Sculpting memory during sleep: concurrent consolidation and forgetting

Feld, Gordon B.; Born, Jan

doi:10.1016/j.conb.2017.02.012

Cited by 153 publications

(118 citation statements)

References 68 publications

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“…It is also premature to conclude that ripple events that are coupled to phase angles distributed within the peak-trough transition of slower oscillations are physiological 18,38,39 , whereas those distributed within the trough-peak transition are pathological. Moreover, SOZ incidence ratios of ripple coupling at both phase angles of slower oscillations were increased in mesial temporal recording sites.…”

Section: Discussionmentioning

confidence: 99%

“…By classifying sleep architecture using an amplitude-based criteria, we could recognize epochs of high amplitude slow and delta activity that can stage sleep even in the absence of EMG/EOG. 19 It is also premature to conclude that ripple events that are coupled to phase angles distributed within the peak-trough transition of slower oscillations are physiologic, 18,37,38 whereas those distributed within the trough-peak transition are pathologic. Moreover, SOZ incidence ratios of ripple coupling at both phase angles of slower oscillations were increased in mesial temporal recording sites.…”

Section: Study Limitationsmentioning

confidence: 99%

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Bimodal coupling of ripples and slower oscillations during sleep in patients with focal epilepsy

et al. 2017

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Summary Objective Differentiating pathological and physiological high-frequency oscillations (HFOs) is challenging. In patients with focal epilepsy, HFOs occur during the transitional periods between the up and down state of slow waves. The preferred phase angles of this form of phase-event amplitude coupling are bimodally distributed, and the ripples (80–150 Hz) that occur during the up-down transition more often occur in the seizure onset zone (SOZ). We investigated if bimodal ripple coupling was also evident for faster sleep oscillations, and could identify the SOZ. Methods Using an automated ripple detector, we identified ripple events in 40–60 minute intracranial EEG (iEEG) recordings from 23 patients with medically refractory mesial temporal lobe or neocortical epilepsy. The detector quantified epochs of sleep oscillations and computed instantaneous phase. We utilized a ripple phasor transform, ripple-triggered averaging, and circular statistics to investigate phase event-amplitude coupling. Results We found that at some individual recording sites, ripple event amplitude was coupled with sleep oscillatory phase and the preferred phase angles exhibited two distinct clusters (p<0.05). The distribution of the pooled mean preferred phase angle, defined by combining the means from each cluster at each individual recording site, also exhibited two distinct clusters (p<0.05). Based on the range of preferred phase angles defined by these two clusters, we partitioned each ripple event at each recording site into two groups: depth iEEG peak-trough and trough-peak. The mean ripple rates of the two groups in the SOZ and NSOZ were compared. We found that in the frontal (spindle, p=0.009; theta, p=0.006, slow, p=0.004) and parietal lobe (theta, p=0.007, delta, p=0.002, slow, p=0.001) the SOZ incidence rate for the ripples occurring during the trough-peak transition was significantly increased. Significance Phase-event amplitude coupling between ripples and sleep oscillations may be useful to distinguish pathological and physiological events in patients with frontal and parietal SOZ.

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Section: Discussionmentioning

confidence: 99%

Section: Study Limitationsmentioning

confidence: 99%

Bimodal coupling of ripples and slower oscillations during sleep in patients with focal epilepsy

et al. 2017

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“…If sleep is a response to waking cellular events that "use dependently" cause sleep need (7,26,40) to serve synaptic homeostatic and/or mnemonic sleep functions (41)(42)(43), TDW is expected to capture the homeostatic determinants of the "cost of waking." In support of this, hippocampal θ activity is associated with heightened synaptic plasticity and memory-related potentiation, and long-term potentiation (LTP) in the hippocampus is optimally induced by θ rhythms resembling those seen in exploring animals (44).…”

Section: Hcrt Is An Essential Regulator Of the Eeg Determinants Of Spmentioning

confidence: 99%

Hypocretin (orexin) is critical in sustaining theta/gamma-rich waking behaviors that drive sleep need

Vassalli

Franken

2017

Proc. Natl. Acad. Sci. U.S.A.

121

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Hcrt gene inactivation in mice leads to behavioral state instability, abnormal transitions to paradoxical sleep, and cataplexy, hallmarks of narcolepsy. Sleep homeostasis is, however, considered unimpaired in patients and narcoleptic mice. We find that whereas Hcrt ko/ko mice respond to 6-h sleep deprivation (SD) with a slowwave sleep (SWS) EEG δ (1.0 to 4.0 Hz) power rebound like WT littermates, spontaneous waking fails to induce a δ power reflecting prior waking duration. This correlates with impaired θ (6.0 to 9.5 Hz) and fast-γ (55 to 80 Hz) activity in prior waking. We algorithmically identify a theta-dominated wakefulness (TDW) substate underlying motivated behaviors and typically preceding cataplexy in Hcrt ko/ko mice. Hcrt ko/ko mice fully implement TDW when waking is enforced, but spontaneous TDW episode duration is greatly reduced. A reformulation of the classic sleep homeostasis model, where homeostatic pressure rises exclusively in TDW rather than all waking, predicts δ power dynamics both in Hcrt ko/ko and WT mouse baseline and recovery SWS. The low homeostatic impact of Hcrt ko/ko mouse spontaneous waking correlates with decreased cortical expression of neuronal activityrelated genes (notably Bdnf, Egr1/Zif268, and Per2). Thus, spontaneous TDW stability relies on Hcrt to sustain θ/fast-γ network activity and associated plasticity, whereas other arousal circuits sustain TDW during SD. We propose that TDW identifies a discrete global brain activity mode that is regulated by contextdependent neuromodulators and acts as a major driver of sleep homeostasis. Hcrt loss in Hcrt ko/ko mice causes impaired TDW maintenance in baseline wake and blunted δ power in SWS, reproducing, respectively, narcolepsy excessive daytime sleepiness and poor sleep quality.hypocretin/orexin | narcolepsy | sleep homeostasis | brain theta oscillations | waking substate W akefulness encompasses a wide spectrum of arousal levels, sensorimotor processing modes, and behaviors, reflected in the electroencephalogram (EEG) by a great variety of signal patterns (1). Fourier transform decomposes the signal into multiple frequency ranges, defining δ, θ (5 to 10 Hz), and γ (>30 Hz) oscillatory components. However, although the EEG has been used to define wakefulness and distinguish it from slow-wave and paradoxical sleep (SWS and PS) for decades, a formal cartography of waking substates, associated EEG features, and their significance for the animal is largely lacking. Likewise, definition of the relation between waking quality and subsequent sleep content has evolved little since enunciation of the twoprocess model of sleep regulation (2) in which a sleep/wakedependent homeostatic "process S," reflected in EEG δ power during SWS, regulates sleep propensity as a function of prior waking duration regardless of waking quality. Later studies described behaviors (3, 4) or EEG components (5, 6) that disproportionally affect the sleep homeostat. Different procedural, cognitive, or emotional experience differentially impacts subsequent SWS δ powe...

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“…According to "Complementary Learning System" theory (McClelland et al, 1995), the hippocampus is responsible for the fast acquisition of new information, while the neocortex would more gradually learn a generalized and distributed representation. Indeed, hippocampal memory replay is currently thought to be the primary mechanism by which the hippocampus can train the neocortex on the newly encoded information (French, 1999;Rasch and Born, 2013;Merhav et al, 2014;Feld and Born, 2017).…”

Section: Catastrophic Forgetting and Biological Systemsmentioning

confidence: 99%

Can sleep protect memories from catastrophic forgetting?

González

Sokolov

Bazhenov

2019

Preprint

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Previously encoded memories can be damaged by encoding of new memories, especially when they are relevant to the new data and hence can be disrupted by new training -a phenomenon called "catastrophic forgetting". Human and animal brains are capable of continual learning, allowing them to learn from past experience and to integrate newly acquired information with previously stored memories. A range of empirical data suggest important role of sleep in consolidation of recent memories and protection of the past knowledge from catastrophic forgetting. To explore potential mechanisms of how sleep can enable continual learning in neuronal networks, we developed a biophysically-realistic thalamocortical network model where we could train multiple memories with different degree of interference. We found that in a wakelike state of the model, training of a "new" memory that overlaps with previously stored "old" memory results in degradation of the old memory. Simulating NREM sleep state immediately after new learning led to replay of both old and new memories -this protected old memory from

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Sculpting memory during sleep: concurrent consolidation and forgetting

Cited by 153 publications

References 68 publications

Bimodal coupling of ripples and slower oscillations during sleep in patients with focal epilepsy

Bimodal coupling of ripples and slower oscillations during sleep in patients with focal epilepsy

Hypocretin (orexin) is critical in sustaining theta/gamma-rich waking behaviors that drive sleep need

Can sleep protect memories from catastrophic forgetting?

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