Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Inhibitory control of sharp-wave ripple duration during learning in hippocampal recurrent networks

Nature Neuroscience volume 26, pages 788–797 (2023)Cite this article

Subjects

Abstract

Recurrent excitatory connections in hippocampal regions CA3 and CA2 are thought to play a key role in the generation of sharp-wave ripples (SWRs), electrophysiological oscillations tightly linked with learning and memory consolidation. However, it remains unknown how defined populations of inhibitory interneurons regulate these events during behavior. Here, we use large-scale, three-dimensional calcium imaging and retrospective molecular identification in the mouse hippocampus to characterize molecularly identified CA3 and CA2 interneuron activity during SWR-associated memory consolidation and spatial navigation. We describe subtype- and region-specific responses during behaviorally distinct brain states and find that SWRs are preceded by decreased cholecystokinin-expressing interneuron activity and followed by increased parvalbumin-expressing basket cell activity. The magnitude of these dynamics correlates with both SWR duration and behavior during hippocampal-dependent learning. Together these results assign subtype- and region-specific roles for inhibitory circuits in coordinating operations and learning-related plasticity in hippocampal recurrent circuits.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Large-scale imaging of molecularly identified GABAergic interneurons in CA3 and CA2.
Fig. 2: Locomotion-related dynamics during spatial navigation.
Fig. 3: Spatial tuning of CA3 and CA2 circuit elements during spatial navigation.
Fig. 4: Subtype-specific offline dynamics during SWR events.
Fig. 5: Peri-SWR dynamics are both predictive and reflective of SWR duration in a subtype-specific manner.
Fig. 6: Learning-related changes in interneuron dynamics around SWRs are both region and subtype specific.

Similar content being viewed by others

Data availability

The data analyzed for this study are available at https://github.com/losonczylab/Vancura_Geiller_NatNeuro_2023. Source data are provided with this paper.

Code availability

The code used for this study is available at https://github.com/losonczylab/Vancura_Geiller_NatNeuro_2023.

References

  1. Tulving, E. Episodic memory: from mind to brain. Annu. Rev. Psychol. 53, 1–25 (2002).

    Article  PubMed  Google Scholar 

  2. Buzsáki, G. Hippocampal sharp wave-ripple: a cognitive biomarker for episodic memory and planning. Hippocampus 25, 1073–1188 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  3. Daumas, S., Halley, H., Francés, B. & Lassalle, J.-M. Encoding, consolidation, and retrieval of contextual memory: differential involvement of dorsal CA3 and CA1 hippocampal subregions. Learn. Mem. 12, 375–382 (2005).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Kesner, R. P. Behavioral functions of the CA3 subregion of the hippocampus. Learn. Mem. 14, 771–781 (2007).

    Article  PubMed  Google Scholar 

  5. Nakashiba, T., Buhl, D. L., McHugh, T. J. & Tonegawa, S. Hippocampal CA3 output is crucial for ripple-associated reactivation and consolidation of memory. Neuron 62, 781–787 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Dudek, S. M., Alexander, G. M. & Farris, S. Rediscovering area CA2: unique properties and functions. Nat. Rev. Neurosci. 17, 89–102 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Alexander, G. M. et al. Social and novel contexts modify hippocampal CA2 representations of space. Nat. Commun. 7, 10300 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Oliva, A., Fernández-Ruiz, A., Buzsáki, G. & Berényi, A. Role of hippocampal CA2 region in triggering sharp-wave ripples. Neuron 91, 1342–1355 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Mishra, R. K., Kim, S., Guzman, S. J. & Jonas, P. Symmetric spike timing-dependent plasticity at CA3–CA3 synapses optimizes storage and recall in autoassociative networks. Nat. Commun. 7, 11552 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Rebola, N., Carta, M. & Mulle, C. Operation and plasticity of hippocampal CA3 circuits: implications for memory encoding. Nat. Rev. Neurosci. 18, 208–220 (2017).

    Article  CAS  PubMed  Google Scholar 

  11. Norimoto, H. et al. Hippocampal ripples down-regulate synapses. Science 359, 1524–1527 (2018).

    Article  CAS  PubMed  Google Scholar 

  12. Pfeiffer, B. E. The content of hippocampal ‘replay’. Hippocampus 30, 6–18 (2020).

    Article  PubMed  Google Scholar 

  13. Hunt, D. L., Linaro, D., Si, B., Romani, S. & Spruston, N. A novel pyramidal cell type promotes sharp-wave synchronization in the hippocampus. Nat. Neurosci. 21, 985–995 (2018).

    Article  CAS  PubMed  Google Scholar 

  14. Kay, K. et al. A hippocampal network for spatial coding during immobility and sleep. Nature 531, 185–190 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Geiller, T. et al. Local circuit amplification of spatial selectivity in the hippocampus. Nature 601, 105–109 (2022).

    Article  CAS  PubMed  Google Scholar 

  16. Sadeh, S. & Clopath, C. Inhibitory stabilization and cortical computation. Nat. Rev. Neurosci. 22, 21–37 (2021).

  17. Vogels, T. P., Sprekeler, H., Zenke, F., Clopath, C. & Gerstner, W. Inhibitory plasticity balances excitation and inhibition in sensory pathways and memory networks. Science 334, 1569–1573 (2011).

    Article  CAS  PubMed  Google Scholar 

  18. Arriaga, M. & Han, E. B. Structured inhibitory activity dynamics in new virtual environments. eLife 8, e47611 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Booker, S. A. & Vida, I. Morphological diversity and connectivity of hippocampal interneurons. Cell Tissue Res. 373, 619–641 (2018).

  20. Dudok, B. et al. Recruitment and inhibitory action of hippocampal axo-axonic cells during behavior. Neuron 109, 3838–3850 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Geiller, T., Royer, S. & Choi, J. -S. Segregated cell populations enable distinct parallel encoding within the radial axis of the CA1 pyramidal layer. Exp. Neurobiol. 26, 1–10 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  22. Geiller, T. et al. Large-scale 3D two-photon imaging of molecularly identified CA1 interneuron dynamics in behaving mice. Neuron 108, 968–983 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Pelkey, K. A. et al. Hippocampal GABAergic inhibitory interneurons. Physiol. Rev. 97, 1619–1747 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Dupret, D., O’Neill, J. & Csicsvari, J. Dynamic reconfiguration of hippocampal interneuron circuits during spatial learning. Neuron 78, 166–180 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Kaufman, A. M., Geiller, T. & Losonczy, A. A role for the locus coeruleus in hippocampal CA1 place cell reorganization during spatial reward learning. Neuron 105, 1018–1026 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Topolnik, L. & Tamboli, S. The role of inhibitory circuits in hippocampal memory processing. Nat. Rev. Neurosci. 23, 476–492 (2022).

    Article  CAS  PubMed  Google Scholar 

  27. Chamberland, S. & Topolnik, L. Inhibitory control of hippocampal inhibitory neurons. Front. Neurosci. 6, 165 (2012).

  28. Klausberger, T. & Somogyi, P. Neuronal diversity and temporal dynamics: the unity of hippocampal circuit operations. Science 321, 53–57 (2008).

  29. Donato, F., Rompani, S. B. & Caroni, P. Parvalbumin-expressing basket-cell network plasticity induced by experience regulates adult learning. Nature 504, 272–276 (2013).

    Article  CAS  PubMed  Google Scholar 

  30. Ruediger, S. et al. Learning-related feedforward inhibitory connectivity growth required for memory precision. Nature 473, 514–518 (2011).

    Article  CAS  PubMed  Google Scholar 

  31. Sharma, V. et al. eIF2α controls memory consolidation via excitatory and somatostatin neurons. Nature 586, 412–416 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Geiller, T., Fattahi, M., Choi, J. S. & Royer, S. Place cells are more strongly tied to landmarks in deep than in superficial CA1. Nat. Commun. 8, 14531 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Hitti, F. L. & Siegelbaum, S. A. The hippocampal CA2 region is essential for social memory. Nature 508, 88–92 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Arriaga, M. & Han, E. B. Dedicated hippocampal inhibitory networks for locomotion and immobility. J. Neurosci. 37, 9222–9238 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Dudok, B. et al. Alternating sources of perisomatic inhibition during behavior. Neuron 109, 997–1012 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. O’Keefe, J. & Dostrovsky, J. The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat. Brain Res. 34, 171–175 (1971).

    Article  PubMed  Google Scholar 

  37. Ego-Stengel, V. & Wilson, M. A. Spatial selectivity and theta phase precession in CA1 interneurons. Hippocampus 17, 161–174 (2007).

    Article  PubMed  Google Scholar 

  38. Grosmark, A. D., Sparks, F. T., Davis, M. J. & Losonczy, A. Reactivation predicts the consolidation of unbiased long-term cognitive maps. Nat. Neurosci. 24, 1574–1585 (2021).

    Article  CAS  PubMed  Google Scholar 

  39. Malvache, A., Reichinnek, S., Villette, V., Haimerl, C. & Cossart, R. Awake hippocampal reactivations project onto orthogonal neuronal assemblies. Science 353, 1280–1283 (2016).

    Article  CAS  PubMed  Google Scholar 

  40. Terada, S. et al. Adaptive stimulus selection for consolidation in the hippocampus. Nature 601, 240–244 (2022).

    Article  CAS  PubMed  Google Scholar 

  41. Jinno, S. et al. Neuronal diversity in GABAergic long-range projections from the hippocampus. J. Neurosci. 27, 8790–8804 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Katona, L. et al. Sleep and movement differentiates actions of two types of somatostatin-expressing GABAergic interneuron in rat hippocampus. Neuron 82, 872–886 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Lasztóczi, B., Tukker, J. J., Somogyi, P. & Klausberger, T. Terminal field and firing selectivity of cholecystokinin-expressing interneurons in the hippocampal CA3 area. J. Neurosci. 31, 18073–18093 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Fernández-Ruiz, A. et al. Long-duration hippocampal sharp wave ripples improve memory. Science 364, 1082–1086 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  45. Grosmark, A. D. & Buzsáki, G. Diversity in neural firing dynamics supports both rigid and learned hippocampal sequences. Science 351, 1440–1443 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Kohus, Z. et al. Properties and dynamics of inhibitory synaptic communication within the CA3 microcircuits of pyramidal cells and interneurons expressing parvalbumin or cholecystokinin. J. Physiol. 594, 3745–3774 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Mercer, A., Trigg, H. L. & Thomson, A. M. Characterization of neurons in the CA2 subfield of the adult rat hippocampus. J. Neurosci. 27, 7329–7338 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Papp, O. I., Karlócai, M. R., Tóth, I. E., Freund, T. F. & Hájos, N. Different input and output properties characterize parvalbumin-positive basket and Axo-axonic cells in the hippocampal CA3 subfield. Hippocampus 23, 903–918 (2013).

    Article  CAS  PubMed  Google Scholar 

  49. Vida, I. & Frotscher, M. A hippocampal interneuron associated with the mossy fiber system. Proc. Natl Acad. Sci. USA 97, 1275–1280 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Maccaferri, G., Tóth, K. & McBain, C. J. Target-specific expression of presynaptic mossy fiber plasticity. Science 279, 1368–1370 (1998).

    Article  CAS  PubMed  Google Scholar 

  51. Viney, T. J. et al. Network state-dependent inhibition of identified hippocampal CA3 axo-axonic cells in vivo. Nat. Neurosci. 16, 1802–1811 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Fuentealba, P. et al. Expression of COUP-TFII nuclear receptor in restricted GABAergic neuronal populations in the adult rat hippocampus. J. Neurosci. 30, 1595–1609 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Evangelista, R. et al. Generation of sharp wave-ripple events by disinhibition. J. Neurosci. 40, 7811–7836 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Mizunuma, M. et al. Unbalanced excitability underlies offline reactivation of behaviorally activated neurons. Nat. Neurosci. 17, 503–505 (2014).

    Article  CAS  PubMed  Google Scholar 

  55. Kajikawa, K., Hulse, B. K., Siapas, A. G. & Lubenov, E. V. UP–DOWN states and ripples differentially modulate membrane potential dynamics across DG, CA3, and CA1 in awake mice. eLife 11, e69596 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Zarnadze, S. et al. Cell-specific synaptic plasticity induced by network oscillations. eLife 5, e14912 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  57. Lau, P. Y.-P. et al. Long-term plasticity in identified hippocampal GABAergic interneurons in the CA1 area in vivo. Brain Struct. Funct. 222, 1809–1827 (2017).

    Article  CAS  PubMed  Google Scholar 

  58. Rolotti, S. V. et al. Local feedback inhibition tightly controls rapid formation of hippocampal place fields. Neuron 110, 783–794 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Francavilla, R. et al. Connectivity and network state-dependent recruitment of long-range VIP–GABAergic neurons in the mouse hippocampus. Nat. Commun. 9, 5043 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  60. Oliva, A., Fernández-Ruiz, A., Leroy, F. & Siegelbaum, S. A. Hippocampal CA2 sharp-wave ripples reactivate and promote social memory. Nature 587, 264–269 (2020).

    Article  CAS  PubMed  Google Scholar 

  61. Szalay, G. et al. Fast 3D imaging of spine, dendritic, and neuronal assemblies in behaving animals. Neuron 92, 723–738 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Jinno, S., Araki, K., Matsumoto, Y., Suh, Y. -H. & Yamamoto, T. Selective apoptosis induction in the hippocampal mossy fiber pathway by exposure to CT105, the C-terminal fragment of Alzheimer’s amyloid precursor protein. Brain Res. 1249, 68–78 (2009).

    Article  CAS  PubMed  Google Scholar 

  63. Gulyás, A. I., Hájos, N. & Freund, T. F. Interneurons containing calretinin are specialized to control other interneurons in the rat hippocampus. J. Neurosci. 16, 3397–3411 (1996).

    Article  PubMed  PubMed Central  Google Scholar 

  64. Kaifosh, P., Zaremba, J. D., Danielson, N. B. & Losonczy, A. SIMA: Python software for analysis of dynamic fluorescence imaging data. Front. Neuroinform. 8, 80 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  65. Keemink, S. W. et al. FISSA: a neuropil decontamination toolbox for calcium imaging signals. Sci. Rep. 8, 3493 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  66. Danielson, N. B. et al. Sublayer-specific coding dynamics during spatial navigation and learning in hippocampal area CA1. Neuron 91, 652–665 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Hardcastle, K., Maheswaranathan, N., Ganguli, S. & Giocomo, L. M. A multiplexed, heterogeneous, and adaptive code for navigation in medial entorhinal cortex. Neuron 94, 375–387 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Hainmueller, T. & Bartos, M. Parallel emergence of stable and dynamic memory engrams in the hippocampus. Nature 558, 292–296 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

B.V. is supported by T32GM007367 (NIH) and F30MH125628 (NIMH). T.G. is supported by K99MH129565 (NIMH). A.L. is supported by 1R01MH124047 and 1R01MH124867 (NIMH), 1U19NS104590 and 1U01NS115530 (NINDS) and the Kavli Foundation. We thank members of the Losonczy lab for their invaluable comments on previous versions of the paper.

Author information

Author notes

  1. These authors contributed equally: Bert Vancura, Tristan Geiller.

Authors and Affiliations

  1. Department of Neuroscience, Columbia University, New York, NY, USA

    Bert Vancura, Tristan Geiller, Andres Grosmark & Attila Losonczy

  2. Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA

    Bert Vancura, Tristan Geiller, Andres Grosmark, Vivian Zhao & Attila Losonczy

  3. University of Connecticut Medical School, Farmington, CT, USA

    Andres Grosmark

  4. The Kavli Institute for Brain Science, Columbia University, New York, NY, USA

    Attila Losonczy

Authors
  1. Bert Vancura
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tristan Geiller
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Andres Grosmark
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Vivian Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Attila Losonczy
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

B.V., T.G. and A.L. designed the project and experiments. B.V. and T.G. performed all experiments with assistance from V.Z. B.V., T.G. and A.G. analyzed the data. All authors wrote the paper. A.L. oversaw all aspects of the project.

Corresponding authors

Correspondence to Tristan Geiller or Attila Losonczy.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Neuroscience thanks Liset de la Prida and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Immunohistochemical identification of interneuron subtypes and separation of CA2 and CA3 interneurons with anti-STEP immunohistochemistry.

(a) Schematic of the experimental pipeline used to determine the molecular identity of imaged cells. Multiple rounds of immunohistochemistry were performed on fixed, horizontal slices that were registered to high-resolution in vivo Z-stacks. (b) Example in vivo 2p-AOD image (left) and confocal image (right) of the registered FOV. White arrows indicate the registered cells. Calbindin immunohistochemistry was used to label the mossy fibers of stratum lucidum of CA3/CA2. This procedure was repeated in n = 22 imaged mice. Scale bars on the left and right images represent 50 and 100 µm, respectively. (c) Example labeling strategy used to determine the subtype and region identity of imaged cells. Immunohistochemical labels were not removed between the different rounds (see Methods). (d) Example immunohistochemical labeling and combinatorial expression patterns of the 5 markers (PV, SOM, SATB1, CCK, CB) used to separate imaged cells into subtypes. This procedure was repeated in n = 22 imaged mice. All images are approximately 60 × 60 µm. (e) CA2 interneurons were identified by their proximity to STEP-expressing CA2 pyramidal cells (top row). In comparison, CA3 interneurons occupied slices where Calbindin-positive mossy fibers were present but where the majority of pyramidal cells were not STEP-expressing (bottom row). This procedure was repeated in n = 22 imaged mice. Scale bars on all four images represent approximately 100 µm.

Extended Data Fig. 2 Molecular profiling of calbindin-positive SATB1-negative immobility-active interneurons.

(a) Confocal micrograph of CB-expressing interneurons, negative for SATB1 but positive for COUP-TFII (top) and M2R (bottom). This staining was repeated in n = 2 mice. Scale bars represent 20 µm. (b) Quantification of the overlap of CB-expressing interneurons split by immunoreactivity to SATB1 with other markers.

Source data

Extended Data Fig. 3 Additional data on interneuron spatial selectivity and generalized-linear model of interneuron activity during spatial navigation.

(a) Spatial information for significantly tuned interneurons, broken down by both region and subtype. Immobility-active CB/SATB1- neurons were silenced during locomotion and were thus not considered in this analysis. Data from 188 cells in n = 9 mice. Significance values over individual violin plots show the results of (one-way) signed-rank tests. (b) Within-day spatial stability of all interneurons, broken down by both region and subtype. Plotted as in A. Significance values over individual violin plots show the results of (one-way) signed-rank tests. Significance values over pairs of violin plots show results from (two-way) ranked-sum tests (only significant differences are shown). Data from 152 cells in n = 9 mice. (c) Across-day spatial stability of all interneurons, broken down by both region and subtype. Plotted as in A. Significance values over individual violin plots show the results of (one-way) signed-rank tests. Significance values over pairs of violin plots show results from (two-way) ranked-sum tests (only significant differences are shown). Data from 142 cells in n = 9 mice. (d) Left: Summary of the fraction of positively tuned CA2 interneurons, broken down by subtype (PVBC: 0.343 ± 0.341, AAC: 0.455 ± 0.267, SOM: 0.405 ± 0.339, CCK: 0.685 ± 0.228, CB/SATB1 + : 0.0 ± 0.0). CA2 CCK cells were more likely to be positively spatially tuned cells than CA2 CB/SATB1+ cells (one-way ANOVA with post-hoc multiple testing correction, p = 0.048). Immobility-active CB/SATB1- neurons were silenced during locomotion and were thus not considered in this analysis. Each data point represents an imaging session. PVBC data from 20 imaging sessions, AAC data from 22 sessions, SOM data from 14 sessions, CCK data from 9 sessions, and CB/SATB1 + data from 2 sessions; data from n = 9 mice. Data reported as mean ± s.d. Right: Same data as on the left, but for negatively tuned CA2 interneurons (PVBC: 0.304 ± 0.261, AAC: 0.270 ± 0.293, SOM: 0.690 ± 0.226, CCK: 0.685 ± 0.228, CB/SATB1 + : 0.75 ± 0.25). Significant differences in the fraction of negatively tuned CA2 interneurons by subtype are indicated (one-way ANOVA with post-hoc multiple testing correction: p(CCK-PVBC) = 0.0075, p(CCK-AAC) = 0.0024, p(SOM-PVBC) = 0.0012, p(SOM-AAC) = 0.001). Immobility-active CB/SATB1- neurons were silenced during locomotion and were thus not considered in this analysis. Each data point represents an imaging session. PVBC data from 20 imaging sessions, AAC data from 22 sessions, SOM data from 14 sessions, CCK data from 9 sessions, and CB/SATB1 + data from 2 sessions; data from n = 9 mice. Data reported as mean ± s.d. (e) Example of 100 seconds of real interneuron activity during locomotion and the predicted activity from a GLM. The predicted activity for each cell was calculated based on 4 predictor behavioral variables: velocity, position, licking, and water delivery (see Methods). (f) Comparison of the GLM weights for each cell for the velocity predictor, separated by both subtype and region. Only cells for which the velocity predictor in the model was a significant predictor are shown. Significance values over individual violin plots show the results of (one-way) signed-rank tests. Significance values over pairs of violin plots show results from (two-way) ranked-sum tests. Only significant differences are shown. Data from 170 cells from n = 9 mice. (g) Same data as shown in F, but now for the licking predictor. Only cells for which the licking predictor in the model was significant are shown. No significance at the subtype or region level was found. Data from 20 cells in n = 9 mice. (h) Same data as shown in F, but now for the reward predictor. Only cells for which the reward predictor in the model was significant are shown. No significance at the subtype or region level was found. Data from 56 cells from n = 9 mice. (i) Same data as shown in F, now for the position predictor. Only cells for which the position predictor in the model was significant are shown. Significance values over pairs of violin plots show results from (two-way) ranked-sum tests. Only significant differences are shown. Data from 45 cells from n = 9 mice.

Source data

Extended Data Fig. 4 Immunohistochemical verification of Grik4-Cre transgenic line.

(a) Top left: Confocal image of FLEX-GCaMP8s expression when injected into CA3/CA2 of the Grik4-Cre transgenic line. Top right: CA2 pyramidal cells identified by their PCP4 immunosignal. Bottom: Merge of the above images. Note that GCaMP expression is largely confined to CA3 in the Grik4-Cre line, although some GCaMP8s-positive pyramidal cells in CA2 can be seen as well. This staining was repeated in n = 3 mice.

Extended Data Fig. 5 CA3 pyramidal cell dynamics around SWRs and correlations between SWR properties.

(a) Left: Representative in vivo two-photon time-average image of a CA3PC FOV. Center: Example CA3PC ΔF/F traces with detected SWRs depicted as vertical red lines. Right: Peri-SWR fluorescence for the entire CA3PC population, averaged over all SWR events. Data from n = 3 mice. Trace represents mean ± s.e.m. (b) Left: Distribution of peri-SWR CA3PC calcium transients for SWRs with short duration (green, taken as SWRs with duration falling between 0–20th percentile of all SWRs for a given mouse) and long duration (purple, for SWRs falling between the 80–100th duration percentile). Right: Quantification of the population transient rate for long- and short-duration SWRs. CA3PCs emitted significantly more transients during long-duration SWRs than during short-duration SWRs (Short duration SWRs: 0.483 ± 0.285 transients/SWR, Long duration SWRs: 0.661 ± 0.331 transients/SWR, two-sided Wilcoxon signed-rank test: p = 0.011). Data from 18 sessions from n = 3 mice. Data reported as mean ± s.d. (c) Correlation between SWR duration and the number of co-active pyramidal cells around the SWR. Each dot represents a SWR event. Long-duration SWRs were associated with greater fractions of co-active CA3PCs around the SWR event (linear regression, r = 0.129, p = 2.50 × 10–4). Only SWRs associated with at least 1 transient in the CA3PC FOV are considered. Data from n = 3 mice. (d) Correlation between amplitude and duration for individual SWRs. Left: Example scatter plot and linear regression line depicting the relationship between amplitude and duration for all SWRs recorded during the imaging of one example interneuron. Right: Distribution of p-values for the two-sided regression between amplitude and duration, calculated over all imaging sessions. The horizontal dashed line corresponds to a p-value of 0.05. A strong relationship between SWR amplitude and duration was present in all imaging sessions. Data from n = 13 mice. * p < 0.05, ** p < 0.01, *** p < 0.001.

Source data

Extended Data Fig. 6 Additional data on CA3 and CA2 interneuron dynamics around SWRs.

(a) Example Z-scored peri-SWR traces for both activated and inhibited cells of each subtype. (b) Average peri-SWR traces for all CA2 interneuron subtypes (n = 46 PVBCs, 46 AACs, 59 SOMs, 19 CCKs, 12 CB/SATB1 + neurons, and 8 CB/SATB1- neurons from n = 13 mice). Traces for each subtype represent mean ± s.e.m. (c) Average SWR activity index for all CA2 interneurons, grouped by subtype. Wilcoxon signed-rank tests against a median of 0 were performed for each subtype (PVBC: 0.56 ± 0.83, p = 1 × 10–5, AAC: 0.03 ± 0.65, p = 0.18; SOM: -0.002 ± 0.5, p = 0.96; CCK: -0.08 ± 0.61, p = 0.12; CB/SATB1 + : 0.17 ± 0.5, p = 0.43; CB/SATB1-: 0.77 ± 0.82, p = 0.04). Between-subtype statistical comparisons were performed using the Kruskal-Wallis test (p = 9 × 10–5) with post-hoc Wilcoxon rank sum tests with p-values adjusted using the Bonferroni correction (significant adjusted p-values: PVBC-AAC = 0.038, PVBC-CCK = 0.016, PVBC-SOM = 0.0004). Data from n = 46 PVBCs, 46 AACs, 59 SOMs, 19 CCKs, 12 CB/SATB1 + , and 8 CB/SATB1- from n = 13 mice. Data reported as mean ± s.d. (d) Left: Average peri-SWR traces for all activated CA2 interneurons, grouped by subtype. Right: Same traces for all inhibited CA2 interneurons, grouped by subtype. Cell numbers for each subtype and condition indicated on the figure, data from n = 13 mice. Traces for each subtype represent mean ± s.e.m. * p < 0.05, ** p < 0.01, *** p < 0.001.

Source data

Extended Data Fig. 7 Dynamics of CA3 CB subtypes and all CA2 interneuron subtypes around short- and long-duration SWRs.

(a) Average Z-scored peri-SWR traces for both short- (0–20th percentile) and long- (80–100th percentile) duration SWRs for CA3 CB/SATB1 + interneurons (n = 8 CB/SATB1+ cells from n = 13 mice). Traces for each condition represent mean ± s.e.m. (b) Average Z-scored peri-SWR traces for both short- (0–20th percentile) and long- (80–100th percentile) duration SWRs for CA3 CB/SATB1- interneurons (n = 13 CB/SATB1- cells from n = 13 mice). Traces for each condition represent mean ± s.e.m. (c) Average value of the difference in activity between long- and short-duration SWRs for CA3 CB+/SATB1+ and CB+/SATB1- subtypes, considered separately for the pre-SWR and post-SWR activity. Neither CB+/SATB1+ nor CB+/SATB1- interneurons responded differently during long-duration compared to short-duration SWRs (two-way, one-sample t-tests against 0 for each subtype and condition: CB+/SATB1+ PRE: 0.028 ± 0.176, p = 0.69; CB+/SATB1+ POST: 0.124 ± 0.251, p = 0.23; CB+/SATB1- PRE: -0.047 ± 0.150, p = 0.30; CB+/SATB1- POST: 0.056 ± 0.239, p = 0.43). Data from 8 CB+/SATB1+ and 13 CB+/SATB1- cells from n = 13 mice. Data reported as mean ± s.d. (d) Average Z-scored peri-SWR traces for both short- (0–20th percentile) and long- (80–100th percentile) duration SWRs for CA2 interneurons of each subtype (n = 46 PVBCs, 46 AACs, 59 SOMs, 19 CCKs, and 22 CBs from n = 13 mice). CB+/SATB1+ and CB+/SATB1- neurons are considered together in the CB subtype. Traces for each subtype and condition represent mean ± s.e.m. (e) Average value of the difference in activity between long- and short-duration SWRs for each CA2 interneuron, considered separately for the pre-SWR and post-SWR activity, and grouped by subtype. PVBCs were significantly more activated after long-duration SWRs, while the other subtypes did not show different dynamics during short- compared to long-duration SWRs. Only significant differences are indicated (two-way, one-sample t-tests against 0 for each subtype with Bonferroni correction for multiple testing: PVBC PRE: -0.044 ± 0.264, p = 1.0; PVBC POST: 0.267 ± 0.464, p = 0.0037; AAC PRE: 0.024 ± 0.250, p = 1.0; AAC POST: -0.053 ± 0.322, p = 1.0; SOM PRE: 0.054 ± 0.389, p = 1.0; SOM POST: 0.042 ± 0.340, p = 1.0; CCK PRE: -0.116 ± 0.252, p = 0.70; CCK POST: -0.036 ± 0.360, p = 1.0; CB PRE: -0.050 ± 0.351, p = 1.0; CB POST: 0.103 ± 0.328, p = 1.0). Data from n = 46 PVBCs, 46 AACs, 59 SOMs, 19 CCKs, and 22 CBs from n = 13 mice. CB+/SATB1+ and CB+/SATB1- neurons are considered together in the CB subtype. Data reported as mean ± s.d. (f) Average Z-scored peri-SWR traces for both short- (0–20th percentile) and long- (80–100th percentile) duration SWRs for CA2 CB+/SATB1+ interneurons (n = 12 CB+/SATB1+ cells from n = 13 mice). Traces for each condition represent mean ± s.e.m. (g) Average Z-scored peri-SWR traces for both short- (0–20th percentile) and long- (80–100th percentile) duration SWRs for CA2 CB/SATB1- interneurons (n = 8 CB+/SATB1- cells from n = 13 mice). Traces for each condition represent mean ± s.e.m. (h) Average value of the difference in activity between long- and short-duration SWRs for CA2 CB+/SATB1+ and CB+/SATB1- subtypes, considered separately for the pre-SWR and post-SWR activity. Neither CB+/SATB1+ nor CB+/SATB1- interneurons responded differently during long-duration compared to short-duration SWRs (two-way, one-sample t-tests against 0 for each subtype and condition: CB+/SATB1+ PRE: -0.034 ± 0.373, p = 0.77; CB+/SATB1+ POST: 0.068 ± 0.263, p = 0.41; CB+/SATB1- PRE: -0.078 ± 0.333, p = 0.56; CB+/SATB1- POST: 0.058 ± 0.374, p = 0.69). Data from 12 CB+/SATB1+ and 8 CB+/SATB1- cells from n = 13 mice. Data reported as mean ± s.d. * p < 0.05, ** p < 0.01, *** p < 0.001.

Source data

Extended Data Fig. 8 Additional data on learning-related CA3/CA2 interneuron dynamics during the GOL task.

(a) Quantification of the peri-SWR modulation for CA3 AACs, SOMs, and CBs during PRE and POST sessions on Learning Days. None of these three subtypes significantly changed their activity around SWRs after learning (AAC PRE: -0.350 ± 0.217, AAC POST: -0.416 ± 0.211, two-sided Wilcoxon signed-rank test: p = 0.33; SOM PRE: -0.571 ± 0.275, SOM POST: -0.555 ± 0.334, two-sided Wilcoxon signed-rank test: p = 0.68; CB PRE: -0.322 ± 0.135, CB POST: -0.335 ± 0.227, two-sided Wilcoxon signed-rank test: p = 0.69). Data from n = 17 AACs, 18 SOMs, and 5 CBs from n = 8 mice. CB+/SATB1+ and CB/SATB1- neurons are considered together in the CB subtype. Data reported as mean ± s.d. (b) Average Z-scored peri-SWR traces for both PRE and POST sessions for all CA2 subtypes on Learning Days. Data from 27 PRE and 26 POST PVBCs, 21 PRE and 19 POST AACs, 27 PRE and 27 POST SOMs, 14 PRE and 14 POST CCKs, and 18 PRE and 16 POST CBs from n = 8 mice. CB/SATB1+ and CB/SATB1- neurons are considered together in the CB subtype. Traces for each subtype and condition represent mean ± s.e.m. (c) Average Z-scored peri-SWR traces for both PRE and POST sessions for all CA3 subtypes on Non-Learning Days. Data from 15 PRE and 16 POST PVBCs, 4 PRE and 4 POST AACs, 26 PRE and 25 POST SOMs, 4 PRE and 4 POST CCKs, and 2 PRE and 2 POST CBs from n = 8 mice. CB/SATB1+ and CB/SATB1- neurons are considered together in the CB subtype. Traces for each subtype and condition represent mean ± s.e.m. (d) Quantification of the change in peri-SWR modulation for CA3 PVBCs and CCKs between PRE and POST sessions on Non-Learning Days. Neither subtype changed its activity significantly after the GOL task (PVBC PRE: 0.360 ± 0.581, PVBC POST: 0.460 ± 0.370, two-sided Wilcoxon signed-rank test: p = 0.39; CCK PRE: -0.433 ± 0.195, CCK POST: -0.390 ± 0.177, two-sided Wilcoxon signed-rank test: p = 0.59; data from n = 15 PVBCs and 3 CCKs from n = 8 mice). Data reported as mean ± s.d. * p < 0.05, ** p < 0.01, *** p < 0.001.

Source data

Extended Data Fig. 9 CA3 interneuron dynamics during the random cue task.

(a) Sensory stimulation paradigm. Water, light, and odor stimuli were presented pseudorandomly while the mouse remained head-fixed on a cue-less, burlap belt. Interneurons were imaged during SWRs in both the PRE and POST sessions as well as during stimulus presentations. (b) Representative example of an individual AAC (green) and CCK (orange) interneuron. Heatmaps represent the activity during all sensory stimulus presentations (45 in total) with the corresponding average response (bottom). The CCK neuron is consistently and significantly activated by cue presentations. The traces are plotted as the mean ± s.e.m. (c) Average sensory cue response for each cell, grouped by subtype (PVBC response: 0.078 ± 0.231, AAC: -0.032 ± 0.208, SOM: -0.145 ± 0.215, CCK: 0.328 ± 0.252, CB: 0.038 ± 0.349). CCK cells were significantly activated by cue presentation, while SOM cells were significantly inhibited (two-way, one-sample t-tests against 0 for each subtype: PVBC: p = 0.12; AAC: p = 0.41; SOM: p = 4.17 × 10–4; CCK: p = 0.0021; CB: p = 0.73). Data from n = 24 PVBCs, 31 AACs, 35 SOMs, 11 CCKs, and 12 CBs from n = 3 mice. CB+/SATB1+ and CB+/SATB1- neurons are considered together in the CB subtype. All reported cells are from CA3; CA2 data not reported. Data reported as mean ± s.d. (d) Sessions PRE and POST cue presentations are split to examine whether sensory cue presentations induced a change in interneuron dynamics around SWRs. (e) Quantification of the average SWR occurrence rate for PRE and POST sessions. The occurrence rate increased significantly from PRE to POST (occurrence PRE: 0.273 ± 0.115 s-1, occurrence POST: 0.354 ± 0.169 s-1, two-sided Wilcoxon signed-rank test: p = 0.0024). Data from n = 26 PRE sessions and 26 POST sessions from n = 5 mice. Data reported as mean ± s.d. (f) Quantification of the average SWR duration for PRE and POST sessions. The SWR duration did not change between PRE and POST sessions (duration PRE: 82.7 ± 13.6 ms, POST: 81.8 ± 13.0 ms, two-sided Wilcoxon signed-rank test: p = 0.28). Data from n = 26 PRE sessions and 26 POST sessions from n = 5 mice. Data reported as mean ± s.d. (g) Quantification of the average SWR maximum amplitude for PRE and POST sessions. The amplitude did not change between PRE and POST sessions (amplitude PRE: 137.3 ± 52.3 µV, POST: 136.6 ± 57.3 µV, two-sided Wilcoxon signed-rank test: p = 0.66). Data from n = 26 PRE sessions and 26 POST sessions from n = 5 mice. Data reported as mean ± s.d. (h) Average Z-scored peri-SWR traces for both PRE and POST sessions for all subtypes. Data from 31 PRE and 32 POST PVBCs, 37 PRE and 34 POST AACs, 49 PRE and 51 POST SOMs, 14 PRE and 15 POST CCKs, and 7 PRE and 7 POST CBs from n = 5 mice. CB+/SATB1+ and CB+/SATB1- neurons are considered together in the CB subtype. All reported cells are from CA3; CA2 data are not reported. Traces for each subtype and condition represent mean ± s.e.m. (i) Quantification of the change in SWR modulation for CA3 PVBCs between PRE and POST sessions. PVBCs did not become more activated around SWRs in response to the sensory stimulation task (PVBC PRE: 0.67 ± 0.44, PVBC POST: 0.62 ± 0.44, two-sided Wilcoxon signed-rank test: p = 0.64; data from n = 31 PVBCs from n = 5 mice). Data reported as mean ± s.d. (j) Quantification of the change in SWR modulation for CA3 CCKs between PRE and POST sessions. CCKs did not become more inhibited around SWRs in response to the sensory stimulation task (CCK PRE: -0.36 ± 0.17, CCK POST: -0.32 ± 0.25, two-sided Wilcoxon signed-rank test: p = 0.23). Data from n = 15 CCKs from n = 5 mice. Data reported as mean ± s.d. * p < 0.05, ** p < 0.01, ***p < 0.001.

Source data

Supplementary information

Reporting Summary

Supplementary Table 1

Supplementary Table 1. Statistical summary for main and Extended Data figures.

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

Source Data Fig. 5

Statistical source data.

Source Data Fig. 6

Statistical source data.

Source Data Extended Data Fig. 2

Statistical source data.

Source Data Extended Data Fig. 3

Statistical source data.

Source Data Extended Data Fig. 5

Statistical source data.

Source Data Extended Data Fig. 6

Statistical source data.

Source Data Extended Data Fig. 7

Statistical source data.

Source Data Extended Data Fig. 8

Statistical source data.

Source Data Extended Data Fig. 9

Statistical source data.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Vancura, B., Geiller, T., Grosmark, A. et al. Inhibitory control of sharp-wave ripple duration during learning in hippocampal recurrent networks. Nat Neurosci 26, 788–797 (2023). https://doi.org/10.1038/s41593-023-01306-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41593-023-01306-7

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing