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Functional Connectivity Analysis with Voxel-Based Morphometry for Diagnosis of Mild Cognitive Impairment

  • JungHoe Kim
  • Jong-Hwan Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7062)

Abstract

The cortical atrophy measured from the magnetic resonance imaging (MRI) data along with aberrant neuronal activation patterns from the functional MRI data have been implicated in the mild cognitive impairment (MCI), which is a potential early form of a dementia. The association between the level of cortical atrophy in the gray matter (GM) and corresponding degree of neuronal connectivity, however, has not systematically been presented. In this study, we aimed to provide anecdotal evidence that there would be a close link between the anatomical abnormality and corresponding functional aberrance associated with the neuropsychiatric condition (i.e. MCI). Firstly, the voxel-based morphometry (VBM) analysis identified the medial temporal lobe and inferior parietal lobule as the regions with substantially decreased (i.e. atrophy) and increased GM concentrations, respectively. In the subsequent functional connectivity (FC) analysis via Pearson’s correlation coefficients, the FC patterns using the regions with a decreased GM concentration showed increased FC patterns (i.e. hyper-connectivity) associated with the MCI. On the other hand, the FC patterns using the seed regions with an increased GM concentration have shown decreased FC (i.e. hypo-connectivity) with the MCI in the task anti-correlated regions including superior frontal gyrus (i.e. task-negative networks or default-mode networks). These results provide a supplemental information that there may be an compensatory mechanism in the human brain function, which potentially allow to diagnose early phase of the neuropsychiatric illnesses including the Alzheimer’s diseases (AD).

Keywords

Functional magnetic resonance imaging mild cognitive impairment voxel-based morphometry functional connectivity dementia 

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References

  1. 1.
    Dickerson, B.C., Sperling, R.A.: Functional Abnormalities of the Medial Temporal Lobe Memory System in Mild Cognitive Impairment and Alzheimer’s Disease: Insights from Functional MRI Studies. Neuropsychologia 46(6), 1624–1635 (2008)CrossRefGoogle Scholar
  2. 2.
    Fan, Y., Resnick, S.M., Wu, X., Davatzikos, C.: Structural and Functional Biomarkers of Prodromal Alzheimer’s Disease: a High-dimensional Pattern Classification Study. Neuroimage 41(2), 277–285 (2008)CrossRefGoogle Scholar
  3. 3.
    Buckner, R.L., Snyder, A.Z., Sanders, A.L., Raichle, M.E., Morris, J.C.: Functional Brain Imaging of Young, Nondemented, and Demented Older Adults. J. Cogn. Neurosci. 12(suppl.2), 24–34 (2000)CrossRefGoogle Scholar
  4. 4.
    Greicius, M.D., Srivastava, G., Reiss, A.L., Menon, V.: Default-mode Network Activity Distinguishes Alzheimer’s Disease from Healthy Aging: Evidence from Functional MRI. Proc. Natl. Acad. Sci. U S A 101(13), 4637–4642 (2004)CrossRefGoogle Scholar
  5. 5.
    Wang, K., Liang, M., Wang, L., Tian, L., Zhang, X., Li, K., Jiang, T.: Altered Functional Connectivity in Early Alzheimer’s Disease: a Resting-state fMRI Study. Hum. Brain Mapp. 28(10), 967–978 (2007)CrossRefGoogle Scholar
  6. 6.
    Ashburner, J., Friston, K.: Voxel-based Morphometry—the Methods. Neuroimage 11, 805–821 (2000)CrossRefGoogle Scholar
  7. 7.
    Mak, H.K., Zhang, Z., Yau, K.K., Zhang, L., Chan, Q., Chu, L.W.: Efficacy of Voxel-based Morphometry with DARTEL and Standard Registration as Imaging Biomarkers in Alzheimer’s Disease Patients and Cognitively Normal Older Adults at 3.0 Tesla MR Imaging. J. Alzheimers Dis. 23(4), 655–664 (2011)Google Scholar
  8. 8.
    Gili, T., Cercignani, M., Serra, L., Perri, R., Giove, F., Maraviglia, B., Caltagirone, C., Bozzali, M.: Regional Brain Atrophy and Functional Disconnection across Alzheimer’s Disease Evolution. J. Neurol. Neurosurg. Psychiatry 82(1), 58–66 (2011)CrossRefGoogle Scholar
  9. 9.
    Huettel, S.A., Song, A.W., McCarthy, G.: Functional Magnetic Resonance Imaging, 2nd edn. Sinauer Associates, Inc., Sunderland (2009)Google Scholar
  10. 10.
    Rytsar, R., Fornari, E., Frackowiak, R.S., Ghika, J.A., Knyazeva, M.G.: Inhibition in Early Alzheimer’s Disease: An fMRI-based Study of Effective Connectivity. Neuroimage (2011) Epub ahead of print Google Scholar
  11. 11.
    Seth, A.K.: A MATLAB Toolbox for Granger Causal Connectivity Analysis. J. Neurosci. Methods 186, 262–273 (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • JungHoe Kim
    • 1
  • Jong-Hwan Lee
    • 1
  1. 1.Department of Brain and Cognitive EngineeringKorea UniversitySeoulRepublic of Korea

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