Skip to main content

The Neural Plasticity of Giftedness

  • Chapter
International Handbook on Giftedness

Abstract

Based on known types of neural plasticity such as phantom limb, pediatric hemispherectomy, and synesthesia, this chapter proposes that giftedness is a type of neural plasticity not well understood. Three questions guide the exploration of this idea. First, how does state of mind contribute to the acquisition and demonstration of giftedness? Second, what is the contribution of stress to the acquisition or demonstration of expertise? Finally, what are the contributions of sensory, perceptual, and motivational mechanisms to superlative higher level cognition and resulting performance state(s)? A larger paradigm is required to integrate existing empirical and theoretical information to guide the exploration of the potential nature of individual differences, human performance, and creativity on an elaborate scale. This chapter will reconcile these topics and issues into a general theory of giftedness as another type of neural plasticity.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 669.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 849.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 849.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Andreasen, N. C., O’Leary, D. S., Cizadlo, T., Arndt, S., Rezai, K., & Ponto, L. (1996). Schizophrenia and cognitive dysmetria: A positron-emission tomography study of dysfunctional prefrontal-thalamic-cerebellar circuitry. Proceedings of the National Academy of Science, 93(18), 9985–9990.

    Google Scholar 

  • Amabile, T. (1996).Creativity in context. Boulder, CO: Westview Press.

    Google Scholar 

  • Amminger, G. P., Schlogelhofer, M., Lehner, T., Looser Ott, S., Friedrich, M. H., & Aschauer, M. (2000). Premorbid performance IQ deficit in schizophrenia. Acta Psychiatrica Scandinavica, 102, 414–422.

    Google Scholar 

  • Baddeley, A. D. (1986). Working memory. Oxford: Clarendon Press.

    Google Scholar 

  • Baron-Cohen, S. (2004). The cognitive neuroscience of autism. Journal of Neurology, Neurosurgery, and Psychiatry, 75(7):945–948.

    Google Scholar 

  • Barron, F., & Harrington, D.M. (1981). Creativity, intelligence, and personality. Annual Review of Psychology, 32, 439–476.

    Google Scholar 

  • Bartsch, K., & Wellman H. M. (1995). Children talk about the mind. London: Oxford University Press.

    Google Scholar 

  • Battaglia, D., Chieffo, D., Lettori, D., Perrino, F., Di Rocco, C., & Guzzetta, F. (2006). Cognitive assessment in epilepsy surgery of children. Child’s nervous system, 22(8), 744–759.

    Google Scholar 

  • Bechara, A., Damasio, H., Tranel, D., & Damasio, A.R. (2005). The Iowa gambling task and the somatic marker hypothesis: Some questions and answers. Trends in Cognitive Sciences, 9(4):159–164.

    Google Scholar 

  • Beilock, S. L., Bertenthal, B. I., McCoy, A. M., & Carr, T. H. (2004a). Haste does not always make waste: Expertise, direction of attention, and speed versus accuracy in performing sensorimotor skills. Psychonomic Bulletin & Review, 11(2), 373–379.

    Google Scholar 

  • Beilock, S. L., & Carr, T. H. (2005). When high-powered people fail: Working memory and ‘choking under pressure’ in math. Psychological Science, 16, 101–105.

    Google Scholar 

  • Beilock, S. L., Kulp, C. A., Holt, L. E., & Carr, T. H. (2004b). More on the fragility of performance: Choking under pressure in mathematical problem solving. Journal of Experimental Psychology: General, 133, 584–600.

    Google Scholar 

  • Beilock, S. L., Wierenga, S. A., & Carr, T. H. (2002). Expertise, attention, and memory in sensorimotor skill execution: Impact of novel task constraints on dual-task performance and episodic memory. The Quarterly Journal of Experimental Psychology. A, Human Experimental Psychology, 55(4), 1211–1240.

    Google Scholar 

  • Berquin, P. C., Giedd, J. N., Jacobsen, L. K., Hamburger, S. D., Krain, A. L., & Rapoport, J. L., et al. (1998). Cerebellum in attention-deficit hyperactivity disorder: A morphometric MRI study. Neurology, 50, 1087–1093

    Google Scholar 

  • Berry, J. W., & Irvine, S. H. (1986). Bricolage: Savages do it daily. In R. J. Sternberg & R. K. Wagner (Eds.), Practical Intelligence: Nature and origins of competence in the everyday world (pp. 271–306). Cambridge: Cambridge University Press.

    Google Scholar 

  • Black, I. (1997). Trophic interactions and brain plasticity. In M. Gazzaniga (Ed.), The cognitive neurosciences. Cambridge, MA: MIT Press.

    Google Scholar 

  • Blackwood, N., Ffytche, D., Simmons, A., Bentall, R., Murray, R., & Howard, R. (2004). The cerebellum and decision making under uncertainty. Cognitive Brain Research, 20, 46–53.

    Google Scholar 

  • Blair, C. (2006). How similar are fluid cognition and general intelligence? A developmental neuroscience perspective on fluid cognition as an aspect of human cognitive ability. Behavioral and Brain Sciences, 29, 109–160.

    Google Scholar 

  • Boatman, D., Vining, E. P., Freeman, J., & Carson, B. (2003). Auditory processing studied prospectively in two hemidecorticectomy patients. Journal of Child Neurology, 18(3), 228–232.

    Google Scholar 

  • Bor, D., & Owen, A. (2007). Cognitive training: Neural correlates of expert skills. Current Biology, 17(3): R95–97.

    Google Scholar 

  • Borsook, D., Becerra, L., Fishman, S., Edwards, A., Jennings, C.L., & Stojanovic, M. et al. (1998). Acute plasticity in the human somatosensory cortex following amputation. Neuroreport, 9(6), 1013–1017.

    Google Scholar 

  • Bransford, J., Brown, A. L.,& Cocking, R. L. (Eds.) (1999). How people learn: Brain, mind, experience, and school. Washington, D.C: National Academy Press

    Google Scholar 

  • Bruner, J. (1979). On knowing: Essays for the left hand. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Carlsson, I., Wendt, P. E., & Risberg, J. (2000). On the neurobiology of creativity. Differences in frontal activity between high and how creative subjects. Neuropsychologia, 38, 873–885.

    Google Scholar 

  • Castellanos, F. X., Lee, P. P., Sharp, W., Jeffries, N. O., Greenstein, D. K., & Clasen L. S., et al. (2002). Developmental trajectories of brain volume abnormalities in children and adolescents with attention-deficit/hyperactivity disorder. JAMA, 288, 1740–1748.

    Google Scholar 

  • Catheline-Antipoff, N., & Poinso, F. (1994). Gifted children and dysharmonious development. Archives of Pediatrics, 1(11), 1034–1039.

    Google Scholar 

  • Chen, R., Cohen, L. G., & Hallett, M. (2002). Nervous system reorganization following injury. Neuroscience, 111(4), 761–773.

    Google Scholar 

  • Colum, R., Jung, R. E., & Haier, R. J. (2006). Distributed brain sites for the g-factor of intelligence. NeuroImage, 31, 1359–1365.

    Google Scholar 

  • Courchesne, E., Redcay, E., Morgan, J. T., & Kennedy, D. P. (2005). Autism at the beginning: Microstructural and growth abnormalities underlying the cognitive and behavioral phenotype of autism. Development and Psychopathology, 17(3), 577–597.

    Google Scholar 

  • Craggs, J. G., Sanchez, J., Kibby, M. Y., Gilger, J. W., & Hynd, G. W. (2006). Brain morphology and neuropsychological profiles in a family displaying dyslexia and superior nonverbal intelligence. Cortex, 42(8), 1107–1118.

    Google Scholar 

  • Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. New York: Harper and Row.

    Google Scholar 

  • Cytowic, R. E. (2002). Synesthesia: A union of the senses (2nd ed). Cambridge, MA: MIT Press.

    Google Scholar 

  • Dabrowski, K. (1967). Personality-shaping through positive disintegration. Boston: Little Brown.

    Google Scholar 

  • Damasio, A. R. (1996). The somatic marker hypothesis and the possible functions of the prefrontal cortex. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 351(1346), 1413–1420.

    Google Scholar 

  • Davidson, R. J. (2002). Anxiety and affective style: Role of prefrontal cortex and amygdala. Biological Psychiatry, 51, 68–80.

    Google Scholar 

  • De Geus, E. J. C., & Boomsma, D. I. (2002). A genetic neuroscience approach to human cognition. European Psychology, 6(4), 241–253.

    Google Scholar 

  • Diamond, A., & Herzberg, C. (1996). Impaired sensitivity to visual contrast in children treated early and continually for phenylketonuria. Brain, 119, 523–538.

    Google Scholar 

  • Diamond, A., Prevor, M. B., Callendar, G., & Druin, D. P. (1997). Prefrontal cognitive deficits in children treated early and continuously for PKU. Monographs of the Society for Research in Child Development, 62(4), Serial No. 252.

    Google Scholar 

  • Dickens, W. T., & Flynn, J. R. (2001). Heritability estimates versus large environmental effect: The IQ paradox resolved. Psychological Review, 108, 346–369.

    Google Scholar 

  • Doctorow, E. L. (2006). Creationists: Selected essays: 1993–2006. Mississauga, ON: Random House

    Google Scholar 

  • Duncan, J. (2003). Intelligence tests predict brain response to demanding task events. Nature Neuroscience, 6(3), 207–208.

    Google Scholar 

  • Duncan, J., Burgess, P., & Emslie, H. (1995). Fluid intelligence after frontal lobe lesions. Neuropsychologia, 33, 261–268.

    Google Scholar 

  • Duncan, J., Emslie, H., Williams, P., Johnson, R., & Freer C. (1996). Intelligence and the frontal lobe: The organization of goal-directed behavior. Cognitive Psychology, 30(3), 257–303.

    Google Scholar 

  • Duncan, J., & Owen, A. M. (2000). Common regions of the human frontal lobe recruited by diverse cognitive demands. Trends in Neuroscience, 23(10), 475–483.

    Google Scholar 

  • Duncan, J., Seltz, R. J., Kolodny, J., Bor, D., Herzog, H., & Ahmed, A., et al. (2000). A neural basis for general intelligence. Science, 289(5478), 399–401.

    Google Scholar 

  • Dunn, B. D., Dalgleish, T., & Lawrence, A. D. (2006). The somatic marker hypothesis: A critical evaluation. Neuroscience and biobehavioral reviews, 30(2), 239–271.

    Google Scholar 

  • Durston, S., Tottenham, N. T., Thomas, K. M., Davidson, M. C., Eigsti, I. M., & Yang, Y., et al. (2003). Differential patterns of striatal activation in young children with and without ADHD. Biological Psychiatry, 53(10), 871–878.

    Google Scholar 

  • Eikhoff, S. B., Amunts, K., Mohlberg, H., & Zilles, K. (2006). Human parietal operculum. II. Cytoarchitectonic mapping of subdivisions. Cerebral Cortex. 16(2), 268–279.

    Google Scholar 

  • Eikhoff, S. B., Schleicher, A., Zilles, K., & Amunts, K. (2006). Human parietal operculum. I. Cytoarchitectonic mapping of subdivisions. Cerebral Cortex, 16(2), 254–267.

    Google Scholar 

  • Elliott, R., Frith, C. D., & Dolan, R. J. (1997). Differential neural response to positive and negative feedback in planning and guessing tasks. Neuropsychologia, 35, 1395–1404.

    Google Scholar 

  • Eysenck, H. J. (1986). Toward a new model of intelligence. Personality and individual differences, 7, 731–736.

    Google Scholar 

  • Feldman, D. H. (1999). The development of creativity. In R. Sternberg (Ed.), The handbook of creativity (pp. 169–186). New York: Cambridge University Press.

    Google Scholar 

  • Feldman, D. H., Czikszentmihalyi, M., & Gardner, H. (1994). Changing the world: A framework for the study of creativity. Westport, CT: Praeger.

    Google Scholar 

  • Fischer, S, Drosopoulos, S, Tsen, J, & Born, J. (2006). Implicit learning – explicit knowing: A role for sleep in memory system interaction. Journal of Cognitive Neuroscience, 18(3), 311–319.

    Google Scholar 

  • Flynn, J. R. (1984). The mean IQ of Americans: Massive gains 1932–1978. Psychological Bulletin, 95, 29–51.

    Google Scholar 

  • Flynn, J. R. (1987). Massive IQ gains in 14 nations: What IQ tests really measure. Psychological Bulletin, 101, 171–191.

    Google Scholar 

  • Frangou, S., Chitins, X., & Williams, S. C. R. (2004). Mapping IQ and gray matter density in healthy young people. NeuroImage, 23, 800–805.

    Google Scholar 

  • Garon, N., & Moore, C. (2004). Complex decision-making in early childhood. Brain and cognition, 55(1), 158–70.

    Google Scholar 

  • Geake, J. G., & Hansen P. (2005). Neural correlates of intelligence as revealed by fMRI of fluid analogies, NeuroImage, 26(2), 555–564.

    Google Scholar 

  • Geidd, J. N., Blumenthal, J., Jeffries, N. O., Castellanos, F. X., Liu, H., & Zijdenbos A., et al. (1999). Brain development during childhood and adolescence: A longitudinal MRI study. Nature Neuroscience, 2(10), 861–863.

    Google Scholar 

  • Giedd, J. N., Lenroot, R., Greenstein, D., Wallace, G. L., Ordaz, S., & Molloy E.A., et al. (2006). Puberty-related influences on brain development. Molecular and Cellular Endocrinology, 254–255:154–162.

    Google Scholar 

  • Gilger, J. W., & Kaplan, B. J. (2001). Atypical brain development: A conceptual framework for understanding developmental learning disabilities. Developmental Neuropsychology, 20(2), 465–481

    Google Scholar 

  • Goel, V., Buchel, C., Frith, C., & Dolan, R. J. (2000). Dissociation of mechanisms underlying syllogistic reasoning. Neuroimage, 12, 504–514.

    Google Scholar 

  • Goel, V., & Dolan, R. (2001). Functional neuroanatomy of three-term relational reasoning, Neuropsychologia, 39(9), 901–909.

    Google Scholar 

  • Goel, V, Dolan, R. J. (2003). Reciprocal neural response within lateral and ventral medial prefrontal cortex during hot and cold reasoning. NeuroImage, 20, 2314–2321.

    Google Scholar 

  • Goel, V., Dolan, R. J. (2004). Differential involvement of left prefrontal cortex in inductive and deductive reasoning. Cognition, 93, B109–B121.

    Google Scholar 

  • Goel, V., Gold, B., Kapur, S., & Houle, S. (1997). The seats of reason? An imaging study of deductive and inductive reasoning. Neuroreport, 8(5),1305–1310.

    Google Scholar 

  • Goel, V., Gold, B., Kapur, S., & Houle, S. (1998). Neuroanatomical correlates of human reasoning. Journal of Cognitive Neuroscience, 10, 293–302.

    Google Scholar 

  • Graber, J. A., & Petersen, A. C. (1991). Cognitive changes at adolescence: Biological perspectives in brain maturation and cognitive development. In K. R. Gibson & A. C. Petersen (Eds.) Brain maturation and cognitive development: Comparative and cross-cultural perspectives. New York: Aldine de Gruyter.

    Google Scholar 

  • Gray, J. R., Chabris, C. F., & Braver, T. S. (2003). Neural mechanisms of general fluid intelligence. Nature Neuroscience, 6(3), 316–322.

    Google Scholar 

  • Graybiel, A. M. (1998). The basal ganglia and chunking action repertoires. Neurobiology of Learning and Memory, 70(1– 2), 119–136.

    Google Scholar 

  • Gunnel, D., Harrison, G., Rasmussen, F., Fouskakis, D., & Tynelius, P. (2002). Associations between premorbid intellectual performance, early life exposures, and dearly onset schizophrenia. British Journal of Psychiatry, 181, 298–305.

    Google Scholar 

  • Haier, R. J., Jung, R. E., Yeo, R. A., Head, K., & Alkire, M.T. (2004). Structural brain variation and general intelligence. NeuroImage, 23, 425–433.

    Google Scholar 

  • Haier, R. J., Jung, R. E., Yeo, R. A., Head, K., & Alkire, M. T. (2005). The neuroanatomy of general intelligence: Sex matters. NeuroImage, 25(1), 320–327.

    Google Scholar 

  • Haier, R. J., White, N. S., & Alkire, M. T. (2003). Individual differences in general intelligence correlate with brain function during nonreasoning tasks. Intelligence, 31(5), 429–441.

    Google Scholar 

  • Heaton, P., & Wallace, G. L. (2004). Annotation: The savant syndrome. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 45(5), 899–911.

    Google Scholar 

  • Hobson, J. A., & Pace-Schott, E. F. (2002). The cognitive neuroscience of sleep: Neuronal systems, consciousness, and learning. Nature Reviews Neuroscience, 3, 679–693.

    Google Scholar 

  • Hubbard, E. M., & Ramachandran, V. S. (2005). Neurocognitive mechanisms of synesthesia. Neuron, 48(3), 509–520.

    Google Scholar 

  • Igawa, M., Atsumi, Y., Takahashi, K., Shiotsuka, S., Hirasawa, H., & Yamamoto R., et al. (2001). Activation of visual cortex in REM sleep measured by 24-channel NIRS imaging. Psychiatry and Clinical Neurosciences, 55(3), 187–188.

    Google Scholar 

  • Jamison K.R. (1995). Manic-depressive illness and creativity. Scientific American, 272(2), 62–67.

    Google Scholar 

  • Jamison, K. R., Gerner, R. H., Hammen, C., & Padesky, C. (1980). Clouds and silver linings: Positive experiences associated with primary affective disorders. The American Journal of Psychiatry, 137(2), 198–202.

    Google Scholar 

  • Johnston , M. V. (2004). Clinical disorders of brain plasticity. Brain & Development, 26(2), 73–80.

    Google Scholar 

  • Jung, R. E., & Haier, R. J. (2007). The Parieto-Frontal Integration Theory (P-FIT) of Intelligence: Converging neuroimaging evidence. Behavioral and Brain Sciences, 30(2), 135–154.

    Google Scholar 

  • Jung, R. E., Haier, R. J., Yeo, R. A., Rowland, L. M., Petropoulos, H., & Levine, A. S., et al. (2005). Sex differences in N-acetylaspartate correlates of general intelligence: An 1H-MRS study of normal human brain. Neuroimage, 26(3), 965–972.

    Google Scholar 

  • Kalbfleisch, M. L. (2004). The functional anatomy of talent. The Anatomical Record, Part B: The New Anatomist, 277(1), 21–36.

    Google Scholar 

  • Kalbfleisch, M. L., & Banasiak, M. (2007). ADHD. In J. A. Plucker & C. M. Callahan (Eds.), Critical Issues and Practices in Gifted Education. Waco, TX: Prufrock Press (pp. 15–30).

    Google Scholar 

  • Kalbfleisch, M. L., & Iguchi, C. (2007). Twice Exceptional Learners. In J. A. Plucker, & C. M. Callahan (Eds.), Critical issues and practices in gifted education. Waco, TX: Prufrock Press (pp. 685–696).

    Google Scholar 

  • Kalbfleisch, M. L., VanMeter, J. W., & Zeffiro, T. A.. (2006). The influences of task difficulty and response correctness on neural systems supporting fluid reasoning. Cognitive Neurodynamics, online first – DOI 10.1007/s11571-006-9007-4/ ISSN 1871-4080 (Print) 1871–4099 (Online).

    Google Scholar 

  • Kalbfleisch, M. L., Van Meter, J. W., & Zeffiro, T. A. (2007). The influences of task difficulty and response correctness on neural systems supporting fluid reasoning. Cognitive Neurodynamics, 1(1), 71–84.

    Google Scholar 

  • Karatekin, C., Lazareff, J.A., & Asarnow, R. F. (2000). Relevance of the cerebellar hemispheres for executive functions. Pediatric Neurology, 22(2), 106–112.

    Google Scholar 

  • Kaufman, F., Kalbfleisch, M. L., & Castellanos, F. X. (2000). Gifted and ADHD: What do we know? Monograph for Senior Scholars Series: National Research Center on the Gifted and Talented. Storrs, CT.

    Google Scholar 

  • Kilts, C. D., Schweitzer, J. B., Quinn, C. K., Gross, R. E., Faber, T. L., & Muhammad, F., et al. (2001). Neural activity related to drug craving in cocaine addiction. Archives of General Psychiatry, 58, 334–341.

    Google Scholar 

  • Kim, S., Ugurbil, P., & Strick, P. (1994). Activation of a cerebellar output nucleus during cognitive processing. Science, 265, 949–951.

    Google Scholar 

  • Koechlin, E., Basso, G., Pietrini, P., Panzer, S., & Grafman, J. (1999). The role of the anterior prefrontal cortex in human cognition. Nature, 399, 148–151.

    Google Scholar 

  • Koizumi, H. (2001). Trans-disciplinarity. Neuroendocrinology Letters, 22, 219–221.

    Google Scholar 

  • Kremen, W. S., Seidman, L. J., Faraone, S. V., & Tsuang, M. T. (2001). Intelligence quotient and neuropsychological profile in patients with schizophrenia and in normal volunteers. Biological Psychiatry, 50, 453–462.

    Google Scholar 

  • Landau, S. M., & D’Esposito, M. (2004). Implicit sequence learning in pianists and nonpianists: An fMRI study of motor expertise. Society for Neuroscience, abstract 774.11.

    Google Scholar 

  • Levi-Strauss, C. (1966). The savage mind. London: Weidenfield and Nicholson.

    Google Scholar 

  • Leiner, H. C., Leiner, A. L., & Dow, R. S. (1986). Does the cerebellum contribute to mental skills? Behavioral Neuroscience, 100, 443–454.

    Google Scholar 

  • Luo, Q., Perry, C., Peng, D., Jin, Z., Xu, D.,& Ding, G., et al. (2003). The neural substrate of analogical reasoning: An fMRI study. Brain Research. Cognitive Brain Research, 17, 527–534.

    Google Scholar 

  • Maia, T. V., & McClelland, J. L. (2004). A reexamination of the evidence for the somatic marker hypothesis: What participants really know in the Iowa gambling task. Proceedings of the National Academy of Science, 101(45), 16075–1680.

    Google Scholar 

  • Maki, A., Yamashita, Y., Ito, Y., Watanabe, E., Mayanagi, Y., & Koizumi, H. (1995). Spatial and temporal analysis of human motor activity using noninvasive NIR topography. Medical Physics, 22(12), 1997–2005.

    Google Scholar 

  • Martindale, C., Anderson, K., Moore, K., & West, A. N. (1996). Creativity, oversensitivity, and the rate of habituation. Personality and Individual Differences, 20, 423–427.

    Google Scholar 

  • McCandliss, B. D., Noble, K. G. (2003). The development of reading impairment: A cognitive neuroscience model. Mental Retardation and Developmental Disabilities Research Reviews, 9, 196–205.

    Google Scholar 

  • Middleton, F. A., & Strick, P. L. (1994). Anatomical evidence for cerebellar and basal ganglia involvement in higher cognitive function. Science, 266, 458–461.

    Google Scholar 

  • Middleton, F. A., & Strick, P. L. (2000). Basal ganglia and cerebellar loops: Motor and cognitive circuits. Brain Research Reviews, 31, 236–250.

    Google Scholar 

  • Molinari, M.., Filippini, V., & Leggio, M. G. (2002). Neuronal plasticity of interrelated cerebellar and cortical networks. Neuroscience, 111(4), 863–870.

    Google Scholar 

  • Moore, C. D., Cohen, M. X., & Ranganath, C. (2006). Neural mechanisms of expert skills in visual working memory. The Journal of Neuroscience, 26(43), 11187–11196.

    Google Scholar 

  • Mottron, L., Dawson, M., Soulieres, I., Hubert, B., & Burack, J. (2006). Enhanced perceptual functioning in autism: An update, and eight principles of autistic perception. Journal of Autism and Developmental Disorders, 36(1), 27–43.

    Google Scholar 

  • Naglieri, J. (1997). The naglieri nonverbal ability test. San Antonio, TX: Psychological Corporation.

    Google Scholar 

  • Niogi, S. N., & McCandliss, B. D. (2006). Left lateralized white matter microstructure accounts for individual differences in reading ability and disability. Neuropsychologia, 44, 2178–2188.

    Google Scholar 

  • Norman, D. A., & Shallice, T. (1980). Attention to action: Willed and automatic control of behaviour. Reprinted in M. Gazzaniga (Ed.) (2000) Cognitive neuroscience: A reader. Oxford: Blackwell.

    Google Scholar 

  • O’Boyle, M. W., Benbow, C. P., & Alexander, J .E. (1995). Sex differences, hemispheric laterality, and associated brain activity in the intellectually gifted. Developmental Neuropsychology, 11(4), 415–443.

    Google Scholar 

  • O’Boyle, M. W., Cunnington, R., Silk, T. J., Vaughan, D., Jackson, G., & Syngeniotis, A., et al. (2005). .Mathematically gifted male adolescents activate a unique brain network during mental rotation. Brain Research. Cognitive Brain Research, 25(2), 583–587.

    Google Scholar 

  • Osherson, D., Perani, D., Cappa, S., Schnur, T., Grassi, F., & Fazio, F. (1998). Distinct brain loci in deductive versus probabilistic reasoning. Neuropsychologia, 36, 369–376.

    Google Scholar 

  • Overman, W. H. (2004). Sex differences in early childhood, adolescence, and adulthood on cognitive tasks that rely on orbital prefrontal cortex. Brain and Cognition, 55, 134–147.

    Google Scholar 

  • Palmeri, T. J., Wong, A. C.-N., & Gauthier, I. (2004). Computational approaches to the development of perceptual expertise. Trends in Cognitive Sciences, 8(8), 378–386.

    Google Scholar 

  • Paulus, M. P., Hozack, N., Frank, L., & Brown, G. G. (2002). Error rate and outcome predictability affect neural activation in prefrontal cortex and anterior cingulate during decision-making. Neuroimage, 15(4), 836–846.

    Google Scholar 

  • Peigneux, P., Laureys, S., Fuchs, S., Destrebecqz, A., Collette, F., & Delbeuck X. et al. (2003). Learned material content and acquisition level modulate cerebral reactivation during posttraining rapid-eye-movements sleep. Neuroimage, 20(1), 125–134.

    Google Scholar 

  • Pennartz, C., Groenewegen, H., & DaSilva, F. (1994). The nucleus accumbens as a complex of functionally distinct neuronal ensembles: An integration of behavioral, eletrophysiological, and anatomical data. Progress in Neurobiology, 42, 719–761.

    Google Scholar 

  • Piechowski, M. M. (1979). Developmental potential. In N. Colangelo & R. T. Zaffrann (Eds.), New voices in counseling the gifted. Dubuque, IW: Kendall Hunt.

    Google Scholar 

  • Posner, M. I., & Snyder, C. R. R. (1975). Attention and cognitive control. In R. Solso (Ed.), Information processing and cognition: The Loyola Symposium. Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Posthuma, D., de Geus, E. J. C., & Boomsma, D. I. (2001). Perceptual speed and IQ are associated through common genetic factors. Behavior Genetics,31(6), 593–602.

    Google Scholar 

  • Posthuma, D., Mulder, E., Boomsma, D. I., & deGeus, E. J. C. (2002). Genetic analysis of IQ, processing speed and stimulus-response incongruency effects. Biological Psychology, 61, 157–182.

    Google Scholar 

  • Prabhakaran, V., Rypma, B., & Gabrieli, J. D. (2001). Neural substrates of mathematical reasoning: A functional magnetic resonance imaging study of neocortical activation during performance of the necessary arithmetic operations test. Neuropsychology, 15(1), 115–127.

    Google Scholar 

  • Pugh, K., Mencl, W., Jenner, A., Katz, L., Frost, S., & Lee J., et al. (2001). Neurobiological studies of reading and reading disability. Journal of Communication Disorders, 34, 479–492.

    Google Scholar 

  • Pulsifer, M. B., Brandt, J., Salorio, C. F., Vining, E. P., Carson, B. S., & Freeman J. M. (2004). The cognitive outcome of hemispherectomy in 71 children. Epilepsia, 45(3), 243–254.

    Google Scholar 

  • Ramachandran, V. S. (2005). Plasticity and functional recovery in neurology. Clinical Medicine, 5(4), 368–373.

    Google Scholar 

  • Ramachandran, V. S., & Hubbard, E. M. (2001). Psychophysical investigations into the neural basis of synaesthesia. Proceedings of the Royal Society of London. Series B Biological Science, 268(1470), 979–983.

    Google Scholar 

  • Ramachandran, V. S., & Rogers-Ramachandran, D. (1996). Synaesthesia in phantom limbs induced with mirrors. Proceedings Biological Sciences, 263(1369), 377–386.

    Google Scholar 

  • Ramachandran, V. S., Rogers-Ramachandran, D., & Stewart, M. (1991). Perceptual correlates of massive cortical reorganization. Science, 252(5014), 1857–1860.

    Google Scholar 

  • Rao, S. M., Bobholz, J. A., Hammeke, T. A., Rosen, A. C., Woodley, S. J., & Cunningham, J. M., et al. (1997). Functional MRI evidence for subcortical participation in conceptual reasoning skills. Neuroreport, 8(8), 1987–1993.

    Google Scholar 

  • Rapoport, M., Van Reekum, R., & Mayberg, H. (2000). The role of the cerebellum in cognition and behavior: A selective review. The Journal of Neuropsychiatry and Clinical Neurosciences, 12(2), 193–198.

    Google Scholar 

  • Ravizza, S. M., & Ivry R. B. (2001). Comparison of the basal ganglia and cerebellum in shifting attention. Journal of Cognitive Neuroscience, 13(3), 285–297.

    Google Scholar 

  • Rich, A. N., Bradshaw, J. L., & Mattingley, J. B. (2005). A systematic, large scale study of synaesthesia: Implications for the role of early experience in lexical-colour associations. Cognition, 98(1), 53–84.

    Google Scholar 

  • Rogers, R., Ramnani, N., Mackay, C., Wilson, J., Jezzard, P, & Carter, C., et al. (2004). Distinct portions of the anterior cingulate cortex and medial prefrontal cortex are activated by reward processing in separable phases of decision-making cognition. Biological Psychiatry, 5(6), 594–602.

    Google Scholar 

  • Rogers, R. D., Everitt, B. J., Baldacchino, A., Blackshaw, A. J., Swainson, R., & Wynne, et al. (1999). Dissociable deficits in the decision-making cognition of chronic amphetamine abusers, opiate abusers, patients with focal damage to prefrontal cortex, and tryptophan-depleted normal volunteers: Evidence for monoaminergic mechanisms. Neuropsychopharmacology, 20(4), 322–339.

    Google Scholar 

  • Rubia, K., Overmeyer, S., Taylor, E., Brammer, M., Williams, S. C., & Simmons A., et al. (1999). Hypofrontality in attention deficit hyperactivity disorder during higher-order motor control: A study with functional MRI. The American Journal of Psychiatry, 156(6), 891–896.

    Google Scholar 

  • Ruff, C. C., Knauff, M., Fangmeier, T., & Spreer, J. (2003). Reasoning and working memory: Common and distinct neuronal processes. Neuropsychologia, 41, 1241–1253.

    Google Scholar 

  • Sakai, K., & Passingham, R. E. (2006). Prefrontal set activity predicts rule-specific neural processing during subsequent cognitive performance. Journal of Neuroscience, 26 (4), 1211–1218.

    Google Scholar 

  • Sato, H., Kiguchi, M., Maki, A., Fuchino, Y., Obata, A., & Yoro, T., et al. (2006). Within-subject reproducibility of near-infrared spectroscopy signals in sensorimotor activation after 6 months. Journal of Biomedical Optics, 11(1), 14–21.

    Google Scholar 

  • Saxe, R., Carey, S., & Kanwisher, N. (2004). Understanding other minds: Linking developmental psychology and functional neuroimaging. Annual Review of Psychology, 55, 87–124.

    Google Scholar 

  • Schmahmann, J.D., & Pandya, D. N. (1995). Prefrontal cortex projections to the basilar pons in rhesus monkey: Implications for the cerebellar contribution to higher function. Neuroscience Letters, 199, 175–178.

    Google Scholar 

  • Schmithorst, V. J., & Holland, S. K. (2006). Functional MRI evidence for disparate developmental processes underlying intelligence in boys and girls. Neuroimage, 31(3), 1366–1379.

    Google Scholar 

  • Schmithorst, V. J., & Holland, S. K. (2007). Sex differences in the development of neuroanatomical functional connectivity underlying intelligence found using Bayesian connectivity analysis. Neuroimage, 35(1), 406–419 (January 11 – E-pub ahead of print).

    Google Scholar 

  • Schmithorst, V. J., Wilke, M., Dardzinski, B.J., & Holland, S. K. (2005). Cognitive functions correlate with white matter architecture in a normal pediatric population: A diffusion tensor MRI study. Human Brain Mapping, 26(2), 139–147.

    Google Scholar 

  • Shaw, P., Greenstein, D., Lerch, J., Clasen, L., Lenroot, R., & Gogtay, N., et al. (2006). Intellectual ability and cortical development in children and adolescents. Nature, 440(7084), 676–679.

    Google Scholar 

  • Shaywitz, B., Shaywitz, S., Pugh, K., Mencl, W., Fulbright, K., & Skudlarski, P., et al. (2002). Disruption of posterior brain systems for reading in children with developmental dyslexia. Biological Psychiatry 52, 101–110.

    Google Scholar 

  • Shulman, R. G, Rothman, D. L., Behar, K. L., & Hyder, F. (2004). Energetic basis of brain activity: Implications for neuroimaging. Trends in Neurosciences, 27(8), 489–495.

    Google Scholar 

  • Silk, T., Vance, A., Rinehart, N., Egan, G., O’Boyle, M., & Bradshaw, J. L., et al. (2005). Fronto-parietal activation in attention-deficit hyperactivity disorder, combined type: Functional magnetic resonance imaging study. British Journal Psychiatry, 187, 282–283.

    Google Scholar 

  • Silk, T. J., Rinehart, N., Bradshaw, J. L., Tonge, B., Egan, G., & O’Boyle, M. W., et al. (2006). Visuospatial processing and the function of prefrontal-parietal networks in autism spectrum disorders: A functional MRI study. The American Journal of Psychiatry, 163(8), 1440–1443.

    Google Scholar 

  • Singer, J. (1995). Mental processes and brain architecture: Confronting the complex adaptive systems of human thought (an overview). In H. Morowitz & J. Singer (Eds.), The mind, the brain, and CAS. Addison-Wesley, New York.

    Google Scholar 

  • Smilek, D., Dixon, M. J., Cudahy, C., & Merikle, P. M. (2002). Synesthetic color experiences influence memory. Psychological Science, 13(6), 548–555.

    Google Scholar 

  • Sowell, E. R., Thompson, P. M., Tessner, K. D., & Toga, A. W. (2001). Mapping continued brain growth and gray matter density reduction in dorsal frontal cortex: Inverse relationships during postadolescent brain maturation. The Journal of Neuroscience, 21(22), 8819–8829.

    Google Scholar 

  • Sowell, E. R., Thompson, P. M., Welcome, S. E., Henkenius, A. L., Toga, A. W., & Peterson, B. S. (2003). Cortical abnormalities in children and adolescents with attention-deficit hyperactivity disorder. Lancet, 362(9397), 1699–1707.

    Google Scholar 

  • Sowell, E. R., Thompson, P. N., Holmes, C. J., Jernigan, T. L., & Toga, A.W. (1999). In vivo evidence for post-adolescent brain maturation in frontal and striatal regions. Nature Neurosciense, 2(10), 859–861.

    Google Scholar 

  • Suzki, A., Hirota, A., Takasawa, N., & Shigemasu, K. (2003). Application of the somatic marker hypothesis to individual differences in decision making. Biological Psychiatry, 65, 81–88.

    Google Scholar 

  • Taga, G., Asakawa, K., Maki, A., Konishi, Y., & Koizumi, H. (2003). Brain imaging in awake infants by near-infrared optical topography. Proceedings of the National Academy of Science, 100(19), 10722–10727.

    Google Scholar 

  • Talwar, V., & Lee, K. (2002a). Emergence of white-lie telling in children between 3 and 7 years of age. Merrill-Palmer Quarterly, 48, 160–181.

    Google Scholar 

  • Talwar, V., & Lee, K. (2002b). Development of lying to conceal a transgression: Children’s control of expressive behavior during verbal deception. International Journal of Behavioral Development, 26, 436–444.

    Google Scholar 

  • Tannenbaum, A. J., & Baldwin, L. J. (1983). Giftedness and learning disability: A paradoxical combination. In L. H. Fox, L. Brody, & D. Tobin (Eds.), Learning-disabled gifted children: Identification and programming (pp. 11–36). Baltimore: University Park Press.

    Google Scholar 

  • Tervaniemi, M., Rytkonen, M., Schroger, E., Ilminiemi, R.J., & Naatanen, R. (2001). Superior formation of cortical memory traces for melodic patterns in musicians. Learning and Memory, 8, 295–300.

    Google Scholar 

  • Thompson, P., Cannon, T.D., & Toga, A.W. (2002). Mapping genetic influences on human brain structure: A review. Annals Medicine, 34(7–8), 523–536.

    Google Scholar 

  • Thompson, P. M., Giedd, J. N., Woods, R. P., MacDonald, D., Evans, A.C., & Toga, A.W. (2000). Growth patterns in the developing brain detected by using continuum mechanical tensor maps. Nature, 404(6774), 190–193.

    Google Scholar 

  • Torrance, E. P. (1966). The Torrance Test of Creative Thinking (TTCT). Lexington, MA: Personnel Press, Ginn and Company.

    Google Scholar 

  • Vaidya, C. J., Bunge, S. A., Dudukovic, N. M., Zalecki, C. A., Elliott, G.R., & Gabrieli, J. D. (2005). Altered neural substrates of cognitive control in childhood ADHD: Evidence from functional magnetic resonance imaging. The American Journal of Psychiatry, 162(9), 1605–1613.

    Google Scholar 

  • van den Heuvel, O. A., Groenewegen, H. J., Barkhof, F., Lazeron, R.H., van Dyck, R., & Veltman, D. J. (2003). Frontostriatal system in planning complexity: A parametric functional magnetic resonance version of Tower of London task. NeuroImage, 18, 367–374.

    Google Scholar 

  • Vernon, P. A. (1987). Speed of information processing and intelligence. Norwood, NJ: Ablex.

    Google Scholar 

  • Wagner, R. K. (2000). Practical intelligence. In R. J. Sternberg (Ed.), Handbook of intelligence (pp. 380–395). Cambridge: Cambridge University Press.

    Google Scholar 

  • Waldrop, M. M. (1992). Complexity. New York: Simon and Schuster.

    Google Scholar 

  • Waltz, J. A., Knowlton, B. J., Holyoak, K. J., Boone, K. B., Mishkin, F.S., & Santos, M., et al. (1999). A system for relational reasoning in the human prefrontal cortex. Psychological Science, 10, 119–125.

    Google Scholar 

  • Werth, R. (2006). Visual functions without the occipital lobe or after cerebral hemispherectomy in infancy. European Journal of Neuroscience. 24(10), 2932–2944.

    Google Scholar 

  • Wharton, C. M., Grafman, J., Flitman, S. S., Hansen, E. K., Brauner, J., & Marks, A., et al. (2000). Toward neuroanatomical models of analogy: A positron emission tomography study of analogical mapping. Cognitive Psychology, 40, 173–197.

    Google Scholar 

  • White, N. M. (1997). Mnemonic functions of the basal ganglia. Current Opinion in Neurobiology, 7, 164–169.

    Google Scholar 

  • Whitmore, J., & Maker, C. J. (1985). Intellectual giftedness in disabled persons. Austin, TX: PRO-ED.

    Google Scholar 

  • Whitmore, J. R. (1980). Giftedness, conflict, and underachievement. Boston: Allyn & Bacon.

    Google Scholar 

  • Wilson, A. E., Smith, M. D., & Ross, H. S. (2003). The nature and effects of young children’s lies. Social Development, 12, 21–45.

    Google Scholar 

  • Wimmer, H., & Perner, J. (1983). Beliefs about beliefs: Representation and constraining function of wrong beliefs in young children’s understanding of deception. Cognition 13, 103–128.

    Google Scholar 

  • Winner, E. (2001). The origins and ends of giftedness. American Psychologist, 55(1), 159–169.

    Google Scholar 

  • Winner, E., von Karolyi, C., Malinsky, D., French, L., Seliger, C., & Ross, E., et al. (2001). Dyslexia and visual-spatial talents: Compensation vs deficit model. Brain Lang, 76(2), 81–110.

    Google Scholar 

  • Witelson, S. F., Kigar, D.L., & Harvey, T. (1999). The exceptional brain of Albert Einstein. The Lancet, 353, 2149–2153.

    Google Scholar 

  • Wright, I. C., Sham, P., Murray, R. M., Weinberger, D. R., & Bullmore, E. T. (2002). Genetic contributions to regional variability in human brain structure: Methods and preliminary results. NeuroImage, 17(1), 256–271.

    Google Scholar 

  • Yamashita, Y., Maki, A., & Koizumi, H. (2001). Wavelength dependence of the precision of noninvasive optical measurement of oxy-, deoxy-, and total-hemoglobin concentration. Medical Physics, 28(6), 1108–1114.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to M. Layne Kalbfleisch .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer Science+Business Media B.V.

About this chapter

Cite this chapter

Kalbfleisch, M.L. (2009). The Neural Plasticity of Giftedness. In: Shavinina, L.V. (eds) International Handbook on Giftedness. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6162-2_12

Download citation

Publish with us

Policies and ethics