Location-specific cortical activation changes during sleep after training for perceptual learning

NREM sleep improves behavioral performance by desynchronizing cortical circuits

Sleep improves cognitive performance, yet little is known about the neural mechanisms of this improvement. We performed multielectrode recording in macaque visual and dorsolateral prefrontal cortex while animals performed a visual discrimination task before and after non-rapid eye movement (NREM) sleep. Although sleep induces synchronized fluctuations in population activity across cortical areas, the post-sleep population activity became more desynchronized relative to the pre-sleep state. The changes after sleep were correlated with an increase in information encoded in population activity in each area and improved behavioral performance. Electrically stimulating visual cortex at 4 hertz emulated the beneficial effects of sleep on network and perceptual performance. A large-scale neural network model indicated that asymmetric depression of local intracortical synapses is consistent with the observed changes in neural activity after sleep.

Distinct Neural Plasticity Enhancing Visual Perception

The developed human brain shows remarkable plasticity following perceptual learning, resulting in improved visual sensitivity. However, such improvements commonly require extensive stimuli exposure. Here we show that efficiently enhancing visual perception with minimal stimuli exposure recruits distinct neural mechanisms relative to standard repetition-based learning. Participants (n = 20, 12 women, 8 men) encoded a visual discrimination task, followed by brief memory reactivations of only five trials each performed on separate days, demonstrating improvements comparable with standard repetition-based learning (n = 20, 12 women, 8 men). Reactivation-induced learning engaged increased bilateral intraparietal sulcus (IPS) activity relative to repetition-based learning. Complementary evidence for differential learning processes was further provided by temporal-parietal resting functional connectivity changes, which correlated with behavioral improvements. The results suggest that efficiently enhancing visual perception with minimal stimuli exposure recruits distinct neural processes, engaging higher-order control and attentional resources while leading to similar perceptual gains. These unique brain mechanisms underlying improved perceptual learning efficiency may have important implications for daily life and in clinical conditions requiring relearning following brain damage.

First-night effect reduces the beneficial effects of sleep on visual plasticity and modifies the underlying neurochemical processes

Individuals experience difficulty falling asleep in a new environment, termed the first night effect (FNE). However, the impact of the FNE on sleep-induced brain plasticity remains unclear. Here, using a within-subject design, we found that the FNE significantly reduces visual plasticity during sleep in young adults. Sleep-onset latency (SOL), an indicator of the FNE, was significantly longer during the first sleep session than the second session, confirming the FNE. We assessed performance gains in visual perceptual learning after sleep and increases in the excitatory-to-inhibitory neurotransmitter (E/I) ratio in early visual areas during sleep using magnetic resonance spectroscopy and polysomnography. These parameters were significantly smaller in sleep with the FNE than in sleep without the FNE; however, these parameters were not correlated with SOL. These results suggest that while the neural mechanisms of the FNE and brain plasticity are independent, sleep disturbances temporarily block the neurochemical process fundamental for brain plasticity.

Enabling identification of component processes in perceptual learning with nonparametric hierarchical Bayesian modeling

Perceptual learning is a multifaceted process, encompassing general learning, between-session forgetting or consolidation, and within-session fast relearning and deterioration. The learning curve constructed from threshold estimates in blocks or sessions, based on tens or hundreds of trials, may obscure component processes; high temporal resolution is necessary. We developed two nonparametric inference procedures: a Bayesian inference procedure (BIP) to estimate the posterior distribution of contrast threshold in each learning block for each learner independently and a hierarchical Bayesian model (HBM) that computes the joint posterior distribution of contrast threshold across all learning blocks at the population, subject, and test levels via the covariance of contrast thresholds across blocks. We applied the procedures to the data from two studies that investigated the interaction between feedback and training accuracy in Gabor orientation identification over 1920 trials across six sessions and estimated learning curve with block sizes L = 10, 20, 40, 80, 160, and 320 trials. The HBM generated significantly better fits to the data, smaller standard deviations, and more precise estimates, compared to the BIP across all block sizes. In addition, the HBM generated unbiased estimates, whereas the BIP only generated unbiased estimates with large block sizes but exhibited increased bias with small block sizes. With L = 10, 20, and 40, we were able to consistently identify general learning, between-session forgetting, and rapid relearning and adaptation within sessions. The nonparametric HBM provides a general framework for fine-grained assessment of the learning curve and enables identification of component processes in perceptual learning.

Auditory stimulation during REM sleep modulates REM electrophysiology and cognitive performance

REM sleep is critical for memory, emotion, and cognition. Manipulating brain activity during REM could improve our understanding of its function and benefits. Earlier studies have suggested that auditory stimulation in REM might modulate REM time and reduce rapid eye movement density. Building on this, we studied the cognitive effects and electroencephalographic responses related to such stimulation. We used acoustic stimulation locked to eye movements during REM and compared two overnight conditions (stimulation and no-stimulation). We evaluated the impact of this stimulation on REM sleep duration and electrophysiology, as well as two REM-sensitive memory tasks: visual discrimination and mirror tracing. Our results show that this auditory stimulation in REM decreases the rapid eye movements that characterize REM sleep and improves performance on the visual task but is detrimental to the mirror tracing task. We also observed increased beta-band activity and decreased theta-band activity following stimulation. Interestingly, these spectral changes were associated with changes in behavioural performance. These results show that acoustic stimulation can modulate REM sleep and suggest that different memory processes underpin its divergent impacts on cognitive performance.

First-night effect reduces the beneficial effects of sleep on visual plasticity and modifies the underlying neurochemical processes

Individuals experience difficulty falling asleep in a new environment, termed the first night effect (FNE). However, the impact of the FNE on sleep-induced brain plasticity remains unclear. Here, using a within-subject design, we found that the FNE significantly reduces visual plasticity during sleep in young adults. Sleep-onset latency (SOL), an indicator of the FNE, was significantly longer during the first sleep session than the second session, confirming the FNE. We assessed performance gains in visual perceptual learning after sleep and increases in the excitatory-to-inhibitory neurotransmitter (E/I) ratio in early visual areas during sleep using magnetic resonance spectroscopy and polysomnography. These parameters were significantly smaller in sleep with the FNE than in sleep without the FNE; however, these parameters were not correlated with SOL. These results suggest that while the neural mechanisms of the FNE and brain plasticity are independent, sleep disturbances temporarily block the neurochemical process fundamental for brain plasticity.

Plasticity-stability dynamics during post-training processing of learning

Learning continues beyond the end of training. Post-training learning is supported by changes in plasticity and stability in the brain during both wakefulness and sleep. However, the lack of a unified measure for assessing plasticity and stability dynamics during training and post-training periods has limited our understanding of how these dynamics shape learning. Focusing primarily on procedural learning, we integrate work using behavioral paradigms and a recently developed measure, the excitatory-to-inhibitory (E/I) ratio, to explore the delicate balance between plasticity and stability and its relationship to post-training learning. This reveals plasticity-stability cycles during both wakefulness and sleep that enhance learning and protect it from new learning during post-training processing.

A meta-analysis of the relation between dream content and memory consolidation

The frequent appearance of newly learned information in dreams suggests that dream content is influenced by memory consolidation. Many studies have tested this hypothesis by asking whether dreaming about a learning task is associated with improved memory, but results have been inconsistent. We conducted a meta-analysis to determine the strength of the association between learning-related dreams and post-sleep memory improvement. We searched the literature for studies that (1) trained participants on a pre-sleep learning task and then tested their memory after sleep, and (2) associated post-sleep memory improvement with the extent to which dreams incorporated learning task content. Sixteen studies qualified for inclusion, which together reported 45 effects. Integrating across effects, we report a strong and statistically significant association between task-related dreaming and memory performance (SMD = 0.51 [95% CI 0.28, 0.74], p < 0.001). Among studies using polysomnography, this relationship was statistically significant for dreams collected from non-rapid eye movement (NREM) sleep (n = 10) but not for dreams collected from rapid eye movement (REM) sleep (n = 12). There was a significant association between dreaming and memory for all types of learning tasks studied. This meta-analysis provides further evidence that dreaming about a learning task is associated with improved memory performance, suggesting that dream content may be an indication of memory consolidation. Furthermore, we report preliminary evidence that the relationship between dreaming and memory may be stronger in NREM sleep compared to REM.

Estimating the Trial-by-Trial Learning Curve in Perceptual Learning with Hierarchical Bayesian Modeling

The learning curve serves as a crucial metric for assessing human performance in perceptual learning. It may encompass various component processes, including general learning, between-session forgetting or consolidation, and within-session rapid relearning and adaptation or deterioration. Typically, empirical learning curves are constructed by aggregating tens or hundreds of trials of data in blocks or sessions. Here, we devised three inference procedures for estimating the trial-by-trial learning curve based on the multi-component functional form identified in Zhao et al. (submitted): general learning, between-session forgetting, and within-session rapid relearning and adaptation. These procedures include a Bayesian inference procedure (BIP) estimating the posterior distribution of parameters for each learner independently, and two hierarchical Bayesian models (HBMv and HBMc) computing the joint posterior distribution of parameters and hyperparameters at the population, subject, and test levels. The HBMv and HBMc incorporate variance and covariance hyperparameters, respectively, between and within subjects. We applied these procedures to data from two studies investigating the interaction between feedback and training accuracy in Gabor orientation identification across about 2000 trials spanning six sessions (Liu et al., 2010, 2012) and estimated the trial-by-trial learning curves at both the subject and population levels. The HBMc generated best fits to the data and the smallest half width of 68.2% credible interval of the learning curves compared to the BIP and HBMv. The parametric HBMc with the multi-component functional form provides a general framework for trial-by-trial analysis of the component processes in perceptual learning and for predicting the learning curve in unmeasured time points.

Modulating temporal dynamics of performance across retinotopic locations enhances the generalization of perceptual learning

Human visual perception can be improved through perceptual learning. However, such learning is often specific to stimulus and learning conditions. Here, we explored how temporal dynamics of performance across conditions impact learning generalization. Participants performed a visual task, with the target at retinotopic location A. Then, the target was presented at location B either immediately after location A (same-session performance) or following a 48h consolidation period (different-session performance). Long-term generalization was measured the following week. Following initial training, both groups demonstrated generalization, consistent with previous accounts of fast learning. However, long-term generalization was enhanced in the same-session performance group. Consistently, improvements at locations A and B were correlated only following same-session performance, implying an integrated learning process across locations. The results support a new account of perceptual learning and generalization dynamics, suggesting that the temporal proximity of learning and consolidation of different conditions may integrate correlated learning processes, facilitating generalized learning.

Only cortical prediction error signals are involved in visual learning, despite availability of subcortical prediction error signals

Both the midbrain systems, encompassing the ventral striatum (VS), and the cortical systems, including the dorsal anterior cingulate cortex (dACC), play roles in reinforcing and enhancing learning. However, the specific contributions of signals from these regions in learning remains unclear. To investigate this, we examined how VS and dACC are involved in visual perceptual learning (VPL) through an orientation discrimination task. In the primary experiment, subjects fasted for 5 hours before each of 14 days of training sessions and 3 days of test sessions. Subjects were rewarded with water for accurate trial responses. During the test sessions, BOLD signals were recorded from regions including VS and dACC. Although BOLD signals in both areas were associated with positive and negative RPEs, only those in dACC associated with negative RPE showed a significant correlation with performance improvement. Additionally, no significant correlation was observed between BOLD signals associated with RPEs in VS and dACC. These results suggest that although signals associated with positive and negative RPEs from both midbrain and cortical systems are readily accessible, only RPE signals in the prefrontal system, generated without linking to RPE signals in VS, are utilized for the enhancement of VPL.

Developmental atlas of phase-amplitude coupling between physiologic high-frequency oscillations and slow waves

We investigated the developmental changes in high-frequency oscillation (HFO) and Modulation Index (MI) - the coupling measure between HFO and slow-wave phase. We generated normative brain atlases, using subdural EEG signals from 8251 nonepileptic electrode sites in 114 patients (ages 1.0-41.5 years) who achieved seizure control following resective epilepsy surgery. We observed a higher MI in the occipital lobe across all ages, and occipital MI increased notably during early childhood. The cortical areas exhibiting MI co-growth were connected via the vertical occipital fasciculi and posterior callosal fibers. While occipital HFO rate showed no significant age-association, the temporal, frontal, and parietal lobes exhibited an age-inversed HFO rate. Assessment of 1006 seizure onset sites revealed that z-score normalized MI and HFO rate were higher at seizure onset versus nonepileptic electrode sites. We have publicly shared our intracranial EEG data to enable investigators to validate MI and HFO-centric presurgical evaluations to identify the epileptogenic zone.

Selective Enhancement of Post-Sleep Visual Motion Perception by Repetitive Tactile Stimulation during Sleep

Tactile sensations can bias visual perception in the awake state while visual sensitivity is known to be facilitated by sleep. It remains unknown, however, whether the tactile sensation during sleep can bias the visual improvement after sleep. Here, we performed nap experiments in human participants (n = 56, 18 males, 38 females) to demonstrate that repetitive tactile motion stimulation on the fingertip during slow wave sleep selectively enhanced subsequent visual motion detection. The visual improvement was associated with slow wave activity. The high activation at the high beta frequency was found in the occipital electrodes after the tactile motion stimulation during sleep, indicating a visual-tactile cross-modal interaction during sleep. Furthermore, a second experiment (n = 14, 14 females) to examine whether a hand- or head-centered coordination is dominant for the interpretation of tactile motion direction showed that the biasing effect on visual improvement occurs according to the hand-centered coordination. These results suggest that tactile information can be interpreted during sleep, and can induce the selective improvement of post-sleep visual motion detection.SIGNIFICANCE STATEMENT Tactile sensations can bias our visual perception as a form of cross-modal interaction. However, it was reported only in the awake state. Here we show that repetitive directional tactile motion stimulation on the fingertip during slow wave sleep selectively enhanced subsequent visual motion perception. Moreover, the visual improvement was positively associated with sleep slow wave activity. The tactile motion stimulation during slow wave activity increased the activation at the high beta frequency over the occipital electrodes. The visual improvement occurred in agreement with a hand-centered reference frame. These results suggest that our sleeping brain can interpret tactile information based on a hand-centered reference frame, which can cause the sleep-dependent improvement of visual motion detection.

Simple contextual cueing prevents retroactive interference in short-term perceptual training of orientation detection tasks

Perceptual training of multiple tasks suffers from interference between the trained tasks. Here, we conducted five psychophysical experiments with separate groups of participants to investigate the possibility of preventing the interference in short-term perceptual training. We trained the participants to detect two orientations of Gabor stimuli in two adjacent days at the same retinal location and examined the interference of training effects between the two orientations. The results showed significant retroactive interference from the second orientation to the first orientation (Experiment 1 and Experiment 2). Introducing a 6-h interval between the pre-test and training of the second orientation did not eliminate the interference effect, excluding the interpretation of disrupted reconsolidation as the pre-test of the second orientation may reactivate and destabilize the representation of the first orientation (Experiment 3). Finally, the training of the two orientations was accompanied by fixations in two colors, each serving as a contextual cue for one orientation. The results showed that the retroactive interference was not evident if the participants passively perceived contextual cues during the training and test sessions (Experiment 4). Importantly, this facilitation effect could be observed if the contextual cues appeared only during the training, demonstrating the robustness of the effect (Experiment 5). Our findings suggest that the retroactive interference effect in short-term perceptual training of orientation detection tasks was likely the result of higher-level factors such as shared contextual cues embedded in the tasks. The efficiency of multiple perceptual trainings could be facilitated by associating the trained tasks with different contextual cues.

Identifying Long- and Short-Term Processes in Perceptual Learning

Practice makes perfect in almost all perceptual tasks, but how perceptual improvements accumulate remains unknown. Here, we developed a multicomponent theoretical framework to model contributions of both long- and short-term processes in perceptual learning. Applications of the framework to the block-by-block learning curves of 49 adult participants in seven perceptual tasks identified ubiquitous long-term general learning and within-session relearning in most tasks. More importantly, we also found between-session forgetting in the vernier-offset discrimination, face-view discrimination, and auditory-frequency discrimination tasks; between-session off-line gain in the visual shape search task; and within-session adaptation and both between-session forgetting and off-line gain in the contrast detection task. The main results of the vernier-offset discrimination and visual shape search tasks were replicated in a new experiment. The multicomponent model provides a theoretical framework to identify component processes in perceptual learning and a potential tool to optimize learning in normal and clinical populations.

Exogenous attention generalizes location transfer of perceptual learning in adults with amblyopia

Visual perceptual learning (VPL) is a behavioral manifestation of brain neuroplasticity. However, its practical effectiveness is limited because improvements are often specific to the trained conditions and require significant time and effort. It is critical to understand the conditions that promote learning and transfer. Covert endogenous (voluntary) and exogenous (involuntary) spatial attention help overcome VPL location specificity in neurotypical adults, but whether they also do so for people with atypical visual development is unknown. This study investigates the role of exogenous attention during VPL in adults with amblyopia, an ideal population given their asymmetrically developed, but highly plastic, visual cortex. Here we show that training on a discrimination task leads to improvements in foveal contrast sensitivity, acuity, and stereoacuity. Notably, exogenous attention helps generalize learning beyond trained spatial locations. Future large-scale studies can verify the extent to which attention enhances the effectiveness of perceptual learning during rehabilitation of visual disorders.

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Contrast sensitivity (CS)-based VPL in amblyopes improves CS, acuity and stereoacuity

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Similar improvement in trained amblyopic eye and untrained fellow eye

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Exogenous spatial attention facilitates location transfer of VPL in amblyopic adults

Coregistration of magnetic resonance spectroscopy and polysomnography for sleep analysis in human subjects

We developed a protocol for simultaneous magnetic resonance spectroscopy (MRS) and polysomnography (PSG) recordings while subjects are in sleep. The approach is useful to estimate plasticity-stability balances by measuring neurochemical changes in the brain during sleep. We detail the steps needed to minimize artifacts in PSG recordings and the setup and coregistration of MRS data to sleep stages. We also describe useful information for various types of electroencephalogram (EEG) experiments in magnetic resonance imaging (MRI) environments. For complete details on the use and execution of this protocol, please refer to Tamaki et al. (2020b).

Occipital sleep spindles predict sequence learning in a visuo-motor task

STUDY OBJECTIVES

The brain appears to use internal models to successfully interact with its environment via active predictions of future events. Both internal models and the predictions derived from them are based on previous experience. However, it remains unclear how previously encoded information is maintained to support this function, especially in the visual domain. In the present study, we hypothesized that sleep consolidates newly encoded spatio-temporal regularities to improve predictions afterwards.

METHODS

We tested this hypothesis using a novel sequence-learning paradigm that aimed to dissociate perceptual from motor learning. We recorded behavioral performance and high-density electroencephalography (EEG) in male human participants during initial training and during testing two days later, following an experimental night of sleep (n = 16, including high-density EEG recordings) or wakefulness (n = 17).

RESULTS

Our results show sleep-dependent behavioral improvements correlated with sleep-spindle activity specifically over occipital cortices. Moreover, event-related potential (ERP) responses indicate a shift of attention away from predictable to unpredictable sequences after sleep, consistent with enhanced automaticity in the processing of predictable sequences.

CONCLUSIONS

These findings suggest a sleep-dependent improvement in the prediction of visual sequences, likely related to visual cortex reactivation during sleep spindles. Considering that controls in our experiments did not fully exclude oculomotor contributions, future studies will need to address the extent to which these effects depend on purely perceptual versus oculomotor sequence learning.

Reward biases spontaneous neural reactivation during sleep

Sleep favors the reactivation and consolidation of newly acquired memories. Yet, how our brain selects the noteworthy information to be reprocessed during sleep remains largely unknown. From an evolutionary perspective, individuals must retain information that promotes survival, such as avoiding dangers, finding food, or obtaining praise or money. Here, we test whether neural representations of rewarded (compared to non-rewarded) events have priority for reactivation during sleep. Using functional MRI and a brain decoding approach, we show that patterns of brain activity observed during waking behavior spontaneously reemerge during slow-wave sleep. Critically, we report a privileged reactivation of neural patterns previously associated with a rewarded task (i.e., winning at a complex game). Moreover, during sleep, activity in task-related brain regions correlates with better subsequent memory performance. Our study uncovers a neural mechanism whereby rewarded life experiences are preferentially replayed and consolidated while we sleep.

Failure of resting-state frontal-occipital connectivity in linking visual perception with reading fluency in Chinese children with developmental dyslexia

It is widely accepted that impairment in visual perception impedes children's reading development, and further studies have demonstrated significant enhancement in reading fluency after visual perceptual training. However, the mechanism of the neural linkage between visual perception and reading is unclear. The purpose of this study was to examine the intrinsic functional relationship between visual perception (indexed by the texture discrimination task,TDT) and reading ability (character reading and reading fluency) in Chinese children with developmental dyslexia (DD) and those with typical development (TD). The resting-state functional connectivity (RSFC) between the primary visual cortex (V1, BA17) and the entire brain was analyzed. In addition, how RSFC maps are associated with TDT performance and reading ability in the DD and TD groups was examined. The results demonstrated that the strength of the RSFC between V1 and the left middle frontal gyrus (LMFG, BA9/BA46) was significantly correlated with both the threshold (SOA) of the TDT and reading fluency in TD children but not in DD children. Moreover, LMFG-V1 resting-state connectivity played a mediating role in the association of visual texture discrimination and reading fluency, but not in character reading, in TD children. In contrast, this mediation was absent in DD children, albeit their strengths of RSFC between V1 and the left middle frontal gyrus (LMFG) were comparable to those for the TD group. These findings indicate that typically developing children use the linkage of the RSFC between the V1 and LMFG for visual perception skills, which in turn promote fluent reading; in contrast, children with dyslexia, who had higher TDT thresholds than TD children, could not take advantage of their frontal-occipital connectivity to improve reading fluency abilities. These findings suggest that visual perception plays an important role in reading skills and that children with developmental dyslexia lack the ability to use their frontal-occipital connectivity to link visual perception with reading fluency.

Training with high perceptual difficulty improves the capacity and fidelity of internal representation in VWM

It has been shown that the capacity of visual working memory (VWM) is a strong predictor of individual intelligence, and researchers have developed various training protocols to improve VWM capacity. However, it seems that whether the fidelity of internal representation in VWM can also be improved by training is largely overlooked in the past literature. Here, we introduced a new training approach that involved increasing the perceptual difficulty of training materials to enhance VWM, and both memory capacity and the fidelity of representation were examined to assess the training efficacy. Participants with normal vision and cognitive abilities received 3-week training on VWM using a change detection task, and the results showed that both the capacity and the fidelity of memory representations were improved for training with perceptually difficult stimuli, while only the fidelity was improved for training with perceptually normal stimuli. In addition, we found that the training effects on memory precision may be subject to capacity constraints. We suggest that long-term adaptive training with perceptually difficult stimuli may facilitate encoding efficiency through familiarizing trainees with an increased baseline of cognitive workload during the encoding process. The present study offers clear evidence that training with high perceptual difficulty is more effective and the improvements in VWM are more stable than training with perceptually normal materials, and the simple manipulation on training stimuli indicates that the method can be generalized to a wider range of training situations and populations.

Early Visual Cortex Stimulation Modifies Well-Consolidated Perceptual Gains

Perception thresholds can improve through repeated practice with visual tasks. Can an already acquired and well-consolidated perceptual skill be noninvasively neuromodulated, unfolding the neural mechanisms involved? Here, leveraging the susceptibility of reactivated memories ranging from synaptic to systems levels across learning and memory domains and animal models, we used noninvasive brain stimulation to neuromodulate well-consolidated reactivated visual perceptual learning and reveal the underlying neural mechanisms. Subjects first encoded and consolidated the visual skill memory by performing daily practice sessions with the task. On a separate day, the consolidated visual memory was briefly reactivated, followed by low-frequency, inhibitory 1 Hz repetitive transcranial magnetic stimulation over early visual cortex, which was individually localized using functional magnetic resonance imaging. Poststimulation perceptual thresholds were measured on the final session. The results show modulation of perceptual thresholds following early visual cortex stimulation, relative to control stimulation. Consistently, resting state functional connectivity between trained and untrained parts of early visual cortex prior to training predicted the magnitude of perceptual threshold modulation. Together, these results indicate that even previously consolidated human perceptual memories are susceptible to neuromodulation, involving early visual cortical processing. Moreover, the opportunity to noninvasively neuromodulate reactivated perceptual learning may have important clinical implications.

Complementary contributions of non-REM and REM sleep to visual learning

Sleep is beneficial for learning. However, it remains unclear whether learning is facilitated by non-REM (NREM) sleep or by REM sleep, whether it results from plasticity increases or stabilization, and whether facilitation results from learning-specific processing. Here, we trained volunteers on a visual task, and measured the excitatory and inhibitory (E/I) balance in early visual areas during subsequent sleep as an index of plasticity. E/I balance increased during NREM sleep irrespective of whether pre-sleep learning occurred, but it was associated with post-sleep performance gains relative to pre-sleep performance. By contrast, E/I balance decreased during REM sleep but only after pre-sleep training, and the decrease was associated with stabilization of pre-sleep learning. These findings indicate that NREM sleep promotes plasticity, leading to performance gains independent of learning, while REM sleep decreases plasticity to stabilize learning in a learning-specific manner.

Transient cholinergic enhancement does not significantly affect either the magnitude or selectivity of perceptual learning of visual texture discrimination

Perceptual learning (PL), often characterized by improvements in perceptual performance with training that are specific to the stimulus conditions used during training, exemplifies experience-dependent cortical plasticity. An improved understanding of how neuromodulatory systems shape PL promises to provide new insights into the mechanisms of plasticity, and by extension how PL can be generated and applied most efficiently. Previous studies have reported enhanced PL in human subjects following administration of drugs that increase signaling through acetylcholine (ACh) receptors, and physiological evidence indicates that ACh sharpens neuronal selectivity, suggesting that this neuromodulator supports PL and its stimulus specificity. Here we explored the effects of enhancing endogenous cholinergic signaling during PL of a visual texture discrimination task. We found that training on this task in the lower visual field yielded significant behavioral improvement at the trained location. However, a single dose of the cholinesterase inhibitor donepezil, administered before training, did not significantly impact either the magnitude or the location specificity of texture discrimination learning compared with placebo. We discuss potential explanations for discrepant findings in the literature regarding the role of ACh in visual PL, including possible differences in plasticity mechanisms in the dorsal and ventral cortical processing streams.

Evidence against a large effect of sleep in protecting verbal memories from interference

The human brain has evolved to acquire novel information rapidly while serving the need to store long-term memories in a stable and lasting form. Presenting interfering information directly after learning can lead to forgetting of the original material. It has been suggested that sleep aids the stabilization of new memories and protects them from interference. Here, we aim to replicate in two separate experiments the claim that sleep protects memories from retroactive interference (Current Biology, 16, 2006 and 1290; PLoS ONE, 4, 2009 and e4117). We let participants study wordlists before letting them sleep for an afternoon nap or for a full night. In a control condition, subjects stayed awake for the same amount of time. After the consolidation interval, participants learnt an interfering wordlist and were tested on memory of the original wordlist. Sleep did not stabilize memory for the original wordlist in either study. We discuss our findings in the light of recent advances in computational neuroscience, and conclude that the stabilizing effect of sleep against interference has been overestimated.

Reward does not facilitate visual perceptual learning until sleep occurs

A growing body of evidence indicates that visual perceptual learning (VPL) is enhanced by reward provided during training. Another line of studies has shown that sleep following training also plays a role in facilitating VPL, an effect known as the offline performance gain of VPL. However, whether the effects of reward and sleep interact on VPL remains unclear. Here, we show that reward interacts with sleep to facilitate offline performance gains of VPL. First, we demonstrated a significantly larger offline performance gain over a 12-h interval including sleep in a reward group than that in a no-reward group. However, the offline performance gains over the 12-h interval without sleep were not significantly different with or without reward during training, indicating a crucial interaction between reward and sleep in VPL. Next, we tested whether neural activations during posttraining sleep were modulated after reward was provided during training. Reward provided during training enhanced rapid eye movement (REM) sleep time, increased oscillatory activities for reward processing in the prefrontal region during REM sleep, and inhibited neural activation in the untrained region in early visual areas in non-rapid eye movement (NREM) and REM sleep. The offline performance gains were significantly correlated with oscillatory activities of visual processing during NREM sleep and reward processing during REM sleep in the reward group but not in the no-reward group. These results suggest that reward provided during training becomes effective during sleep, with excited reward processing sending inhibitory signals to suppress noise in visual processing, resulting in larger offline performance gains over sleep.

Trained-feature-specific offline learning by sleep in an orientation detection task

Training-induced performance gains in a visual perceptual learning (VPL) task that take place during sleep are termed "offline performance gains." Offline performance gains of VPL so far have been reported in the texture discrimination task and other discrimination tasks. This raises the question as to whether offline performance gains on VPL occur exclusively in discrimination tasks. The present study examined whether offline performance gains occur in detection tasks. In Experiment 1, subjects were trained on a Gabor orientation detection task. They were retested after a 12-hr interval, which included either nightly sleep or only wakefulness. Offline performance gains occurred only after sleep on the trained orientation, not on an untrained orientation. In Experiment 2, we tested whether offline performance gains in the detection task occur over a nap using polysomnography. Moreover, we tested whether sigma activity during non-rapid eye movement (NREM) sleep recorded from occipital electrodes, previously implicated in offline performance gains of the texture discrimination task, was associated with the degree of offline performance gains of the Gabor orientation detection task. We replicated offline performance gains on the trained orientation in the detection task over the nap. Sigma activity during NREM sleep was significantly larger in the occipital electrodes relative to control electrodes in correlation with offline performance gains. The results suggest that offline performance gains occur over the sleep period generally in VPL. Moreover, sigma activity in the occipital region during NREM sleep may play an important role in offline performance gains of VPL.

Post-training TMS abolishes performance improvement and releases future learning from interference

The period immediately after the offset of visual training is thought to be critical for memory consolidation. Nevertheless, we still lack direct evidence for the causal role of this period to perceptual learning of either previously or subsequently trained material. To address these issues, we had human subjects complete two consecutive trainings with different tasks (detecting different Gabor orientations). We applied continuous theta burst stimulation (cTBS) to either the visual cortex or a control site (vertex) immediately after the offset of the first training. In the vertex cTBS condition, subjects showed improvement on the first task but not on the second task, suggesting the presence of anterograde interference. Critically, cTBS to the visual cortex abolished the performance improvement on the first task and released the second training from the anterograde interference. These results provide causal evidence for a role of the immediate post-training period in the consolidation of perceptual learning.

The impact of frequent napping and nap practice on sleep-dependent memory in humans

Napping benefits long-term memory formation and is a tool many individuals use to improve daytime functioning. Despite its potential advantages, approximately 47% of people in the United States eschew napping. The goal of this study was to determine whether people who endorse napping at least once a week (nap+) show differences in nap outcomes, including nap-dependent memory consolidation, compared with people who rarely or never nap (nap-). Additionally, we tested whether four weeks of nap practice or restriction would change sleep and performance profiles. Using a perceptual learning task, we found that napping enhanced performance to a greater degree in nap+ compared with nap- individuals (at baseline). Additionally, performance change was associated with different electrophysiological sleep features in each group. In the nap+ group, spindle density was positively correlated with performance improvement, an effect specific to spindles in the hemisphere contralateral to the trained visual field. In the nap- group, slow oscillatory power (0.5-1 Hz) was correlated with performance. Surprisingly, no changes to performance or brain activity during sleep emerged after four weeks of nap practice or restriction. These results suggest that individual differences may impact the potential benefits of napping on performance and the ability to become a better napper.

Feature-Specific Awake Reactivation in Human V1 after Visual Training

Brain activity patterns exhibited during task performance have been shown to spontaneously reemerge in the following restful awake state. Such "awake reactivation" has been observed across higher-order cortex for complex images or associations. However, it is still unclear whether the reactivation extends to primary sensory areas that encode simple stimulus features. To address this question, we trained human subjects from both sexes on a particular visual feature (Gabor orientation) and tested whether this feature will be reactivated immediately after training. We found robust reactivation in human V1 that lasted for at least 8 min after training offset. This effect was not present in higher retinotopic areas, such as V2, V3, V3A, or V4v. Further analyses suggested that the amount of awake reactivation was related to the amount of performance improvement on the visual task. These results demonstrate that awake reactivation extends beyond higher-order areas and also occurs in early sensory cortex.SIGNIFICANCE STATEMENT How do we acquire new memories and skills? New information is known to be consolidated during offline periods of rest. Recent studies suggest that a critical process during this period of consolidation is the spontaneous reactivation of previously experienced patterns of neural activity. However, research in humans has mostly examined such reactivation processes in higher-order cortex. Here we show that awake reactivation occurs even in the primary visual cortex V1 and that this reactivation is related to the amount of behavioral learning. These results pinpoint awake reactivation as a process that likely occurs across the entire human brain and could play an integral role in memory consolidation.

Rates of cerebral protein synthesis in primary visual cortex during sleep-dependent memory consolidation, a study in human subjects

If protein synthesis during sleep is required for sleep-dependent memory consolidation, we might expect rates of cerebral protein synthesis (rCPS) to increase during sleep in the local brain circuits that support performance on a particular task following training on that task. To measure circuit-specific brain protein synthesis during a daytime nap opportunity, we used the L-[1-(11)C]leucine positron emission tomography (PET) method with simultaneous polysomnography. We trained subjects on the visual texture discrimination task (TDT). This was followed by a nap opportunity during the PET scan, and we retested them later in the day after the scan. The TDT is considered retinotopically specific, so we hypothesized that higher rCPS in primary visual cortex would be observed in the trained hemisphere compared to the untrained hemisphere in subjects who were randomized to a sleep condition. Our results indicate that the changes in rCPS in primary visual cortex depended on whether subjects were in the wakefulness or sleep condition but were independent of the side of the visual field trained. That is, only in the subjects randomized to sleep, rCPS in the right primary visual cortex was higher than the left regardless of side trained. Other brain regions examined were not so affected. In the subjects who slept, performance on the TDT improved similarly regardless of the side trained. Results indicate a regionally selective and sleep-dependent effect that occurs with improved performance on the TDT.

Visual perceptual training reconfigures post-task resting-state functional connectivity with a feature-representation region

The neural mechanisms underlying visual perceptual learning (VPL) have typically been studied by examining changes in task-related brain activation after training. However, the relationship between post-task "offline" processes and VPL remains unclear. The present study examined this question by obtaining resting-state functional magnetic resonance imaging (fMRI) scans of human brains before and after a task-fMRI session involving visual perceptual training. During the task-fMRI session, participants performed a motion coherence discrimination task in which they judged the direction of moving dots with a coherence level that varied between trials (20, 40, and 80%). We found that stimulus-induced activation increased with motion coherence in the middle temporal cortex (MT+), a feature-specific region representing visual motion. On the other hand, stimulus-induced activation decreased with motion coherence in the dorsal anterior cingulate cortex (dACC) and bilateral insula, regions involved in decision making under perceptual ambiguity. Moreover, by comparing pre-task and post-task rest periods, we revealed that resting-state functional connectivity (rs-FC) with the MT+ was significantly increased after training in widespread cortical regions including the bilateral sensorimotor and temporal cortices. In contrast, rs-FC with the MT+ was significantly decreased in subcortical regions including the thalamus and putamen. Importantly, the training-induced change in rs-FC was observed only with the MT+, but not with the dACC or insula. Thus, our findings suggest that perceptual training induces plastic changes in offline functional connectivity specifically in brain regions representing the trained visual feature, emphasising the distinct roles of feature-representation regions and decision-related regions in VPL.

Identification of memory reactivation during sleep by EEG classification

Memory reactivation during sleep is critical for consolidation, but also extremely difficult to measure as it is subtle, distributed and temporally unpredictable. This article reports a novel method for detecting such reactivation in standard sleep recordings. During learning, participants produced a complex sequence of finger presses, with each finger cued by a distinct audio-visual stimulus. Auditory cues were then re-played during subsequent sleep to trigger neural reactivation through a method known as targeted memory reactivation (TMR). Next, we used electroencephalography data from the learning session to train a machine learning classifier, and then applied this classifier to sleep data to determine how successfully each tone had elicited memory reactivation. Neural reactivation was classified above chance in all participants when TMR was applied in SWS, and in 5 of the 14 participants to whom TMR was applied in N2. Classification success reduced across numerous repetitions of the tone cue, suggesting either a gradually reducing responsiveness to such cues or a plasticity-related change in the neural signature as a result of cueing. We believe this method will be valuable for future investigations of memory consolidation.

Towards a whole brain model of Perceptual Learning

A hallmark of modern Perceptual Learning (PL) is the extent to which learning is specific to the trained stimuli. Such specificity to orientation, spatial location and even eye of training has been used as psychophysical evidence of the neural basis of learning. This argument that specificity of PL implies regionalization of brain plasticity implicitly assumes that examination of a singular locus of PL is an appropriate approach to understand learning. However, recent research shows that learning effects once thought to be specific depend on subtleties of the training paradigm and that within even a simple training procedure there are multiple aspects of the task and stimuli that are learned simultaneously. Here, we suggest that learning on any task involves a broad network of brain regions undergoing changes in representations, read-out weights, decision rules, attention and feedback processes as well as oculomotor changes. However, importantly, the distribution of learning across the neural system depends upon the details of the training procedure and the characterstics of the individual being trained. We propose that to advance our understanding of PL, the field must move towards understanding how distributed brain processes jointly contribute to behavioral learning effects.

Structural and Functional Connectivity Changes Beyond Visual Cortex in a Later Phase of Visual Perceptual Learning

The neural mechanisms of visual perceptual learning (VPL) remain unclear. Previously we found that activation in the primary visual cortex (V1) increased in the early encoding phase of training, but returned to baseline levels in the later retention phase. To examine neural changes during the retention phase, we measured structural and functional connectivity changes using MRI. After weeks of training on a texture discrimination task, the fractional anisotropy of the inferior longitudinal fasciculus, a major tract connecting visual and anterior areas, was increased, as well as the functional connectivity between V1 and anterior regions mediated by the ILF. These changes were strongly correlated with behavioral performance improvements. These results suggest a two-phase model of VPL in which localized functional changes in V1 in the encoding phase of training are followed by changes in both structural and functional connectivity in ventral visual processing, perhaps leading to the long-term stabilization of VPL.

[Effect of Reading a Book on a Tablet Computer on Cerebral Blood Flow in the Prefrontal Cortex]

OBJECTIVES

By measuring cerebral blood flow in the prefrontal cortex, we aimed to determine how reading a book on a tablet computer affects sleep.

METHODS

Seven students (7 men age range, 21-32 years) participated in this study. In a controlled illuminance environment, the subjects read a novel in printed form or on a tablet computer from any distance. As the subjects were reading, the cerebral blood flow in their prefrontal cortex was measured by near-infrared spectroscopy. The study protocol was as follows. 1) Subjects mentally counted a sequence of numbers for 30 s as a pretest to standardized thinking and then 2) read the novel for 10 min, using the printed book or tablet computer. In step 2), the use of the book or tablet computer was in a random sequence. Subjects rested between the two tasks.

RESULTS

Significantly increased brain activity (increase in regional cerebral blood flow) was observed following reading a novel on a tablet computer compared with that after reading a printed book. Furthermore, the region around Broca's area was more active when reading on a tablet computer than when reading a printed book.

CONCLUSIONS

Considering the results of this study and previous studies on physiological characteristics during nonrapid eye movement sleep, we concluded that reading a book on a tablet computer before the onset of sleep leads to the potential inhibition of sound sleep through mechanisms other than the suppression of melatonin secretion.

Two different mechanisms support selective attention at different phases of training

Selective attention supports the prioritized processing of relevant sensory information to facilitate goal-directed behavior. Studies in human subjects demonstrate that attentional gain of cortical responses can sufficiently account for attention-related improvements in behavior. On the other hand, studies using highly trained nonhuman primates suggest that reductions in neural noise can better explain attentional facilitation of behavior. Given the importance of selective information processing in nearly all domains of cognition, we sought to reconcile these competing accounts by testing the hypothesis that extensive behavioral training alters the neural mechanisms that support selective attention. We tested this hypothesis using electroencephalography (EEG) to measure stimulus-evoked visual responses from human subjects while they performed a selective spatial attention task over the course of ~1 month. Early in training, spatial attention led to an increase in the gain of stimulus-evoked visual responses. Gain was apparent within ~100 ms of stimulus onset, and a quantitative model based on signal detection theory (SDT) successfully linked the magnitude of this gain modulation to attention-related improvements in behavior. However, after extensive training, this early attentional gain was eliminated even though there were still substantial attention-related improvements in behavior. Accordingly, the SDT-based model required noise reduction to account for the link between the stimulus-evoked visual responses and attentional modulations of behavior. These findings suggest that training can lead to fundamental changes in the way attention alters the early cortical responses that support selective information processing. Moreover, these data facilitate the translation of results across different species and across experimental procedures that employ different behavioral training regimes.

Overlearning hyperstabilizes a skill by rapidly making neurochemical processing inhibitory-dominant

Overlearning refers to the continued training of a skill after performance improvement has plateaued. Whether overlearning is beneficial is a question in our daily lives that has never been clearly answered. Here, we report a new important role: Overlearning abruptly changes neurochemical processing to hyper-stabilize and protect trained perceptual learning from subsequent new learning. Usually, learning immediately after training is so unstable that it can be disrupted by subsequent new learning, unless waiting for passive stabilization, which takes hours. However, overlearning so rapidly and strongly stabilizes the learning state that it not only becomes resilient against, but disrupts, subsequent new learning. Such hyper-stabilization is associated with an abrupt shift from glutamate-dominant excitatory to gamma-aminobutyric-acid-dominant inhibitory processing in early visual areas. Hyper-stabilization contrasts with passive and slower stabilization, which is associated with a mere reduction of an excitatory dominance to baseline levels. Utilizing hyper-stabilization may lead to efficient learning paradigms.

Sleep Spindle Characteristics in Children with Neurodevelopmental Disorders and Their Relation to Cognition

Empirical evidence indicates that sleep spindles facilitate neuroplasticity and “off-line” processing during sleep, which supports learning, memory consolidation, and intellectual performance. Children with neurodevelopmental disorders (NDDs) exhibit characteristics that may increase both the risk for and vulnerability to abnormal spindle generation. Despite the high prevalence of sleep problems and cognitive deficits in children with NDD, only a few studies have examined the putative association between spindle characteristics and cognitive function. This paper reviews the literature regarding sleep spindle characteristics in children with NDD and their relation to cognition in light of what is known in typically developing children and based on the available evidence regarding children with NDD. We integrate available data, identify gaps in understanding, and recommend future research directions. Collectively, studies are limited by small sample sizes, heterogeneous populations with multiple comorbidities, and nonstandardized methods for collecting and analyzing findings. These limitations notwithstanding, the evidence suggests that future studies should examine associations between sleep spindle characteristics and cognitive function in children with and without NDD, and preliminary findings raise the intriguing question of whether enhancement or manipulation of sleep spindles could improve sleep-dependent memory and other aspects of cognitive function in this population.

Learning to Associate Orientation with Color in Early Visual Areas by Associative Decoded fMRI Neurofeedback

Associative learning is an essential brain process where the contingency of different items increases after training. Associative learning has been found to occur in many brain regions [1-4]. However, there is no clear evidence that associative learning of visual features occurs in early visual areas, although a number of studies have indicated that learning of a single visual feature (perceptual learning) involves early visual areas [5-8]. Here, via decoded fMRI neurofeedback termed "DecNef" [9], we tested whether associative learning of orientation and color can be created in early visual areas. During 3 days of training, DecNef induced fMRI signal patterns that corresponded to a specific target color (red) mostly in early visual areas while a vertical achromatic grating was physically presented to participants. As a result, participants came to perceive "red" significantly more frequently than "green" in an achromatic vertical grating. This effect was also observed 3-5 months after the training. These results suggest that long-term associative learning of two different visual features such as orientation and color was created, most likely in early visual areas. This newly extended technique that induces associative learning is called "A-DecNef," and it may be used as an important tool for understanding and modifying brain functions because associations are fundamental and ubiquitous functions in the brain.

Neuroimaging Evidence for 2 Types of Plasticity in Association with Visual Perceptual Learning

Visual perceptual learning (VPL) is long-term performance improvement as a result of perceptual experience. It is unclear whether VPL is associated with refinement in representations of the trained feature (feature-based plasticity), improvement in processing of the trained task (task-based plasticity), or both. Here, we provide empirical evidence that VPL of motion detection is associated with both types of plasticity which occur predominantly in different brain areas. Before and after training on a motion detection task, subjects' neural responses to the trained motion stimuli were measured using functional magnetic resonance imaging. In V3A, significant response changes after training were observed specifically to the trained motion stimulus but independently of whether subjects performed the trained task. This suggests that the response changes in V3A represent feature-based plasticity in VPL of motion detection. In V1 and the intraparietal sulcus, significant response changes were found only when subjects performed the trained task on the trained motion stimulus. This suggests that the response changes in these areas reflect task-based plasticity. These results collectively suggest that VPL of motion detection is associated with the 2 types of plasticity, which occur in different areas and therefore have separate mechanisms at least to some degree.

Form and Function of Sleep Spindles across the Lifespan

Since the advent of EEG recordings, sleep spindles have been identified as hallmarks of non-REM sleep. Despite a broad general understanding of mechanisms of spindle generation gleaned from animal studies, the mechanisms underlying certain features of spindles in the human brain, such as “global” versus “local” spindles, are largely unknown. Neither the topography nor the morphology of sleep spindles remains constant throughout the lifespan. It is likely that changes in spindle phenomenology during development and aging are the result of dramatic changes in brain structure and function. Across various developmental windows, spindle activity is correlated with general cognitive aptitude, learning, and memory; however, these correlations vary in strength, and even direction, depending on age and metrics used. Understanding these differences across the lifespan should further clarify how these oscillations are generated and their function under a variety of circumstances. We discuss these issues, and their translational implications for human cognitive function. Because sleep spindles are similarly affected in disorders of neurodevelopment (such as schizophrenia) and during aging (such as neurodegenerative conditions), both types of disorders may benefit from therapies based on a better understanding of spindle function.

Behavioural and neurofunctional impact of transcranial direct current stimulation on somatosensory learning

We investigated the effect of repeated delivery of anodal transcranial direct current stimulation (tDCS) on somatosensory performance and long-term learning. Over the course of five days, tDCS was applied to the primary somatosensory cortex (S1) by means of neuronavigation employing magnetencephalography (MEG). Compared to its sham application, tDCS promoted tactile learning by reducing the two-point discrimination threshold assessed by the grating orientation task (GOT) primarily by affecting intersessional changes in performance. These results were accompanied by alterations in the neurofunctional organization of the brain, as revealed by functional magnetic resonance imaging conducted prior to the study, at the fifth day of tDCS delivery and four weeks after the last application of tDCS. A decrease in activation at the primary site of anodal tDCS delivery in the left S1 along retention of superior tactile acuity was observed at follow-up four weeks after the application of tDCS. Thus, we demonstrate long-term effects that repeated tDCS imposes on somatosensory functioning. This is the first study to provide insight into the mode of operation of tDCS on the brain's response to long-term perceptual learning, adding an important piece of evidence from the domain of non-invasive brain stimulation to show that functional changes detectable by fMRI in primary sensory cortices participate in perceptual learning.

Real-Time Strategy Video Game Experience and Visual Perceptual Learning

Visual perceptual learning (VPL) is defined as long-term improvement in performance on a visual-perception task after visual experiences or training. Early studies have found that VPL is highly specific for the trained feature and location, suggesting that VPL is associated with changes in the early visual cortex. However, the generality of visual skills enhancement attributable to action video-game experience suggests that VPL can result from improvement in higher cognitive skills. If so, experience in real-time strategy (RTS) video-game play, which may heavily involve cognitive skills, may also facilitate VPL. To test this hypothesis, we compared VPL between RTS video-game players (VGPs) and non-VGPs (NVGPs) and elucidated underlying structural and functional neural mechanisms. Healthy young human subjects underwent six training sessions on a texture discrimination task. Diffusion-tensor and functional magnetic resonance imaging were performed before and after training. VGPs performed better than NVGPs in the early phase of training. White-matter connectivity between the right external capsule and visual cortex and neuronal activity in the right inferior frontal gyrus (IFG) and anterior cingulate cortex (ACC) were greater in VGPs than NVGPs and were significantly correlated with RTS video-game experience. In both VGPs and NVGPs, there was task-related neuronal activity in the right IFG, ACC, and striatum, which was strengthened after training. These results indicate that RTS video-game experience, associated with changes in higher-order cognitive functions and connectivity between visual and cognitive areas, facilitates VPL in early phases of training. The results support the hypothesis that VPL can occur without involvement of only visual areas. Significance statement: Although early studies found that visual perceptual learning (VPL) is associated with involvement of the visual cortex, generality of visual skills enhancement by action video-game experience suggests that higher-order cognition may be involved in VPL. If so, real-time strategy (RTS) video-game experience may facilitate VPL as a result of heavy involvement of cognitive skills. Here, we compared VPL between RTS video-game players (VGPs) and non-VGPs (NVGPs) and investigated the underlying neural mechanisms. VGPs showed better performance in the early phase of training on the texture discrimination task and greater level of neuronal activity in cognitive areas and structural connectivity between visual and cognitive areas than NVGPs. These results support the hypothesis that VPL can occur beyond the visual cortex.

Sleep-Dependent Memory Consolidation in Children

In the past 30 years, much research has been conducted elucidating the role of sleep in memory and learning; however, the interaction between sleep and cognitive functioning may be unknown in clinical realms. This article serves to provide a primer on sleep-dependent memory consolidation, a process in which memory is stabilized or even enhanced over a period of sleep. Given the increased amounts of sleep needed in infancy and childhood, the link between sleep and neuronal plasticity is highlighted in this article. Furthermore, sleep disruptions are common to children with neurodevelopmental disorders such as attention-deficit hyperactivity disorder; thus, recent studies showing direct relationships between sleep and memory functioning in such vulnerable groups are discussed.

Cued memory reactivation during slow-wave sleep promotes explicit knowledge of a motor sequence

Memories are gradually consolidated after initial encoding, and this can sometimes lead to a transition from implicit to explicit knowledge. The exact physiological processes underlying this reorganization remain unclear. Here, we used a serial reaction time task to determine whether targeted memory reactivation (TMR) of specific memory traces during slow-wave sleep promotes the emergence of explicit knowledge. Human participants learned two 12-item sequences of button presses (A and B). These differed in both cue order and in the auditory tones associated with each of the four fingers (one sequence had four higher-pitched tones). Subsequent overnight sleep was monitored, and the tones associated with one learned sequence were replayed during slow-wave sleep. After waking, participants demonstrated greater explicit knowledge (p = 0.005) and more improved procedural skill (p = 0.04) for the cued sequence relative to the uncued sequence. Furthermore, fast spindles (13.5-15 Hz) at task-related motor regions predicted overnight enhancement in procedural skill (r = 0.71, p = 0.01). Auditory cues had no effect on post-sleep memory performance in a control group who received TMR before sleep. These findings suggest that TMR during sleep can alter memory representations and promote the emergence of explicit knowledge, supporting the notion that reactivation during sleep is a key mechanism in this process.