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High-Dimensional ICA Analysis Detects Within-Network Functional Connectivity Damage of Default-Mode and Sensory-Motor Networks in Alzheimer’s Disease
High-dimensional independent component analysis (ICA), compared to low-dimensional ICA, allows to conduct a detailed parcellation of the resting-state networks. The purpose of this study was to give further insight into functional connectivity (FC) in Alzheimer’s disease (AD) using high-dimensional...
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| 發表在: | Front Hum Neurosci |
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| Main Authors: | , , , , , |
| 格式: | Artigo |
| 語言: | Inglês |
| 出版: |
Frontiers Media S.A.
2015
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| 主題: | |
| 在線閱讀: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4315015/ https://ncbi.nlm.nih.gov/pubmed/25691865 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnhum.2015.00043 |
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