Boosting slow oscillations during sleep potentiates memory

Transcranial current stimulation focality using disc and ring electrode configurations: FEM analysis

We calculated the electric fields induced in the brain during transcranial current stimulation (TCS) using a finite-element concentric spheres human head model. A range of disc electrode configurations were simulated: (1) distant-bipolar; (2) adjacent-bipolar; (3) tripolar; and three ring designs, (4) belt, (5) concentric ring, and (6) double concentric ring. We compared the focality of each configuration targeting cortical structures oriented normal to the surface ('surface-radial' and 'cross-section radial'), cortical structures oriented along the brain surface ('surface-tangential' and 'cross-section tangential') and non-oriented cortical surface structures ('surface-magnitude' and 'cross-section magnitude'). For surface-radial fields, we further considered the 'polarity' of modulation (e.g. superficial cortical neuron soma hyper/depolarizing). The distant-bipolar configuration, which is comparable with commonly used TCS protocols, resulted in diffuse (un-focal) modulation with bi-directional radial modulation under each electrode and tangential modulation between electrodes. Increasing the proximity of the two electrodes (adjacent-bipolar electrode configuration) increased focality, at the cost of more surface current. At similar electrode distances, the tripolar-electrodes configuration produced comparable peak focality, but reduced radial bi-directionality. The concentric-ring configuration resulted in the highest spatial focality and uni-directional radial modulation, at the expense of increased total surface current. Changing ring dimensions, or use of two concentric rings, allow titration of this balance. The concentric-ring design may thus provide an optimized configuration for targeted modulation of superficial cortical neurons.

Cholinergic brainstem neurons modulate cortical gamma activity during slow oscillations

Cholinergic neurons in the rostral brainstem, including the pedunculopontine nucleus (PPN), are critical for switching behavioural state from sleep to wakefulness, and their presumed inactivity during sleep is thought to promote slow cortical rhythms that are characteristic of this state. However, it is possible that the diminished activity of cholinergic brainstem neurons during slow-wave sleep continues to have a functional impact upon ongoing cortical activity. Here we show that identified cholinergic projection neurons in the PPN fire rhythmically during cortical slow oscillations, and predominantly discharge in time with the phase of the slow oscillations supporting nested gamma oscillations (30-60 Hz). In contrast, PPN non-cholinergic neurons that are linked to cortical activity fire in the opposite phase and independent of nested gamma oscillations. Furthermore, cholinergic PPN neurons emit extensive local axon collaterals (as well as long-range projections), and increasing cholinergic tone within the PPN enhances the nested gamma oscillations without producing sustained cortical activation. Thus, in addition to driving global state transitions in the cortex, cholinergic PPN neurons also play an active role in organizing cortical activity during slow-wave sleep. Our results suggest that the role of the PPN in sleep homeostasis is more diverse than previously conceived. The functions supported by nested gamma oscillations during sleep (i.e. consolidation, plasticity) are critically dependent on the gating of the underlying cortical ensembles, and our data show that cholinergic PPN neurons have an hitherto unappreciated influence on this gating process.

Techniques and devices to restore cognition

Executive planning, the ability to direct and sustain attention, language and several types of memory may be compromised by conditions such as stroke, traumatic brain injury, cancer, autism, cerebral palsy and Alzheimer's disease. No medical devices are currently available to help restore these cognitive functions. Recent findings about the neurophysiology of these conditions in humans coupled with progress in engineering devices to treat refractory neurological conditions imply that the time has arrived to consider the design and evaluation of a new class of devices. Like their neuromotor counterparts, neurocognitive prostheses might sense or modulate neural function in a non-invasive manner or by means of implanted electrodes. In order to paint a vision for future device development, it is essential to first review what can be achieved using behavioral and external modulatory techniques. While non-invasive approaches might strengthen a patient's remaining intact cognitive abilities, neurocognitive prosthetics comprised of direct brain-computer interfaces could in theory physically reconstitute and augment the substrate of cognition itself.

Fast sleep spindle (13-15 hz) activity correlates with sleep-dependent improvement in visuomotor performance

STUDY OBJECTIVES

The relationship between memory enhancement and fast (13-16 Hz) versus slow (10-13 Hz) spindle activity during sleep was investigated.

DESIGN

Standard polysomnographic recordings were conducted during an adaptation, control nonlearning, and learning night. Automatic spindle detection and measurement was utilized with visual confirmation.

SETTING

Participants slept in individual, temperature-controlled bedrooms in a sleep laboratory.

PARTICIPANTS

Twelve healthy student volunteers (9 women and 3 men, mean age: 22.3 years) participated.

INTERVENTIONS

On the learning night, participants completed a presleep learning session on a modified version of mirror-tracing task followed by a postsleep test session. No learning or test sessions were performed on the adaptation and nonlearning nights.

MEASUREMENTS AND RESULTS

Tracing time was reduced by 6.4 seconds (20.6% +/- 2.07%) from the presleep to the postsleep session. Mean amplitude and duration of fast spindles was greater on the learning night than on the nonlearning night (both P values < 0.05). Skill improvement and fast-spindle activity were positively correlated (density [r = 0.76, P < 0.01], amplitude [r = 0.69, P < 0.05], and duration [r = 0.67, P <0.05]). Significant correlations between fast-spindle activity and mirror-tracing performance were also evident for the nonlearning night. There was no significant relationship between mirror-tracing performance and slow-spindle activity on any night.

CONCLUSIONS

The thalamocortical network underlying fast-spindle generation may contribute to or reflect plasticity during sleep.

Structure of spontaneous UP and DOWN transitions self-organizing in a cortical network model

Synaptic plasticity is considered to play a crucial role in the experience-dependent self-organization of local cortical networks. In the absence of sensory stimuli, cerebral cortex exhibits spontaneous membrane potential transitions between an UP and a DOWN state. To reveal how cortical networks develop spontaneous activity, or conversely, how spontaneous activity structures cortical networks, we analyze the self-organization of a recurrent network model of excitatory and inhibitory neurons, which is realistic enough to replicate UP-DOWN states, with spike-timing-dependent plasticity (STDP). The individual neurons in the self-organized network exhibit a variety of temporal patterns in the two-state transitions. In addition, the model develops a feed-forward network-like structure that produces a diverse repertoire of precise sequences of the UP state. Our model shows that the self-organized activity well resembles the spontaneous activity of cortical networks if STDP is accompanied by the pruning of weak synapses. These results suggest that the two-state membrane potential transitions play an active role in structuring local cortical circuits.

Rhythmic Constraints on Hippocampal Processing: State and Phase-Related Fluctuations of Synaptic Excitability During Theta and the Slow Oscillation

Coordinated patterns of state-dependent synchronized oscillatory activity have been suggested to play differential roles in both the encoding and consolidation phases of hippocampal-dependent memories. Previous studies have concentrated on the mutually exclusive patterns of theta and sharp-wave/ripple activity because these were thought to be the only collective oscillatory patterns expressed in the hippocampus. Recently we (and others) have described a novel rhythmic activity expressed during anesthesia and deep sleep, the hippocampal slow oscillation (SO). In an attempt to describe the differential effects of theta and the SO on processing in the hippocampal circuit, we performed evoked potential analysis of two major pathways (the commissural and perforant) in urethan-anesthetized rats across spontaneously expressed theta and SO states. We show that synaptic excitability was significantly enhanced in all pathways during the SO as compared with theta with the exception of the medial perforant path to the dentate gyrus, which showed greater excitability during theta. Furthermore, within each ongoing rhythm, there was a phase-dependent modulation of synaptic excitability. This occurred across all sites and similarly favored the falling phase (positive to negative) of both theta and the SO. Differential effects on the input, processing, and output circuitries of the hippocampus across mutually exclusive coordinated oscillatory patterns expressed during different states may be relevant for the staging of memory processes in the medial temporal lobe.

Excitation of coherent oscillations in a noisy medium

We numerically study the influence of neuronal threshold modulation on the properties of cortical traveling waves. For that reason we simplify a Wilson-Cowan-type integrodifferential equation model of propagating neocortical activity to a spatially discrete version. Further we introduce a noisy threshold. Depending on the noise level we find different states of the network activity, ranging from asynchronous oscillations, traveling waves, to synchronous oscillations. Finally, we induce the transition between these different states by an external modulation.

Slow-wave sleep and the risk of type 2 diabetes in humans

There is convincing evidence that, in humans, discrete sleep stages are important for daytime brain function, but whether any particular sleep stage has functional significance for the rest of the body is not known. Deep non-rapid eye movement (NREM) sleep, also known as slow-wave sleep (SWS), is thought to be the most "restorative" sleep stage, but beneficial effects of SWS for physical well being have not been demonstrated. The initiation of SWS coincides with hormonal changes that affect glucose regulation, suggesting that SWS may be important for normal glucose tolerance. If this were so, selective suppression of SWS should adversely affect glucose homeostasis and increase the risk of type 2 diabetes. Here we show that, in young healthy adults, all-night selective suppression of SWS, without any change in total sleep time, results in marked decreases in insulin sensitivity without adequate compensatory increase in insulin release, leading to reduced glucose tolerance and increased diabetes risk. SWS suppression reduced delta spectral power, the dominant EEG frequency range in SWS, and left other EEG frequency bands unchanged. Importantly, the magnitude of the decrease in insulin sensitivity was strongly correlated with the magnitude of the reduction in SWS. These findings demonstrate a clear role for SWS in the maintenance of normal glucose homeostasis. Furthermore, our data suggest that reduced sleep quality with low levels of SWS, as occurs in aging and in many obese individuals, may contribute to increase the risk of type 2 diabetes.

Memory consolidation during sleep: interactive effects of sleep stages and HPA regulation

Sleep is critically involved in the consolidation of previously acquired memory traces. However, nocturnal sleep is not uniform but is subject to distinct changes in electrophysiological and neuroendocrine activity. Specifically, the first half of the night is dominated by slow wave sleep (SWS), whereas rapid eye movement (REM) sleep prevails in the second half. Concomitantly, hypothalamo-pituitary-adrenal (HPA) activity as indicated by cortisol release is suppressed to a minimum during early sleep, while drastically increasing during late sleep. We have shown that the different sleep stages and the concomitant glucocorticoid release are interactively involved in the consolidation of different types of memories. SWS-rich early sleep has been demonstrated to benefit mainly the consolidation of hippocampus-dependent declarative memories (i.e. facts and episodes). In contrast, REM sleep-rich late sleep was shown to improve in particular emotional memories involving amygdalar function, as well as procedural memories (for skills) not depending on hippocampal or amygdalar function. Enhancing plasma glucocorticoid concentrations during SWS-rich early sleep counteracted hippocampus-dependent declarative memory consolidation, but did not affect hippocampus-independent procedural memory. Preventing the increase in cortisol during late REM sleep-rich sleep by administration of metyrapone impaired hippocampus-dependent declarative memory but enhanced amygdala-dependent emotional aspects of memory. The data underscore the importance of pituitary-adrenal inhibition during early SWS-rich sleep for efficient consolidation of declarative memory. The increase in cortisol release during late REM sleep-rich sleep may counteract an overshooting consolidation of emotional memories.

Enhancement of neocortical-medial temporal EEG correlations during non-REM sleep

Interregional interactions of oscillatory activity are crucial for the integrated processing of multiple brain regions. However, while the EEG in virtually all brain structures passes through substantial modifications during sleep, it is still an open question whether interactions between neocortical and medial temporal EEG oscillations also depend on the state of alertness. Several previous studies in animals and humans suggest that hippocampal-neocortical interactions crucially depend on the state of alertness (i.e., waking state or sleep). Here, we analyzed scalp and intracranial EEG recordings during sleep and waking state in epilepsy patients undergoing presurgical evaluation. We found that the amplitudes of oscillations within the medial temporal lobe and the neocortex were more closely correlated during sleep, in particular during non-REM sleep, than during waking state. Possibly, the encoding of novel sensory inputs, which mainly occurs during waking state, requires that medial temporal dynamics are rather independent from neocortical dynamics, while the consolidation of memories during sleep may demand closer interactions between MTL and neocortex.

Immediate as well as delayed post learning sleep but not wakefulness enhances declarative memory consolidation in children

While there is mounting evidence for the importance of sleep for declarative memory consolidation in adults, so far this issue has not been investigated in children despite considerable differences in sleep duration and sleep architecture between children and adults. Here, 27 children (aged between 9 and 12yr) were examined on two conditions: on the Sleep-Wake condition, subjects learned word pairs in the evening and delayed recall was tested first in the next morning after sleep and then again in the following evening after daytime wakefulness. On the Wake-Sleep condition, learning took place in the morning and delayed recall was tested in the evening of the same day and again in the next morning after sleep. In both conditions retention of declarative memory was significantly increased only after an interval of sleep that either followed immediately after learning (as in the Sleep-Wake condition) or that followed after daytime wakefulness (as in the Wake-Sleep condition), respectively. The results support the hypothesis that sleep plays an active role in declarative memory consolidation even if delayed and further show for the first time the importance of sleep for declarative memory consolidation during childhood.

Sleep does not benefit probabilistic motor sequence learning

It has become widely accepted that sleep-dependent consolidation occurs for motor sequence learning based on studies using finger-tapping tasks. Studies using another motor sequence learning task [the serial response time task (SRTT)] have portrayed a more nuanced picture of off-line consolidation, involving both sleep-dependent and daytime consolidation, as well as modifying influences of explicit awareness. The present study used a variant of the SRTT featuring probabilistic sequences to investigate off-line consolidation. Probabilistic sequences confer two advantages: first, spontaneous explicit awareness does not occur, and second, sequence learning measures are continuous, making it easier to separate general skill from sequence-specific learning. We found that sleep did not enhance general skill or sequence-specific learning. In contrast, daytime enhancement occurred for general skill but not for sequence-specific learning. Overall, these results suggest that motor learning does not always undergo consolidation with sleep.

Homer1a is a core brain molecular correlate of sleep loss

Sleep is regulated by a homeostatic process that determines its need and by a circadian process that determines its timing. By using sleep deprivation and transcriptome profiling in inbred mouse strains, we show that genetic background affects susceptibility to sleep loss at the transcriptional level in a tissue-dependent manner. In the brain, Homer1a expression best reflects the response to sleep loss. Time-course gene expression analysis suggests that 2,032 brain transcripts are under circadian control. However, only 391 remain rhythmic when mice are sleep-deprived at four time points around the clock, suggesting that most diurnal changes in gene transcription are, in fact, sleep-wake-dependent. By generating a transgenic mouse line, we show that in Homer1-expressing cells specifically, apart from Homer1a, three other activity-induced genes (Ptgs2, Jph3, and Nptx2) are overexpressed after sleep loss. All four genes play a role in recovery from glutamate-induced neuronal hyperactivity. The consistent activation of Homer1a suggests a role for sleep in intracellular calcium homeostasis for protecting and recovering from the neuronal activation imposed by wakefulness.

Comparatively weak after-effects of transcranial alternating current stimulation (tACS) on cortical excitability in humans

OBJECTIVE

Interference with brain rhythms by noninvasive transcranial stimulation that uses weak transcranial alternating current may reveal itself to be a new tool for investigating cortical mechanisms currently unresolved. Here, we aim to extend transcranial direct current stimulation (tDCS) techniques to transcranial alternating current stimulation (tACS).

BACKGROUND

Parameters such as electrode size and position were taken from those used in previous tDCS studies.

METHODS

Motor evoked potentials (MEPs) revealed by transcranial magnetic stimulation (TMS), electroencephalogram (EEG)-power, and reaction times measured in a motor implicit learning task, were analyzed to detect changes in cortical excitability after 2-10 minutes of AC stimulation and sinusoidal DC stimulation (tSDCS) by using 1, 10, 15, 30, and 45 Hz and sham stimulation over the primary motor cortex in 50 healthy subjects (eight-16 subjects in each study).

RESULTS

A significantly improved implicit motor learning was observed after 10 Hz AC stimulation only. No significant changes were observed in any of the analyzed frequency bands of EEG and with regard to the MEP amplitudes after AC or tSDCS stimulation. Similarly, if the anodal or cathodal DC stimulation was superimposed on 5, 10, and 15 Hz AC stimulation, the MEP amplitudes did not change significantly.

CONCLUSIONS

Transcranial application of weak AC current may appear to be a tool for basic and clinical research in diseases with altered EEG activity. However, its effect seems to be weaker than tDCS stimulation, at least in the present context of stimulus intensity and duration. Further studies are required to extend cautiously the safety range and uncover its influence on neuronal circuitries.

The contribution of sleep to hippocampus-dependent memory consolidation

There is now compelling evidence that sleep promotes the long-term consolidation of declarative and procedural memories. Behavioral studies suggest that sleep preferentially consolidates explicit aspects of these memories, which during encoding are possibly associated with activation in prefrontal-hippocampal circuitry. Hippocampus-dependent declarative memory benefits particularly from slow-wave sleep (SWS), whereas rapid-eye-movement (REM) sleep seems to benefit procedural aspects of memory. Consolidation of hippocampus-dependent memories relies on a dialog between the neocortex and hippocampus. Crucial features of this dialog are the neuronal reactivation of new memories in the hippocampus during SWS, which stimulates the redistribution of memory representations to neocortical networks; and the neocortical slow (<1Hz) oscillation that synchronizes hippocampal-to-neocortical information transfer to activity in other brain structures.

Memory trace stabilization leads to large-scale changes in the retrieval network: a functional MRI study on associative memory

Spaced learning with time to consolidate leads to more stabile memory traces. However, little is known about the neural correlates of trace stabilization, especially in humans. The present fMRI study contrasted retrieval activity of two well-learned sets of face-location associations, one learned in a massed style and tested on the day of learning (i.e., labile condition) and another learned in a spaced scheme over the course of one week (i.e., stabilized condition). Both sets of associations were retrieved equally well, but the retrieval of stabilized association was faster and accompanied by large-scale changes in the network supporting retrieval. Cued recall of stabilized as compared with labile associations was accompanied by increased activity in the precuneus, the ventromedial prefrontal cortex, the bilateral temporal pole, and left temporo-parietal junction. Conversely, memory representational areas such as the fusiform gyrus for faces and the posterior parietal cortex for locations did not change their activity with stabilization. The changes in activation in the precuneus, which also showed increased connectivity with the fusiform area, are likely to be related to the spatial nature of our task. The activation increase in the ventromedial prefrontal cortex, on the other hand, might reflect a general function in stabilized memory retrieval. This area might succeed the hippocampus in linking distributed neocortical representations.

Are corticothalamic 'up' states fragments of wakefulness?

The slow (<1 Hz) oscillation, with its alternating 'up' and 'down' states in individual neurons, is a defining feature of the electroencephalogram (EEG) during slow-wave sleep (SWS). Although this oscillation is well preserved across mammalian species, its physiological role is unclear. Electrophysiological and computational evidence from the cortex and thalamus now indicates that slow-oscillation 'up' states and the 'activated' state of wakefulness are remarkably similar dynamic entities. This is consistent with behavioural experiments suggesting that slow-oscillation 'up' states provide a context for the replay, and possible consolidation, of previous experience. In this scenario, the T-type Ca(2+) channel-dependent bursts of action potentials that initiate each 'up' state in thalamocortical (TC) neurons might function as triggers for synaptic and cellular plasticity in corticothalamic networks. This review is part of the INMED/TINS special issue Physiogenic and pathogenic oscillations: the beauty and the beast, based on presentations at the annual INMED/TINS symposium (http://inmednet.com).

The Role of Sleep in Declarative Memory Consolidation—Direct Evidence by Intracranial EEG

Two step theories of memory formation assume that an initial learning phase is followed by a consolidation stage. Memory consolidation has been suggested to occur predominantly during sleep. Very recent findings, however, suggest that important steps in memory consolidation occur also during waking state but may become saturated after some time awake. Sleep, in this model, specifically favors restoration of synaptic plasticity and accelerated memory consolidation while asleep and briefly afterwards. To distinguish between these different views, we recorded intracranial electroencephalograms from the hippocampus and rhinal cortex of human subjects while they retrieved information acquired either before or after a "nap" in the afternoon or on a control day without nap. Reaction times, hippocampal event-related potentials, and oscillatory gamma activity indicated a temporal gradient of hippocampal involvement in information retrieval on the control day, suggesting hippocampal-neocortical information transfer during waking state. On the day with nap, retrieval of recent items that were encoded briefly after the nap did not involve the hippocampus to a higher degree than retrieval of items encoded before the nap. These results suggest that sleep facilitates rapid processing through the hippocampus but is not necessary for information transfer into the neocortex per se.

Going beyond a mean-field model for the learning cortex: second-order statistics

Mean-field models of the cortex have been used successfully to interpret the origin of features on the electroencephalogram under situations such as sleep, anesthesia, and seizures. In a mean-field scheme, dynamic changes in synaptic weights can be considered through fluctuation-based Hebbian learning rules. However, because such implementations deal with population-averaged properties, they are not well suited to memory and learning applications where individual synaptic weights can be important. We demonstrate that, through an extended system of equations, the mean-field models can be developed further to look at higher-order statistics, in particular, the distribution of synaptic weights within a cortical column. This allows us to make some general conclusions on memory through a mean-field scheme. Specifically, we expect large changes in the standard deviation of the distribution of synaptic weights when fluctuation in the mean soma potentials are large, such as during the transitions between the "up" and "down" states of slow-wave sleep. Moreover, a cortex that has low structure in its neuronal connections is most likely to decrease its standard deviation in the weights of excitatory to excitatory synapses, relative to the square of the mean, whereas a cortex with strongly patterned connections is most likely to increase this measure. This suggests that fluctuations are used to condense the coding of strong (presumably useful) memories into fewer, but dynamic, neuron connections, while at the same time removing weaker (less useful) memories.

Dreams recall and auditory evoked potentials during propofol anaesthesia

It is unclear whether shorter wave latencies of middle-latency-auditory-evoked-potentials may be associated to cognitive function other than nondeclarative memory. We investigated the presence of declarative, nondeclarative and dreaming memory in propofol-anaesthetized patients and any relationship to intraoperatively registered middle-latency-auditory-evoked-potentials. An audiotape containing one of two stories was presented to patients during anaesthesia. Patients were interviewed on dream recall immediately upon emergence from anaesthesia. Declarative and nondeclarative memories for intraoperative listening were assessed 24 h after awakening without pointing out positive findings. Six patients who reported dream recall showed an intraoperative Pa latency less than that of patients who were unable to remember any dreams (P<0.001). A high responsiveness degree of primary cortex was associated to dream recall formation during anaesthesia.

Ethanol inhibits persistent activity in prefrontal cortical neurons

Cognitive functions supported by neurons in the prefrontal cortex (PFC) are disrupted by acute and chronic exposure to alcohol, yet little is known about the mechanisms that underlie these effects. In the present study, in vivo and in vitro electrophysiology was used to determine the effects of ethanol on neuronal firing and network patterns of persistent activity in PFC neurons. In vivo, ethanol (0.375-3.5 g/kg) dose-dependently reduced spike activity in the PFC measured with multielectrode extracellular recording in the anesthetized rat. In an in vitro coculture system containing slices of PFC, hippocampus, and ventral tegmental area (VTA), ethanol (25-100 mM) decreased persistent activity of PFC neurons, but had little effect on firing evoked by direct current injection. Persistent activity was often enhanced after ethanol washout and this effect was maintained in cultures lacking the VTA. A low concentration of the NMDA antagonist APV (5 microM) mimicked the inhibition of ethanol of persistent activity with no change in activity after washout. Ethanol inhibition of spontaneous and VTA-evoked persistent activity was enhanced by the D1 dopamine receptor antagonist SCH23390 [R(+)-7-chloro-8-hydroxy-3-methyl-1-phenyl-2,3,4,5-tetrahydro-1H-3-benzazepine hydrochloride]. The results of this study show that ethanol inhibits persistent activity and spike firing of PFC neurons and that the degree of ethanol inhibition may be influenced by D1 receptor tone. Ethanol-induced alterations in the activity of deep-layer cortical neurons may underlie some of the behavioral effects associated with ethanol intake.

Triggering sleep slow waves by transcranial magnetic stimulation

During much of sleep, cortical neurons undergo near-synchronous slow oscillation cycles in membrane potential, which give rise to the largest spontaneous waves observed in the normal electroencephalogram (EEG). Slow oscillations underlie characteristic features of the sleep EEG, such as slow waves and spindles. Here we show that, in sleeping subjects, slow waves and spindles can be triggered noninvasively and reliably by transcranial magnetic stimulation (TMS). With appropriate stimulation parameters, each TMS pulse at <1 Hz evokes an individual, high-amplitude slow wave that originates under the coil and spreads over the cortex. TMS triggering of slow waves reveals intrinsic bistability in thalamocortical networks during non-rapid eye movement sleep. Moreover, evoked slow waves lead to a deepening of sleep and to an increase in EEG slow-wave activity (0.5-4.5 Hz), which is thought to play a role in brain restoration and memory consolidation.

The impact of post-learning sleep vs. wakefulness on recognition memory for faces with different facial expressions

A beneficial effect of sleep after learning, compared to wakefulness, on memory formation has been shown in many studies using a variety of tasks. However, none of these studies has specifically addressed recognition memory for faces so far. The recognition of familiar faces, together with the extraction of emotional information from facial expression, is a fundamental cognitive skill in human everyday life, for which specific neural systems and mechanisms of processing have been developed. Here, we investigated the role of post-learning sleep for later recognition memory for neutral, happy, and angry faces. Twelve healthy subjects, after judging the emotional valence of the faces in the evening (learning phase), either slept normally in the subsequent night, with sleep recorded polysomnographically (sleep condition), or remained awake (wake condition) according to a cross-over design. Recognition testing took place in the second evening after learning, i.e. after a further night of regular sleep spent at home. Sleep after learning, compared to wakefulness, enhanced memory accuracy in recognition memory. This effect was independent of the emotional valence of facial expression. The response criterion at recognition testing did not differ between sleep and wake conditions. The amount of non rapid eye movement (NonREM) sleep during post-learning sleep correlated positively with memory accuracy at recognition testing, while time in REM sleep was associated with a speeded responding to the learned faces. Results suggest that face recognition, despite its dependence on specialized brain systems, nevertheless relies on the general neural mechanisms of sleep-associated memory consolidation.

Midlife decline in declarative memory consolidation is correlated with a decline in slow wave sleep

Sleep architecture as well as memory function are strongly age dependent. Slow wave sleep (SWS), in particular, decreases dramatically with increasing age, starting already beyond the age of 30. SWS normally predominates during early nocturnal sleep and is implicated in declarative memory consolidation. However, the consequences of changes in sleep across the life span for sleep-associated memory consolidation have not been evaluated so far. Here, we compared declarative memory consolidation (for word-pair associates) during sleep in young and middle-aged healthy humans. The age groups (18-25 vs. 48-55 yr) did not differ with regard to learning performance before retention periods that covered, respectively, the first and second half of nocturnal sleep. However, after early retention sleep, where the younger subjects showed distinctly more SWS than the middle-aged (62.3 +/- 3.7 min vs. 18.4 +/- 7.2 min, P < 0.001), retrieval of the word pairs in the middle-aged was clearly worse than in the young (P < 0.001). In contrast, declarative memory retention did not differ between groups after late sleep, where retention was generally worse than after early sleep (P = 0.005). Retention of declarative memories was the same in both age groups when sleep periods containing equal amounts of SWS were compared, i.e., across late sleep in the young and across early sleep in the middle-aged. Our results indicate a decline in sleep-associated declarative memory consolidation that develops already during midlife and is associated with a decrease in early nocturnal SWS.

Sleep enforces the temporal order in memory

Background

Temporal sequence represents the main principle underlying episodic memory. The storage of temporal sequence information is thought to involve hippocampus-dependent memory systems, preserving temporal structure possibly via chaining of sequence elements in heteroassociative networks. Converging evidence indicates that sleep enhances the consolidation of recently acquired representations in the hippocampus-dependent declarative memory system. Yet, it is unknown if this consolidation process comprises strengthening of the temporal sequence structure of the representation as well, or is restricted to sequence elements independent of their temporal order. To address this issue we tested the influence of sleep on the strength of forward and backward associations in word-triplets.

Methodology/Principal Findings

Subjects learned a list of 32 triplets of unrelated words, presented successively (A-B-C) in the center of a screen, and either slept normally or stayed awake in the subsequent night. After two days, retrieval was assessed for the triplets sequentially either in a forward direction (cueing with A and B and asking for B and C, respectively) or in a backward direction (cueing with C and B and asking for B and A, respectively). Memory was better for forward than backward associations (p<0.01). Sleep did not affect backward associations, but enhanced forward associations, specifically for the first (AB) transitions (p<0.01), which were generally more difficult to retrieve than the second transitions.

Conclusions/Significance

Our data demonstrate that consolidation during sleep strengthens the original temporal sequence structure in memory, presumably as a result of a replay of new representations during sleep in forward direction. Our finding suggests that the temporally directed replay of memory during sleep, apart from strengthening those traces, could be the key mechanism that explains how temporal order is integrated and maintained in the trace of an episodic memory.

Spike timing amplifies the effect of electric fields on neurons: implications for endogenous field effects

Despite compelling phenomenological evidence that small electric fields (<5 mV/mm) can affect brain function, a quantitative and experimentally verified theory is currently lacking. Here we demonstrate a novel mechanism by which the nonlinear properties of single neurons "amplify" the effect of small electric fields: when concurrent to suprathreshold synaptic input, small electric fields can have significant effects on spike timing. For low-frequency fields, our theory predicts a linear dependency of spike timing changes on field strength. For high-frequency fields (relative to the synaptic input), the theory predicts coherent firing, with mean firing phase and coherence each increasing monotonically with field strength. Importantly, in both cases, the effects of fields on spike timing are amplified with decreasing synaptic input slope and increased cell susceptibility (millivolt membrane polarization per field amplitude). We confirmed these predictions experimentally using CA1 hippocampal neurons in vitro exposed to static (direct current) and oscillating (alternating current) uniform electric fields. In addition, we develop a robust method to quantify cell susceptibility using spike timing. Our results provide a precise mechanism for a functional role of endogenous field oscillations (e.g., gamma) in brain function and introduce a framework for considering the effects of environmental fields and design of low-intensity therapeutic neurostimulation technologies.

The sleeping brain, the states of consciousness, and the human intelligence

A large number of experimental results clearly indicate that sleep has an important role for human intelligence. Sleep-wake stages and their specific patterns of brain activation and neuromodulation subserve human memory, states of consciousness, and modes of information processing that strongly relate to intelligence. Therefore, human intelligence should be explained in a broader framework than is implicated by neuroimaging data alone.

Odor cues during slow-wave sleep prompt declarative memory consolidation

Sleep facilitates memory consolidation. A widely held model assumes that this is because newly encoded memories undergo covert reactivation during sleep. We cued new memories in humans during sleep by presenting an odor that had been presented as context during prior learning, and so showed that reactivation indeed causes memory consolidation during sleep. Re-exposure to the odor during slow-wave sleep (SWS) improved the retention of hippocampus-dependent declarative memories but not of hippocampus-independent procedural memories. Odor re-exposure was ineffective during rapid eye movement sleep or wakefulness or when the odor had been omitted during prior learning. Concurring with these findings, functional magnetic resonance imaging revealed significant hippocampal activation in response to odor re-exposure during SWS.

Transcranial slow oscillatory stimulation drives consolidation of declarative memory by synchronization of the neocortex

Evaluation of: Marshall L, Helgadottir H, Molle M, Born J: Boosting slow oscillations during sleep potentiates memory. Nature 444, 610–613 (2006). Slow-wave sleep plays a crucial role in the consolidation of declarative memory. During this sleep stage the electroencephalogram predominantly shows slow oscillatory activity and slow sleep spindles. The latter are likely to be linked to hippocampal fast ripples and subsequent neuronal firing, presumably supporting the transformation of memory. Anodal transcranial direct-current stimulation generates a temporary negativity of the extracellular space in the underlying tissue, secondarily causing a shift of the neuronal membrane potential towards depolarization. A novel type of transcranial ‘intermittent’ slow oscillatory stimulation was applied over the frontal cortex during early stage-two sleep with the purpose of inducing endogenous slow oscillations and slow spindle activity. It is argued that this form of stimulation elicited a specific enhancement of the hippocampus-dependent declarative memory, while the nondeclarative memory remained unaffected. It is proposed that transcranial slow oscillatory stimulation, capable of modulating a wide thalamo–cortico–hippocampal network, could contribute to the treatment of memory and sleep disorders.

Sleep to remember

Recently, compelling evidence has accumulated that links sleep to learning and memory. Sleep has been identified as a state that optimizes the consolidation of newly acquired information in memory. Consolidation is an active process that is presumed to rely on the covert reactivation and reorganization of newly encoded representations. Hippocampus-dependent memories benefit primarily from slow-wave sleep (SWS), whereas memories not depending on the hippocampus show greater gains over periods containing high amounts of rapid eye movement sleep. One way sleep does this is by establishing different patterns of neurotransmitters and neurohormone secretion between sleep stages. Another central role for consolidating memories is played by the slow oscillation, that is, the oscillating field potential change dominating SWS. The emergence of slow oscillations in neocortical networks depends on the prior use of these networks for encoding of information. Via efferent pathways, they synchronize the occurrence of sharp wave ripples accompanying memory reactivations in the hippocampus with thalamocortical spindle activity. Thus, hippocampal memories are fed back into neocortical networks at a time when these networks are depolarized and, because of concurrent spindle activity, can most sensitively react to these inputs with plastic changes underlying the formation of long-term memory representations.

Interaction between neocortical and hippocampal networks via slow oscillations

Both the thalamocortical and limbic systems generate a variety of brain state-dependent rhythms but the relationship between the oscillatory families is not well understood. Transfer of information across structures can be controlled by the offset oscillations. We suggest that slow oscillation of the neocortex, which was discovered by Mircea Steriade, temporally coordinates the self-organized oscillations in the neocortex, entorhinal cortex, subiculum and hippocampus. Transient coupling between rhythms can guide bidirectional information transfer among these structures and might serve to consolidate memory traces.