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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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Items 301–400 of 931
Uncovering temporal structure in hippocampal output patterns
Maboudi, K., Ackermann, E., de Jong, L. W., Pfeiffer, B. E., Foster, D. J., Diba, K., & Kemere, C. T. (2018) · eLife · doi:10.7554/elife.34467 · Cited by 62
“By now, multiple studies have shown that during many sharp-wave ripple-associated PBEs, hippocampal ‘place cells’ (O’Keefe and O’Keefe, 1976) fire in compressed sequences that reflect the firing order determined by the sequential locations of their individual place fields (Diba and Buzsáki, 2007; Foster and Wilson, 20…”
BackgroundLow-Probability Transmission of Neocortical and Entorhinal Impulses Through the Perirhinal Cortex
Pelletier, J. G., Apergis, J., & Paré, D. (2004) · Journal of Neurophysiology · doi:10.1152/jn.01197.2003 · Cited by 62
“Although evidence of replay was obtained in the hippocampus (Nadasdy et al. 1999; Skaggs and McNaughton 1996; Wilson and McNaughton 1994; reviewed in Sutherland and McNaughton 2000), whether hippocampal-driven activity is relayed by the perirhinal cortex back to neocortical storage sites has never…”
BackgroundMultiple memories can be simultaneously reactivated during sleep as effectively as a single memory
Schechtman, E., Antony, J. W., Lampe, A., Wilson, B. J., Norman, K. A., & Paller, K. A. (2021) · Communications Biology · doi:10.1038/s42003-020-01512-0 · Cited by 61
“Indeed, replay during sleep in rodents can be temporally compressed by a factor of 20 37,38 and recent evidence in humans also suggests temporal compression is at play, at least during wake 39,40 .”
Field Potential Signature of Distinct Multicellular Activity Patterns in the Mouse Hippocampus
Reichinnek, S., Künsting, T., Draguhn, A., & Both, M. (2010) · Journal of Neuroscience · doi:10.1523/jneurosci.2535-10.2010 · Cited by 57
“These sequences are replayed, at faster pace, during subsequent sleep or inactive wakefulness (Wilson and McNaughton, 1994; Nadasdy et al., 1999; Foster and Wilson, 2006).”
BackgroundIdentification of memory reactivation during sleep by EEG classification
Belal, S. Y., Cousins, J. N., El‐Deredy, W., Parkes, L. M., Schneider, J., Tsujimura, H., Zoumpoulaki, A., Amadó, M. P., Santamaria, L., & Lewis, P. A. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.04.029 · Cited by 66
Nicola, W., & Clopath, C. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0415-2 · Cited by 61
Normal values in anal manometry and rectal sensation: a problem of range.
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Evaluating theories of bird song learning: implications for future directions
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“Comparison of spontaneous neural activity to activity recorded at other times in the context of observable behavior is statistically challenging, and criteria for which analysis techniques apply and how to assess statistical significance is under active investigation (e.g., Nadasdy et al. 1999).”
BackgroundSleep, off-line processing, and vocal learning
Margoliash, D., & Schmidt, M. F. (2010) · Brain and Language · doi:10.1016/j.bandl.2009.09.005 · Cited by 105
Five Decades of Hippocampal Place Cells and EEG Rhythms in Behaving Rats
Colgin, L. L. (2019) · Journal of Neuroscience · doi:10.1523/jneurosci.0741-19.2019 · Cited by 62
“Later studies extended these findings to show that place cells that fired sequentially during waking behaviors were later replayed in the same order during sharp wave-ripples in sleep (Nádasdy et al., 1999; Lee and Wilson, 2002).”
BackgroundResultInfluentialContributions of post-learning REM and NREM sleep to memory retrieval
MacDonald, K. J., & Côté, K. A. (2021) · Sleep Medicine Reviews · doi:10.1016/j.smrv.2021.101453 · Cited by 66
HectoSTAR μLED Optoelectrodes for Large‐Scale, High‐Precision In Vivo Opto‐Electrophysiology
Vöröslakos, M., Kim, K., Slager, N., Ko, E., Oh, S., Parizi, S. S., Hendrix, B., Seymour, J. P., Wise, K. D., Buzsáki, G., et al. (2022) · Advanced Science · doi:10.1002/advs.202105414 · Cited by 60
Self-citationA possible role of ectopic action potentials in the in vitro hippocampal sharp wave–ripple complexes
Papatheodoropoulos, C. (2008) · Neuroscience · doi:10.1016/j.neuroscience.2008.09.040 · Cited by 60
Memory reactivation and consolidation during sleep: from cellular mechanisms to human performance
Pennartz, C. M. A., Uylings, H. B. M., Barnes, C. A., & McNaughton, B. L. (2002) · Progress in brain research · doi:10.1016/s0079-6123(02)38076-2 · Cited by 59
Temporally delayed linear modelling (TDLM) measures replay in both animals and humans
Liu, Y., Dolan, R. J., Higgins, C., Penagos, H., Woolrich, M. W., Ólafsdóttir, H. F., Barry, C., Kurth-Nelson, Z. L., & Behrens, T. E. J. (2021) · eLife · doi:10.7554/elife.66917 · Cited by 65
Mental simulation of routes during navigation involves adaptive temporal compression
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Why REM sleep? Clues beyond the laboratory in a more challenging world
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Recurrent Infomax Generates Cell Assemblies, Neuronal Avalanches, and Simple Cell-Like Selectivity
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“The existence of interesting types of neuronal activity, such as patterned firings, synchronization, oscillation, and global state transitions has been revealed by multielectrode recording and calcium imaging (Nadasdy et al., 1999; Cossart et al., 2003; Ikegaya et al., 2004; Fujisawa et al., 2006; Sakurai and Takahash…”
BackgroundDevelopment of schemas revealed by prior experience and NMDA receptor knock-out
Dragoi, G., & Tonegawa, S. (2013) · eLife · doi:10.7554/elife.01326 · Cited by 61
“…or, separately, described the phenomenon of temporal sequence replay during awake resting (Foster and Wilson, 2006; Diba and Buzsaki, 2007; Davidson et al., 2009; Karlsson and Frank, 2009) or post-Run sleep (Nadasdy et al., 1999; Lee and Wilson, 2002; Ji and Wilson, 2007; Karlsson and Frank, 2009).”
BackgroundInfluentialJiang, X., González-Martínez, J., & Halgren, E. (2019) · Journal of Neuroscience · doi:10.1523/jneurosci.2858-18.2019 · Cited by 59
“Pyramidal cell firing during HC-SWR tends to reproduce the spatio-temporal patterns established during the preceding active periods; this “replay” is hypothesized to guide cortical activity as it consolidates memories (Wilson and McNaughton, 1994; Skaggs and McNaughton, 1996; Nádasdy et al., 1999).”
BackgroundMemory Capacity for Sequences in a Recurrent Network with Biological Constraints
Leibold, C., & Kempter, R. (2006) · Neural Computation · doi:10.1162/neco.2006.18.4.904 · Cited by 58
“The latter are supposed to be generated by CA3 pyramidal cells (Behrens, van den Boom, de Hoz, Friedman, & Heinemann, 2005) and may reflect sequence replay (Wilson & McNaughton, 1994; Nádasdy et al., 1999; Lee & Wilson, 2002) occurring in timeslices of about 5 ms.”
BackgroundNew excitement in cognitive space: between place cells and spatial memory
Moser, E. I., & Paulsen, O. (2001) · Current Opinion in Neurobiology · doi:10.1016/s0959-4388(01)00279-3 · Cited by 58
Berners-Lee, A., Feng, T., Silva, D., Wu, X., Ambrose, E. R., Pfeiffer, B. E., & Foster, D. J. (2022) · Neuron · doi:10.1016/j.neuron.2022.03.010 · Cited by 65
Hemberger, M., Idelson, M. S., Pammer, L., & Laurent, G. (2019) · Neuron · doi:10.1016/j.neuron.2019.07.017 · Cited by 57
“These sequences share striking similarities with those produced during replay events in mammalian hippocampus (Diba and Buzsáki, 2007; Foster and Wilson, 2006; Nádasdy et al., 1999) and in song-generating circuits in zebrafinch high vocal center (HVC; Hahnloser et al.”
BackgroundSpike sequences and their consequences
Nádasdy, Z. (2000) · Journal of Physiology-Paris · doi:10.1016/s0928-4257(00)01103-7 · Cited by 57
“Recurring patterns of action potentials can either be generated as independent trains or a flow of activity from one neuron to another in the chain of synaptic connections [2, 26, 30, 35].”
BackgroundMethodInfluentialSelf-citationCharacteristics of sequential activity in networks with temporally asymmetric Hebbian learning
Gillett, M., Pereira, U., & Brunel, N. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1918674117 · Cited by 58
“Such a mechanism could underlie the phenomenon of hippocampal replay during sharp-wave ripple events, in which previously experienced sequences of place cell-activity can reactivate on significantly temporally compressed timescales (57).”
Berners-Lee, A., Wu, X., & Foster, D. J. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.1158-20.2021 · Cited by 58
“During rest periods, sharp-wave ripples (SWRs; 150–250 Hz) in the HP local field potential (LFP) occur concurrently with patterns across populations of HP neurons that depict trajectories through explored space, termed “replay” (Nádasdy et al., 1999; Foster and Wilson, 2006; Karlsson and Frank, 2009; Foster, 2017).”
BackgroundSleep Enforces the Temporal Order in Memory
Drosopoulos, S., Windau, E., Wagner, U., & Jan Born, A. (2007) · PLoS ONE · doi:10.1371/journal.pone.0000376 · Cited by 61
“Along this line of reasoning, our results agree with concepts of sequence memory pinpointing that sequence structure is preserved during replay in the sleep state although it can occur at a faster rate than during waking [6,23,28,29].”
ResultSurrogate spike train generation through dithering in operational time
Louis, S. (2010) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2010.00127 · Cited by 56
“The methods consist in randomly shifting individual spikes (Date et al., 1998; Nadasdy et al., 1999; Hatsopoulus et al., 2003; Shmiel et al., 2006; Stark and Abeles, 2009), patterns of spikes (Harrison and Geman, 2009), or the whole spike train (Perkel et al., 1967; Pipa et al., 2008) by an amount…”
How our understanding of memory replay evolves
Chen, Z. S., & Wilson, M. A. (2023) · Journal of Neurophysiology · doi:10.1152/jn.00454.2022 · Cited by 68
Hippocampal information processing across sleep/wake cycles
Mizuseki, K., & Miyawaki, H. (2017) · Neuroscience Research · doi:10.1016/j.neures.2017.04.018 · Cited by 58
Sharp wave/ripple network oscillations and learning-associated hippocampal maps
Csicsvari, J., & Dupret, D. (2013) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2012.0528 · Cited by 55
“Indeed, a large number of studies have confirmed the reactivation of waking neuronal activity patterns during sleep, particularly during SWRs [5,9–12].”
BackgroundSelf-citationSequence Memory in the Hippocampal–Entorhinal Region
Bellmund, J. L. S., Polti, I., & Doeller, C. F. (2020) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01592 · Cited by 56
Cortical reactivations predict future sensory responses
Nguyen, N. D., Lutas, A., Amsalem, O., Fernando, J., Ahn, A. Y.-E., Hakim, R., Vergara, J., McMahon, J., Dimidschstein, J., Sabatini, B. L., et al. (2023) · Nature · doi:10.1038/s41586-023-06810-1 · Cited by 53
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Extracellular potentials in low-density dissociated neuronal cultures
Claverol-Tinturé, E., & Pine, J. (2002) · Journal of Neuroscience Methods · doi:10.1016/s0165-0270(02)00043-2 · Cited by 52
Hippocampal CA1 Ripples as Inhibitory Transients
Malerba, P., Krishnan, G. P., Fellous, J., & Bazhenov, M. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004880 · Cited by 52
“On average 10% of pyramidal cells are active in any given ripple, and their spikes are locked to the trough of each the oscillations within a ripple event [25, 26].”
BackgroundHampson, R. E., Zhuang, S.-Y., Weiner, J. L., & Deadwyler, S. A. (2003) · Journal of Neurophysiology · doi:10.1152/jn.01161.2002 · Cited by 52
“The one normal circumstance in which prolonged action potential bursts occur frequently in hippocampal neurons in the rat is during sleep (Nadasdy et al. 1999); however, even these episodes are transient and, outside of providing a synchronizing influence, tend to mimic firing patterns that occur…”
BackgroundA Computational Model of Craving and Obsession
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The malleable brain: plasticity of neural circuits and behavior – a review from students to students
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“This allows for the repetition of new experiences and enables mechanisms supporting synaptic plasticity (Nadasdy et al. 1999; Buzsaki 2015; Jahnke et al. 2015; Sadowski et al. 2016).”
BackgroundChenani, A., Sabariego, M., Schlesiger, M. I., Leutgeb, J. K., Leutgeb, S., & Leibold, C. (2019) · Nature Communications · doi:10.1038/s41467-019-09280-0 · Cited by 52
Local Sleep Oscillations: Implications for Memory Consolidation
Geva‐Sagiv, M., & Nir, Y. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00813 · Cited by 56
“Extensive animal research established a tight link between HC SWRs and memory consolidation in both wakefulness and sleep: SWRs accompany the sleep-associated re-activation of HC neuron ensembles that were active during the preceding awake learning experience (Nadasdy et al., 1999; Eschenko et al., 2008; Peyrache et a…”
BackgroundWittkuhn, L., Chien, S., Hall-McMaster, S., & Schuck, N. W. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.08.002 · Cited by 49
Continuous attractors for dynamic memories
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The Role of Sleep in Human Declarative Memory Consolidation
Alger, S. E., Chambers, A. M., Cunningham, T. J., & Payne, J. D. (2014) · Current topics in behavioral neurosciences · doi:10.1007/7854_2014_341 · Cited by 55
“Subsequently, during SWS, sharp-wave ripples participate in the reactivation of neuronal networks that were most recently fired during waking, namely those representing declarative information (Pavlides and Winson 1989; Wilson and McNaughton 1994; Skaggs and McNaughton 1996; Kudrimoti et al. 1999; Nadasdy et al. 1999;…”
BackgroundDetecting neural assemblies in calcium imaging data
Mölter, J., Avitan, L., & Goodhill, G. J. (2018) · BMC Biology · doi:10.1186/s12915-018-0606-4 · Cited by 46
On the methods for reactivation and replay analysis
Tingley, D., & Peyrache, A. (2020) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2019.0231 · Cited by 52
Image sequence reactivation in awake V4 networks
Eagleman, S. L., & Dragoi, V. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1212059109 · Cited by 50
“In those studies, the temporal firing patterns of multiple neurons during learning are repeated either during sleep (9, 43, 44) or in the awake state (25).”
BackgroundResultHasselmo, M. E., Giocomo, L. M., Brandon, M. P., & Yoshida, M. (2009) · Behavioural Brain Research · doi:10.1016/j.bbr.2009.12.010 · Cited by 48
“Hippocampal place cells sequentially activated during waking on a linear track appear to fire with the same sequential relationship during the ripple events in slow wave sleep [122] [154].”
Negrón-Oyarzo, I., Neira, D., Espinosa, N., Fuentealba, P., & Aboitiz, F. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhu108 · Cited by 50
“intervals (Nádasdy et al. 1999) and the cross-correlation procedure was performed on the pseudo-random sequence.”
MethodLewandowski, B. C., Vyssotski, A. L., Hahnloser, R. H. R., & Schmidt, M. F. (2013) · Journal of Physiology-Paris · doi:10.1016/j.jphysparis.2013.04.001 · Cited by 48
“…task also exhibit an increased tendency to fire together during subsequent slow-wave sleep (Wilson and McNaughton, 1994); and spike sequences of pyramidal cells during wheel running are ‘re-played’ during slow-wave sleep, though at a faster timescale than during behavior (Nadasdy et al., 1999).”
Neural Avalanches at the Critical Point between Replay and Non-Replay of Spatiotemporal Patterns
Scarpetta, S., & CANDIA, A. D. (2013) · PLoS ONE · doi:10.1371/journal.pone.0064162 · Cited by 47
“temporal patterns has been observed to occur, both in the cortex and hippocampus, during sleep [16,19,20] and in the awake state [21–24], and it has been hypothesized that this replay may subserve memory consolidation.”
BackgroundCell Assemblies in the Cortico-Hippocampal-Reuniens Network during Slow Oscillations
Angulo‐García, D., Ferraris, M., Ghestem, A., Nallet-Khosrofian, L., Bernard, C., & Quilichini, P. (2020) · Journal of Neuroscience · doi:10.1523/jneurosci.0571-20.2020 · Cited by 49
“In both HPC and mPFC, cell assemblies fire in a fine time-resolved manner (Skaggs and McNaughton, 1996; Nadasdy et al., 1999; Lee and Wilson, 2002; Euston et al., 2007; Luczak et al., 2007; Pastalkova et al., 2008; Peyrache et al., 2009; Battaglia et al., 2011).”
BackgroundSugden, A. U., Zaremba, J. D., Sugden, L. A., McGuire, K. L., Lutas, A., Ramesh, R. N., Alturkistani, O., Lensjø, K. K., Burgess, C. R., & Andermann, M. L. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-0651-5 · Cited by 43
Donoso, J. R., Schmitz, D., Maier, N., & Kempter, R. (2018) · Journal of Neuroscience · doi:10.1523/jneurosci.0188-17.2018 · Cited by 43
“The activity of various cell types is locked to ripple oscillations, but the pace-making mechanisms are unclear, although many in vivo and in vitro studies addressed this question (Ylinen et al., 1995; Draguhn et al., 1998; Nádasdy et al., 1999; Csicsvari et al., 2000; Klausberger et al., 2003, 2005; Maier et al., 200…”
BackgroundProcedural learning and sleep hippocampal low frequencies in humans
Moroni, F., Nobili, L., Curcio, G., Carli, F. D., Tempesta, D., Marzano, C., Gennaro, L. D., Mai, R., Francione, S., Russo, G. L., et al. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.05.027 · Cited by 44
“Consistent with these findings, neuroimaging studies in humans have reported re-activation of the hippocampal and mediotemporal structures during SWS following procedural (Maquet et al., 2000) and declarative (Peigneux et al., 2004) learning, which correlated with performance improvement after sleep (Peigneux et al.,…”
InfluentialCell assemblies, sequences and temporal coding in the hippocampus
Dragoi, G. (2020) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2020.03.003 · Cited by 56
Sleep-Related Spike Bursts in HVC Are Driven by the Nucleus Interface of the Nidopallium
Hahnloser, R. H. R., & Fee, M. S. (2006) · Journal of Neurophysiology · doi:10.1152/jn.00547.2006 · Cited by 42
“With the possibility of existence of off-line learning mechanisms during sleep (Deregnaucourt et al. 2005; Margoliash 2001; Nadasdy et al. 1999), we could imagine that auditory hallucination of the BOS originating in NIf is the driving force of such memory consolidation processes.”
Quaglio, P., Yegenoglu, A., Torre, E., Endres, D., & Grün, S. (2017) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2017.00041 · Cited by 43
“Tools developed in former studies for the analysis of STPs in small populations of neurons (e.g., Prut et al., 1998; Nadasdy et al., 1999) scale poorly with the size of the data and thus cannot be applied to massively parallel spike trains (MPST).”
MethodVisual–Procedural Memory Consolidation during Sleep Blocked by Glutamatergic Receptor Antagonists
Gais, S., Rasch, B., Wagner, U., & Born, J. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.5374-07.2008 · Cited by 47
“This reactivation hypothesis has received considerable support in animal research with regard to the declarative, hippocampal memory system (Wilson and McNaughton, 1994; Nadasdy et al., 1999), but also with regard to other memory systems (Dave and Margoliash, 2000; Ribeiro et al.”
ResultMarshall, L., & Binder, S. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00614 · Cited by 42
“While it is in line with theoretical concepts described above and in Figure 1 that SO-tDCS over the dorso-lateral PFC during SWS in humans enhanced EEG power both in the SO and spindle frequency ranges (Marshall et al., 2006), effects of SO-tDCS during waking are more difficult to reconcile.”
BackgroundInfluentialActive Dendrites and Local Field Potentials: Biophysical Mechanisms and Computational Explorations
Sinha, M., & Narayanan, R. (2021) · Neuroscience · doi:10.1016/j.neuroscience.2021.08.035 · Cited by 44
“During SPW-Rs, spatial memory associated theta sequences, and emotional/social memory correlates have been observed to be reactivated in a time-compressed manner (Nadasdy et al., 1999; Louie and Wilson, 2001; Cei et al., 2014; Girardeau et al., 2017; Oliva et al., 2020).”
De novo inter-regional coactivations of preconfigured local ensembles support memory
Miyawaki, H., & Mizuseki, K. (2022) · Nature Communications · doi:10.1038/s41467-022-28929-x · Cited by 42
“Triple-activation of ensembles across brain region To evaluate simultaneous reactivation across BLA, vCA1 and PL5 ensembles, we expanded CCG analyses for ensemble triplets by using a similar method previously used for spike triplet analyses (Nadasdy et al., 1999).”
MethodHasselmo, M. E. (2008) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2008.06437.x · Cited by 45
“With appropriate increases in replay speed, this circuit could also underlie forward hippocampal replay occurring during slow wave sleep (Skaggs & McNaughton, 1996; Nadasdy et al., 1999) that could drive the replay shown in neocortical structures (Ribeiro et al.”
BackgroundTitiz, A. S., Mahoney, J. M., Testorf, M. E., Holmes, G. L., & Scott, R. C. (2014) · Hippocampus · doi:10.1002/hipo.22297 · Cited by 40
“…in memory performance is the experience-dependent reactivation of place cell activity patterns representative of previous behavior—previously defined as hippocampal replay (Wilson and McNaughton, 1994; Nadasdy et al., 1999; Louie and Wilson, 2001; Lee and Wilson, 2002; Davidson et al., 2009).”
BackgroundMicro-, Meso- and Macro-Dynamics of the Brain
Buzsáki, G., Christen, Y., & Publishing, S. I. (2016) · Research and perspectives in neurosciences · doi:10.1007/978-3-319-28802-4 · Cited by 44
Self-citationNeural Activity Patterns Underlying Spatial Coding in the Hippocampus
Sosa, M., Gillespie, A. K., & Frank, L. M. (2016) · Current topics in behavioral neurosciences · doi:10.1007/7854_2016_462 · Cited by 43
“With improvements in analysis techniques, it became possible to observe the reactivation of more specific neuronal sequences during sleep that recapitulated awake experience (Skaggs and McNaughton 1996; Kudrimoti et al. 1999; Nadasdy et al. 1999; Lee and Wilson 2002).”
BackgroundPicard‐Deland, C., Aumont, T., Samson-Richer, A., Paquette, T., & Nielsen, T. (2021) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2021.107460 · Cited by 43
Computational theories on the function of theta oscillations
Lengyel, M., Huhn, Z., & Érdi, P. (2005) · Biological Cybernetics · doi:10.1007/s00422-005-0567-x · Cited by 42
“Sequences of neural activities recorded in the hippocampus of the awake animal are also replayed during subsequent sleep sessions (Skaggs and McNaughton 1996; Nádasdy et al. 1999; Louie and Wilson 2001; Lee and Wilson 2002), giving further support to sequence learning theories.”
MethodBehavior-Dependent States of the Hippocampal Network Affect Functional Clustering of Neurons
Hirase, H., Leinekugel, X., Csicsvari, J. L., Czurkó, A., & Buzsáki, G. (2001) · Journal of Neuroscience · doi:10.1523/jneurosci.21-10-j0003.2001 · Cited by 40
“Such local clustering may emerge because during sharp waves selective subgroups of CA3 pyramidal cells discharge together preferentially and consistently (Wilson and McNaughton, 1994; Kudrimoti et al., 1999; Nadasdy et al., 1999; Csicsvari et al., 2000).”
BackgroundSelf-citationLearning offline: memory replay in biological and artificial reinforcement learning
Roscow, E. L., Chua, R., Costa, R. P., Jones, M. W., & Lepora, N. (2021) · Trends in Neurosciences · doi:10.1016/j.tins.2021.07.007 · Cited by 36
Neuronal sequences in population bursts encode information in human cortex
Xie, W., Wittig, J. H., Chapeton, J. I., El-Kalliny, M. M., Jackson, S. N., Inati, S. K., & Zaghloul, K. A. (2024) · Nature · doi:10.1038/s41586-024-08075-8 · Cited by 42
“We developed classifiers to decode visual information content based on the sequence of spiking activity within each burst using a template-matching approach 30,59 .”
A neural mechanism for learning from delayed postingestive feedback
Zimmerman, C. A., Bolkan, S. S., Pan-Vazquez, A., Wu, B., Keppler, E., Meares-Garcia, J. B., Guthman, E. M., Fetcho, R. N., McMannon, B., Lee, J., et al. (2025) · Nature · doi:10.1038/s41586-025-08828-z · Cited by 49
STDP Provides the Substrate for Igniting Synfire Chains by Spatiotemporal Input Patterns
Hosaka, R., Araki, O., & Ikeguchi, T. (2007) · Neural Computation · doi:10.1162/neco.2007.11-05-043 · Cited by 39
“brainics@rs.kagu.tus.ac.jp”
The effects of developmental alcohol exposure on the neurobiology of spatial processing
Harvey, R. E., Berkowitz, L. E., Hamilton, D. A., & Clark, B. J. (2019) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.09.018 · Cited by 40
“During slow wave sleep, hippocampal place cell firing sequences observed during recent locomotion will “replay” in a temporally ordered and faster timescale in series of sharp wave bursts (Lee and Wilson, 2002; Nádasdy et al., 1999; Skaggs and McNaughton, 1996; Wilson and McNaughton, 1994).”
BackgroundHellman, K. M., Hernandez, P. J., Park, A., & Abel, T. G. (2010) · SLEEP · doi:10.1093/sleep/33.1.19 · Cited by 37
Attenuated long-term Arc expression in the aged fascia dentata
Marrone, D. F., Satvat, E., Schaner, M. J., Worley, P. F., & Barnes, C. A. (2010) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2010.07.022 · Cited by 38
Bunce, J. G., Sabolek, H. R., & Chrobak, J. J. (2004) · Hippocampus · doi:10.1002/hipo.10200 · Cited by 38
“Foremost, the temporal pattern of spikes among small groups of CA1 neurons during sensory experience reoccur in a compressed time frame during subsequent sharp waves (e.g., Wilson and McNaughton, 1994; Skaggs and McNaughton, 1996; Nadasdy et al., 1999; Hirase et al., 2001; Lee and Wilson, 2002).”
Increasing Explicit Sequence Knowledge by Odor Cueing during Sleep in Men but not Women
Diekelmann, S., Jan Born, A., & Rasch, B. (2016) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2016.00074 · Cited by 39
“During subsequent sleep, half of the subjects were re-exposed to the odor during periods of slow wave sleep (SWS), while the other half received odorless vehicle.”
BackgroundTadavarty, R., Kaan, T. K. Y., & Sastry, B. R. (2008) · Experimental Neurology · doi:10.1016/j.expneurol.2008.11.012 · Cited by 37
“Single and en masse network recordings from these cells reveal that the firing pattern as well as temporal order is played back on a faster time scale (Nadasdy et al., 1999) during rapid-eye movement (REM) and slow wave sleep (SWS) (Poe et al.”
Construction and disruption of spatial memory networks during developmentPreprint
Baram, T. Z., Donato, F., & Holmes, G. L. (2019) · Learning & Memory · doi:10.1101/lm.049239.118 · Cited by 38
Lee, A. K., & Wilson, M. A. (2004) · Journal of Neurophysiology · doi:10.1152/jn.01030.2003 · Cited by 40
“A previous study of exact time interval patterns in hippocampal data used even larger bins and found many repeating patterns, but did not focus on patterns with Ն4 distinct cells (Nádasdy et al. 1999).”
Replay-triggered brain-wide activation in humans
Huang, Q., Xiao, Z., Yu, Q., Luo, Y., Xu, J., Qu, Y., Dolan, R. J., Behrens, T. E. J., & Liu, Y. (2024) · Nature Communications · doi:10.1038/s41467-024-51582-5 · Cited by 45
“…point at which the regression slope crossed y =0 in the forward mental simulation in the positive tonegative direction (e.g., junction = 5.2 TR), with the 1 st period preceding the junction (e.g., 1 st period = [1, 2, 3, 4, 5] TR) and the 2 nd period following it (e.g., 2 nd period = [6, 7, 8] TR).”
InfluentialExperience and sleep-dependent synaptic plasticity: from structure to activity
Sun, L., Zhou, H., Cichon, J., & Yang, G. (2020) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2019.0234 · Cited by 39
Consolidation of temporal order in episodic memories
Griessenberger, H., Hoedlmoser, K., Heib, D. P. J., Lechinger, J., Klimesch, W., & Schabus, M. (2012) · Biological Psychology · doi:10.1016/j.biopsycho.2012.05.012 · Cited by 39
“This idea of complementary functions of SWS and REM sleep for successful memory consolidation was revived by Diekelmann and Born (2010) who suggested an essential role of SWS for system consolidation which is complemented by synaptic consolidation taking place during REM sleep.”
InfluentialInterictal network dysfunction and cognitive impairment in epilepsy
Gelinas, J. N., & Khodagholy, D. (2025) · Nature reviews. Neuroscience · doi:10.1038/s41583-025-00924-3 · Cited by 37
“The spike content of SPW-Rs is organized and sequential, and critically it consists of a temporally compressed version of firing patterns that occur during waking experience 153–155 .”
Potential factors influencing replay across CA1 during sharp-wave ripples
de la Prida, L. M. (2020) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2019.0236 · Cited by 35
Firing rate modulation: A simple statistical view of memory trace reactivation
Battaglia, F. P., Sutherland, G. R., Cowen, S. L., Naughton, B. L. M., & Harris, K. D. (2005) · Neural Networks · doi:10.1016/j.neunet.2005.08.011 · Cited by 35
Generation and Selection of Surrogate Methods for Correlation Analysis
Louis, S., Borgelt, C., & Grün, S. (2010) · Springer eBooks · doi:10.1007/978-1-4419-5675-0_17 · Cited by 34
“ISI shuffling within and across trials (Nádasdy et al. 1999; Masuda and Aihara 2003; Ikegaya et al. 2004), for example, will have similar effects as spike time randomization and trial shuffling respectively, the former flattening the rate profile to a stationary one, and the latter ignoring cross-trial nonstationariti…”
BackgroundMethodInfluentialPropagating synchrony in feed-forward networks
Jahnke, S., Memmesheimer, R.-M., & Timme, M. (2013) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2013.00153 · Cited by 34
“…by: Tatjana Tchumatchenko, Max Planck Institute for Brain Research, Germany Reviewed by: Robert Rosenbaum, University of Pittsburgh, USA Arvind Kumar, University of Freiburg, Germany Raul C. Muresan, Romanian Institute of Science and Tehnology, Romania *Correspondence: Sven Jahnke,…”
BackgroundAllocentric representations of space in the hippocampus
Danjo, T. (2019) · Neuroscience Research · doi:10.1016/j.neures.2019.06.002 · Cited by 34
SASTRY, P. S., & Unnikrishnan, K. P. (2009) · Neural Computation · doi:10.1162/neco.2009.12-08-928 · Cited by 32
Learning Beyond Finite Memory in Recurrent Networks of Spiking Neurons
Peter Tiňo, B., & Mills, A. J. S. (2006) · Neural Computation · doi:10.1162/089976606775623360 · Cited by 34
Input Prediction and Autonomous Movement Analysis in Recurrent Circuits of Spikitfg Neurons
Legenstein, R. A., Markram, Η., & Maass, W. (2003) · Reviews in the Neurosciences · doi:10.1515/revneuro.2003.14.1-2.5 · Cited by 36
Memory processing in great apes: the effect of time and sleep
Martín-Ordás, G., & Call, J. (2011) · Biology Letters · doi:10.1098/rsbl.2011.0437 · Cited by 34
ASSET: Analysis of Sequences of Synchronous Events in Massively Parallel Spike Trains
Torre, E., Canova, C., Denker, M., Gerstein, G. L., Helias, M., & Grün, S. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004939 · Cited by 33
“Spatio-temporal patterns in a more general sense (with different time intervals between spikes) were suggested as signatures of synfire chain activity in data of low numbers of simultaneously recorded neurons [40, 46, 47].”
BackgroundMidline thalamic neurons are differentially engaged during hippocampus network oscillations
Lara-Vásquez, A., Espinosa, N., Durán, E., Stockle, M., & Fuentealba, P. (2016) · Scientific Reports · doi:10.1038/srep29807 · Cited by 37
Hwaun, E., & Colgin, L. L. (2019) · Hippocampus · doi:10.1002/hipo.23090 · Cited by 35
Time as the fourth dimension in the hippocampus
Banquet, J. P., Gaussier, P., Cuperlier, N., Hok, V., Save, É., Poucet, B., Quoy, M., & Wiener, S. I. (2020) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2020.101920 · Cited by 33
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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