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Brain Imaging and Behavior

, Volume 12, Issue 2, pp 303–308 | Cite as

Parieto-frontal gyrification and working memory in healthy adults

  • Sophie Green
  • Karen Blackmon
  • Thomas Thesen
  • Jonathan DuBois
  • Xiuyuan Wang
  • Eric Halgren
  • Orrin Devinsky
Original Research

Abstract

Gyrification of the cortical mantle is a dynamic process that increases with cortical surface area and decreases with age. Increased gyrification is associated with higher scores on cognitive tasks in adults; however, the degree to which this relationship is independent of cortical surface area remains undefined. This study investigates whether regional variation in gyrification is associated with domain-general and domain-specific cognition. Our hypothesis is that increased local gyrification confers a functional advantage that is independent of surface area. To quantify regional gyrification, we computed the local gyrification index (LGI) at each vertex and averaged across a bilateral parietal-frontal region associated with general intelligence and reasoning (Jung and Haier 2007). A sample of 48 healthy adults (24 males/24 females; ages 18–68 years) completed a high-resolution 3 T T1-weighted MRI and standardized administration of the Wechsler Adult Intelligence Scale (WAIS). We found a positive correlation between cortical gyrification and working memory, which remained significant after controlling for cortical surface area. Results suggest that a higher degree of local cortical folding confers a functional advantage that is independent from surface area and evident for more dynamic or “fluid” cognitive processes (i.e., working memory) rather than over-learned or “crystallized” cognitive processes.

Keywords

Cortical folding Neuroimaging Working memory Neuroanatomy Brain-structure function 

Notes

Compliance with ethical standards

Funding

The study was funded by generous support from Finding a Cure for Epilepsy and Seizures (FACES).

Conflict of interest

Sophie Green declares that she has no conflict of interest. Orrin Devinsky declares that he has no conflict of interest. Karen Blackmon declares that she has no conflict of interest. Jonathan DuBois declares that he has no conflict of interest. Xiuyuan Wang declares that he has no conflict of interest. Eric Halgren declares that he has no conflict of interest. Thomas Thesen declares that he has no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

References

  1. Allman, J. M. (1999). Evolving brains (pp. 116–156). New York: Freeman WH.Google Scholar
  2. Buzsáki, G. (2006). Rhythms of the brain (pp. 36–7). New York: Oxford UP.CrossRefGoogle Scholar
  3. Buzsáki, G., Geisler, C., Henze, D. A., & Wang, X. J. (2004). Interneuron diversity series: Circuit complexity and axon wiring economy of cortical interneurons. Trends in Neuroscience, 27, 186–193.CrossRefGoogle Scholar
  4. Cattell, R. B. (1963). Theory of fluid and crystallized intelligence: A critical experiment. Journal of Educational Psychology, 54(1), 1.CrossRefGoogle Scholar
  5. Dale, A. M., Fischl, B., & Sereno, M. I. (1999). Cortical surface-based analysis. I. Segmentation and surface reconstruction. Neuroimage, 9, 179–194.CrossRefPubMedGoogle Scholar
  6. Dobbing, J., & Sands, J. (1979). Comparative aspects of the brain growth spurt. Early Human Development, 311, 79–83.CrossRefGoogle Scholar
  7. Docherty, A. R., Hagler Jr., D. J., Panizzon, M. S., Neale, M. C., Eyler, L. T., Fennema-Notestine, C., et al. (2015). Does degree of gyrification underlie the phenotypic and genetic associations between cortical surface area and cognitive ability? NeuroImage, 106, 154–160.CrossRefPubMedGoogle Scholar
  8. Douglas, R. J., & Martin, K. A. C. (2004). Neuronal circuits of the neocortex. Annual Review of Neuroscience, 27, 419–451.CrossRefPubMedGoogle Scholar
  9. Finn, E. S., Shen, X., Scheinost, D., Rosenberg, M. D., Huang, J., Chun, M. M., Papademetris, X., & Constable, R. T. (2015). Functional connectome fingerprinting: Identifying individuals using patterns of brain connectivity. Nature Neuroscience, 18, 1664–1671.CrossRefPubMedPubMedCentralGoogle Scholar
  10. Fischl, B., & Dale, A. M. (2000). Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proceedings of the National Academy of Sciences, 97, 11050–11055.Google Scholar
  11. Fischl, B., van der Kouwe, A., Destrieux, C., Halgren, E., Ségonne, F., Salat, D. H., et al. (2004). Automatically parcellating the human cerebral cortex. Cerebral Cortex, 14, 11–22.CrossRefPubMedGoogle Scholar
  12. Gautam, P., Anstey, K. J., Wen, W., Sachdev, S. P., & Cherbuin, N. (2015). Cortical gyrification and its relationships with cortical volume, cortical thickness, and cognitive performance in healthy mid-life adults. Behavioral Brain Research, 287, 331–339.CrossRefGoogle Scholar
  13. Herculano-Houzel, S., Mota, B., & Lent, R. (2006). Cellular scaling rules for rodent brains. Proceedings of the National Academy of Sciences, 03(32), 12138–12143.CrossRefGoogle Scholar
  14. Herculano-Houzel, S., Collins, C. E., Wong, P., & Kaas, J. H. (2007). Cellular scaling rules for primate brains. Proceedings of the National Academy of Sciences, 104(9), 3562–3567.CrossRefGoogle Scholar
  15. Hof, P. R., Chanis, R., & Marino, L. (2005). Cortical complexity in cetacean brains. The anatomical record. Part A, Discoveries in molecular, cellular, and evolutionary biology, 287, 1142–1152.CrossRefGoogle Scholar
  16. Jung, R. H., & Haier, R. J. (2007). The parieto-frontal integration theory (P-FIT) of intelligence: Converging neuroimaging evidence. Behavioral Brain Science, 30, 135–154.CrossRefGoogle Scholar
  17. Kaas, J. H. (2009). Cerebral Fissure Patterns (pp. 739–800). Oxford: Elsevier.Google Scholar
  18. Larkum, M. E., Senn, W., & Lüscher, H.-R. (2004). Top-down dendritic input increases the gain of layer 5 pyramidal neurons. Cereral. Cortex, 14, 1059–1070.CrossRefGoogle Scholar
  19. Li, G., Wang, L., Shi, F., Lyall, A. E., Lin, W., Gilmore, J. H., & Shen, D. (2014). Mapping longitudinal development of local cortical gyrification in infants from birth to 2 years of age. Journal of Neuroscience, 34(12), 4228–4238.CrossRefPubMedPubMedCentralGoogle Scholar
  20. Luders, E., Narr, K. L., Bilder, R. M., Szeszko, P. R., Gurbani, M. N., Hamilton, L., et al. (2008). Mapping the relationship between cortical convolution and intelligence: Effects of gender. Cerebral Cortex, 18, 2019–2026.CrossRefPubMedGoogle Scholar
  21. Moore, M. J., Knowlton, A. R., Kraus, S., McLellan, W. A., & Bonde, R. K. (2004). Morphometry, gross morphology, and available histopathology in North Atlantic right whale (Eubalaena glacialis) mortalities. Journal of Cetacean Research and Management, 6, 199–214.Google Scholar
  22. Oldfield, R. C. (1971). The assessment and analysis of handedness: The Edinburgh inventory. Neuropsychologia, 1, 97–113.CrossRefGoogle Scholar
  23. Pillay, P., & Manger, P. R. (2007). Order-specific quantitative patterns of cortical gyrification. European Journal of Neuroscience, 25, 2705–2712.CrossRefPubMedGoogle Scholar
  24. Pucak, M., Levitt, J., Lund, J., & Lewis, D. (1996). Patterns of intrinsic and associational circuitry in monkey prefrontal cortex. Journal of Comparative Neruology, 376, 614–630.CrossRefGoogle Scholar
  25. Ronan, L., & Fletcher, P. C. (2015). From genes to folds: A review of cortical gyrificaiton theory. Brain Structure and Function, 220(5), 2475–2483.CrossRefPubMedGoogle Scholar
  26. Rubio-Garrido, P., Pérez-De-Manzo, F., Porrero, C., Galazo, M. J., & Clascá, F. (2009). Thalamic input to distal apical dendrites in neocortical layer 1 is massive and highly convergent. Cerebral Cortex, 19, 2380–2395.CrossRefPubMedGoogle Scholar
  27. Schaer, M., Caudra, M. B., Tamarit, L., Lazeyras, F., Eliez, S., & Thiran, J.-P. (2008). A surface-based approach to quantify local cortical gyrification. IEEE Transactions on Medical Imaging, 27, 161–170.CrossRefPubMedGoogle Scholar
  28. Schaftenaar, W., & Hildebrandt, T. (2006). Veterinary guidelines for reproduction-related management in captive female elephants. Elephant TAG Veterinary Advisors.Google Scholar
  29. Striedter, G. F., Srinivasan, S., & Monuki, E. S. (2015). Cortical folding: When, where, how and why? Annual Review of Neuroscience, 38, 291–307.CrossRefPubMedGoogle Scholar
  30. Van Essen, D. C. (1997). A tension-based theory of morphogenesis and compact wiring in the central nervous system. Nature, 385, 313–318.CrossRefPubMedGoogle Scholar
  31. Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of 'small-world' networks. Nature, 393, 440–442.CrossRefPubMedGoogle Scholar
  32. Wechsler, D. (1997). Wechsler Adult Intelligence Scale – third edition. San Antonio: Pearson.Google Scholar
  33. Wechsler, D. (2008). Wechsler Adult Intelligence Scale – fourth edition. San Antonio: Pearson.Google Scholar
  34. Welker, W. (1990). Why does the cerebral cortex fissure and fold? Cerebral Cortex, 8, 3–136.CrossRefGoogle Scholar
  35. Zilles, K., Armstrong, E., Schleicher, A., & Kretschmann, H. J. (1988). The human pattern of gyrification in the cerebral cortex. Anatomy and Embryology (Berlin), 179, 173–179.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Sophie Green
    • 1
    • 2
  • Karen Blackmon
    • 1
    • 3
  • Thomas Thesen
    • 1
    • 4
  • Jonathan DuBois
    • 5
  • Xiuyuan Wang
    • 1
  • Eric Halgren
    • 6
  • Orrin Devinsky
    • 1
  1. 1.Department of Neurology, Epilepsy DivisionNew York University School of MedicineNew YorkUSA
  2. 2.Florida Atlantic University, Charles E. Schmidt College of MedicineBoca RatonUSA
  3. 3.Department of Behavioral SciencesSt. George’s University School of MedicineWest IndiesGrenada
  4. 4.Department of RadiologyNew York University School of MedicineNew YorkUSA
  5. 5.Department of Neurology and Neurosurgery, Montreal Neurological InstituteMcGill UniversityQuebecCanada
  6. 6.Multimodal Imaging LaboratoryUniversity of California, San DiegoLa JollaUSA

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