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Found 2 papers, 1 papers with code
Identifying Functional Brain Networks of Spatiotemporal Wide-Field Calcium Imaging Data via a Long Short-Term Memory Autoencoder
The goal of this study is to elucidate and illustrate, qualitatively and quantitatively, the FBNs identified by use of the LSTM-AER method and compare them to those from traditional SBC and ICA.
Attention-Based CNN-BiLSTM for Sleep State Classification of Spatiotemporal Wide-Field Calcium Imaging Data
Comparison with Existing Method: On a 3-hour WFCI recording, the CNN-BiLSTM achieved a kappa of 0. 67, comparable to a kappa of 0. 65 corresponding to the human EEG/EMG-based scoring.
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