No abstract

Sleep is known to elicit off-line improvements of newly learned procedural skills, a phenomenon attributed to enhancement consolidation of an internal skill representation. In the motor domain, enhancement consolidation has been reported almost exclusively for sequential-finger-tapping skills. The aim of the present study was to extend the notion of sleep-related enhancement consolidation to tasks closer to everyday motor skills. This was achieved by employing a sequence of unrestrained reaching-movements with the non-dominant arm. Fifteen reaching-movements had to be executed as fast as possible, following a spatial pattern in the horizontal plane. Terminating each movement, a peg had to be fitted into a hole on an electronic pegboard. Two experimental groups received initial training, one in the evening, the other one in the morning. Subsequently, performance in both groups was retested twelve, and again 24 hrs later. Thus, during retention each individual experienced a night of sleep, either followed or preceded by a wake interval. Performance error remained low throughout training and retests. Yet mean total execution time, indicative of task execution-speed, significantly decreased for all individuals throughout initial training (no group differences), and significantly decreased again in either group following nocturnal sleep, but not following wake. This finding does not appear to result merely from additional practice afforded at the time of retests, because only after a night of sleep individuals of both experimental groups also revealed performance improvement beyond that estimated from their initial training performance.

Nocturnal sleep effects on memory consolidation following gross motor sequence learning were examined using a complex arm movement task. This task required participants to produce non-regular spatial patterns in the horizontal plane by successively fitting a small peg into different target-holes on an electronic pegboard. The respective reaching movements typically differed in amplitude and direction. Targets were visualized prior to each transport movement on a computer screen. With this task we tested 18 subjects (22.6 ± 1.9 years; 8 female) using a between-subjects design. Participants initially learned a 10-element arm movement sequence either in the morning or in the evening. Performance was retested under free recall requirements 15 min post training, as well as 12 and 24 h later. Thus, each group was provided with one sleep-filled and one wake retention interval. Dependent variables were error rate (number of Erroneous Sequences, ES) and average sequence execution time (correct sequences only). Performance improved during acquisition. Error rate remained stable across retention. Sequence execution time (inverse to execution speed) significantly decreased again during the sleep-filled retention intervals, but remained stable during the respective wake intervals. These results corroborate recent findings on sleep-related enhancement consolidation in ecological valid, complex gross motor tasks. At the same time, they suggest this effect to be truly memory-based and independent from repeated access to extrinsic sequence information during retests.

Recently, a number of authors have advocated the introduction of gross motor tasks into research on sleep-related motor offline learning. Such tasks are often designed to be more complex than traditional key-pressing tasks. However, until now, little effort has been undertaken to scrutinize the role of task complexity in any systematic way. Therefore, the effect of task complexity on the consolidation of gross motor sequence memory was examined by our group in a series of three experiments. Criterion tasks always required participants to produce unrestrained arm movement sequences by successively fitting a small peg into target holes on a pegboard. The sequences always followed a certain spatial pattern in the horizontal plane. The targets were visualized prior to each transport movement on a computer screen. The tasks differed with respect to sequence length and structural complexity. In each experiment, half of the participants initially learned the task in the morning and were retested 12 h later following a wake retention interval. The other half of the subjects underwent practice in the evening and was retested 12 h later following a night of sleep. The dependent variables were the error rate and total sequence execution time (inverse to the sequence execution speed). Performance generally improved during acquisition. The error rate was always low and remained stable during retention. The sequence execution time significantly decreased again 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 or when subjects performed a highly regular movement pattern. It is assumed that the occurrence of sleep-related offline performance improvements in sequential motor tasks is associated with a sufficient amount of motor task complexity.

This paper addresses the notion of chunk concatenation being associated with sleep-related enhancement consolidation of motor sequence memory, thereby essentially contributing to improvements in sequence execution speed. To this end, element movement times of a multi-joint arm movement sequence incorporated in a recent study by Malangré et al. (2014) were reanalyzed. As sequence elements differed with respect to movement distance, element movement times had to be purged from differences solely due to varying trajectory lengths. This was done by dividing each element movement time per subject and trial block by the respective “reference movement time” collected from subjects who had extensively practiced each sequence element in isolation. Any differences in these “relative element movement times” were supposed to reflect element-specific “production costs” imposed solely by the sequence context. Across all subjects non-idiosyncratic, lasting sequence segmentation was shown, and four possible concatenation points (i.e. transition points between successive chunks) within the original arm movement sequence were identified. Based on theoretical suppositions derived from previous work with the discrete sequence production task and the dual processor model (Abrahamse et al., 2013), significantly larger improvements in transition speed occurring at these four concatenation points as compared to the five fastest transition positions within the sequence (associated with mere element execution) were assumed to indicate increased chunk concatenation. As a result, chunk concatenation was shown to proceed during acquisition with physical practice, and, most importantly, to significantly progress some more during retention following a night of sleep, but not during a waking interval.

No abstract