The effects of sleep, wake activity and time-on-task on offline motor sequence learning
Introduction
There is an increasing body of evidence showing that intervening sleep promotes the consolidation of memory (Diekelmann et al., 2009, Rasch and Born, 2013). Explicit motor sequence learning tasks, have been frequently used to measure the influence of sleep on memory consolidation. These tasks have typically demonstrated that after a practice session, task performance remains stable over retention periods composed purely of wakefulness, however significant ‘offline’ enhancements in performance (approximately 15–20% improvements in task speed) occur following a period that contains sleep (Walker, 2005, Walker et al., 2002). The mechanisms by which this sleep-dependent learning occurs is still debated. Sleep has been hypothesized to provide a period of reduced interference compared to wakefulness, thereby permitting consolidation to occur more efficaciously (Mednick et al., 2011, Wixted, 2004). This does not rule out, however, the possibility that active sleep-specific processes additionally promote the consolidation of memory.
During wakefulness, retrograde interference due to similar learnt material impairs memory retention (Nairne & Pandeirada, 2008). Some contemporary interference accounts extend this concept to also include any mental activity and/or new learning that can compete for consolidative resources (Mednick et al., 2011, Wixted, 2004). Relatedly, manipulations of the amount of activity during a wake episode (e.g. allowing a participant to go about their normal daily routine, compared to having participants remain reclined while listening to music) can have a notable impact on memory consolidation outcomes. Periods of reduced activity or ‘quiet’ wakefulness, can therefore have a similar benefit to learning as certain periods sleep (Gottselig et al., 2004, McDevitt et al., 2013, Mednick et al., 2009). With this is mind, studies assessing the impact of intervening sleep on consolidation must take into account the potential interfering properties of the wake comparison (mental activity/potential for new learning) or risk confounding the effect of sleep with waking interference.
Interference or disruption to memory consolidation processes is not uniquely a wake phenomenon; it can also occur during sleep. Patients with substantially disrupted sleep, such as obstructive sleep apnea (OSA), demonstrate reduced offline enhancements in motor skill performance after sleep compared to healthy controls, presumably due to impaired memory consolidation processes during sleep (Djonlagic et al., 2012, Djonlagic et al., 2014, Landry et al., 2014). Furthermore, as the rate of respiratory arousals (Arousal Index, AI) is negatively associated with the degree of offline improvement (Djonlagic et al., 2012), this impairment in consolidation has been attributed to sleep fragmentation. To our knowledge no study has experimentally induced sleep fragmentation in human participants to evaluate the extent to which fragmentation alone (without the associated hypoxic effects of apnea) can interfere with memory consolidation.
In addition to interference or disruption to sleep during a retention period, time on task fatigue is another factor that may affect motor learning and hence obscure offline changes in performance due to memory consolidation. Time on task fatigue has been shown to accumulate over motor task training periods (Rickard et al., 2008, Rieth et al., 2010). This effect on performance is greatest for trials at the end of training which are then used as a baseline to compare performance improvements that may occur over sleep/wake intervals. The change in performance measured is thus inadvertently due to both the alleviation of fatigue as well as any performance change due to consolidation. The use of spaced training regimes, (i.e. decreasing the length of task trials, while also increasing the length of rest between trials) has been shown to reduce the impact of fatigue, with the subsequent effect of eliminating the typically observed post sleep enhancement in motor performance (Rickard et al., 2008, Rieth et al., 2010). Brawn, Fenn, Nusbaum, and Margoliash (2010) using these methodological alterations, similarly found an elimination of post sleep enhancements, however demonstrated that performance would be maintained over sleep but would deteriorate over a wake period. While this finding challenges the notion that sleep imparts an offline/sleep-dependent gain in motor task performance, it does still suggest that sleep plays a beneficial role in the consolidation of learning. This benefit manifests however, as a stabilization of pre-sleep performance against losses accrued over wakefulness.
These findings discussed above suggest that there are a range of manipulable qualities of both sleep and wake intervals that can play a critical role as to whether offline-consolidation related gains in learning occur. Furthermore, typical measurements of these changes in motor learning are confounded by time on task fatigue effects, which when resolved, substantially change the way in which these consolidation related gains in performance are expressed. In order to disentangle these factors, the current study aimed to investigate the role of time on task fatigue effects as well the influence of interference applied over both wake (via activity) and disruption over sleep (via sleep fragmentation) on offline motor skill learning.
Section snippets
Design
Motor skill learning and consolidation outcomes were compared between uninterrupted and fragmented sleep periods as well as over comparable periods of wakefulness that was experimentally manipulated to be either ‘quiet’ or ‘active’ (see procedure for details). Two groups of participants completed both a sleep and a wake condition in a randomized order and separated by a wash-out period of at least one week. One group was composed of uninterrupted sleep and quiet wake conditions, while the other
Results
Two participants were removed from analysis due to missing or corrupted SFTT data. Data for forty-two participants remained for subsequent analysis. There were no differences between groups for participant age (F(3, 84) = .402, p = .752; M = 21.8, SEM = .32), or total number of years of education (F(3, 84) = .473, p = .702; M = 15.5, SEM = .19). Neither was there any difference in the number of self-reported hours spent touch tying per day (F(3, 84) = .095, p = .995; M = 3.0, SEM = .22). Furthermore participants’ trait
Discussion
The current study examined offline motor skill outcomes using the Sequential Finger Tapping Task (SFTT) under conditions of increased/decreased activity during wakefulness and sleep. An altered version of the SFTT that allows for the control of time on task/fatigue effects was also used to examine any potential impact of fatigue due to time on task. After initial training, in all conditions significant offline enhancements in SFTT motor speed were found over a short (10 min) delay. Subsequently
Conclusions
In summary, the present study found large improvements in motor skill performance on the SFTT following a short 10 min period of rest composed purely of wakefulness. These performance gains are likely the result of the alleviation of time on task fatigue and were equivalent in magnitude to performance enhancements previously considered to be sleep dependent. Subsequent changes in performance over a longer retention interval including either a nap or wake period were small, and not statistically
Acknowledgments
The authors would like to thank Emma Curtin and Selina Tran for their assistance with data collection as well as Julian Renzo for mastering the audio tones.
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2019, Sleep MedicineCitation Excerpt :In addition to gender-related effects, it must be acknowledged that beneficial effects of post-learning sleep for the consolidation of novel skills in procedural memory remain a controversial issue. Whereas some studies found motor skill learning improvement with post-training sleep [46–48], others observed equivalent stabilization or improvement effects after sleep and wakefulness [49,50], or that sleep-related effects are actually modulated by several factors [51]. For instance, sleep was found to induce stronger FTT improvement when associated with anticipated reward [52], or to promote higher gains in tasks featuring a greater degree of motor skill complexity [53].
Sleep and Memory Consolidation: Conceptual and Methodological Challenges
2019, Handbook of Behavioral NeuroscienceCitation Excerpt :As pointed out by others (Brokaw et al., 2016; Mednick, Cai, Shuman, Anagnostaras, & Wixted, 2011), the large majority of empirical studies in the sleep-memory field have used active waking (AW) as the comparison for sleep. Typically, participants assigned to the “wake” condition are required to perform engaging activities that involve high levels of attentional, perceptual, and cognitive processing, including various forms of “distractor” tasks, watching movies, or going about one's regular daily activities (for examples of typical AW conditions, see Brokaw et al., 2016; Huber et al., 2004; Landry, Anderson, & Conduit, 2016; Maier et al., 2017; Piosczyk et al., 2013). There are justifiable reasons why an AW condition is commonly used as a comparison for sleep, including the effectiveness of AW for preventing involuntary sleep or the explicit (or perhaps implicit) rehearsal/reactivation of information.
Qualitative differences in offline improvement of procedural memory by daytime napping and overnight sleep: An fMRI study
2018, Neuroscience ResearchCitation Excerpt :These reports suggest that the nap-induced speed enhancement observed in the present study may represent an early boost effect, perhaps also including recovery effect from the gradual build-up of fatigue over the course of the concentrated training that preceded the nap (Rickard et al., 2008). Because there was no significant difference in speed enhancement between the nap group and whole-night sleep group, the speed enhancement in both groups may have been related to the early boost effect (Hotermans et al., 2006; Nettersheim et al., 2015; Landry et al., 2016). This is consistent with the idea that sleep per se does not enhance performance in terms of speed (Rickard et al., 2008).