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Hippocampal Replay of Extended Experience
Open accessAbstract
During pauses in exploration, ensembles of place cells in the rat hippocampus re-express firing sequences corresponding to recent spatial experience. Such "replay" co-occurs with ripple events: short-lasting (approximately 50-120 ms), high-frequency (approximately 200 Hz) oscillations that are associated with increased hippocampal-cortical communication. In previous studies, rats exploring small environments showed replay anchored to the rat's current location and compressed in time into a single ripple event. Here, we show, using a neural decoding approach, that firing sequences corresponding to long runs through a large environment are replayed with high fidelity and that such replay can begin at remote locations on the track. Extended replay proceeds at a characteristic virtual speed of approximately 8 m/s and remains coherent across trains of ripple events. These results suggest that extended replay is composed of chains of shorter subsequences, which may reflect a strategy for the storage and flexible expression of memories of prolonged experience.
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“The reactivation of task-relevant regions was found to be particular prominent during sleep oscillatory events linked to memory consolidation, such as spindles and SOs.”
From Sleep—A brain-state serving systems memory consolidation (2023) · cites this paper as [108]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“both sleep and wake replay can represent knowledge about an environment and also share anticipatory features, such that they can e.g., include offline ''pre-activations'' of trajectories entailing visible but yet unexplored paths and locations.”
From Sleep—A brain-state serving systems memory consolidation (2023) · cites this paper as [148]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
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“Spindle activity is increased over cortical regions involved in prior learning and, moreover, positively correlates with post sleep retrieval performance 180,181 and appears to accompany memory reactivations during sleep.108,114”
From Sleep—A brain-state serving systems memory consolidation (2023) · cites this paper as [108]
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“Reactivations of hippocampal cell firing patterns occur also during waking when the animal rests after task performance or during brief pauses of active behavior like explo-ration or running in a maze (191, 268, 556, 673, 870; see Ref. 175 for a review).”
From About Sleep's Role in Memory (2013) · cites this paper as [268]
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“In larger experimental environments, both forward and reverse replay can occur over multiple SW-R events thereby covering longer distances (268).”
From About Sleep's Role in Memory (2013) · cites this paper as [268]
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Citations
Cites
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“…replay detection in the decoded spatial domain affords advantages over methods that examine firing order across individual units, such as pair-wise correlation (Wilson and McNaughton, 1994) and spike-sequence detection (Diba and Buzsáki, 2007; Foster and Wilson, 2006; Lee and Wilson, 2004).”
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“This interpretation of the functional role of awake replay is also consistent with work suggesting a high degree of overlap in the cognitive processes supporting both episodic recall and the evaluation of future events in humans (Buckner and Carroll, 2007; Schacter et al., 2007).”
InfluentialDynamics of the Hippocampal Ensemble Code for Space
Wilson, M. A., & McNaughton, B. L. (1993) · Science · doi:10.1126/science.8351520 · Cited by 2,350 · cited 3×
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Self-citationSleep-dependent memory consolidation
Stickgold, R. (2005) · Nature · doi:10.1038/nature04286 · Cited by 1,857 · cited 2×
“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.”
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Items 501–600 of 806
Cerebellar Cortex 4–12 Hz Oscillations and Unit Phase Relation in the Awake Rat
Lévesque, M., Gao, H., Southward, C., Langlois, J. M. P., Léna, C., & Courtemanche, R. (2020) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2020.475948 · Cited by 9
“The particular ‘‘pauses’’ in the Purkinje cell firing to the deep cerebellar nuclei could be facilitated by the 4–12 Hz rhythm across the cerebellar cortex (De Schutter and Steuber, 2009), favoring synchronicity of firing towards the nuclei (Jaeger, 2011).”
BackgroundLippmann, K., Klaft, Z., Salar, S., Hollnagel, J., Valero, M., & Maslarova, A. (2022) · Neurobiology of Disease · doi:10.1016/j.nbd.2022.105929 · Cited by 8
Imagining the Possibilities: Ripples, Routes, and Reactivation
Knierim, J. J. (2009) · Neuron · doi:10.1016/j.neuron.2009.08.002 · Cited by 8
“Unlike the extended reactivations of Davidson et al. (2009), the putative VTE sweeps of Johnson and Redish (2007) were not associated with SW-R events.”
BackgroundCorrespondence Theory of Semantic Information
Miłkowski, M. (2021) · The British Journal for the Philosophy of Science · doi:10.1086/714804 · Cited by 10
Prioritizing replay when future goals are unknownPreprint
Sagiv, Y., Akam, T. E., Witten, I. B., & Daw, N. D. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.02.29.582822 · Cited by 8
“In particular, sequential replay of nonlocal trajectories during sharp-wave ripples in the Preprint hippocampal place cell system [1, 2, 3, 4, 5, 6] (and similar events else-where [7, 8, 9]) serve as a tantalizing example suggesting some kind of navigation-related computation [10, 5, 11, 12, 13,…”
BackgroundThe hippocampus contributes to retroactive stimulus associations during trace fear conditioning
Puhger, K. R., Crestani, A. P., Diniz, C. R. A. F., & Wiltgen, B. J. (2024) · iScience · doi:10.1016/j.isci.2024.109035 · Cited by 10
“9, 13 , These replay occur rapidly ( 150– 29 Edward Tolman wrote, ‘‘ Learning what to avoid . may occur exclusively during the period after the shock ’’ .”
BackgroundBlanco, I., Deasy, S., Amontree, M., Gabriel, M., Caccavano, A., Vicini, S., Glasgow, E. F., & Conant, K. E. (2025) · Molecular Psychiatry · doi:10.1038/s41380-025-03007-y · Cited by 7
“Longer duration events are increased during demanding mnemonic tasks and are thought to facilitate the transfer of more relevant information possibly via increasing the number of embedded ripple events [56, 57].”
Between planning and map building: Prioritizing replay when future goals are uncertain
Sagiv, Y., Akam, T., Witten, I. B., & Daw, N. D. (2025) · Neuron · doi:10.1016/j.neuron.2025.09.021 · Cited by 23
Inhibition enhances memory capacity: optimal feedback, transient replay and oscillations
Kammerer, A., Tejero-Cantero, Á., & Leibold, C. (2012) · Journal of Computational Neuroscience · doi:10.1007/s10827-012-0410-z · Cited by 8
“The response of a population of place cells hence encodes the position of an animal in an environment and a spatial trajectory of this animal is represented by a sequence of active place cells (e.g. Dragoi and Buzsáki 2006; Davidson et al. 2009).”
Eszopiclone and Zolpidem Produce Opposite Effects on Hippocampal Ripple Density
Becker, L. A., Penagos, H., Flores, F. J., Manoach, D. S., Wilson, M. A., & Varela, C. (2022) · Frontiers in Pharmacology · doi:10.3389/fphar.2021.792148 · Cited by 7
Self-citationOkada, R., Ikegaya, Y., & Matsumoto, N. (2024) · Biological and Pharmaceutical Bulletin · doi:10.1248/bpb.b24-00118 · Cited by 9
Nested compressed co-representations of multiple sequential experiences during sleep
Liu, K., Sibille, J., & Dragoi, G. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01703-6 · Cited by 11
Human single-unit recordings reveal a link between place-cells and episodic memory
Niediek, J., & Bain, J. S. (2014) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2014.00158 · Cited by 7
“An additional, possibly clearer analysis would have been the prediction of the objects’ locations based on the recall responses (or similarity scores), similar to an analysis by Davidson et al. (2009).”
ResultNoguchi, W., Iizuka, H., & Yamamoto, M. (2017) · Adaptive Behavior · doi:10.1177/1059712317711487 · Cited by 7
Hippocampal place cells are topographically organized, but physical space has nothing to do with it
França, T. F. A., & Monserrat, J. M. (2019) · Brain Structure and Function · doi:10.1007/s00429-019-01968-9 · Cited by 7
Retrospective Inference as a Form of Bounded Rationality, and Its Beneficial Influence on Learning
FitzGerald, T. H. B., Penny, W. D., Bonnici, H. M., & Adams, R. A. (2020) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2020.00002 · Cited by 8
“On the further supposition that retrospective inference is implemented using filtering and smoothing as described above, this leads to the hypothesis that forward and backward sweeps through recently encountered states, as are known to occur in the hippocampus (Diba and Buzsáki, 2007; Pastalkova et al., 2008; Davidson…”
MethodCharacterizing hippocampal replay using hybrid point process state space models
Denovellis, E. L., Frank, L. M., & Eden, U. T. (2019) · Asilomar Conference on Signals, Systems and Computers (ACSSC) · doi:10.1109/ieeeconf44664.2019.9048688 · Cited by 10
“Because replays have a characteristic speed of approximately 10 m/s [10], we define our continuous state transition (not to be confused with the continuous trajectory state) as:”
BackgroundCrystal, J. D. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108564113.012 · Cited by 7
Adaptive erasure of spurious sequences in sensory cortical circuits
Bernacchia, A., Fiser, J., Hennequin, G., & Lengyel, M. (2022) · Neuron · doi:10.1016/j.neuron.2022.03.006 · Cited by 7
“Moreover, during periods of inactivity, although the replay of either of these sequences in the hippocampus is known to occur in both the forward and reverse direction, forward replay is significantly more frequent than reverse replay (Diba and Buzsáki, 2007; Davidson et al., 2009), thus again avoiding the collapse of…”
Models for Neural Spike Computation and Cognition
Staelin, D. H., & Staelin, C. (2011) · Cited by 6
Hippocampal theta sequences in REM sleep during spatial learningPreprint
Zielinski, M. C., Shin, J. D., & Jadhav, S. P. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.04.15.439854 · Cited by 8
“760 Theta Sequence Validation: Sequence Scores 761 For every putative theta sequence and every trajectory decoding template, the slope/line 762 fitting procedure from (Davidson et al., 2009; Kloosterman et al., 2014; Feng et al., 2015) was 763 used.”
MethodInfluentialSubspace communication in the hippocampal–retrosplenial axis
Gonzalez, J., Vöröslakos, M., Aykan, D., Soto, N., Nitzan, N., Swanson, R., Karadas, M., Chen, Z. S., & Buzsáki, G. (2026) · Nature · doi:10.1038/s41586-026-10481-z · Cited by 7
“For replay analysis 73,74 , we identified candidate events during post-maze NREM sleep as intervals in which the population firing rate exceeded 2 s.d. above the mean.”
Thomschewski, A. C., Gerner, N., Langthaler, P. B., Trinka, E., Bathke, A. C., Fell, J., & Höller, Y. (2020) · Frontiers in Neurology · doi:10.3389/fneur.2020.563577 · Cited by 6
Shapiro, M. L. (2011) · Neuron · doi:10.1016/j.neuron.2011.08.006 · Cited by 6
Sequential memory improves sample and memory efficiency in episodic control
Freire, I. T., Amil, A. F., & Verschure, P. F. M. J. (2024) · Nature Machine Intelligence · doi:10.1038/s42256-024-00950-3 · Cited by 6
“Both of these solutions are partially inspired by some features of the hippocampal episodic memory in biological systems, in particular the known phenomenon of the acquisition, retention and replay of stored behavioural sequences 16 .”
Sato, Y., Mizuno, H., Matsumoto, N., & Ikegaya, Y. (2021) · Physiology International · doi:10.1556/2060.2021.00001 · Cited by 6
Context-independent expression of spatial code in hippocampus
Kapl, S., Tichánek, F., Zitricky, F., & Ježek, K. (2022) · Scientific Reports · doi:10.1038/s41598-022-25006-7 · Cited by 7
O’Donnell, P. (2013) · Neuron · doi:10.1016/j.neuron.2013.10.012 · Cited by 6
“Replay of exploration-associated hippocampal activity during rest is an important aspect of spatial learning (Davidson et al., 2009; Karlsson and Frank, 2009; Skaggs and McNaughton, 1996).”
BackgroundДавидович, Ц. В. (2014) · Mathematical Biology and Bioinformatics · doi:10.17537/2014.9.216 · Cited by 6
Singer, A. C., Franzesi, G. T., Kodandaramaiah, S. B., Flores, F. J., Cohen, J. D., Lee, A. K., Börgers, C., Forest, C. R., Kopell, N., & Boyden, E. S. (2017) · Journal of Neurophysiology · doi:10.1152/jn.00116.2017 · Cited by 6
“…of the filtered LFP. Spikes that occurred during the SWR and during the 250 ms before and after the ripples were classified as SWR spikes because population spiking related to SWRs (such as replay events) often extends before and after the SWR itself (Davidson et al. 2009; Dragoi and Tonegawa 2011).”
BackgroundExperience-dependent persistent Arc expression is reduced in the aged hippocampus
Gheidi, A., Damphousse, C. C., & Marrone, D. F. (2020) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2020.07.032 · Cited by 6
Computational models of Idling brain activity for memory processing
Fukai, T. (2022) · Neuroscience Research · doi:10.1016/j.neures.2022.12.024 · Cited by 7
Overnight exposure to pink noise could jeopardize sleep-dependent insight and pattern detection
Vickrey, B., & Lerner, I. (2023) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2023.1302836 · Cited by 7
“…to the transfer and integration of information from the hippocampus to the neocortex that yields memory consolidation (McClelland et al., 1995; Davidson et al., 2009; Gupta et al., 2010; Klinzing et al., 2019), with some recent models suggesting replay’s time-compressed nature plays a core…”
BackgroundEnzyme replacement therapy with imiglucerase in Taiwanese patients with type I Gaucher disease.
Hsu, C., Chien, Y., Lai, M., & Hwu, W. (2002) · PubMed · Cited by 6
Linderman, S. W., Johnson, M. J., Wilson, M. A., & Chen, Z. S. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1411.7706 · Cited by 6
Self-citationGroßberger, L., Battaglia, F. P., & Vinck, M. A. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/252791 · Cited by 7
Regular cycling between representations of alternatives in the hippocampusPreprint
Kay, K., Chung, J. E., Sosa, M., Schor, J. S., Karlsson, M. P., Larkin, M. C., Liu, D. F., & Frank, L. M. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/528976 · Cited by 7
Replay as structural inference in the hippocampal-entorhinal systemPreprint
Evans, T., & Burgess, N. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.08.07.241547 · Cited by 7
Grosmark, A., Sparks, F. T., Davis, M. J., & Losonczy, A. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.08.20.259879 · Cited by 6
Replay of procedural experience is independent of the hippocampusPreprint
Thompson, E. J., Rollik, L. B., Waked, B., Mills, G., Kaur, J., Geva, B., Carrasco-Davis, R., George, T. M., Dominé, C., Dorrell, W., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.06.05.597547 · Cited by 6
“…expert and lesioned expert mouse. k. Average movement variability (standard deviation from mean trajectory) across the four subsequence trajectories for novice mice (n = 8 mice, n = 18 sessions) and expert mice before and after lesion to DLS (paired t-test; p = 0.0085, n = 5 mice). decoding 35-38 .”
BackgroundInfluentialProbability of Repeating Patterns in Simultaneous Neural Data
Smith, A. C., Nguyen, V., Karlsson, M. P., Frank, L. M., & Smith, P. (2010) · Neural Computation · doi:10.1162/neco_a_00020 · Cited by 5
“More recent approaches involve using either decoding to determine whether the place cell sequence represents a meaningful trajectory (Karlsson & Frank, 2009; Davidson, Kloosterman, & Wilson, 2009) or use of high-throughput temporal data mining algorithms (Laxman, Sastry, & Unnikrishnan, 2007).”
MethodKharybina, Z., Давидович, Ц. В., & Kulakov, S. V. (2014) · Applied Mathematical Sciences · doi:10.12988/ams.2014.312681 · Cited by 5
“It is shown that trajectory episodes are functionally similar to the SWR associated events and are repeating episode sequences (replay) [5,6,9,10].”
BackgroundExecution of new trajectories toward a stable goal without a functional hippocampus
Duszkiewicz, A. J., Rossato, J. I., Moreno, A., Takeuchi, T., Yamasaki, M., Genzel, L., Spooner, P. A., Canals, S., & Morris, R. (2023) · Hippocampus · doi:10.1002/hipo.23497 · Cited by 5
“The presence of the animal at a goal location is associated with awake SWR-associated hippocampal replay events that include (Davidson et al., 2009; Diba & Buzsáki, 2007; Foster & Wilson, 2006; Pfeiffer & Foster, 2013), but are not limited to, representations of immediate past and future…”
BackgroundA unifying account of replay as context-driven memory reactivation
Zhou, Z., Kahana, M. J., & Schapiro, A. C. (2026) · eLife · doi:10.1101/2023.03.22.533833 · Cited by 7
Validation of a rodent model of episodic memory replay
Sheridan, C. L., Panoz‐Brown, D., Shiffrin, R. M., & Crystal, J. D. (2024) · Learning & Behavior · doi:10.3758/s13420-024-00632-5 · Cited by 5
“…wave ripple complexes consisting of transient, brief, high-frequency network oscillations), a phenomenon known as hippocampal replay (Carr et al., 2011; Davidson et al., 2009; Diba & Buzsáki, 2007; Foster & Wilson, 2006; MacDonald et al., 2011; O'Keefe & Dostrovsky, 1971; Pfeiffer & Foster, 2013).”
Goal-Directed Sequences in the Hippocampus
Schmidt, B., Wikenheiser, A. M., & Redish, A. D. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-812098-9.00006-1 · Cited by 5
A Variable Clock Underlies Internally Generated Hippocampal Sequences
Deng, X., Chen, S., Sosa, M., Karlsson, M. P., Wei, X.-X., & Frank, L. M. (2022) · Journal of Neuroscience · doi:10.1523/jneurosci.1120-21.2022 · Cited by 5
“Time-compressed versions of these sequences are also seen during hippocampal sharp-wave ripple (SWR) events (Lee and Wilson, 2002; Foster and Wilson, 2006; Davidson et al., 2009; Karlsson and Frank, 2009).”
BackgroundDiCola, N. M., Lacy, A. L., Bishr, O. J., Kimsey, K. M., Whitney, J. L., Lovett, S. D., Burke, S. N., & Maurer, A. P. (2022) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2022.04.014 · Cited by 5
“They may also reflect synaptic reorganization that occurs during behavior (Foster and Wilson, 2006; Csicsvari et al., 2007; Davidson et al., 2009; Atherton et al., 2015; Buzsáki, 2015; Ambrose et al., 2016; Deng et al., 2016; Cazin et al., 2020), although some findings have challenged that hypothetical role of reactiv…”
BackgroundAssociative Reactivation of Place–Reward Information in the Hippocampal–Ventral Striatal Circuitry
Lansink, C. S., & Pennartz, C. M. A. (2014) · Springer series in computational neuroscience · doi:10.1007/978-1-4939-1969-7_4 · Cited by 4
“[ 96 ]).”
BackgroundBeyond replay: Introduction to the special issue on hippocampal replay
Redish, A. D. (2019) · Hippocampus · doi:10.1002/hipo.23184 · Cited by 5
Behavioral clusters revealed by end-to-end decoding from microendoscopic imagingPreprint
Chang, C.-J., Guo, W., Zhang, J. J., Newman, J., Sun, S.-H., & Wilson, M. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.04.15.440055 · Cited by 7
“…at speeds above 5 cm/s (RUN), because previous studies have demonstrated that the hippocampal neurons had very different response profiles when the animal was resting or moved at very slow speeds (STOP) (Ahmed and Mehta, 2012; Davidson et al., 2009; Geisler et al., 2007; Ólafsdóttir et al., 2017).”
ResultInfluentialSelf-citationThermoMaze behavioral paradigm for assessing immobility-related brain events in rodentsPreprint
Vöröslakos, M., Zhang, Y., McClain, K., Huszár, R., Rothstein, A., & Buzsáki, G. (2023) · eLife · doi:10.7554/elife.90347 · Cited by 5
“…to replay activity patterns observed during previous spatial navigation experiences ( Foster and Wilson, 2006 ; O’Neill et al., 2006 ; Diba and Buzsáki, 2007 ) and can even be predictive of activity during future experiences ( Davidson et al., 2009 ; Gupta et al., 2010 ; Karlsson and Frank, 2009 ).”
Asabuki, T., & Claudia Clopath, A. (2024) · eLife · doi:10.7554/elife.95243 · Cited by 5
A unifying account of replay as context-driven memory reactivationPreprint
Zhou, Z., Kahana, M. J., & Schapiro, A. C. (2024) · eLife · doi:10.7554/elife.99931.1 · Cited by 5
Spontaneous emergence and evolution of neuronal sequences in recurrent networksPreprint
Shao, S., Riquelme, J. L., & Gjorgjieva, J. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.09.27.615499 · Cited by 6
No evidence for a preferential role of sleep in episodic memory abstraction
Talamini, L. M., van Moorselaar, D., Bakker, R., Bulath, M., Szegedi, S., Sinichi, M., & De Boer, M. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.871188 · Cited by 4
“This might be related to observations in rodents showing that hippocampocortical replay occurs not only during sleep but also during awake rest and consummatory behaviours (Foster and Wilson, 2006; Davidson et al., 2009; Karlsson and Frank, 2009).”
BackgroundSakairi, T., Kawabata, M., Ríos, A., Sakai, Y., & Isomura, Y. (2025) · Journal of Neuroscience · doi:10.1523/jneurosci.0080-25.2025 · Cited by 5
Ripple contributions to human memory: making the spiking content count
Reithler, J., Sundby, K. K., & Zaghloul, K. A. (2025) · Nature reviews. Neuroscience · doi:10.1038/s41583-025-00971-w · Cited by 4
“Moreover, temporally extended or increasingly rich experiences could be represented by multiple concatenated subsequences 93,139,165 and spiking sequences may also be used to selectively activate specific dendritic segments, shifting the locus of computation in human neurons to the dendrite 166,167…”
Brain Rhythms Provide a Framework for Neural Syntax
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0006 · Cited by 3
Coherent noise enables probabilistic sequence replay in spiking neuronal networks
Bouhadjar, Y., Wouters, D. J., Diesmann, M., & Tetzlaff, T. (2023) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010989 · Cited by 6
A new type of pyramidal neuron in the hippocampus promotes sequence replay
Yang, Y., Li, Y., & Sun, X. (2024) · Nonlinear Dynamics · doi:10.1007/s11071-024-10216-7 · Cited by 4
Hippocampal Place Cell Sequences Are Impaired in a Rat Model of Fragile X Syndrome
Donahue, M. M., Robson, E., & Colgin, L. L. (2025) · Journal of Neuroscience · doi:10.1523/jneurosci.1978-24.2025 · Cited by 7
“We quanti fi ed replay fi delity, duration, and temporal compression of each replay event using protocols similar to previously published procedures (Davidson et al., 2009; Karlsson and Frank, 2009; Hwaun and Colgin, 2019).”
InfluentialTemudo, A., Dolfen, N., King, B. R., & Albouy, G. (2025) · PLoS Biology · doi:10.1371/journal.pbio.3003267 · Cited by 6
“…suggesting that the hippocampus processes temporal order information during sequence learning irrespective of the nature of the items (e.g., letters, odors, objects and movements; [15,16,18,27] and the type of memory (i.e., motor versus non-motor: [15,16]; spatial versus non-spatial: [28,29]).”
Episodic memory in non-humans: an approach to understand an evolutionary function of consciousness
Crystal, J. D. (2025) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2024.0304 · Cited by 4
Mahoney, J. M., Titiz, A. S., Hernan, A. E., & Scott, R. C. (2016) · PLoS ONE · doi:10.1371/journal.pone.0147708 · Cited by 4
Neural and Spinal Modules in Implementation of a Simple Ballistic Movement
Hemami, H., & Dariush, B. (2016) · Journal of Software Engineering and Applications · doi:10.4236/jsea.2016.97023 · Cited by 4
The Role of Sleep in Memory Consolidation: Active or Permissive?
Schönauer, M., & Jan Born, A. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-809324-5.21034-1 · Cited by 4
Neuromorphic Neural Interfaces
Broccard, F. D., Joshi, S., Wang, J., & Cauwenberghs, G. (2022) · Handbook of Neuroengineering · doi:10.1007/978-981-15-2848-4_41-1 · Cited by 4
Crystal, J. D. (2022) · Cambridge University Press eBooks · doi:10.1017/9781108768450.021 · Cited by 5
The expanded circuitry of hippocampal ripples and replay
He, H., Guan, H., & McHugh, T. J. (2022) · Neuroscience Research · doi:10.1016/j.neures.2022.12.010 · Cited by 4
Clearwater, J. M., & Bilkey, D. K. (2011) · Hippocampus · doi:10.1002/hipo.20911 · Cited by 5
“…trajectories during extended SPW-R events are not predictive of upcoming path and that reverse replay events do not preferentially reflect the path just taken by the animal (Davidson et al., 2009) are also consistent with an interpretation that is not directly linked to spatial trajectories.”
BackgroundJeffery, K. J. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-809324-5.21077-8 · Cited by 9
Behavioral status modulates CA2 influence on hippocampal network dynamics
He, H., Wang, Y., & McHugh, T. J. (2023) · Hippocampus · doi:10.1002/hipo.23498 · Cited by 4
“A replay score that represents the estimated likelihood of an experienced trajectory by using a linear fitting algorithm was calculated as previously described (Davidson et al., 2009).”
MethodDefining the synaptic mechanisms that tune CA3-CA1 reactivation during sharp-wave ripplesPreprint
Malerba, P., Jones, M. W., & Bazhenov, M. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/164699 · Cited by 4
“In our model, SWRs occur stochastically, with long stochastic pauses in between packets of events, consistent with in vivo findings (Davidson et al. 2009).”
BackgroundResultPrenatal alcohol exposure disrupts hippocampal sharp-wave ripple-associated spike dynamicsPreprint
Harvey, R. E., Berkowitz, L. E., Savage, D. D., & Clark, B. J. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.06.29.450435 · Cited by 4
Mental navigation and telekinesis with a hippocampal map-based brain-machine interfacePreprint
Lai, C., Tanaka, S., Harris, T. D., & Lee, A. K. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.04.07.536077 · Cited by 4
“…spatial representations suggestive of the planning of specific paths within a cognitive map (Johnson and Redish, 2007; Diba and Buzsáki, 2007; Davidson et al., 2009; Karlsson and Frank, 2009; Pfeiffer and Foster, 2013; Wikenheiser and Redish, 2015; Mou et al., 2022; Widloski and Foster,…”
BackgroundInfluentialAsabuki, T., & Clopath, C. (2024) · eLife · doi:10.7554/elife.95243.1 · Cited by 4
Dynamical Modulation of Hippocampal Replay Sequences through Firing Rate AdaptationPreprint
Ji, Z., Chu, T., Dong, X., Yu, C., Bush, D., Burgess, N., & Wu, S. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.09.13.612895 · Cited by 4
“This decoder reliably estimated the animal’s position (with a median error of 9.0 cm, and 95% CI of 8.2 − 9.8 cm), comparable to results from prior studies [Davidson et al., 2009, Farooq and Dragoi, 2019].”
ResultInfluentialConserved neural population geometry supports behavioral generalizationPreprint
Solla, S. A., Disterhoft, J. F., & Wirtshafter, H. S. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.10.24.620127 · Cited by 4
Dynamical modulation of hippocampal replay through firing rate adaptation
Ji, Z., Chu, T., Dong, X., Yu, C., Bush, D., Burgess, N., & Wu, S. (2026) · Nature Communications · doi:10.1038/s41467-025-68042-3 · Cited by 12
“We found that the decoded position closely tracks the animal ’ s actual position ( fi vefold cross-validation; with the distance difference between the actual and decoded location having a median of 9.0 cm, and 95% CI of 8.2 − 9.8 cm), which is comparable to previous studies 35,82 .”
InfluentialExploring Ripple Waves in the Human Brain
Takagi, S. (2021) · Clinical EEG and Neuroscience · doi:10.1177/15500594211034371 · Cited by 3
“48,49 Consistent with these works in rodents, SPW-Rs in humans are strongly suggested to play an important role in the initiation of self-generated recall events with anticipation.”
BackgroundFormation of cognitive maps in large-scale environments by sensorimotor integration
Zhao, D., & Si, B. (2025) · Cognitive Neurodynamics · doi:10.1007/s11571-024-10200-2 · Cited by 3
“Place cells exhibit multiple place fields in a large-scale environment (Fenton et al. 2008; Kjelstrup et al. 2008; Davidson et al. 2009; Rich et al. 2014).”
Palmer, J., Keane, A., & Gong, P. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005669 · Cited by 3
Mushtaq, M., Haq, R. U., Anwar, M. W., Marshall, L., Bazhenov, M., Zia, K., Alam, H., Hertel, L., Awan, A. A., & Martinetz, T. (2021) · Bioengineered · doi:10.1080/21655979.2021.1936894 · Cited by 3
“Previously stored information reactivation is strongly observed during SPWRs in immobile state, slow-wave sleep [10,11] and rarely during searching [12,13].”
BackgroundSynthetic Data Resource and Benchmarks for Time Cell Analysis and Detection Algorithms
Ananthamurthy, K. G., & Bhalla, U. S. (2023) · eNeuro · doi:10.1523/eneuro.0007-22.2023 · Cited by 3
“Such correlates include but are not limited to measurements of spatial navigation (O’Keefe and Dostrovsky, 1971; O’Keefe and Nadel, 1978; Wilson and McNaughton, 1993) and decision-making (Foster and Wilson, 2006; Csicsvari et al., 2007; Diba and Buzsáki, 2007; Davidson et al., 2009; Karlsson and Frank, 2009; Gupta et…”
BackgroundAsabuki, T., & Claudia Clopath, A. (2025) · eLife · doi:10.7554/elife.95243.3 · Cited by 3
Stochastic characterization of navigation strategies in an automated variant of the Barnes maze
Lee, J.-Y., Jung, D., & Royer, S. (2024) · eLife · doi:10.7554/elife.88648.4 · Cited by 3
Learning-dependent gating of hippocampal inputs by frontal interneurons
Zhang, C.-L., Sontag, L., Gómez-Ocádiz, R., & Schmidt‐Hieber, C. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2403325121 · Cited by 3
Cellular Mechanisms of Thalamocortical Oscillations in the Sleeping Brain
Timofeev, I., Bonjean, M., & Bazhenov, M. (2020) · Springer eBooks · doi:10.1007/978-1-0716-0653-7_5 · Cited by 4
Unsupervised Methods for Detection of Neural States: Case Study of Hippocampal-Amygdala Interactions
Cocina, F., Vitalis, A., & Caflisch, A. (2021) · eNeuro · doi:10.1523/eneuro.0484-20.2021 · Cited by 2
“Clearly, our analysis is best-suited to identify mesoscopic interactions that are related to the generation of sustained rhythms, of sequences of burst events and, generally, of large irregular activity (Davidson et al., 2009; Palmigiano et al., 2017; van Ede et al., 2018; Fernández-Ruiz et al., 2019; Zich et al., 202…”
BackgroundReinforcement Learning and Hippocampal Dynamics
Johnson, A. C., & Venditto, S. J. C. (2014) · Springer series in computational neuroscience · doi:10.1007/978-1-4939-1969-7_14 · Cited by 3
Large-Scale Tetrode Recording in the Rodent Hippocampus
Mou, X., & Ji, D. (2017) · Neuromethods · doi:10.1007/978-1-4939-7549-5_5 · Cited by 3
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0001 · Cited by 4
Memory Consolidation, Replay, and Cortico-Hippocampal Interactions
Holleman, E., & Battaglia, F. P. (2014) · Springer series in computational neuroscience · doi:10.1007/978-1-4939-1969-7_10 · Cited by 3
Re-encoding of associations by recurrent plasticity increases memory capacity
Medina, D., & Leibold, C. (2014) · Frontiers in Synaptic Neuroscience · doi:10.3389/fnsyn.2014.00013 · Cited by 3
“Examples for such intrinsic activities are the recurring sequences of neuronal activity patterns in the hippocampus (Wilson and McNaughton, 1994; Nadasdy et al., 1999; Lee and Wilson, 2002; Davidson et al., 2009); see Buhry et al. (2011); Wikenheiser and Redish (2012) for review.”
BackgroundAwake hippocampal-prefrontal replay mediates spatial learning and decision makingPreprint
Shin, J. D., Tang, W., & Jadhav, S. P. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/632042 · Cited by 3
“…spatial trajectories that span parts of the entire environment in either forward or reverse order (Ambrose et al., 2016; Csicsvari et al., 2007; Davidson et al., 2009; Diba and Buzsáki, 2007; Farooq and Dragoi, 2019; Foster and Wilson, 2006; Gupta et al., 2010; Ólafsdóttir et al., 2017;…”
BackgroundImpairments in Hippocampal Place Cell Sequences during Errors in Spatial MemoryPreprint
Zheng, C., Hwaun, E., & Colgin, L. L. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.04.20.051755 · Cited by 3
Fragmented Spatial Maps from Surprisal: State Abstraction and Efficient PlanningPreprint
Klukas, M., Sharma, S., Du, Y., Lozano‐Pérez, T., Kaelbling, L. P., & Fiete, I. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.10.29.466499 · Cited by 2
Distinct replay signatures for prospective decision-making and memory preservationPreprint
Wimmer, G. E., Liu, Y., McNamee, D., & Dolan, R. J. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.11.08.467745 · Cited by 3
Awake Hippocampal-Prefrontal Replay Mediates Spatial Learning and Decision MakingPreprint
Shin, J. D., Tang, W., & Jadhav, S. P. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3385138 · Cited by 4
Metadata
- Authors
- Davidson, T. J., Kloosterman, F., & Wilson, M. A.
- Affiliations
- Massachusetts Institute of Technology (US)
- Corresponding author
- Kloosterman, Fabian
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2009-08
- Volume
- 63
- Issue
- 4
- Pages
- 497-507
- ISSN
- 0896-6273 (ISSN-L)
- PMC
- PMC4364032
- OpenAlex
- W2079161053
- Cited by
- 806
- References
- 53
- Citations by year
- 2026: 41 · 2025: 54 · 2024: 68 · 2023: 57 · 2022: 56 · 2021: 65 · 2020: 49 · 2019: 72 · 2018: 42 · 2017: 41 · 2016: 49 · 2015: 42 · 2014: 57 · 2013: 40 · 2012: 26
- FWCI
- 11.45
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 1477 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Neuron (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Lirias (KU Leuven) (submittedVersion)
- Funders
- National Institutes of Health (MH061976)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Developmental Neuroscience › Neurogenesis and neuroplasticity mechanisms
- Keywords
- hippocampal replay, place cells, spatial memory, neural decoding, memory storage
- MeSH terms
- Animals, Exploratory Behavior, Hippocampus, Learning, Male, Spatial Behavior, Time Factors, Rats, Long-Evans, Rats
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