Effects of Night‐Time Sleep and Timing Following Observational Sequence Learning: Evidence for a Nonlinear Relationship in Procedural Task Performance

The optimal timing of sleep's influence on motor skill consolidation following observational sequence learning remains largely undefined. This study investigated how the interval between visual pattern observation and subsequent night-time sleep impacts skill retention. Forty female university students (mean age = 24.35 ± 1.25 years) were assigned to a wake control group (Noon-Night, observing at 12 PM) and three experimental groups undergoing overnight sleep with varying observation-to-sleep intervals: Noon-Morning (12 PM observation), Evening-Morning (6 PM observation) and Night-Morning (11:30 PM observation). Performance was assessed via overall reaction times on sequential trials (procedural task performance) and reaction time difference scores (sequence learning). Results of independent t-test on difference scores revealed no significant difference in sequence learning between the Noon-Morning and Noon-Night groups. The mixed ANOVA with repeated measures indicated that participants generally improved their sequence learning from training to retention. There were also significant overall differences in sequence learning among the groups, with the Night-Morning group exhibiting better performance. However, the interaction between group and test phase was not significant. Results on reaction time revealed the Noon-Morning group's reaction time was significantly faster than the Noon-Night group's, confirming a positive effect of night-time sleep on ASRTT performance. Mixed ANOVA indicated a significant interaction effect; both the Noon-Morning and Night-Morning groups demonstrated significantly better retention than the Evening-Morning group. These findings suggest a nonlinear, inverted-U relationship between the observation-sleep interval and procedural task performance, where optimal consolidation occurs with either very short or relatively long pre-sleep intervals.