Advertisement

Data and Information Granule Rules Retrieval: Differences of Activation in Parietal Cortex

  • Wei Zhao
  • Hongyu Li
  • Gue Gu
  • Xiuzhen Wang
  • Guohui Zhou
  • Jiaxin Cui
  • Weiquan Gu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8609)

Abstract

Efficient encoding of Roman rules is based on the neural bases of mathematical cognitive abilities. The present imaging studies have shown that information granule representing a form of Roman rules is associated with arithmetical domain-sensitive parietal cortex, indicating a switch from the data to the information granule retrieval of memory rules. So far, however, little is known about the developing neural substrate for the establishment of rules from data to information granule. The aim of the present fMRI study is to investigate whether and how mathematical intelligence might be enhanced from data to information granule of Roman arithmetic rules in the parietal cortex. Concerning the same rules, the paired t-test analysis indicated that different activation in the bilateral parietal lobule associated with different retrieval levels. In conclusion, the present study yielded some evidence that a successful model for knowledge-building of rules is accompanied by modifications of brain activation patterns.

Keywords

data information granule experiential knowledge parietal lobule mathematical intelligence 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Pedrycz, W.: Knowledge-based clustering: from data to information granules. Wiley Interscience (2005)Google Scholar
  2. 2.
    Schoenfeld, A.H., Herrmann, D.J.: Problem perception and knowledge structure in expert and novice mathematical problem solvers. J. Exp. Psychol. Learn. Mem. Cogn. 8, 484 (1982)CrossRefGoogle Scholar
  3. 3.
    Kolb, D.A.: Experimental learning. Experience as the source of learning and development. Prentice-Hall, New Jersey (1984)Google Scholar
  4. 4.
    Baroody, A.J., Dowker, A.: The development of arithmetic concepts and skills: Constructive adaptive expertise. Routledge (2013)Google Scholar
  5. 5.
    Price, G.R., Mazzocco, M.M., Ansari, D.: Why mental arithmetic counts: brain activation during single digit arithmetic predicts high school math scores. J. Neurosci. 33, 156–163 (2013)CrossRefGoogle Scholar
  6. 6.
    Ischebeck, A., Zamarian, L., Schocke, M., Delazer, M.: Flexible transfer of knowledge in mental arithmetic–an fMRI study. Neuroimage 44, 1103–1112 (2009)CrossRefGoogle Scholar
  7. 7.
    Dehaene, S., Piazza, M., Pinel, P., Cohen, L.: Three parietal circuits for number processing. Cogn. Neuropsychol. 20, 487–506 (2003)CrossRefGoogle Scholar
  8. 8.
    Simon, O., Mangin, J.-F., Cohen, L., Le Bihan, D., Dehaene, S.: Topographical layout of hand, eye, calculation, and language-related areas in the human parietal lobe. Neuron 33, 475–487 (2002)CrossRefGoogle Scholar
  9. 9.
    Sandrini, M., Rossini, P.M., Miniussi, C.: The differential involvement of inferior parietal lobule in number comparison: a rTMS study. Neuropsychologia 42, 1902–1909 (2004)CrossRefGoogle Scholar
  10. 10.
    Goel, V., Dolan, R.J.: Explaining modulation of reasoning by belief. Cognition 87, B11–B22 (2003)Google Scholar
  11. 11.
    Wagner, A.D., Shannon, B.J., Kahn, I., Buckner, R.L.: Parietal lobe contributions to episodic memory retrieval. Trends in Cog. Sci. 9, 445–453 (2005)CrossRefGoogle Scholar
  12. 12.
    Masataka, N., Ohnishi, T., Imabayashi, E., Hirakata, M., Matsuda, H.: Neural correlates for learning to read Roman numerals. Brain Lang 100, 276–282 (2007)CrossRefGoogle Scholar
  13. 13.
    Ashburner, J., Friston, K.J.: Unified segmentation. Neuroimage 26, 839–851 (2005)CrossRefGoogle Scholar
  14. 14.
    Harvey, B., Klein, B., Petridou, N., Dumoulin, S.: Topographic representation of numerosity in the human parietal cortex. Science 341, 1123–1126 (2013)CrossRefGoogle Scholar
  15. 15.
    Henson, R.N., Rugg, M., Shallice, T., Josephs, O., Dolan, R.: Recollection and familiarity in recognition memory: an event-related functional magnetic resonance imaging study. J. Neurosci. 19, 3962–3972 (1999)Google Scholar
  16. 16.
    Arsalidou, M., Taylor, M.J.: Is 2+ 2= 4? Meta-analyses of brain areas needed for numbers and calculations. NeuroImage 54, 2382–2393 (2011)CrossRefGoogle Scholar
  17. 17.
    Delazer, M., Ischebeck, A., Domahs, F., Zamarian, L., Koppelstaetter, F., Siedentopf, C.M., Kaufmann, L., Benke, T., Felber, S.: Learning by strategies and learning by drill—Evidence from an fMRI study. NeuroImage 25, 838–849 (2005)CrossRefGoogle Scholar
  18. 18.
    Matejko, A.A., Price, G.R., Mazzocco, M.M.M., Ansari, D.: Individual differences in left parietal white matter predict math scores on the Preliminary Scholastic Aptitude Test. NeuroImage 66, 604–610 (2013)CrossRefGoogle Scholar
  19. 19.
    Simon, O., Mangin, J.F., Cohen, L., Le Bihan, D., Dehaene, S.: Topographical Layout of Hand, Eye, Calculation, and Language-Related Areas in the Human Parietal Lobe. Neuron 33, 475–487 (2002)CrossRefGoogle Scholar
  20. 20.
    Newman, S.D., Carpenter, P.A., Varma, S., Just, M.A.: Frontal and parietal participation in problem solving in the Tower of London: fMRI and computational modeling of planning and high-level perception. Neuropsychologia 41, 1668–1682 (2003)CrossRefGoogle Scholar
  21. 21.
    Fletcher, P.C., Frith, C.D., Baker, S.C., Shallice, T., Frackowiak, R.S.J., Dolan, R.J.: The mind’s eye—precuneus activation in memory-related imagery. Neuroimage 2, 195–200 (1995)CrossRefGoogle Scholar
  22. 22.
    Cavanna, A.E., Trimble, M.R.: The precuneus: a review of its functional anatomy and behavioural correlates. Brain 129, 564–583 (2006)CrossRefGoogle Scholar
  23. 23.
    Kelley, W.M., Macrae, C.N., Wyland, C.L., Caglar, S., Inati, S., Heatherton, T.F.: Finding the self? An event-related fMRI study. J. Cogn. Neurosci. 14, 785–794 (2002)CrossRefGoogle Scholar
  24. 24.
    Dehaene, S., Cohen, L.: Cerebral pathways for calculation: Double dissociation between rote verbal and quantitative knowledge of arithmetic. Cortex 33, 219–250 (1997)CrossRefGoogle Scholar
  25. 25.
    Takayama, Y., Sugishita, M., Akiguchi, I., Kimura, J.: Isolated acalculia due to left parietal lesion. Arch. Neurol. 51, 286 (1994)CrossRefGoogle Scholar
  26. 26.
    Baldo, J.V., Dronkers, N.F.: Neural correlates of arithmetic and language comprehension: A common substrate? Neuropsychologia 45, 229–235 (2007)CrossRefGoogle Scholar
  27. 27.
    Iwamura, Y.: Somatosensory association cortices. International Congress Series, 3–14 (2003)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Wei Zhao
    • 1
  • Hongyu Li
    • 1
  • Gue Gu
    • 2
  • Xiuzhen Wang
    • 1
  • Guohui Zhou
    • 1
  • Jiaxin Cui
    • 3
    • 4
  • Weiquan Gu
    • 5
  1. 1.College of Computer Science and Information EngineeringHarbin Normal UniversityHarbinChina
  2. 2.Software CollegeNortheast Agricultural UniversityHarbinChina
  3. 3.State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern, Institute for Brain ResearchBeijing Normal UniversityBeijingChina
  4. 4.Center for Collaboration and Innovation in Brain and Learning SciencesBeijing Normal UniversityBeijingChina
  5. 5.Harbin Normal UniversityHarbinChina

Personalised recommendations