The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
Hippocampal place-cell sequences depict future paths to remembered goals
Open accessAbstract
Effective navigation requires planning extended routes to remembered goal locations. Hippocampal place cells have been proposed to have a role in navigational planning, but direct evidence has been lacking. Here we show that before goal-directed navigation in an open arena, the rat hippocampus generates brief sequences encoding spatial trajectories strongly biased to progress from the subject's current location to a known goal location. These sequences predict immediate future behaviour, even in cases in which the specific combination of start and goal locations is novel. These results indicate that hippocampal sequence events characterized previously in linearly constrained environments as 'replay' are also capable of supporting a goal-directed, trajectory-finding mechanism, which identifies important places and relevant behavioural paths, at specific times when memory retrieval is required, and in a manner that could be used to control subsequent navigational behaviour.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“representations of rewarded spatial locations are preferentially reactivated in both wake and sleep states, 80,81,[142][143][144] although there are also findings of a bias of reactivations in the opposite direction.”
From Sleep—A brain-state serving systems memory consolidation (2023) · cites this paper as [144]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“both sleep and wake replay can represent knowledge about an environment and also share anticipatory features, such that they can e.g., include offline ''pre-activations'' of trajectories entailing visible but yet unexplored paths and locations.”
From Sleep—A brain-state serving systems memory consolidation (2023) · cites this paper as [144]
Experimental — accuracy not yet measuredIn the citing paper
“Along with these human studies, there is now an accumulating wealth of reports of the sort of neural response profile that would be predicted if indeed an animal is evaluating a menu of internally represented actions and their consequences at critical decision points.”
From Goals and Habits in the Brain (2013) · cites this paper as Pfeiffer and Foster, 2013
In the citing paper
“They do so in a manner consistent with the idea that the subject is engaged in some form of deliberation regarding its future potential states and the worth thereof (Johnson and Redish, 2007; Pfeiffer and Foster, 2013; van der Meer and Redish, 2009), for instance, being correlated with the subject’s ultimate choices.”
From Goals and Habits in the Brain (2013) · cites this paper as Pfeiffer and Foster, 2013
In the citing paper
“In particular, at decision points such as a branch point in a maze, hippocampal place cell responses can be observed to sweep forward from the actual location of the subject.”
From Goals and Habits in the Brain (2013) · cites this paper as Pfeiffer and Foster, 2013
In the citing paper
“rats have been argued to show behavioural and neurological evidence for what appears to be future planning [172], or at least, the precursors to planning [89,173,174].”
From Is episodic-like memory like episodic memory? (2024) · cites this paper as [172]
In the citing paper
“pathways to remembered goals were ‘pre-played’ before they engaged in goal-directed navigation through an area, even when the specific routes were novel [172].”
From Is episodic-like memory like episodic memory? (2024) · cites this paper as [172]
In the citing paper
“This pre-play directly predicts future navigation behaviour, suggesting its role in future planning.”
From Is episodic-like memory like episodic memory? (2024) · cites this paper as [172]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
(1978) · UA Campus Repository (The University of Arizona) · Cited by 8,010
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
Place navigation impaired in rats with hippocampal lesions
Morris, R. G. M., Garrud, P., Rawlins, J. N. P., & O'Keefe, J. (1982) · Nature · doi:10.1038/297681a0 · Cited by 6,340
The hippocampus as a cognitive map
Passingham, R. E. (1979) · Neuroscience · doi:10.1016/0306-4522(79)90015-0 · Cited by 5,128
Episodic memory: from mind to brain
Tulving, E. (2002) · Annual Review of Psychology · doi:10.1146/annurev.psych.53.100901.135114 · Cited by 4,950
Phase 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
Purposive Behavior in Animals and Men
Rodhom, C., & Tolman, E. C. (1950) · The American Journal of Psychology · doi:10.2307/1418946 · Cited by 2,455
Dynamics of the Hippocampal Ensemble Code for Space
Wilson, M. A., & McNaughton, B. L. (1993) · Science · doi:10.1126/science.8351520 · Cited by 2,350
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
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 1,993
Cited by
Sorted by citations
Items 601–700 of 1,000
Waypoint Path Planning With Synaptic-Dependent Spike Latency
Koul, S., & Horiuchi, T. K. (2019) · IEEE Transactions on Circuits and Systems I Regular Papers · doi:10.1109/tcsi.2018.2882818 · Cited by 18
Hippocampal theta sweeps indicate goal direction during navigation
Yu, C., Ji, Z., Ormond, J., O'Keefe, J. M., & Burgess, N. (2026) · Nature Neuroscience · doi:10.1038/s41593-026-02365-2 · Cited by 17
A model of hippocampal spiking responses to items during learning of a context-dependent task
Raudies, F., & Hasselmo, M. E. (2014) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2014.00178 · Cited by 17
Mastrogiuseppe, C., & Moreno‐Bote, R. (2022) · Scientific Reports · doi:10.1038/s41598-022-13862-2 · Cited by 17
Network mechanisms of hippocampal laterality, place coding, and goal-directed navigation
Kitanishi, T., Ito, H., Hayashi, Y., Shinohara, Y., Mizuseki, K., & Hikida, T. (2016) · The Journal of Physiological Sciences · doi:10.1007/s12576-016-0502-z · Cited by 17
Nonequilibrium Statistical Mechanics of Continuous Attractors
Zhong, W., Lu, Z., Schwab, D. J., & Murugan, A. (2020) · Neural Computation · doi:10.1162/neco_a_01280 · Cited by 17
Single-trial dynamics of hippocampal spatial representations are modulated by reward value
Michon, F., Krul, E., Sun, J., & Kloosterman, F. (2021) · Current Biology · doi:10.1016/j.cub.2021.07.058 · Cited by 16
Minicolumn-Based Episodic Memory Model With Spiking Neurons, Dendrites and Delays
Zhang, Y., Chen, Y., Zhang, J., Luo, X., Zhang, M., Qu, H., & Zhang, Y. (2022) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2022.3213688 · Cited by 16
Deleglise, Á., Donnelly-Kehoe, P. A., Yeffal, A., Jacobacci, F., Jovicich, J., Amaro, E., Armony, J. L., Doyon, J., & Della‐Maggiore, V. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac489 · Cited by 16
Rethinking the hippocampal cognitive map as a meta-learning computational module
Ambrogioni, L., & Ólafsdóttir, H. F. (2023) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2023.05.011 · Cited by 16
Piray, P., & Daw, N. D. (2025) · Nature Communications · doi:10.1038/s41467-025-62733-7 · Cited by 16
Pietras, B., Schmutz, V., & Schwalger, T. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010809 · Cited by 16
Linking temporal coordination of hippocampal activity to memory function
Etter, G., Carmichael, J. E., & Williams, S. (2023) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2023.1233849 · Cited by 16
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
Morita, K., Jitsev, J., & Morrison, A. (2016) · Behavioural Brain Research · doi:10.1016/j.bbr.2016.05.017 · Cited by 16
Gönner, L., Vitay, J., & Hamker, F. H. (2017) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2017.00084 · Cited by 16
Mechanisms of neural organization and rhythmogenesis during hippocampal and cortical ripples
McKenzie, S., Nitzan, N., & English, D. F. (2020) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2019.0237 · Cited by 16
Cao, L., Varga, V., & Chen, Z. S. (2021) · Cell Reports Methods · doi:10.1016/j.crmeth.2021.100101 · Cited by 16
Remembering rewarding futures: A simulation‐selection model of the hippocampus
Jung, M. W., Lee, H., Jeong, Y., Lee, J. W., & Lee, I. (2018) · Hippocampus · doi:10.1002/hipo.23023 · Cited by 16
Spatial localization of hippocampal replay requires dopamine signalingPreprint
Kleinman, M. R., & Foster, D. J. (2024) · eLife · doi:10.7554/elife.99678 · Cited by 16
Self-citationWang, R., Cai, Z., Pu, F., Xu, J., Yin, W., Wang, M., Ji, R., Gu, C., Li, B., Huang, Z., et al. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-37086-0_17 · Cited by 15
Fragmented replay of very large environments in the hippocampus of bats
Eliav, T., Maimon, S. R., Sarel, A., Palgi, S., Las, L., & Ulanovsky, N. (2025) · Cell · doi:10.1016/j.cell.2025.05.024 · Cited by 15
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 15
Self-citationJin, W., Qin, H., Zhang, K., & Chen, X. (2020) · Advances in experimental medicine and biology · doi:10.1007/978-981-15-7086-5_7 · Cited by 15
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
Laventure, S., & Benchenane, K. (2019) · Hippocampus · doi:10.1002/hipo.23143 · Cited by 15
Generalizing from the Past, Choosing the Future
Cowie, S., & Davison, M. (2020) · Perspectives on Behavior Science · doi:10.1007/s40614-020-00257-9 · Cited by 15
Trompoukis, G., Rigas, P., Leontiadis, L. J., & Papatheodoropoulos, C. (2020) · Molecular and Cellular Neuroscience · doi:10.1016/j.mcn.2020.103531 · Cited by 15
Recursive Cognition as a Prelude to Language
Corballis, M. C. (2013) · Springer eBooks · doi:10.1007/978-1-4614-9414-0_3 · Cited by 15
A distributed neural code in the dentate gyrus and in CA1Preprint
Stefanini, F., Kheirbek, M. A., Kushnir, L., Jimenez, J., Jennings, J. H., Stuber, G. D., Hen, R., & Fusi, S. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/292953 · Cited by 15
Goal-specific hippocampal inhibition gates learning
Jeong, N., Zheng, X. X., Paulson, A. L., Prince, S., Nguyen, V. P., Thomas, S. R., Gilpin, C. E., Goodson, M. C., & Singer, A. C. (2025) · Nature · doi:10.1038/s41586-025-08868-5 · Cited by 14
The Prefrontal-Hippocampal Comparator: Volition and Episodic Memory
Numan, R. (2021) · Perceptual and Motor Skills · doi:10.1177/00315125211041341 · Cited by 14
Donato, F., Schwartzlose, A. X., & Mendes, R. A. V. (2023) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-090922-010618 · Cited by 14
Deceuninck, L., & Kloosterman, F. (2024) · eLife · doi:10.7554/elife.84004 · Cited by 14
Rapaka, D., Tebogo, M. O., Mathew, E. M., Adiukwu, P. C., & Bitra, V. R. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e30574 · Cited by 14
Dendrites, deep learning, and sequences in the hippocampus
Bhalla, U. S. (2017) · Hippocampus · doi:10.1002/hipo.22806 · Cited by 14
The dopamine circuit as a reward-taxis navigation system
Karin, O., & Alon, U. S. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010340 · Cited by 14
Silencing hippocampal CA2 reduces behavioral flexibility in spatial learning
Lehr, A. B., Hitti, F. L., Deibel, S. H., & Stöber, T. M. (2023) · Hippocampus · doi:10.1002/hipo.23521 · Cited by 14
Spatial Cognition: Grid Cells Support Imagined Navigation
Jacobs, J., & Lee, S. A. (2016) · Current Biology · doi:10.1016/j.cub.2016.02.032 · Cited by 14
Edelman, S. (2017) · Language Sciences · doi:10.1016/j.langsci.2017.04.003 · Cited by 14
Interneuronal gap junctions increase synchrony and robustness of hippocampal ripple oscillations
Holzbecher, A., & Kempter, R. (2018) · European Journal of Neuroscience · doi:10.1111/ejn.14267 · Cited by 14
Multiplexing of Information about Self and Others in Hippocampal Ensembles
Bos, J. J., Vinck, M. A., Marchesi, P., Keestra, A., Mourik-Donga, L. A. V., Jackson, J. C., Verschure, P. F. M. J., & Pennartz, C. M. A. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.11.057 · Cited by 14
Similarity-based cognition: radical enactivism meets cognitive neuroscience
Segundo‐Ortin, M., & Hutto, D. D. (2019) · Synthese · doi:10.1007/s11229-019-02505-1 · Cited by 14
Future-thinking in animals: capacities and limits
Redshaw, J., & Bulley, A. (2018) · Cited by 14
Pevzner, A., & Guzowski, J. F. (2014) · Learning & Memory · doi:10.1101/lm.035469.114 · Cited by 14
Grid codes underlie multiple cognitive maps in the human brain
Chen, D., Axmacher, N., & Wang, L. (2024) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2024.102569 · Cited by 13
Function and causal relevance of content
Miłkowski, M. (2015) · New Ideas in Psychology · doi:10.1016/j.newideapsych.2014.12.003 · Cited by 13
Yagi, S., Igata, H., Shikano, Y., Aoki, Y., Sasaki, T., & Ikegaya, Y. (2018) · Hippocampus · doi:10.1002/hipo.22846 · Cited by 13
Distinct Neural Circuits Underlie Prospective and Concurrent Memory-Guided Behavior
Hamm, A. G., & Mattfeld, A. T. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.08.002 · Cited by 13
Spatial inference without a cognitive map: the role of higher‐order path integration
Bouchekioua, Y., Blaisdell, A. P., Kosaki, Y., Tsutsui‐Kimura, I., Craddock, P., Mimura, M., & Watanabe, S. (2020) · Biological reviews/Biological reviews of the Cambridge Philosophical Society · doi:10.1111/brv.12645 · Cited by 13
From Paths to Routes: A Method for Path Classification
Gonsek, A., Jeschke, M., Rönnau, S., & Bertrand, O. J. N. (2021) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2020.610560 · Cited by 13
Memory reactivations during sleep
Ghandour, K., & Inokuchi, K. (2022) · Neuroscience Research · doi:10.1016/j.neures.2022.12.018 · Cited by 13
Ripples in macaque V1 and V4 are modulated by top-down visual attention
Doostmohammadi, J., Gieselmann, M. A., van Kempen, J., Lashgari, R., Yoonessi, A., & Thiele, A. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2210698120 · Cited by 13
Mugan, U., Hoffman, S. L., & Redish, A. D. (2024) · Neuron · doi:10.1016/j.neuron.2024.10.004 · Cited by 13
The gradual evolution of language
Corballis, M. C. (2014) · DOAJ (DOAJ: Directory of Open Access Journals) · Cited by 13
Hsu, C. L., Best, J. R., Chiu, B. K., Nagamatsu, L. S., Voss, M. W., Handy, T. C., Bolandzadeh, N., & Liu-Ambrose, T. Y. L. (2016) · Experimental Gerontology · doi:10.1016/j.exger.2016.04.001 · Cited by 13
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
From Conditioning to Emotion: Translating Animal Models of Learning to Human Psychopathology
Heller, A. S. (2019) · The Neuroscientist · doi:10.1177/1073858419866820 · Cited by 13
A Computational Neuroscience Perspective on the Change Process in Psychotherapy
Smith, R. P., Lane, R. D., Nadel, L., & Moutoussis, M. (2020) · Oxford University Press eBooks · doi:10.1093/oso/9780190881511.003.0015 · Cited by 13
Li, M., Fan, J., Cheng, S., Yang, L., Yang, L., Wang, L., Shang, Z., & Wan, H. (2021) · Animals · doi:10.3390/ani11072003 · Cited by 13
Dabaghian, Y. A. (2016) · Neural Computation · doi:10.1162/neco_a_00840 · 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
Oh, S., Song, H., Slager, N., Ruiz, J. R. L., Park, S., & Yoon, E. (2023) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2023.3298662 · Cited by 12
Memory and Planning in Brains and Machines
Momennejad, I. (2025) · Oxford University Press eBooks · doi:10.1093/oso/9780192882547.003.0012 · Cited by 12
Dynamical modulation of hippocampal replay through firing rate adaptation
Ji, Z., Chu, T., Dong, X., Yu, C., Bush, D., Burgess, N., & Wu, S. (2026) · Nature Communications · doi:10.1038/s41467-025-68042-3 · Cited by 12
Memory 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
Howe, A. G., & Blair, H. T. (2021) · Hippocampus · doi:10.1002/hipo.23398 · Cited by 12
Life on the Edge: Latching Dynamics in a Potts Neural Network
Kang, C. J., Naim, M., Boboeva, V., & Treves, A. (2017) · Entropy · doi:10.3390/e19090468 · Cited by 12
Memory reactivations and consolidation: considering neuromodulators across wake and sleep
Samanta, A., Alonso, A., & Genzel, L. (2020) · Current Opinion in Physiology · doi:10.1016/j.cophys.2020.01.003 · Cited by 12
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
Alterations of Neuronal Dynamics as a Mechanism for Cognitive Impairment in Epilepsy
Lenck‐Santini, P., & Sakkaki, S. (2020) · Current topics in behavioral neurosciences · doi:10.1007/7854_2020_193 · Cited by 12
Robotic Navigation Based on Experiences and Predictive Map Inspired by Spatial Cognition
Liu, D., Lyu, Z., Zou, Q., Bian, X., Cong, M., & Du, Y. (2022) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/tmech.2022.3155614 · Cited by 12
Foundations of human spatial problem solving
Zarr, N., & Brown, J. W. (2023) · Scientific Reports · doi:10.1038/s41598-023-28834-3 · Cited by 12
Hippocampal and Prefrontal Processing of Network Topology to Simulate the Future
(2017) · Conscious Cities Anthology · doi:10.33797/cca17.01.12 · Cited by 12
Dark Control: Towards a Unified Account of Default Mode Function by Markov Decision ProcessesPreprint
Dohmatob, E., Dumas, G., & Bzdok, D. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/148890 · Cited by 12
The generative neural microdynamics of cognitive processing
McNamee, D. (2024) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2024.102855 · Cited by 11
Egocentric value maps of the near-body environment
Bufacchi, R. J., Somervail, R., Fitzpatrick, A. M., Murayama, Y., Logothetis, N. K., Caminiti, R., & Iannetti, G. D. (2025) · Nature Neuroscience · doi:10.1038/s41593-025-01958-7 · Cited by 11
Yuan, L., Figueroa, J. G., Khan, A., Narayan, G., Leutgeb, J. K., & Leutgeb, S. (2025) · Nature Communications · doi:10.1038/s41467-025-62498-z · Cited by 11
Estimating Location without External Cues
Cheung, A. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003927 · Cited by 11
Path planning by spike propagation
Koul, S., & Horiuchi, T. K. (2015) · IEEE Biomedical Circuits and Systems Conference (BioCAS) · doi:10.1109/biocas.2015.7348409 · Cited by 11
Transition Scale-Spaces: A Computational Theory for the Discretized Entorhinal Cortex
Waniek, N. (2019) · Neural Computation · doi:10.1162/neco_a_01255 · Cited by 11
Experience-driven rate modulation is reinstated during hippocampal replay
Tirole, M., Gorriz, M. H., Takigawa, M., Kukovska, L., & Bendor, D. (2022) · eLife · doi:10.7554/elife.79031 · Cited by 11
Spatial Cognition: Goal-Vector Cells in the Bat Hippocampus
de Cothi, W., & Spiers, H. J. (2017) · Current Biology · doi:10.1016/j.cub.2017.01.061 · Cited by 11
Lerner, I. (2017) · Wiley eBooks · doi:10.1002/9781119159193.ch18 · Cited by 11
Brain-state invariant thalamo-cortical coordination revealed by non-linear encoders
Viejo, G. D., Cortier, T., & Peyrache, A. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006041 · Cited by 11
Making our way through the world: Towards a functional understanding of the brain's spatial circuits
Kanitscheider, I., & Fiete, I. (2017) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2017.04.008 · Cited by 11
Meilinger, T., Henson, A., Rebane, J. T., Bülthoff, H., & Mallot, H. A. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-96385-3_2 · Cited by 11
Cognitive swarming: an approach from the theoretical neuroscience of hippocampal function
Monaco, J. D., Hwang, G. M., Schultz, K., & Zhang, K. (2019) · Micro- and Nanotechnology Sensors, Systems, and Applications · doi:10.1117/12.2518966 · Cited by 11
Methods for Assessment of Memory Reactivation
Liu, S., Grosmark, A., & Chen, Z. S. (2018) · Neural Computation · doi:10.1162/neco_a_01090 · Cited by 11
Intuitive Experimentation in the Physical WorldPreprint
Bramley, N. R., Gerstenberg, T., Tenenbaum, J. B., & Gureckis, T. M. (2017) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/u9y4c · Cited by 11
Testing two competing hypotheses for Eurasian jays’ caching for the future
Amodio, P., Brea, J., Farrar, B. G., Ostojić, L., & Clayton, N. S. (2021) · Scientific Reports · doi:10.1038/s41598-020-80515-7 · Cited by 10
A dynamic Bayesian model of homeostatic control
Penny, W., & Stephan, K. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-11298-5_7 · Cited by 10
Expectancy-related changes in firing of dopamine neurons depend on hippocampus
Zhang, Z., Takahashi, Y. K., Montesinos-Cartagena, M., Kahnt, T., Langdon, A., & Schoenbaum, G. M. (2024) · Nature Communications · doi:10.1038/s41467-024-53308-z · Cited by 10
Evaluating hippocampal replay without a ground truth
Takigawa, M., Gorriz, M. H., Tirole, M., & Bendor, D. (2024) · eLife · doi:10.7554/elife.85635 · Cited by 10
Antonov, G. K., & Dayan, P. (2025) · Nature Communications · doi:10.1038/s41467-025-56731-y · Cited by 10
Kim, E. J., Park, S., Schuessler, B. P., Boo, H., Cho, J., & Kim, J. J. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.116081 · Cited by 10
Hippocampal sharp-wave ripples in cognitive map maintenance versus episodic simulation
Diba, K. (2021) · Neuron · doi:10.1016/j.neuron.2021.09.006 · Cited by 10
Time and Causality across the Sciences
(2019) · Cambridge University Press eBooks · doi:10.1017/9781108592703 · Cited by 10
Theta-band phase locking during encoding leads to coordinated entorhinal-hippocampal replay
Santos-Pata, D., Barry, C., & Ólafsdóttir, H. F. (2023) · Current Biology · doi:10.1016/j.cub.2023.09.011 · Cited by 10
Granato, G., & Baldassarre, G. (2024) · Neural Networks · doi:10.1016/j.neunet.2024.106292 · Cited by 10
Metadata
- Authors
- Pfeiffer, B. E., & Foster, D. J.
- Affiliations
- Johns Hopkins University (US)
- Corresponding author
- Foster, David J.
- Venue
- Nature
- Published
- 2013-04-17
- Volume
- 497
- Issue
- 7447
- Pages
- 74-79
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3990408
- OpenAlex
- W1975958074
- Cited by
- 1,216
- References
- 53
- Citations by year
- 2026: 67 · 2025: 111 · 2024: 78 · 2023: 88 · 2022: 89 · 2021: 96 · 2020: 107 · 2019: 121 · 2018: 103 · 2017: 106 · 2016: 86 · 2015: 73 · 2014: 64 · 2013: 26
- FWCI
- 45.52
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Institute of Mental Health (MH085823, R01MH085823)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Spatial Cognition and Navigation
- Life Sciences › Neuroscience › Developmental Neuroscience › Neurogenesis and neuroplasticity mechanisms
- Keywords
- place cells, goal-directed navigation, memory replay, rats, memory retrieval, spatial memory
- MeSH terms
- Animals, Decision Making, Goals, Hippocampus, Locomotion, Male, Memory, Probability, Rats, Long-Evans, Rats
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review