Figure 4 - available via license: Creative Commons Attribution 4.0 International
Content may be subject to copyright.
Neural correlates of motor sequence memory consolidation during post-sleep resting-state periods. The ventrolateral putamen (A) and the cerebellar cortex (lobules V-VI) (B) functional connectivity within the consolidated pattern differed significantly between the MSL and CTL conditions during post-sleep resting-state periods (RS3) as compared to baseline (RS1). Bar plot illustrates the change in functional connectivity of putamen within the consolidated pattern between RS3 and RS1 scans averaged across subjects in each task condition. The scatter plot in (A) shows that only the putamen functional connectivity was significantly related to the extent of overnight behavioral gains in performance speed. The color-coded activations maps indicate Z-score values and are corrected for multiple comparisons using GRF, p<0.05. Error bars represent s.e.m.; * and ** indicate p<0:05 and p<0:01, respectively. DOI: 10.7554/eLife.24987.015 The following figure supplements are available for figure 4: Figure supplement 1. Functional connectivity within the consolidated pattern during post-sleep resting-state periods (RS3) and baseline (RS1) in each task. DOI: 10.7554/eLife.24987.016 Figure supplement 2. Neural correlates of motor sequence learning during resting-state periods immediately following training. DOI: 10.7554/eLife.24987.017 Figure supplement 3. Changes in brain functional connectivity related to motor sequence learning during the post-sleep (top row) and the pre-sleep (bottom row) resting-state conditions. DOI: 10.7554/eLife.24987.018
Source publication
Sleep is necessary for the optimal consolidation of newly acquired procedural memories. However, the mechanisms by which motor memory traces develop during sleep remain controversial in humans, as this process has been mainly investigated indirectly by comparing pre- and post-sleep conditions. Here, we used functional magnetic resonance imaging and...
Similar publications
It has been proposed that sleep’s contribution to memory consolidation is to reactivate prior encoded information. To elucidate the neural mechanisms carrying reactivation-related mnemonic information, we investigated whether content-specific memory signatures associated with memory reactivation dur- ing wakefulness reoccur during subsequent sleep....
The conditioning tasks have been widely used to model fear and anxiety and to study their association with sleep. Many reports suggest that sleep plays a vital role in the consolidation of fear memory. Studies have also demonstrated that fear-conditioning influences sleep differently in mice strains having a low or high anxiety level. It is, theref...
Oscillating waves during sleep play an essential role in memory consolidation. The cortical slow wave activity (SWA) and sigma waves during NREM sleep and theta waves during REM sleep increase after a variety of memory tasks including declarative, procedural and associative learning tasks. These oscillatory waves during sleep help to promote neural...
Citations
... A landmark study using positron emission tomography found that hippocampal responses observed during spatial navigation were observed again during post-learning sleep (but not pre-learning sleep) [98]. A multitude of subsequent neuroimaging studies have repeatedly demonstrated that patterns of brain activity associated with learning are reinstated during sleep, with the level of reinstatement correlating with post-sleep retention [99][100][101][102][103][104][105][106]. ...
Purpose of Review
Pioneering work in rodents has shown that the reactivation of recently acquired memories during sleep is a key mechanism underlying the beneficial effect of sleep on memory consolidation. In this review, we consider recent evidence of memory reactivation processes in human sleep.
Recent Findings
The precise temporal coupling of sleep spindles to slow oscillations during non-rapid eye movement sleep plays a central role in sleep-associated memory consolidation. Both correlational studies and studies directly manipulating oscillatory activity in the sleeping brain have confirmed that spindles coupled to slow oscillations are better predictors of memory than uncoupled spindles and that the greatest memory benefit comes when spindles are tightly coupled to the up-state of the slow oscillation. Recent evidence suggests that memory content is reactivated during sleep, with a functional benefit for memory performance after sleep. Reactivation events are time-locked around slow oscillation-spindle coupling events, as well as sharp-wave ripples in hippocampus.
Summary
Memory reactivation, which is facilitated by slow oscillation-spindle coupling events, can be observed during human sleep and shows promise as a prime mechanism underlying sleep’s beneficial effects on memory.
... Interestingly for the weaker FC observed within horns (ventro-dorsal FC), the various denoising models did not signi cantly impact the FC. Figure 7 shows activation clusters associated with the motor task performance in the brain and brainstem. At the brain level, all of the anticipated sensorimotor cortical and subcortical areas related to unilateral hand movement (Vahdat et al., 2017(Vahdat et al., , 2015(Vahdat et al., , 2011 showed signi cant activation, including the contralateral primary motor cortex (M1), dorsal premotor cortex, primary and secondary somatosensory cortices (SI, SII), thalamus (ventral lateral and pulvinar nuclei), putamen, ipsilateral cerebellar cortex (lobules I-IV, and V-VI), bilateral posterior parietal cortex (PPC), and supplementary motor area (SMA) (corrected for multiple comparisons using GRF, Z > 2.7, p < 0.5, Fig. 7A). Interestingly, our high in-plane spatial resolution (1.6×1.6 mm 2 ) allowed us to detect and delineate task-related brainstem activations, including bilateral pontine reticular formation (PRF), medullary reticular formation (MRF), and red nucleus (RN) (Fig. 7B). ...
... The force control task was selected due to 3 main advantages compared to similar motor tasks performed in the scanner: 1) The task is isometric, so there is no difference in movement kinematics across participants, 2) The produced force is normalized across individuals using their MVC, and 3) The isometric task minimizes motion artifacts, which are critical for spinal cord imaging at the neck level. The activated cortical and subcortical areas during this task are consistent with our previous fMRI studies using hand movements (Braaß et al., 2023;Vahdat et al., 2017Vahdat et al., , 2015Vahdat et al., , 2011, including contralateral M1, S1, premotor cortex, SII, PPC, thalamus, striatum, SMA, and ipsilateral cerebellum (Fig. 7). Importantly, we found signi cant task-related activations at the C5-C8 cervical level, mainly at the ipsilateral ventral horn (Fig. 8), consistent with the known neuroanatomical location of the nger/wrist motoneurons. ...
Simultaneous functional magnetic resonance imaging (fMRI) of the spinal cord and brain represents a powerful method for examining both ascending sensory and descending motor pathways in humans in vivo . However, its image acquisition protocols, and processing pipeline are less well established. This limitation is mainly due to technical difficulties related to spinal cord fMRI, and problems with the logistics stemming from a large field of view covering both brain and cervical cord. Here, we propose an acquisition protocol optimized for both anatomical and functional images, as well as an optimized integrated image processing pipeline, which consists of a novel approach for automatic modeling and mitigating the negative impact of spinal voxels with low temporal signal to noise ratio (tSNR). We validate our integrated pipeline, named FASB, using simultaneous fMRI data acquired during the performance of a motor task, as well as during resting-state conditions. We demonstrate that FASB outperforms the current spinal fMRI processing methods in three domains, including motion correction, registration to the spinal cord template, and improved detection power of the group-level analysis by removing the effects of participant-specific low tSNR voxels, typically observed at the disk level. Using FASB, we identify significant task-based activations in the expected sensorimotor network associated with a unilateral handgrip force production task across the entire central nervous system, including the contralateral sensorimotor cortex, thalamus, striatum, cerebellum, brainstem, as well as ipsilateral ventral horn at C5-C8 cervical levels. Additionally, our results show significant task-based functional connectivity between the key sensory and motor brain areas and the dorsal and ventral horns of the cervical cord. Overall, our proposed acquisition protocol and processing pipeline provide a robust method for characterizing the activation and functional connectivity of distinct cortical, subcortical, brainstem and spinal cord regions in humans.
... Taken together with our findings of increased LRTC in the control group, we hypothesize that increased LRTC may be a general indicator of overall performance/cognitive flexibility, whereas decreased LRTC is a specific indicator of ongoing plasticity in regions that are actively engaged in processing new information. Furthermore, given the key importance of sleep in motor learning consolidation (Vahdat et al., 2017), it is plausible that decreased LRTC during non-REM sleep and the wakeful resting-state both reflect the ongoing learning process and consolidation. As such, gaining further insights into these questions through future research would be highly valuable. ...
Decreased long‐range temporal correlations (LRTC) in brain signals can be used to measure cognitive effort during task execution. Here, we examined how learning a motor sequence affects long‐range temporal memory within resting‐state functional magnetic resonance imaging signal. Using the Hurst exponent (HE), we estimated voxel‐wise LRTC and assessed changes over 5 consecutive days of training, followed by a retention scan 12 days later. The experimental group learned a complex visuomotor sequence while a complementary control group performed tightly matched movements. An interaction analysis revealed that HE decreases were specific to the complex sequence and occurred in well‐known motor sequence learning associated regions including left supplementary motor area, left premotor cortex, left M1, left pars opercularis, bilateral thalamus, and right striatum. Five regions exhibited moderate to strong negative correlations with overall behavioral performance improvements. Following learning, HE values returned to pretraining levels in some regions, whereas in others, they remained decreased even 2 weeks after training. Our study presents new evidence of HE's possible relevance for functional plasticity during the resting‐state and suggests that a cortical subset of sequence‐specific regions may continue to represent a functional signature of learning reflected in decreased long‐range temporal dependence after a period of inactivity.
... Hippocampal activity during sleep was higher than control groups who either performed no pre-sleep learning task, or engaged in non-hippocampal dependent learning, indicating that the observed hippocampal reactivation was selective for the spatial memories that recruited hippocampus during learning [83]. Many subsequent studies ( primarily fMRI), have repeatedly shown that brain regions engaged at learning are re-engaged during subsequent sleep, with the level of re-engagement correlating with the behavioural benefits of sleep for memory consolidation [84][85][86][87][88][89][90][91][92][93]. ...
Sleep promotes memory consolidation: the process by which newly acquired memories are stabilised, strengthened, and integrated into long-term storage. Pioneering research in rodents has revealed that memory reactivation in sleep is a primary mechanism underpinning sleep's beneficial effect on memory. In this review, we consider evidence for memory reactivation processes occurring in human sleep. Converging lines of research support the view that memory reactivation occurs during human sleep, and is functionally relevant for consolidation. Electrophysiology studies have shown that memory reactivation is tightly coupled to the cardinal neural oscillations of non-rapid eye movement sleep, namely slow oscillation-spindle events. In addition, functional imaging studies have found that brain regions recruited during learning become reactivated during post-learning sleep. In sum, the current evidence paints a strong case for a mechanistic role of neural reactivation in promoting memory consolidation during human sleep.
... New information and experience details form memories while you sleep. Researchers found that NREM sleep is essential for two complementary processes that support the consolidation of human motor memory, including the restoration and restructuring of freshly learned information while we sleep [23]. ...
Sleep is such a complex and dynamic process and dream that it still is a scientific enigma. Over more than a century of research has established a wide range of dream-relevant theories, whereas, no one has yet reached an accurate conclusion about the function and meaning of dreams. So, in this project, I desire to review the relationship between sleep and dream and illustrate what is the function of sleep and dream. Firstly, is to state the specific processes of sleep. Humans undergo REM (Rapid Eye Movement) and NREM (non-rapid-eye-movement) during sleep. Additionally, there are various functions of REM, NREM sleep, and dreams which remain controversial. The third ambition of this project is to discuss whether dreams can act as a kind of therapy for mental disorders. And evaluate the effectiveness of lucid dreaming therapy (LDT) in patients suffering from mental disorders.
... Written instructions (including illustrations) were visually displayed on the screen at the beginning of the task. Instantaneous performance was calculated as correct sequence tapping speed (keypresses/sec) (1,24) to quantify absolute performance levels and microscale changes during early learning and as the number of correct sequences per trial, a trial-to-trial skill measure traditionally used in this task (25)(26)(27) (Fig 1a,b; Supplementary Figs 1-4). ...
When humans begin learning new motor skills, they typically display early rapid performance improvements. It is not well understood how knowledge acquired during this early skill learning period generalizes to new, related skills. Here, we addressed this question by investigating factors influencing generalization of early learning from a skill A to a different, but related skill B. Early skill generalization was tested over four experiments (N = 2,095). Subjects successively learned two related motor sequence skills (skills A and B) over different practice schedules. Skill A and B sequences shared ordinal (i.e., matching keypress locations), transitional (i.e., ordered keypress pairs), parsing rule (i.e., distinct sequence events like repeated keypresses that can be used as a breakpoint for segmenting the sequence into smaller units) structures, or possessed no structure similarities. Results showed generalization for shared parsing rule structure between skills A and B after only a single 10-second practice trial of skill A. Manipulating the initial practice exposure to skill A (1 to 12 trials) and inter-practice rest interval (0 to 30s) between skills A and B had no impact on parsing rule structure generalization. Furthermore, this generalization was not explained by stronger sensorimotor mapping between individual keypress actions and their symbolic representations. In contrast, learning from skill A did not generalize to skill B during early learning when the sequences shared only ordinal or transitional structure features. These results document sequence structure that can be very rapidly generalized during initial learning to facilitate generalization of skill.
... Across all test blocks, the PP group performed 14.6 (G 1.6) accurate sequences, 14.1 (G 1.7) for the MI group, and 14.6 (G 1.7) for the AO group (out of a maximum of 16 sequences). To better reflect individual performance on the motor sequence task we computed mean RT performance on accurately typed sequences, 43,44 which has been proposed as a sensitive measure of sleep-related motor sequence consolidation. 88 Individual RTs were then averaged to obtain an overall estimation of the performance for each practice block. ...
Sleep benefits the consolidation of motor skills learned by physical practice, mainly through periodic thalamocortical sleep spindle activity. However, motor skills can be learned without overt movement through motor imagery or action observation. Here, we investigated whether sleep spindle activity also supports the consolidation of non-physically learned movements. Forty-five electroencephalographic sleep recordings were collected during a daytime nap after motor sequence learning by physical practice, motor imagery, or action observation. Our findings reveal that a temporal cluster-based organization of sleep spindles underlies motor memory consolidation in all groups, albeit with distinct behavioral outcomes. A daytime nap offers an early sleep window promoting the retention of motor skills learned by physical practice and motor imagery, and its generalizability toward the inter-manual transfer of skill after action observation. Findings may further have practical impacts with the development of non-physical rehabilitation interventions for patients having to remaster skills following peripherical or brain injury.
... Although our optogenetic fMRI results did not provide direct access to memory representations per se, they did capture various regions and networks that were likely involved in different memory representations, which cannot be fully revealed by any simplified memory experiments. For example, while activated regions in basal ganglia (e.g., CPu) are less likely to be involved in representing sensory-related memory compared to the sensorimotor thalamocortical regions and limbic regions [49][50][51][52][53] , they could participate in procedural memory (e.g., motor sequences) 27,34,69,70 . ...
... Based on these results, we speculate that interregional interactions between these regions and distributed neuronal populations over other key targets of the additionally-evoked thalamocortical spindle-like activities participated in such processes 16,32,88,89 . At the systems level, such interactions could be reflected in variations of long-range functional connectivity measured by rsfMRI 18,69,90 or electrophysiology 23,70 . ...
... rsfMRI constitutes the most robust, quantitative and non-invasive measurement tool for large-scale, brain-wide functional connectivity or networks that can reflect inter-regional integration of memory information 2,18,69,90 . Examining the effects of thalamo-cortical spindlelike activities on brain-wide rsfMRI connectivity will provide important clues about how they may organize inter-regional information integration to promote memory consolidation at systems level 5,27,28 . ...
As a key oscillatory activity in the brain, thalamic spindle activities are long believed to support memory consolidation. However, their propagation characteristics and causal actions at systems level remain unclear. Using functional MRI (fMRI) and electrophysiology recordings in male rats, we found that optogenetically-evoked somatosensory thalamic spindle-like activities targeted numerous sensorimotor (cortex, thalamus, brainstem and basal ganglia) and non-sensorimotor limbic regions (cortex, amygdala, and hippocampus) in a stimulation frequency- and length-dependent manner. Thalamic stimulation at slow spindle frequency (8 Hz) and long spindle length (3 s) evoked the most robust brain-wide cross-modal activities. Behaviorally, evoking these global cross-modal activities during memory consolidation improved visual-somatosensory associative memory performance. More importantly, parallel visual fMRI experiments uncovered response potentiation in brain-wide sensorimotor and limbic integrative regions, especially superior colliculus, periaqueductal gray, and insular, retrosplenial and frontal cortices. Our study directly reveals that thalamic spindle activities propagate in a spatiotemporally specific manner and that they consolidate associative memory by strengthening multi-target memory representation.
... Typically, the striatum is known for its participation in acquisition, consolidation, and retrieval of motor memories, especially in sequential motor tasks (Doyon et al., 2009). Offline gains correlate with increased striatal activity during and after sleep (Debas et al., 2010;Peigneux et al., 2003;Vahdat et al., 2017). However, there is also evidence for a contribution of the putamen to certain episodic memory tasks, particularly at later learning stages (Sadeh et al., 2011;Scimeca & Badre, 2012;Wang & Voss, 2014). ...
Sleep benefits memory performance by fostering systems consolidation, a process that embeds memories into neocortical networks and renders them independent of the hippocampus. Recent evidence shows that memory rehearsal during wakefulness likewise initiates systems consolidation and rapidly engenders neocortical engrams. Here, we investigate the effect of sleep-dependent consolidation for memories that have undergone rapid systems consolidation during wakefulness. After sleep compared to wakefulness, we find better memory retention and higher functional brain activity during memory retrieval in the medial parietal cortex, which hosts memory representations after rehearsal, and in the striatum and thalamus. Increased striatal and thalamic contributions were correlated with higher retrieval performance. Furthermore, all three regions decreased their functional connectivity to the hippocampus specifically after sleep. These findings show that besides continuing of systems consolidation initiated during wakefulness, sleep also acts to integrate different memory systems. Thus, rehearsal-induced and sleep-dependent consolidation seem to be complementary in nature.
... Given these complex interactions between brain areas, resting-state functional connectivity approaches provide a useful way to assess system-level memory consolidation. Assessing the functional connectivity among these brain regions has further revealed the transformation process that occurs over the course of sleep-dependent memory consolidation (Vahdat et al. 2017;Fang et al. 2021;Samanta et al. 2021). For example, taking a short daytime nap (as compared with remaining awake) after learning a novel motor procedural skill enhances both offline gains in performance and the functional connectivity between the putamen and motor cortical areas ). ...
... For example, taking a short daytime nap (as compared with remaining awake) after learning a novel motor procedural skill enhances both offline gains in performance and the functional connectivity between the putamen and motor cortical areas ). In addition, simultaneous EEG-fMRI sleep recording studies have shown that functional connectivity increases only during periods of NREM sleep, but not wake, in subcortical areas involved in the consolidation of procedural memories (Vahdat et al. 2017). Moreover, the putamen was found to be a central hub for this increased connectivity that occurred exclusively during postlearning sleep, and the strength of this connectivity was related to offline gains in performance (Vahdat et al. 2017). ...
... In addition, simultaneous EEG-fMRI sleep recording studies have shown that functional connectivity increases only during periods of NREM sleep, but not wake, in subcortical areas involved in the consolidation of procedural memories (Vahdat et al. 2017). Moreover, the putamen was found to be a central hub for this increased connectivity that occurred exclusively during postlearning sleep, and the strength of this connectivity was related to offline gains in performance (Vahdat et al. 2017). Thus, changes in functional connectivity can provide insight into how sleep is involved in the enhancement and reorganization process that supports systemlevel memory consolidation. ...
Sleep consolidates procedural memory for motor skills, and this process is associated with strengthened functional connectivity in hippocampal–striatal–cortical areas. It is unknown whether similar processes occur for procedural memory that requires cognitive strategies needed for problem-solving. It is also unclear whether a full night of sleep is indeed necessary for consolidation to occur, compared with a daytime nap. We examined how resting-state functional connectivity within the hippocampal–striatal–cortical network differs after offline consolidation intervals of sleep, nap, or wake. Resting-state fMRI data were acquired immediately before and after training on a procedural problem-solving task that requires the acquisition of a novel cognitive strategy and immediately prior to the retest period (i.e., following the consolidation interval). ROI to ROI and seed to whole-brain functional connectivity analyses both specifically and consistently demonstrated strengthened hippocampal–prefrontal functional connectivity following a period of sleep versus wake. These results were associated with task-related gains in behavioral performance. Changes in functional communication were also observed between groups using the striatum as a seed. Here, we demonstrate that at the behavioral level, procedural strategies benefit from both a nap and a night of sleep. However, a full night of sleep is associated with enhanced functional communication between regions that support problem-solving skills.
