Brain State Decoding Based on fMRI Using Semisupervised Sparse Representation Classifications
Multivariate classification techniques have been widely applied to decode brain states using functional magnetic resonance imaging (fMRI). Due to variabilities in fMRI data and the limitation of the collection of human fMRI data, it is not easy to train an efficient and robust supervised-learning cl...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2018-01-01
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| Series: | Computational Intelligence and Neuroscience |
| Online Access: | http://dx.doi.org/10.1155/2018/3956536 |