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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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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
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Sorted by citations
Items 501–600 of 931
Neuroimaging Studies of Sleep and Memory in Humans
Peigneux, P. (2014) · Current topics in behavioral neurosciences · doi:10.1007/7854_2014_326 · Cited by 20
“For instance, cell recording studies in the rat hippocampus and cortex following exposure to a spatial environment (Kudrimoti et al. 1999; Lee and Wilson 2002; Louie and Wilson 2001; Nadasdy et al. 1999; Pavlides and Winson 1989; Wilson and Mcnaughton 1994) and in the song area of young zebra finches (e.”
BackgroundReactivation of interference during sleep does not impair ongoing memory consolidation
Seibold, M., Rasch, B., Jan Born, A., & Diekelmann, S. (2017) · Memory · doi:10.1080/09658211.2017.1329442 · Cited by 16
Comparing Surrogates to Evaluate Precisely Timed Higher-Order Spike Correlations
Stella, A., Bouss, P., Palm, G., & Grün, S. (2022) · eNeuro · doi:10.1523/eneuro.0505-21.2022 · Cited by 16
“…Grün et al., 2003), spike exchange (across neurons or trials; Harrison et al., 2007; Smith and Kohn, 2008), ISI shuffling (within and across trials; Nádasdy et al., 1999; Masuda and Aihara, 2003; Ikegaya et al., 2004; Rivlin-Etzion et al., 2006), spike shuffling across neurons (within-trial;…”
BackgroundSleep sharp wave ripple and its functions in memory and synaptic plasticity
Zhou, Z., & Norimoto, H. (2023) · Neuroscience Research · doi:10.1016/j.neures.2023.01.011 · Cited by 17
Smooth Exact Gradient Descent Learning in Spiking Neural Networks
Klos, C., & Memmesheimer, R.-M. (2025) · Physical Review Letters · doi:10.1103/physrevlett.134.027301 · Cited by 16
“…that seemed fundamentally impossible [8]: despite the inherent discreteness of spikes, there can be exact nondisruptive, even smooth gradient descent learning in spiking neural networks, including the gradient-based removal and, after augmentation with pseudodynamics, also generation of spikes.”
L’hippocampe et le code neural de la mémoire spatiale
Poucet, B., Alvernhe, A., Hok, V., Renaudineau, S., Sargolini, F., & Save, É. (2010) · Biologie Aujourd hui · doi:10.1051/jbio/2010009 · Cited by 22
“D ` a un détail près , qui est que la séquence activée pendant le sommeil est temporelle - ment compressée et durè a peine quelques dizaines de millisecondes , même si elle correspondaità une période beaucoup plus longue dans la réalité ( Nadasdy et al .”
BackgroundPassot, J.-B., Luque, N. R., & Arleo, A. (2013) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2013.00095 · Cited by 18
Replays of spatial memories suppress topological fluctuations in cognitive map
Babichev, A., Morozov, D., & Dabaghian, Y. A. (2018) · Network Neuroscience · doi:10.1162/netn_a_00076 · Cited by 17
“gical fluctuations in the cognitive map. Specifically, we identified the periods when the speed of the animal falls below 15 cm/sec (which, in our simulations happens during 14% of time, see Fig. S3 and [81, 82]), and replayed the place cell sequences only during these periods. It turns out that although the resulting sl…”
Characterizing Complex, Multi-Scale Neural Phenomena Using State-Space Models
Eden, U. T., Frank, L. M., & Tao, L. (2017) · Springer eBooks · doi:10.1007/978-3-319-71976-4_2 · Cited by 17
Progress and issues in second-order analysis of hippocampal replay
van der Meer, M. A. A., Kemere, C. T., & Diba, K. (2020) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2019.0238 · Cited by 22
Kalman Filter Control Embedded into the Reinforcement Learning Framework
Szita, I., & Lörincz, A. (2004) · Neural Computation · doi:10.1162/089976604772744884 · Cited by 16
“…does have some plausibility in neurobiological models—consider, for example, hippocampal replays of time sequences (Skaggs & McNaughton, 1996; Nadasdy, Hirase, Czurko, Csicsvari, & Buzs´aki, 1999)—the extent of such batch learning should be limited given that the environment is subject to…”
BackgroundRecent Evidence of Memory Processing in Sleep
Pavlides, C., & Ribeiro, S. T. G. (2003) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780198574002.003.0017 · Cited by 16
Spatiotemporal Precision of Neuroimaging in Psychiatry
McFadyen, J., & Dolan, R. J. (2022) · Biological Psychiatry · doi:10.1016/j.biopsych.2022.08.016 · Cited by 16
Abbaspoor, S., & Hoffman, K. L. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114519 · Cited by 17
Mapped Clock Oscillators as Ring Devices and Their Application to Neuronal Electrical Rhythms
Zalay, O. C., & Bardakjian, B. L. (2008) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2008.923708 · Cited by 15
“suggests distinct rhythms have distinctive functionality, and that information is encoded in their patterns of activity [16], [18], [49].”
BackgroundToward an integrative theory of sleep and dreaming
Muzur, A. (2004) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2004.09.011 · Cited by 17
Precise Spiking Motifs in Neurobiological and Neuromorphic Data
Grimaldi, A., Gruel, A., Besnainou, C., Jérémie, J.-N., Martinet, J., & Perrinet, L. (2022) · Brain Sciences · doi:10.3390/brainsci13010068 · Cited by 16
Inhibitory plasticity supports replay generalization in the hippocampus
Liao, Z., Terada, S., Raikov, I., Hadjiabadi, D. H., Szoboszlay, M., Soltész, I., & Losonczy, A. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01745-w · Cited by 14
“Despite this, replay has mostly been investigated within the hippocampal CA1 circuitry 7–10, 13 with fewer studies reporting replay in CA3 To simulate the offline state (Fig.”
Braun, W., & Memmesheimer, R.-M. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009891 · Cited by 14
Raksin, J. N., Glaze, C. M., Smith, S. E., & Schmidt, M. F. (2011) · Journal of Neurophysiology · doi:10.1152/jn.01003.2009 · Cited by 14
Spatiotemporal learning in analog neural networks using spike-timing-dependent synaptic plasticity
Yoshioka, M., Scarpetta, S., & Marinaro, M. (2007) · Physical Review E · doi:10.1103/physreve.75.051917 · Cited by 14
Shamay‐Tsoory, S., Marton-Alper, I. Z., & Markus, A. (2024) · iScience · doi:10.1016/j.isci.2024.108796 · Cited by 14
Control Principles of Neural Dynamics Revealed by the Neurobiology of Timing
Stine, G. M., & Jazayeri, M. (2025) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-091724-015512 · Cited by 12
“Sequential activity is widespread in perceptual, cognitive, and motor tasks (Crowe et al. 2010, Fujisawa et al. 2008, Hahnloser et al. 2002, Harvey et al. 2012, Ikegaya et al. 2004, Jin et al. 2009, Koay et al. 2022, Nádasdy et al. 1999, Seidemann et al. 1996).”
Tatsuno, M., Malek, S., Kalvi, L., Ponce‐Alvarez, A., Ali, K., Euston, D. R., Grün, S., & McNaughton, B. L. (2020) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2019.0227 · Cited by 13
Han, R., Wang, J., Yu, H., Deng, B., Wei, X., Qin, Y., & Wang, H. (2015) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/1.4917014 · Cited by 13
The Functions of Sleep and the Effects of Sleep Deprivation
During, E., & Kawai, M. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-804074-4.00003-0 · Cited by 15
“Studies in rats demonstrate a hippocampal chronological “replay” during SWS following an experience of environment exploration (spatial learning)(112) that are associated with hippocampal “ripples” (100–200 Hz) and sharp wave activity.(113,114) In addition, coupling of hippocampal sharp-wave/ripple complexes with neoc…”
BackgroundAnalysis of perfect mappings of the stimuli through neural temporal sequences
Rodrı́guez, F. B., & Huerta, R. (2004) · Neural Networks · doi:10.1016/j.neunet.2003.12.003 · Cited by 13
On the Neuronal Activity in the Human Brain during Visual Recognition, Imagery and Binocular Rivalry
Kreiman, G. (2002) · CaltechTHESIS (California Institute of Technology) · doi:10.7907/e0xz-qp78 · Cited by 13
Episodic memory retrieval success is associated with rapid replay of episode contentPreprint
Wimmer, G. E., Liu, Y., Vehar, N., Behrens, T. E. J., & Dolan, R. J. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/758185 · Cited by 13
Jeong, H., Namboodiri, V. M. K., Jung, M. W., & Andermann, M. L. (2023) · Current Biology · doi:10.1016/j.cub.2023.10.073 · Cited by 12
Chang, H., Esteves, I. M., Neumann, A. R., Mohajerani, M. H., & McNaughton, B. L. (2023) · Nature Communications · doi:10.1038/s41467-023-43254-7 · Cited by 12
From Inhibition to Exciting Science
Buzsáki, G. (2024) · Hippocampus · doi:10.1002/hipo.23659 · Cited by 12
Self-citationMemory Replay in the Hippocampus
Jadhav, S. P., & Frank, L. M. (2014) · Springer eBooks · doi:10.1007/978-3-7091-1292-2_13 · Cited by 12
The hippocampal physiology of approaching middle‐age: Early indicators of change
Huxter, J. R., Miranda, J. A., & Dias, R. (2012) · Hippocampus · doi:10.1002/hipo.22027 · Cited by 14
“The correlation between temporal bias scores is significantly increased after the RUN trial (F(1,13) 5 19,315, P 5 0.001), as shown previously (Skaggs and McNaughton, 1996; Nadasdy et al., 1999).”
MethodInfluentialTracking Human Engrams Using Multivariate Analysis Techniques
Kunz, L., Deuker, L., Zhang, H., & Axmacher, N. (2018) · Handbook of behavioral neuroscience · doi:10.1016/b978-0-12-812028-6.00026-4 · Cited by 12
Unsupervised Detection of Cell-Assembly Sequences by Similarity-Based Clustering
Watanabe, K., Haga, T., Euston, D. R., Tatsuno, M., & Fukai, T. (2019) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2019.00039 · Cited by 13
“These patterns presumably correspond to place-cell firing phase-locked to theta oscillation and their ripple-associated replays, respectively (Nádasdy et al., 1999; Foster and Wilson, 2006).”
BackgroundFunamizu, A., Kanzaki, R., & Takahashi, H. (2011) · Neural Networks · doi:10.1016/j.neunet.2010.12.010 · Cited by 12
Statistical significance of sequential firing patterns in multi-neuronal spike trains
Diekman, C. O., SASTRY, P. S., & Unnikrishnan, K. P. (2009) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2009.06.018 · Cited by 11
Computational models of memory consolidation and long-term synaptic plasticity during sleep
Rennó‐Costa, C., da Silva, A. C. C., Blanco, W., & Ribeiro, S. T. G. (2018) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2018.10.003 · Cited by 12
Silent Synapse Unsilencing in Hippocampal CA1 Neurons for Associative Fear Memory Storage
Wang, Y., Liu, Y., Wang, L., Tang, W., & Wang, Z. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy288 · Cited by 12
The Ins and Outs of Hippocampal Circuits
Tonegawa, S., & McHugh, T. J. (2008) · Neuron · doi:10.1016/j.neuron.2008.01.005 · Cited by 12
“It has been shown that neurons with overlapping place fields tend to fire together during ripple oscillation—brief, large-amplitude high-frequency bursts (150–250 Hz) in the local field potential (LFP)—that occur in subsequent periods of sleep (Nadasdy et al., 1999; Wilson and McNaughton, 1994).”
BackgroundMethods for Assessment of Memory Reactivation
Liu, S., Grosmark, A., & Chen, Z. S. (2018) · Neural Computation · doi:10.1162/neco_a_01090 · Cited by 11
“For instance, for a linearized spatial task, we can compare with template matching (Nadasdy et al., 1999; Louie & Wilson, 2001; Euston, Tatsuno, & McNaughton, 2007; Wilber et al., 2017) and line fit (Davidson et al., 2009) methods.”
MethodMiyata, R., Ota, K., & Aonishi, T. (2013) · PLoS ONE · doi:10.1371/journal.pone.0077395 · Cited by 11
“It has been reported that characteristic ensemble spiking patterns are consistently repeated in the hippocampal CA1 region during waking and sleep periods [1–9].”
BackgroundInitiation of sleep-dependent cortical-hippocampal correlations at wakefulness-sleep transition
Haggerty, D. C., & Ji, D. (2014) · Journal of Neurophysiology · doi:10.1152/jn.00783.2013 · Cited by 11
Cona, F., & Ursino, M. (2014) · Journal of Computational Neuroscience · doi:10.1007/s10827-014-0533-5 · Cited by 11
PV+ Cells Enhance Temporal Population Codes but not Stimulus-Related Timing in Auditory Cortex
Krause, B. M., Murphy, C. A., Uhlrich, D. J., & Banks, M. I. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx345 · Cited by 11
“The timing of action potentials in cortical pyramidal cells often contains information about current and remembered sensory experiences (Optican and Richmond 1987; Abeles et al. 1994; Nadasdy et al. 1999; Lisman 2005; Kayser et al. 2009; Victor 2000; Shmiel et al. 2005; Wang et al. 2008).”
BackgroundNeural mechanisms of vocal imitation: The role of sleep replay in shaping mirror neurons
Giret, N., Edeline, J., & Negro, C. D. (2017) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2017.01.051 · Cited by 12
Liu, T., & Watson, B. O. (2020) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2019.0233 · Cited by 10
“from seconds down to less than 100 ms) and with reduced numbers of total action potentials [2,9,10].”
BackgroundResultLearning Beyond Finite Memory in Recurrent Networks of Spiking Neurons
Peter Tiňo, B., & Mills, A. (2005) · Lecture notes in computer science · doi:10.1007/11539117_95 · Cited by 11
Connectivity and Dynamics in Local Cortical Networks
Beggs, J. M., Klukas, J., & Chen, W. (2007) · Understanding complex systems · doi:10.1007/978-3-540-71512-2_3 · Cited by 11
Huo, J., & Murray, A. (2008) · Neural Networks · doi:10.1016/j.neunet.2008.10.007 · Cited by 10
Zavecz, Z., Janacsek, K., Simor, P., Cohen, M. X., & Németh, D. (2024) · Cortex · doi:10.1016/j.cortex.2024.07.008 · Cited by 10
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Smith, A. C., & Smith, P. (2006) · Neural Computation · doi:10.1162/089976606776241020 · Cited by 10
Lin, C.-C., & Yang, C. (2014) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2014.08.011 · Cited by 12
The grammar of mammalian brain capacity
Rodriguez, A., & Granger, R. (2016) · Theoretical Computer Science · doi:10.1016/j.tcs.2016.03.021 · Cited by 11
Evidence for Long-Timescale Patterns of Synaptic Inputs in CA1 of Awake Behaving Mice
Kolb, I., Franzesi, G. T., Wang, M. C., Kodandaramaiah, S. B., Forest, C. R., Boyden, E. S., & Singer, A. C. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.1519-17.2017 · Cited by 10
“, 2009) reoccurs during behavior and during periods of quiescence (replay or reactivation, and preplay; Nádasdy et al., 1999; Louie and Wilson, 2001; Dragoi and Tonegawa, 2011), and is tied to sharp-wave ripples (SWRs), thought to play an important role in learning and memory (Girardeau et al.”
BackgroundMethodInfluentialvan der Meij, R., & Voytek, B. (2018) · eNeuro · doi:10.1523/eneuro.0379-17.2018 · Cited by 11
“The above is different from techniques that search for template spike sequences in their original neuron-by-time representations (Abeles and Gerstein, 1988; Nádasdy et al., 1999; Tetko and Villa, 2001; Lee and Wilson, 2002; Schnitzer and Meister, 2003; Ikegaya et al., 2004; Gansel and Singer, 2012).”
MethodThe Role of the Locus Coeruleus in Cellular and Systems Memory Consolidation
Eschenko, O. (2018) · Handbook of behavioral neuroscience · doi:10.1016/b978-0-12-812028-6.00018-5 · Cited by 10
Martinez, R. H., Lansner, A., & Herman, P. A. (2019) · PLoS ONE · doi:10.1371/journal.pone.0220161 · Cited by 11
“, 2009), the hippocampus (Nádasdy et al., 1999; Pastalkova et al., 2008; Louie and Wilson, 2001; Davidson et al., 2009; MacDonald et al., 2013) and the HVC area in songbirds (Hahnloser et al.”
Yegenoglu, A., Quaglio, P., Torre, E., Grün, S., & Endres, D. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-40985-6_1 · Cited by 10
Consolidation of Episodic Memory: An Epiphenomenon of Semantic Learning
Cheng, S. (2017) · Studies in neuroscience, psychology and behavioral economics · doi:10.1007/978-3-319-45066-7_4 · Cited by 9
Pattern reverberation in networks of excitable systems with connection delays
Lücken, L., Rosin, D. P., Worlitzer, V. M., & Yanchuk, S. (2017) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/1.4971971 · Cited by 10
Ribeiro, S. T. G., Simões, C., & Nicolelis, M. A. L. (2008) · Springer eBooks · doi:10.1007/978-1-4020-8352-5_17 · Cited by 10
Brown, A., Gervais, N. J., Gravelsins, L. L., O’Byrne, J., Calvo, N., Ramana, S., Shao, Z., Bernardini, M. Q., Jacobson, M. R., Rajah, M. N., et al. (2024) · Hormones and Behavior · doi:10.1016/j.yhbeh.2024.105619 · Cited by 9
A visual paired associate learning ( vPAL ) paradigm to study memory consolidation during sleep
Schmidig, F. J., Geva‐Sagiv, M., Falach, R., Yakim, S., Gat, Y., Sharon, O., Fried, I., & Nir, Y. (2024) · Journal of Sleep Research · doi:10.1111/jsr.14151 · Cited by 9
Rusu, S. I., Bos, J. J., Marchesi, P., Lankelma, J. V., Pica, I. F., Gentet, L. J., Joëls, M., & Pennartz, C. M. A. (2024) · iScience · doi:10.1016/j.isci.2024.109205 · Cited by 7
“Furthermore, cross-correlograms during Rest2 did not reveal a clear temporal compression of pairwise firing relationships, unlike the compressed, ripple-associated replay reported for hippocampus, 52,53,71 mPFC, 29,41 and ventral striatum.”
BackgroundHippocampal ripples coincide with “up-state” and spindles in retrosplenial cortex
Pedrosa, R., Nazari, M., Kergoat, L., Bernard, C., Mohajerani, M. H., Stella, F., & Battaglia, F. P. (2024) · Cerebral Cortex · doi:10.1093/cercor/bhae083 · Cited by 12
Stable and unstable periodic orbits in complex networks of spikingneurons with delays
Memmesheimer, R.-M., & Timme, M. (2010) · Discrete and Continuous Dynamical Systems · doi:10.3934/dcds.2010.28.1555 · Cited by 9
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Bukalo, O., Lee, P. R., & Fields, R. D. (2016) · Neuroscience Letters · doi:10.1016/j.neulet.2016.10.023 · Cited by 11
“4 by decreased sensory input and offline replay of neural sequences learned during encoding sensory information [4, 5], and disrupting SPW-Rs impairs memory retention [6, 7].”
Different propagation speeds of recalled sequences in plastic spiking neural networks
Huang, X., Zheng, Z., Hu, G., Wu, S., & Rasch, M. J. (2015) · New Journal of Physics · doi:10.1088/1367-2630/17/3/035006 · Cited by 8
Propagation of Collective Temporal Regularity in Noisy Hierarchical Networks
Han, R., Wang, J., Miao, R., Deng, B., Qin, Y., Yu, H., & Wei, X. (2015) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2015.2502993 · Cited by 9
Moriya, F., Shimba, K., Kotani, K., & Jimbo, Y. (2021) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac1c88 · Cited by 9
“Several computational studies regarding hippocampal adult neurogenesis speculate that NSCs in the dentate gyrus contribute to encoding novel inputs [67] and reducing interference among new information [68, 69].”
BackgroundMolecular Mechanisms of Memory Consolidation
Hellman, K. M., & Abel, T. G. (2003) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780198574002.003.0016 · Cited by 9
Ortega, R. S., & Peigneux, P. (2024) · SLEEP · doi:10.1093/sleep/zsae114 · Cited by 9
Propagation of sharp wave‐ripple activity in the mouse hippocampal CA3 subfield in vitro
Schieferstein, N., del Toro, A., Evangelista, R., Imbrosci, B., Swaminathan, A., Schmitz, D., Maier, N., & Kempter, R. (2024) · The Journal of Physiology · doi:10.1113/jp285671 · Cited by 9
“During SPW-Rs, hippocampal ensembles are reactivated (Kudrimoti et al., 1999; Lee & Wilson, 2002; Nádasdy et al., 1999; Wilson & McNaughton, 1994).”
BackgroundIntact ultrafast memory consolidation in adults with autism and neurotypicals with autism traits
Nagy, C. A., Hann, F., Brezóczki, B., Farkas, K., Vékony, T., Pesthy, O., & Németh, D. (2024) · Brain Research · doi:10.1016/j.brainres.2024.149299 · Cited by 8
“First discovered in rodents (N ´ adasdy et al., 1999; Wilson & McNaughton, 1994), it primarily involves the reactivation of hippocampal place cell sequences that represent spatial trajectories, occurring much faster than the original experience.”
BackgroundSchlingloff, D., Freund, T. F., Hangya, B., & Gulyás, A. I. (2025) · Journal of Neuroscience · doi:10.1523/jneurosci.0500-25.2025 · Cited by 11
“…waves predominantly occur during consummatory behaviors and slow-wave sleep, when they feature time-compressed “ o ff -line ” reactivation of neuronal ensembles (e.g., memory traces) linked together by recent experience during exploratory behavior (Nádasdy et al., 1999; Foster and Wilson, 2006).”
Hierarchical Replay of Multi-regional Sequential Spiking Associated with Working Memory
Huang, E., Xu, D., Zhu, H., Chen, Z., Chen, Y., Lei, S., Liu, J., Li, C., & Zhang, X. (2025) · Neuroscience Bulletin · doi:10.1007/s12264-025-01524-y · Cited by 7
Sleep-Wake and Cortical Synaptic Plasticity
Timofeev, I., & Chauvette, S. (2019) · Handbook of behavioral neuroscience · doi:10.1016/b978-0-12-813743-7.00029-3 · Cited by 8
Sonho, memória e o reencontro de Freud com o cérebro
Ribeiro, S. T. G. (2003) · Brazilian Journal of Psychiatry · doi:10.1590/s1516-44462003000600013 · Cited by 8
A hidden Markov model for decoding and the analysis of replay in spike trains
Box, M., Jones, M. W., & Whiteley, N. (2016) · Journal of Computational Neuroscience · doi:10.1007/s10827-016-0621-9 · Cited by 9
“However, it remains to be demonstrated whether the same encoded information is being replayed within the two regions during replay events, as implied by the consolidation hypothesis.”
BackgroundMethodInfluentialPost-Training Sleep Modulates Topographical Relearning-Dependent Resting State Activity
Deantoni, M., Villemonteix, T., Balteau, E., Schmidt, C., & Peigneux, P. (2021) · Brain Sciences · doi:10.3390/brainsci11040476 · Cited by 8
“Supporting this hypothesis, rodent studies showed that learning-related neural patterns of hippocampal place cell activity are spontaneously replayed during sleep, in particular during non-rapid eye movement (NREM) sleep [15,16], which does not preclude an important role for REM sleep in memory consolidation (see e.”
BackgroundThe Evolution of Neural Systems for Sleep and Dreaming
Ribeiro, S. T. G., & Nicolelis, M. A. L. (2007) · Elsevier eBooks · doi:10.1016/b0-12-370878-8/00007-0 · Cited by 8
Blanco, W., & Ribeiro, S. T. G. (2013) · Revista USP · doi:10.11606/issn.2316-9036.v0i98p17-30 · Cited by 8
Memory Processing during Sleep Mechanisms and Evidence from Neuroimaging Studies
Peigneux, P., Melchior, G., Schmidt, C., Dang‐Vu, T. T., Boly, M., Laureys, S., & Maquet, P. (2004) · Psychologica Belgica · doi:10.5334/pb.1020 · Cited by 8
Waking EEG power spectra in the rat: correlations with training performance
Mandile, P., Giuditta, A., ROMANO, F., Montagnese, P., Piscopo, S., Cotugno, M., & Vescia, S. (2003) · Cognitive Brain Research · doi:10.1016/s0926-6410(03)00084-3 · Cited by 8
van den Berg, N. H., Benoit, A., Toor, B., & Fogel, S. (2019) · Handbook of Behavioral Neuroscience · doi:10.1016/b978-0-12-813743-7.00030-x · Cited by 10
Neural Representation of Episodic Time
Kwok, S. C., Lapate, R. C., Sakon, J. J., van Wassenhove, V., Xue, G., & Zheng, J. (2025) · Journal of Neuroscience · doi:10.1523/jneurosci.1397-25.2025 · Cited by 10
“One of the essential signatures for a temporal code in the brain is the replay of neural sequences (Nádasdy et al., 1999) in which a sequence of neuronal activity previously observed during a behavior is being replayed posttask and at sleep.”
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
“…sleep and resting states, spontaneous hippocampal activity bursts have been observed in which neurons were activated in an order similar to exploratory phases (Wilson and McNaughton 1994; Nádasdy et al. 1999; Lee et al. 2002; Diba and Buzsáki 2007; Gupta et al. 2010; Dragoi and Tonegawa 2011).”
Hyperpolarization-activated currents drive neuronal activation sequences in sleep
Mehrotra, D., Levenstein, D., Duszkiewicz, A. J., Carrasco, S. S., Booker, S. A., Kwiatkowska, A., & Peyrache, A. (2024) · Current Biology · doi:10.1016/j.cub.2024.05.048 · Cited by 7
Local sleep: A new concept in brain plasticity
Avvenuti, G., & Bernardi, G. (2022) · Handbook of clinical neurology · doi:10.1016/b978-0-12-819410-2.00003-5 · Cited by 10
Howard, M. D., Skorheim, S. W., & Pilly, P. K. (2022) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2022.972235 · Cited by 10
“Replays are primarily observed during the UP states of SWOs during SWS (Nádasdy et al., 1999), which we have simulated as shown in Figure 5.”
BackgroundInfluentialMental Time Travel: A Retrospective
Redish, A. D. (2024) · Hippocampus · doi:10.1002/hipo.23661 · Cited by 8
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
Sleep Loss Immediately After Fear Memory Reactivation Attenuates Fear Memory Reconsolidation
Sharma, R., Sahota, P. K., & Thakkar, M. M. (2020) · Neuroscience · doi:10.1016/j.neuroscience.2019.12.024 · Cited by 8
“In this process, prior experiences are replayed during sleep resulting in reactivation and strengthening of hippocampal memory traces followed by integration of information into the neocortical long-term memory networks (Euston et al., 2007; Ji and Wilson, 2007; Louie and Wilson, 2001; Nadasdy et al., 1999; Peyrache e…”
BackgroundCharacterizing 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
“When the animal is asleep or immobile, these activity patterns reappear, but on a shorter timescale [2], [3].”
BackgroundAdaptive 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
“Some of these methods focus on identifying individual sequences within a distribution of responses, which were recorded over multiple trials or over an extended time period (Nádasdy et al., 1999; Ikegaya et al., 2004; Mackevicius et al., 2019).”
Replay in Humans—First Evidence and Open Questions
Zhang, H., Deuker, L., & Axmacher, N. (2017) · Studies in neuroscience, psychology and behavioral economics · doi:10.1007/978-3-319-45066-7_15 · Cited by 7
Dynamics in Co-evolving Networks of Active Elements
Tanaka, T., Aoki, T., & Aoyagi, T. (2009) · Forma · Cited by 7
Yoshioka, M. (2002) · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · doi:10.1103/physreve.66.061913 · Cited by 7
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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