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.

Introduction

Sleep is believed to participate in the long-term consolidation of recent memory traces Maquet, 2001, Smith, 2001, Stickgold et al., 2001. Although the mechanisms of memory reprocessing during sleep are not yet fully understood, the hypothesis implies that memories recently acquired during wakefulness are actively restructured and strengthened during sleep. These processes would thus promote dynamic plastic changes in neuronal populations previously engaged in memory acquisition (Maquet, 2001). Consistent with this hypothesis, several animal studies have shown that neural activity expressed during waking behavior is reinstated during subsequent sleep (e.g., Wilson and McNaughton, 1994, Skaggs and McNaughton, 1996, Qin et al., 1997, Nadasdy et al., 1999, Louie and Wilson, 2001.

In humans, we have previously reported experience-dependent reactivation in cortical neuronal ensembles during rapid-eye-movements (REM) sleep after extended practice on a probabilistic serial reaction time (SRT) task (Maquet et al., 2000), a well-known paradigm of implicit sequence learning. In the probabilistic SRT task (Cleeremans and McClelland, 1991), subjects had to press as fast and as accurately as possible on the key that corresponds to the location of a stimulus displayed at one of six possible locations on a computer screen. Unknown to subjects, the material contained sequential structure. The sequence of successive locations visited by the stimulus over trials was probabilistically determined by an artificial grammar (Fig. 1). Using positron emission tomography (PET), we showed that several brain areas activated during practice on the SRT task during wakefulness were significantly more active during subsequent REM sleep in subjects who had been previously trained on the task than in subjects without prior SRT practice. Consequently, we suggested that experience-dependent cerebral reactivation during posttraining REM sleep reflected the reprocessing of the memory traces formed during SRT practice. However, because the analyses compared subjects trained on the SRT task to subjects without any SRT practice, it was not possible to ascertain whether posttraining REM sleep reactivation related to the reprocessing of elementary visuomotor associations or of the complex sequential rules prescribed by the artificial grammar.

Here, we report a complementary study aimed to test the hypothesis that cerebral reactivation during posttraining REM sleep specifically reflects the reprocessing of high-order information about the sequential structure of the material to be learned. The alternative interpretation is that experience-dependent reactivation during REM sleep is merely related to the reprocessing of the simple visuomotor associations between stimulus location and key response. To explore these issues, we scanned a new group of subjects during sleep after practice on the same SRT task, but using a completely random sequence of stimuli. The experimental protocol was thus identical in all respects to that used for the trained group in our original study (Maquet et al., 2000), except for the absence of sequential rules. Because visuomotor training is strictly comparable in both cases, possible differences in posttraining regional cerebral blood flow (rCBF) between the subjects trained, respectively, to the probabilistic SRT task or to its random version could only be interpreted as reflecting specifically the reprocessing of the high-order, elaborated, sequential information after probabilistic sequence learning. Moreover, functional connections during REM sleep should be reinforced between the reactivated areas and cerebral structures involved in sequence learning for the group trained specifically on probabilistic material. Finally, we could also expect to observe that regional brain reactivation during posttraining REM sleep is modulated by the level of learning achieved prior to sleep.