Differential roles of sleep spindles and sleep slow oscillations in memory consolidation
Fig 7
The role of sleep spindles during two-sequence learning.
a) The model simulated transitions from awake to N2 sleep, to N3 sleep, and to awake again. Sequence training is the same as in Fig 3. b) The bar plots of performance for Seq1 and Seq2 during test sessions. Note significant increase in Seq2 performance after the sleep. Error bars indicate SEM. c) A characteristic example of sequence replay during slow oscillations. Note, that both Seq1 and Seq2 can be replayed during the same Up state of slow oscillation. d) The bar plots of the replay count for Seq1 and Seq2 during N2 (purple) and N3 (dark green) sleep. Error bars indicate SEM. Note that for both sequences number of correct order replays (“A1B1C1D1E1” for Seq1 and “E2D2C2B2A2” for Seq2) was higher than the number of reversed order replays. e) The change of synaptic weights relative to the initial values after N2 (right) and after subsequent N3 sleep (left). The synaptic change after training is the same as in 4j). The enough amount of sleep spindles enhanced synaptic connections associated with both sequences independently. f). The progressive increase in synaptic weights associated with Seq1 (red), Seq2 (magenta), and Seq2 alone (black). The patch error bar represents standard deviation. * p<0.05, ** p<0.01, *** p<0.001. N.S. represents no significant difference.