Sleep-dependent memory consolidation

By Robert Stickgold. 2005

1,844 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

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Citations in the corpus

Synaptic weight decay with selective consolidation enables fast learning without catastrophic forgetting (2019, background): “This is explained by the decay of the fast component that leads to a forgetting of the sample-speciﬁc noise, while the class-relevant information is consolidated akin to the consolidation and the semantization of memory during sleep (Stickgold, 2005).”
Replay in Deep Learning: Current Approaches and Missing Biological Elements (2021, neutral): “, 2005, 2002a), motor adaptation (Stickgold, 2005), and goal-related sequence tasks (Albouy et al.”
Hippocampal replay of extended experience (2009, positive): “For example, the reverse replay event in Figure 4D proceeds in the B/A direction (from 7.5 to 2.5 m on the track) but uses the hippocampal ensemble code associated with running in the opposite A/B direction, as indicated by the blue color.”
Biologically inspired sleep algorithm for increased generalization and adversarial robustness in deep neural networks (2020, background): “During sleep, there is reactivation of neurons involved in previously learned activity (Stickgold (2005)) and this reactivation is likely to invoke the same spatio-temporal pattern of neuronal ﬁring as the pattern observed during training in the awake state (Wilson & McNaughton, 1994).”
The Parieto-Frontal Integration Theory (P-FIT) of intelligence: Converging neuroimaging evidence (2007, background): “A large body of data clearly demonstrates that sleep does have an essential role for different types of learning andmemory, and, likewise, for our intelligence (Hobson 2005; Maquet 2001; Stickgold 2005; Stickgold & Walker 2005).”
A single pair of neurons links sleep to memory consolidation in Drosophila melanogaster (2015, background): “Accumulating evidence suggests that sleep plays a role in promoting the consolidation of memory (Stickgold, 2005; Diekelmann and Born, 2010; Mednick et al., 2011; Abel et al., 2013; Rasch and Born, 2013).”
Sleep Preferentially Enhances Memory for Emotional Components of Scenes (2008, background): “Although most studies to date have focused on procedural memory (Stickgold, 2005), emerging evidence suggests that sleep benefits episodic memory as well (Born, Rasch, & Gais,”
Sleep and Athletic Performance: The Effects of Sleep Loss on Exercise Performance, and Physiological and Cognitive Responses to Exercise (2015, background): “Indeed, increases in perceived effort accompanied by a reduction in power output would support neuromuscular causes of fatigue [104], possibly indicating an association between a reduction in central drive and the neural theory of sleep [36, 103, 105].”
Artificial Intelligence and Surgical Decision-Making (2019, background): “52,53 For a surgical oncologist with a busy outpatient clinic, automated production of prognostic data from artificial intelligence models could improve efficiency and preserve face-to-face patient-surgeon interactions by obviating manual data acquisition and entry into prognostic models.”
Processing of emotional reactivity and emotional memory over sleep (2012, positive): “Accumulating evidence points to an enhancing effect of sleep on memory consolidation (Stickgold, 2005).”