Hippocampal Replay Captures the Unique Topological Structure of a Novel Environment
Open accessAbstract
Hippocampal place-cell replay has been proposed as a fundamental mechanism of learning and memory, which might support navigational learning and planning. An important hypothesis of relevance to these proposed functions is that the information encoded in replay should reflect the topological structure of experienced environments; that is, which places in the environment are connected with which others. Here we report several attributes of replay observed in rats exploring a novel forked environment that support the hypothesis. First, we observed that overlapping replays depicting divergent trajectories through the fork recruited the same population of cells with the same firing rates to represent the common portion of the trajectories. Second, replay tended to be directional and to flip the represented direction at the fork. Third, replay-associated sharp-wave–ripple events in the local field potential exhibited substructure that mapped onto the maze topology. Thus, the spatial complexity of our recording environment was accurately captured by replay: the underlying neuronal activities reflected the bifurcating shape, and both directionality and associated ripple structure reflected the segmentation of the maze. Finally, we observed that replays occurred rapidly after small numbers of experiences. Our results suggest that hippocampal replay captures learned information about environmental topology to support a role in navigation.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Repeated replay or rehearsal of assemblies that encode recent experiences does occur.
“as does repeated replay or rehearsal of assemblies that encode recent experiences108,109.”
From The right time to learn: Mechanisms and optimization of spaced learning (2016) · cites this paper as [109]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
(1978) · UA Campus Repository (The University of Arizona) · Cited by 8,010 · see citing works
LOSS OF RECENT MEMORY AFTER BILATERAL HIPPOCAMPAL LESIONS
Scoville, W. B., & Milner, B. (1957) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp.20.1.11 · Cited by 7,322 · see citing works
Cognitive maps in rats and men
Tolman, E. C. (1948) · Psychological Review · doi:10.1037/h0061626 · Cited by 6,641 · see citing works
The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat
O'Keefe, J., & Dostrovsky, J. (1971) · Brain Research · doi:10.1016/0006-8993(71)90358-1 · Cited by 6,151 · see citing works
Reactivation of hippocampal ensemble memories during sleep
Wilson, M. A., & McNaughton, B. L. (1994) · Science · doi:10.1126/science.8036517 · Cited by 3,118 · see citing works
Synaptic Plasticity and Memory: An Evaluation of the Hypothesis
Martin, S. J., Grimwood, P. D., & Morris, R. G. M. (2000) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.23.1.649 · Cited by 2,794 · see citing works
Gallistel, C. R. (1990) · Cited by 2,571 · see citing works
A framework for mesencephalic dopamine systems based on predictive Hebbian learning
Montague, P., Dayan, P., & Sejnowski, T. (1996) · The Journal of Neuroscience · doi:10.1523/jneurosci.16-05-01936.1996 · Cited by 2,066 · see citing works
Remembrance of places passed: Spatial memory in rats.
Olton, D. S., & Samuelson, R. J. (1976) · Journal of Experimental Psychology Animal Behavior Processes · doi:10.1037/0097-7403.2.2.97 · Cited by 1,934 · see citing works
The cognitive neuroscience of constructive memory: remembering the past and imagining the future
Schacter, D. L., & Addis, D. R. (2007) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2007.2087 · Cited by 1,836 · see citing works
Reverse replay of behavioural sequences in hippocampal place cells during the awake state
Foster, D. J., & Wilson, M. A. (2006) · Nature · doi:10.1038/nature04587 · Cited by 1,727 · see citing works
Self-citationTwo-stage model of memory trace formation: A role for “noisy” brain states
Buzsáki, G. (1989) · Neuroscience · doi:10.1016/0306-4522(89)90423-5 · Cited by 1,709 · see citing works
Coordinated memory replay in the visual cortex and hippocampus during sleep
Ji, D., & Wilson, M. A. (2007) · Nature Neuroscience · doi:10.1038/nn1825 · Cited by 1,669 · see citing works
Selective suppression of hippocampal ripples impairs spatial memory
Girardeau, G., Benchenane, K., Wiener, S. I., Buzsáki, G., & Zugaro, M. B. (2009) · Nature Neuroscience · doi:10.1038/nn.2384 · Cited by 1,560 · see citing works
Memory of sequential experience in the hippocampus during slow wave sleep
Lee, A. K., & Wilson, M. A. (2002) · Neuron · doi:10.1016/s0896-6273(02)01096-6 · Cited by 1,296 · see citing works
Hippocampal place-cell sequences depict future paths to remembered goals
Pfeiffer, B. E., & Foster, D. J. (2013) · Nature · doi:10.1038/nature12112 · Cited by 1,216 · see citing works
Self-citationForward and reverse hippocampal place-cell sequences during ripples
Diba, K., & Buzsáki, G. (2007) · Nature Neuroscience · doi:10.1038/nn1961 · Cited by 1,205 · see citing works
Temporally structured replay of awake hippocampal ensemble activity during rapid eye movement sleep
Louie, K., & Wilson, M. A. (2001) · Neuron · doi:10.1016/s0896-6273(01)00186-6 · Cited by 1,148 · see citing works
Requirement for Hippocampal CA3 NMDA Receptors in Associative Memory Recall
Nakazawa, K., Quirk, M. C., Chitwood, R. A., Watanabe, M., Yeckel, M. F., Sun, L. D., Kato, A., Carr, C. A., Johnston, D., Wilson, M. A., et al. (2002) · Science · doi:10.1126/science.1071795 · Cited by 1,090 · see citing works
Hippocampal replay in the awake state: a potential substrate for memory consolidation and retrieval
Carr, M. F., Jadhav, S. P., & Frank, L. M. (2011) · Nature Neuroscience · doi:10.1038/nn.2732 · Cited by 958 · see citing works
Awake hippocampal sharp-wave ripples support spatial memory
Jadhav, S. P., Kemere, C., German, P. W., & Frank, L. M. (2012) · Science · doi:10.1126/science.1217230 · Cited by 924 · see citing works
Disruption of ripple‐associated hippocampal activity during rest impairs spatial learning in the rat
Ego‐Stengel, V., & Wilson, M. A. (2010) · Hippocampus · doi:10.1002/hipo.20707 · Cited by 842 · see citing works
Hippocampal replay of extended experience
Davidson, T. J., Kloosterman, F., & Wilson, M. A. (2009) · Neuron · doi:10.1016/j.neuron.2009.07.027 · Cited by 806 · cited 13× · see citing works
“Directional place fields were calculated and were used to compute joint posterior probabilities over both position and direction (Davidson et al., 2009), for the already identified replays.”
BackgroundMethodInfluentialAwake replay of remote experiences in the hippocampus
Karlsson, M. P., & Frank, L. M. (2009) · Nature Neuroscience · doi:10.1038/nn.2344 · Cited by 769 · cited 4× · see citing works
“It is now well established that hippocampal place cells engage in extended spiking sequences across neuronal ensembles that match sequences from previous behavioral episodes, often in a temporally condensed form during 100 –200 ms sharp-wave–ripple (SWR) events in the hippocampal local field potential (LFP; Louie and…”
BackgroundInfluentialHippocampal replay is not a simple function of experience
Gupta, A. S., van der Meer, M. A. A., Touretzky, D. S., & Redish, A. D. (2010) · Neuron · doi:10.1016/j.neuron.2010.01.034 · Cited by 733 · see citing works
Trajectory Encoding in the Hippocampus and Entorhinal Cortex
Frank, L. M., Brown, E. N., & Wilson, M. A. (2000) · Neuron · doi:10.1016/s0896-6273(00)00018-0 · Cited by 731 · see citing works
The global record of memory in hippocampal neuronal activity
Wood, E. R., Dudchenko, P. A., & Eichenbaum, H. (1999) · Nature · doi:10.1038/17605 · Cited by 707 · see citing works
Gaffan, D. (1994) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.1994.6.4.305 · Cited by 484 · see citing works
Play it again: reactivation of waking experience and memory
O’Neill, J., Pleydell-Bouverie, B., Dupret, D., & Csicsvari, J. L. (2010) · Trends in Neurosciences · doi:10.1016/j.tins.2010.01.006 · Cited by 448 · see citing works
The Role of the Hippocampus in Prediction and Imagination
Buckner, R. L. (2010) · Annual Review of Psychology · doi:10.1146/annurev.psych.60.110707.163508 · Cited by 419 · see citing works
Rewarded Outcomes Enhance Reactivation of Experience in the Hippocampus
Singer, A. C., & Frank, L. M. (2009) · Neuron · doi:10.1016/j.neuron.2009.11.016 · Cited by 385 · see citing works
Jensen, O., & Lisman, J. E. (1996) · Learning & Memory · doi:10.1101/lm.3.2-3.279 · Cited by 383 · see citing works
Morris, R. (2001) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2001.0945 · Cited by 221 · see citing works
Csicsvari, J. L., O'Neill, J., Allen, K. L., & Senior, T. J. (2007) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2007.05684.x · Cited by 145 · see citing works
Sequence learning and the role of the hippocampus in rodent navigation
Foster, D. J., & Knierim, J. J. (2012) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2011.12.005 · Cited by 124 · see citing works
Self-citationSharp, P. E., Blair, H. T., & Brown, M. A., Sr. (1996) · Hippocampus · doi:10.1002/(sici)1098-1063(1996)6:6 · Cited by 64 · see citing works
Memory 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 · see citing works
Molter, C., Sato, N., & Yamaguchi, Y. (2007) · Hippocampus · doi:10.1002/hipo.20258 · Cited by 42 · see citing works
Koene, R. A., & Hasselmo, M. E. (2008) · Neural Networks · doi:10.1016/j.neunet.2007.12.029 · Cited by 30 · see citing works
Flagged first, then by citations
1 of the 41 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Hippocampal sharp wave-ripple: A cognitive biomarker for episodic memory and planning
Buzsáki, G. (2015) · Hippocampus · doi:10.1002/hipo.22488 · Cited by 1,759 · see citing works
The cognitive map in humans: spatial navigation and beyond
Epstein, R. A., Patai, E. Z., Julian, J. B., & Spiers, H. J. (2017) · Nature Neuroscience · doi:10.1038/nn.4656 · Cited by 921 · see citing works
What Learning Systems do Intelligent Agents Need? Complementary Learning Systems Theory Updated
Kumaran, D., Hassabis, D., & McClelland, J. L. (2016) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2016.05.004 · Cited by 736 · see citing works
Josselyn, S. A., Köhler, S., & Frankland, P. W. (2015) · Nature reviews. Neuroscience · doi:10.1038/nrn4000 · Cited by 687 · see citing works
Rhythms of the hippocampal network
Colgin, L. L. (2016) · Nature reviews. Neuroscience · doi:10.1038/nrn.2016.21 · Cited by 654 · see citing works
The hippocampal sharp wave-ripple in memory retrieval for immediate use and consolidation
Joo, H. R., & Frank, L. M. (2018) · Nature Reviews Neuroscience · doi:10.1038/s41583-018-0077-1 · Cited by 430 · see citing works
Diversity in neural firing dynamics supports both rigid and learned hippocampal sequences
Grosmark, A. D., & Buzsáki, G. (2016) · Science · doi:10.1126/science.aad1935 · Cited by 367 · see citing works
Foster, D. J. (2017) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-072116-031538 · Cited by 375 · see citing works
Self-citationThe successor representation in human reinforcement learning
Momennejad, I., Russek, E. M., Cheong, J. H., Botvinick, M., Daw, N. D., & Gershman, S. J. (2017) · Nature Human Behaviour · doi:10.1038/s41562-017-0180-8 · Cited by 384 · see citing works
Buzsáki, G. (2019) · doi:10.1093/oso/9780190905385.001.0001 · Cited by 358 · see citing works
The right time to learn: Mechanisms and optimization of spaced learning
Smolen, P., Zhang, Y., & Byrne, J. H. (2016) · Nature Reviews Neuroscience · doi:10.1038/nrn.2015.18 · Cited by 326 · see citing works
Constant Sub-second Cycling between Representations of Possible Futures in the Hippocampus
Kay, K., Chung, J. E., Sosa, M., Schor, J. S., Karlsson, M. P., Larkin, M. C., Liu, D. F., & Frank, L. M. (2020) · Cell · doi:10.1016/j.cell.2020.01.014 · Cited by 296 · see citing works
Reverse replay of hippocampal place cells is uniquely modulated by changing reward
Ambrose, R. E., Pfeiffer, B. E., & Foster, D. J. (2016) · Neuron · doi:10.1016/j.neuron.2016.07.047 · Cited by 292 · see citing works
Self-citationStructuring knowledge with cognitive maps and cognitive graphs
Peer, M., Brunec, I. K., Newcombe, N. S., & Epstein, R. A. (2021) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2020.10.004 · Cited by 283 · see citing works
Hippocampal and prefrontal processing of network topology to simulate the future
Javadi, A.-H., Emo, B., Howard, L. R., Zisch, F. E., Yu, Y., Knight, R., Pinelo Silva, J., & Spiers, H. J. (2017) · Nature Communications · doi:10.1038/ncomms14652 · Cited by 207 · see citing works
Hippocampal replay reflects specific past experiences rather than a plan for subsequent choice
Gillespie, A. K., Maya, D. A., Denovellis, E. L., Liu, D. F., Kastner, D. B., Coulter, M. E., Roumis, D. K., Eden, U. T., & Frank, L. M. (2021) · Neuron · doi:10.1016/j.neuron.2021.07.029 · Cited by 192 · see citing works
Trajectory events across hippocampal place cells require previous experience
Silva, D., Feng, T., & Foster, D. J. (2015) · Nature Neuroscience · doi:10.1038/nn.4151 · Cited by 183 · see citing works
Self-citationMemory trace replay: The shaping of memory consolidation by neuromodulation
Atherton, L. A., Dupret, D., & Mellor, J. R. (2015) · Trends in Neurosciences · doi:10.1016/j.tins.2015.07.004 · Cited by 180 · see citing works
Neuronal Computation Underlying Inferential Reasoning in Humans and Mice
Barron, H. C., Reeve, H. M., Koolschijn, R. S., Perestenko, P. V., Shpektor, A., Nili, H., Rothaermel, R., Campo-Urriza, N., O’Reilly, J. X., Bannerman, D. M., et al. (2020) · Cell · doi:10.1016/j.cell.2020.08.035 · Cited by 179 · see citing works
The content of hippocampal “replay”
Pfeiffer, B. E. (2017) · Hippocampus · doi:10.1002/hipo.22824 · Cited by 172 · see citing works
The Neurobiology of Mammalian Navigation
Poulter, S. L., Hartley, T., & Lever, C. (2018) · Current Biology · doi:10.1016/j.cub.2018.05.050 · Cited by 171 · see citing works
Learning structures: Predictive representations, replay, and generalization
Momennejad, I. (2020) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2020.02.017 · Cited by 159 · see citing works
Integrating memories to guide decisions
Daphna Shohamy, A., & Daw, N. D. (2015) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2015.08.010 · Cited by 141 · see citing works
Spatiotemporal patterns of neocortical activity around hippocampal sharp-wave ripples
Abadchi, J. K., Nazari-Ahangarkolaee, M., Gattas, S., Bermudez-Contreras, E. J., Luczak, A., McNaughton, B. L., & Mohajerani, M. H. (2020) · eLife · doi:10.7554/elife.51972 · Cited by 124 · see citing works
Offline replay supports planning in human reinforcement learning
Momennejad, I., Otto, A. R., Daw, N. D., & Norman, K. A. (2018) · eLife · doi:10.7554/elife.32548 · Cited by 133 · see citing works
Valero, M., Averkin, R. G., Fernández‐Lamo, I., Aguilar, J., Lopez‐Pigozzi, D., Brotons‐Mas, J. R., Cid, E., Tamás, G., & de la Prida, L. M. (2017) · Neuron · doi:10.1016/j.neuron.2017.05.032 · Cited by 126 · see citing works
Predictive Representations in Hippocampal and Prefrontal Hierarchies
Brunec, I. K., & Momennejad, I. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.1327-21.2021 · Cited by 116 · see citing works
Hippocampal reactivation of random trajectories resembling brownian diffusion
Stella, F., Baracskay, P., O’Neill, J., & Csicsvari, J. (2019) · Neuron · doi:10.1016/j.neuron.2019.01.052 · Cited by 107 · see citing works
Hippocampo-cortical circuits for selective memory encoding, routing, and replay
Harvey, R. E., Robinson, H. L., Liu, C., Oliva, A., & Fernandez-Ruiz, A. (2023) · Neuron · doi:10.1016/j.neuron.2023.04.015 · Cited by 101 · see citing works
Internally generated hippocampal sequences as a vantage point to probe future‐oriented cognition
Pezzulo, G., Kemere, C. T., & van der Meer, M. A. A. (2017) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.13329 · Cited by 93 · see citing works
Hippocampal replay of experience at real-world speeds
Denovellis, E. L., Gillespie, A. K., Coulter, M. E., Sosa, M., Chung, J. E., Eden, U. T., & Frank, L. M. (2021) · eLife · doi:10.7554/elife.64505 · Cited by 89 · see citing works
Differential roles of sleep spindles and sleep slow oscillations in memory consolidation
Wei, Y., Krishnan, G. P., Komarov, M., & Bazhenov, M. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006322 · Cited by 92 · see citing works
Imagination as a fundamental function of the hippocampus
Comrie, A. E., Frank, L. M., & Kay, K. (2022) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2021.0336 · Cited by 84 · see citing works
Reactivation predicts the consolidation of unbiased long-term cognitive maps
Grosmark, A. D., Sparks, F. T., Davis, M. J., & Losonczy, A. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00920-7 · Cited by 71 · see citing works
Specific hippocampal representations are linked to generalized cortical representations in memory
Yu, J. Y., Liu, D. F., Loback, A., Grossrubatscher, I., & Frank, L. M. (2018) · Nature Communications · doi:10.1038/s41467-018-04498-w · Cited by 71 · see citing works
Prioritized experience replays on a hippocampal predictive map for learning
Igata, H., Ikegaya, Y., & Sasaki, T. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2011266118 · Cited by 75 · see citing works
Routing of Hippocampal Ripples to Subcortical Structures via the Lateral Septum
Tingley, D., & Buzsáki, G. (2019) · Neuron · doi:10.1016/j.neuron.2019.10.012 · Cited by 71 · see citing works
Three brain states in the hippocampus and cortex
Kay, K., & Frank, L. M. (2018) · Hippocampus · doi:10.1002/hipo.22956 · Cited by 63 · see citing works
The evolving view of replay and its functions in wake and sleep
Findlay, G., Tononi, G., & Cirelli, C. (2020) · SLEEP Advances · doi:10.1093/sleepadvances/zpab002 · Cited by 61 · see citing works
Predicting the past, remembering the future
Gershman, S. J. (2017) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2017.05.025 · Cited by 57 · see citing works
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 57 · see citing works
Self-citationBerners-Lee, A., Wu, X., & Foster, D. J. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.1158-20.2021 · Cited by 56 · see citing works
Self-citationHow our understanding of memory replay evolves
Chen, Z. S., & Wilson, M. A. (2023) · Journal of Neurophysiology · doi:10.1152/jn.00454.2022 · Cited by 65 · see citing works
Smolen, P., Baxter, D. A., & Byrne, J. H. (2019) · Learning & Memory · doi:10.1101/lm.049395.119 · Cited by 53 · see citing works
Wiegand, J. L., Gray, D. T., Schimanski, L. A., Lipa, P., Barnes, C. A., & Cowen, S. L. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.3069-15.2016 · Cited by 50 · see citing works
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 45 · see citing works
Hippocampal place cells encode global location but not connectivity in a complex space
Duvelle, É., Grieves, R. M., Liu, A., Jedidi-Ayoub, S., Holeniewska, J., Harris, A., Nyberg, N., Donnarumma, F., Lefort, J. M., Jeffery, K. J., et al. (2021) · Current Biology · doi:10.1016/j.cub.2021.01.005 · Cited by 48 · see citing works
Yu, J. Y., Kay, K., Liu, D. F., Grossrubatscher, I., Loback, A., Sosa, M., Chung, J. E., Karlsson, M. P., Larkin, M. C., & Frank, L. M. (2017) · eLife · doi:10.7554/elife.27621 · Cited by 48 · see citing works
Recurrent network model for learning goal-directed sequences through reverse replay
Haga, T., & Fukai, T. (2018) · eLife · doi:10.7554/elife.34171 · Cited by 43 · see citing works
Circuit mechanisms of hippocampal reactivation during sleep
Malerba, P., & Bazhenov, M. (2018) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2018.04.018 · Cited by 25 · see citing works
The Hippocampus and Memory Integration: Building Knowledge to Navigate Future Decisions
Schlichting, M. L., & Preston, A. R. (2017) · Springer eBooks · doi:10.1007/978-3-319-50406-3_13 · Cited by 42 · see citing works
Neural 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 39 · see citing works
Hippocampal replays under the scrutiny of reinforcement learning models
Cazé, R. D., Khamassi, M., Aubin, L., & Girard, B. (2018) · Journal of Neurophysiology · doi:10.1152/jn.00145.2018 · Cited by 38 · see citing works
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 36 · see citing works
Rapid classification of hippocampal replay content for real-time applications
Deng, X., Liu, D. F., Karlsson, M. P., Frank, L. M., & Eden, U. T. (2016) · Journal of Neurophysiology · doi:10.1152/jn.00151.2016 · Cited by 32 · see citing works
Differential replay of reward and punishment paths predicts approach and avoidance
McFadyen, J., Liu, Y., & Dolan, R. J. (2023) · Nature Neuroscience · doi:10.1038/s41593-023-01287-7 · Cited by 34 · see citing works
Distinct effects of reward and navigation history on hippocampal forward and reverse replays
Bhattarai, B., Lee, J. W., & Jung, M. W. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1912533117 · Cited by 33 · see citing works
A map of spatial navigation for neuroscience
Parra-Barrero, E., Vijayabaskaran, S., Seabrook, E., Wiskott, L., & Cheng, S. (2023) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2023.105200 · Cited by 31 · see citing works
Interictal epileptiform discharges affect memory in an Alzheimer’s disease mouse model
Soula, M., Maslarova, A., Harvey, R. E., Valero, M., Brandner, S., Hamer, H. M., Fernández‐Ruiz, A., & Buzsáki, G. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2302676120 · Cited by 31 · see citing works
Ciliberti, D., Michon, F., & Kloosterman, F. (2018) · eLife · doi:10.7554/elife.36275 · Cited by 31 · see citing works
Incidence and prevalence of inflammatory bowel disease in Devon, UK
Hamilton, B., Green, H., Heerasing, N. M., Hendy, P. J., Moore, L., Chanchlani, N., Walker, G., Bewshea, C., Kennedy, N. A., Ahmad, T., et al. (2020) · Frontline Gastroenterology · doi:10.1136/flgastro-2019-101369 · Cited by 31 · see citing works
Theodoni, P., Rovira, B., Wang, Y., & Roxin, A. (2018) · eLife · doi:10.7554/elife.37388 · Cited by 31 · see citing works
Topological Schemas of Cognitive Maps and Spatial Learning
Babichev, A., Cheng, S., & Dabaghian, Y. A. (2016) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2016.00018 · Cited by 27 · see citing works
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 28 · see citing works
Replay as wavefronts and theta sequences as bump oscillations in a grid cell attractor network
Kang, L., & DeWeese, M. R. (2019) · eLife · doi:10.7554/elife.46351 · Cited by 24 · see citing works
Observational learning promotes hippocampal remote awake replay toward future reward locations
Mou, X., Pokhrel, A., Suresh, P., & Ji, D. (2021) · Neuron · doi:10.1016/j.neuron.2021.12.005 · Cited by 25 · see citing works
Offline memory replay in recurrent neuronal networks emerges from constraints on online dynamics
Milstein, A. D., Tran, S., Ng, G. Y., & Soltész, I. (2022) · The Journal of Physiology · doi:10.1113/jp283216 · Cited by 22 · see citing works
Multiple-Timescale Representations of Space: Linking Memory to Navigation
Tang, W., & Jadhav, S. P. (2021) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-111020-084824 · Cited by 22 · see citing works
Fernandez, C., Jiang, J., Wang, S.-F., Choi, H. L., & Wagner, A. D. (2023) · eLife · doi:10.7554/elife.80281 · Cited by 20 · see citing works
Diekmann, N., & Cheng, S. (2023) · eLife · doi:10.7554/elife.82301 · Cited by 23 · see citing works
Neuronal ‘Ensemble’ Recording and the Search for the Cell Assembly: A Personal History
McNaughton, B. L. (2024) · Hippocampus · doi:10.1002/hipo.23669 · Cited by 22 · see citing works
Multiple forms of metaplasticity at a single hippocampal synapse during late postnatal development
McHail, D. G., & Dumas, T. C. (2015) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2015.01.009 · Cited by 20 · see citing works
Does the Hippocampus Map Out the Future?
Bendor, D., & Spiers, H. J. (2016) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2016.01.003 · Cited by 20 · see citing works
Through synapses to spatial memory maps via a topological model
Dabaghian, Y. A. (2019) · Scientific Reports · doi:10.1038/s41598-018-36807-0 · Cited by 19 · see citing works
The mosaic structure of the mammalian cognitive map
Jeffery, K. J. (2024) · Learning & Behavior · doi:10.3758/s13420-023-00618-9 · Cited by 21 · see citing works
Feliciano‐Ramos, P. A., Galazo, M. J., Penagos, H., & Wilson, M. A. (2023) · Learning & Memory · doi:10.1101/lm.053834.123 · Cited by 19 · see citing works
Awake hippocampal synchronous events are incorporated into offline neuronal reactivation
Yagi, S., Igata, H., Ikegaya, Y., & Sasaki, T. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112871 · Cited by 18 · see citing works
Robust spatial memory maps encoded by networks with transient connections
Babichev, A., Morozov, D., & Dabaghian, Y. A. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006433 · Cited by 15 · see citing works
Gamma Synchronization Influences Map Formation Time in a Topological Model of Spatial Learning
Basso, E., Arai, M., & Dabaghian, Y. A. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005114 · Cited by 17 · see citing works
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 · see citing works
Replay and representation dynamics in the hippocampus of freely flying bats
Forli, A., Fan, W., Qi, K. K., & Yartsev, M. M. (2025) · Nature · doi:10.1038/s41586-025-09341-z · Cited by 16 · see citing works
Sleep 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 16 · see citing works
Hippocampal Mechanisms for the Segmentation of Space by Goals and Boundaries
McKenzie, S., & Buzsáki, G. (2016) · Research and perspectives in neurosciences · doi:10.1007/978-3-319-28802-4_1 · Cited by 15 · see citing works
Topological Schemas of Memory Spaces
Babichev, A., & Dabaghian, Y. A. (2018) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2018.00027 · Cited by 16 · see citing works
Gardner, R. S., Suarez, D. F., Robinson-Burton, N. K., Rudnicky, C. J., Gulati, A., Ascoli, G. A., & Dumas, T. C. (2016) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2016.03.008 · Cited by 16 · see citing works
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 16 · see citing works
A model of topological mapping of space in bat hippocampus
Hoffman, K., Babichev, A., & Dabaghian, Y. A. (2016) · Hippocampus · doi:10.1002/hipo.22610 · Cited by 15 · see citing works
Pietras, B., Schmutz, V., & Schwalger, T. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010809 · Cited by 15 · see citing works
Trompoukis, G., Rigas, P., Leontiadis, L. J., & Papatheodoropoulos, C. (2020) · Molecular and Cellular Neuroscience · doi:10.1016/j.mcn.2020.103531 · Cited by 13 · see citing works
Pu, Y., Cornwell, B. R., Cheyne, D., & Johnson, B. W. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.05.029 · Cited by 14 · see citing works
Activity-dependent Organization of Topographic Neural Circuits
Cline, H. T., Lau, M., & Hiramoto, M. (2022) · Neuroscience · doi:10.1016/j.neuroscience.2022.11.032 · Cited by 12 · see citing works
A Bio-Inspired Goal-Directed Visual Navigation Model for Aerial Mobile Robots
Mao, J., Hu, X., Zhang, L., He, X., & Milford, M. J. (2020) · Journal of Intelligent & Robotic Systems · doi:10.1007/s10846-020-01190-4 · Cited by 12 · see citing works
Sleep targets highly connected global and local nodes to aid consolidation of learned graph networks
Feld, G. B., Bernard, M., Rawson, A. B., & Spiers, H. J. (2022) · Scientific Reports · doi:10.1038/s41598-022-17747-2 · Cited by 13 · see citing works
Spatial localization of hippocampal replay requires dopamine signalingPreprint
Kleinman, M. R., & Foster, D. J. (2024) · eLife · doi:10.7554/elife.99678 · Cited by 13 · see citing works
Self-citationJeong, H., Namboodiri, V. M. K., Jung, M. W., & Andermann, M. L. (2023) · Current Biology · doi:10.1016/j.cub.2023.10.073 · Cited by 11 · see citing works
Replay without sharp wave ripples in a spatial memory task
Widloski, J., & Foster, D. J. (2025) · Nature Communications · doi:10.1038/s41467-025-65181-5 · Cited by 17 · see citing works
Self-citationGauge Fields in the Central Nervous System
Tozzi, A., Sengupta, B., Peters, J. F., & Friston, K. J. (2017) · Springer series in cognitive and neural systems · doi:10.1007/978-3-319-29674-6_9 · Cited by 12 · see citing works
Sutton, N. M., & Ascoli, G. A. (2021) · Cognitive Systems Research · doi:10.1016/j.cogsys.2021.07.008 · Cited by 12 · see citing works
Hippocampal and Prefrontal Processing of Network Topology to Simulate the Future
(2017) · Conscious Cities Anthology · doi:10.33797/cca17.01.12 · Cited by 12 · see citing works
Methods for Assessment of Memory Reactivation
Liu, S., Grosmark, A., & Chen, Z. S. (2018) · Neural Computation · doi:10.1162/neco_a_01090 · Cited by 12 · see citing works
- Authors
- Wu, X., & Foster, D. J.
- Affiliations
- Johns Hopkins University (US)
- ORCID
- Foster, David J.
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2014-05-07
- Volume
- 34
- Issue
- 19
- Pages
- 6459-6469
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC4012305
- OpenAlex
- W2002978960
- Cited by
- 201
- References
- 41
- Citations by year
- 2026: 9 · 2025: 17 · 2024: 17 · 2023: 16 · 2022: 10 · 2021: 18 · 2020: 18 · 2019: 26 · 2018: 23 · 2017: 18 · 2016: 21 · 2015: 7 · 2014: 1
- FWCI
- 8.74
- 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
- Alfred P. Sloan Foundation
- Whitehall Foundation
- National Institutes of Health
- National Institute of Mental Health (R01MH085823)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Developmental Neuroscience › Neurogenesis and neuroplasticity mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- hippocampal replay, place cells, maze navigation, sharp-wave ripples, local field potentials, novel environment, spatial memory
- MeSH terms
- Algorithms, Animals, Environment, Evoked Potentials, Hippocampus, Learning, Male, Neural Pathways, Neurons, Reward, Spatial Behavior, Linear Models, Maze Learning, Rats, Long-Evans, Rats, Electrophysiological Phenomena
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
