Sleep-Dependent Memory Consolidation and Incremental Sentence Comprehension : Computational Dependencies during Language Learning as Revealed by Neuronal Oscillations

We hypothesize a beneficial influence of sleep on the consolidation of the combinatorial mechanisms underlying incremental sentence comprehension. These predictions are grounded in recent work examining the effect of sleep on the consolidation of linguistic information, which demonstrate that sleep-dependent neurophysiological activity consolidates the meaning of novel words and simple grammatical rules. However, the sleep-dependent consolidation of sentence-level combinatorics has not been studied to date. Here, we propose that dissociable aspects of sleep neurophysiology consolidate two different types of combinatory mechanisms in human language: sequence-based (order-sensitive) and dependency-based (order-insensitive) combinatorics. The distinction between the two types of combinatorics is motivated both by cross-linguistic considerations and the neurobiological underpinnings of human language. Unifying this perspective with principles of sleep-dependent memory consolidation, we posit that a function of sleep is to optimize the consolidation of sequence-based knowledge (thewhen) and the establishment of semantic schemas of unordered items (thewhat) that underpin cross-linguistic variations in sentence comprehension. This hypothesis builds on the proposal that sleep is involved in the construction of predictive codes, a unified principle of brain function that supports incremental sentence comprehension. Finally, we discuss neurophysiological measures (EEG/MEG) that could be used to test these claims, such as the quantification of neuronal oscillations, which reflect basic mechanisms of information processing in the brain

Hippocampal Sleep Features: Relations to Human Memory Function

The recent spread of intracranial electroencephalographic (EEG) recording techniques for presurgical evaluation of drug-resistant epileptic patients is providing new information on the activity of different brain structures during both wakefulness and sleep. The interest has been mainly focused on the medial temporal lobe, and in particular the hippocampal formation, whose peculiar local sleep features have been recently described, providing support to the idea that sleep is not a spatially global phenomenon. The study of the hippocampal sleep electrophysiology is particularly interesting because of its central role in the declarative memory formation. Recent data indicate that sleep contributes to memory formation. Therefore, it is relevant to understand whether specific patterns of activity taking place during sleep are related to memory consolidation processes. Fascinating similarities between different states of consciousness (wakefulness, REM sleep, non-REM sleep) in some electrophysiological mechanisms underlying cognitive processes have been reported. For instance, large-scale synchrony in gamma activity is important for waking memory and perception processes, and its changes during sleep may be the neurophysiological substrate of sleep-related deficits of declarative memory. Hippocampal activity seems to specifically support memory consolidation during sleep, through specific coordinated neurophysiological events (slow waves, spindles, ripples) that would facilitate the integration of new information into the pre-existing cortical networks. A few studies indeed provided direct evidence that rhinal ripples as well as slow hippocampal oscillations are correlated with memory consolidation in humans. More detailed electrophysiological investigations assessing the specific relations between different types of memory consolidation and hippocampal EEG features are in order. These studies will add an important piece of knowledge to the elucidation of the ultimate sleep function

Manipulating sleep spindles - expanding views on sleep, memory, and disease.

Sleep spindles are distinctive electroencephalographic (EEG) oscillations emerging during non-rapid-eye-movement sleep (NREMS) that have been implicated in multiple brain functions, including sleep quality, sensory gating, learning, and memory. Despite considerable knowledge about the mechanisms underlying these neuronal rhythms, their function remains poorly understood and current views are largely based on correlational evidence. Here, we review recent studies in humans and rodents that have begun to broaden our understanding of the role of spindles in the normal and disordered brain. We show that newly identified molecular substrates of spindle oscillations, in combination with evolving technological progress, offer novel targets and tools to selectively manipulate spindles and dissect their role in sleep-dependent processes

Sleep Spindles – As a Biomarker of Brain Function and Plasticity

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Sleep-dependent consolidation in multiple memory systems

Before newly formed memories can last for the long-term, they must undergo a period of consolidation. It has been shown that sleep facilitates this process. One hypothesis about how this may occur is that learning-related neuronal activity is replayed during following sleep periods. Such a reactivation of neural activity patterns has been repeatedly shown in the hippocampal formation in animals. Hippocampally-induced reactivation can also be observed in other brain areas like the neocortex and basal ganglia. On the behavioral level, sleep has been found to benefit performance on a broad range of memory tasks that rely on different neural systems. Up to now, however, it is unclear whether the same mechanisms mediate effects of sleep on consolidation in different memory systems. In this thesis, we investigated both the effects and the mechanisms of sleep-dependent consolidation in multiple memory systems. We find that sleep benefits performance on a broad range of procedural and declarative memory tasks (studies 1 and 2). These beneficial effects of sleep go beyond a reduction of retroactive interference as effected by quiet wakeful meditation (study 1). In study 2, we demonstrate that the processes underlying these beneficial effects of sleep are different for different memory systems. We assessed performance on typical declarative and procedural memory tasks during one week after participants slept or were sleep deprived for one night after learning. Sleep-dependent consolidation of hippocampal and non-hippocampal memory follows different time-courses. Hippocampal memory shows a benefit of sleep only one day after learning. Performance after sleep deprivation recovers following the next night of sleep, so that no enduring effect of sleep can be observed. However, sleep deprivation before recall does not impair performance. For non-hippocampal memory, on the other hand, long-term benefits of sleep after learning can be observed even after four days. Here, delayed sleep cannot rescue performance. This indicates a dissociation between two sleep-related consolidation mechanisms, which rely on distinct neuronal processes. We studied the neuronal processes underlying sleep effects on declarative memory in study 3, where we investigate learning-related electrophysiological activity in the sleeping brain. With the help of multivariate pattern classification algorithms, we show that brain activity during sleep contains information about the kind of visual stimuli that were learned earlier. We thus find that learned material is actively reprocessed during sleep. In a next step, we examined whether procedural memory can also benefit from reactivation during sleep. We find that a procedural memory task that has been found to activate the hippocampus can be strengthened by externally cueing the reactivation process during sleep. Similar to study 2, this indicates that it is not the traditional distinction between declarative and procedural memory that determines how memories are consolidated during sleep. Rather, memory systems, and in particular hippocampal contribution, decide the sleep-dependent consolidation process. In the first four studies, we examined how sleep affects memory in different memory systems. In our last study, we went one step further and investigated whether multiple memory systems can also interact during consolidation in sleep. We devised a task during which both implicit and explicit memory develop during learning. Results show that sleep not only strengthens implicit and explicit memory individually, it also integrates these formerly separate representations of the learning task. Implicit and explicit memory are negatively correlated immediately after training. Sleep renders this association positive and allows cooperation between the two memory traces. We observe this change both in behavior, using structural equation modeling, and on the level of brain activity, measured by fMRI. After sleep, the hippocampus is more strongly activated during recall of implicit memory, whereas the caudate nucleus shows stronger activity during explicit memory recall. Moreover, both regions show correlated stimulus-induced responses in a task that allows memory systems cooperation. These results provide conclusive evidence that sleep not only strengthens memory, but also reorganizes the contributing neural circuits. In this way, sleep actually changes the quality of the memory representation

Chapter Sleep Spindles – As a Biomarker of Brain Function and Plasticity

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Sleep in the Human Hippocampus: A Stereo-EEG Study

Background. There is compelling evidence indicating that sleep plays a crucial role in the consolidation of new declarative, hippocampus-dependent memories. Given the increasing interest in the spatiotemporal relationships between cortical and hippocampal activity during sleep, this study aimed to shed more light on the basic features of human sleep in the hippocampus. Methodology/Principal Findings. We recorded intracerebral stereo-EEG directly from the hippocampus and neocortical sites in five epileptic patients undergoing presurgical evaluations. The time course of classical EEG frequency bands during the first three NREM-REM sleep cycles of the night was evaluated. We found that delta power shows, also in the hippocampus, the progressive decrease across sleep cycles, indicating that a form of homeostatic regulation of delta activity is present also in this subcortical structure. Hippocampal sleep was also characterized by: i) a lower relative power in the slow oscillation range during NREM sleep compared to the scalp EEG; ii) a flattening of the time course of the very low frequencies (up to 1 Hz) across sleep cycles, with relatively high levels of power even during REM sleep; iii) a decrease of power in the beta band during REM sleep, at odds with the typical increase of power in the cortical recordings. Conclusions/Significance. Our data imply that cortical slow oscillation is attenuated in the hippocampal structures during NREM sleep. The most peculiar feature of hippocampal sleep is the increased synchronization of the EEG rhythms during REM periods. This state of resonanc

Spatio-temporal Principles of Infra-slow Brain Activity

In the study of systems where basic laws have eluded us, as is largely the case in neuroscience, the simplest approach to progress might be to ask: what are the biggest, most noticeable things the system does when left alone? Without any perturbations or fine dissections, can regularities be found in the basic operations of the system as a whole? In the case of the brain, it turns out that there is an amazing amount of activity even in the absence of explicit environmental inputs or outputs. We call this spontaneous, or resting state, brain activity. Prior work has shown that spontaneous brain activity is dominated by very low frequencies: the biggest changes in brain activity happen relatively slowly, over 10’s-100’s of seconds. Moreover, this very slow activity of the brain is quite metabolically expensive. The brain accounts for 2% of body mass in an adult, but requires 20% of basal metabolic expenditure. Remarkably, the energy required to sustain brain function is nearly constant whether one is engaged in a demanding mental task or simply out to lunch. Furthermore, work over the past three decades has established that the spontaneous activities of the brain are not random, but instead organized into specific patterns, most often characterized by correlations within large brain systems. Yet, how do these correlations arise, and does spontaneous activity support slow signaling within and between neural systems? In this thesis, we approach these questions by providing a comprehensive analysis of the temporal structure of very low frequency spontaneous activity. Specifically, we focus on the direction of travel in low frequency activity, measured using resting state fMRI in humans, but also using electrophysiological techniques in humans and mice, and optical calcium imaging in mice. Our temporal analyses reveal heretofore unknown regularities in the way slow signals move through the brain. We further find that very low frequency activity behaves differently than faster frequencies, that it travels through distinct layers of the cortex, and that its travel patterns give rise to correlations within networks. We also demonstrate that the travel patterns of very low frequency activity are highly dependent on the state of the brain, especially the difference between wake and sleep states. Taken together, the findings in this thesis offer a glimpse into the principles that govern brain activity

The effect of cognitive training on subsequent sleep characteristics

Introduction: Several studies have consistently shown that pre-sleep learning produces changes in sleep structure. Whereas the majority of these studies has mainly focused on post-training changes in sleep states (namely REM and NREM sleep amount) and, more recently, in specific electrophysiological features (e.g., sleep spindles, slow wave activity), very little attention has been paid to the hypothesis that pre-sleep learning might improve sleep quality, as expressed by sleep continuity, stability and cyclic organization measures. Furthermore, studies addressing the relationship between sleep and learning usually employ purely declarative or procedural tasks, neglecting that everyday life learning processes depend on the simultaneous activation of different memory systems. Recently, we have reported that a complex ecological learning task (requiring the simultaneous activation of several cognitive functions), intensively administered at bedtime, improves daytime sleep continuity and stability, possibly as a result of ongoing memory processes. To follow up our previous study, here we aimed to extend these findings to a night paradigm and to test whether a similar post-training sleep improvement may be obtained in a sample of individuals with sleep complaints. Specifically, our focus was on post-training changes in objective and subjective sleep quality. Furthermore, we compared overnight performance changes with those obtained over a wake retention period, in order to address the possible differential effect of sleep and wake on memory processes. Method: After a habituation night, twenty-one subjects (F=15, mean age: 27.5±7.7 years, all bad sleepers according to the Pittsburgh Sleep Quality Index) underwent conventional polygraphic recording under three conditions: 1) BL, baseline night sleep; 2) post-active control sleep (AC), a sleep episode preceded by a non-learning control task; 3) post-training sleep (TR), a sleep episode preceded by a complex ecological task. The same task as in TR was administered in a Wake condition (W), in which the retention period between training sessions corresponded to the duration of the subject’s baseline sleep time. Subjects underwent AC, TR and W conditions in balanced order. The complex cognitive task consisted in a slightly modified version of the famous word game “Ruzzle”. In this game, the player has two minutes to form as many words as possible and reach the highest score achievable with the 16 letters available in a 4x4 grid on an iPad screen. Performance measures were R-WORDS%, i.e., the number of detected words over total available words, and R-SCORE%, i.e., the global score achieved, depending on the number of words found, on their length and on the ability to use the coloured bonus letters which multiply letter or word values. Results: Post-training sleep (TR) showed a reduction in Stage 1 proportion (F=4.39, p=.021; TRTR and AC) and brief awakenings frequency (F=5.89, p=.007, BL>TR and AC), decreased frequency of arousals (F=6.25, p=.005; TRTR and AC) and functional uncertainty (FU) periods (F=14.23, pTR and AC), as well as a reduction of time spent in FU periods (F=515.33, pTR and AC); an increase in the number of NREM-REM cycles (F=4.51, p=.019; TR>BL and AC), and of time spent in cycles (F=4.77, p=.015; TR>BL and AC). This improvement in objective sleep quality was paralleled by that in subjective ratings, assessed through the Self-Rating Scale for Sleep and Awakenings Quality (χ2=9.13, p=.010; TRW), while the opposite effect emerged for the R-WORDS% (t=-2.96, p=.01; W>TR). Conclusions: Our results extend previous findings on post-training changes in sleep continuity, stability and organization to a sample of bad sleepers; also, they show that objective sleep improvement may be reflected in subjective sleep quality perception. Interestingly, the active control task also produced improvements in some of these features, prompting future investigations on the contribution to post-training sleep changes of additional factors not specifically linked to learning processes. As for performance, the finding of a significant sleep effect for the more complex performance measure (R-SCORE%) suggests that sleep preferentially promotes effective learning of elaborate cognitive strategies rather than that of simpler cognitive processes. In conclusion, in light of the importance of non-pharmacological treatments for sleep disturbances, this study offers the possibility to further explore planned cognitive training as a low-cost treatment strategy to improve sleep quality

Transcranial Electrical Currents to Probe EEG Brain Rhythms and Memory Consolidation during Sleep in Humans

Previously the application of a weak electric anodal current oscillating with a frequency of the sleep slow oscillation (∼0.75 Hz) during non-rapid eye movement sleep (NonREM) sleep boosted endogenous slow oscillation activity and enhanced sleep-associated memory consolidation. The slow oscillations occurring during NonREM sleep and theta oscillations present during REM sleep have been considered of critical relevance for memory formation. Here transcranial direct current stimulation (tDCS) oscillating at 5 Hz, i.e., within the theta frequency range (theta-tDCS) is applied during NonREM and REM sleep. Theta-tDCS during NonREM sleep produced a global decrease in slow oscillatory activity conjoint with a local reduction of frontal slow EEG spindle power (8–12 Hz) and a decrement in consolidation of declarative memory, underlining the relevance of these cortical oscillations for sleep-dependent memory consolidation. In contrast, during REM sleep theta-tDCS appears to increase global gamma (25–45 Hz) activity, indicating a clear brain state-dependency of theta-tDCS. More generally, results demonstrate the suitability of oscillating-tDCS as a tool to analyze functions of endogenous EEG rhythms and underlying endogenous electric fields as well as the interactions between EEG rhythms of different frequencies