Functional connectivity analysis with voxel-based morphometry for diagnosis of mild cognitive impairment

JungHoe Kim, Jong-Hwan Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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).

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages306-313
Number of pages8
Volume7062 LNCS
EditionPART 1
DOIs
Publication statusPublished - 2011 Nov 28
Event18th International Conference on Neural Information Processing, ICONIP 2011 - Shanghai, China
Duration: 2011 Nov 132011 Nov 17

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume7062 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other18th International Conference on Neural Information Processing, ICONIP 2011
CountryChina
CityShanghai
Period11/11/1311/11/17

Fingerprint

Morphometry
Functional analysis
Voxel
Magnetic resonance
Seed
Brain
Connectivity
Chemical activation
Association reactions
Imaging techniques
Dementia
Pearson Correlation
Alzheimer's Disease
Functional Magnetic Resonance Imaging
Magnetic Resonance Imaging
Correlation coefficient
Activation

Keywords

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

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Kim, J., & Lee, J-H. (2011). Functional connectivity analysis with voxel-based morphometry for diagnosis of mild cognitive impairment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 1 ed., Vol. 7062 LNCS, pp. 306-313). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7062 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-24955-6_37

Functional connectivity analysis with voxel-based morphometry for diagnosis of mild cognitive impairment. / Kim, JungHoe; Lee, Jong-Hwan.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7062 LNCS PART 1. ed. 2011. p. 306-313 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7062 LNCS, No. PART 1).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kim, J & Lee, J-H 2011, Functional connectivity analysis with voxel-based morphometry for diagnosis of mild cognitive impairment. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 1 edn, vol. 7062 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 7062 LNCS, pp. 306-313, 18th International Conference on Neural Information Processing, ICONIP 2011, Shanghai, China, 11/11/13. https://doi.org/10.1007/978-3-642-24955-6_37
Kim J, Lee J-H. Functional connectivity analysis with voxel-based morphometry for diagnosis of mild cognitive impairment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 1 ed. Vol. 7062 LNCS. 2011. p. 306-313. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). https://doi.org/10.1007/978-3-642-24955-6_37
Kim, JungHoe ; Lee, Jong-Hwan. / Functional connectivity analysis with voxel-based morphometry for diagnosis of mild cognitive impairment. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7062 LNCS PART 1. ed. 2011. pp. 306-313 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).
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