Name
Title | ||
|---|---|---|
Group sparse dictionary learning and inference for resting-state fMRI analysis of Alzheimer'S disease |
Abstract | ||
|---|---|---|
A novel group analysis tool for data-driven resting state fMRI analysis using group sparse dictionary learning and mixed model is presented along with the promising indications of Alzheimer's disease progression. Instead of using independency assumption as in popular ICA approaches, the proposed approach is based on the sparse graph assumption such that a temporal dynamics at each voxel position is a sparse combination of global brain dynamics. In estimating the unknown global dynamics and local network structures, we perform sparse dictionary learning for the concatenated temporal data across the subjects by constraining that the network structures within a group are similar. Under the homoscedasticity variance assumption across subjects and groups, we show that the mixed model group inference can be easily performed using second level GLM with summary statistics. Using extensive resting fMRI data set obtained from normal, Mild Cognitive Impairment (MCI), Clinical Dementia Rating scale (CDR) 0.5, CDR 1.0, and CDR 2.0 of Alzheimer's disease patients groups, we demonstrated that the changes of default mode network extracted by the proposed method is more closely correlated with the progression of Alzheimer's disease. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ISBI.2013.6556531 | ISBI |
Keywords | Field | DocType |
cognition,extensive resting fmri data set,summary statistics,group sparse dictionary learning,diseases,alzheimer's disease,statistics,neurophysiology,ica approach,default mode network,resting state fmri,echo planar imaging sequence,resting-state fmri analysis,inference,second level glm,biomedical mri,homoscedasticity variance assumption,image sequences,sparse graph assumption,sparse dictionary learning,clinical dementia rating scale,brain,concatenated temporal data,alzheimer disease progression,mixed model,global brain dynamics,mild cognitive impairment,medical image processing,dictionaries,indexes,analysis of variance | Voxel,Clinical Dementia Rating,Default mode network,Pattern recognition,Inference,Computer science,Homoscedasticity,Resting state fMRI,Speech recognition,Temporal database,Artificial intelligence,Group analysis | Conference |
ISSN | ISBN | Citations |
1945-7928 | 978-1-4673-6456-0 | 5 |
PageRank | References | Authors |
0.47 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jeonghyeon Lee | 1 | 8 | 1.24 |
| Yong Jeong | 2 | 57 | 5.68 |
| Jong Chul Ye | 3 | 715 | 79.99 |