Article contents
Neurodevelopment and executive function in autism
Published online by Cambridge University Press: 07 October 2008
Abstract
Autism is a neurodevelopmental disorder characterized by social and communication deficits, and repetitive behavior. Studies investigating the integrity of brain systems in autism suggest a wide range of gray and white matter abnormalities that are present early in life and change with development. These abnormalities predominantly affect association areas and undermine functional integration. Executive function, which has a protracted development into adolescence and reflects the integration of complex widely distributed brain function, is also affected in autism. Evidence from studies probing response inhibition and working memory indicate impairments in these core components of executive function, as well as compensatory mechanisms that permit normative function in autism. Studies also demonstrate age-related improvements in executive function from childhood to adolescence in autism, indicating the presence of plasticity and suggesting a prolonged window for effective treatment. Despite developmental gains, mature executive functioning is limited in autism, reflecting abnormalities in wide-spread brain networks that may lead to impaired processing of complex information across all domains.
- Type
- Research Article
- Information
- Development and Psychopathology , Volume 20 , Special Issue 4: Imaging Brain Systems in Normality and Psychopathology , Fall 2008 , pp. 1103 - 1132
- Copyright
- Copyright © Cambridge University Press 2008
References
Abell, F., Krams, M., Ashburner, J., Passingham, R., Friston, K., Frackowiak, R., et al. (1999). The neuroanatomy of autism: A voxel-based whole brain analysis of structural scans. NeuroReport, 10, 1647–1651.Google Scholar
Acosta, M. T., & Pearl, P. L. (2003). The neurobiology of autism: New pieces of the puzzle. Current Neurology and Neuroscience Reports, 3, 149–156.Google Scholar
Adleman, N. E., Menon, V., Blasey, C. M., White, C. D., Warsofsky, I. S., Glover, G. H., et al. (2002). A developmental fMRI study of the Stroop color-word task. NeuroImage, 16, 61–75.Google Scholar
Akshoomoff, N. A., & Courchesne, E. (1992). A new role for the cerebellum in cognitive operations. Behavioral Neuroscience, 106, 731–738.Google Scholar
Alexander, A. L., Lee, J. E., Lazar, M., Boudos, R., DuBray, M. B., Oakes, T. R., et al. (2007). Diffusion tensor imaging of the corpus callosum in Autism. NeuroImage, 34, 61–73.Google Scholar
Allen, G., & Courchesne, E. (2003). Differential effects of developmental cerebellar abnormality on cognitive and motor functions in the cerebellum: An fMRI study of autism. American Journal of Psychiatry, 160, 262–273.Google Scholar
Amaral, D. G., Schumann, C. M., & Nordahl, C. W. (2008). Neuroanatomy of autism. Trends in Neurosciences, 31, 137–145.Google Scholar
American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed., text revision). Washington, DC: Author.Google Scholar
Asato, M. R., & Hardan, A. Y. (2004). Neuropsychiatric problems in tuberous sclerosis complex. Journal of Child Neurology, 19, 241–249.Google Scholar
Asato, M. R., Sweeney, J. A., & Luna, B. (2006). Cognitive processes in the development of TOL performance. Neuropsychologia, 44, 2259–2269.Google Scholar
Ashtari, M., Cervellione, K. L., Hasan, K. M., Wu, J., McIlree, C., Kester, H., et al. (2007). White matter development during late adolescence in healthy males: A cross-sectional diffusion tensor imaging study. NeuroImage, 35, 501–510.Google Scholar
Aylward, E. H., Minshew, N. J., Field, K., Sparks, B. F., & Singh, N. (2002). Effects of age on brain volume and head circumference in autism. Neurology, 59, 175–183.Google Scholar
Aylward, E. H., Minshew, N. J., Goldstein, G., Honeycutt, N. A., Augustine, A. M., Yates, K. O., et al. (1999). MRI volumes of amygdala and hippocampus in non-mentally retarded autistic adolescents and adults. Neurology, 53, 2145–2150.Google Scholar
Bailey, A., Luthert, P., Dean, A., Harding, B., Janota, I., Montgomery, M., et al. (1998). A clinicopathological study of autism. Brain, 121, 889–905.Google Scholar
Barkley, R. A. (1997). Behavioral inhibition, sustained attention, and executive functions: Constructing a unifying theory of ADHD. Psychological Bulletin, 121, 65–94.Google Scholar
Barnea-Goraly, N., Kwon, H., Menon, V., Eliez, S., Lotspeich, L., & Reiss, A. L. (2004). White matter structure in autism: Preliminary evidence from diffusion tensor imaging. Biological Psychiatry, 55, 323–326.Google Scholar
Barnea-Goraly, N., Menon, V., Eckert, M., Tamm, L., Bammer, R., Karchemskiy, A., et al. (2005). White matter development during childhood and adolescence: A cross-sectional diffusion tensor imaging study. Cerebral Cortex, 15, 1848–1854.Google Scholar
Ben Bashat, D., Ben Sira, L., Graif, M., Pianka, P., Hendler, T., Cohen, Y., et al. (2005). Normal white matter development from infancy to adulthood: Comparing diffusion tensor and high b value diffusion weighted MR images. Journal of Magnetic Resonance Imaging, 21, 503–511.Google Scholar
Benes, F. M. (1989). Myelination of cortical-hippocampal relays during late adolescence. Schizophrenia Bulletin, 15, 585–593.Google Scholar
Benes, F. M., Turtle, M., Khan, Y., & Farol, P. (1994). Myelination of a key relay zone in the hippocampal formation occurs in the human brain during childhood, adolescence, and adulthood. Archives of General Psychiatry, 51, 477–484.Google Scholar
Bennetto, L., Pennington, B. F., & Rogers, S. J. (1996). Intact and impaired memory functions in autism. Child Development, 67, 1816–1835.Google Scholar
Bjorklund, D. F., & Harnishfeger, K. K. (1995). The evolution of inhibition mechanisms and their role in human cognition and behavior. In Dempster, F. N. & Brainerd, C. J. (Eds.), Interference & inhibition in cognition (pp. 141–173). San Diego, CA: Academic Press.Google Scholar
Booth, J. R., Burman, D. D., Meyer, J. R., Lei, Z., Trommer, B. L., Davenport, N. D., et al. (2003). Neural development of selective attention and response inhibition. NeuroImage, 20, 737–751.Google Scholar
Booth, J. R., Burman, D. D., Meyer, J. R., Lei, Z., Trommer, B. L., Davenport, N. D., et al. (2005). Larger deficits in brain networks for response inhibition than for visual selective attention in attention deficit hyperactivity disorder (ADHD). Journal of Child Psychology and Psychiatry and Allied Disciplines, 46, 94–111.Google Scholar
Brian, J. A., Tipper, S. P., Weaver, B., & Bryson, S. E. (2003). Inhibitory mechanisms in autism spectrum disorders: Typical selective inhibition of location versus facilitated perceptual processing. Journal of Child Psychology and Psychiatry, 44, 552–560.Google Scholar
Bunge, S. A., Dudukovic, N. M., Thomason, M. E., Vaidya, C. J., & Gabrieli, J. D. (2002). Immature frontal lobe contributions to cognitive control in children: Evidence from fMRI. Neuron, 33, 301–311.Google Scholar
Burman, D. D., & Bruce, C. J. (1997). Suppression of task-related saccades by electrical stimulation in the primate's frontal eye field. Journal of Neurophysiology, 77, 2252–2267.Google Scholar
Carlson, S., Martinkauppi, S., Raemae, P., Salli, E., Korvenoja, K., & Aronen, H. J. (1998). Distribution of cortical activation during visuospatial n-back tasks as revealed by functional magnetic resonance imaging. Cerebral Cortex, 8, 743–752.Google Scholar
Carper, R. A., & Courchesne, E. (2005). Localized enlargement of the frontal cortex in early autism. Biological Psychiatry, 57, 126–133.Google Scholar
Cascio, C. J., Gerig, G., & Piven, J. (2007). Diffusion tensor imaging: Application to the study of the developing brain. Journal of the American Academy of Child & Adolescent Psychiatry, 46, 213–223.Google Scholar
Case, R. (1992). The role of the frontal lobes in the regulation of cognitive development. Brain and Cognition, 20, 51–73.Google Scholar
Casey, B. J., Cohen, J. D., Jezzard, P., Turner, R., Noll, D. C., Trainor, R. J., et al. (1995). Activation of prefrontal cortex in children during a nonspatial working memory task with functional MRI. NeuroImage, 2, 221–229.Google Scholar
Casey, B. J., Cohen, J. D., O'Craven, K., Davidson, R. J., Irwin, W., Nelson, C., et al. (1998). Reproducibility of fMRI results across four institutions using a spatial working memory task. NeuroImage, 8, 249–261.Google Scholar
Casey, B. J., Trainor, R. J., Orendi, J. L., Schubert, A. B., ystrom, L. E., Giedd, J. N., et al. (1997). A developmental functional MRI study of prefrontal activation during performance of a go-no-go task. Journal of Cognitive Neuroscience, 9, 835–847.Google Scholar
Castellanos, F. X., Marvasti, F. F., Ducharme, J. L., Walter, J. M., Israel, M. E., Krain, A., et al. (2000). Executive function oculomotor tasks in girls with ADHD. Journal of the American Academy of Child & Adolescent Psychiatry, 39, 644–650.Google Scholar
Castelli, F., Frith, C., Happe, F., & Frith, U. (2002). Autism, Asperger syndrome and brain mechanisms for the attribution of mental states to animated shapes. Brain, 125, 1839–1849.Google Scholar
Caviness, V. S., Kennedy, D. N., Bates, J. F., & Makris, N. (1996). The developing human brain: A morphometric profile. In Thatcher, R. W., Reid Lyon, G., Rumsey, J., & Krasnegor, N. A. (Eds.), Developmental neuroimaging: Mapping the development of brain and behavior (pp. 3–14). New York: Academic Press.Google Scholar
Cherkassky, V. L., Kana, R. K., Keller, T. A., & Just, M. A. (2006). Functional connectivity in a baseline resting-state network in autism. NeuroReport, 17, 1687–1690.Google Scholar
Cicchetti, D. V., & Cannon, T. D. (1999). Neurodevelopmental processes in the ontogenesis and epigenesis of psychopathology. Development and Psychopathology, 11, 375–393.Google Scholar
Ciesielski, K. T., Lesnik, P. G., Savoy, R. L., Grant, E. P., & Ahlfors, S. P. (2006). Developmental neural networks in children performing a categorical n-back task. NeuroImage, 33, 980–990.Google Scholar
Conklin, H. M., Luciana, M., Hooper, C. J., & Yarger, R. S. (2007). Working memory performance in typically developing children and adolescents: Behavioral evidence of protracted frontal lobe development. Developmental Neuropsychology, 31, 103–128.Google Scholar
Connolly, J. D., Goodale, M. A., DeSouza, J. F. X., Menon, R. S., & Vilis, T. (2000). A comparison of frontoparietal fMRI activation during anti-saccades and anti-pointing. Journal of Neurophysiology, 84, 1645–1655.Google Scholar
Cornelissen, F. W., Kimmig, H., Schira, M., Rutschmann, R. M., Maguire, R. P., Broerse, A., et al. (2002). Event-related fMRI responses in the human frontal eye fields in a randomized pro- and antisaccade task. Experimental Brain Research, 145, 270–274.Google Scholar
Courchesne, E. (1997). Brainstem, cerebellar and limbic neuroanatomical abnormalities in autism. Current Opinion in Neurobiology, 7, 269–278.Google Scholar
Courchesne, E., Carper, R., & Akshoomoff, N. (2003). Evidence of brain overgrowth in the first year of life in autism. Journal of the American Medical Association, 290, 337–344.Google Scholar
Courchesne, E., Karns, C. M., Davis, H. R., Ziccardi, R., Carper, R. A., Tigue, Z. D., et al. (2001). Unusual brain growth patterns in early life in patients with autistic disorder: An MRI study. Neurology, 57, 245–254.Google Scholar
Courchesne, E., Pierce, K., Schumann, C. M., Redcay, E., Buckwalter, J. A., Kennedy, D. P., et al. (2007). Mapping early brain development in autism. Neuron, 56, 399–413.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, 577–597.Google Scholar
Courchesne, E., Yeung-Courchesne, R., Press, G. A., Hesselink, J. R., & Jernigan, T. L. (1988). Hypoplasia of cerebellar vermal lobules VI and VII in autism. New England Journal of Medicine, 318, 1349–1354.Google Scholar
Courtney, S. M., Petit, L., Maisog, J. M., Ungerleider, L. G., & Haxby, J. V. (1998). An area specialized for spatial working memory in human frontal cortex. Science, 279, 1347–1351.Google Scholar
Crone, E. A., Wendelken, C., Donohue, S., van Leijenhorst, L., & Bunge, S. A. (2006). Neurocognitive development of the ability to manipulate information in working memory. Proceedings of the National Academy of Sciences of the United States of America, 103, 9315–9320.Google Scholar
Curtis, C. E., & D'Esposito, M. (2003). Success and failure suppressing reflexive behavior. Journal of Cognitive Neuroscience, 15, 409–418.Google Scholar
Curtis, C. E., Rao, V. Y., & D'Esposito, M. (2004). Maintenance of spatial and motor codes during oculomotor delayed response tasks. Journal of Neuroscience, 24, 3944–3952.Google Scholar
D'Esposito, M., Detre, J. A., Alsop, D. C., Shin, R. K., Atlas, S., & Grossman, M. (1995). The neural basis of the central executive system of working memory. Nature, 378, 279–281.Google Scholar
Damasio, H., Maurer, R. G., Damasio, A. R., & Chui, H. C. (1980). Computerized tomographic scan findings in patients with autistic behavior. Archives of Neurology, 37, 504–510.Google Scholar
Dawson, G., Webb, S., Schellenberg, G. D., Dager, S., Friedman, S., Aylward, E., et al. (2008). Defining the broader phenotype of autism: Genetic, brain, and behavioral perspectives. Development and Psychopathology, 14, 581–611.Google Scholar
DeLuca, C. R., Wood, S. J., Anderson, V., Bucanan, J., Proffitt, T. M., & Mahony, K. (2003). Normative data from the CANTAB: I. Development of executive function over the lifespan. Journal of Clinical & Experimental Neuropsychology, 25, 242–254.Google Scholar
Demetriou, A., Christou, C., Spanoudis, G., & Platsidou, M. (2002). The development of mental processing: Efficiency, working memory, and thinking. Monographs of the Society for Research in Child Development, 67, 1–156.Google Scholar
Dempster, F. N. (1981). Memory span: Sources of individual and developmental differences. Psychological Bulletin, 89, 63–100.Google Scholar
Dempster, F. N. (1992). The rise and fall of the inhibitory mechanism: Toward a unified theory of cognitive development and aging. Developmental Review, 12, 45–75.Google Scholar
Diamond, A. (1990). Developmental time course in human infants and infant monkeys, and the neural bases of, inhibitory control in reaching. In Diamond, A. (Ed.), The development and neural bases of higher cognitive functions (pp. 637–676). New York: New York Academy of Science.Google Scholar
Diamond, A., & Goldman-Rakic, P. S. (1989). Comparison of human infants and rhesus monkeys on Piaget's AB task: Evidence for dependence on dorsolateral prefrontal cortex. Experimental Brain Research, 74, 24–40.Google Scholar
Doricchi, F., Perani, D., Incoccia, C., Grassi, F., Cappa, S. F., Bettinardi, V., et al. (1997). Neural control of fast-regular saccades and antisaccades: An investigation using positron emission tomographytomography. Experimental Brain Research, 116, 50–62.Google Scholar
Duncan, J. (1986). Disorganisation of behavior after frontal lobe damage. Cognitive Neuropsychology, 3, 271–290.Google Scholar
Durston, S., Davidson, M. C., Tottenham, N., Galvan, A., Spicer, J., Fossella, J. A., et al. (2006). A shift from diffuse to focal cortical activity with development. Developmental Science, 9, 1–8.Google Scholar
Edin, F., Macoveanu, J., Olesen, P. J., Tegner, J., & Klingberg, T. (2007). Stronger synaptic connectivity as a mechanism behind development of working memory-related brain activity during childhood. Journal of Cognitive Neuroscience, 19, 750–760.Google Scholar
Egaas, B., Courchesne, E., & Saitoh, O. (1995). Reduced size of corpus callosum in autism. Archives of Neurology, 52, 794–801.Google Scholar
Eskes, G. A., Bryson, S. E., & McCormick, T. A. (1990). Comprehension of concrete and abstract words in autistic children. Journal of Autism and Developmental Disorders, 20, 61–73.Google Scholar
Everling, S., Dorris, M. C., Klein, R. M., & Munoz, D. P. (1999). Role of primate superior colliculus in preparation and execution of anti-saccades and pro-saccades. Journal of Neuroscience, 19, 2740–2754.Google Scholar
Fair, D. A., Dosenbach, N. U., Church, J. A., Cohen, A. L., Brahmbhatt, S., Miezin, F. M., et al. (2007). Development of distinct control networks through segregation and integration. Proceedings of the National Academy of Sciences of the United States of America, 104, 13507–13512.Google Scholar
Filipek, P. A. (1999). Neuroimaging in the developmental disorders: The state of the science. Journal of Child Psychology and Psychiatry and Allied Disciplines, 40, 113–128.Google Scholar
Filipek, P. A., Richelme, C., Kennedy, D. N., Rademacher, J., Pitcher, D. A., Zidel, S., et al. (1992). Morphometric analysis of the brain in developmental language disorders and autism. Annals of Neurology, 32, 475.Google Scholar
Fischer, B., Biscaldi, M., & Gezeck, S. (1997). On the development of voluntary and reflexive components in human saccade generation. Brain Research, 754, 285–297.Google Scholar
Ford, K. A., Goltz, H. C., Brown, M. R., & Everling, S. (2005). Neural processes associated with antisaccade task performance investigated with event-related FMRI. Journal of Neurophysiology, 94, 429–440.Google Scholar
Fukushima, J., Hatta, T., & Fukushima, K. (2000). Development of voluntary control of saccadic eye movements. I. Age-related changes in normal children. Brain & Development, 22, 173–180.Google Scholar
Funahashi, S., Chafee, M. V., & Goldman-Rakic, P. S. (1993). Prefrontal neuronal activity in rhesus monkeys performing a delayed anti-saccade task. Nature, 365, 753–756.Google Scholar
Funahashi, S., Inoue, M., & Kubota, K. (1997). Delay-period activity in the primate prefrontal cortex encoding multiple spatial positions and their order of presentation. Behavioural Brain Research, 84, 203–223.Google Scholar
Garber, H. J., & Ritvo, E. R. (1992). Magnetic resonance imaging of the posterior fossa in autistic adults. American Journal of Psychiatry, 149, 245–247.Google Scholar
Geurts, H. M., Verte, S., Oosterlaan, J., Roeyers, H., & Sergeant, J. A. (2004). How specific are executive functioning deficits in attention deficit hyperactivity disorder and autism? Journal of Child Psychology and Psychiatry and Allied Disciplines, 45, 836–854.Google Scholar
Giedd, 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, 861–863.Google Scholar
Giedd, J. N., Rumsey, J. M., Castellanos, F. X., Rajapakse, J. C., Kaysen, D., Vaituzis, A. C., et al. (1996). A quantitative MRI study of the corpus callosum in children and adolescents. Developmental Brain Research, 91, 274–280.Google Scholar
Gogtay, N., Giedd, J. N., Lusk, L., Hayashi, K. M., Greenstein, D., Vaituzis, A. C., et al. (2004). Dynamic mapping of human cortical development during childhood through early adulthood. Proceedings of the National Academy of Sciences of the United States of America, 101, 8174–8179.Google Scholar
Goldberg, M. C., Lasker, A. G., Zee, D. S., Garth, E., Landa, R. J., Tien, A., et al. (2002). Deficits in the initiation of eye movements in the absence of a visual target in adolescents with high functioning autism. Neuropsychologia, 40, 2039–2049.Google Scholar
Goldberg, M. C., Mostofsky, S. H., Cutting, L. E., Mahone, E. M., Astor, B. C., Denckla, M. B., et al. (2005). Subtle executive impairment in children with autism and children with ADHD. Journal of Autism & Developmental Disorders, 35, 279–293.Google Scholar
Goldman-Rakic, P. S. (1988). Topography of cognition: Parallel distributed networks in primate association cortex. Annual Review of Neuroscience, 11, 137–156.Google Scholar
Goldman-Rakic, P. S., Chafee, M., & Friedman, H. (1993). Allocation of function in distributed circuits. In Ono, T., Squire, L. R., Raichle, M. E., Perrett, D. I., & Fukuda, M. (Eds.), Brain mechanisms of perception and memory: From neuron to behavior (pp. 445–456). New York: Oxford University Press.Google Scholar
Gottlieb, J., & Goldberg, M. E. (1999). Activity of neurons in the lateral intraparietal area of the monkey during an antisaccade task. Nature Neuroscience, 2, 906–912.Google Scholar
Greenberg, L. M., & Waldman, I. D. (1993). Developmental normative data on the test of variables of attention (T.O.V.A.). Journal of Child Psychology and Psychiatry and Allied Disciplines, 34, 1019–1030.Google Scholar
Greene, C. M., Braet, W., Johnson, K. A., & Bellgrove, M. A. (in press). Imaging the genetics of executive function. Biological Psychology.Google Scholar
Griffith, E. M., Pennington, B. F., Wehner, E. A., & Rogers, S. J. (1999). Executive functions in young children with autism. Child Development, 70, 817–832.Google Scholar
Guitton, D., Buchtel, H. A., & Douglas, R. M. (1985). Frontal lobe lesions in man cause difficulties in suppressing reflexive glances and in generating goal-directed saccades. Experimental Brain Research, 58, 455–472.Google Scholar
Hale, S., Bronik, M. D., & Fry, A. F. (1997). Verbal and spatial working memory in school-age children: Developmental differences in susceptibility to interference. Developmental Psychology, 33, 364–371.Google Scholar
Hallett, P. E. (1978). Primary and secondary saccades to goals defined by instructions. Vision Research, 18, 1279–1296.Google Scholar
Happe, F., Booth, R., Charlton, R., & Hughs, C. (2006). Executive function deficits in autism spectrum disorders and attention-deficit/hyperactivity disorder: Examining profiles across domains and ages. Brain and Cognition, 61, 25–39.Google Scholar
Hardan, A. Y., Minshew, N. J., & Keshavan, M. S. (2000). Corpus callosum size in autism. Neurology, 55, 1033–1036.Google Scholar
Hardan, A. Y., Minshew, N. J., Mallikarjuhn, M., & Keshavan, M. S. (2001). Brain volume in autism. Journal of Child Neurology, 16, 421–424.Google Scholar
Hashimoto, T., Tayama, M., Murakawa, K., Yoshimoto, T., Miyazaki, M., Harada, M., et al. (1995). Development of the brainstem and cerebellum in autistic patients. Journal of Autism and Developmental Disorders, 25, 1–18.Google Scholar
Herbert, M. R., Ziegler, D. A., Deutsch, C. K., O'Brien, L. M., Lange, N., Bakardjiev, A., et al. (2003). Dissociations of cerebral cortex, subcortical and cerebral white matter volumes in autistic boys. Brain, 126, 1182–1192.Google Scholar
Herbert, M. R., Ziegler, D. A., Makris, N., Filipek, P. A., Kemper, T. L., Normandin, J. J., et al. (2004). Localization of white matter volume increase in autism and developmental language disorder. Annals of Neurology, 55, 530–540.Google Scholar
Hikosaka, O., & Wurtz, R. H. (1983a). Visual and oculomotor function in monkey substantia nigra pars reticulata. I. Relation of visual and auditory responses to saccades. Journal of Neurophysiology, 49, 1230–1253.Google Scholar
Hikosaka, O., & Wurtz, R. H. (1983b). Visual and oculomotor functions of monkey substantia nigra pars reticulata. III. Memory-contingent visual and saccade responses. Journal of Neurophysiology, 49, 1268–1284.Google Scholar
Hill, E. L. (2004). Executive dysfunction in autism. Trends in Cognitive Sciences, 8, 26–32.Google Scholar
Hughes, C. & Russell, J. (1993). Autistic children's difficulty with mental disengagement from an object: Its implications for theories of autism. Developmental Psychology, 29, 498–510.Google Scholar
Hughes, J. R. (2007). Autism: The first firm finding = underconnectivity? Epilepsy & Behavior, 11, 20–24.Google Scholar
Hughes, J. R., & Melyn, M. (2005). EEG and seizures in autistic children and adolescents: Further findings with therapeutic implications. Clinical EEG and Neuroscience, 36, 15–20.Google Scholar
Huttenlocher, P. R. (1990). Morphometric study of human cerebral cortex development. Neuropsychologia, 28, 517–527.Google Scholar
Huttenlocher, P. R., & Dabholkar, A. S. (1997). Regional differences in synaptogenesis in human cerebral cortex. The Journal of Comparative Neurology, 387, 167–178.Google Scholar
Johnson, K. A., Robertson, I. H., Kelly, S. P., Silk, T. J., Barry, E., Daibhis, A., et al. (2007). Dissociation in performance of children with ADHD and high-functioning autism on a task of sustained attention. Neuropsychologia, 45, 2234–2245.Google Scholar
Johnstone, S. J., Pleffer, C. B., Barry, R. J., Clarke, A. R., & Smith, J. L. (2005). Development of inhibitory processing during the go/nogo task: A behavioral and event-related potential study of children and adults. Journal of Psychophysiology, 19, 11–23.Google Scholar
Joseph, R. M., McGrath, L. M., & Tager-Flusberg, H. (2005). Executive dysfunction and its relation to language ability in verbal school-age children with autism. Developmental Neuropsychology, 27, 361–378.Google Scholar
Just, M. A., Cherkassky, V. L., Keller, T. A., Kana, R. K., & Minshew, N. J. (2007). Functional and anatomical cortical underconnectivity in autism: Evidence from an FMRI study of an executive function task and corpus callosum morphometry. Cerebral Cortex, 17, 951–961.Google Scholar
Just, M. A., Cherkassky, V. L., Keller, T. A., & Minshew, N. J. (2004). Cortical activation and synchronization during sentence comprehension in high-functioning autism: Evidence of underconnectivity. Brain, 127, 1811–1821.Google Scholar
Kana, R. K., Keller, T. A., Cherkassky, V. L., Minshew, N. J., & Just, M. A. (2006). Sentence comprehension in autism: Thinking in pictures with decreased functional connectivity. Brain, 129, 2484–2493.Google Scholar
Kana, R. K., Keller, T. A., Minshew, N. J., & Just, M. A. (2007). Inhibitory control in high-functioning autism: Decreased activation and underconnectivity in inhibition networks. Biological Psychiatry, 62, 198–206.Google Scholar
Keller, T. A., Kana, R. K., & Just, M. A. (2007). A developmental study of the structural integrity of white matter in autism. NeuroReport, 18, 23–27.Google Scholar
Kimmig, H., Greenlee, M. W., Gondan, M., Schira, M., Kassubek, J., & Mergner, T. (2001). Relationship between saccadic eye movements and cortical activity as measured by fMRI: Quantitative and qualitative aspects. Experimental Brain Research, 141, 184–194.Google Scholar
Klein, C., & Foerster, F. (2001). Development of prosaccade and antisaccade task performance in participants aged 6 to 26 years. Psychophysiology, 38, 179–189.Google Scholar
Klein, C. H., Raschke, A., & Brandenbusch, A. (2003). Development of pro- and antisaccades in children with attention-deficit hyperactivity disorder (ADHD) and healthy controls. Psychophysiology, 40, 17–28.Google Scholar
Klingberg, T. (2006). Development of a superior frontal-intraparietal network for visuo-spatial working memory. Neuropsychologia, 44, 2171–2177.Google Scholar
Klingberg, T., Forssberg, H., & Westerberg, H. (2002). Increased brain activity in frontal and parietal cortex underlies the development of visuospatial working memory capacity during childhood. Journal of Cognitive Neuroscience, 14, 1–10.Google Scholar
Klingberg, T., Vaidya, C. J., Gabrieli, J. D. E., Moseley, M. E., & Hedehus, M. (1999). Myelination and organization of the frontal white matter in children: A diffusion tensor MRI study. NeuroReport, 10, 2817–2821.Google Scholar
Koshino, H., Carpenter, P. A., Minshew, N. J., Cherkassky, V. L., Keller, T. A., & Just, M. A. (2005). Functional connectivity in an fMRI working memory task in high-functioning autism. NeuroImage, 24, 810–821.Google Scholar
Koshino, H., Kana, R. K., Keller, T. A., Cherkassky, V. L., Minshew, N. J., & Just, M. A. (2008). fMRI investigation of working memory for faces in autism: Visual coding and underconnectivity with frontal areas. Cerebral Cortex, 18, 289–300.Google Scholar
Lainhart, J. E., Piven, J., Wzorek, M., Landa, R., Santangelo, S. L., Coon, H., et al. (1997). Macrocephaly in children and adults with autism. Journal of the American Academy of Child & Adolescent Psychiatry, 36, 282–290.Google Scholar
Landa, R. J., & Goldberg, M. C. (2005a). Language, social, and executive functions in high functioning autism: A continuum of performance. Journal of Autism and Developmental Disorders, 35, 557–573.Google Scholar
Landa, R. J., & Goldberg, M. C. (2005b). Language, social, and executive functions in high functioning autism: A continuum of performance. Journal of Autism and Developmental Disorders, 35, 557–573.Google Scholar
Lebel, C., Walker, L., Leemans, A., Phillips, L., & Beaulieu, C. (2008). Microstructural maturation of the human brain from childhood to adulthood. NeuroImage, 140, 1044–1055.Google Scholar
Lee, J. E., Bigler, E. D., Alexander, A. L., Lazar, M., DuBray, M. B., Chung, M. K., et al. (2007). Diffusion tensor imaging of white matter in the superior temporal gyrus and temporal stem in autism. Neuroscience Letters, 424, 127–132.Google Scholar
Lenroot, R. K., & Giedd, J. N. (2006). Brain development in children and adolescents: Insights from anatomical magnetic resonance imaging. Neuroscience and Biobehavioral Reviews, 30, 718–729.Google Scholar
Levin, H. S., Culhane, K. A., Hartmann, J., Evankovich, K., & Mattson, A. J. (1991). Developmental changes in performance on tests of purported frontal lobe functioning. Developmental Neuropsychology, 7, 377–395.Google Scholar
Levitas, A., Hagerman, R. J., Braden, M., Rimland, B., McBogg, P., & Matus, I. (1983). Autism and the fragile X syndrome. Journal of Developmental and Behavioral Pediatrics, 4, 151–158.Google Scholar
Li, T. Q., & Noseworthy, M. D. (2002). Mapping the development of white matter tracts with diffusion tensor imaging. Developmemtal Science, 5, 293–300.Google Scholar
Liston, C., Watts, R., Tottenham, N., Davidson, M. C., Niogi, S., Ulug, A. M., et al. (2006). Frontostriatal microstructure modulates efficient recruitment of cognitive control. Cerebral Cortex, 16, 553–560.Google Scholar
Lopez, B. R., Lincoln, A. J., Ozonoff, S., & Lai, Z. (2005). Examining the relationship between executive functions and restricted, repetitive symptoms of autistic disorder. Journal of Autism & Developmental Disorders, 35, 445–460.Google Scholar
Luciana, M., Conklin, H. M., Hooper, C. J., & Yarger, R. S. (2005). The development of nonverbal working memory and executive control processes in adolescents. Child Development, 76, 697–712.Google Scholar
Luciana, M., & Nelson, C. (1998). The functional emergence of prefrontally-guided working memory systems in four- to eight-year-old children. Neuropsychologia, 36, 273–293.Google Scholar
Luciana, M., & Nelson, C. A. (2002). Assessment of neuropsychological function through use of the Cambridge Neuropsychological Testing Automated Battery: Performance in 4- to 12-year-old children. Develomental Neuropsychology, 22, 595–624.Google Scholar
Luna, B., Doll, S., Hegedus, S. J., Minshew, N., & Sweeney, J. (2007). Maturation of executive function in autism. Biological Psychiatry, 61, 474–481.Google Scholar
Luna, B., Doll, S. K., Hegedus, S. J., Minshew, N. J., & Sweeney, J. A. (2006). Maturation of executive function in autism. Biological Psychiatry, 61, 474–481.Google Scholar
Luna, B., Garver, K., & Sweeney, J. A. (2000). Development in cognitive and sensorimotor systems from late childhood to adulthood. Paper presented at the 30th Annual Meeting of the Society for Neuroscience.Google Scholar
Luna, B., Garver, K. E., Urban, T. A., Lazar, N. A., & Sweeney, J. A. (2004). Maturation of cognitive processes from late childhood to adulthood. Child Development, 75, 1357–1372.Google Scholar
Luna, B., Minshew, N. J., Garver, K. E., Lazar, N. A., Thulborn, K. R., Eddy, W. F., et al. (2002). Neocortical system abnormalities in autism: An fMRI study of spatial working memory. Neurology, 59, 834–840.Google Scholar
Luna, B., Thulborn, K. R., Munoz, D. P., Merriam, E. P., Garver, K. E., Minshew, N. J., et al. (2001). Maturation of widely distributed brain function subserves cognitive development. NeuroImage, 13, 786–793.Google Scholar
Mabbott, D. J., Noseworthy, M., Bouffet, E., Laughlin, S., & Rockel, C. (2006). White matter growth as a mechanism of cognitive development in children. NeuroImage, 33, 936–946.Google Scholar
Marsh, R., Zhu, H., Schultz, R. T., Quackenbush, G., Royal, J., Skudlarski, P., et al. (2006). A developmental fMRI study of self-regulatory control. Human Brain Mapping, 27, 848–863.Google Scholar
Matson, J. L., & Nebel-Schwalm, M. S. (2007). Comorbid psychopathology with autism spectrum disorder in children: An overview. Research in Developmental Disabilities, 28, 341–352.Google Scholar
Matsuda, T., Matsuura, M., Ohkubo, T., Ohkubo, H., Matsushima, E., Inoue, K., et al. (2004). Functional MRI mapping of brain activation during visually guided saccades and antisaccades: Cortical and subcortical networks. Psychiatry Research, 131, 147–155.Google Scholar
McCarthy, G., Blamire, A. M., Puce, A., Nobre, A. C., Bloch, G., Hyder, F., et al. (1994). Functional magnetic resonance imaging of human prefrontal cortex activation during a spatial working memory task. Proceedings of the National Academy of Science of the United States of America, 91, 8690–8694.Google Scholar
McLaughlin, N. C., Paul, R. H., Grieve, S. M., Williams, L. M., Laidlaw, D., DiCarlo, M., et al. (2007). Diffusion tensor imaging of the corpus callosum: A cross-sectional study across the lifespan. Internation Journal of Developmental Neuroscience, 25, 215–221.Google Scholar
Menzies, L., Achard, S., Chamberlain, S. R., Fineberg, N., Chen, C., del Campo, N., et al. (2007a). Neurocognitive endophenotypes of obsessive–compulsive disorder. Brain, 130, 3223–3236.Google Scholar
Menzies, L., Chamberlain, S. R., Laird, A. R., Thelen, S. M., Sahakian, B. J., & Bullmore, E. T. (2007b). Integrating evidence from neuroimaging and neuropsychological studies of obsessive–compulsive disorder: The orbitofronto-striatal model revisited. Neuroscience & Biobehavioral Reviews, 3, 525–549.Google Scholar
Middleton, F. A., & Strick, P. L. (2001). Cerebellar projections to the prefrontal cortex of the primate. Journal of Neuroscience, 21, 700–712.Google Scholar
Minshew, N. J., Luna, B., & Sweeney, J. A. (1999). Oculomotor evidence for neocortical systems but not cerebellar dysfunction in autism. Neurology, 52, 917–922.Google Scholar
Minshew, N. J., Meyer, J. A., & Dunn, M. (2003). Autism spectrum disorders. In Segakiwutz, S. D. & Rapin, I. (Eds.), Handbook of neuropsychology (2nd ed., pp. 863–896). Amsterdam: Elsevier.Google Scholar
Minshew, N. J., Sweeney, J., & Luna, B. (2002). Autism as a selective disorder of complex information processing and underdevelopment of neocortical systems. Molecular Psychiatry, 7, S14–S15.Google Scholar
Minshew, N. J., & Williams, D. L. (2007). The new neurobiology of autism: Cortex, connectivity, and neuronal organization. Archives of Neurology, 64, 945–950.Google Scholar
Moseley, M. E., Cohen, Y., Kucharczyk, J., Mintorovitch, J., Asgari, H. S., Wendland, M. F., et al. (1990). Diffusion-weighted MR imaging of anisotropic water diffusion in cat central nervous system. Radiology, 176, 439–445.Google Scholar
Mostofsky, S. H., Goldberg, M. C., & Denckla, M. B. (2000). Evidence for a deficit in procedural learning in children and adolescents with autism: Implications for cerebellar contribution. Journal of the International Neuropsychological Society, 6, 752–759.Google Scholar
Mukherjee, P., Miller, J. H., Shimony, J. S., Conturo, T. E., Lee, B. C. P., Almli, C. R., et al. (2001). Normal brain maturation during childhood: Developmental trends characterized with diffusion-tensor MR imaging. Radiology, 221, 349–358.Google Scholar
Munoz, D. P., Broughton, J. R., Goldring, J. E., & Armstrong, I. T. (1998). Age-related performance of human subjects on saccadic eye movement tasks. Experimental Brain Research, 121, 391–400.Google Scholar
Muri, R. M., Heid, O., Nirkko, A. C., Ozdoba, C., Felblinger, J., Schroth, G., et al. (1998). Functional organisation of saccades and antisaccades in the frontal lobe in humans: A study with echo planar functional magnetic resonance imaging. Journal of Neurology, Neurosurgery and Psychiatry, 65, 374–377.Google Scholar
Murias, M., Webb, S. J., Greenson, J., & Dawson, G. (2007). Resting state cortical connectivity reflected in EEG coherence in individuals with autism. Biological Psychiatry, 62, 270–273.Google Scholar
Nacewicz, B., Dalton, K., Johnstone, T., Long, M., McAuliff, E., Oakes, T., et al. (2006). Amygdala volume and nonverbal social impairment in adolescent and adult males with autism. Archives of General Psychiatry, 63, 1417–1428.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 Cognition and Neuroscience, 16, 1227–1233.Google Scholar
Nelson, C. A., Monk, C. S., Lin, J., Carver, L. J., Thomas, K. M., & Truwitt, C. L. (2000). Functional neuroanatomy of spatial working memory in children. Developmental Psychology, 36, 109–116.Google Scholar
O'Driscoll, G. A., Alpert, N. M., Matthysse, S. W., Levy, D. L., Rauch, S. L., & Holzman, P. S. (1995). Functional neuroanatomy of antisaccade eye movements investigated with positron emission tomography. Proceedings of the National Academy of Sciences of the United States of America, 92, 925–929.Google Scholar
Olesen, P. J., Macoveanu, J., Tegner, J., & Klingberg, T. (2007). Brain activity related to working memory and distraction in children and adults. Cerebral Cortex, 17, 1047–1054.Google Scholar
Olesen, P. J., Nagy, Z., Westerberg, H., & Klingberg, T. (2003). Combined analysis of DTI and fMRI data reveals a joint maturation of white and grey matter in a fronto-parietal network. Cognitive Brain Research, 18, 48–57.Google Scholar
Owen, A. M., Downes, J. J., Sahakian, B. J., Polkey, C. E., & Robbins, T. W. (1990). Planning and spatial working memory following frontal lobe lesions in man. Neuropsychologia, 28, 1021–1034.Google Scholar
Owen, A. M., Evans, A. C., & Petrides, M. (1996). Evidence for a two-stage model of spatial working memory processing within the lateral frontal cortex: A positron emission tomography study. Cerebral Cortex, 6, 31–38.Google Scholar
Owen, A. M., Herrod, N. J., Menon, D. K., Clark, J. C., Downey, S. P. M. J., Carpenter, T. A., et al. (1999). Redefining the functional organization of working memory processes within human lateral prefrontal cortex. European Journal of Neuroscience, 11, 567–574.Google Scholar
Owen, A. M., Morris, R. G., Sahakian, B. J., Polkey, C. E., & Robbins, T. W. (1996). Double dissociations of memory and executive functions in working memory tasks following frontal lobe excisions, temporal lobe excisions or amygdalo-hippocampectomy in man. Brain, 119, 1597–1615.Google Scholar
Ozonoff, S., Cook, I., Coon, H., Dawson, G., Joseph, R. M., Klin, A., et al. (2004). Performance on Cambridge Neuropsychological Test Automated Battery subtests sensitive to frontal lobe function in people with autistic disorder: Evidence from the Collaborative Programs of Excellence in Autism Network. Journal of Autism and Developmental Disorders, 34, 139–150.Google Scholar
Ozonoff, S., & Strayer, D. L. (1997). Inhibitory function in nonretarded children with autism. Journal of Autism and Developmental Disorders, 27, 59–77.Google Scholar
Ozonoff, S., & Strayer, D. L. (2001). Further evidence of intact working memory in autism. Journal of Autism and Developmental Disorders, 31, 257–263.Google Scholar
Ozonoff, S., Strayer, D. L., McMahon, W. N., & Filloux, F. (1994). Executive function abilities in autism and Tourette syndrome: An information processing approach. Journal of Child Psychology and Psychiatry, 35, 1015–1032.Google Scholar
Pascualvaca, D. M., Fantie, B. D., Papageorgiou, M., & Mirsky, A. F. (1998). Attentional capacities in children with autism: Is there a general deficit in shifting focus? Journal of Autism and Developmental Disorders, 28, 467–478.Google Scholar
Paus, T. (1999). Imaging the brain before, during, and after transcranial magnetic stimulation. Neuropsychologia, 37, 219–224.Google Scholar
Paus, T., Babenko, V., & Radil, T. (1990). Development of an ability to maintain verbally instructed central gaze fixation studied in 8- to 10-year-old children. International Journal of Psychophysiology, 10, 53–61.Google Scholar
Paus, T., Zijdenbos, A., Worsley, K., Collins, D. L., Blumenthal, J., Giedd, J. N., et al. (1999). Structural maturation of neural pathways in children and adolescents: In vivo study. Science, 283, 1908–1911.Google Scholar
Penadés, R., Catalan, R., Rubia, K., Andres, S., Salamero, M., & Gasto, C. (2007). Impaired response inhibition in obsessive compulsive disorder. European Psychiatry, 22, 404–410.Google Scholar
Pennington, B. F., & Ozonoff, S. (1996). Executive functions and developmental psychopathology. Journal of Child Psychology and Psychiatry and Allied Disciplines, 37, 51–87.Google Scholar
Peterson, B. S., Pine, D. S., Cohen, P., & Brook, J. S. (2001). Prospective, longitudinal study of tic, obsessive-compulsive, and attention-deficit/hyperactivity disorders in an epidemiological sample. Journal of the American Academy of Child & Adolescent Psychiatry, 40, 685–695.Google Scholar
Pfefferbaum, A., Mathalon, D. H., Sullivan, E. V., Rawles, J. M., Zipursky, R. B., & Lim, K. O. (1994). A quantitative magnetic resonance imaging study of changes in brain morphology from infancy to late adulthood. Archives of Neurology, 51, 874–887.Google Scholar
Piven, J., Arndt, S., Bailey, J., & Andreasen, N. (1996). Regional brain enlargement in autism: A magnetic resonance imaging study. Journal of the American Academy of Child & Adolescent Psychiatry, 35, 530–536.Google Scholar
Piven, J., Arndt, S., Bailey, J., Havercamp, S., Andreasen, N. C., & Palmer, P. (1995). An MRI study of brain size in autism. American Journal of Psychiatry, 152, 1145–1149.Google Scholar
Piven, J., Bailey, J., Ranson, B. J., & Arndt, S. (1997). An MRI study of the corpus callosum in autism. American Journal of Psychiatry, 154, 1051–1056.Google Scholar
Piven, J., Bailey, J., Ranson, B. J., & Arndt, S. (1998). No difference in hippocampus volume detected on magnetic resonance imaging in autistic individuals. Journal of Autism and Developmental Disorders, 28, 105–110.Google Scholar
Piven, J., Berthier, M. L., Starkstein, S. E., Nehme, E., Pearlson, G., & Folstein, S. (1990). Magnetic resonance imaging evidence for a defect of cerebral cortical development in autism. American Journal of Psychiatry, 147, 734–739.Google Scholar
Pujol, J., Vendrell, P., Junqué, C., Martí-Vilalta, J. L., & Capdevila, A. (1993). When does human brain development end? Evidence of corpus callosum growth up to adulthood. Annals of Neurology, 34, 71–75.Google Scholar
Raemaekers, M., Vink, M., van den Heuvel, M. P., Kahn, R. S., & Ramsey, N. F. (2005). Brain activation related to retrosaccades in saccade experiments. NeuroReport, 16, 1043–1047.Google Scholar
Rakic, P., Bourgeois, J. P., Eckenhoff, M. F., Zecevic, N., & Goldman-Rakic, P. S. (1986). Concurrent overproduction of synapses in diverse regions of the primate cerebral cortex. Science, 232, 232–235.Google Scholar
Rauschecker, J. P., & Marler, P. (1987). What signals are responsible for synaptic changes in visual cortical plasticity? In Rauschecker, J. P. & Marler, P. (Eds.), Imprinting and cortical plasticity (pp. 193–200). New York: Wiley.Google Scholar
Ravizza, S. M., McCormick, C. A., Schlerf, J. E., Justus, T., Ivry, R. B., & Fiez, J. A. (2006). Cerebellar damage produces selective deficits in verbal working memory. Brain, 129, 306–320.Google Scholar
Raymaekers, R., Antrop, I., van der Meere, J. J., Wiersema, J. R., & Roeyers, H. (2007). HFA and ADHD: A direct comparison on state regulation and response inhibition. Journal of Clinical and Experimental Neuropsychology, 29, 418–427.Google Scholar
Raymaekers, R., van der Meere, J., & Roeyers, H. (2004). Event-rate manipulation and its effect on arousal modulation and response inhibition in adults with high functioning autism. Journal of Clinical and Experimental Neuropsychology, 26, 74–82.Google Scholar
Redcay, E., & Courchesne, E. (2005). When is the brain enlarged in autism? A meta-analysis of all brain size reports. Biological Psychiatry, 58, 1–9.Google Scholar
Reiss, A. L., Abrams, M. T., Singer, H. S., Ross, J. L., & Denckla, M. B. (1996). Brain development, gender and IQ in children. A volumetric imaging study. Brain, 119, 1763–1774.Google Scholar
Ridderinkhof, K. R., Band, G. P. H., & Logan, G. D. (1999). A study of adaptive behavior: Effects of age and irrelevant information on the ability to inhibit one's actions. Acta Psychologica, 101, 315–337.Google Scholar
Ridderinkhof, K. R., & van der Molen, M. W. (1997). Mental resources, processing speed, and inhibitory control: A developmental perspective. Biol Psychol, 45, 241–261.Google Scholar
Ridderinkhof, K. R., van der Molen, M. W., Band, G. P., & Bashore, T. R. (1997). Sources of interference from irrelevant information: A developmental study. Journal of Experimental Child Psychology, 65, 315–341.Google Scholar
Robbins, T. W., James, M., Owen, A. M., Sahakian, B. J., Lawrence, A. D., McInnes, L., et al. (1998). A study of performance on tests from the CANTAB battery sensitive to frontal lobe dysfunction in a large sample of normal volunteers: Implications for theories of executive functioning and cognitive aging. Cambridge Neuropsychological Test Automated Battery. Journal of the International Neuropsychological Society, 4, 474–490.Google Scholar
Romer, D., & Walker, E. (2007). Adolescent psychopathology and the developing brain. New York: Oxford University Press.Google Scholar
Ross, R. G., Harris, J. G., Olincy, A., & Radant, A. (2000). Eye movement task measures inhibition and spatial working memory in adults with schizophrenia, ADHD, and a normal comparison group. Psychiatry Research, 95, 35–42.Google Scholar
Roth, R. M., Saykin, A. J., Flashman, L. A., Pixley, H. S., West, J. D., & Mamourian, A. C. (2007). Event-related functional magnetic resonance imaging of response inhibition in obsessive–compulsive disorder. Biological Psychiatry, 62, 901–909.Google Scholar
Rubia, K., Overmeyer, S., Taylor, E., Brammer, M., Williams, S. C., Simmons, A. et al. (2000). Functional frontalisation with age: Mapping neurodevelopmental trajectories with fMRI. Neuroscience and Biobehavioral Reviews, 24, 13–19.Google Scholar
Rubia, K., Russel, T., Overmeyer, S., Brammer, M. J., Bullmore, E. T., Sharma, T., et al. (2001). Mapping motor inhibition: Conjunctive brain activations across different versions of go/no-go and stop tasks. NeuroImage, 13, 250–261.Google Scholar
Rubia, K., Smith, A. B., Brammer, M. J., Toone, B., & Taylor, E. (2005). Abnormal brain activation during inhibition and error detection in medication-naive adolescents with ADHD. The American Journal of Psychiatry, 162, 1067–1075.Google Scholar
Rubia, K., Smith, A. B., Taylor, E., & Brammer, M. (2007). Linear age-correlated functional development of right inferior fronto-striato-cerebellar networks during response inhibition and anterior cingulate during error-related processes. Human Brain Mapping, 28, 1163–1177.Google Scholar
Rubia, K., Smith, A. B., Woolley, J., Nosarti, C., Heyman, I., Taylor, E. et al. (2006). Progressive increase of frontostriatal brain activation from childhood to adulthood during event-related tasks of cognitive control. Human Brain Mapping, 27, 973–993.Google Scholar
Ruchsow, M., Reuter, K., Hermle, L., Ebert, D., Kiefer, M., & Falkenstein, M. (2007). Executive control in obsessive–compulsive disorder: Event-related potentials in a go/no go task. Journal of Neural Transmission, 114, 1595–1601.Google Scholar
Rumsey, J. M., & Hamburger, S. D. (1988). Neuropsychological findings in high-functioning men with infantile autism, residual state. Journal of Clinical & Experimental Neuropsychology, 10, 201–221.Google Scholar
Russell, J. (1997). Autism as an executive disorder. New York: Oxford University Press.Google Scholar
Russell, J., Jarrold, C., & Hood, B. (1999). Two intact executive capacities in children with autism: Implications for the core executive dysfunctions in the disorder. Journal of Autism and Developmental Disorders, 29, 103–112.Google Scholar
Russo, N., Flanagan, T., Iarocci, G., Berringer, D., Zelazo, P. D., & Burack, J. A. (2007). Deconstructing executive deficits among persons with autism: implications for cognitive neuroscience. Brain and Cognition, 65, 77–86.Google Scholar
Saitoh, O., Courchesne, E., Egaas, B., Lincoln, A. J., & Schreibman, L. (1995). Cross-sectional area of the posterior hippocampus in autistic patients with cerebellar and corpus callosum abnormalities. Neurology, 45, 317–324.Google Scholar
Santesso, D. L., & Segalowitz, S. J. (2008). Developmental differences in error-related ERPs in middle- to late-adolescent males. Developmental Psychology, 44, 205–217.Google Scholar
Schaefer, G. B., Thompson, J. N., Bodensteiner, J. B., McConnell, J. M., Kimberling, W. J., Gay, C. T., et al. (1996). Hypoplasia of the cerebellar vermis in neurogenetic syndromes. Annals of Neurology, 39, 382–385.Google Scholar
Scherf, K. S., Sweeney, J. A., & Luna, B. (2006). Brain basis of developmental change in visuospatial working memory. Journal of Cognitive Neuroscience, 18, 1045–1058.Google Scholar
Schifter, T., Hoffman, J. M., Hatten, P., Hanson, M. W., Coleman, R. E., & DeLong, G. R. (1994). Neuroimaging in infantile autism. Journal of Child Neurology, 9, 155–161.Google Scholar
Schlag-Rey, M., Amador, N., Sanchez, H., & Schlag, J. (1997). Antisaccade performance predicted by neuronal activity in the supplementary eye field. Nature, 390, 398–401.Google Scholar
Schmithorst, V. J., Wilke, M., Dardzinski, B. J., & Holland, S. K. (2002). Correlation of white matter diffusivity and anisotropy with age during childhood and adolescence: A cross-sectional diffusion-tensor MR imaging study. Radiology, 222, 212–218.Google Scholar
Schmitz, N., Rubia, K., Daly, E., Smith, A., Williams, S., & Murphy, D. G. (2006). Neural correlates of executive function in autistic spectrum disorders. Biological Psychiatry, 59, 7–16.Google Scholar
Schumann, C. M., & Amaral, D. G. (2006). Stereological analysis of amygdala neuron number in autism. Journal of Neuroscience, 26, 7674–7679.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. American Journal of Psychiatry, 163, 1440–1443.Google Scholar
Simpson, A., & Riggs, K. J. (2006). Conditions under which children experience inhibitory difficulty with a “button-press” go/no-go task. Journal of Experimental Child Psychology, 94, 18–26.Google Scholar
Snook, L., Plewes, C., & Beaulieu, C. (2007). Voxel based versus region of interest analysis in diffusion tensor imaging of neurodevelopment. NeuroImage, 34, 243–252.Google Scholar
Song, S. K., Sun, S. W., Ju, W. K., Lin, S. J., Cross, A. H., & Neufeld, A. H. (2003). Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia. NeuroImage, 20, 1714–1722.Google Scholar
South, M., Ozonoff, S., & McMahon, W. M. (2007). The relationship between executive functioning, central coherence, and repetitive behaviors in the high-functioning autism spectrum. Autism, 11, 437–451.Google Scholar
Sowell, E. R., Thompson, P. M., Holmes, C. J., Jernigan, T. L., & Toga, A. W. (1999). In vivo evidence for post-adolescent brain maturation in frontal and striatal regions. Nature Neuroscience, 2, 859–861.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. Journal of Neuroscience, 21, 8819–8829.Google Scholar
Sparks, B. F., Friedman, S. D., Shaw, D. W., Aylward, E. H., Echelard, D., Artru, A. A. et al. (2002). Brain structural abnormalities in young children with autism spectrum disorder. Neurology, 59, 184–192.Google Scholar
Steele, S., Minshew, N., Luna, B., & Sweeney, J. (2007). Spatial working memory deficits in autism. Journal of Autism and Developmental Disorders, 37, 605–612.Google Scholar
Stevens, M. C., Kiehl, K. A., Pearlson, G. D., & Calhoun, V. D. (2007). Functional neural networks underlying response inhibition in adolescents and adults. Behavioural Brain Reserach, 181, 12–22.Google Scholar
Suskauer, S. J., Simmonds, D. J., Fotedar, S., Blankner, J. G., Pekar, J. J., Denckla, M. B., et al. (2008). Functional magnetic resonance imaging evidence for abnormalities in response selection in attention deficit hyperactivity disorder: Differences in activation associated with response inhibition but not habitual motor response. Journal of Cognitive Neuroscience, 20, 478–493.Google Scholar
Swanson, H. L. (1999). What develops in working memory? A life span perspective. Developmental Psychology, 35, 986–1000.Google Scholar
Sweeney, J. A., Mintun, M. A., Kwee, S., Wiseman, M. B., Brown, D. L., Rosenberg, D. R. et al. (1996). Positron emission tomography study of voluntary saccadic eye movements and spatial working memory. Journal of Neurophysiology, 75, 454–468.Google Scholar
Sweeney, J. A., Takarae, Y., Macmillan, C., Luna, B., & Minshew, N. J. (2004). Eye movements in neurodevelopmental disorders. Current Opinion in Neurology, 17, 37–42.Google Scholar
Taber, K. H., Shaw, J. B., Loveland, K. A., Pearson, D. A., Lane, D. M., & Hayman, L. A. (2004). Accentuated Virchow–Robin spaces in the centrum semiovale in children with autistic disorder. Journal of Computer Assisted Tomography, 28, 263–268.Google Scholar
Takarae, Y., Minshew, N. J., Luna, B., Krisky, C. M., & Sweeney, J. A. (2004). Pursuit eye movement deficits in autism. Brain, 127, 2584–2594.Google Scholar
Takarae, Y., Minshew, N. J., Luna, B., & Sweeney, J. A. (2004). Oculomotor abnormalities parallel cerebellar histopathology in autism. Journal of Neurology, Neurosurgery and Psychiatry, 75, 1359–1361.Google Scholar
Tamm, L., Menon, V., & Reiss, A. L. (2002). Maturation of brain function associated with response inhibition. Journal of the American Academy of Child & Adolescent Psychiatry, 41, 1231–1238.Google Scholar
Thatcher, R. W., Walker, R. A., & Giudice, S. (1987). Human cerebral hemispheres develop at different rates and ages. Science, 236, 1110–1113.Google Scholar
Thomas, K. M., King, S. W., Franzen, P. L., Welsh, T. F., Berkowitz, A. L., Noll, D. C., et al. (1999). A developmental functional MRI study of spatial working memory. NeuroImage, 10, 327–338.Google Scholar
Tipper, S. P., Bourque, T. A., Anderson, S. H., & Brehaut, J. C. (1989). Mechanisms of attention: A developmental study. Journal of Experimental Child Psychology, 48, 353–378.Google Scholar
Toga, A. W., Thompson, P. M., & Sowell, E. R. (2006). Mapping brain maturation. Trends in Neurosciences, 29, 148–159.Google Scholar
Townsend, J., Courchesne, E., Covington, J., Westerfield, M., Harris, N. S., Lyden, P., et al. (1999). Spacial attention deficits in patients with acquired or developmental cerebellar abnormality. Journal of Neuroscience, 19, 5632–5643.Google Scholar
van der Geest, J. N., Kemner, C., Camfferman, G., Verbaten, M. N. & van Engeland, H. (2001). Eye movements, visual attention, and autism: A saccadic reaction time study using the gap and overlap paradigm. Biological Psychiatry, 50, 614–619.Google Scholar
Velanova, K., Wheeler, M. E., & Luna, B. (in press). Maturational changes in anterior cingulate and frontoparietal recruitment support the development of error processing and inhibitory control. Cerebral Cortex.Google Scholar
Verte, S., Geurts, H. M., Roeyers, H., Oosterlaan, J., & Sergeant, J. A. (2006). The relationship of working memory, inhibition, and response variability in child psychopathology. Journal of Neuroscience Methods, 151, 5–14.Google Scholar
Volkmar, R., Chawarska, K., & Klin, A. (2005). Autism in infancy and early childhood. Annual Review of Psychology, 56, 315–336.Google Scholar
Vuontela, V., Steenari, M. R., Carlson, S., Koivisto, J., Fjällberg, M., & Aronen, E. T. (2003). Audiospatial and visuospatial working memory in 6–13 year old school children. Learning & Memory, 10, 74–81.Google Scholar
Waiter, G. D., Williams, J. H., Murray, A. D., Gilchrist, A., Perrett, D. I., & Whiten, A. (2005). Structural white matter deficits in high-functioning individuals with autistic spectrum disorder: A voxel-based investigation. NeuroImage, 24, 455–461.Google Scholar
Walker, R., Husain, M., Hodgson, T. L., Harrison, J., & Kennard, C. (1998). Saccadic eye movement and working memory deficits following damage to human prefrontal cortex. Neuropsychologia, 36, 1141–1159.Google Scholar
Williams, B. R., Ponesse, J. S., Schachar, R. J., Logan, G. D., & Tannock, R. (1999). Development of inhibitory control across the life span. Developmental Psychology, 35, 205–213.Google Scholar
Williams, D. L., & Minshew, N. J. (2007). Understanding autism and related disorders: what has imaging taught us? Neuroimaging Clinics of North America, 17, 495–509.Google Scholar
Wilson, T. W., Rojas, D. C., Reite, M. L., Teale, P. D., & Rogers, S. J. (2007). Children and adolescents with autism exhibit reduced MEG steady-state gamma responses. Biological Psychiatry, 62, 192–197.Google Scholar
Wise, L. A., Sutton, J. A., & Gibbons, P. D. (1975). Decrement in Stroop interference time with age. Perceptual and Motor Skills, 41, 149–150.Google Scholar
Woolley, J., Heyman, I., Brammer, M., Frampton, I., McGuire, P. K., & Rubia, K. (2008). Brain activation in paediatric obsessive compulsive disorder during tasks of inhibitory control. British Journal of Psychiatry, 192, 25–31.Google Scholar
Yakovlev, P. I., & Lecours, A. R. (1967). The myelogenetic cycles of regional maturation of the brain. In Minkowski, A. (Ed.), Regional development of the brain in early life (pp. 3–70). Oxford: Blackwell Scientific.Google Scholar
Zald, D. H., & Iacono, W. G. (1998). The development of spatial working memory abilities. Developmental Neuropsychology, 14, 563–578.Google Scholar
- 169
- Cited by