Extended Data Fig. 10: Neural population activity patterns in other time windows.
From: Cortical preparatory activity indexes learned motor memories
a, PCs 1-4 during -100 to +100 ms from target onset (TO), -100 to +100 ms from go cue (GC), and -200 to +400 ms from movement onset (MOO). We applied PCA to trial-averaged neural activity for different reach directions in the before-learning and error-clamp blocks. Across all learning sessions in both monkeys, PC 1 explained 30 – 40% of the total variance, PC 2 explained 10 - 20%, PC 3 explained 8 - 10%, and PC 4 explained 6 - 8%. Neural trajectories in PCs 1-4 were bundled together around the target onset time window and diverged around the go cue time window (preparatory period). Error-clamp neural trajectories all shifted from their corresponding before-learning trajectories in PC 3. The time window −50 to +50 ms from go cue (grey shadow) we chose for preparatory neural state analysis was within the preparatory period and had stronger neural tuning than earlier time windows (e.g., the first 100 ms after target onset). Top left inset: color-coded reach directions. b, No significant neural repertoire change of baseline neural activity (before target onset on each trial) after learning the curl field. Black: no-learning control results (n = 36, 36). Red: learning results (n = 48, 36). One-sided Wilcoxon rank-sum test: monkey U, P = 0.999; monkey V, P = 0.595. c–i, Patterns of peri-movement neural population states. c, Peri-movement states of before-learning (color circles), learning (grey circles) and after-learning error-clamp (diamonds) reaches projected to PCs 1-3. After-learning states of the trained target and its nearby untrained targets left the before-learning states. One example session. d, Quantification of neural shift during learning along the ‘peri-movement shift axis’ that connected the before-learning and error-clamp states of the trained target, normalized against the distance between these two states. n = 4 (monkey U), 5 (monkey V). Cuzick’s test: monkey U, P = 0.032; monkey V, P = 3.92 x 10−5. e, The Euclidian distance between before-learning and after-learning peri-movement states showed bell-shaped local generalization. Error bars, s.e.m. across sessions (monkey U: n = 4, 3; monkey V: n = 5, 3). f, Peri-movement activity patterns showed significantly greater repertoire change for the trained target and near targets than far targets (monkey U: n = 28, 20; monkey V: n = 21, 15). Black: no-learning control sessions (n = 36 for both monkeys). One-sided Wilcoxon rank-sum test: monkey U, Pblack vs. blue = 0.26, Pblack vs. red = 4.52 x 10−6, Pblue vs. red = 0.002; monkey V, Pblack vs. blue = 3.70 x 10−7, Pblack vs. red = 6.02 x 10−9, Pblue vs. red = 5.29 x 10−4. g, Peri-movement states in the same PCA subspace during washout. h, Distance between washout and before-learning states decreased significantly along the peri-movement shift axis. Normalized against the distance between the before-learning and after-learning states of the trained target. n = 4 (monkey U), 5 (monkey V). Cuzick’s test: monkey U, P = 0.0077; monkey V, P = 0.0028. i, Pairwise dot products between peri-movement neural dimensions. PCs 1-3 significantly overlapped with the peri-movement shift (one-sided signed-rank test compared to 0: monkeys U + V, n = 9 and P = 0.002 for all comparisons). TDR 1 / 2 axes also significantly overlapped with the peri-movement shift (one-sided signed-rank test compared to 0: monkeys U + V, n = 18 and P = 1.07 x 10−4). For all the box plots, the central line indicates the median, the bottom and top edges indicate the 25th and 75th percentiles of the data, and the whiskers extend to the 5th and 95th percentiles of the data.
