MEG Source Localization Via Deep Learning
We present a deep learning solution to the problem of localization of magnetoencephalography (MEG) brain signals. The proposed deep model architectures are tuned to single and multiple time point MEG data, and can estimate varying numbers of dipole sources. Results from simulated MEG data on the cor...
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Format: | Article |
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Multidisciplinary Digital Publishing Institute
2021
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Online Access: | https://hdl.handle.net/1721.1/136674 |