A recurrent neural network model of prefrontal brain activity during a working memory task
Fig 3
The geometry of the uncued item representations.
A. Visualisation of the pre- (left) and post-cue (right) geometry of the uncued memory items reported in [10]. Population activity patterns from macaque LPFC were averaged across the cued items and binned into 4 uncued colour categories (denoted by marker colours). Data from each delay period was plotted in reduced dimensionality space, degined by the first 3 PCs of the 8 location-colour pairs. Planes of best fit for each location shown as grey quadrilaterals. All conventions as described in Fig 2A. B. Hidden activity patterns for the uncued items, from two example models visualised in a 3-dimensional space. All conventions as in Fig 2B. C. Between-plane angles (θ, left) and phase alignment angles (ψ, right) between the two uncued colour planes in the post-cue delay. Individual models and population mean shown as transparent and opaque markers, respectively. D. Alignment index for the uncued subspaces in the pre- and post-cue delays. Note that prior to the presentation of the retro-cue, the coding format is location based. Therefore, the pre-cue data is the same as shown in Fig 2E. E. Visualisation of the cued and uncued memory items on trials where the upper location was cued reported in [10]. Population activity patterns from macaque LPFC were averaged across the uncued items to calculate the cued item representations, and across cued items for the uncued representations, prior to binning into 4 colour categories each. Data from each delay plotted in the reduced dimensionality space, corresponding to the first 3PCs. F. Visualisation of the hidden activity patterns for cued and uncued items in the post-cue delay, on trials where L1 was cued. Data from two example models. Note the plane for L2 is severely compressed and thus hard to see. G. Left: Angles θ (rectified) between cued and uncued planes in the post-cue delay, averaged across the two retro-cue locations. Values for individual models shown in grey, average across networks in black. Right: Complementary AI values between the cued and uncued subspaces, averaged across the two retro-cue locations. AI calculated for 2- and 3-dimensional subspaces. Black circles correspond to values for individual models, grey bars denote the means across all networks. H. Colour discriminability index (CDI) for the pre-cue subspaces (averaged across both locations, black circles) and cued and uncued subspaces in the post-cue delay (blue triangles and green crosses, respectively).