title: Learned material content and acquisition level modulate cerebral reactivation during posttraining rapid-eye-movements sleep.
abstract: We have previously shown that several brain areas are activated both during sequence learning at wake and during subsequent rapid-eye-movements (REM) sleep (Nat. Neurosci. 3 (2000) 831-836), suggesting that REM sleep participates in the reprocessing of recent memory traces in humans. However, the nature of the reprocessed information remains open. Here, we show that regional cerebral reactivation during posttraining REM sleep is not merely related to the acquisition of basic visuomotor skills during prior practice of the serial reaction time task, but rather to the implicit acquisition of the probabilistic rules that defined stimulus sequences. Moreover, functional connections between the reactivated cuneus and the striatum--the latter being critical for implicit sequence learning--are reinforced during REM sleep after practice on a probabilistic rather than on a random sequence of stimuli. Our results therefore support the hypothesis that REM sleep is deeply involved in the reprocessing and optimization of the high-order information contained in the material to be learned. In addition, we show that the level of acquisition of probabilistic rules attained prior to sleep is correlated to the increase in regional cerebral blood flow during subsequent REM sleep. This suggests that posttraining cerebral reactivation is modulated by the strength of the memory traces developed during the learning episode. Our data provide the first experimental evidence for a link between behavioral performance and cerebral reactivation during REM sleep.
authors.affiliation: Cyclotron Research Center and Department of Neuropsychology, Université de Liège, Belgium. Philippe.Peigneux@ulg.ac.be
authors.forename: Philippe
authors.initials: P
authors.lastname: Peigneux
authors.forename: Steven
authors.initials: S
authors.lastname: Laureys
authors.forename: Sonia
authors.initials: S
authors.lastname: Fuchs
authors.forename: Arnaud
authors.initials: A
authors.lastname: Destrebecqz
authors.forename: Fabienne
authors.initials: F
authors.lastname: Collette
authors.forename: Xavier
authors.initials: X
authors.lastname: Delbeuck
authors.forename: Christophe
authors.initials: C
authors.lastname: Phillips
authors.forename: Joel
authors.initials: J
authors.lastname: Aerts
authors.forename: Guy
authors.initials: G
authors.lastname: Del Fiore
authors.forename: Christian
authors.initials: C
authors.lastname: Degueldre
authors.forename: André
authors.initials: A
authors.lastname: Luxen
authors.forename: Axel
authors.initials: A
authors.lastname: Cleeremans
authors.forename: Pierre
authors.initials: P
authors.lastname: Maquet
mesh_terms: D000328:Adult; D001921:Brain / Q000000981:diagnostic imaging / Q000502:physiology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007858:Learning / Q000502:physiology*; D008279:Magnetic Resonance Imaging; D008297:Male; D011597:Psychomotor Performance / Q000502:physiology; D011930:Reaction Time / Q000502:physiology; D012691:Serial Learning / Q000502:physiology; D012895:Sleep, REM / Q000502:physiology*; D013238:Stereotaxic Techniques; D014055:Tomography, Emission-Computed