Local sleep and wakefulness—the concept and its potential for the understanding and treatment of insomnia disorder

Ramfjord, Lina Stålesen; Hertenstein, Elisabeth; Fehér, Kristoffer; Mikutta, Christian; Schneider, Carlotta L.; Nissen, Christoph; Maier, Jonathan G.

doi:10.1007/s11818-020-00245-w

Cited by 6 publications

(2 citation statements)

References 46 publications

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“…The stochasticity in our model by which stored memories are selectively recalled is mirrored in the randomness of hippocampal replay during sleep that goes beyond the more typical behavior [58], or in free memory recall in humans [59]. The oscillatory recall that supports cognitive computation in our model can also be related to creative thinking [60], to midbrain oscillatory activity during stimulus disambiguation [61], to mind wandering [62] and to local sleep [63].…”

Section: Plos Computational Biologymentioning

confidence: 81%

Cortical oscillations support sampling-based computations in spiking neural networks

et al. 2022

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Being permanently confronted with an uncertain world, brains have faced evolutionary pressure to represent this uncertainty in order to respond appropriately. Often, this requires visiting multiple interpretations of the available information or multiple solutions to an encountered problem. This gives rise to the so-called mixing problem: since all of these “valid” states represent powerful attractors, but between themselves can be very dissimilar, switching between such states can be difficult. We propose that cortical oscillations can be effectively used to overcome this challenge. By acting as an effective temperature, background spiking activity modulates exploration. Rhythmic changes induced by cortical oscillations can then be interpreted as a form of simulated tempering. We provide a rigorous mathematical discussion of this link and study some of its phenomenological implications in computer simulations. This identifies a new computational role of cortical oscillations and connects them to various phenomena in the brain, such as sampling-based probabilistic inference, memory replay, multisensory cue combination, and place cell flickering.

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Section: Plos Computational Biologymentioning

confidence: 81%

Cortical oscillations support sampling-based computations in spiking neural networks

et al. 2022

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“…Local sleep. Recently, the concept of "local sleep" has emerged [20][21][22], where instead of thinking about sleep as being a homogeneous process across the entire brain, different brain regions can be in different sleep stages. Contradictory features of different sleep stages can therefore be observed at the same time, making it hard to identify the correct sleep stage.…”

Section: Biological Factorsmentioning

confidence: 99%

Certainty about uncertainty in sleep staging: a theoretical framework

Gorp

Huijben

Fonseca

et al. 2022

Sleep

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Sleep stage classification is an important tool for the diagnosis of sleep disorders. Because sleep staging has such a high impact on clinical outcome, it is important that it is done reliably. However, it is known that uncertainty exists in both expert scorers and automated models. On average, agreement between human scorers is only 82.6%. In this manuscript, we provide a theoretical framework to facilitate discussion and further analyses of uncertainty in sleep staging. To this end, we introduce two variants of uncertainty, known from statistics and the machine learning community: aleatoric and epistemic uncertainty. We discuss what these types of uncertainties are, why the distinction is useful, where they arise from in sleep staging, and provide recommendations on how this framework can improve sleep staging in the future.

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Local sleep: A new concept in brain plasticity

Avvenuti¹,

Bernardi²

2022

Handbook of Clinical Neurology

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Local sleep and wakefulness—the concept and its potential for the understanding and treatment of insomnia disorder

Abstract: Local sleep and wakefulness-the concept and its potential for the understanding and treatment of insomnia disorderSomnologie 2 • 2020 117

Cited by 6 publications

References 46 publications

Cortical oscillations support sampling-based computations in spiking neural networks

Cortical oscillations support sampling-based computations in spiking neural networks

Certainty about uncertainty in sleep staging: a theoretical framework

Local sleep: A new concept in brain plasticity

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