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Hippocampus shapes entorhinal cortical output through a direct feedback circuit

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Abstract

Our brains integrate sensory, cognitive and internal state information with memories to extract behavioral relevance. Cortico–hippocampal interactions likely mediate this interplay, but underlying circuit mechanisms remain elusive. Unlike the entorhinal cortex-to-hippocampus pathway, we know little about the organization and function of the hippocampus-to-cortex feedback circuit. Here we report in mice, two functionally distinct parallel hippocampus-to-entorhinal cortex feedback pathways: the canonical disynaptic route via layer 5 and a novel monosynaptic input to layer 2/3. Circuit mapping reveals that hippocampal input predominantly drives excitation in layer 5 but feed-forward inhibition in layer 2/3. Upon repetitive pairing with cortical layer 1 inputs, hippocampal inputs undergo homosynaptic potentiation in layer 5, but induce heterosynaptic plasticity and spike output in layer 2/3. Behaviorally, hippocampal inputs to layer 5 and layer 2/3 support object memory encoding versus recall, respectively. Two-photon imaging during navigation reveals hippocampal suppression reduces spatially tuned cortical axonal activity. We present a model, where hippocampal feedback could iteratively shape ongoing cortical processing.

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Fig. 1: Anterograde viral tracing identifies hippocampal feedback to superficial layers of the EC.
Fig. 2: Retrograde viral tracing confirms monosynaptic hippocampal feedback to superficial layers of the EC.
Fig. 3: Hippocampal feedback recruits strong excitation upon ECL5 neurons, but predominantly feed-forward inhibition upon ECL2/3 neurons.
Fig. 4: HC–ECL2/3 feedback heterosynaptically modulates L1-driven output in the EC.
Fig. 5: Silencing HC–ECL2/3 input during recall impairs task performance in novel object-recognition behaviors.

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Data availability

Experimental data from anatomy, physiology, imaging and behavior are available on Zenodo via https://doi.org/10.5281/zenodo.14768533 (ref. 112).

Following publication, neuronal morphological reconstruction data will be submitted to https://neuromorpho.org/.

Code availability

All the code used in the analysis and generation of two-photon calcium imaging figures is available on GitHub (https://github.com/basulab-nyu/) and Zenodo (https://doi.org/10.5281/zenodo.14768533)112.

The models built for this study and the computer code will be uploaded online after publication on GitHub (https://github.com/clopath/hippocampus_feedback_circuit).

Change history

  • 28 March 2025

    In the version of the article initially published, the outlines in the box and whisker plot on the far-right of Fig. 5f (ECL5, Jaws, Novel) were shifted down from the data points during figure preparation and have now been amended in the HTML and PDF versions of the article.

References

  1. Aggleton, J. P. Multiple anatomical systems embedded within the primate medial temporal lobe: implications for hippocampal function. Neurosci. Biobehav. Rev. 36, 1579–1596 (2012).

    Article  PubMed  Google Scholar 

  2. Bonnevie, T. et al. Grid cells require excitatory drive from the hippocampus. Nat. Neurosci. 16, 309–317 (2013).

    Article  CAS  PubMed  Google Scholar 

  3. Goshen, I. et al. Dynamics of retrieval strategies for remote memories. Cell 147, 678–689 (2011).

    Article  CAS  PubMed  Google Scholar 

  4. Buzsáki, G. & Moser, E. I. Memory, navigation and theta rhythm in the hippocampal-entorhinal system. Nat. Neurosci. 16, 130–138 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Suh, J., Rivest, A. J., Nakashiba, T., Tominaga, T. & Tonegawa, S. Entorhinal cortex layer III input to the hippocampus is crucial for temporal association memory. Science 334, 1415–1420 (2011).

    Article  CAS  PubMed  Google Scholar 

  6. Igarashi, K. M., Lu, L., Colgin, L. L., Moser, M. -B. & Moser, E. I. Coordination of entorhinal-hippocampal ensemble activity during associative learning. Nature 510, 143–147 (2014).

    Article  CAS  PubMed  Google Scholar 

  7. Remondes, M. & Schuman, E. M. Role for a cortical input to hippocampal area CA1 in the consolidation of a long-term memory. Nature 431, 699–703 (2004).

    Article  CAS  PubMed  Google Scholar 

  8. Squire, L. R. & Wixted, J. T. The cognitive neuroscience of human memory since H.M. Annu. Rev. Neurosci. 34, 259–288 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Eichenbaum, H., Sauvage, M., Fortin, N., Komorowski, R. & Lipton, P. Towards a functional organization of episodic memory in the medial temporal lobe. Neurosci. Biobehav. Rev. 36, 1597–1608 (2012).

    Article  PubMed  Google Scholar 

  10. Knierim, J. J., Neunuebel, J. P. & Deshmukh, S. S. Functional correlates of the lateral and medial entorhinal cortex: objects, path integration and local-global reference frames. Philos. Trans. R. Soc. Lond. B 369, 20130369 (2014).

    Article  Google Scholar 

  11. Zemla, R. & Basu, J. Hippocampal function in rodents. Curr. Opin. Neurobiol. 43, 187–197 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Sürmeli, G. et al. Molecularly defined circuitry reveals input-output segregation in deep layers of the medial entorhinal cortex. Neuron 88, 1040–1053 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Witter, M. P., Doan, T. P., Jacobsen, B., Nilssen, E. S. & Ohara, S. Architecture of the entorhinal cortex: a review of entorhinal anatomy in rodents with some comparative notes. Front. Syst. Neurosci. 11, 46 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Cenquizca, L. A. & Swanson, L. W. Spatial organization of direct hippocampal field CA1 axonal projections to the rest of the cerebral cortex. Brain Res. Rev. 56, 1–26 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Ino, T., Kaneko, T. & Mizuno, N. Projections from the hippocampal and parahippocampal regions to the entorhinal cortex. An anterograde and retrograde tract-tracing study in the cat. Neurosci. Res. 39, 51–69 (2001).

    Article  CAS  PubMed  Google Scholar 

  16. Rockland, K. S. & DeFelipe, J. Editorial: why have cortical layers? what is the function of layering? do neurons in cortex integrate information across different layers? Front. Neuroanat. 12, 78 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Beed, P. et al. Layer 3 pyramidal cells in the medial entorhinal cortex orchestrate up-down states and entrain the deep layers differentially. Cell Rep. 33, 108470 (2020).

    Article  CAS  PubMed  Google Scholar 

  18. Rolls, E. T. & Mills, W. P. C. Computations in the deep vs superficial layers of the cerebral cortex. Neurobiol. Learn. Mem. 145, 205–221 (2017).

    Article  PubMed  Google Scholar 

  19. Gnatkovsky, V. & de Curtis, M. Hippocampus-mediated activation of superficial and deep layer neurons in the medial entorhinal cortex of the isolated guinea pig brain. J. Neurosci. 26, 873–881 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Maass, A. et al. Laminar activity in the hippocampus and entorhinal cortex related to novelty and episodic encoding. Nat. Commun. 5, 5547 (2014).

    Article  CAS  PubMed  Google Scholar 

  21. Stuart, G., Spruston, N & Häusser, M. in Dendrites 3rd edn (eds Stuart, G. et al.) 351–398 (Oxford University Press, 2016).

  22. Duncan, K., Ketz, N., Inati, S. J. & Davachi, L. Evidence for area CA1 as a match/mismatch detector: a high-resolution fMRI study of the human hippocampus. Hippocampus 22, 389–398 (2012).

    Article  PubMed  Google Scholar 

  23. Lipton, P. A. & Eichenbaum, H. Complementary roles of hippocampus and medial entorhinal cortex in episodic memory. Neural Plast. 2008, 258467 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Fuchsberger, T. & Paulsen, O. Modulation of hippocampal plasticity in learning and memory. Curr. Opin. Neurobiol. 75, 102558 (2022).

    Article  CAS  PubMed  Google Scholar 

  25. Kitamura, T. et al. Island cells control temporal association memory. Science 343, 896–901 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Rowland, D. C. et al. Transgenically targeted rabies virus demonstrates a major monosynaptic projection from hippocampal area CA2 to medial entorhinal layer II neurons. J. Neurosci. 33, 14889–14898 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Blankvoort, S., Witter, M. P., Noonan, J., Cotney, J. & Kentros, C. Marked diversity of unique cortical enhancers enables neuron-specific tools by enhancer-driven gene expression. Curr. Biol. 28, 2103–2114 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Caballero-Bleda, M. & Witter, M. P. Projections from the presubiculum and the parasubiculum to morphologically characterized entorhinal-hippocampal projection neurons in the rat. Exp. Brain Res. 101, 93–108 (1994).

    Article  CAS  PubMed  Google Scholar 

  29. van Haeften, T., Baks-te-Bulte, L., Goede, P. H., Wouterlood, F. G. & Witter, M. P. Morphological and numerical analysis of synaptic interactions between neurons in deep and superficial layers of the entorhinal cortex of the rat. Hippocampus 13, 943–952 (2003).

    Article  PubMed  Google Scholar 

  30. Canto, C. B., Wouterlood, F. G. & Witter, M. P. What does the anatomical organization of the entorhinal cortex tell us? Neural Plast. 2008, 381243 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Cappaert, N. L. M., Van Strien, N. M. & Witter, M. P. Chapter 20—hippocampal formation. in The Rat Nervous System (Fourth Edition) (ed. G. Paxinos) 511–573 (Academic Press, 2015). https://doi.org/10.1016/B978-0-12-374245-2.00020-6

  32. Basu, J. et al. A cortico-hippocampal learning rule shapes inhibitory microcircuit activity to enhance hippocampal information flow. Neuron 79, 1208–1221 (2013).

    Article  CAS  PubMed  Google Scholar 

  33. Basu, J. et al. Gating of hippocampal activity, plasticity, and memory by entorhinal cortex long-range inhibition. Science 351, aaa5694 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Yeckel, M. F. & Berger, T. W. Feedforward excitation of the hippocampus by afferents from the entorhinal cortex: redefinition of the role of the trisynaptic pathway. Proc. Natl Acad. Sci. USA 87, 5832–5836 (1990).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Schomburg, E. W. et al. Theta phase segregation of input-specific gamma patterns in entorhinal-hippocampal networks. Neuron 84, 470–485 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Zhang, L., Lee, J., Rozell, C. & Singer, A. C. Sub-second dynamics of theta-gamma coupling in hippocampal CA1. eLife 8, e44320 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Hirase, H., Leinekugel, X., Czurkó, A., Csicsvari, J. & Buzsáki, G. Firing rates of hippocampal neurons are preserved during subsequent sleep episodes and modified by novel awake experience. Proc. Natl Acad. Sci. USA 98, 9386–9390 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Mizuseki, K. & Buzsáki, G. Preconfigured, skewed distribution of firing rates in the hippocampus and entorhinal cortex. Cell Rep. 4, 1010–1021 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Frank, L. M., Brown, E. N. & Wilson, M. Trajectory encoding in the hippocampus and entorhinal cortex. Neuron 27, 169–178 (2000).

    Article  CAS  PubMed  Google Scholar 

  40. Littman, M. L. Reinforcement learning improves behaviour from evaluative feedback. Nature 521, 445–451 (2015).

    Article  CAS  PubMed  Google Scholar 

  41. Mnih, V. et al. Human-level control through deep reinforcement learning. Nature 518, 529–533 (2015).

    Article  CAS  PubMed  Google Scholar 

  42. Silver, D. et al. A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play. Science 362, 1140–1144 (2018).

    Article  CAS  PubMed  Google Scholar 

  43. Moore, J. et al. Sub-cellular population imaging tools reveal stable apical dendrites in hippocampal area CA3. Nat. Commun. 16, 1119 (2025).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Robert, V. et al. Entorhinal cortex glutamatergic and GABAergic projections bidirectionally control discrimination and generalization of hippocampal representations. Preprint at bioRxiv https://doi.org/10.1101/2023.11.08.566107 (2023).

  45. Zemla, R., Moore, J. J., Hopkins, M. D. & Basu, J. Task-selective place cells show behaviorally driven dynamics during learning and stability during memory recall. Cell Rep. 41, 111700 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Bowler, J. C. & Losonczy, A. Direct cortical inputs to hippocampal area CA1 transmit complementary signals for goal-directed navigation. Neuron 111, 4071–4085 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Grienberger, C. & Magee, J. C. Entorhinal cortex directs learning-related changes in CA1 representations. Nature 611, 554–562 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Hafting, T., Fyhn, M., Molden, S., Moser, M. -B. & Moser, E. I. Microstructure of a spatial map in the entorhinal cortex. Nature 436, 801–806 (2005).

    Article  CAS  PubMed  Google Scholar 

  49. Hargreaves, E. L., Rao, G., Lee, I. & Knierim, J. J. Major dissociation between medial and lateral entorhinal input to dorsal hippocampus. Science 308, 1792–1794 (2005).

    Article  CAS  PubMed  Google Scholar 

  50. Barnes, C. A. Memory deficits associated with senescence: a neurophysiological and behavioral study in the rat. J. Comp. Physiol. Psychol. 93, 74–104 (1979).

    Article  CAS  PubMed  Google Scholar 

  51. Antunes, M. & Biala, G. The novel object recognition memory: neurobiology, test procedure, and its modifications. Cogn. Process. 13, 93–110 (2012).

    Article  CAS  PubMed  Google Scholar 

  52. Meeter, M., Murre, J. M. J. & Talamini, L. M. Mode shifting between storage and recall based on novelty detection in oscillating hippocampal circuits. Hippocampus 14, 722–741 (2004).

    Article  CAS  PubMed  Google Scholar 

  53. Lörincz, A. & Buzsáki, G. Two-phase computational model training long-term memories in the entorhinal-hippocampal region. Ann. N. Y. Acad. Sci. 911, 83–111 (2000).

    Article  PubMed  Google Scholar 

  54. Duncan, K., Curtis, C. & Davachi, L. Distinct memory signatures in the hippocampus: intentional States distinguish match and mismatch enhancement signals. J. Neurosci. 29, 131–139 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Berteau, S. & Bullock, D. Simulations reveal how M-currents and memory-based inputs from CA3 enable single neuron mismatch detection for EC3 inputs to the CA1 subfield of hippocampus. J. Neurophysiol. 124, 544–556 (2020).

    Article  PubMed  Google Scholar 

  56. Kumaran, D. & Maguire, E. A. Match–mismatch processes underlie human hippocampal responses to associative novelty. J. Neurosci. 27, 8517–8524 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Masurkar, A. V. et al. Postsynaptic integrative properties of dorsal CA1 pyramidal neuron subpopulations. J. Neurophysiol. 123, 980–992 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Amaral, D. G. & Witter, M. P. The three-dimensional organization of the hippocampal formation: a review of anatomical data. Neuroscience 31, 571–591 (1989).

    Article  CAS  PubMed  Google Scholar 

  59. Bilash, O. M., Chavlis, S., Johnson, C. D., Poirazi, P. & Basu, J. Lateral entorhinal cortex inputs modulate hippocampal dendritic excitability by recruiting a local disinhibitory microcircuit. Cell Rep. 42, 111962 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Caputi, A., Liu, X., Fuchs, E. C., Liu, Y. -C. & Monyer, H. Medial entorhinal cortex commissural input regulates the activity of spatially and object-tuned cells contributing to episodic memory. Neuron 110, 3389–3405 (2022).

    Article  CAS  PubMed  Google Scholar 

  61. Ohara, S. et al. Hippocampal-medial entorhinal circuit is differently organized along the dorsoventral axis in rodents. Cell Rep. 42, 112001 (2023).

    Article  CAS  PubMed  Google Scholar 

  62. Ben-Simon, Y. et al. A direct excitatory projection from entorhinal layer 6b neurons to the hippocampus contributes to spatial coding and memory. Nat. Commun. 13, 4826 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Rozov, A. et al. Processing of hippocampal network activity in the receiver network of the medial entorhinal cortex layer V. J. Neurosci. 40, 8413–8425 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Ohara, S. et al. Local projections of layer Vb-to-Va are more prominent in lateral than in medial entorhinal cortex. eLife 10, e67262 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Basu, J. & Siegelbaum, S. A. The corticohippocampal circuit, synaptic plasticity, and memory. Cold Spring Harb. Perspect. Biol. 7, a021733 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  66. Ashida, G. & Carr, C. E. Sound localization: Jeffress and beyond. Curr. Opin. Neurobiol. 21, 745–751 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Mizuseki, K., Sirota, A., Pastalkova, E. & Buzsáki, G. Theta oscillations provide temporal windows for local circuit computation in the entorhinal-hippocampal loop. Neuron 64, 267–280 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Yamazaki, T. & Tanaka, S. Computational models of timing mechanisms in the cerebellar granular layer. Cerebellum 8, 423–432 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  69. Rutherford, M. A., von Gersdorff, H. & Goutman, J. D. Encoding sound in the cochlea: from receptor potential to afferent discharge. J. Physiol. 599, 2527–2557 (2021).

    Article  CAS  PubMed  Google Scholar 

  70. Almog, N. et al. During hippocampal inactivation, grid cells maintain synchrony, even when the grid pattern is lost. eLife 8, e47147 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  71. Bush, D., Barry, C. & Burgess, N. What do grid cells contribute to place cell firing? Trends Neurosci. 37, 136–145 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Rolls, E. T., Stringer, S. M. & Elliot, T. Entorhinal cortex grid cells can map to hippocampal place cells by competitive learning. Network 17, 447–465 (2006).

    Article  PubMed  Google Scholar 

  73. Solstad, T., Moser, E. I. & Einevoll, G. T. From grid cells to place cells: a mathematical model. Hippocampus 16, 1026–1031 (2006).

    Article  PubMed  Google Scholar 

  74. Hartley, T., Burgess, N., Lever, C., Cacucci, F. & O’Keefe, J. Modeling place fields in terms of the cortical inputs to the hippocampus. Hippocampus 10, 369–379 (2000).

    Article  CAS  PubMed  Google Scholar 

  75. Moser, E. I., Kropff, E. & Moser, M. -B. Place cells, grid cells, and the brain’s spatial representation system. Annu. Rev. Neurosci. 31, 69–89 (2008).

    Article  CAS  PubMed  Google Scholar 

  76. Knierim, J. J., Kudrimoti, H. S. & McNaughton, B. L. Place cells, head direction cells, and the learning of landmark stability. J. Neurosci. 15, 1648–1659 (1995).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Fyhn, M., Molden, S., Witter, M. P., Moser, E. I. & Moser, M. -B. Spatial representation in the entorhinal cortex. Science 305, 1258–1264 (2004).

    Article  CAS  PubMed  Google Scholar 

  78. Solstad, T., Boccara, C. N., Kropff, E., Moser, M. -B. & Moser, E. I. Representation of geometric borders in the entorhinal cortex. Science 322, 1865–1868 (2008).

    Article  CAS  PubMed  Google Scholar 

  79. Butler, W. N., Hardcastle, K. & Giocomo, L. M. Remembered reward locations restructure entorhinal spatial maps. Science 363, 1447–1452 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Giocomo, L. M. et al. Topography of head direction cells in medial entorhinal cortex. Curr. Biol. 24, 252–262 (2014).

    Article  CAS  PubMed  Google Scholar 

  81. Kropff, E., Carmichael, J. E., Moser, M. -B. & Moser, E. I. Speed cells in the medial entorhinal cortex. Nature 523, 419–424 (2015).

    Article  CAS  PubMed  Google Scholar 

  82. Hinman, J. R., Brandon, M. P., Climer, J. R., Chapman, G. W. & Hasselmo, M. E. Multiple running speed signals in medial entorhinal cortex. Neuron 91, 666–679 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Diehl, G. W., Hon, O. J., Leutgeb, S. & Leutgeb, J. K. Grid and nongrid cells in medial entorhinal cortex represent spatial location and environmental features with complementary coding schemes. Neuron 94, 83–92 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Killian, N. J., Jutras, M. J. & Buffalo, E. A. A map of visual space in the primate entorhinal cortex. Nature 491, 761–764 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Sato, M. et al. Hippocampus-dependent goal localization by head-fixed mice in virtual reality. eNeuro https://doi.org/10.1523/ENEURO.0369-16.2017 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  86. Schlesiger, M. I. et al. Hippocampal activation during the recall of remote spatial memories in radial maze tasks. Neurobiol. Learn. Mem. 106, 324–333 (2013).

    Article  CAS  PubMed  Google Scholar 

  87. Binder, S. et al. Monosynaptic hippocampal-prefrontal projections contribute to spatial memory consolidation in mice. J. Neurosci. 39, 6978–6991 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Shao, Q. et al. A non-canonical visual cortical-entorhinal pathway contributes to spatial navigation. Nat. Commun. 15, 4122 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Wahlstrom, K. L. et al. Basolateral amygdala inputs to the medial entorhinal cortex selectively modulate the consolidation of Spatial and contextual learning. J. Neurosci. 38, 2698–2712 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Squire, L. R., Wixted, J. T. & Clark, R. E. Recognition memory and the medial temporal lobe: a new perspective. Nat. Rev. Neurosci. 8, 872–883 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Broadbent, N. J., Gaskin, S., Squire, L. R. & Clark, R. E. Object recognition memory and the rodent hippocampus. Learn. Mem. 17, 5–11 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  92. Molas, S. et al. A circuit-based mechanism underlying familiarity signaling and the preference for novelty. Nat. Neurosci. 20, 1260–1268 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Tsien, J. Z. et al. Subregion- and cell type-restricted gene knockout in mouse brain. Cell 87, 1317–1326 (1996).

    Article  CAS  PubMed  Google Scholar 

  94. Madisen, L. et al. A robust and high-throughput Cre reporting and characterization system for the whole mouse brain. Nat. Neurosci. 13, 133–140 (2010).

    Article  CAS  PubMed  Google Scholar 

  95. Lee, J. H. et al. Global and local fMRI signals driven by neurons defined optogenetically by type and wiring. Nature 465, 788–792 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Klapoetke, N. C. et al. Independent optical excitation of distinct neural populations. Nat. Methods 11, 338–346 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Nilssen, E. S. et al. Inhibitory connectivity dominates the fan cell network in layer II of lateral entorhinal cortex. J. Neurosci. 38, 9712–9727 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Wickersham, I. R., Sullivan, H. A. & Seung, H. S. Production of glycoprotein-deleted rabies viruses for monosynaptic tracing and high-level gene expression in neurons. Nat. Protoc. 5, 595–606 (2010).

    Article  CAS  PubMed  Google Scholar 

  99. Krashes, M. J. et al. Rapid, reversible activation of AgRP neurons drives feeding behavior in mice. J. Clin. Invest. 121, 1424–1428 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Chen, T. -W. et al. Ultrasensitive fluorescent proteins for imaging neuronal activity. Nature 499, 295–300 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Chuong, A. S. et al. Noninvasive optical inhibition with a red-shifted microbial rhodopsin. Nat. Neurosci. 17, 1123–1129 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Oh, S. W. et al. A mesoscale connectome of the mouse brain. Nature 508, 207–214 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Susaki, E. A. et al. Advanced CUBIC protocols for whole-brain and whole-body clearing and imaging. Nat. Protoc. 10, 1709–1727 (2015).

    Article  CAS  PubMed  Google Scholar 

  104. Canto, C. B. & Witter, M. P. Cellular properties of principal neurons in the rat entorhinal cortex II. The medial entorhinal cortex. Hippocampus 22, 1277–1299 (2012).

    Article  PubMed  Google Scholar 

  105. Petreanu, L., Mao, T., Sternson, S. M. & Svoboda, K. The subcellular organization of neocortical excitatory connections. Nature 457, 1142–1145 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Witter, M. P. in Hippocampal Microcircuits: a Computational Modeler’s Resource Book (eds Cutsuridis, V. et al.) 5–26 (Springer, 2010).

  107. Paxinos, G. & Franklin, K. The Mouse Brain in Stereotaxic Coordinates (Academic Press, 2012).

  108. Moore, J. J., Robert, V., Rashid, S. K. & Basu, J. Assessing local and branch-specific activity in dendrites. Neuroscience 489, 143–164 (2022).

    Article  CAS  PubMed  Google Scholar 

  109. Pachitariu, M. et al. Suite2p: beyond 10,000 neurons with standard two-photon microscopy. Preprint at bioRxiv https://doi.org/10.1101/061507 (2017).

  110. Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).

    Article  CAS  PubMed  Google Scholar 

  111. Skaggs, W. E., McNaughton, B. L., Gothard, K. M. & Markus, E. J. An information theoretic approach to deciphering the hippocampal code. Adv. Neural Inf. Process. 5, 1030–1037 (1993).

    Google Scholar 

  112. Butola, T. & Basu, J. Hippocampus shapes entorhinal cortical output and novelty coding through a direct feedback circuit. Zenodo https://doi.org/10.5281/zenodo.14768533 (2024).

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Acknowledgements

This work was supported by the following grants to J.B.: NIH NINDS 1R01NS109362-01, NIH NIMH 3R01MH122391, NIH NINDS 1RM1NS132981, Alzheimer’s Association AARGD-NTF-23-1151101, Parekh Center for Interdisciplinary Neurology (PCIN) Pilot Research Grant, Mathers Charitable Foundation Investigator Award, McKnight Scholar Award in Neuroscience, Klingenstein Fund—Simons Foundation Fellowship Award in Neuroscience, Alfred P. Sloan Research Fellowship, Whitehall Research Grant, American Epilepsy Society Junior Investigator Award, Blas Frangione Young Investigator Research Grant, New York University Whitehead Fellowship for Junior Faculty in Biomedical and Biological Sciences and Leon Levy Foundation Award. The collaborative effort was supported by NIH BRAIN INITIATIVE grant 1R01NS109994 to J.B., C.C. and C.K. T.B. was supported by Leon Levy Foundation postdoctoral fellowship, FACES Award (Finding A Cure for Epilepsy & Seizures award) by New York University Langone Health and Comprehensive Epilepsy Center, and Collaborative and Research Pilot Project Award, CTSI (Clinical and Translational Science Institute) by New York University Langone Health. M.H.-F. was supported by REC Scholar Program of NYU Alzheimer’s Disease Research Center (ADRC) P30 AG066512, and the Alzheimer’s Association grant 23AARFD-1026841 fellowship. A.H. was supported by an Irene & Eric Simon (IES) Brain Research Foundation grant. C.D.J. was supported by NIH NIMH Diversity Supplement 3R01MH122391-04S1. F.H. was supported by McKnight Endowment Fund for Neuroscience Mathew Pecot Award for Training Underrepresented Minority Students. We thank R. Froemke, M. Long, D. Lin, O. Bilash, V. Robert and R. Tsien for helpful discussion on earlier versions of the paper. We thank A. Mar and C. Denny for their advice on freely moving behavior analysis and interpretation of results. We thank M. Dufour and S. Sundar for their input and technical support during the early stages of the project, and J. Moore for input and support on the in vivo imaging data analysis.

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T.B. and J.B. conceptualized and designed the study. J.B. secured primary funding, supervised and coordinated the project. T.B. and L.P. acquired and analyzed the anterograde tracing data. A.H. acquired and analyzed the data for dissociating CA1 versus subiculum projections. S.B. and M.S.F. acquired and analyzed the retrograde rabies tracing data. T.B. performed, acquired data for and analyzed all the electrophysiology experiments. F.H. reconstructed the recorded neurons. C.C. performed all the modeling. T.B. performed and acquired data for the in vivo two-photon calcium imaging, and analyzed the data with assistance from A.A. T.B. and M.H.-F. performed the surgeries for the in vivo experiments. M.H.-F. performed (with assistance from C.D.J. during revision experiments), acquired and analyzed data for all the behavior experiments with statistical analysis provided by T.B. T.B., with assistance from F.H. and C.D.J., performed the post hoc immunohistochemistry and imaging for in vivo imaging and behavior experiments. M.E. and A.H. contributed to the early-stage characterization and optimization of viral serotypes and incubation windows for functional and anatomical mapping experiments. T.B. prepared all the figures for visualization with input from J.B., S.B., C.C. and M.H.-F. T.B. and J.B. wrote the original manuscript with input from M.H.-F., S.B., C.K. and C.C.

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Correspondence to Jayeeta Basu.

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Extended data

Extended Data Fig. 1 Injection site in dorsal hippocampus CA1.

a-b. Schematic depicting horizontal sections through the mouse brain at ventral distance of -1600 µm (a) and -2800 µm (b) from bregma. AAV 2.5 EF1α-double floxed-ChR2-eYFP injected into dorsal CA1 (a; inset). Abbreviations used: Sub – subiculum, dentate gyrus (DG), lateral ventricle (LV), PrS – presubiculum, PaS – parasubiculum, MEC – medial entorhinal cortex, PRh – perirhinal cortex, and TeA – temporal association cortex. c. Confocal image of a brain slice of a mouse injected with AAV 2.5 EF1α-double floxed-ChR2-eYFP into dorsal CA1 and immunostained for GFP to demarcate the injection site (left). The viral infection is contained within CA1 and subiculum (marked by white arrowhead). Expanded views of the areas within the white dotted boxes on the right show infected CA1 pyramidal neurons (top), and no infection in the adjacent area CA2 (bottom). Duration of viral incubation is depicted on bottom right corner (d16). d. Confocal image of horizontal brain slice from the same mouse as in c immunostained for GFP. Green hippocampal axons were observed in entorhinal cortex (EC) layers 5 and 2/3. White dotted lines demarcate the different cortical layers and brain regions. Note the absence of infected neurons in EC. e. Same as c but the duration of viral incubation was 21 days. f. Same as d but the duration of viral incubation was 21 days. g. Same as c but the duration of viral incubation was 21 days. h. Same as d but the duration of viral incubation was 21 days. i. Same as c but the duration of viral incubation was 25 days. The slice was stained for GFP and DAPI (nuclear marker). j. Same as d but the duration of viral incubation was 25 days. k. Same as c but the duration of viral incubation was 25 days. l. Same as d but the duration of viral incubation was 25 days. m. Same as c but the duration of viral incubation was 25 days. n. Same as d but the duration of viral incubation was 25 days. A single infected neuron was observed in ECL2/3 pointed by the white arrowhead with a magnified view in the inset. This is an example of an animal that was excluded from the dataset due retrograde viral infection in cortical layers. All scale bars are 100 µm. For incubation days of 16, 21, and 25 days, we repeated the experiment 1, 10, and 3 times.

Extended Data Fig. 2 Dorsal to ventral axis of hippocampal projections to entorhinal cortex.

a. (a1) Schematic depicting a horizontal section of a mouse brain showing the various brain regions that are included in the confocal image in panel a2. The position of the horizontal plane of section through the mouse brain is reported as ventral distance from bregma (-2400 µm) in the bottom left corner. (a2) Confocal image of horizontal brain slice of a mouse injected with AAV 2.5 EF1α-double floxed-ChR2-eYFP into dorsal CA1 and immunostained for GFP and DAPI (nuclear marker). Green hippocampal axons were observed in medial entorhinal cortex (MEC) layers 5 and 2/3, and parasubiculum (experiment repeated 10 times with similar results). White dotted lines demarcate the different cortical layers and brain regions. Arrowheads point the layer detailed in panels a3 and a4. (a3) Magnified view of the hippocampal axons in ECL5, an area pointed by the white arrowhead labeled a3 in panel a2. (a4) Magnified view of the hippocampal axons in ECL2/3, an area pointed by the white arrowhead labeled a4 in panel a2. b. Same as a. but for -2800 µm from bregma. c. Same as a. but for -3200 µm from bregma. d. Same as a. but for -3600 µm from bregma. e. Same as a. but for -4000 µm from bregma. Abbreviations used: Au1 – primary auditory cortex, AuV – secondary auditory cortex ventral, DG – dentate gyrus, LEC – lateral entorhinal cortex, LV – lateral ventricle, MEC – medial entorhinal cortex, PaS – parasubiculum, PRh – perirhinal cortex, PrS – presubiculum, S2 – secondary somatosensory cortex, Sub – subiculum, TeA – temporal association cortex.

Extended Data Fig. 3 Validation of hippocampal feedback using different viral strategies.

a. Top - Confocal image of a horizontal brain slice of a CamKII-Cre mouse injected in dorsal CA1 with AAV 2.1 EF1α-double floxed-ChR2-eYFP (41.5 nl/site with 3 week incubation), immunostained for GFP and DAPI (nuclear marker). Green hippocampal axons were observed in entorhinal cortex layers 5 and 2/3. Center – Expanded view of the hippocampal projection to ECL5 shows no infected neurons. Bottom – Expanded view the hippocampal projection to ECL2/3 shows a sample infected ECL2/3 neuron. b. Similar to (a), but using AAV 2.9 EF1α-double floxed-ChR2-eYFP. Hippocampal axons target ECL5 and ECL2/3. No infected neurons in ECL5; one infected neuron observed in ECL2/3. c. Similar to (a), but with AAV 2.5 EF1α-double floxed-ChR2-eYFP (82.8 nl/site, 3-week incubation). Axons in ECL5 and ECL2/3. No infected neurons detected in either layer. d. Similar to (a), but with a C57Bl/6 mouse injected with AAV 2.2 CAMKII-ChR2-eYFP. Axons innervate ECL5 and ECL2/3; no infected neurons in either layer. e. Quantification of the number of infected neurons observed in EC after 3 weeks of viral incubation period. 41.4 nl of virus was injected per site for viral serotypes AAV 2.1 (n = 8), 2.2 (n = 8), and 2.9 (n = 22), and 82.8 nl per site for AAV 2.5 (n = 11). Data represented as box and whisker plots (median, upper/lower quartiles, min to max whiskers). Each data point represents number of infected neurons in a mouse. Fitting a full model two-way ANOVA showed a significant effect of serotype used (p-value < 0.0001), EC layer (p-value < 0.0001), and significant interaction between the two factors (p-value < 0.0001). Post-hoc Šidák’s multiple comparison test shows a significant difference in the infection between ECL2/3 and ECL5 for AAV 2.9 (**** - p-value < 0.0001). Post-hoc Tukey’s multiple comparisons test showed significant difference in the number of infected cells between all serotypes except AAV 2.2 and AAV 2.5 (**** - p-value < 0.0001). f. Representative confocal image of a horizontal brain slice of a CamKII-Cre mouse injected with AAV 2.5 EF1α-double floxed-ChR2-eYFP into dorsal CA1, immunostained for GFP, MAP2 (marker for dendrites), and DAPI (nuclear marker). Green hippocampal axons were observed in ECL5 and ECL2/3. Enlarged views (f1–f3) show no GFP-MAP2 colocalization, confirming no EC neuronal infection (3 independent experiments). g. Schematic showing the injection strategy used to isolate MECL2/3 projecting dCA1 neurons. As proof of principle in one wild-type mouse, we injected AAV 2.retro Syn Cre along with AAV 2.1 Syn Flex GCaMP6s in MECL2/3. In the same animal, we injected a Cre-dependent virus expressing mCherry in dorsal CA1. h. (h1) Confocal image of a horizontal brain slice from a mouse stained for RFP showing injection site (dorsal CA1) of AAV 2.5 Syn DIO hM4D mCherry. (h2) Confocal image of horizontal section from the same mouse as in h1 stained for RFP showing the injection site (green neurons) for AAV 2.1 SynFlex GCaMP6s and AAV 2.retro Syn Cre in ECL2/3. While we targeted MECL2/3 projecting hippocampal neurons, we see projections to MECL5 as well. i. Confocal image of a horizontal brain slice from a mouse injected as described in (g). Green GCaMP+ MECL2/3 axons present in SLM of dCA1 at loci of our viral injection coordinates showing hM4D-mCherry positive CA1 PNs.

Extended Data Fig. 4 Specificity of Double-virus Rabies Tracing.

a-b. Sections from two different transgenic animals showing the extent of 2A label, a proxy for starter cells. Dotted line is lamina dessicans, the border between L3 and deep layers of EC. Note the two distinct needle tracks, the restriction of 2A label to ECL3, and the fact that there is a “hole” in the 2A expression pattern (and cell death, as judged by NeuN staining) corresponding to the actual AAV injection sites. c. Zoom of the 4th section from the right in panel b, showing (c1) 2A label, (c2) rabies GFP expression, (c3) NeuN expression, and (c4) merged of the 3, with GFP in green, NeuN in purple, and 2A label in blue. Note that CA1 is a major input, nearly on par with the known major inputs, the deep layers of EC and Pre/Postsubiculum, as shown in Table 2. d. Zoom of c1-c4, respectively, showing the only instance where the two injections were visible in the same section, with the rabies track visible on the right (open yellow arrowhead) and the area of cell death resulting from the large bolus of the AAV injection on the left (solid yellow arrowhead). Note that rabies-GFP label tends to erase the 2 A label (circles), making the distinction between L3 starter cells and L3 presynaptic cells difficult to judge precisely. So our data cannot speak definitively on the interconnectivity of neurons within L3. The variability of the number of starter cells in our dataset comes from this fact, as well as the fact that the overlap between the two injections varies between animals, but they all point to the same basic results. All scale bars are 100 µm. The experiment was repeated in 4 animals with similar results.

Extended Data Fig. 5 Optogenetic circuit mapping reveals functional hippocampal feedback to ECL2/3 and ECL5 with pathway specific synaptic excitation-inhibition ratio and plasticity.

a. Schematic of direct and indirect circuits overlaid on a representative confocal image of a horizontal brain slice (10 animals, similar results). Green CA1 axons project to both ECL5 and ECL2/3. EC: entorhinal cortex, PrS: presubiculum, PaS: parasubiculum. be. Functional channelrhodopsin 2 (ChR2) expression restricted to hippocampal neurons. Top: Intrinsic firing and sag properties of CA1 pyramidal (b), ECL2/3 stellate (c), ECL2/3 pyramidal (d), and ECL5 pyramidal (e) neurons in response to current steps. Bottom: A 500 ms, 470 nm light pulse evokes sustained photocurrents in CA1 pyramidal neurons only, confirming no off-target ChR2 expression in ECL2/3 or ECL5 neurons. f. Representative voltage clamp recordings from ECL2/3 neuron to record excitatory and inhibitory postsynaptic currents (EPSC and IPSC respectively) at -80 mV and +10 mV respectively. Insets show parts of the trace enclosed in the dotted box. g. IPSC amplitudes in ECL2/3 neurons increase with LED intensity. Each blue trace: individual neuron (n = 10, N = 7 mice); bold red: mean ± SEM. h. EPSC amplitudes in ECL2/3 neurons as LED intensity increases. Each blue trace: individual neuron (n = 12, N = 6 mice); bold green: mean ± SEM. i. Same f. but for ECL5 neurons. j. IPSC amplitudes in ECL5 neurons. Gray traces: individual neurons (n = 10, N = 5 mice); bold red: mean ± SEM. k. EPSC amplitudes in ECL5 neurons. Gray traces: individual neurons (n = 9, N = 6 mice); bold green: mean ± SEM. l. Schematic of hippocampal feedback (green) to ECL2/3 (blue) and ECL5 (black), with multimodal input arriving at ECL1. Hippocampal input is optically stimulated, and ECL1 input is electrically stimulated. m. Example traces of post-synaptic potentials recorded in ECL2/3 pyramidal neuron in response to (from left to right) –: baseline ECL1 stimulation, paired ECL1 + HC inputs (20 ms interval, 1 Hz, 90 s), and ECL1 stimulation at 5 and 20 min post-pairing show long-term potentiation. n. Time window tuning for LTP induction in ECL2/3 neurons. Pairing intervals of 0, 5, 10, 20, 30, 40, 50 ms tested. Maximal LTP at 20 ms. Data: mean ± SEM. Number of neurons tested for each pairing interval (n) was as follows: 0 (n = 3), 5 (n = 5), 10 (n = 4), 20 (n = 7), 30 (n = 4), 40 (n = 4), and, 50 (n = 3) ms.

Extended Data Fig. 6 Rate based circuit model of direct hippocampal feedback modulation of cortical output in ECL2/3.

a. Schematic of a rate-based model: Two multimodal inputs (I1, I2) project onto an ECL2/3 read-out neuron with weights w1 and w2. In the hypothetical behavior task, only I1 is paired with hippocampal feedback, leading to ITDP-like potentiation of w1 (thick red arrow). b. Case 1 (Slice Condition): With intact HC → ECL2/3 but severed ECL2/3→HC connections, pairing I1 with hippocampal feedback increases w1 by ~1.5-fold, simulating slice ITDP results. The output of the unpaired input I2 remains unchanged. Potentiation scales with pairing repetitions and hippocampal feedback strength (blue=50, yellow=100, green=150 iterations). Case 2 (Intact Loop): Case 1 likely underestimates the effect due to severed axons (connections) between EC and HC. To answer whether learning rate increases with reciprocally driven activity between cortex and hippocampus, we simulated the in vivo condition where the whole ECL2/3→HC→ECL2/3 loop is intact. In this condition, the bar graph indicates that upon simulating an intact ECL2/3-HC-ECL2/3 loop, the same number of pairings of I1 with HC-ECL2/3 feedback and the subsequent reciprocal activation of the circuit sped up the learning rate and lead to a higher potentiation of I1 than seen in Case 1. Again, potentiation scales with pairing iterations and HC feedback strength (blue=50, yellow=100, green=150). Thus, our computational model suggests that reverberating activity in the reciprocal connections between hippocampus and ECL2/3 leads to a true feedback circuit, which iteratively improves the learning and output behavior of the system. Case 3: Silencing HC-EC loop – Upon silencing the entirety of the ECL2/3-HC-ECL2/3 loop, both the paired and unpaired inputs fail to potentiate as demonstrated by their weight holding at 1.0. Case 4: Silencing HC feedback – Silencing only the HC feedback to ECL2/3 is sufficient to eliminate the potentiation of the sensory input post-pairing.

Extended Data Fig. 7 Validation of injection site and goal-oriented learning in in vivo two-photon calcium imaging experiments.

a. (a1) Confocal image of horizontal brain slice stained for RFP showing injection of AAV 2.5 Syn DIO hM4D mCherry in dorsal CA1 of a CamKII-Cre mouse. (a2) Confocal image of horizontal section from the same mouse as in a1 stained for RFP and DAPI showing the injection site (green neurons) for AAV 2.1 SynFlex GCaMP6s in ECL2/3, and red hippocampal axons in ECL2/3 and ECL5. (a3-a4) Same as a2 but only green (a3) and red (a4) channels. b-d. Same as (a) for different animals used in the two-photon calcium imaging experiments. e. (e1) Confocal image of horizontal brain slice for RFP showing injection of AAV 2.5 Syn DIO hM4D mCherry in dorsal CA1 of a wildtype mouse. (e2) Confocal image of horizontal section from the same mouse as in e1 stained for RFP and DAPI showing the injection site (green neurons) for AAV 2.1 SynFlex GCaMP6s and AAV 2.retro Syn Cre in ECL2/3. While we targeted ECL2/3 projecting hippocampal neurons, we see red hippocampal axons to ECL5 as well. All scale bars are 100 µm. White dotted lines demarcate the different sub-regions of the hippocampus (CA1 or Sub – subiculum) or the different EC layers. The confocal images show all the five animals used in the experiment.

Extended Data Fig. 8 in vivo chemogenetic silencing of the hippocampal feedback alters medial entorhinal cortex activity in mice performing goal-oriented spatial learning task.

a. Experimental setup: Head-fixed mice run on a textured Möbius belt for water rewards (top). Two-photon (2P) imaging of MEC axons projecting to CA1 is performed through a cranial window (bottom). CamKII-Cre mice are injected with AAV 2.1 SynFlex GCaMP6s in ECL2/3 and AAV 2.5 Syn DIO hM4D mCherry in dorsal CA1. b. Example field of view showing GCaMP-labeled MEC axons, with five ROIs indicated by different colors. c. Raw ΔF/F traces from the five ROIs in b. d. Box and whisker plots (median, lower/upper quartile, 10-90th percentiles) showing the fraction of licks in the reward zone over training days. GOL - goal-oriented learning. Each data point represents the behavior of individual animal averaged over different training sessions within the same recording day. Significance between different experimental conditions (last 4 days) was tested with two-tailed paired t-test. For control condition, (saline injection; +HC) p = 0.03. For test condition, (CNO injection; -HC) p = 0.06. e. Task schematic and representative lick raster plots. Animals navigate familiar or novel belts (top) under saline ( + HC) or CNO (-HC) conditions, with water rewards delivered at fixed locations (pink columns). f. Spatial tuning of MEC axon activity (ratemaps) on familiar/novel belts under saline or CNO conditions. Pink columns indicate reward zones. g. Violin plots of number of calcium events in EC axonal ROIs in different experimental conditions. Significance tested with Kruskal-Wallis test with Dunn’s posthoc correction for multiple comparisons, **** - p < 0.0001, ns – not significant. h. Bar plots depicting proportion of spatially tuned (shaded region) versus non-tuned (clear region) ROIs in different experimental conditions. Error bars represent SEM. Each data point represents the proportion of spatially tuned ROIs in an individual animal. Significance tested with one-way ANOVA with posthoc Šidák’s multiple comparison test. No statistical significance found between groups. i-l. Violin plots of calcium event rate (i) and area under the curve (AUC; j) in spatially tuned ROIs, and calcium event rate (k) and area under the curve (AUC; l) in non-tuned ROIs. Fitting a full model two-way ANOVA confirmed significant effect of tuning (p = 0.0067), environment (p < 0.0001), and significant interaction between the two factors (p < 0.0001). Our data suggest a differential effect of hippocampal silencing in tuned vs non-tuned ROIs. We used post-hoc Šidák’s multiple comparison test to compare significant differences in event rate and event AUC under different conditions. For tuned ROIs, we found a significant reduction upon hippocampal silencing in event rate in novel environment (p = 0.03), and event AUC in both familiar (p < 0.0001) and novel (p = 0.04) environments. For non-tuned ROIs, the event rate was significantly reduced in familiar environment upon hippocampal silencing (p = 0.03), and no significant differences were observed in event AUC upon hippocampal silencing. m. Violin plots of place field width in tuned ROIs. Significance tested with Kruskal-Wallis test with Dunn’s posthoc correction for multiple comparisons, ** - p < 0.002, ns – not significant. n. Violin plots of spatial information (SI) in tuned ROIs. Significance tested with one-way ANOVA with posthoc Šidák’s multiple comparison test, ** - p = 0.01, **** - p < 0.0001. Violin plots show median (solid line) and upper/lower quartiles (dashed line).

Extended Data Fig. 9 in vivo optogenetic silencing of hippocampal feedback to entorhinal cortex does not affect spatial memory performance in Barnes Maze.

ad. (a) Experimental setup: JAWS-expressing hippocampal axons (green) are optically stimulated with a 2 ms, 625 nm light pulse (red symbol) while recording from ECL5 or ECL2/3 neurons. (b) Characteristic firing and sag in a CA1 pyramidal neuron (PN). (c) Increasing hyperpolarization with stronger 625 nm light pulses. (d) A CA1 PN at -70 mV normally fires during 300 pA current injection, but is silenced during the 500 ms 625 nm light pulse. (top). Stimulation pattern: 500 ms of 625 nm light stimulation in the middle of a second-long recording period (bottom). e-f. Confocal images showing the injection site (dorsal CA1) of AAV 2.5 JAWS-KGC-GFP-ER2. g-h. Confocal images of hippocampal axons (green) innervating ECL2/3 (g) and ECL5 (h). White arrowheads show optical fiber implant locations, white arrow marks MEC-LEC border. All scale bars are 100 µm. Each mouse used in the experiment was tested for implant location post-hoc. i. Experimental design of Barnes maze test. In the “learning” phase, (day 1-7) animal is placed in the escape box for 1 min. Then the animal is placed at the center of the maze and allowed to freely explore the maze and its holes for 3 minutes or until it finds the escape hole (data not shown). In the “test” phase, animal is allowed to explore the maze until it finds the escape hole. During this test phase, laser light pulse of 625 nm is delivered to both control and JAWS injected animals. j. Comparison of the total time for which the animal explored the arena (latency) before entering the escape box in “test” phase. Statistical significance tested with Kruskal-Wallis test with post-hoc correction for multiple comparisons with Dunn’s test. No significant difference observed between groups. k. Comparison of the total number of errors made by the animal counted as the number of times it explores different holes including the escape hole without entering the escape box, in “test” phase. Statistical significance tested with Kruskal-Wallis test with post-hoc correction for multiple comparisons with Dunn’s test. No significant difference observed between groups. l. Comparison of the total time for which the animal explored the arena (latency) before entering the escape box, during the learning phase on day 1 vs day 7. Statistical significance tested with two-tailed Wilcoxon matched-pairs signed rank test for control and ECL2/3, and with two-tailed paired t-test for ECL5. *** p – value < 0.001, **** p – value < 0.0001. m. Comparison of the total number of errors made by the animal during the learning phase on day 1 vs day 7. Errors counted as the number of times an animal explored different holes including the escape hole without entering the escape box. Statistical significance tested with two-tailed Wilcoxon matched-pairs signed rank test for control and ECL2/3, and with two-tailed paired t-test for ECL5. ** p – value < 0.01, *** p – value < 0.001. Box and whisker plots show the median, lower/upper quartiles, and 10-90th percentiles. Each gray dot and red triangle (right way up triangle – ECL2/3, inverted triangle – ECL5) represents the data from an individual control and JAWS animal respectively. Data for HC projections silencing in ECL2/3 and ECL5 presented in blue and gray boxes respectively. n = 15 for control, n = 15 for JAWS ECL2/3, and n = 6 for JAWS ECL5.

Extended Data Fig. 10 in vivo hippocampal-EC pathway silencing disrupts novelty detection and object-location memory.

a. Novel Object Recognition (NOR) – silencing during encoding. Mice are habituated to an empty arena for 10 min each day (day 1–2). On the “test” day (day 3 or 4) the animal is placed in the arena with two identical objects and allowed to explore for 10 minutes. During this “encoding” phase, laser light pulse of 625 nm is delivered to both control and JAWS injected animals. After 30 minutes of rest in home cage, the animal is placed in the arena but one of the objects is replaced with a novel and different object. During the recall test phase, animals are allowed to freely explore the two objects for 10 minutes. b. Comparison of the time that the animals spent exploring the two familiar and similar objects during habituation phase of NOR task. For control and ECL2/3, statistical significance tested with two-tailed Wilcoxon matched-pairs signed rank test and for ECL5 with two-tailed paired t-test. c. Comparison of the time that the animals spent exploring the familiar vs novel objects during the test trial of the NOR task. Statistical significance tested with two-tailed Wilcoxon matched-pairs signed rank test for all groups. **** p – value < 0.0001. d. Comparison of novel object recognition index for the cohort of animals during NOR test trial. Statistical significance between the three groups tested with Kruskal-Wallis test with post-hoc correction for multiple comparisons with Dunn’s test. Each group was tested for variation from theoretical mean of 0.5 (chance value) using two-tailed one sample t-test for JAWS ECL2/3 (p-value = 0.03) and ECL5 (p-value = 0.88) groups, and two-tailed one sample Wilcoxon test for the control group (p-value = 0.01). e. Comparison of novel object discrimination index for the cohort of animals during NOR test trial. Statistical significance between the three groups tested with ordinary one-way ANOVA with post-hoc correction for multiple comparisons with Dunnett’s test. Each group was tested for variation from theoretical mean of 0.0 (no discrimination) using two-tailed one sample t-test. For control p-value < 0.0001, JAWS ECL2/3 p-value = 0.03, and JAWS ECL5 p-value = 0.88. Box and whisker plots show the median, lower/upper quartiles, and 10-90th percentiles. Each gray dot and red triangle (right way up triangle – ECL2/3, inverted triangle – ECL5) represents the data from an individual control and JAWS animal respectively. Data for HC projections silencing in ECL2/3 and ECL5 presented in blue and gray boxes respectively. Sample size: Control – 14, ECL2/3 – 11, ECL5 – 5. f. Experimental design of Novel Object Location (NOL) test. Mice are habituated to an empty arena (day 1–2). On the test day (day 3 or 4), mice explore two identical objects for 10 min. 30 minutes after the animal is removed from the arena one of the two ‘familiar’ objects is moved to a new location in the arena. The animal is again allowed to explore the two object locations for ten minutes. During this test phase, laser light pulse of 625 nm is delivered through fiber optic cannulae implanted over ECL2/3 to both control and JAWS injected animals. g. Comparison of the time that the animals spent exploring the two familiar and similar location during habituation phase of NOL task. Statistical significance tested with two-tailed paired t-test for controls (p-value = 0.52) and two-tailed Wilcoxon matched-pairs signed rank test for the JAWS cohort (p-value = 0.26). ns – not significant. h. Comparison of the time that the animals spent exploring the familiar vs novel object locations during the test trial of the NOL task. Statistical significance tested with two-tailed Wilcoxon matched-pairs signed rank test for both cohorts, p – value < 0.0001 for control, p – value = 0.56 for JAWS injected animals. i. Comparison of the novel location discrimination index for the cohort of animals during NOL test trial. Statistical significance tested with two-tailed unpaired t-test with Welch’s correction, p – value = 0.01. Each group was tested for variation from theoretical mean of 0.0 (no discrimination) using two-tailed one sample t-test. For control p-value < 0.0001, for JAWS cohort p-value = 0.86. **** p-value < 0.0001, ns – not significant. j. Comparison of novel object location index for the cohort of animals. Statistical significance test with two-tailed unpaired t-test with Welch’s correction (p – value = 0.01), Each group was tested for variation from theoretical mean of 0.5 (chance value) using two-tailed one sample t-test. For control p-value < 0.0001, for JAWS cohort p-value = 0.86. **** p-value < 0.0001, ns – not significant. Box and whisker plots show the median, lower/upper quartiles, and 10-90th percentiles. Each gray dot and red triangle represents the data from an individual control and JAWS animal respectively. n = 17 for control, n = 23 for JAWS.

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Butola, T., Hernández-Frausto, M., Blankvoort, S. et al. Hippocampus shapes entorhinal cortical output through a direct feedback circuit. Nat Neurosci 28, 811–822 (2025). https://doi.org/10.1038/s41593-025-01883-9

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  • DOI: https://doi.org/10.1038/s41593-025-01883-9

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