The DOI matches its Crossref record; 64 of the 65 references it cites were found in a registry or an index.
Replay and Time Compression of Recurring Spike Sequences in the Hippocampus
Open accessAbstract
Information in neuronal networks may be represented by the spatiotemporal patterns of spikes. Here we examined the temporal coordination of pyramidal cell spikes in the rat hippocampus during slow-wave sleep. In addition, rats were trained to run in a defined position in space (running wheel) to activate a selected group of pyramidal cells. A template-matching method and a joint probability map method were used for sequence search. Repeating spike sequences in excess of chance occurrence were examined by comparing the number of repeating sequences in the original spike trains and in surrogate trains after Monte Carlo shuffling of the spikes. Four different shuffling procedures were used to control for the population dynamics of hippocampal neurons. Repeating spike sequences in the recorded cell assemblies were present in both the awake and sleeping animal in excess of what might be predicted by random variations. Spike sequences observed during wheel running were “replayed” at a faster timescale during single sharp-wave bursts of slow-wave sleep. We hypothesize that the endogenously expressed spike sequences during sleep reflect reactivation of the circuitry modified by previous experience. Reactivation of acquired sequences may serve to consolidate information.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“In fact, entire spike trains observed during a task performed during prior waking reemerged in the same temporal order during succeeding sleep, with this “replay” running at a faster speed, i.e., in a time-compressed form (715, 716, 843).”
From About Sleep's Role in Memory (2013) · cites this paper as [843]
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
“1) during SWS, firing patterns observed during waking are replayed at a much faster (10 -20 times) rate, suggesting a time-compressed form of memory reactivation (160, 551, 606, 715, 843, 1090);”
From About Sleep's Role in Memory (2013) · cites this paper as [843]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
(1978) · UA Campus Repository (The University of Arizona) · Cited by 8,010
McClelland, J. L., McNaughton, B. L., & O'Reilly, R. C. (1995) · Psychological Review · doi:10.1037/0033-295x.102.3.419 · Cited by 5,256
The Integrative Action of the Nervous System.
Sherrington, C. (1907) · The Journal of Nervous and Mental Disease · doi:10.1097/00005053-190734120-00021 · Cited by 4,136
Reactivation of hippocampal ensemble memories during sleep
Wilson, M. A., & McNaughton, B. L. (1994) · Science · doi:10.1126/science.8036517 · Cited by 3,118 · cited 11×
“Rapid reinstatement of the spatiotemporal patterns of pyramidal cell activity in the CA3–CA1 regions and deep layers of the entorhinal cortex (Chrobak and Buzsaki, 1994, 1996) is hypothesized to transfer the stored representations in the hippocampus to neocortical networks (Buzsáki, 1989; Wilson and McNaughton, 1994;…”
BackgroundMethodResultInfluentialPhase relationship between hippocampal place units and the EEG theta rhythm
O'Keefe, J. M., & Recce, M. L. (1993) · Hippocampus · doi:10.1002/hipo.450030307 · Cited by 2,643
Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex
Gray, C. M., & Singer, W. (1989) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.86.5.1698 · Cited by 2,463 · cited 2×
“, 1996; Marder and Calabrese, 1996) and vertebrate (Strehler and Lestienne, 1986; Ts’o et al., 1986; Vaadia and Abeles, 1987; Eckhorn et al., 1988; Gray and Singer, 1989; Frostig et al., 1990b; Aertsen et al., 1991; Abeles et al., 1993; Riehle et al., 1997) brains.”
BackgroundCoherent oscillations: A mechanism of feature linking in the visual cortex?
Eckhorn, R., Bauer, R., Jordan, W., Brosch, M., Kruse, W., Munk, M., & Reitboeck, H. J. (1988) · Biological Cybernetics · doi:10.1007/bf00202899 · Cited by 2,329
Llinás, R. R. (1988) · Science · doi:10.1126/science.3059497 · Cited by 2,285 · cited 1×
“…on individual pyramidal neurons and their network interactions suggest that pyramidal cells are equipped with intrinsic oscillatory properties (Llinás, 1988; Leung and Yim, 1991; Kamondi et al., 1998) and are embedded in an oscillatory network of interneurons (Buzsáki and Chrobak, 1995;…”
BackgroundShadlen, M. N., & Newsome, W. T. (1998) · The Journal of Neuroscience · doi:10.1523/jneurosci.18-10-03870.1998 · Cited by 2,178 · cited 1×
“If the dynamics of cortical neurons could be described by a Poisson process (Bair and Koch, 1996; Shadlen and Newsome, 1998), then within-spike-train randomization of spike occurrences would be appropriate because this procedure does not alter the average firing rate of the individual neurons.”
BackgroundGeorgopoulos, A. P., Kalaska, J. F., Caminiti, R., & Massey, J. (1982) · Journal of Neuroscience · doi:10.1523/jneurosci.02-11-01527.1982 · Cited by 2,133 · cited 1×
“Several explanations have been proposed on theoretical grounds, including frequency coding (Sherrington, 1906; Eccles, 1957; Barlow, 1972; Georgopoulos et al., 1982), temporal coincidence coding (von der Malsburg and Bienenstock, 1986; Singer, 1993), temporal delay of spikes (O’Keefe and Recce,…”
Background
Research works printed but not linked: 5
- Nadasdy, 1996, Repeating spatio-temporal patterns of neuronal activity in the hippocampus during sleep., Soc Neurosci Abstr, 22, 445.11
- Nadasdy, 1997, Relationship between recurring spatio-temporal spike patterns and local field oscillations in the hippocampus., Soc Neurosci Abstr, 23, 188.5
- Nadasdy, 1998, Persistence, compression and behavioral induction of spike sequences in the hippocampus., Soc Neurosci Abstr, 24, 362.18
- Nádasdy Z Csicsvari J Penttonen M Hetke J Wise K Buzsáki G (1998) Extracellular recording and analysis of neuronal activity: from single cells to ensembles. in Neuronal ensembles: strategies for recording and encoding, eds Eichenbaum H Davis J (Wiley, New York), pp 17–55.
- Quirk, 1998, Temporal changes in the firing properties of CA1 pyramidal cells in the freely behaving rat., Soc Neurosci Abstr, 24, 758.13
Cited by
Sorted by citations
Items 801–900 of 931
Prior-knowledge Effects on Associative Memory Processing
Liu, Z. X. (2015) · TSpace (University of Toronto)
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0011
Self-citationThe Next Phase for Tracking and Predicting the Navigational Behavior Using Machine Learning
TAKAHASHI, S. Y., Hoshino, S., & Ide, K. (2019) · IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) · doi:10.1109/percomw.2019.8730808
“To address the issue, template matching have been utilized [16].”
MethodRecurrent infomax generates cell assemblies, avalanches, and simple cell-like selectivityPreprint
Tanaka, T., Kaneko, T., & Aoyagi, T. (2008) · arXiv (Cornell University) · doi:10.48550/arxiv.0801.1885
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0012
Self-citationBuzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0005
Self-citationBuzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0013
Self-citationEnhancing Brain Performance by Externalizing Thought
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0009
Self-citationInternally Organized Activity During Offline Brain States
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0008
Self-citationBuzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0004
Self-citationSingle-Neuron and Network Dynamics in the Neocortical-Entorhinal-Hippocampal Circuit
McFarland, J. M. (2011) · doi:10.7301/z0dr2sq2
Molyakov, A. (2019) · Biomedical Journal of Scientific & Technical Research · doi:10.26717/bjstr.2019.21.003657
Neural correlates of navigation in large-scale space
Tanni, S. (2020) · UCL Discovery (University College London)
Hippocampal Representations of Targeted Memory Reactivation and Reactivated Temporal Sequences
Alm, K. H. (2017) · TUScholarShare (Temple University)
Sleep’s role in the reprocessing and restructuring of memory
Koopman, A. C. M. (2020) · ORCA Online Research @Cardiff (Cardiff University)
Niittymäki, E. (2021) · Työväentutkimus Vuosikirja
Bhasin, G. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.08.19.456964
Advanced Age Has Dissociable Effects on Hippocampal CA1 and CA3 RipplesPreprint
DiCola, N. M., Lacy, A. L., Bishr, O. J., Kimsey, K. M., Whitney, J. L., Lovett, S. D., Burke, S. N., & Maurer, A. P. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.08.27.457373
“…which occur during slow-wave sleep (Wilson and McNaughton, 1994; Chrobak and Buzsaki, 1996; Skaggs and McNaughton, 1996; Kudrimoti et al., 1999; Nadasdy et al., 1999; Sutherland and McNaughton, 2000; Lee and Wilson, 2002; Buzsáki et al., 2003; Born et al., 2006; Grosmark et al., 2012; Cox et…”
BackgroundThe Effects of Repetition and Sequence Length on Hippocampal Memory Trace Reactivation
Sutherland, G. R. (2008) · UA Campus Repository (The University of Arizona)
Schutter, E. D. (2006) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.1031973.371880
Faculty Opinions recommendation of Awake replay of remote experiences in the hippocampus.
Moser, E. I., & Derdikman, D. (2009) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.1164561.627084
Hallett, M. (2004) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.1022379.255629
Wolfer, D. P. (2013) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.718023375.793481793
Stickgold, R. (2009) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.1160548.620913
Knierim, J. J. (2010) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.1165798.856081
Neural Networks with Nonlinear Couplings
Jahnke, S. (2015) · eDiss (Georg-August-Universität Göttingen) · doi:10.53846/goediss-5056
Cerebral Functional Segregation and Integration during Human Sleep
Maquet, P. (2004) · CRC Press eBooks · doi:10.1201/9780203496732.ch13
(2001) · Elsevier eBooks · doi:10.1016/b978-0-12-311624-6.50026-8
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0014
Self-citationReactivation of Neural Ensembles During Memory Retrieval
Tayler, K. K. (2014) · doi:10.18130/v3zj75
Faculty Opinions recommendation of Fast Sequences of Non-spatial State Representations in Humans.
Kiebel, S. J. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.726435693.793559771
Statistical Evaluation of Spatio-temporal Spike Patterns
Grün, S., Quaglio, P., Stella, A., & Torre, E. (2022) · Encyclopedia of Computational Neuroscience · doi:10.1007/978-1-0716-1006-0_100702
Disk-Drive-Like Operations in the HippocampusPreprint
Nicola, W., Dupret, D., & Clopath, C. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.05.511000
Spatiotemporal Spike Pattern Detection with Second-order Memristive Synapses
Wu, Y., Yoo, S., Meng, F.-H., & Lu, W. D. (2022) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas48785.2022.9937414
“Memristor-based In biology, repeated occurrence patterns has been detected across cortical regions and is believed to encode critical information for downstream processing[7-9].”
BackgroundSynchronous ensembles of hippocampal CA1 pyramidal neurons during novel exploration
Chen, E.-L., Chen, T., Schreiter, E. R., & Lin, B. (2025) · eLife · doi:10.7554/elife.96718.6
Biophysical models of synaptic interactions
Alain Destexhe, A., & B, T. J. S. A. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198864998.003.0005
Thalamocortical mechanisms for spike-and-wave epileptic seizures
Alain Destexhe, A., & B, T. J. S. A. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198864998.003.0008
(2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198864998.002.0009
Spindle oscillations in thalamic circuits
Alain Destexhe, A., & B, T. J. S. A. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198864998.003.0006
Ionic bases of the membrane potential
Alain Destexhe, A., & B, T. J. S. A. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198864998.005.0001
A physiological role for sleep oscillations
Alain Destexhe, A., & B, T. J. S. A. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198864998.003.0009
Biophysical models of the membrane potential and ionic currents
Alain Destexhe, A., & B, T. J. S. A. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198864998.003.0002
Spindle oscillations in the thalamocortical system
Alain Destexhe, A., & B, T. J. S. A. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198864998.003.0007
Data available on the Internet
Alain Destexhe, A., & B, T. J. S. A. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198864998.005.0003
(2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198864998.002.0006
Electrophysiological properties of thalamic reticular neurons
Alain Destexhe, A., & B, T. J. S. A. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198864998.003.0004
(2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198864998.002.0005
(2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198864998.002.0004
Alain Destexhe, A., & B, T. J. S. A. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198864998.003.0001
(2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198864998.002.0003
(2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198864998.002.0007
Electrophysiological properties of thalamic relay neurons
Alain Destexhe, A., & B, T. J. S. A. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198864998.003.0003
Optimized algorithms for simulating synaptic currents
Alain Destexhe, A., & B, T. J. S. A. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780198864998.005.0002
Altered patterning of neural activity in a tauopathy mouse modelPreprint
Hoffman, C., Cheng, J., Morales, R., Ji, D., & Dabaghian, Y. A. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.03.23.586417
“Indeed, a replay may last between a couple of dozens to a couple of hundreds of milliseconds, which is comparable to the characteristic interval between spikes triggered by the animal’s physical passing through place fields [60, 64–68].”
BackgroundLearning Sequence Attractors in Recurrent Networks with Hidden NeuronsPreprint
Lu, Y., & Wu, S. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4786003
Marchesi, P., Bos, J. J., Vinck, M. A., & Pennartz, C. M. A. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.04.18.590059
Chen, E.-L., Chen, T., Schreiter, E. R., & Lin, B. (2024) · eLife · doi:10.7554/elife.96718.1
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.002.0006
Self-citationBuzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.002.0003
Self-citationBuzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.002.0004
Self-citationJauch, J., Becker, M., Tetzlaff, C., & Fauth, M. J. (2024) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1012218
Associations: more than connections and statistics
Chartier, T. F. (2024) · L’Année psychologique · doi:10.3917/anpsy1.242.0199
Extended Poisson Gaussian-Process Latent Variable Model for Unsupervised Neural Decoding
Luo, D., Giri, B. K., Diba, K., & Kemere, C. T. (2024) · Neural Computation · doi:10.1162/neco_a_01685
“In this cognitive map framework, the ensemble activity thus represents unobserved conceptual places that evolve over time on a latent manifold.”
BackgroundAnde, S., Avasarala, S., Swain, S., Karunarathne, A., Giri, L., & Jana, S. (2024) · Journal of Neural Engineering · doi:10.1088/1741-2552/ad6cf4
“However, this cost escalation was less than an order of magnitude and should be tolerable, suggesting its potential utility for online estimation of information content in spike trains, particularly in scenarios where spikes occur at intervals of a few milliseconds [62].”
Bredenberg, C., Normandin, F., Richards, B. A., & Lajoie, G. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.09.27.615483
“In total, our model of the functional effect of psychedelics on pyramidal neurons could provide a explanation for the perceptual psychedelic experience in terms of learning mechanisms for consolidation during sleep [21], and cortical ‘replay’ phenomena [22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32].”
Kim, M., Kim, S.-P., & Sohn, J.-W. (2024) · Molecular Brain · doi:10.1186/s13041-024-01161-y
“Precise spike sorting is crucial for understanding the firing patterns of neurons in response to endogenous and exogenous stimuli [2, 3].”
Emergence of novel-path sequences during a maze task in hippocampal CA3 spiking neural network model
Takada, K., & Tateno, K. (2024) · Nonlinear Theory and Its Applications IEICE · doi:10.1587/nolta.16.64
Theories of Hippocampal Function
McKenzie, S., Gobbo, F., & Morris, R. (2025) · Oxford University Press eBooks · doi:10.1093/med/9780190065324.003.0014
Chen, E.-L., Chen, T., Schreiter, E. R., & Lin, B. (2025) · eLife · doi:10.7554/elife.96718.2
Reciprocal interactions between CA1 pyramidal and axo-axonic cells control sharp wave-ripple eventsPreprint
English, D. F., Gilbert, E. T., Klaver, L. M. F., Arndt, K. C., Kim, J., Jia, X., & McKenzie, S. (2025) · Research Square · doi:10.21203/rs.3.rs-5844238/v1
Accelerated signal propagation speed in human neocortical dendritesPreprint
Oláh, G., Lákovics, R., Shapira, S., Leibner, Y., Szűcs, A. L., Csajbók, É., Barzó, P., Molnár, G., Segev, I., & Tamás, G. (2025) · eLife · doi:10.7554/elife.93781.3 · Cited by 1
Chen, E.-L., Chen, T., Schreiter, E. R., & Lin, B. (2025) · eLife · doi:10.7554/elife.96718.3
It’s time to examine neural coding from the message’s point of view
Graham, D. J. (2025) · The Transmitter · doi:10.53053/cwmm5126
Optogenetic disruption of neural dynamics in the prefrontal cortex impaired spatial learningPreprint
Negrón-Oyarzo, I., Dib, T., Chacana-Véliz, L., Barria, D., Morales-Weil, K., Fuenzalida, M., & Espinosa, N. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.04.07.647582
“Both prefrontal cortex neuronal spike timestamps and start times of behavioral events were shuffled by randomized exchange of the original inter-event intervals (Nádasdy et al., 1999) and the cross-correlation procedure was performed on the pseudo-random sequence.”
Hippocampal reactivation and replay: Findings and insights from rodent studies
Kim, B., & Diba, K. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-15754-7.00091-2 · Cited by 1
Sleep, Neurocognitive Function, Learning, and Memory
Baena, D., Alyssa, P., Hordijk, J., Ray, L. B., & Fogel, S. M. (2025) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780197602751.013.2
Bredenberg, C., Normandin, F., Richards, B. A., & Lajoie, G. (2025) · eLife · doi:10.7554/elife.105968.1
Challenges in replay detection by TDLM in post-encoding resting state
Kern, S., Nagel, J., Wittkuhn, L., Gais, S., Dolan, R. J., & Feld, G. B. (2026) · eLife · doi:10.7554/elife.108023.3
Synchronous Ensembles of Hippocampal CA1 Pyramidal Neurons During Novel ExplorationPreprint
Chen, E.-L., Chen, T., Schreiter, E. R., & Lin, B. (2025) · eLife · doi:10.7554/elife.96718.4
Synchronous Ensembles of Hippocampal CA1 Pyramidal Neurons During Novel ExplorationPreprint
Chen, E.-L., Chen, T., Schreiter, E. R., & Lin, B. (2025) · eLife · doi:10.7554/elife.96718.5
Efficient memorization of dynamic stimuli with future interactionsPreprint
Aparicio‐Rodríguez, G., Ruiz-Navalon, D., Manubens, P., Sánchez‐Jiménez, A., Calvo, C., & Villacorta-Atienza, J. A. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.09.28.678599
“There are different mechanisms to construct long-term memories 44 , as consolidation of the working memory through similar experiences 45 and through replay 46,47 .”
A Bio-realistic Synthetic Hippocampus for Robotic Cognition
Vallverdú, J., Feinstein, X., Robertson, P., Kipelkin, I., & Talanov, M. O. (2025) · BioNanoScience · doi:10.1007/s12668-025-02229-2
“Replay density is highest during SWS, where hippocampal SWRs are phase-locked to cortical slow waves and spindles [21, 41].”
Segawa, Y., Minoshima, W., Masui, K., & Hosokawa, C. (2025) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2025.153049
Sleep-modulated disinhibition enables replay for memory consolidation, accelerated by ripplesPreprint
Dutta, S. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.09.693276
“Intra-regional inter-assembly delays within MEC, CA3, and CR are assumed to be 20 ms to enable sequential activations during offline replays [103, 189, 250, 251].”
THE SMALL IRREGULAR ACTIVITY STATE IN THE RAT HIPPOCAMPUS
Jarosiewicz, B. (2004) · D-Scholarship@Pitt (University of Pittsburgh)
Finding Repeating Synaptic Inputs in a Single Neocortical Neuron
Aaron, G. B. (2009) · Springer eBooks · doi:10.1007/978-1-4419-0389-1_3
Intersection of transient cell states with stable cell types in hippocampusPreprint
Olmstead, J. A., King, L. E., & Bloodgood, B. L. (2025) · eLife · doi:10.7554/elife.109663
Intersection of transient cell states with stable cell types in hippocampusPreprint
Olmstead, J. A., King, L. E., & Bloodgood, B. L. (2025) · eLife · doi:10.7554/elife.109663.1 · Cited by 1
A unifying account of replay as context-driven memory reactivationPreprint
Zhou, Z., Kahana, M. J., & Schapiro, A. C. (2025) · eLife · doi:10.7554/elife.99931.2
Bredenberg, C., Normandin, F., Richards, B., & Lajoie, G. (2026) · eLife · doi:10.7554/elife.105968.2
A microcircuit model for initiation and reward-dependent termination of hippocampal replayPreprint
Musset, H., & Fukai, T. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.18.700234 · Cited by 1
“…enhances memory performance, respectively (Girardeau et Nested within SWRs, replay describes trajectory through space by sequentially reactivating place cells and provides a framework for synaptic plasticity (N´adasdy et al. 1999; Carr et al. 2011; Sadowski et al. 2016; ´Olafsd´ottir et al. 2018).”
La somniloquie : un modèle pour l'étude de la consolidation mnésique verbale pendant le sommeil
Uguccioni, G. (2015) · theses.fr (ABES) · doi:10.70675/e340385dzc46bz4e59z9c16z216cb0dd5810
Mécanismes responsables de l'activation corticale pendant le sommeil paradoxal
Renouard, L. (2011) · theses.fr (ABES) · doi:10.70675/fb03b5cez134bz4527zb76cz110ad804221c
Metadata
- Authors
- Nádasdy, Z., Hirase, H., Czurkó, A., Csicsvari, J., & Buzsáki, G.
- Affiliations
- Rutgers, The State University of New Jersey (US)
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 1999-11-01
- Volume
- 19
- Issue
- 21
- Pages
- 9497-9507
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC6782894
- OpenAlex
- W1580901834
- Cited by
- 932
- References
- 65
- Citations by year
- 2026: 25 · 2025: 46 · 2024: 46 · 2023: 44 · 2022: 36 · 2021: 34 · 2020: 43 · 2019: 53 · 2018: 36 · 2017: 46 · 2016: 38 · 2015: 40 · 2014: 51 · 2013: 39 · 2012: 29
- FWCI
- 7.04
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health
- National Institute of Mental Health (R01MH054671, MH54671)
- National Institute of Neurological Disorders and Stroke (R01NS034994, NS-34994)
- 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
- replay, slow-wave sleep, pyramidal neurons, template matching, memory consolidation, spatial navigation
- MeSH terms
- Animals, Brain Mapping, Evoked Potentials, Hippocampus, Models, Neurological, Monte Carlo Method, Motor Activity, Nerve Net, Neurons, Probability, Sleep, Time Factors, Wakefulness, Rats, Sprague-Dawley, Pyramidal Cells, Rats
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
