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Priority-based transformations of stimulus representation in visual working memory
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Description: We investigate how working memory representations transform with priority status via human subjects (EEG) and RNNs performing a 2-back task.
'dpca_code_V2' folder contains python notebooks (I used Google Colab) for RNN training, data analysis and plotting.
- '2back_rnn_train.ipynb' trains and tests 7-unit and 60-unit RNNs (with circular input) and plots the PCA projections shown in Figure 4.
- 'dpca_timecourse.ipynb' plots timecourses of dPCA projection of stimulus means, and timecourses of scalar transform, for both RNN and EEG (Figures …
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