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Speed of time-compressed forward replay flexibly changes in human episodic memory

Abstract

Remembering information from continuous past episodes is a complex task1. On the one hand, we must be able to recall events in a highly accurate way, often including exact timings. On the other hand, we can ignore irrelevant details and skip to events of interest. Here, we track continuous episodes consisting of different subevents as they are recalled from memory. In behavioural and magnetoencephalography data, we show that memory replay is temporally compressed and proceeds in a forward direction. Neural replay is characterized by the reinstatement of temporal patterns from encoding2,3. These fragments of activity reappear on a compressed timescale. Herein, the replay of subevents takes longer than the transition from one subevent to another. This identifies episodic memory replay as a dynamic process in which participants replay fragments of fine-grained temporal patterns and are able to skip flexibly across subevents.

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Fig. 1: Experimental design and behavioural results.
Fig. 2: Reinstatement of oscillatory patterns from encoding.
Fig. 3: Chronometry of memory replay.
Fig. 4: Illustration of several replay speeds and their aggregation.

Data availability

Group statistical data relating to this project are deposited in a public repository (https://doi.org/10.25500/eData.bham.00000254). The individual data that support the findings of this study are available from the corresponding author upon request.

References

  1. 1.

    Tulving, E. What is episodic memory? Curr. Dir. Psychol. Sci. 2, 67–70 (1993).

    Article  Google Scholar 

  2. 2.

    Michelmann, S., Bowman, H. & Hanslmayr, S. The temporal signature of memories: identification of a general mechanism for dynamic memory replay in humans. PLoS Biol. 14, e1002528 (2016).

    Article  Google Scholar 

  3. 3.

    Michelmann, S., Bowman, H. & Hanslmayr, S. Replay of stimulus-specific temporal patterns during associative memory formation. J. Cogn. Neurosci. 30, 1577–1589 (2018).

    Article  Google Scholar 

  4. 4.

    Arnold, A. E. G. F., Iaria, G. & Ekstrom, A. D. Mental simulation of routes during navigation involves adaptive temporal compression. Cognition 157, 14–23 (2016).

    Article  Google Scholar 

  5. 5.

    Bonasia, K., Blommesteyn, J. & Moscovitch, M. Memory and navigation: compression of space varies with route length and turns. Hippocampus 26, 9–12 (2016).

    Article  Google Scholar 

  6. 6.

    Foster, D. J. & Wilson, M. A. Reverse replay of behavioural sequences in hippocampal place cells during the awake state. Nature 440, 680–683 (2006).

    CAS  Article  Google Scholar 

  7. 7.

    Carr, M. F., Jadhav, S. P. & Frank, L. M. Hippocampal replay in the awake state: a potential substrate for memory consolidation and retrieval. Nat. Neurosci. 14, 147–153 (2011).

    CAS  Article  Google Scholar 

  8. 8.

    Yaffe, R. B., Shaikhouni, A., Arai, J., Inati, S. K. & Zaghloul, K. A. Cued memory retrieval exhibits reinstatement of high gamma power on a faster timescale in the left temporal lobe and prefrontal cortex. J. Neurosci. 37, 4472–4480 (2017).

    CAS  Article  Google Scholar 

  9. 9.

    Staudigl, T., Vollmar, C., Noachtar, S. & Hanslmayr, S. Temporal-pattern similarity analysis reveals the beneficial and detrimental effects of context reinstatement on human memory. J. Neurosci. 35, 5373–5384 (2015).

    CAS  Article  Google Scholar 

  10. 10.

    Zhang, H. et al. Gamma power reductions accompany stimulus-specific representations of dynamic events. Curr. Biol. 25, 635–640 (2015).

    Article  Google Scholar 

  11. 11.

    Wimber, M., Maaß, A., Staudigl, T., Richardson-Klavehn, A. & Hanslmayr, S. Rapid memory reactivation revealed by oscillatory entrainment. Curr. Biol. 22, 1482–1486 (2012).

    CAS  Article  Google Scholar 

  12. 12.

    Chen, J. et al. Shared memories reveal shared structure in neural activity across individuals. Nat. Neurosci. 20, 115–125 (2017).

    CAS  Article  Google Scholar 

  13. 13.

    Kriegeskorte, N. Representational similarity analysis—connecting the branches of systems neuroscience. Front. Syst. Neurosci. 2, 1–28 (2008).

    Google Scholar 

  14. 14.

    Staresina, B. P. et al. Hippocampal pattern completion is linked to gamma power increases and alpha power decreases during recollection. eLife 5, e17397 (2016).

    Article  Google Scholar 

  15. 15.

    Yaffe, R. B. et al. Reinstatement of distributed cortical oscillations occurs with precise spatiotemporal dynamics during successful memory retrieval. Proc. Natl Acad. Sci. USA 111, 18727–18732 (2014).

    CAS  Article  Google Scholar 

  16. 16.

    Kurth-Nelson, Z., Barnes, G., Sejdinovic, D., Dolan, R. & Dayan, P. Temporal structure in associative retrieval. eLife 4, e04919 (2015).

    Article  Google Scholar 

  17. 17.

    Ng, B. S. W., Logothetis, N. K. & Kayser, C. EEG phase patterns reflect the selectivity of neural firing. Cereb. Cortex 23, 389–398 (2013).

    Article  Google Scholar 

  18. 18.

    Schyns, P. G., Thut, G. & Gross, J. Cracking the code of oscillatory activity. PLoS Biol. 9, e1001064 (2011).

    CAS  Article  Google Scholar 

  19. 19.

    Lachaux, J.-P. et al. Studying single-trials of phase-synchronous activity in the brain. Int. J. Bifurc. Chaos 10, 2429–2439 (2000).

    Google Scholar 

  20. 20.

    Mormann, F., Lehnertz, K., David, P. & Elger, E. C. Mean phase coherence as a measure for phase synchronization and its application to the EEG of epilepsy patients. Physica D 144, 358–369 (2000).

    Article  Google Scholar 

  21. 21.

    Ji, D. & Wilson, M. A. Coordinated memory replay in the visual cortex and hippocampus during sleep. Nat. Neurosci. 10, 100–107 (2007).

    CAS  Article  Google Scholar 

  22. 22.

    Albers, A. M., Kok, P., Toni, I., Dijkerman, H. C. & de Lange, F. P. Shared representations for working memory and mental imagery in early visual cortex. Curr. Biol. 23, 1427–1431 (2013).

    CAS  Article  Google Scholar 

  23. 23.

    Ekman, M., Kok, P. & de Lange, F. P. Time-compressed preplay of anticipated events in human primary visual cortex. Nat. Commun. 8, 15276 (2017).

    CAS  Article  Google Scholar 

  24. 24.

    Bosch, S. E., Jehee, J. F. M., Fernandez, G. & Doeller, C. F. Reinstatement of associative memories in early visual cortex is signaled by the hippocampus. J. Neurosci. 34, 7493–7500 (2014).

    CAS  Article  Google Scholar 

  25. 25.

    Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B 57, 289–300 (1995).

    Google Scholar 

  26. 26.

    Radvansky, G. A. & Zacks, J. M. Event boundaries in memory and cognition. Curr. Opin. Behav. Sci. 17, 133–140 (2017).

    Article  Google Scholar 

  27. 27.

    Sols, I., DuBrow, S., Davachi, L. & Fuentemilla, L. Event boundaries trigger rapid memory reinstatement of the prior events to promote their representation in long-term memory. Curr. Biol. 27, 3499–3504.e4 (2017).

    CAS  Article  Google Scholar 

  28. 28.

    Davachi, L. & DuBrow, S. How the hippocampus preserves order: the role of prediction and context. Trends Cogn. Sci. 19, 92–99 (2015).

    Article  Google Scholar 

  29. 29.

    Buzsáki, G. & Tingley, D. Space and time: the hippocampus as a sequence generator. Trends Cogn. Sci. 22, 853–869 (2018).

    Article  Google Scholar 

  30. 30.

    Johnson, A. & Redish, A. D. Neural ensembles in CA3 transiently encode paths forward of the animal at a decision point. J. Neurosci. 27, 12176–12189 (2007).

    CAS  Article  Google Scholar 

  31. 31.

    Jafarpour, A., Fuentemilla, L., Horner, A. J., Penny, W. & Duzel, E. Replay of very early encoding representations during recollection. J. Neurosci. 34, 242–248 (2014).

    CAS  Article  Google Scholar 

  32. 32.

    Coltheart, M. The MRC psycholinguistic database. Q. J. Exp. Psychol. A 33, 497–505 (1981).

    Article  Google Scholar 

  33. 33.

    Brysbaert, M. & New, B. Moving beyond Kučera and Francis: a critical evaluation of current word frequency norms and the introduction of a new and improved word frequency measure for American English. Behav. Res. Methods 41, 977–990 (2009).

    Article  Google Scholar 

  34. 34.

    Brainard, D. H. The Psychophysics Toolbox. Spat. Vis. 10, 433–436 (1997).

    CAS  Article  Google Scholar 

  35. 35.

    Ratcliff, R. Group reaction time distributions and an analysis of distribution statistics. Psychol. Bull. 86, 446–461 (1979).

    CAS  Article  Google Scholar 

  36. 36.

    Oostenveld, R., Fries, P., Maris, E. & Schoffelen, J.-M. FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Comput. Intell. Neurosci. 2011, 1–9 (2011).

    Article  Google Scholar 

  37. 37.

    Delorme, A. & Makeig, S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J. Neurosci. Methods 134, 9–21 (2004).

    Article  Google Scholar 

  38. 38.

    Tal, I. & Abeles, M. Cleaning MEG artifacts using external cues. J. Neurosci. Methods 217, 31–38 (2013).

    CAS  Article  Google Scholar 

  39. 39.

    Stolk, A., Todorovic, A., Schoffelen, J. M. & Oostenveld, R. Online and offline tools for head movement compensation in MEG. Neuroimage 68, 39–48 (2013).

    Article  Google Scholar 

  40. 40.

    Long, N. M., Burke, J. F. & Kahana, M. J. Subsequent memory effect in intracranial and scalp EEG. NeuroImage 84, 488–494 (2014).

    Article  Google Scholar 

  41. 41.

    Tzourio-Mazoyer, N. et al. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. NeuroImage 51, 273–289 (2002).

    Article  Google Scholar 

  42. 42.

    Tallon-Baudry, C., Bertrand, O., Delpuech, C. & Pernier, J. Stimulus specificity of phase-locked and non-phase-locked 40 Hz visual responses in human. J. Neurosci. 16, 4240–4249 (1996).

    CAS  Article  Google Scholar 

  43. 43.

    Busch, N. A., Dubois, J. & VanRullen, R. The phase of ongoing EEG oscillations predicts visual perception. J. Neurosci. 29, 7869–7876 (2009).

    CAS  Article  Google Scholar 

  44. 44.

    Hentschke, H. & Stüttgen, M. C. Computation of measures of effect size for neuroscience data sets. Eur. J. Neurosci. 34, 1887–1894 (2011).

    Article  Google Scholar 

  45. 45.

    Rouder, J. N., Speckman, P.L., Sun, D., Morey, R. D. & Iverson, G. Bayesian t tests for accepting and rejecting the null hypothesis. Psychon. Bull. Rev. 16, 225–237 (2009).

    Article  Google Scholar 

  46. 46.

    Maris, E. & Oostenveld, R. Nonparametric statistical testing of EEG- and MEG-data. J. Neurosci. Methods 164, 177–190 (2007).

    Article  Google Scholar 

  47. 47.

    Kriegeskorte, N., Simmons, W. K., Bellgowan, P. S. & Baker, C. I. Circular analysis in systems neuroscience: the dangers of double dipping. Nat. Neurosci. 12, 535–540 (2009).

    CAS  Article  Google Scholar 

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Acknowledgements

The authors thank the SPMIC—specifically G. O’Neill, B. A. E. Hunt and L. Gascoyne—for help with data collection. This work was supported by the ERC Grant Code4Memory (647954) awarded to S.H., who is further supported by the Wolfson Society and Royal Society. B.P.S. is supported by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (107672/Z/15/Z). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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S.M., B.P.S. and S.H. conceived and designed the experiments. S.M. performed the experiments. S.M. analysed the data under the supervision of S.H. S.M., S.H. and H.B. contributed reagents, materials and analysis tools. S.M. and S.H. wrote the paper, with comments and edits by B.P.S. and H.B.

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Correspondence to Simon Hanslmayr.

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Supplementary Notes, Supplementary Methods, Supplementary Figures 1–7

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Michelmann, S., Staresina, B.P., Bowman, H. et al. Speed of time-compressed forward replay flexibly changes in human episodic memory. Nat Hum Behav 3, 143–154 (2019). https://doi.org/10.1038/s41562-018-0491-4

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