Connectome-scale assessments of structural and functional connectivity in MCI.
Journal Article (Journal Article)
Mild cognitive impairment (MCI) has received increasing attention not only because of its potential as a precursor for Alzheimer's disease but also as a predictor of conversion to other neurodegenerative diseases. Although MCI has been defined clinically, accurate and efficient diagnosis is still challenging. Although neuroimaging techniques hold promise, compared to commonly used biomarkers including amyloid plaques, tau protein levels and brain tissue atrophy, neuroimaging biomarkers are less well validated. In this article, we propose a connectomes-scale assessment of structural and functional connectivity in MCI via two independent multimodal DTI/fMRI datasets. We first used DTI-derived structural profiles to explore and tailor the most common and consistent landmarks, then applied them in a whole-brain functional connectivity analysis. The next step fused the results from two independent datasets together and resulted in a set of functional connectomes with the most differentiation power, hence named as "connectome signatures." Our results indicate that these "connectome signatures" have significantly high MCI-vs-controls classification accuracy, at more than 95%. Interestingly, through functional meta-analysis, we found that the majority of "connectome signatures" are mainly derived from the interactions among different functional networks, for example, cognition-perception and cognition-action domains, rather than from within a single network. Our work provides support for using functional "connectome signatures" as neuroimaging biomarkers of MCI.
Full Text
Duke Authors
Cited Authors
- Zhu, D; Li, K; Terry, DP; Puente, AN; Wang, L; Shen, D; Miller, LS; Liu, T
Published Date
- July 2014
Published In
Volume / Issue
- 35 / 7
Start / End Page
- 2911 - 2923
PubMed ID
- 24123412
Pubmed Central ID
- PMC3969864
Electronic International Standard Serial Number (EISSN)
- 1097-0193
Digital Object Identifier (DOI)
- 10.1002/hbm.22373
Language
- eng
Conference Location
- United States