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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.
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“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]
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“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]
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Background
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A large majority of awake hippocampal sharp-wave ripples feature spatial trajectories with momentum
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Encoding New Episodes and Making Them Stick
SUZUKI, W. A. (2006) · Neuron · doi:10.1016/j.neuron.2006.03.029 · Cited by 34
“The standard memory replay hypothesis states that patterns of brain activity that occurred during waking states are replayed during sleep and that this replay may be critical for the process of memory consolidation (Louie and Wilson, 2001; Nadasdy et al., 1999; Wilson and Mcnaughton, 1994).”
BackgroundThe time course and organization of hippocampal replay
Mallory, C. S., Widloski, J., & Foster, D. J. (2025) · Science · doi:10.1126/science.ads4760 · Cited by 42
Odor cueing during slow-wave sleep benefits memory independently of low cholinergic tone
Klinzing, J. G., Kugler, S., Soekadar, S. R., Rasch, B., Jan Born, A., & Diekelmann, S. (2017) · Psychopharmacology · doi:10.1007/s00213-017-4768-5 · Cited by 33
“For declarative memories, a central component of consolidation is the repeated reactivation of learning-associated neuronal activity patterns originating in the hippocampus (Pavlides and Winson 1989; Wilson and McNaughton 1994; Nádasdy et al. 1999).”
Großberger, L., Battaglia, F. P., & Vinck, M. A. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006283 · Cited by 33
“Many approaches to this problem are supervised, that is, they take patterns occurring concurrently with a known event, such as the delivery of a stimulus for sensory neurons or the traversal of a running track for hippocampal place fields, as a “template” and then search for repetitions of the same template in spiking…”
BackgroundSubiculum as a Generator of Sharp Wave-Ripples in the Rodent Hippocampus
Imbrosci, B., Nitzan, N., McKenzie, S., Donoso, J. R., Swaminathan, A., Böhm, C., Maier, N., & Schmitz, D. (2020) · Cell Reports · doi:10.1016/j.celrep.2021.109021 · Cited by 37
“The pivotal role of SWRs in the process of memory consolidation is supported by studies showing that SWRs can replay neuronal activity that which contain information about recent active behavior (Kudrimoti et al.,1999; Nádasdy et al., 1999; Lee andWilson, 2002).”
BackgroundBackbone spiking sequence as a basis for preplay, replay, and default states in human cortex
Vaz, A. P., Wittig, J. H., Inati, S. K., & Zaghloul, K. A. (2023) · Nature Communications · doi:10.1038/s41467-023-40440-5 · Cited by 32
“001), while flexible units carry more information in spike timing compared to rigid units (t(5) = 7.”
BackgroundMethodInfluentialÇalışkan, G., Schulz, S., Gruber, D., Behr, J., Heinemann, U., & Gerevich, Z. (2014) · European Journal of Neuroscience · doi:10.1111/ejn.12750 · Cited by 31
Kelemen, E., & Fenton, A. A. (2013) · PLoS Biology · doi:10.1371/journal.pbio.1001607 · Cited by 34
Differential behavioral state-dependence in the burst properties of CA3 and CA1 neurons
Sneider, J. T., Chrobak, J. J., Quirk, M. C., Oler, J. A., & Markus, E. J. (2006) · Neuroscience · doi:10.1016/j.neuroscience.2006.05.052 · Cited by 33
Sequence anticipation and spike-timing-dependent plasticity emerge from a predictive learning rule
Saponati, M., & Vinck, M. A. (2023) · Nature Communications · doi:10.1038/s41467-023-40651-w · Cited by 35
“These fi ndingshavebeen interpretedin termsofalocalreorganization of synaptic weight distributions as a result of repeated activation with an input sequence 7,34,35,37,38 .”
BackgroundTracking human skill learning with a hierarchical Bayesian sequence model
Éltető, N., Németh, D., Janacsek, K., & Dayan, P. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009866 · Cited by 33
“Structures in birds, such as area HVC, that apparently sequence song [55], or the hippocampus of rodents with its rich forms of on-line and off-line activation of neurons in behaviourally-relevant sequences [56, 57], or the temporal pole and posterior orbitofrontal cortex of humans [58], whose activity apparently incr…”
MethodRauske, P. L., Chi, Z., Dave, A. S., & Margoliash, D. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.3112-09.2010 · Cited by 31
“…replay of premotor bursts has been observed in RA (Dave and Margoliash, 2000) and may play similar roles in other systems (Wilson and McNaughton, 1994; Qin et al., 1997; Nadasdy et al., 1999; Hoffman and McNaughton, 2002; Pennartz et al., 2004; Ji and Wilson, 2007; Peyrache et al., 2009).”
BackgroundPignatelli, M., Lebreton, F., Cho, Y. H., & Leinekugel, X. (2012) · Neurobiology of Disease · doi:10.1016/j.nbd.2012.07.015 · Cited by 31
“…patterns, sleep and cognitive function (Pavlides and Winson, 1989; Wilson and McNaughton, 1994; Skaggs and McNaughton, 1996; Kudrimoti et al., 1999; Nadasdy et al., 1999; Peigneux et al., 2004; Foster and Wilson, 2006; Diba and Buzsaki, 2007; Ji and Wilson, 2007; O'Neill et al., 2008; Davidson et…”
BackgroundHashmi, A. G., Nere, A., & Tononi, G. (2013) · Frontiers in Neurology · doi:10.3389/fneur.2013.00148 · Cited by 33
Reyes‐Puerta, V., Yang, J., Siwek, M. E., Kilb, W., Sun, J., & Luhmann, H. J. (2016) · Brain Structure and Function · doi:10.1007/s00429-015-1173-x · Cited by 30
“…methods (Luczak et al. 2007; Sakata and Harris 2009) and were further characterized by identifying temporally precise spike sequences, which have been proposed as a signature for the flow of activity within neural networks (Abeles and Gerstein 1988; Sun et al. 2010; Nadasdy et al. 1999).”
BackgroundMethodInfluentialPreconfigured patterns are the primary driver of offline multi‐neuronal sequence replay
Liu, K., Sibille, J., & Dragoi, G. (2018) · Hippocampus · doi:10.1002/hipo.23034 · Cited by 30
“, 1999; Lee & Wilson, 2002) and were generally implied to represent a replay of a previous similar experience when expressed before a now familiar environment (Kudrimoti et al., 1999; Nadasdy et al., 1999).”
BackgroundLevel of Arousal During the Small Irregular Activity State in the Rat Hippocampal EEG
Jarosiewicz, B., & Skaggs, W. E. (2004) · Journal of Neurophysiology · doi:10.1152/jn.01082.2003 · Cited by 32
“…the patterns of activity during the preceding waking period more than expected by chance, but unlike the reactivation during REM, the reactivation during LIA is highly compressed in time (Nádasdy et al. 1999; Pavlides and Winson 1989; Skaggs and McNaughton 1996; Wilson and McNaughton 1994).”
BackgroundPeyrache, A. (2010) · Frontiers in Systems Neuroscience · doi:10.3389/neuro.06.018.2009 · Cited by 30
A model for complex sequence learning and reproduction in neural populations
Verduzco-Flores, S. O., Bodner, M., & Ermentrout, B. (2011) · Journal of Computational Neuroscience · doi:10.1007/s10827-011-0360-x · Cited by 29
Synchronized excitability in a network enables generation of internal neuronal sequences
Wang, Y., Roth, Z., & Pastalkova, E. (2016) · eLife · doi:10.7554/elife.20697 · Cited by 34
Brain temperature affects quantitative features of hippocampal sharp wave ripples
Petersen, P. C., Vöröslakos, M., & Buzsáki, G. (2022) · Journal of Neurophysiology · doi:10.1152/jn.00047.2022 · Cited by 34
Self-citationHippocampal place cells: The “where” of episodic memory?
Kentros, C. G. (2006) · Hippocampus · doi:10.1002/hipo.20199 · Cited by 32
“This result was later extended (Skaggs and McNaughton, 1996; Kudrimoti et al., 1999; Nadasdy et al., 1999; Lee and Wilson, 2002) to include the key concept of reactivation, that assemblies of cells can fire during slow wave and REM (Louie and Wilson, 2001) sleep in the same temporal order they…”
BackgroundDynamical Constraints on Using Precise Spike Timing to Compute in Recurrent Cortical Networks
Banerjee, A., Seriès, P., & Pouget, A. (2007) · Neural Computation · doi:10.1162/neco.2008.05-06-206 · Cited by 29
“Several researchers have also reported spike patterns at a coarser timescale in the cortex, on the order of 25+ msec (Nadasdy et al., 1999; Hahnloser et al., 2002).”
BackgroundThe generative grammar of the brain: a critique of internally generated representations
Dragoi, G. (2024) · Nature Reviews Neuroscience · doi:10.1038/s41583-023-00763-0 · Cited by 28
“However, debates leading up to 2011 revolved around whether hippocampal activity during the sleep or rest preceding a re-exposure to a familiar context was correlated 31,61 or not 30 with the activity patterns that would be re-expressed during that re-exposure.”
Uncovering representations of sleep-associated hippocampal ensemble spike activity
Chen, Z. S., Grosmark, A., Penagos, H., & Wilson, M. A. (2016) · Scientific Reports · doi:10.1038/srep32193 · Cited by 29
“More importantly, only a small subset of pyramidal neurons are active during individual SPW-ripple events 15 .”
InfluentialMontijn, J. S., Olcese, U., & Pennartz, C. M. A. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.0853-16.2016 · Cited by 24
“PE occurrence is independent of prior events at the timescale of seconds Assembly occurrence in brain regions other than the visual cortex, such as hippocampus, has been associated with replay of past events and other memoryrelated phenomena (Wilson and McNaughton, 1994; Nádasdy et al., 1999; Lee and Wilson, 2002; Gir…”
BackgroundKim, B., Kocsis, B., Hwang, E., Kim, Y., Strecker, R. E., McCarley, R. W., & Choi, J. H. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1615230114 · Cited by 29
“, the discharge probability increases independent of whether a neuron is part of a spatiotemporal spike sequence or not”, as suggested for ripple busts (40, 52).”
BackgroundMalinowski, J. E., Scheel, D., & McCloskey, M. (2021) · Consciousness and Cognition · doi:10.1016/j.concog.2021.103214 · Cited by 27
Neural-Event-Triggered fMRI of large-scale neural networks
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Aussel, A., Buhry, L., Tyvaert, L., & Ranta, R. (2018) · Journal of Computational Neuroscience · doi:10.1007/s10827-018-0704-x · Cited by 30
Altered Network Timing in the CA3-CA1 Circuit of Hippocampal Slices from Aged Mice
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Synaptic gating at axonal branches, and sharp‐wave ripples with replay: a simulation study
Vladimirov, N., Tu, Y., & Traub, R. D. (2013) · European Journal of Neuroscience · doi:10.1111/ejn.12342 · Cited by 26
“The experience-specific reactivation is strongest during SPW-Rs in slow-wave sleep and quiet wakefulness (Kudrimoti et al., 1999; N adasdy et al., 1999), and in the occasional SPW-Rs during exploration (O’Neill et al., 2006; Davidson et al., 2009).”
BackgroundLandi, N., Malins, J. G., Frost, S. J., Magnuson, J. S., Molfese, P. J., Ryherd, K., Rueckl, J. G., Mencl, W. E., & Pugh, K. R. (2018) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2018.01.011 · Cited by 28
“correlated with activity in those same areas during subsequent slow wave sleep (SWS), suggesting a replaying of events to strengthen memories (Ji and Wilson, 2007; Nádasdy et al., 1999; Pavlides and Winson, 1989; Skaggs and McNaughton, 1996; Wilson and McNaughton, 1994).”
BackgroundBayati, M., Valizadeh, A., Abbassian, A., & Cheng, S. (2015) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2015.00069 · Cited by 26
“The propagation of neural spiking activity has been observed in various parts of the brain, including neocortex (Mao et al., 2001; Ikegaya et al., 2004; Pinto et al., 2005) and hippocampus (Miles et al., 1988; Nádasdy et al., 1999; Buhry et al., 2011; Cheng, 2013).”
Oscillation-Induced Signal Transmission and Gating in Neural Circuits
Jahnke, S., Memmesheimer, R.-M., & Timme, M. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003940 · Cited by 26
“realized by local feed-forward structures [13,14,16,60], possible”
Pacing Hippocampal Sharp-Wave Ripples With Weak Electric Stimulation
Jiang, H., Liu, S., Geng, X., Caccavano, A., Conant, K. E., Vicini, S., & Wu, J. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00164 · Cited by 26
“fragments of sequential activation (Wilson and McNaughton, 1994; Nádasdy et al., 1999; Lee and Wilson, 2002; Pfeiffer and Foster, 2013).”
BackgroundDissociating the past from the present in the activity of place cells
de Hoz, L., & Wood, E. R. (2006) · Hippocampus · doi:10.1002/hipo.20207 · Cited by 26
Neural ensemble coding and statistical periodicity: Speculations on the operation of the mind's eye
MILTON, J. G., & Mackey, M. C. (2000) · Journal of Physiology-Paris · doi:10.1016/s0928-4257(00)01102-5 · Cited by 26
“The spike sequences recorded in the awake animal appear to be ‘replayed’ on a faster time scale during sleep which may serve to consolidate information [66, 82, 95].”
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Cell-type-specific silence in thalamocortical circuits precedes hippocampal sharp-wave ripples
Chambers, A. R., Berge, C. N., & Vervaeke, K. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111132 · Cited by 25
Lee, S. A., Holly, K. S., Voziyanov, V., Vanhoof‐Villalba, S. L., Tong, R., Grigsby, H. E., Glasscock, E., Szele, F. G., VLACHOS, I. K., & Murray, T. A. (2016) · PLoS ONE · doi:10.1371/journal.pone.0146533 · Cited by 24
“Other techniques, such as chronically implanted multielectrode arrays [21] and optogenetics [22] enable recording and control, respectively, of large numbers of neurons in deep regions of the brain [23, 24].”
Could electrical coupling contribute to the formation of cell assemblies?
Traub, R. D., Whittington, M. A., Maier, N., Schmitz, D., & Nagy, J. I. (2019) · Reviews in the Neurosciences · doi:10.1515/revneuro-2019-0059 · Cited by 29
“Second is the replay/preplay phenomenon (Wilson and McNaughton, 1994; Skaggs and McNaughton, 1996; Nádasdy et al., 1999; Diba and Buzsáki, 2007; Pastalkova et al., 2008; Girardeau et al., 2009; reviewed by Carr et al., 2011; Figure 10), where there is a relation between firing sequences of…”
BackgroundSleep-mediated regulation of reward circuits: implications in substance use disorders
Guo, R., Vaughan, D. T., Rojo, A. L. A., & Huang, Y. H. (2022) · Neuropsychopharmacology · doi:10.1038/s41386-022-01356-8 · Cited by 25
Sharp‐wave ripple features in macaques depend on behavioral state and cell‐type specific firing
Hussin, A. T., Leonard, T. K., & Hoffman, K. L. (2018) · Hippocampus · doi:10.1002/hipo.23046 · Cited by 26
Learning Beyond Finite Memory in Recurrent Networks of Spiking Neurons
Peter Tiňo, B., & Mills, A. J. S. (2006) · Neural Computation · doi:10.1162/neco.2006.18.3.591 · Cited by 24
“In this study we are concerned with possibilities of inducing deep temporal structures without fading memory in recurrent networks of spiking neurons.”
BackgroundTemplate-Based Spike Pattern Identification With Linear Convolution and Dynamic Time Warping
Chi, Z., Wu, W. L., Haga, Z. D., Hatsopoulos, N. G., & Margoliash, D. (2006) · Journal of Neurophysiology · doi:10.1152/jn.00448.2006 · Cited by 24
Incubation, not sleep, aids problem-solving
Brodt, S., Pöhlchen, D., Täumer, E., Gais, S., & Schönauer, M. (2018) · Sleep · doi:10.1093/sleep/zsy155 · Cited by 23
A model for navigation in unknown environments based on a reservoir of hippocampal sequences
Leibold, C. (2020) · Neural Networks · doi:10.1016/j.neunet.2020.01.014 · Cited by 24
A conserved role for sleep in supporting Spatial Learning in Drosophila
Melnattur, K. V., Kirszenblat, L., Morgan, E. P., Militchin, V., Sakran, B., English, D., Patel, R., Chan, D., van Swinderen, B., & Shaw, P. J. (2020) · SLEEP · doi:10.1093/sleep/zsaa197 · Cited by 22
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“The activity generated during waking in the hippocampus is reproduced in sequence during rapid eye movement (REM) sleep with the same time scale as the original experiences, lasting tens of seconds to minutes (Louie & Wilson, 2001), or is compressed during slowwave sleep (Nádasdy et al. 1999).”
BackgroundYoshioka, M. (2001) · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · doi:10.1103/physreve.65.011903 · Cited by 22
Gusev, P. A., & Alkon, D. L. (2001) · Journal of Neurophysiology · doi:10.1152/jn.2001.86.2.881 · Cited by 23
“…also facilitate involvement of the particular PCs in neuronal ensemble reactivation and depolarization of specific downstream CA1 targets during the animal’s rest cycle and period of sharp waves in the HC electroencephalogram (Csicsvari et al. 1999; Kudrimoti et al. 1999; Nadasdy et al. 1999).”
BackgroundConsolidation of Prospective Memory: Effects of Sleep on Completed and Reinstated Intentions
Barner, C., Seibold, M., Born, J., & Diekelmann, S. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2016.02025 · Cited by 29
A spatial code for temporal information is necessary for efficient sensory learning
Bagur, S., Bourg, J., Kempf, A., Tarpin, T., Bergaoui, K., Guo, Y., Ceballo, S., Schwenkgrub, J., Verdier, A., Puel, J., et al. (2025) · Science Advances · doi:10.1126/sciadv.adr6214 · Cited by 21
Long Synfire Chains Emerge by Spike-Timing Dependent Plasticity Modulated by Population Activity
Weissenberger, F., Meier, F., Lengler, J., Einarsson, H., & Steger, A. (2017) · International Journal of Neural Systems · doi:10.1142/s0129065717500447 · Cited by 22
3d-SPADE: Significance evaluation of spatio-temporal patterns of various temporal extents
Stella, A., Quaglio, P., Torre, E., & Grün, S. (2019) · Biosystems · doi:10.1016/j.biosystems.2019.104022 · Cited by 23
Role of Sleep in Formation of Relational Associative Memory
Tadros, T., & Bazhenov, M. (2022) · Journal of Neuroscience · doi:10.1523/jneurosci.2044-21.2022 · Cited by 19
Brady, E. S., Griffiths, J., Andrianova, L., Bielska, M. H., Saito, T., Saido, T. C., Randall, A. D., Tamagnini, F., Witton, J., & Craig, M. T. (2023) · Neurobiology of Disease · doi:10.1016/j.nbd.2023.106151 · Cited by 20
“SWR are oscillatory events that coincide with the replay of previously encoded information (N ´ adasdy et al., 1999) (Fig.”
BackgroundZutshi, I., & Buzsáki, G. (2023) · Current Biology · doi:10.1016/j.cub.2023.07.039 · Cited by 23
Self-citationThe Mystery of Structure and Function of Sensory Processing Areas of the Neocortex: A Resolution
Lörincz, A., Szatmáry, B., & Szirtes, G. (2002) · Journal of Computational Neuroscience · doi:10.1023/a:1020262214821 · Cited by 21
“…result, the output pattern sequences of the CA3 are similar in both theta and SPW states (Wilson and McNaughton, 1994; Skaggs and McNaughton, 1996; Nádasdy et al., 1999 Although in the model the layer V to layer II synapses are assigned as the neuronal substrate of LTM, it is also assumed in the…”
MethodBifurcation analysis of a two-compartment hippocampal pyramidal cell model
Atherton, L. A., Prince, L. Y., & Tsaneva-Atanasova, K. T. (2016) · Journal of Computational Neuroscience · doi:10.1007/s10827-016-0606-8 · Cited by 21
“During sharp wave ripples, hippocampal place cells that fire in discrete locations of an environment [50], reactivate such that co-active place cell activity, representing a discrete environmental location, or sequences of place cell activity, representing a trajectory through an environment, are replayed [71,46,36,20…”
BackgroundAssociative memory of phase-coded spatiotemporal patterns in leaky Integrate and Fire networks
Scarpetta, S., & Giacco, F. (2012) · Journal of Computational Neuroscience · doi:10.1007/s10827-012-0423-7 · Cited by 20
“Temporally structured replay of spatiotemporal patterns have been observed to occur during sleep, both in the cortex and hippocampus [1–4], and it has been hypothesized that this replay may subserve memory consolidation.”
BackgroundHub-activated signal transmission in complex networks
Jahnke, S., Memmesheimer, R.-M., & Timme, M. (2014) · Physical Review E · doi:10.1103/physreve.89.030701 · Cited by 21
Ponomarenko, A. A., Lin, J., Selbach, O., & Haas, H. L. (2003) · Neuroscience · doi:10.1016/s0306-4522(03)00524-4 · Cited by 21
Statistical Significance of Precisely Repeated Intracellular Synaptic Patterns
Ikegaya, Y., Matsumoto, W., Chiou, H.-Y., Yuste, R., & Aaron, G. B. (2008) · PLoS ONE · doi:10.1371/journal.pone.0003983 · Cited by 21
“With the help of computationally-intensive searches, there have been several studies that have claimed to demonstrate the existence of surprisingly precise and intricate patterns of repeating activity in neuronal circuits from in vivo preparations [7–13], intact slices [1,7,14,15], dissociated neuronal cultures [16–18…”
BackgroundJohnson, A. C., Jackson, J. C., & Redish, A. D. (2008) · Cambridge University Press eBooks · doi:10.1017/cbo9780511541650.005 · Cited by 20
“Cell firing during subsequent sleep states reflects recently experienced memories rather than the current location of the animal (Wilson and McNaughton, 1994; Kudrimoti et al., 1999; Nádasdy et al., 1999; Sutherland and McNaughton, 2000; Hoffmann and McNaughton, 2002; Lee and Wilson, 2002).”
BackgroundMethodInfluentialDynamic Hippocampal Circuits Support Learning- and Memory-Guided BehaviorsPreprint
Anderson, E. B., Grossrubatscher, I., & Frank, L. M. (2014) · Cold Spring Harbor Symposia on Quantitative Biology · doi:10.1101/sqb.2014.79.024760 · Cited by 22
“…shown that power in the 30–50-Hz slow g band of the local-field potential reflects the strength of coupling of CA3 to CA1 (Csicsvari et al. 2000; Colgin et al. 2009; Nakashiba et al. 2009), whereas power in the 50–100-Hz fast g band reflects the strength of EC3–CA1 coupling (Colgin et al. 2009).”
BackgroundNeural mechanisms of mental schema: a triplet of delta, low beta/spindle and ripple oscillations
Ohki, T., & Takei, Y. (2018) · European Journal of Neuroscience · doi:10.1111/ejn.13844 · Cited by 20
“It should be noted that replay often coincides with ripple oscillations; namely, any specific neuronal firing pattern is embedded in ripple oscillations (Kudrimoti et al., 1999; Nadasdy et al., 1999; Lee & Wilson, 2002; Buzsaki, 2015).”
BackgroundDynamics of sleep spindles and coupling to slow oscillations following motor learning in adult mice
Kam, K., Pettibone, W. D., Shim, K., Chen, R. K., & Varga, A. W. (2019) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2019.107100 · Cited by 23
Fuchsberger, T., Clopath, C., Jarzębowski, P., Brzosko, Z., Wang, H., & Paulsen, O. (2022) · eLife · doi:10.7554/elife.81071 · Cited by 19
“…of an environment, when the hippocampus shows theta activity, and later reactivated or replayed both during sleep (Wilson and McNaughton, 1994; Nadasdy et al., 1999; Lee and Wilson, 2002) and in the awake state (Kudrimoto et al., 1999; Foster and Wilson, 2006; Csicsvari et al., 2007; Diba and…”
BackgroundComparative biology of sleep in diverse animals
Lakhiani, R., Shanavas, S., & Melnattur, K. V. (2023) · Journal of Experimental Biology · doi:10.1242/jeb.245677 · Cited by 20
Methodological Caveats in the Detection of Coordinated Replay between Place Cells and Grid Cells
Trimper, J. B., Trettel, S. G., Hwaun, E., & Colgin, L. L. (2017) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2017.00057 · Cited by 21
“…and quiet wakefulness, recently active place cells have been shown to reactivate in a way that can reflect recently traveled trajectories (Pavlides and Winson, 1989; Wilson and McNaughton, 1994; Skaggs and McNaughton, 1996; Nádasdy et al., 1999; Foster and Wilson, 2006; Diba and Buzsáki, 2007).”
BackgroundFetterhoff, D., Opriș, I. C., Simpson, S. L., Deadwyler, S. A., Hampson, R. E., & Kraft, R. (2014) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2014.07.013 · Cited by 18
Sleep and hippocampus: Do we search for the right things?
Brankačk, J., Platt, B., & Riedel, G. (2009) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2009.03.027 · Cited by 22
“Another intensively studied electrophysiological phenomenon, the so-called replay or reactivation of activewaking neuronal activity both in the hippocampus (Pavlides and Winson, 1989; Wilson and McNaughton, 1994; Skaggs and McNaughton, 1996; Kudrimoti et al., 1999; Nádasdy et al., 1999) and in neocortex (Qin et al.”
BackgroundA new class of metrics for spike trainsPreprint
Rusu, C. V., & Florian, R. V. (2016) · Cited by 21
Expert consensus on clinical applications of high-frequency oscillations in epilepsy
Wang, Y., Zhou, D., Yang, X., Xu, X., Ren, L., Yu, T., Zhou, W., Shao, X., Yang, Z., Wang, S., et al. (2020) · Acta Epileptologica · doi:10.1186/s42494-020-00018-w · Cited by 21
Molecular Mechanisms of Memory Consolidation That Operate During Sleep
Reyes‐Resina, I., Samer, S., Kreutz, M. R., & Oelschlegel, A. M. (2021) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2021.767384 · Cited by 19
“…was found to result in impaired long-term memory performance 7 days after training, which was accompanied by reduced synaptic pruning in CA1 pyramidal cells, while short-term memory performance 2 days after training was intact (Katche et al., 2010, 2012; Nakayama et al., 2015).”
BackgroundInfluentialSleep and Synaptic Down-Selection
Tononi, G., & Cirelli, C. (2016) · Research and perspectives in neurosciences · doi:10.1007/978-3-319-28802-4_8 · Cited by 23
Saravanan, V., Arabali, D., Jochems, A., Cui, A., Gootjes-Dreesbach, L., Cutsuridis, V., & Yoshida, M. (2015) · Hippocampus · doi:10.1002/hipo.22429 · Cited by 18
“This compression rate is in agreement with the observations in vivo (~ 5 to 20 times; Nádasdy et al., 1999; Lee and Wilson, 2002; Ji and Wilson 2007).”
ResultSuitability of the Cingulate Cortex for Neural Control
Marzullo, T., Miller, C. R., & Kipke, D. R. (2006) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2006.886730 · Cited by 19
The Role of Sleep in Memory Processing: the Sequential Hypothesis
Giuditta, A., Mandile, P., Montagnese, P., Piscopo, S., & Vescia, S. (2003) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780198574002.003.0009 · Cited by 19
Forcato, C., Klinzing, J. G., Carbone, J., Radloff, M., Weber, F. D., Jan Born, A., & Diekelmann, S. (2020) · Communications Biology · doi:10.1038/s42003-020-01457-4 · Cited by 17
Sequence learning, prediction, and replay in networks of spiking neurons
Bouhadjar, Y., Wouters, D. J., Diesmann, M., & Tetzlaff, T. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010233 · Cited by 23
“In general, sequence replay is faster than the sequence presentation during learning, consistent with sequence compression and fast replay observed in hippocampus [46–48] and neocortex [6,49].”
Reap while you sleep: Consolidation of memories differs by how they were sown
Antony, J. W., & Schechtman, E. (2023) · Hippocampus · doi:10.1002/hipo.23526 · Cited by 23
“…findings that cellular activity underlying new learning is reactivated (Buzsáki, 1989; Pavlides & Winson, 1989; Wilson & McNaughton, 1994)—and even replayed in a similar spatiotemporal pattern (Ji & Wilson, 2007; Lee & Wilson, 2002; Nádasdy et al., 1999)—during post-learning sleep.”
BackgroundInternal operations in the hippocampus: single cell and ensemble temporal coding
Dragoi, G. (2013) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2013.00046 · Cited by 24
Spatio-temporal pattern recognizers using spiking neurons and spike-timing-dependent plasticity
Humble, J., Denham, S. L., & Wennekers, T. (2012) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2012.00084 · Cited by 18
Repertoires of Spike Avalanches Are Modulated by Behavior and Novelty
Ribeiro, T. L., Ribeiro, S. T. G., & Copelli, M. (2016) · Frontiers in Neural Circuits · doi:10.3389/fncir.2016.00016 · Cited by 18
“Although recurring spike patterns have been subject of research for a long time (Abeles et al., 1993; Wilson and McNaughton, 1994; Nádasdy et al., 1999; Dave and Margoliash, 2000; Hoffman and McNaughton, 2002; Hahnloser et al., 2003; Luczak et al., 2007; Madhavan et al., 2007; Rolston et al., 2007;…”
BackgroundChaotic phase synchronization in bursting-neuron models driven by a weak periodic force
Ando, H., Suetani, H., Kurths, J., & Aihara, K. (2012) · Physical Review E · doi:10.1103/physreve.86.016205 · Cited by 18
A New Class of Metrics for Spike Trains
Rusu, C. V., & Florian, R. V. (2013) · Neural Computation · doi:10.1162/neco_a_00545 · Cited by 18
“For example, temporally-structured multicell spiking patterns were observed in the hippocampus and cortex, and were associated to memory traces (Nádasdy et al., 1999; Ji and Wilson, 2007) while the coding of information in the phases of spikes relative to a background oscillation has been observed in many brain region…”
BackgroundChi, Z., Rauske, P. L., & Margoliash, D. (2003) · Neural Computation · doi:10.1162/089976603322362374 · Cited by 18
“There can be systematic differences between states in the rate that processes evolve; these differences are not accounted for by the templates (Wilson & McNaughton, 1994; Nádasdy et al., 1999; Dave & Margoliash, 2000; Louie & Wilson, 2001).”
BackgroundMethodInfluentialHippocampal ripple diversity organizes neuronal reactivation dynamics in the offline brain
Castelli, M., Lopes‐dos‐Santos, V., Gava, G. P., Lambiotte, R., & Dupret, D. (2025) · Neuron · doi:10.1016/j.neuron.2025.09.012 · Cited by 22
Functional Interactions of Prefrontal Cortex and the Hippocampus in Learning and Memory
Shapiro, M. L., Riceberg, J. S., Seip-Cammack, K., & Guise, K. G. (2014) · Springer eBooks · doi:10.1007/978-3-7091-1292-2_19 · Cited by 19
Increased mesiotemporal delta activity characterizes virtual navigation in humans
Clemens, Z., Borbély, C., Weiss, B., Erőss, L., Szűcs, A., Kelemen, A., Fabó, D., Rásonyi, G., Janszky, J., & Halász, P. (2013) · Neuroscience Research · doi:10.1016/j.neures.2013.03.004 · Cited by 19
“…there has been much progress in understanding the role of theta oscillations in organizing neuronal activity in animals (O‘Keefe and Dostrovsky, 1971; O‘Keefe and Recce, 1993; Skaggs et al., 1996; Skaggs and McNaughton, 1996; Nádasdy et al., 1999; Huerta and Lisman, 1993; Montgomery et al., 2008).”
Information-Geometric Measures as Robust Estimators of Connection Strengths and External Inputs
Tatsuno, M., Fellous, J., & Амари, Ш.-И. (2009) · Neural Computation · doi:10.1162/neco.2009.04-08-748 · Cited by 17
Off-line simulation inspires insight: A neurodynamics approach to efficient robot task learning
de Sousa, E. A. F., Erlhagen, W., Ferreira, F., & Bicho, E. G. (2015) · Neural Networks · doi:10.1016/j.neunet.2015.09.002 · Cited by 17
Gauy, M. M., Lengler, J., Einarsson, H., Meier, F., Weissenberger, F., Yanik, M. F., & Steger, A. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00961 · Cited by 15
“Spontaneous replays of such events in sharp-wave ripples, however, are independent of such speeds, stopping times or locations of the animal (Wilson and McNaughton, 1994; Nádasdy et al., 1999; Geisler et al., 2007; Davidson et al., 2009; Yamamoto and Tonegawa, 2017), as well during sleep (Wilson and McNaughton, 1994;…”
BackgroundOptimizing for generalization in the decoding of internally generated activity in the hippocampus
van der Meer, M. A. A., Carey, A. A., & Tanaka, Y. (2017) · Hippocampus · doi:10.1002/hipo.22714 · Cited by 19
Folschweiller, S., & Sauer, J. (2022) · Pflügers Archiv - European Journal of Physiology · doi:10.1007/s00424-022-02708-5 · Cited by 19
“It has been argued that Hebbian plasticity during replay might strengthen connections among neurons [53], which could facilitate the formation of new assemblies.”
BackgroundMethod
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
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