Slow waves, a key feature of the EEG of NREM sleep, may be causally involved in producing a sleep-dependent, progressive downscaling of synaptic strength, which would lead to several benefits in terms of both cellular function and network performance. Also the A1 subtypes of the so-called cyclic alternating pattern (CAP) are composed mostly of slow waves and map over the frontal and prefrontal regions of the scalp. The aim of this study was to evaluate the eventual changes of CAP induced by an implicit learning paradigm which has already been shown to be able to increase locally sleep slow-wave activity (SWA). Our hypothesis was that learning is accompanied by a change in the components of CAP characterized by SWA (0.5-2.5Hz), i.e. its A1 subtypes. For this reason, in the present study we evaluated sleep recordings obtained in 10 healthy young normal subjects (mean age 25.8+/-1.8 years) who were asked to perform a motor learning task just before going to sleep. Sleep EEG was recorded for 2h and subjects were also tested after the night following the rotation task. Sleep stages and CAP (classified into three subtypes: A1, A2, and A3) were identified in the first hour of each recording. We found a significant increase in the number of CAP A1 subtypes per hour of NREM sleep on the night following the rotation test; the correlation between the change in A1 index and the post-sleep performance improvement after the rotation task was positive. These results confirm our hypothesis that CAP slow components are modified by a learning task during the day preceding sleep and support the idea that these components may play a role in sleep-related cognitive processes.