Learning-enhanced coupling between ripple oscillations in association cortices and hippocampus
Open accessAbstract
Memory transfer for long-term storage: Explicit memory formation involves the transfer of rapidly encoded information from the hippocampus to long-term storage sites in the association cortex. Khodagholy et al. developed a microelectrode system for large-scale simultaneous electrophysiological monitoring of multiple sites in the rat neocortex. They observed discrete high-frequency neocortical oscillations called ripples only in the association cortex. These cortical ripples shared many properties with hippocampal ripples. Hippocampal ripples were coupled with cortical ripples in the posterior parietal cortex, an association cortical area linked to navigational planning. This coupling was increased during sleep after the induction of long-term hippocampal-dependent spatial memory. Science , this issue p. 369
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Spontaneous memory reactivations can be decoded from EEG during SO-spindle complexes after learning word-image pairs using multivariate classification.
“Spontaneous memory reactivations can be decoded from the EEG signal during SO-spindle complexes after the participants had learned word-image pairs using multivariate classification 114 (Figure 3).”
From Sleep—A brain-state serving systems memory consolidation (2023) · cites this paper as [114]
The passages describing the methods and learning task state that this study recorded cortical and hippocampal activity in rats trained on a spatial cheeseboard maze, not EEG from participants learning word–image pairs. The reported result was stronger hippocampal–cortical ripple coupling during postlearning sleep; the source does not report decoding memory reactivations with multivariate classification. (LLM, conf=0.86)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredAnalyses of multiunit neuronal responses in retrosplenial cortex to sharp-wave ripple events in CA1 during awake rest did not reveal notable impairments in timing or magnitude in BACE1 knockout animals compared to controls.
“In addition, analyses of multiunit neuronal responses in retrosplenial cortex to sharp-wave ripple (SWR) events in CA1 during awake rest [41] did not reveal any notable impairments in the timing or magnitude of cortical neuronal responses in the BACE1 knockout animals compared to controls (S15 Fig).”
From Selective suppression of oligodendrocyte-derived amyloid beta rescues neuronal dysfunction in Alzheimer’s disease (2024) · cites this paper as [41]
The paper reports ripples in retrosplenial cortex, cortical neural firing associated with ripples, and cortical ripples during quiet wakefulness (Abstract section; page unavailable). It does not establish the specific analysis of retrosplenial multiunit responses to CA1 events during awake rest. The BACE1 knockout comparison appears after citation [41] and points to the citing paper’s S15 Fig, so it is not attributed to this source. (LLM, conf=0.83)
Experimental — accuracy not yet measuredReactivations were found to occur coupled to hippocampal ripples and to spindles coupled to SOs, but not to solitary SOs or spindles.
“Reactivations were found to occur coupled to the oscillatory hallmarks of non-REM sleep, specifically to hippocampal ripples 112 and to spindles coupled to SOs, but not to solitary SOs or spindles”
From Sleep—A brain-state serving systems memory consolidation (2023) · cites this paper as [114]
The paper reports that hippocampal ripples co-occur with cortical ripples during NREM sleep and links ripple coupling to the transfer of memory traces (Abstract; passage on Fig. 2). This supports an association between hippocampal ripples and memory-related activity, but it does not report measuring reactivations coupled to those ripples. Citation 112 follows “hippocampal ripples,” so the later comparison with solitary SOs or spindles is not treated as attributed to this source. (LLM, conf=0.79)
Experimental — accuracy not yet measuredRipples also occur during quiet wakefulness and outside the hippocampus, including entorhinal cortex and neocortex.
“They also occur during quiet wakefulness, and outside the hippocampus, including entorhinal cortex and neocortex.[190][191][192]”
From Sleep—A brain-state serving systems memory consolidation (2023) · cites this paper as [191]
The passage on posterior parietal cortex (section labeled Abstract; page unavailable) reports ripples during quiet wakefulness, and other passages report ripples in neocortical association areas. The paper mentions the entorhinal cortex as a possible route of excitation, but does not report ripples occurring there. (LLM, conf=0.87)
Experimental — accuracy not yet measuredIn both of these studies, the accuracy of the classifier to correctly identify the previously encoded stimulus category was positively correlated to later memory recall.
“In both of these studies, the accuracy of the classifier to correctly identify the previously encoded stimulus category was positively correlated to later memory recall”
From Sleep—A brain-state serving systems memory consolidation (2023) · cites this paper as [114]
The study description and results (indexed under Abstract; page unavailable) concern rats learning reward locations and increased hippocampal–cortical ripple coupling after training. Searches for classifier accuracy, encoded stimulus categories, and subsequent recall found no passage reporting the claimed correlation. (LLM, conf=0.75)
Experimental — accuracy not yet measured
Using machine learning classifiers, categories of previously encoded stimuli could be decoded solely from sleep EEG, revealing category-specific information is reactivated during sleep.
“Using machine learning classifiers, categories of previously encoded stimuli (e.g., faces vs. houses; objects vs. scenes) could be decoded solely from sleep EEG, revealing that category-specific information is reactivated during sleep.”
From Sleep—A brain-state serving systems memory consolidation (2023) · cites this paper as [114]
Our copy reports NeuroGrid and hippocampal recordings in rats and stronger ripple coupling during sleep after spatial learning (Abstract; page unavailable). Searches for machine-learning classification, stimulus categories, and decoding from sleep EEG found no passage addressing those claims. (LLM, conf=0.76)
Experimental — accuracy not yet measuredSpindles co-occur with SOs, with the depolarizing SO upstate driving thalamic generation of spindles.
“Spindles co-occur with SOs, with the depolarizing SO upstate driving the thalamic generation of spindles.4,114,176”
From Sleep—A brain-state serving systems memory consolidation (2023) · cites this paper as [114]
The passage labeled Abstract (no page supplied) links cortical ripples to slow-oscillation down-to-up transitions and separately links ripples to spindles. It does not say that spindles co-occur with slow oscillations or that an SO upstate drives thalamic spindle generation. Searches for those relationships found no supporting passage in our copy. (LLM, conf=0.70)
Experimental — accuracy not yet measuredDecoding classification accuracy strongly depended on the precision of SO-spindle coupling, which in turn strongly correlated with memory performance after sleep.
“However decoding classification accuracy strongly depended on the precision of SO-spindle coupling, which in turn strongly correlated with memory performance after sleep.”
From Sleep—A brain-state serving systems memory consolidation (2023) · cites this paper as [114]
The passages on sleep oscillations (section labeled Abstract; page unavailable) describe ripple–spindle timing and ripples occurring near slow-oscillation transitions. The postlearning passage reports stronger hippocampal–cortical ripple coupling. Searches for decoding classification accuracy and slow-oscillation–spindle coupling found no passage linking coupling precision to decoding accuracy or post-sleep memory performance. (LLM, conf=0.77)
Experimental — accuracy not yet measured
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- Authors
- Khodagholy, D., Gelinas, J. N., & Buzsáki, G.
- Affiliations
- New York University (US)
- Columbia University Irving Medical Center (US)
- Corresponding author
- Khodagholy, Dion
- Gelinas, Jennifer N.
- Buzsáki, György
- Venue
- Science
- Published
- 2017-10-20
- Volume
- 358
- Issue
- 6361
- Pages
- 369-372
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC5872145
- OpenAlex
- W2765562806
- Semantic Scholar
- 6395c6b34ac2a29c386138b79821677f7683fa34
- Cited by
- 357
- References
- 36
- Citations by year
- 2026: 22 · 2025: 33 · 2024: 31 · 2023: 48 · 2022: 35 · 2021: 41 · 2020: 49 · 2019: 59 · 2018: 38 · 2017: 1
- FWCI
- 23.06
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIH Office of the Director (UO1NS099705)
- Simons Foundation (Junior Fellow)
- March of Dimes Foundation (fellow of Pediatric Scientist development program)
- NIH (U01NS090583, MH107396)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Sleep and Wakefulness Research
- Keywords
- sharp-wave ripples, memory consolidation, sleep-dependent memory consolidation, association cortex, parietal cortex, prefrontal cortex, hippocampus, local field potentials, neural spiking, learning
- MeSH terms
- Memory Consolidation, Animals, Electroencephalography, Hippocampus, Male, Sleep, Neocortex, Rats, Long-Evans, Rats
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