Skip to main content
SpringerLink
Log in

Brain organization of the preparation to visual recognition in preadolescent children

  • Published:
Human Physiology Aims and scope Submit manuscript

Abstract

The brain organization of the preparation to perceiving incomplete images fragmented to different extents was studied in children aged 10–11 and 11–12 years. Functional connections of the ventrolateral and dorsoventral cortical zones with other zones were examined at three consecutive stages of the preparation to perceiving incomplete images. The results were compared with data obtained for adults. The effect of preparation on image recognition was inferred from regional event-related potentials. In adults, functional interactions of the dorsolateral and ventrolateral prefrontal cortex with other cortical zones of the right hemisphere were enhanced at the stage of waiting for a target stimulus not recognized yet, while connections in the left hemisphere became stronger short before the stimulus was successfully recognized. In children, stagerelated changes in functional interactions were similar between the two hemispheres, and peak interaction activity was observed at the stage preceding the successful recognition. Children aged 11–12 years showed a lower involvement of the ventrolateral cortex in the preparatory stage and recognition as compared with adults and 10- to 11-year-old children. At the same time, the older children had a more mature pattern of the dorsolateral cortex involvement, which provided for a more efficient recognition than in the younger children. The features observed for the brain organization of visual recognition and preceding preparatory processes in 11- to 12-year-old children were assumed to result from the multidirectional effects sex hormones exert on the function of various prefrontal cortical zones in early puberty.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Machinskaya, R.I., Machinskii, N.O., and Deryugina, E.I., Functional organization of the right and left hemispheres of the human brain during selective attention, Fiziol. Chel., 1992, vol. 18, no. 6, p. 77.

    Google Scholar 

  2. Yamagishi, N., Callan, D.E., Anderson, S.J., and Kawato, M., Attentional changes in pre-stimulus oscillatory activity within early visual cortex are predictive of human visual performance, Brain Res., 2008, vol. 1197, no. 4, p. 115.

    Article  CAS  PubMed  Google Scholar 

  3. Posner, M.I. and Fan, J., Attention as an organ system, Topics in Integrative Neuroscience: From Cells to Cognition, Pomerantz, J.R., Ed., Cambridge: Cambridge Univ. Press, 2008, p. 31.

    Chapter  Google Scholar 

  4. Bar, M., A cortical mechanism for triggering top-down facilitation in visual object recognition, J. Cogn. Neurosci., 2003, vol. 15, p. 600.

    Article  PubMed  Google Scholar 

  5. Farber, D.A. and Petrenko, N.E., Recognition of fragmented images and mechanisms of memory, Hum. Physiol., 2008, vol. 34, no. 1, p. 1.

    Article  Google Scholar 

  6. Kurganskii, A.V. and Grigal, P.P., Execution of serial movements determined by a consequence of sensory signals: Individual differences in the character of the early stage of serial learning, Zh. Vyssh. Nervn. Deyat. im. I.P. Pavlova, 2009, vol. 59, no. 6, p. 640.

    Google Scholar 

  7. Bollinger, J., Rubens, M.T., Zanto, T.P., and Gazzaley, A., Expectation-driven changes in cortical functional connectivity influence working-memory and long-term memory performance, J. Neurosci., 2010, vol. 30, no. 43, p. 399.

    Article  Google Scholar 

  8. Machinskaya, R.I. and Dubrovinskaya, N.V., Functional organization of brain hemispheres during selective attention in sevento eight-year-old children, Zh. Vyssh. Nervn. Deyat. im. I.P. Pavlova, 1996, vol. 46, no. 3, p. 437.

    Google Scholar 

  9. Machinskaya, R.I. and Semenova, O.A., Functional organization of attention and voluntary organization of activity, Razvitie mozga i formirovanie poznavatel’noi deyatel’nosti rebenka (Brain Development and the Formation of Cognitive Activity in Children), Farber, D.A. and Bezrukikh, M.M, Eds., Moscow: Izd-vo MPSI, 2009, p. 161.

    Google Scholar 

  10. Farber, D.A. and Beteleva, T.G., Development of the brain’s organization of working memory in young schoolchildren, Hum. Physiol., 2011, vol. 37, no. 1, p. 1.

    Article  Google Scholar 

  11. Mozgovye mekhanizmy formirovaniya poznavatel’noi deyatel’nosti v predshkol’nom i mladshem shkol’nom vozraste (Brain Mechanisms of the Formation of Cognitive Activity in Preschool and Young Schoolchildren), Machinskaya, R.I. and Farber, D.A., Eds., Moscow: MPSU, 2014, p. 157.

  12. Klingberg, T., Development of superior frontal-intraparietal network for visuo-spatial working memory, Neuropsychologia, 2006, vol. 44, no. 11, p. 2171.

    Article  PubMed  Google Scholar 

  13. Lenroot, R.K. and Giedd, J.N., Brain development in children and adolescents: Insights from anatomical magnetic resonance imaging, Neurosci. Biobehav. Rev., 2006, vol. 30, no. 6, p. 718.

    Article  PubMed  Google Scholar 

  14. Razvitie mozga i formirovanie poznavatel’noi deyatel’nosti rebenka (Brain Development and the Formation of Cognitive Activity in Children), Farber, D.A. and Bezrukikh, M.M., Eds., Moscow: MPSI, 2009.

  15. Kolesov, D.V. and Sel’verova, N.B., Fiziologo-pedagogicheskie aspekty polovogo sozrevaniya (Physiological and Pedagogical Aspects of Puberty), Moscow, 1978.

    Google Scholar 

  16. Fiziologiya podrostka (Adolescent Physiology), Farber, D.A., Ed., Moscow: Pedagogika, 1988.

  17. Sisk, C. and Zehr, J., Pubertal hormones organize the adolescent brain and behavior, Front. Neuroendocrinol., 2005, vol. 26, nos. 3–4, p. 163.

    Article  CAS  PubMed  Google Scholar 

  18. Sowell, E.R., Trauner, D.A., Gamst, A., and Jernigan, T.L., Development of cortical and subcortical brain structures in childhood and adolescence: A structural MRI study, Dev. Med. Child Neurol., 2002, vol. 44, no. 1, p. 4.

    Article  PubMed  Google Scholar 

  19. Lebel, C., Walker, L., Leemans, A., et al., Microstructural maturation of the human brain from childhood to adulthood, Neuroimage, 2008, vol. 40, no. 3, p. 1044.

    Article  CAS  PubMed  Google Scholar 

  20. Toga, A.W., Thompson, P.M., and Sowell, E.R., Mapping brain maturation, Trends Neurosci, 2006, vol. 29, no. 3, p. 148.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  21. Huizinga, M., Dolan, C.V., and Molen, M.W., Agerelated change in executive function: Developmental trends and a latent variable analysis, Neuropsychologia, 2006, vol. 44, p. 2017.

    Article  PubMed  Google Scholar 

  22. Casey, B., Getz, S., and Galvan, A., The adolescents brain, Dev. Rev., 2008, vol. 28, no. 1, p. 62.

    Article  PubMed Central  PubMed  Google Scholar 

  23. Dubrovinskaya, N.V., Psychophysiological features of adolescents, Hum. Physiol., 2015, vol. 41, no. 2, p. 209.

    Article  Google Scholar 

  24. Fair, D.A., Bathula, D., Mills, K.L., et al., Maturing thalamokortical functional connectivity across development, Front. Syst. Neurosci., 2010, vol. 4, p. 10.

    PubMed Central  PubMed  Google Scholar 

  25. New Oxford American Dictionary, 2nd ed., New York: Oxford Univ. Press, 2005.

  26. Diamond, A., Normal development of prefrontal cortex from birth to young adulthood, Principles of Frontal Lobe Function, Stuss, D.T. and Knight, R.T., Eds., New York: Oxford Univ. Press, 2002, p. 466.

    Chapter  Google Scholar 

  27. Somerville, L., Hare, T., and Casey, B., Fronto-striatal maturation predicts cognitive control failure to appetitive cues in adolescents, J. Cogn.Neurosci., 2011, vol. 23, no. 9, p. 2323.

    Article  Google Scholar 

  28. Viggiano, M.R. and Kutas, M., The covert interplay between perception and memory: Event-related potential evidence, EEG Clin. Neurophysiol., 1998, vol. 108, p. 435.

    CAS  Google Scholar 

  29. Snodgrass, J.G. and Corwin, J., Perceptual identification thresholds for 150 fragmented pictures from the Snodgrass and Vanderwart picture set, Percept. Motor Skills, 1988, vol. 67, p. 3.

    Article  CAS  PubMed  Google Scholar 

  30. Farber, D.A., Machinskaya, R.I., Kurganskii, A.V., and Petrenko, N.E., Functional organization of the brain during the preparation to recognizing fragmentary images, Zh. Vyssh. Nervn. Deyat. im. I.P. Pavlova, 2014, vol. 64, no. 2, p. 190.

    CAS  Google Scholar 

  31. Kurganskii, A.V., Several problems of studying the cortex–cortex functional connections with the vector autoregression model of a multilead EEG, Zh. Vyssh. Nervn. Deyat. im. I.P. Pavlova, 2010, vol. 60, no. 6, p. 740.

    CAS  Google Scholar 

  32. Machinskaya, R.I. and Kurganskii, A.V., A comparative electrophysiological study of regulatory components of the working memory in adults and sevento eight-year-old children: Analysis of the EEG rhythm coherence, Hum. Physiol., 2012, vol. 38, no. 1, p. 1.

    Article  Google Scholar 

  33. Farber, D.A. and Petrenko, N.E., Voluntary selective attention and the efficiency of recognizing fragmentary images in children aged 10–11 years, Novye Issledovaniya, 2013, no. 3 (36), p. 5.

    Google Scholar 

  34. Donchin, E.A., Multivariate approach to the analysis of average evoked potentials, IFFE Transactions on BioMedical Engineering, 1966, vol. 13, no. 3, p. 132.

    Google Scholar 

  35. Machinskaya, R.I., Control brain systems and their morphological and functional maturation in children, Mozgovye mekhanizmy formirovaniya poznavatel’noi deyatel’nosti v predshkol’nom i mladshem shkol’nom vozraste (Brain Mechanisms of the Formation of Cognitive Activity in Preschool and Young Schoolchildren), Machinskaya, R.I. and Farber, D.A., Eds., Moscow: MPSU, 2014, p. 157.

    Google Scholar 

  36. Eshel, N., Nelson, E., Blair, J., et al., Neural substrates of choice selection in adults and adolescents: Development of ventrolateral and anterior cingulate cortices, Neuropsychologia, 2007, vol. 45, no. 6, p. 270.

    Article  Google Scholar 

  37. Petrides, M., Lateral prefrontal cortex: Architectonic and functional organization, Phil. Trans. R. Soc. London, B: Biol. Sci., 2005, vol. 360, no. 1456, p. 781.

    Article  Google Scholar 

  38. Ptak, R., The frontoparietal attention network of the human brain: Action, saliency, and a priority map of the environment, Neuroscientist, 2011, vol. 18, no. 5, p. 502.

    Article  PubMed  Google Scholar 

  39. Bressler, S.L., Tang, W., Sylvester, C.M., et al., Topdown control of human visual cortex by frontal and parietal cortex in anticipatory visual spatial attention, J. Neurosci., 2008, vol. 28, no. 40, p. 10056.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  40. Fuster, J.M., The prefrontal cortex—an update: Time is of the essence, Neuron, 2001, vol. 30, no. 2, p. 319.

    Article  CAS  PubMed  Google Scholar 

  41. Schulz, K., Molenda-Figueira, H., and Sisk, C., Back to the future: The organizational-activational hypothesis adapted to puberty and adolescents, Horm. Behav., 2009, vol. 55, no. 5, p. 597.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  42. Van Leijenhorst, L. and Gunther, Moor B., Op de Macks, Z., et al., Adolescent risky decision-making: Neurocognitive development of reward and control regions, Neuroimage, 2010, vol. 51, no. 1, p. 345.

    Article  PubMed  Google Scholar 

  43. Ernst, M., Daniele, T., and Frantz, K., New perspectives on adolescent motivated behavior: Attention and conditioning, Dev. Cogn. Neurosci., 2011, vol. 1, no. 4, p. 377.

    Article  PubMed Central  PubMed  Google Scholar 

  44. Viggiano, M.R. and Kutas, M., Overt and covert identification of fragmented objects inferred from performance and electrophysiological measures, J. Exp. Psychol.: General, 2000, vol. 129, no. 1, p. 107.

    Article  CAS  Google Scholar 

  45. Schendan, H.E. and Maher, S.M., Object knowledge during entry-level categorization is activated and modified by implicit memory after 200 ms, Neuroimage, 2009, vol. 44, no. 4, p. 1423.

    Article  PubMed  Google Scholar 

  46. Sowell, E.R., Thompson, P., Leonard, C., et al., Longitudinal mapping of cortical thickness and brain growth in normal children, J. Neurosci., 2004, vol. 24, no. 38, p. 8223.

    Article  CAS  PubMed  Google Scholar 

  47. Muftuler, L.T., Davis, E.P., Buss, C., et al., Cortical and subcortical changes in typically developing preadolescent children, Brain. Res, 2011, vol. 1399, p. 15.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  48. Doniger, G.M., Foxe, J.J., Schroeder, C.E., et al., Visual perceptual learning in human object recognition areas: A repetition priming study using high-density electrical mapping, Neuroimage, 2001, vol. 13, no. 2, p. 305.

    Article  CAS  PubMed  Google Scholar 

  49. Sehatpour, P., Molholm, S., Javitt, D.C., and Foxe, J.J., Spatiotemporal dynamics of human object recognition processing: An integrated high-density electrical mapping and functional imaging study of “closure” processes, NeuroImage, 2006, vol. 29, no. 2, p. 605.

    Article  PubMed  Google Scholar 

  50. Tsekhmistrenko, T.A., Vasil’eva, V.A., Shumeiko, N.S., and Chernykh, N.A., Structural reorganization of the human cortex and cerebellum in postnatal ontogeny, Razvitie mozga i formirovanie poznavatel’noi deyatel’nosti rebenka (Brain Development and the Formation of Cognitive Activity in Children), Farber, D.A. and Bezrukikh, M.M., Eds., Moscow: MPSI, 2009, p. 9.

    Google Scholar 

  51. Bar, M.A., Kassam, K.S., Ghuman, A.S., et al., Topdown facilitation of visual recognition, Proc. Natl. Acad. Sci. USA, 2006, vol. 103, no. 2, p. 449.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  52. Thatcher, R.W., North, D.M., and Biver, C.J., Development of cortical connections as measured by EEG coherence and phase delays, Hum. Brain. Mapp., 2008, vol. 29, no. 12, p. 1400.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Developmental Physiology, Russian Academy of Education, Moscow, Russia

    D. A. Farber, A. V. Kurganskii & N. E. Petrenko

Authors
  1. D. A. Farber
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. V. Kurganskii
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. N. E. Petrenko
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to D. A. Farber.

Additional information

Original Russian Text © D.A. Farber, A.V. Kurganskii, N.E. Petrenko, 2015, published in Fiziologiya Cheloveka, 2015, Vol. 41, No. 5, pp. 5–15.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Farber, D.A., Kurganskii, A.V. & Petrenko, N.E. Brain organization of the preparation to visual recognition in preadolescent children. Hum Physiol 41, 459–467 (2015). https://doi.org/10.1134/S0362119715050035

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0362119715050035

Keywords

Search

Navigation