Replay of rule-learning related neural patterns in the prefrontal cortex during sleep

By Adrien Peyrache, Mehdi Khamassi, Karim Benchenane, Sidney I. Wiener, Francesco Battaglia. 2009

782 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

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In Cognitive Neuroscience

Citations in the corpus

Replay in Deep Learning: Current Approaches and Missing Biological Elements (2021, neutral): “…used methods for analyzing replay, such as template matching, principal component analysis, and independent component analysis, have shown high similarity but not an exact match, between activation patterns during waking and sleep (Lee & Wilson, 2002; Louie & Wilson, 2001; Peyrache et al., 2009).”
On simplicity and complexity in the brave new world of large-scale neuroscience. (2015, background): “in insect [23, 20, 24, 25, 26] olfactory systems, mammalian olfactory [27, 26], prefrontal [28, 29, 21, 30, 22], motor and premotor,[31, 32], somatosensory [33], visual [34, 35], hippocampal [36], and brain stem [37] systems) a much smaller number of dimensions than the number of recorded neurons ca”
Awake reactivation of emotional memory traces through hippocampal-neocortical interactions (2016, positive): “Furthermore, replay in the neocortex has been found with increased probability during the occurrence of hippocampal sharp waves (Logothetis et al., 2012; Peyrache et al., 2009).”
Coherent theta oscillations and reorganization of spike timing in the hippocampal- prefrontal network upon learning. (2010, positive): “This would occur during sharp wave/ripple (SPWR) activity in slow-wave sleep (Girardeau et al., 2009; Peyrache et al., 2009b).”
Cellular and Systems Consolidation of Declarative Memory (2017, background): “Some evidence suggests that only during sleep does replay occur in the cortex as well as the hippocampus (Peyrache et al. 2009; Ramanathan et al. 2015).”
Rewarded Outcomes Enhance Reactivation of Experience in the Hippocampus (2009, positive): “Because SWR reactivation occurs after the path is complete and can be coherent with activity in neocortical and striatal areas (Chrobak and Buzsáki, 1996; Ji and Wilson, 2007; Wierzynski et al., 2009; Peyrache et al., 2009; Lansink et al., 2009), reactivation could help link a specific path with rew”
Distinct hippocampal-cortical memory representations for experiences associated with movement versus immobility (2017, positive): “Hippocampal SWRs are also accompanied by coordinated changes in activity patterns in PFC (Jadhav et al., 2016; Logothetis et al., 2012; Peyrache et al., 2009; Remondes and Wilson, 2015; Wang et al., 2015), which reflect a coherent reinstatement of stored representations of experience.”
Efficient Partitioning of Memory Systems and Its Importance for Memory Consolidation (2013, positive): “The analysis proposed in [32,33] should allow Memory Consolidation in Partitioned Neural Systems”
Strengthening Procedural Memories by Reactivation in Sleep (2014, background): “Hippocampal activity precedes replay in neocortical sites and may thus hold a crucial role in the orchestration of memory trace reactivation and integration (Peyrache et al., 2009; Ji & Wilson, 2007).”
Hippocampal replays under the scrutiny of reinforcement learning models. (2018, methodology): “reactivations during sleep in rats before and after a binary decision-making task in a Y-maze (Peyrache et al., 2009).”
Dreaming More Data: Class-dependent Distributions over Diffeomorphisms for Learned Data Augmentation (2015, background): “arlier as a metaphor for generative modeling [32,58]. In dreams, rodents replay behavior, seemingly at a high speed [19], while frontal-cortex replay during slowwave sleep is related to rule learning [46]. In a recent review Stickgold and Walker pointed out that sleep is selective [52]: Sleep seems ”