ArticleFrontiers in neurology2013
Sleep-Dependent Synaptic Down-Selection (II): Single-Neuron Level Benefits for Matching, Selectivity, and Specificity.
Article in Frontiers in neurology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
22 citing papers in PubMed.
- Article
- Ultrastructural effects of sleep and wake on the parallel fiber synapses of the cerebellum.eLife · 2022Article
- Multiple traces and altered signal-to-noise in systems consolidation: Evidence from the 7T fMRI Natural Scenes Dataset.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- The why and how of sleep-dependent synaptic down-selection.Seminars in cell & developmental biology · 2022Article
- Sleep and synaptic down-selection.The European journal of neuroscience · 2020Review
- Article
- Memory corticalization triggered by REM sleep: mechanisms of cellular and systems consolidation.Cellular and molecular life sciences : CMLS · 2018Review
- Activity-Dependent Downscaling of Subthreshold Synaptic Inputs during Slow-Wave-Sleep-like Activity In Vivo.Neuron · 2018Article
- Sleep increases explicit solutions and reduces intuitive judgments of semantic coherence.Learning & memory (Cold Spring Harbor, N.Y.) · 2017Article
- Formation and suppression of acoustic memories during human sleep.Nature communications · 2017Article
- Plasticity during Sleep Is Linked to Specific Regulation of Cortical Circuit Activity.Frontiers in neural circuits · 2017Review
- Cycle-Triggered Cortical Stimulation during Slow Wave Sleep Facilitates Learning a BMI Task: A Case Report in a Non-Human Primate.Frontiers in behavioral neuroscience · 2017Article
- Synaptic refinement during development and its effect on slow-wave activity: a computational study.Journal of neurophysiology · 2016Article
- Sleep-Dependent Potentiation in the Visual System Is at Odds with the Synaptic Homeostasis Hypothesis.Sleep · 2016Article
- Spindle Activity Orchestrates Plasticity during Development and Sleep.Neural plasticity · 2016Review
- Synaptic Homeostasis and Restructuring across the Sleep-Wake Cycle.PLoS computational biology · 2015Article
- Sleep and Motor Learning: Implications for Physical Rehabilitation After Stroke.Frontiers in neurology · 2015Review
- Article
- From the phenomenology to the mechanisms of consciousness: Integrated Information Theory 3.0.PLoS computational biology · 2014Article
- Sleep and the price of plasticity: from synaptic and cellular homeostasis to memory consolidation and integration.Neuron · 2014Review
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Authors and funding
3 authors.
Funding
Abstract
In a companion paper (1), we used computer simulations to show that a strategy of activity-dependent, on-line net synaptic potentiation during wake, followed by off-line synaptic depression during sleep, can provide a parsimonious account for several memory benefits of sleep at the systems level, including the consolidation of procedural and declarative memories, gist extraction, and integration of new with old memories. In this paper, we consider the theoretical benefits of this two-step process at the single-neuron level and employ the theoretical notion of Matching between brain and environment to measure how this process increases the ability of the neuron to capture regularities in the environment and model them internally. We show that down-selection during sleep is beneficial for increasing or restoring Matching after learning, after integrating new with old memories, and after forgetting irrelevant material. By contrast, alternative schemes, such as additional potentiation in wake, potentiation in sleep, or synaptic renormalization in wake, decrease Matching. We also argue that, by selecting appropriate loops through the brain that tie feedforward synapses with feedback ones in the same dendritic domain, different subsets of neurons can learn to specialize for different contingencies and form sequences of nested perception-action loops. By potentiating such loops when interacting with the environment in wake, and depressing them when disconnected from the environment in sleep, neurons can learn to match the long-term statistical structure of the environment while avoiding spurious modes of functioning and catastrophic interference. Finally, such a two-step process has the additional benefit of desaturating the neuron's ability to learn and of maintaining cellular homeostasis. Thus, sleep-dependent synaptic renormalization offers a parsimonious account for both cellular and systems level effects of sleep on learning and memory.
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