Estimating effective connectivity from fMRI data using factor-based subspace autoregressive models
We consider the problem of identifying large-scale effective connectivity of brain networks from fMRI data. Standard vector autoregressive (VAR) models fail to estimate reliably networks with large number of nodes. We propose a new method based on factor modeling for reliable and efficient high-dime...
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| 主要な著者: | , , , |
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| フォーマット: | 論文 |
| 出版事項: |
Institute of Electrical and Electronics Engineers (IEEE)
2015
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| 主題: | |
| オンライン･アクセス: | http://eprints.utm.my/id/eprint/52734/ http://dx.doi.org/10.1109/LSP.2014.2365634 |
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