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Contextual MEG and EEG Source Estimates Using Spatiotemporal LSTM Networks
2021
Frontiers in Neuroscience
Most magneto- and electroencephalography (M/EEG) based source estimation techniques derive their estimates sample wise, independently across time. However, neuronal assemblies are intricately interconnected, constraining the temporal evolution of neural activity that is detected by MEG and EEG; the observed neural currents must thus be highly context dependent. Here, we use a network of Long Short-Term Memory (LSTM) cells where the input is a sequence of past source estimates and the output is
doi:10.3389/fnins.2021.552666
pmid:33767606
pmcid:PMC7985163
fatcat:bcgiequ4jfbdxnjfgvmzt6up3e