Brain Imaging and Behavior

, Volume 10, Issue 2, pp 517–523 | Cite as

Is the Alzheimer’s disease cortical thickness signature a biological marker for memory?

  • Edgar Busovaca
  • Molly E. Zimmerman
  • Irene B. Meier
  • Erica Y. Griffith
  • Stuart M. Grieve
  • Mayuresh S. Korgaonkar
  • Leanne M. Williams
  • Adam M. Brickman
Original Research


Recent work suggests that analysis of the cortical thickness in key brain regions can be used to identify individuals at greatest risk for development of Alzheimer’s disease (AD). It is unclear to what extent this “signature” is a biological marker of normal memory function – the primary cognitive domain affected by AD. We examined the relationship between the AD signature biomarker and memory functioning in a group of neurologically healthy young and older adults. Cortical thickness measurements and neuropsychological evaluations were obtained in 110 adults (age range 21–78, mean = 46) drawn from the Brain Resource International Database. The cohort was divided into young adult (n = 64, age 21–50) and older adult (n = 46, age 51–78) groups. Cortical thickness analysis was performed with FreeSurfer, and the average cortical thickness extracted from the eight regions that comprise the AD signature. Mean AD-signature cortical thickness was positively associated with performance on the delayed free recall trial of a list learning task and this relationship did not differ between younger and older adults. Mean AD-signature cortical thickness was not associated with performance on a test of psychomotor speed, as a control task, in either group. The results suggest that the AD signature cortical thickness is a marker for memory functioning across the adult lifespan.


Alzheimer’s Disease Cortical thickness Structural MRI Neuropsychology Memory 



We acknowledge the data and support provided by BRAINnet;, under the governance of the BRAINnet Foundation. BRAINnet is the scientific network that coordinates access to the Brain Resource International Database for independent scientific purposes. We also thank the individuals who gave their time to participate in the database. This research was approved by local ethics committees. SMG acknowledges the Sydney Medical School Foundation for support.


Dr. Grieve previously received consulting fees from Brain Resource Ltd.

Dr. Williams previously received consulting fees and stock options from Brain Resource Ltd.

Mr. Busovaca, Dr. Zimmerman, Ms. Meier, Ms. Griffith, and Dr. Korgaonkar declare that they do not have financial and personal relationships that might bias this work.

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, and the applicable revisions at the time of the investigation. Informed consent was obtained from all patients for being included in the study.


  1. Arnaiz, E., & Almkvist, O. (2003). Neuropsychological features of mild cognitive impairment and preclinical Alzheimer’s disease. Acta Neurologica Scandinavica. Supplementum, 179, 34–41.CrossRefPubMedGoogle Scholar
  2. Bakkour, A., Morris, J. C., & Dickerson, B. C. (2009). The cortical signature of prodromal AD: regional thinning predicts mild AD dementia. Neurology, 72(12), 1048–1055.CrossRefPubMedPubMedCentralGoogle Scholar
  3. Bakkour, A., Morris, J. C., Wolk, D. A., & Dickerson, B. C. (2013). The effects of aging and Alzheimer’s disease on cerebral cortical anatomy: specificity and differential relationships with cognition. NeuroImage, 76, 332–344. doi: 10.1016/j.neuroimage.2013.02.059.CrossRefPubMedPubMedCentralGoogle Scholar
  4. Braak, H., & Braak, E. (1991). Neuropathological stageing of Alzheimer-related changes. Acta Neuropathologica, 82(4), 239–259.CrossRefPubMedGoogle Scholar
  5. Brickman, A. M., Meier, I. B., Korgaonkar, M. S., Provenzano, F. A., Grieve, S. M., Siedlecki, K. L., & Zimmerman, M. E. (2012). Testing the white matter retrogenesis hypothesis of cognitive aging. Neurobiology of Aging, 33(8), 1699–1715. doi: 10.1016/j.neurobiolaging.2011.06.001.CrossRefPubMedGoogle Scholar
  6. Brun, A., & Gustafson, L. (1976). Distribution of cerebral degeneration in Alzheimer’s disease. A clinico-pathological study. Archiv für Psychiatrie und Nervenkrankheiten, 223(1), 15–33.CrossRefPubMedGoogle Scholar
  7. Burns, A., Byrne, E. J., & Maurer, K. (2002). Alzheimer’s disease. Lancet, 360(9327), 163–165. doi: 10.1016/S0140-6736(02)09420-5.CrossRefPubMedGoogle Scholar
  8. Clark, C. R., Paul, R. H., Williams, L. M., Arns, M., Fallahpour, K., Handmer, C., & Gordon, E. (2006). Standardized assessment of cognitive functioning during development and aging using an automated touchscreen battery. Archives of Clinical Neuropsychology, 21(5), 449–467.CrossRefPubMedGoogle Scholar
  9. Cosentino, S. A., Brickman, A. M., & Manly, J. J. (2011). Neuropsychological assessment of the dementias of late life. In K. W. Schaie & S. L. Willis (Eds.), Handbook of the psychology of aging (7th ed., pp. 339–352). London: Academic.CrossRefGoogle Scholar
  10. Dale, A. M., Fischl, B., & Sereno, M. I. (1999). Cortical surface-based analysis. I. Segmentation and surface reconstruction. NeuroImage, 9(2), 179–194.CrossRefPubMedGoogle Scholar
  11. Desikan, R. S., Segonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., & Killiany, R. J. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage, 31(3), 968–980. doi: 10.1016/j.neuroimage.2006.01.021.CrossRefPubMedGoogle Scholar
  12. Dickerson, B. C., Goncharova, I., Sullivan, M. P., Forchetti, C., Wilson, R. S., Bennett, D. A., & deToledo-Morrell, L. (2001). MRI-derived entorhinal and hippocampal atrophy in incipient and very mild Alzheimer’s disease. Neurobiology of Aging, 22(5), 747–754.CrossRefPubMedGoogle Scholar
  13. Dickerson, B. C., Bakkour, A., Salat, D. H., Feczko, E., Pacheco, J., Greve, D. N., & Buckner, R. L. (2009). The cortical signature of Alzheimer’s disease: regionally specific cortical thinning relates to symptom severity in very mild to mild AD dementia and is detectable in asymptomatic amyloid-positive individuals. Cerebral Cortex, 19(3), 497–510. doi: 10.1093/cercor/bhn113.CrossRefPubMedGoogle Scholar
  14. Dickerson, B. C., Stoub, T. R., Shah, R. C., Sperling, R. A., Killiany, R. J., Albert, M. S., & Detoledo-Morrell, L. (2011). Alzheimer-signature MRI biomarker predicts AD dementia in cognitively normal adults. Neurology, 76(16), 1395–1402. doi: 10.1212/WNL.0b013e3182166e96.CrossRefPubMedPubMedCentralGoogle Scholar
  15. 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 of the United States of America, 97(20), 11050–11055.CrossRefPubMedPubMedCentralGoogle Scholar
  16. Fischl, B., Sereno, M. I., & Dale, A. M. (1999). Cortical surface-based analysis. II: inflation, flattening, and a surface-based coordinate system. NeuroImage, 9(2), 195–207.CrossRefPubMedGoogle Scholar
  17. Fischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., & Dale, A. M. (2002). Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron, 33(3), 341–355.CrossRefPubMedGoogle Scholar
  18. Flicker, C., Ferris, S. H., & Reisberg, B. (1991). Mild cognitive impairment in the elderly: predictors of dementia. Neurology, 41(7), 1006–1009.CrossRefPubMedGoogle Scholar
  19. Forstl, H., & Kurz, A. (1999). Clinical features of Alzheimer’s disease. European Archives of Psychiatry and Clinical Neuroscience, 249(6), 288–290.CrossRefPubMedGoogle Scholar
  20. Gordon, E., Cooper, N., Rennie, C., Hermens, D., & Williams, L. M. (2005). Integrative neuroscience: the role of a standardized database. Clinical EEG and Neuroscience, 36(2), 64–75.CrossRefPubMedGoogle Scholar
  21. Grieve, S. M., Clark, C. R., Williams, L. M., Peduto, A. J., & Gordon, E. (2005). Preservation of limbic and paralimbic structures in aging. Human Brain Mapping, 25(4), 391–401. doi: 10.1002/hbm.20115.CrossRefPubMedGoogle Scholar
  22. Grieve, S. M., Korgaonkar, M. S., Clark, C. R., & Williams, L. M. (2011). Regional heterogeneity in limbic maturational changes: evidence from integrating cortical thickness, volumetric and diffusion tensor imaging measures. NeuroImage, 55(3), 868–879. doi: 10.1016/j.neuroimage.2010.12.087.CrossRefPubMedGoogle Scholar
  23. Hickie, I. B., Davenport, T. A., Naismith, S. L., & Scott, E. M. (2001). SPHERE: a national depression project. SPHERE National Secretariat. The Medical Journal of Australia, 175(Suppl), S4-5.PubMedGoogle Scholar
  24. Jacobs, D. M., Sano, M., Dooneief, G., Marder, K., Bell, K. L., & Stern, Y. (1995). Neuropsychological detection and characterization of preclinical Alzheimer’s disease. Neurology, 45(5), 957–962.CrossRefPubMedGoogle Scholar
  25. Lerch, J. P., Pruessner, J. C., Zijdenbos, A., Hampel, H., Teipel, S. J., & Evans, A. C. (2005). Focal decline of cortical thickness in Alzheimer’s disease identified by computational neuroanatomy. Cerebral Cortex, 15(7), 995–1001. doi: 10.1093/cercor/bhh200.CrossRefPubMedGoogle Scholar
  26. Paul, R. H., Lawrence, J., Williams, L. M., Richard, C. C., Cooper, N., & Gordon, E. (2005). Preliminary validity of “integneuro”: a new computerized battery of neurocognitive tests. The International Journal of Neuroscience, 115(11), 1549–1567. doi: 10.1080/00207450590957890.CrossRefPubMedGoogle Scholar
  27. Rolls, E. T. (2000). Memory systems in the brain. Annual Review of Psychology, 51, 599–630. doi: 10.1146/annurev.psych.51.1.599.CrossRefPubMedGoogle Scholar
  28. Silverstein, S. M., Jaeger, J., Donovan-Lepore, A. M., Wilkniss, S. M., Savitz, A., Malinovsky, I., & Dent, G. (2010). A comparative study of the MATRICS and IntegNeuro cognitive assessment batteries. Journal of Clinical and Experimental Neuropsychology, 32(9), 937–952. doi: 10.1080/13803391003596496.CrossRefPubMedGoogle Scholar
  29. Squire, L. R., & Kowlton, B. J. (1999). The medial temporal lobe, the hippcomapus, and the memory systems of the brain. In M. S. Gazzaniga (Ed.), The new cognitive neurosciences. Cambridge: The MIT Press.Google Scholar
  30. Squire, L. R., & Zola-Morgan, S. (1991). The medial temporal lobe memory system. Science, 253(5026), 1380–1386.CrossRefPubMedGoogle Scholar
  31. Troster, A. I., Butters, N., Salmon, D. P., Cullum, C. M., Jacobs, D., Brandt, J., & White, R. F. (1993). The diagnostic utility of savings scores: differentiating Alzheimer’s and huntington’s diseases with the logical memory and visual reproduction tests. Journal of Clinical and Experimental Neuropsychology, 15(5), 773–788. doi: 10.1080/01688639308402595.CrossRefPubMedGoogle Scholar
  32. Williams, L. M., Simms, E., Clark, C. R., Paul, R. H., Rowe, D., & Gordon, E. (2005). The test-retest reliability of a standardized neurocognitive and neurophysiological test battery: “neuromarker”. The International Journal of Neuroscience, 115(12), 1605–1630. doi: 10.1080/00207450590958475.CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Edgar Busovaca
    • 1
  • Molly E. Zimmerman
    • 2
    • 3
  • Irene B. Meier
    • 1
  • Erica Y. Griffith
    • 1
  • Stuart M. Grieve
    • 4
    • 5
    • 6
  • Mayuresh S. Korgaonkar
    • 4
    • 5
    • 6
  • Leanne M. Williams
    • 7
    • 8
  • Adam M. Brickman
    • 1
  1. 1.Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Department of Neurology, College of Physicians and SurgeonsColumbia UniversityNew YorkUSA
  2. 2.Department of PsychologyFordham UniversityBronxUSA
  3. 3.Department of NeurologyAlbert Einstein College of MedicineBronxUSA
  4. 4.Sydney Translational Imaging Laboratory, Sydney Medical SchoolUniversity of SydneySydneyAustralia
  5. 5.Brain Dynamics CentreWestmead Millennium InstituteWestmeadAustralia
  6. 6.Sydney Medical SchoolWestmeadAustralia
  7. 7.Department of Psychiatry and Behavioral SciencesStanford UniversityStanfordUSA
  8. 8.Sierra-Pacific Mental Illness Research, EducationClinical Center (MIRECC) Veterans Affairs Palo Alto Health Care SystemPalo AltoUSA

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