Spindle-dependent memory consolidation in healthy adults: A meta-analysis.

Accumulating evidence suggests a central role for sleep spindles in the consolidation of new memories. However, no meta-analysis of the association between sleep spindles and memory performance has been conducted so far. Here, we report meta-analytical evidence for spindle-memory associations and investigate how multiple factors, including memory type, spindle type, spindle characteristics, and EEG topography affect this relationship. The literature search yielded 53 studies reporting 1427 effect sizes, resulting in a small to moderate effect for the average association. We further found that spindle-memory associations were significantly stronger for procedural memory than for declarative memory. Neither spindle types nor EEG scalp topography had an impact on the strength of the spindle-memory relation, but we observed a distinct functional role of global and fast sleep spindles, especially for procedural memory. We also found a moderation effect of spindle characteristics, with power showing the largest effect sizes. Collectively, our findings suggest that sleep spindles are involved in learning, thereby representing a general physiological mechanism for memory consolidation.

Continuously changing memories: a framework for proactive and non-linear consolidation.

The traditional view of long-term memory is that memory traces mature in a predetermined 'linear' process: their neural substrate shifts from rapidly plastic medial temporal regions towards stable neocortical networks. We propose that memories remain malleable, not by repeated reinstantiations of this linear process but instead via dynamic routes of proactive and non-linear consolidation: memories change, their trajectory is flexible and reversible, and their physical basis develops continuously according to anticipated demands. Studies demonstrating memory updating, increasing hippocampal dependence to support adaptive use, and rapid neocortical plasticity provide evidence for continued non-linear consolidation. Although anticipated demand can affect all stages of memory formation, the extent to which it shapes the physical memory trace repeatedly and proactively will require further dedicated research.

On the extraction of purely motor EEG neural correlates during an upper limb visuomotor task.

Deciphering and analyzing the neural correlates of different movements from the same limb using electroencephalography (EEG) would represent a notable breakthrough in the field of sensorimotor neurophysiology. Functional movements involve concurrent posture co-ordination and head and eye movements, which create electrical activity that affects EEG recordings. In this paper, we revisit the identification of brain signatures of different reaching movements using EEG and present, test, and validate a protocol to separate the effect of head and eye movements from a reaching task-related visuomotor brain activity. Ten healthy participants performed reaching movements under two different conditions: avoiding head and eye movements and moving with no constrains. Reaching movements can be identified from EEG with unconstrained eye and head movement, whereas the discriminability of the signals drops to chance level otherwise. These results show that neural patterns associated with different arm movements could only be extracted from EEG if the eye and head movements occurred concurrently with the task, polluting the recordings. Although these findings do not imply that brain correlates of reaching directions cannot be identified from EEG, they show the consequences that ignoring these events can have in any EEG study that includes a visuomotor task.

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.

Sleep Spindles and Memory Reprocessing.

We propose a framework for the memory function of spindle oscillations during sleep. In this framework, memories are reinstated by spindle events and further reprocessed during subsequent spindle refractory periods. We posit that spindle refractoriness is crucial for protecting memory reprocessing from interference. We further argue that temporally-coordinated spindle refractory periods across local networks facilitate the consolidation of rich, multimodal representations, and that localized spindle refractoriness optimizes oscillatory interactions that support systems consolidation in the sleeping brain.

Sleep spindles.

Schönauer and Pöhlchen introduce the reader to sleep spindles, brain oscillations that occur during nREM sleep that are thought to function in the stabilization of memories.

Multivariate classification of neuroimaging data with nested subclasses: Biased accuracy and implications for hypothesis testing.

Biological data sets are typically characterized by high dimensionality and low effect sizes. A powerful method for detecting systematic differences between experimental conditions in such multivariate data sets is multivariate pattern analysis (MVPA), particularly pattern classification. However, in virtually all applications, data from the classes that correspond to the conditions of interest are not homogeneous but contain subclasses. Such subclasses can for example arise from individual subjects that contribute multiple data points, or from correlations of items within classes. We show here that in multivariate data that have subclasses nested within its class structure, these subclasses introduce systematic information that improves classifiability beyond what is expected by the size of the class difference. We analytically prove that this subclass bias systematically inflates correct classification rates (CCRs) of linear classifiers depending on the number of subclasses as well as on the portion of variance induced by the subclasses. In simulations, we demonstrate that subclass bias is highest when between-class effect size is low and subclass variance high. This bias can be reduced by increasing the total number of subclasses. However, we can account for the subclass bias by using permutation tests that explicitly consider the subclass structure of the data. We illustrate our result in several experiments that recorded human EEG activity, demonstrating that parametric statistical tests as well as typical trial-wise permutation fail to determine significance of classification outcomes correctly.

Incubation, not sleep, aids problem-solving.

Solving a novel problem and finding innovative solutions requires a flexible and creative recombination of prior knowledge. It is thought that setting a problem aside before giving it another try aids problem-solving. The underlying mechanisms of such an incubation period could include unconscious processing that fosters spreading activation along associated networks and the restructuring of problem representations. Recently, it has been suggested that sleep may also support problem-solving by supporting the transformation and restructuring of memory elements. Since the effect of sleep on problem-solving has been mainly tested using the Remote Associates Test, we chose three different tasks-classical riddles, visual change detection, and anagrams-to examine various aspects of problem-solving and to pinpoint task-specific prerequisites for effects of sleep or incubation to emerge. Sixty-two participants were given two attempts to solve the problems. Both attempts either occurred consecutively or were spaced apart by a 3-hour incubation interval that was spent awake or asleep. We found that a period of incubation positively affected solutions rates in classical riddles, but not in visual change detection or anagram solving. Contrary to our hypothesis, spending the incubation period asleep, did not yield any additional benefit. Our study thus supports the notion that a period of letting a problem rest is beneficial for its solution and confines the role of sleep to memory transformations that do not directly impact on problem-solving ability.

Sleep Spindles: Timed for Memory Consolidation.

It has long been known that sleep supports memory consolidation. Two recent studies now shed light on how sleep spindles, characteristic 11-16 Hz activity bursts, contribute critically to memory processing during the night.

Sleep Does Not Promote Solving Classical Insight Problems and Magic Tricks.

During creative problem solving, initial solution attempts often fail because of self-imposed constraints that prevent us from thinking out of the box. In order to solve a problem successfully, the problem representation has to be restructured by combining elements of available knowledge in novel and creative ways. It has been suggested that sleep supports the reorganization of memory representations, ultimately aiding problem solving. In this study, we systematically tested the effect of sleep and time on problem solving, using classical insight tasks and magic tricks. Solving these tasks explicitly requires a restructuring of the problem representation and may be accompanied by a subjective feeling of insight. In two sessions, 77 participants had to solve classical insight problems and magic tricks. The two sessions either occurred consecutively or were spaced 3 h apart, with the time in between spent either sleeping or awake. We found that sleep affected neither general solution rates nor the number of solutions accompanied by sudden subjective insight. Our study thus adds to accumulating evidence that sleep does not provide an environment that facilitates the qualitative restructuring of memory representations and enables problem solving.

Decoding cognitive concepts from neuroimaging data using multivariate pattern analysis.

Multivariate pattern analysis (MVPA) methods are now widely used in life-science research. They have great potential but their complexity also bears unexpected pitfalls. In this paper, we explore the possibilities that arise from the high sensitivity of MVPA for stimulus-related differences, which may confound estimations of class differences during decoding of cognitive concepts. We propose a method that takes advantage of concept-unrelated grouping factors, uses blocked permutation tests, and gradually manipulates the proportion of concept-related information in data while the stimulus-related, concept-irrelevant factors are held constant. This results in a concept-response curve, which shows the relative contribution of these two components, i.e. how much of the decoding performance is specific to higher-order category processing and to lower order stimulus processing. It also allows separating stimulus-related from concept-related neuronal processing, which cannot be achieved experimentally. We applied our method to three different EEG data sets with different levels of stimulus-related confound to decode concepts of digits vs. letters, faces vs. houses, and animals vs. fruits based on event-related potentials at the single trial level. We show that exemplar-specific differences between stimuli can drive classification accuracy to above chance levels even in the absence of conceptual information. By looking into time-resolved windows of brain activity, concept-response curves can help characterize the time-course of lower-level and higher-level neural information processing and detect the corresponding temporal and spatial signatures of the corresponding cognitive processes. In particular, our results show that perceptual information is decoded earlier in time than conceptual information specific to processing digits and letters. In addition, compared to the stimulus-level predictive sites, concept-related topographies are spread more widely and, at later time points, reach the frontal cortex. Thus, our proposed method yields insights into cognitive processing as well as corresponding brain responses.

Untangling a Cholinergic Pathway from Wakefulness to Memory.

Acetylcholine is a major modulator of learning and memory, and its availability varies across the sleep-wake cycle. In this issue of Neuron, Papouin et al. (2017) describe a D-serine-dependent pathway involving astroglia by which the transmitter tunes the hippocampus toward memory encoding during wakefulness.

Night sleep in patients with vegetative state.

Polysomnographic recording of night sleep was carried out in 15 patients with the diagnosis vegetative state (syn. unresponsive wakefulness syndrome). Sleep scoring was performed by three raters, and confirmed by means of a spectral power analysis of the electroencephalogram, electrooculogram and electromyogram. All patients but one exhibited at least some signs of sleep. In particular, sleep stage N1 was found in 13 patients, N2 in 14 patients, N3 in nine patients, and rapid eye movement sleep in 10 patients. Three patients exhibited all phenomena characteristic for normal sleep, including spindles and rapid eye movements. However, in all but one patient, sleep patterns were severely disturbed as compared with normative data. All patients had frequent and long periods of wakefulness during the night. In some apparent rapid eye movement sleep episodes, no eye movements were recorded. Sleep spindles were detected in five patients only, and their density was very low. We conclude that the majority of vegetative state patients retain some important circadian changes. Further studies are necessary to disentangle multiple factors potentially affecting sleep pattern of vegetative state patients.

Sleep-mediated memory consolidation depends on the level of integration at encoding.

There is robust evidence that sleep facilitates declarative memory consolidation. Integration of newly acquired memories into existing neocortical knowledge networks has been proposed to underlie this effect. Here, we test whether sleep affects memory retention for word-picture associations differently when it was learned explicitly or using a fast mapping strategy. Fast mapping is an incidental form of learning that references new information to existing knowledge and possibly allows neocortical integration already during encoding. If the integration of information into neocortical networks is a main function of sleep-dependent memory consolidation, material learned via fast mapping should therefore benefit less from sleep. Supporting this idea, we find that sleep has a protective effect on explicitly learned associations. In contrast, memory for associations learned by fast mapping does not benefit from sleep and remains stable regardless of whether sleep or wakefulness follows learning. Our results thus indicate that the need for sleep-mediated consolidation depends on the strategy used for learning and might thus be related to the level of integration of newly acquired memory achieved during encoding.

Rapid and independent memory formation in the parietal cortex.

Previous evidence indicates that the brain stores memory in two complementary systems, allowing both rapid plasticity and stable representations at different sites. For memory to be established in a long-lasting neocortical store, many learning repetitions are considered necessary after initial encoding into hippocampal circuits. To elucidate the dynamics of hippocampal and neocortical contributions to the early phases of memory formation, we closely followed changes in human functional brain activity while volunteers navigated through two different, initially unknown virtual environments. In one condition, they were able to encode new information continuously about the spatial layout of the maze. In the control condition, no information could be learned because the layout changed constantly. Our results show that the posterior parietal cortex (PPC) encodes memories for spatial locations rapidly, beginning already with the first visit to a location and steadily increasing activity with each additional encounter. Hippocampal activity and connectivity between the PPC and hippocampus, on the other hand, are strongest during initial encoding, and both decline with additional encounters. Importantly, stronger PPC activity related to higher memory-based performance. Compared with the nonlearnable control condition, PPC activity in the learned environment remained elevated after a 24-h interval, indicating a stable change. Our findings reflect the rapid creation of a memory representation in the PPC, which belongs to a recently proposed parietal memory network. The emerging parietal representation is specific for individual episodes of experience, predicts behavior, and remains stable over offline periods, and must therefore hold a mnemonic function.

Classification based hypothesis testing in neuroscience: Below-chance level classification rates and overlooked statistical properties of linear parametric classifiers.

Multivariate pattern analysis (MVPA) has recently become a popular tool for data analysis. Often, classification accuracy as quantified by correct classification rate (CCR) is used to illustrate the size of the effect under investigation. However, we show that in low sample size (LSS), low effect size (LES) data, which is typical in neuroscience, the distribution of CCRs from cross-validation of linear MVPA is asymmetric and can show classification rates considerably below what would be expected from chance classification. Conversely, the mode of the distribution in these cases is above expected chance levels, leading to a spuriously high number of above chance CCRs. This unexpected distribution has strong implications when using MVPA for hypothesis testing. Our analyses warrant the conclusion that CCRs do not well reflect the size of the effect under investigation. Moreover, the skewness of the null-distribution precludes the use of many standard parametric tests to assess significance of CCRs. We propose that MVPA results should be reported in terms of P values, which are estimated using randomization tests. Also, our results show that cross-validation procedures using a low number of folds, e.g. twofold, are generally more sensitive, even though the average CCRs are often considerably lower than those obtained using a higher number of folds. Hum Brain Mapp 37:1842-1855, 2016. © 2016 Wiley Periodicals, Inc.

Evidence for two distinct sleep-related long-term memory consolidation processes.

Numerous studies examine the effect of a night's sleep on memory consolidation, but few go beyond this short time-scale to test long-lasting effects of sleep on memory. We investigated long-term effects of sleep on typical memory tasks. During the hours following learning, participants slept or stayed awake. We compared recall performance between wake and sleep conditions after delays of up to 6 days. Performance develops in two distinct ways. Word pair, syllable, and motor sequence learning tasks benefit from sleep during the first day after encoding, when compared with daytime or nighttime wakefulness. However, performance in the wake conditions recovers after another night of sleep, so that we observe no lasting effect of sleep. Sleep deprivation before recall does not impair performance. Thus, fatigue cannot adequately explain the lack of long-term effects. We suggest that the hippocampus might serve as a buffer during the retention interval, and consolidation occurs during delayed sleep. In contrast, a non-hippocampal mirror-tracing task benefits significantly from sleep, even when tested after a 4-day delay including recovery sleep. This indicates a dissociation between two sleep-related consolidation mechanisms, which could rely on distinct neuronal processes.

Exploring the effect of sleep and reduced interference on different forms of declarative memory.

STUDY OBJECTIVES: Many studies have found that sleep benefits declarative memory consolidation. However, fundamental questions on the specifics of this effect remain topics of discussion. It is not clear which forms of memory are affected by sleep and whether this beneficial effect is partly mediated by passive protection against interference. Moreover, a putative correlation between the structure of sleep and its memory-enhancing effects is still being discussed. DESIGN: In three experiments, we tested whether sleep differentially affects various forms of declarative memory. We varied verbal content (verbal/nonverbal), item type (single/associate), and recall mode (recall/recognition, cued/free recall) to examine the effect of sleep on specific memory subtypes. We compared within-subject differences in memory consolidation between intervals including sleep, active wakefulness, or quiet meditation, which reduced external as well as internal interference and rehearsal. PARTICIPANTS: Forty healthy adults aged 18-30 y, and 17 healthy adults aged 24-55 y with extensive meditation experience participated in the experiments. RESULTS: All types of memory were enhanced by sleep if the sample size provided sufficient statistical power. Smaller sample sizes showed an effect of sleep if a combined measure of different declarative memory scales was used. In a condition with reduced external and internal interference, performance was equal to one with high interference. Here, memory consolidation was significantly lower than in a sleep condition. We found no correlation between sleep structure and memory consolidation. CONCLUSIONS: Sleep does not preferentially consolidate a specific kind of declarative memory, but consistently promotes overall declarative memory formation. This effect is not mediated by reduced interference.

Strengthening procedural memories by reactivation in sleep.

There is robust evidence that sleep facilitates procedural memory consolidation. The exact mechanisms underlying this process are still unclear. We tested whether an active replay of prior experience can underlie sleep effects on procedural memory. Participants learned a finger-tapping task in which key presses were associated with tones during practice. Later, during a consolidation interval spent either sleeping or awake, we presented auditory cues to reactivate part of the learned sequence. We show that reactivation strengthens procedural memory formation during sleep, but not during wakefulness. The improvement was restricted to those finger transitions that were cued. Thus, reactivation is a very specific process underpinning procedural memory consolidation. When comparing periods of sleep with and without reactivation, we find that it is not the time spent in a specific stage of sleep per se, but rather the occurrence of reactivation that mediates the effect of sleep on memory consolidation. Our data show that longer sleep time as well as additional reactivation by cueing during sleep can enhance later memory performance.