521
   PubMed Web of Science ®Google Scholar
• Terman, L. M. (1925). Mental and physical traits of a thousand gifted children. Stanford University Press, Printing.
   Google Scholar
• Terrassier, J. C. (1979). The asynchrony syndrome (author’s transl). Neuropsychiatrie de L’Enfance et de L’adolescence, 27(10–11), 445–450.
   PubMedGoogle Scholar
• Thurstone, L. L. (1931). The measurement of social attitudes. The Journal of Abnormal and Social Psychology, 26(3), 249–269. https://doi.org/10.1037/h0070363
   Google Scholar
• Thurstone, L. L. (1975). Primary mental abilities. University of Chicago Press.
   Google Scholar
• Tomasi, D., & Volkow, N. D. (2012). Aging and functional brain networks. Molecular Psychiatry, 17(5), 471, 549–558. https://doi.org/10.1038/mp.2011.81
   PubMed Web of Science ®Google Scholar
• Unsworth, N., Fukuda, K., Awh, E., & Vogel, E. K. (2014). Working memory and fluid intelligence: Capacity, attention control, and secondary memory retrieval. Cognitive Psychology, 71, 1–26. https://doi.org/10.1016/j.cogpsych.2014.01.003
   PubMed Web of Science ®Google Scholar
• Vaivre-Douret, L., Hamdioui, S., & Cannafarina, A. (2020). The influence of IQ levels on clinical features of developmental coordination disorder. Journal of Psychiatry and Psychiatric Disorder, 04(04), 107. https://doi.org/10.26502/jppd.2572-519X0107
   Google Scholar
• Vaivre-Douret, L. (2011). Developmental and cognitive characteristics of “high-level potentialities” (Highly Gifted) children. International Journal of Pediatrics, 2011, 420297–420214. https://doi.org/10.1155/2011/420297
   PubMedGoogle Scholar
• Van der Maas, H., Kan, K.-J., & Borsboom, D. (2014). Intelligence is what the intelligence test measures. Journal of Intelligence, 2(1), 12–15. https://doi.org/10.3390/jintelligence2010012
   Google Scholar
• Van Viersen, S., de Bree, E. H., Kalee, L., Kroesbergen, E. H., & de Jong, P. F. (2017). Foreign language reading and spelling in gifted students with dyslexia in secondary education. Reading and Writing, 30(6), 1173–1192. https://doi.org/10.1007/s11145-016-9717-x
   PubMed Web of Science ®Google Scholar
• Van Viersen, S., de Bree, E. H., Kroesbergen, E. H., Slot, E. M., & de Jong, P. F. (2015). Risk and protective factors in gifted children with dyslexia. Annals of Dyslexia, 65(3), 178–198. https://doi.org/10.1007/s11881-015-0106-y
   PubMed Web of Science ®Google Scholar
• Van Viersen, S., Kroesbergen, E. H., Slot, E. M., & de Bree, E. H. (2016). High reading skills mask dyslexia in gifted children. Journal of Learning Disabilities, 49(2), 189–199. https://doi.org/10.1177/0022219414538517
   PubMed Web of Science ®Google Scholar
• Wechsler, D. (1939). The nature of intelligence. In D. Wechsler (Ed.), The measurement of adult intelligence (pp. 3–12). Williams & Wilkins Co. https://doi.org/10.1037/10020-001
   Google Scholar
• Wu, M., Liang, X., Lu, S., & Wang, Z. (2017). Infant motor and cognitive abilities and subsequent executive function. Infant Behavior & Development, 49, 204–213. https://doi.org/10.1016/j.infbeh.2017.09.005
   PubMed Web of Science ®Google Scholar
• Zeidner, M., & Matthews, G. (2017). Emotional intelligence in gifted students. Gifted Education International, 33(2), 163–182. https://doi.org/10.1177/0261429417708879
   Google Scholar
• Zeidner, M., Matthews, G., Roberts, R. D., & MacCann, C. (2003). Development of emotional intelligence: Towards a multi-level investment model. Human Development, 46(2–3), 69–96. https://doi.org/10.1159/000068580
   Web of Science ®Google Scholar
• Zeidner, M., & Shani-Zinovich, I. (2011). Do academically gifted and nongifted students differ on the Big-Five and adaptive status? Some recent data and conclusions. Personality and Individual Differences, 51(5), 566–570. https://doi.org/10.1016/j.paid.2011.05.007
   Web of Science ®Google Scholar
• Zeidner, M., Shani-Zinovich, I., Shani-Zinovich, G., & Roberts, R. (2005). Assessing emotional intelligence in gifted and non-gifted high school students: Outcomes depend on the measure. Intelligence, 33(4), 369–391. https://doi.org/10.1016/j.intell.2005.03.001
   Web of Science ®Google Scholar
• Ziegler, A. (2009). Research on giftedness in the 21st Century. In International handbook on giftedness (pp. 1509–1524). Springer.
   Google Scholar
• Ziegler, A., & Raul, T. (2000). Myth and reality: A review of empirical studies on giftedness. High Ability Studies, 11(2), 113–136. https://doi.org/10.1080/13598130020001188
   Web of Science ®Google Scholar
• Zwicker, J. G., Missiuna, C., Harris, S. R., & Boyd, L. A. (2011). Brain activation associated with motor skill practice in children with developmental coordination disorder: An fMRI study. International Journal of Developmental Neuroscience, 29(2), 145–152. https://doi.org/10.1016/j.ijdevneu.2010.12.002
   PubMed Web of Science ®Google Scholar