Abstract:

Implicit learning is integral to human cognition. It occurs during the learning phase (online periods) and the offline interval after the learning phase (offline periods). The process during the offline periods is referred to as consolidation, which means stabilization or enhancement of a memory trace even without additional practice after the initial acquisition. Some studies have preliminarily explored the effect of sleep on the consolidation of perceptual and motor sequences in implicit learning. However, these studies have failed to achieve a complete separation of motor sequences and perceptual sequences, thus leaving open the question of whether the sequence type moderates the effects of sleep on the consolidation of implicit sequence learning. In addition, previous studies of explicit learning have found that sequences with long length and high complexity were more likely to benefit from sleep than simple sequences, showing a sleep-based offline consolidation effect. Therefore, the question of whether the effect of sleep on offline consolidation of implicit learning of perceptual and motor sequences is moderated by sequence complexity remains unresolved.
The present study addressed these issues through three experiments applying different sequence length levels and complexities using a modified version of the Serial Reaction Time (SRT) task, which allows independent manipulation of perceptual and motor sequences. Participants were instructed to press the corresponding button as quickly and accurately as possible according to which color of the target square was the same as that of the surrounding square (Figure 1). In the perceptual sequence group, the target square color followed a sequence, but the finger response orders were randomly assigned. The opposite was true for the motor sequence group. Subsequently, a prediction test was used to estimate the amount of possible explicit knowledge.
Experiment 1 preliminarily explored the effects of sleep on the consolidation of perceptual and motor sequence implicit learning using a short six-element sequence with lower complexity. A 2 (sequence types: perceptual vs. motor) × 2 (group: day vs. night) between-subjects ANOVA showed a significant main effect of sequence types (F(1, 75) = 16.47, p < 0.001, η_p² = 0.18, Figure 2), indicating a more robust offline consolidation effect in the motor sequence group compared to the perceptual sequence group. However, sleep does not promote the offline consolidation of both sequences, F(1, 75) = 0.58, p = 0.448.
In Experiment 2, a more complex sequence (sequence length 11) was used. The results showed that participants implicitly learned the motor sequence (Figure 3). In the motor sequence group, participants with sleep performed a better offline consolidation effect than those without sleep, F(1, 71) = 12.45, p = 0.001, η_p² = 0.15. However, participants neither implicitly acquired the sequence nor showed an offline consolidation effect in the perceptual sequence group.
Given that a small or non-significant perceptual sequence learning effect were found in Experiments 1 and 2, the sleep-related offline consolidation of the perceptual sequence was further examined using a more simple sequence of length 4 in Experiment 3 (Figure 4). The results showed that participants exhibited a trend toward improvement in the performance of perceptual sequences learning, but no offline consolidation effect was observed in either group (Figure 5).
The combined results of the three experiments showed that sleep does not promote the offline consolidation of perceptual sequences, regardless of the degree of difficulty. For motor sequences, the sequence learning effect significantly increased following sleep but not after waking when the sequence length was long and structural complexity was high. However, sleep-related offline improvements were absent when the sequence length was short. In conclusion, these results indicated that the offline consolidation of implicit sequence knowledge based on sleep is modulated by sequence type and sequence complexity.

Key words: sleep, implicit learning, perceptual sequences, motor sequences, offline consolidation