184 research outputs found

    The benefits of targeted memory reactivation for consolidation in sleep are contingent on memory accuracy and direct cue-memory associations

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    Objectives: To investigate how the effects of targeted memory reactivation (TMR) are influenced by memory accuracy prior to sleep and the presence or absence of direct cue-memory associations. Methods: 30 participants associated each of 50 pictures with an unrelated word and then with a screen location in two separate tasks. During picture-location training, each picture was also presented with a semantically related sound. The sounds were therefore directly associated with the picture locations but indirectly associated with the words. During a subsequent nap, half of the sounds were replayed in slow wave sleep (SWS) (TMR). The effect of TMR on memory for the picture locations (direct cue-memory associations) and picture-word pairs (indirect cue-memory associations) was then examined. Results: TMR reduced overall memory decay for recall of picture locations. Further analyses revealed a benefit of TMR for picture locations recalled with a low degree of accuracy prior to sleep, but not those recalled with a high degree of accuracy. The benefit of TMR for low accuracy memories was predicted by time spent in SWS. There was no benefit of TMR for memory of the picture-word pairs, irrespective of memory accuracy prior to sleep. Conclusions: TMR provides the greatest benefit to memories recalled with a low degree of accuracy prior to sleep. The memory benefits of TMR may also be contingent on direct cue-memory associations

    Targeted memory reactivation during sleep with closed-loop auditory stimuli: Comparing the effects of slow oscillatory up-phase and down-phase cueing on sleep-dependent declarative memory consolidation

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    In the last decade, an increasing number of studies have demonstrated that using a relatively new technique called ‘targeted memory reactivation’ can modulate and enhance memory consolidation during sleep. This technique is performed by matching specific externally applied sensory stimuli (e.g., sound cues) with target information (e.g., associated word pairs) during wakefulness and then presenting the learned cues during subsequent non-REM sleep. The present study combines this technique with an auditory closed-loop stimulation (ACLS) algorithm, which detects slow oscillations (SOs) and triggers the presentation of the auditory cues precisely during a specific phase of a SO once the EEG signal passes a certain amplitude threshold. SOs are high-amplitude, lowfrequency undulating EEG signals, which represent the hallmark oscillations during slowwave sleep (SWS). Following the widely accepted assumption that SOs play a central role in the consolidation of memory by driving memory reactivation processes during SWS, the present study aimed to identify the optimal time window for the presentation of auditory cues within a single SO during SWS in order to optimize targeted memory reactivation and thus overnight consolidation. The main focus of the study lay thereby on the comparison of the differential benefits on declarative memory retention during two stimulation conditions: SO up-phase and down-phase. For this purpose, auditory stimuli were presented to subjects during non-REM sleep, timed to set in with SO negative peaks during down-phase stimulation conditions, and with SO positive peaks during up-phase stimulation conditions. As SO up states are assumed to represent a state of increased neuronal firing, the hypothesis of this study proposes that auditory cueing in-phase with online detected SO up states leads to better declarative memory consolidation than cueing during SO down states. During the evening of each experimental condition, subjects performed on a paired-associate learning task (PAL task), during which they were presented with each word pair on a screen while the first syllable of the first word was played simultaneously over in-ear headphones. They were first tasked to learn to match syllables with corresponding word pairs and then to recall a word pair when presented with the matching syllable only. Following this learning session of declarative memory contents after reaching a criterion of 60% correctly recalled word pairs, memory performance was tested once immediately and once during a delayed recall session the next morning. The syllables used in the task where of 600-ms length each and were later presented as cues during post-learning nonREM sleep. Contrary to expectations, analyses of behavioral results during up-phase conditions showed no significant declarative memory benefit compared to down-phase conditions. Also, no significant cueing effect could be observed during both conditions. Analyses of subjects’ averaged auditory evoked potential signals showed the typical immediate evoked potential responses for up-phase and down-phase stimulations, indicating correctly performed auditory cueing during both experimental conditions. Additionally, subjects performed on additional cognitive tests and psychometric assessment tasks, the results of which showed no significant differences for both conditions. The hypothesis of the present study, stating that up-phases represent a superior time window for auditory stimulations compared to down-phases of SOs, was not validated. However, the study facilitated new insights into the relatively new field of closed-loop targeted memory reactivation for potential memory enhancement. As was demonstrated in previous research, targeted memory reactivation combined with precise closed-loop auditory stimulation seems not only to represent a non-invasive and effective method to enhance memory consolidation during sleep, but also to hold various potential benefits, particularly in regard to clinical applications in the field of psychotherapy and neurological disorders. As a result, the present study has undeniably demonstrated that further research is still necessary and might benefit from the present study’s findings as many questions remain unanswered, particularly in regard to specific cueing conditions, underlying neural mechanisms, long-term effects, limitations, and potential side effects of the cued memory reactivation technique

    How Aging Affects Sleep-Dependent Memory Consolidation?

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    Memories are not stored as they were initially encoded but rather undergo a gradual reorganization process, termed memory consolidation. Numerous data indicate that sleep plays a major role in this process, notably due to the specific neurochemical environment and the electrophysiological activity observed during the night. Two putative, probably not exclusive, models (“hippocampo-neocortical dialogue” and “synaptic homeostasis hypothesis”) have been proposed to explain the beneficial effect of sleep on memory processes. However, all data gathered until now emerged from studies conducted in young subjects. The investigation of the relationships between sleep and memory in older adults has sparked off little interest until recently. Though, aging is characterized by memory impairment, changes in sleep architecture, as well as brain and neurochemical alterations. All these elements suggest that sleep-dependent memory consolidation may be impaired or occurs differently in older adults. This review outlines the mechanisms governing sleep-dependent memory consolidation, and the crucial points of this complex process that may dysfunction and result in impaired memory consolidation in aging

    How Targeted Memory Reactivation Promotes the Selective Strengthening of Memories in Sleep

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    Over the last ten years, scientists have developed a method called targeted memory reactivation (TMR) for selectively strengthening memories during sleep. Prior to this, memory manipulation during sleep was at most a plot device in science fiction movies, but a large corpus of studies now demonstrates that TMR is both reliable and effective. TMR studies hypothesize that this method taps into normal consolidation mechanisms that require the repeated replay of memories during sleep. This idea has recently been supported by several new studies demonstrating that TMR upregulates the reactivation of cued memories, and that such upregulation predicts subsequent memory performance. This new body of work provides a unique window onto many properties of memory reactivation and helps to close the gap between our understanding of replay in rodents, where it has been visualised at the neural level for many years, and humans, where such studies are only just starting to become possible. We will discuss this new literature and highlight the vast potential of these new methods for future research

    Emotional arousal modulates oscillatory correlates of targeted memory reactivation during NREM, but not REM sleep

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    Rapid eye movement (REM) sleep is considered to preferentially reprocess emotionally arousing memories. We tested this hypothesis by cueing emotional vs. neutral memories during REM and NREM sleep and wakefulness by presenting associated verbal memory cues after learning. Here we show that cueing during NREM sleep significantly improved memory for emotional pictures, while no cueing benefit was observed during REM sleep. On the oscillatory level, successful memory cueing during NREM sleep resulted in significant increases in theta and spindle oscillations with stronger responses for emotional than neutral memories. In contrast during REM sleep, solely cueing of neutral (but not emotional) memories was associated with increases in theta activity. Our results do not support a preferential role of REM sleep for emotional memories, but rather suggest that emotional arousal modulates memory replay and consolidation processes and their oscillatory correlates during NREM sleep

    The beneficial role of memory reactivation for language learning during sleep: a review

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    Sleep is essential for diverse aspects of language learning. According to a prominent concept these beneficial effects of sleep rely on spontaneous reactivation processes. A series of recent studies demonstrated that inducing such reactivation processes by re-exposure to memory cues during sleep enhances foreign vocabulary learning. Building upon these findings, the present article reviews recent models and empirical findings concerning the beneficial effects of sleep on language learning. Consequently, the memory function of sleep, its neural underpinnings and the role of the sleeping brain in language learning will be summarized. Finally, we will propose a working model concerning the oscillatory requirements for successful reactivation processes and future research questions to advance our understanding of the role of sleep on language learning and memory processes in general

    Closed-Loop Targeted Memory Reactivation during Sleep Improves Spatial Navigation

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    Sounds associated with newly learned information that are replayed during non-rapid eye movement (NREM) sleep can improve recall in simple tasks. The mechanism for this improvement is presumed to be reactivation of the newly learned memory during sleep when consolidation takes place. We have developed an EEG-based closed-loop system to precisely deliver sensory stimulation at the time of down-state to up-state transitions during NREM sleep. Here, we demonstrate that applying this technology to participants performing a realistic navigation task in virtual reality results in a significant improvement in navigation efficiency after sleep that is accompanied by increases in the spectral power especially in the fast (12\u201315 Hz) sleep spindle band. Our results show promise for the application of sleep-based interventions to drive improvement in real-world tasks

    Overlapping memory replay during sleep builds cognitive schemata

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    Sleep enhances integration across multiple stimuli, abstraction of general rules, insight into hidden solutions and false memory formation. Newly learned information is better assimilated if compatible with an existing cognitive framework or schema. This article proposes a mechanism by which the reactivation of newly learned memories during sleep could actively underpin both schema formation and the addition of new knowledge to existing schemata. Under this model, the overlapping replay of related memories selectively strengthens shared elements. Repeated reactivation of memories in different combinations progressively builds schematic representations of the relationships between stimuli. We argue that this selective strengthening forms the basis of cognitive abstraction, and explain how it facilitates insight and false memory formation

    Testing the Effects of Targeted Memory Reactivation during Rapid Eye Movement Sleep and Wakefulness on Problem-Solving

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    Anecdotal references and sayings attribute a beneficial effect of sleep on solving problems, especially if these are difficult. Currently scientific results are split. Some sleep research teams found beneficial effects on problem-solving, particularly for difficult problems (Sio et al, 2013). Other teams could not corroborate this (Landmann et al, 2016). Moreover, results indicate that sleeping after solving analogical problems facilitates the solution of logical problems after wakening (Monaghan et al, 2015). Sleep is a heterogenous process of distinguishable sleep stages (Rechtschaffen, 1968). Although studies keep providing new evidence for models and theories that postulate how subconscious sleep-facilitated improvements in learning, memory and problem-solving occur, there are no definitive answers yet (Almeida-Filho et al, 2018). As a possible equivalent for memory consolidation, neuronal activity during a task is replayed in a coherent and temporal order in a succeeding rest period (Hoffman & McNaughton, 2002). The reactivations may help to incorporate new types of information into preexisting memories (Gisquet-Verrier & Riccio, 2012). The reactivation of specific memory loops can be triggered in subjects, even when asleep (Rasch et al, 2007). This “targeted memory reactivation” (TMR) at large has produced increases in sleep-dependent memory processing, utilizing either olfactory or auditory stimuli as triggers (Schouten et al, 2017). Evidence has emerged that the rapid eye movement sleep stage (REM sleep) may be directly involved with the selectivity of sleep-dependent memory consolidation (Oudiette et al, 2013; Stickgold & Walker, 2013). REM sleep memory reactivations may reduce self-imposed constraints, thereby facilitating creative and analogical problem-solving (Lewis et al, 2018). This present study used auditory targeted memory reactivation (TMR) of problem-associated memories to facilitate the solution of a specific video game level (Problem-Solving Test, PST). Furthermore, this study used a second video game level with an analogical solution strategy (Analogical Problem-Solving Test, APST), which had been shown to increase the solving rate of logical problems (Monaghan et al, 2015). In the present study 32 subjects participated and were allocated to the REM sleep TMR group (REM Stim) and to the active wakefulness TMR group (Wake Stim). After the video game training session (including an attempt at the Problem-Solving Test), REM Stim subjects slept overnight in the sleep laboratory and auditory TMR was applied during REM sleep. After a 45-minute break, Wake Stim subjects received auditory TMR while working on a vigilance task and pursued their regular day schedule outside the laboratory, to return in the evening for further testing. During the testing session half of each group started with the Problem-Solving Test (PST) and the other half with the Analogical Problem-Solving Test (APST) and all attempted to complete both levels. This study found no beneficial effect for REM sleep TMR over active wakefulness TMR on solving rate or speed of the PST. The theory that REM sleep memory reactivations facilitate problem-solving was not confirmed (Lewis et al, 2018). A beneficial effect of sleep for problem-solving as described by other authors was not found (Beijamini et al, 2014; Sio et al, 2013). PST solving was facilitated by prior APST solving only for REM Stim subjects. APST solving rate was higher in the REM Stim group. These results support that sleep improves analogical problem-solving (Monaghan et al, 2015). Possible confounding effects were mental and mood state, sleepiness and subjective video game experience. Apart from the latter, these effects seem to be partly related to the circadian rhythm (Borb & Achermann, 1999). Future studies should try to replicate these results with control conditions of slow wave sleep TMR and no TMR sleep and wake groups. Additionally, larger sample sizes should be used, to further assess the overall importance of sleep and TMR for problem-solving. Enhancing sleep procedures to optimize cognitive capabilities remain an interesting prospect for further research.Anekdoten und Redewendungen weisen Schlaf einen positiven Effekt insbesondere auf das Lösen von schwierigen Problemen zu. Derzeit ist der Forschungsstand uneins. Manche Studien fanden Belege fĂŒr verbessertes Lösen vor allem schwieriger Probleme durch Schlaf (Sio et al, 2013). Andere fanden keinen Effekt (Landmann et al, 2016). Durch Schlafen nach dem Lösen analoger Probleme verbessere sich das Problemlösen danach (Monaghan et al, 2015). Schlaf ist ein heterogener Prozess unterscheidbarer Schlafstadien (Rechtschaffen, 1968). Obwohl Belege fĂŒr ErklĂ€rungsmodelle der positiven Effekte von Schlaf auf Lernen, GedĂ€chtnis und Problemlösung gefunden wurden, fehlen bisher die abschließenden Beweise (Almeida-Filho et al, 2018). Als mögliches Korrelat der GedĂ€chtniskonsolidierung wiederholen sich kongruente neuronale Aktivierungen wĂ€hrend einer TĂ€tigkeit auch in den folgenden Ruhephasen (Hoffman & McNaughton, 2002). Diese Reaktivierungen können die Integration neuer Informationen in frĂŒhere Erinnerungen ermöglichen (Gisquet-Verrier & Riccio, 2012). Selbst wĂ€hrend des Schlafes lassen sich Reaktivierungen bestimmter Erinnerungen triggern (Rasch et al, 2007). Mit olfaktorischen oder auditorischen Stimuli kann diese „Gezielte Erinnerungsreaktivierung“ (TMR) Effekte von Schlaf auf diese Erinnerungen verstĂ€rken (Schouten et al, 2017). Ein Zusammenhang des Rapid Eye Movement Schlafes (REM Schlaf) mit der SelektivitĂ€t der schlafabhĂ€ngigen GedĂ€chtniskonsolidierung wurde beschrieben (Oudiette et al, 2013; Stickgold & Walker, 2013). GedĂ€chtnisreaktivierungen im REM Schlaf können selbstauferlegte EinschrĂ€nkungen abschwĂ€chen und damit kreatives und analoges Problemlösen fördern (Lewis et al, 2018). Die vorliegende Studie verwendete eine auditorische „Gezielte Erinnerungsreaktivierung“ (TMR) von Problem-assoziierten Erinnerungen um die Lösung eines speziellen Videospiellevels (Problem-Solving Test, PST) zu erleichtern. Ein weiteres Level mit einer analogen Lösungsstrategie (Analogical Problem-Solving Test, APST) wurde eingesetzt, welches Konzept in anderen Studien die Lösungsrate von Problemen erhöhte (Monaghan et al, 2015). An dieser Studie nahmen 32 Probanden teil und wurden der REM Schlaf TMR Gruppe (REM Stim) und der Gruppe mit TMR wĂ€hrend aktiven Wachseins (Wake Stim) zugeteilt. Nach einer Trainingseinheit (inklusive eines Versuches am Problem-Solving Test) schlief die REM Stim Gruppe ĂŒber Nacht im Schlaflabor und erhielt TMR wĂ€hrend des REM Schlafes. Wake Stim Probanden hingegen erhielten nach einer 45-minĂŒtigen Pause die TMR wĂ€hrend eines Vigilanztestes und gingen ihren tĂ€glichen AktivitĂ€ten außerhalb des Labors nach, um abends fĂŒr weitere Tests zurĂŒckzukehren. In der Testeinheit startete die HĂ€lfte jeder Gruppe mit dem Problem-Solving Test (PST) und die andere HĂ€lfte mit dem Analogical Problem-Solving Test (APST) und alle versuchten beide Level zu lösen. Diese Studie fand keine verbesserte Lösungsrate oder -geschwindigkeit des PST durch REM Schlaf TMR im Vergleich zu der TMR wĂ€hrend des aktiven Wachseins. Die Theorie, dass GedĂ€chtnisreaktivierungen im REM Schlaf Problemlösen erleichtern, wurde nicht bestĂ€tigt. (Lewis et al, 2018). Beschriebene Verbesserungen des Problemlösens durch Schlaf konnten nicht bestĂ€tigt werden (Beijamini et al, 2014; Sio et al, 2013). Nur in der REM Stim Gruppe war PST-Lösungsrate höher nach APST-Lösung. Die Lösungsrate des APST selbst war höher in der REM Stim Gruppe. Dies könnte ein Beleg fĂŒr ein verbessertes Lösen analoger Probleme nach dem Schlafen sein (Monaghan et al, 2015). Mögliche konfundierende Faktoren waren geistige und emotionale Verfassung, SchlĂ€frigkeit und subjektives Erleben des Videospiels. Außer letzterem lassen sich diese teilweise durch die zirkadiane Rhythmik erklĂ€ren (Borb & Achermann, 1999). ZukĂŒnftige Studien sollten versuchen diese Ergebnisse mit grĂ¶ĂŸeren Stichproben zu replizieren. Kontrollgruppen mit „Slow Wave“ Schlaf TMR, sowie Schlaf- und Wachgruppen ohne TMR sollten zusĂ€tzlich untersucht werden, um die Bedeutung von Schlaf und TMR auf Problemlösen im Gesamten einzuschĂ€tzen. Die Möglichkeiten einer Optimierung kognitiver FĂ€higkeiten durch additive Prozeduren wĂ€hrend des Schlafes bleiben eine interessante Idee
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