A recurrent neural network model of prefrontal brain activity during a working memory task
Fig 6
A. Cross-temporal generalisation scores for decoders trained to discriminate between colour pairs. Data has been averaged across all trained networks. Black lines indicate the junctions between task events–stimulus presentation, pre-cue delay, retro-cue, and post-cue delay. Left: Average scores for models trained with a fixed-length delay interval. Right: analogous plot for models trained with variable delay lengths. Note that the networks show a stable (cross-generalisable) memory code between the 10 and 16 cycle mark, which covers the range of temporal variability experienced during training (with the post-cue delay starting at the 10 cycle mark and lasting until between the 11 and 18 cycle marks). B. Boxplots showing the distribution of mean cross-temporal decoding accuracy scores, averaged across the two memory delays, for all models. Variable delay interval length condition shown on the left in green, fixed delay length condition on the right in sand. Asterisks denote the results of the one-sided one-sample t-tests against the chance (50%) decoding level, *** corresponds to p < .001. C.-D. Plane angles θ between the cued subspaces in the pre- and post-cue delay periods, respectively. E. Phase alignment angles ψ between the cued subspaces in the post-cue delay.