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Symposium V: Sleep and learning: New developments
Brain and Cognition 60 (2006) 331–332 www.elsevier.com/locate/b&c
Symposium V—Sleep and learning: New developments Carlyle Smith Trent University, Peterborough, Ont., Canada Available online 2 November 2005 A role for REM sleep in offline memory reprocessing, Carlyle Smith, Department of Psychology, Trent University, Peterborough, Canada It has been shown in both animal and human studies that some tasks are most efficiently learned if rapid eye movement (REM) sleep occurs between task acquisition and re-test sessions. In animals, post-training REM sleep increases are observed following successful acquisition of appetitive or aversive tasks. Selective REM sleep deprivation at strategic post-training times called REM Sleep Windows results in subsequent memory impairment. In humans, following successful task acquisition, there is an increase in REM sleep intensity, as measured by number and density of actual REMs. The intensity of these REMs is correlated with learning progress and may be a biological marker for some types of intelligence. Selective REM sleep deprivation results in post acquisition memory deficits. In humans, memory for cognitive procedural tasks seems most vulnerable to REM sleep deprivation. Sleep, memory, and dreams: A neurocognitive approach, Robert Stickgold, Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, USA Converging evidence provides a broad base of support for the hypothesis that sleep plays an important, and possibly critical role in learning and memory consolidation. Studies of procedural learning in humans demonstrate that performance enhancements accrue as a consequence of sleep, and are not seen following similar periods of wake. Sleep deprivation the night after training can block this enhancement, even after subsequent nights of recovery sleep. For a visual texture-discrimination task, overnight improvement correlates with both the amount of deep, slow-wave sleep (SWS) early in the night and of rapid-eye-movement (REM) sleep late in the night. Together, these two sleep parameters explain over 80% of the intersubject variance in overnight improvement. In contrast, overnight improvement on a motor sequence learning task correlates with the amount of light (Stage 2) nonREM sleep, especially late in the night, explaining over half of intersubject variance. In addition to these low-level procedural tasks, preliminary evidence suggests that similar overnight improvement is seen on a ‘‘complex cognitive procedural’’ weather-predicting task involving probabilistic learning. While these tasks demonstrate changes in memory across a night, changes in performance on a semantic priming task following awakenings from REM and nonREM sleep suggest state-dependent changes in associative memory networks during sleep, with weaker associations being preferentially accessed during REM sleep. Dreams also provide evidence of memory processing during sleep, with near veridical replay of prior waking events shifting toward more associative images as the night progresses. 0278-2626/$ - see front matter Ó 2005 Elsevier Inc. All rights reserved. doi:10.1016/j.bandc.2005.09.005
Linking sleep stages to memory: How many stages do we need? Kevin Peters, Department of Psychology, Trent University, Peterborough, Canada Despite a growing body of literature supporting the role of sleep in memory consolidation, there is a current debate regarding attempts to link different sleep stages to different types of memory. In particular, a number of mixed findings have been reported with respect to mapping certain sleep stages to different types of motor learning tasks. For example, some tasks (e.g., the pursuit rotor) appear to be Stage 2-dependent; whereas other tasks (e.g., the mirror trace) appear to be dependent upon rapid eye movement (REM) sleep. We have proposed a new model that attempts to account for these mixed findings. The basic premise of this model is that different sleep stages are involved in consolidating different kinds of motor tasks depending upon how novel the task is to the participant. Novel tasks that require participants to learn entirely new motor sequences are initially consolidated within the cortico-cerebellar circuit (motor cortex, pons, cerebellum, and thalamus), which occurs primarily during REM sleep. On the other hand, tasks that can be performed using pre-existing and well practiced motor programs are consolidated within the cortico-striatal system (motor cortex, striatum, and thalamus) which occurs primarily during Stage 2 sleep. This model is dynamic: as novel tasks become well learned, there is a shift in the neural circuits that mediate those tasks and this shift is reflected in the sleep architecture. We are currently in the process of testing a number of specific predictions that can be made using this model. Sometimes brain imaging shows the hidden: Offline processes of memory consolidation through the sleep-wake cycle, Philippe Peigneux, Cyclotron Research Centre, University of Lie`ge, Lie`ge, Belgium During the last decade, functional brain imaging techniques have demonstrated the re-expression and modulation of learning-related cerebral activity during post-training sleep in man. Using positron emission tomography (PET) then functional magnetic resonance imaging (fMRI), we have shown that learning-related patterns of cerebral activity are re-expressed during subsequent sleep stages (REM versus slow wave sleep, respectively) according to specific memory types (procedural versus spatial/episodic, respectively). Conversely, sleep deprivation hampers the cooperative activity of cortical and subcortical networks during subsequent task practice. Offline modifications of brain activity during posttraining sleep are not merely the consequence of extended pre-sleep practice, but are crucially contingent upon the underlying cognitive content of the task, which emphasizes the importance of pre-sleep information processing during, and after, the acquisition episode. Accordingly, we recently evidenced the offline persistence and evolution of learning-related
332
Abstract / Brain and Cognition 60 (2006) 331–332
cerebral activity during post-training periods of wakefulness. Furthermore, these data suggest a functional connection between offline cerebral activity during the sleep-wake cycle and memory consolidation. On the one hand, level of procedural learning correlates to the increase in regional cerebral blood flow during subsequent REM sleep, suggesting that post-training cerebral reactivation is modulated by the strength of the recently developed memory traces. On the other hand, and most importantly, the amount of hippocampal activity re-expressed during slow wave sleep has been shown to predict the level of overnight improvement in topographical learning. As a whole, these studies represent a pre-
liminary attempt to delineate the cerebral correlates of the journey of a new memory, from its initial acquisition and maintenance during wakefulness to its re-expression and consolidation during post-training sleep, which eventually leads to the plastic changes underlying the subsequent improvement in performance.
Acknowledgments Supported by: FNRS; IAP—Belgian Science Policy; FMRE; ULg Special Funds.
Symposium V—Sleep and learning: New developments Carlyle Smith Trent University, Peterborough, Ont., Canada Available online 2 November 2005 A role for REM sleep in offline memory reprocessing, Carlyle Smith, Department of Psychology, Trent University, Peterborough, Canada It has been shown in both animal and human studies that some tasks are most efficiently learned if rapid eye movement (REM) sleep occurs between task acquisition and re-test sessions. In animals, post-training REM sleep increases are observed following successful acquisition of appetitive or aversive tasks. Selective REM sleep deprivation at strategic post-training times called REM Sleep Windows results in subsequent memory impairment. In humans, following successful task acquisition, there is an increase in REM sleep intensity, as measured by number and density of actual REMs. The intensity of these REMs is correlated with learning progress and may be a biological marker for some types of intelligence. Selective REM sleep deprivation results in post acquisition memory deficits. In humans, memory for cognitive procedural tasks seems most vulnerable to REM sleep deprivation. Sleep, memory, and dreams: A neurocognitive approach, Robert Stickgold, Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, USA Converging evidence provides a broad base of support for the hypothesis that sleep plays an important, and possibly critical role in learning and memory consolidation. Studies of procedural learning in humans demonstrate that performance enhancements accrue as a consequence of sleep, and are not seen following similar periods of wake. Sleep deprivation the night after training can block this enhancement, even after subsequent nights of recovery sleep. For a visual texture-discrimination task, overnight improvement correlates with both the amount of deep, slow-wave sleep (SWS) early in the night and of rapid-eye-movement (REM) sleep late in the night. Together, these two sleep parameters explain over 80% of the intersubject variance in overnight improvement. In contrast, overnight improvement on a motor sequence learning task correlates with the amount of light (Stage 2) nonREM sleep, especially late in the night, explaining over half of intersubject variance. In addition to these low-level procedural tasks, preliminary evidence suggests that similar overnight improvement is seen on a ‘‘complex cognitive procedural’’ weather-predicting task involving probabilistic learning. While these tasks demonstrate changes in memory across a night, changes in performance on a semantic priming task following awakenings from REM and nonREM sleep suggest state-dependent changes in associative memory networks during sleep, with weaker associations being preferentially accessed during REM sleep. Dreams also provide evidence of memory processing during sleep, with near veridical replay of prior waking events shifting toward more associative images as the night progresses. 0278-2626/$ - see front matter Ó 2005 Elsevier Inc. All rights reserved. doi:10.1016/j.bandc.2005.09.005
Linking sleep stages to memory: How many stages do we need? Kevin Peters, Department of Psychology, Trent University, Peterborough, Canada Despite a growing body of literature supporting the role of sleep in memory consolidation, there is a current debate regarding attempts to link different sleep stages to different types of memory. In particular, a number of mixed findings have been reported with respect to mapping certain sleep stages to different types of motor learning tasks. For example, some tasks (e.g., the pursuit rotor) appear to be Stage 2-dependent; whereas other tasks (e.g., the mirror trace) appear to be dependent upon rapid eye movement (REM) sleep. We have proposed a new model that attempts to account for these mixed findings. The basic premise of this model is that different sleep stages are involved in consolidating different kinds of motor tasks depending upon how novel the task is to the participant. Novel tasks that require participants to learn entirely new motor sequences are initially consolidated within the cortico-cerebellar circuit (motor cortex, pons, cerebellum, and thalamus), which occurs primarily during REM sleep. On the other hand, tasks that can be performed using pre-existing and well practiced motor programs are consolidated within the cortico-striatal system (motor cortex, striatum, and thalamus) which occurs primarily during Stage 2 sleep. This model is dynamic: as novel tasks become well learned, there is a shift in the neural circuits that mediate those tasks and this shift is reflected in the sleep architecture. We are currently in the process of testing a number of specific predictions that can be made using this model. Sometimes brain imaging shows the hidden: Offline processes of memory consolidation through the sleep-wake cycle, Philippe Peigneux, Cyclotron Research Centre, University of Lie`ge, Lie`ge, Belgium During the last decade, functional brain imaging techniques have demonstrated the re-expression and modulation of learning-related cerebral activity during post-training sleep in man. Using positron emission tomography (PET) then functional magnetic resonance imaging (fMRI), we have shown that learning-related patterns of cerebral activity are re-expressed during subsequent sleep stages (REM versus slow wave sleep, respectively) according to specific memory types (procedural versus spatial/episodic, respectively). Conversely, sleep deprivation hampers the cooperative activity of cortical and subcortical networks during subsequent task practice. Offline modifications of brain activity during posttraining sleep are not merely the consequence of extended pre-sleep practice, but are crucially contingent upon the underlying cognitive content of the task, which emphasizes the importance of pre-sleep information processing during, and after, the acquisition episode. Accordingly, we recently evidenced the offline persistence and evolution of learning-related
332
Abstract / Brain and Cognition 60 (2006) 331–332
cerebral activity during post-training periods of wakefulness. Furthermore, these data suggest a functional connection between offline cerebral activity during the sleep-wake cycle and memory consolidation. On the one hand, level of procedural learning correlates to the increase in regional cerebral blood flow during subsequent REM sleep, suggesting that post-training cerebral reactivation is modulated by the strength of the recently developed memory traces. On the other hand, and most importantly, the amount of hippocampal activity re-expressed during slow wave sleep has been shown to predict the level of overnight improvement in topographical learning. As a whole, these studies represent a pre-
liminary attempt to delineate the cerebral correlates of the journey of a new memory, from its initial acquisition and maintenance during wakefulness to its re-expression and consolidation during post-training sleep, which eventually leads to the plastic changes underlying the subsequent improvement in performance.
Acknowledgments Supported by: FNRS; IAP—Belgian Science Policy; FMRE; ULg Special Funds.