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.

Reset of hippocampal–prefrontal circuitry facilitates learning

Abstract

The ability to rapidly adapt to novel situations is essential for survival, and this flexibility is impaired in many neuropsychiatric disorders1. Thus, understanding whether and how novelty prepares, or primes, brain circuitry to facilitate cognitive flexibility has important translational relevance. Exposure to novelty recruits the hippocampus and medial prefrontal cortex (mPFC)2 and may prime hippocampal–prefrontal circuitry for subsequent learning-associated plasticity. Here we show that novelty resets the neural circuits that link the ventral hippocampus (vHPC) and the mPFC, facilitating the ability to overcome an established strategy. Exposing mice to novelty disrupted a previously encoded strategy by reorganizing vHPC activity to local theta (4–12 Hz) oscillations and weakening existing vHPC–mPFC connectivity. As mice subsequently adapted to a new task, vHPC neurons developed new task-associated activity, vHPC–mPFC connectivity was strengthened, and mPFC neurons updated to encode the new rules. Without novelty, however, mice adhered to their established strategy. Blocking dopamine D1 receptors (D1Rs) or inhibiting novelty-tagged cells that express D1Rs in the vHPC prevented these behavioural and physiological effects of novelty. Furthermore, activation of D1Rs mimicked the effects of novelty. These results suggest that novelty promotes adaptive learning by D1R-mediated resetting of vHPC–mPFC circuitry, thereby enabling subsequent learning-associated circuit plasticity.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Novel experience enhances learning.
Fig. 2: Novelty reorganizes vHPC activity patterns.
Fig. 3: Novelty permits vHPC–mPFC circuit plasticity and mPFC information updating.
Fig. 4: Blocking D1Rs or inhibiting novelty-tagged cells in the vHPC reverses the effects of novelty.

Data availability

All data are available from the corresponding authors upon reasonable request. Source data are provided with this paper.

Code availability

All custom codes are available from the corresponding authors upon reasonable request.

References

  1. 1.

    Waltz, J. A. The neural underpinnings of cognitive flexibility and their disruption in psychotic illness. Neuroscience 345, 203–217 (2017).

    CAS  PubMed  Google Scholar 

  2. 2.

    Yamaguchi, S., Hale, L. A., D’Esposito, M. & Knight, R. T. Rapid prefrontal-hippocampal habituation to novel events. J. Neurosci. 24, 5356–5363 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  3. 3.

    Benchenane, K. et al. Coherent theta oscillations and reorganization of spike timing in the hippocampal-prefrontal network upon learning. Neuron 66, 921–936 (2010).

    CAS  PubMed  Google Scholar 

  4. 4.

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

    CAS  PubMed  PubMed Central  Google Scholar 

  5. 5.

    Mukai, J. et al. Molecular substrates of altered axonal growth and brain connectivity in a mouse model of schizophrenia. Neuron 86, 680–695 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Shah, D. et al. Spatial reversal learning defect coincides with hypersynchronous telencephalic BOLD functional connectivity in APPNL-F/NL-F knock-in mice. Sci. Rep. 8, 6264 (2018).

    ADS  PubMed  PubMed Central  Google Scholar 

  7. 7.

    Latif-Hernandez, A. et al. Quinolinic acid injection in mouse medial prefrontal cortex affects reversal learning abilities, cortical connectivity and hippocampal synaptic plasticity. Sci. Rep. 6, 36489 (2016).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  8. 8.

    Blot, K. et al. Modulation of hippocampus-prefrontal cortex synaptic transmission and disruption of executive cognitive functions by MK-801. Cereb. Cortex 25, 1348–1361 (2015).

    PubMed  Google Scholar 

  9. 9.

    Oswal, A. et al. Deep brain stimulation modulates synchrony within spatially and spectrally distinct resting state networks in Parkinson’s disease. Brain 139, 1482–1496 (2016).

    PubMed  PubMed Central  Google Scholar 

  10. 10.

    Krause, M. R. et al. Transcranial direct current stimulation facilitates associative learning and alters functional connectivity in the primate brain. Curr. Biol. 27, 3086–3096.e3 (2017).

    CAS  PubMed  Google Scholar 

  11. 11.

    Kim, J.-I. et al. PI3Kγ is required for NMDA receptor-dependent long-term depression and behavioral flexibility. Nat. Neurosci. 14, 1447–1454 (2011).

    CAS  PubMed  Google Scholar 

  12. 12.

    Kitamura, T. et al. Adult neurogenesis modulates the hippocampus-dependent period of associative fear memory. Cell 139, 814–827 (2009).

    CAS  PubMed  Google Scholar 

  13. 13.

    Epp, J. R., Silva Mera, R., Köhler, S., Josselyn, S. A. & Frankland, P. W. Neurogenesis-mediated forgetting minimizes proactive interference. Nat. Commun. 7, 10838 (2016).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Alam, M. J. et al. Adult neurogenesis conserves hippocampal memory capacity. J. Neurosci. 38, 6854–6863 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Abraham, W. C. & Bear, M. F. Metaplasticity: the plasticity of synaptic plasticity. Trends Neurosci. 19, 126–130 (1996).

    CAS  PubMed  Google Scholar 

  16. 16.

    O’Dell, T. J. & Kandel, E. R. Low-frequency stimulation erases LTP through an NMDA receptor-mediated activation of protein phosphatases. Learn. Mem. 1, 129–139 (1994).

    PubMed  Google Scholar 

  17. 17.

    Dietz, B. & Manahan-Vaughan, D. Hippocampal long-term depression is facilitated by the acquisition and updating of memory of spatial auditory content and requires mGlu5 activation. Neuropharmacology 115, 30–41 (2017).

    CAS  PubMed  Google Scholar 

  18. 18.

    Manahan-Vaughan, D. & Braunewell, K. H. Novelty acquisition is associated with induction of hippocampal long-term depression. Proc. Natl Acad. Sci. USA 96, 8739–8744 (1999).

    ADS  CAS  PubMed  Google Scholar 

  19. 19.

    Moncada, D. & Viola, H. Induction of long-term memory by exposure to novelty requires protein synthesis: evidence for a behavioral tagging. J. Neurosci. 27, 7476–7481 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. 20.

    Buzsáki, G., Anastassiou, C. A. & Koch, C. The origin of extracellular fields and currents — EEG, ECoG, LFP and spikes. Nat. Rev. Neurosci. 13, 407–420 (2012).

    PubMed  PubMed Central  Google Scholar 

  21. 21.

    de Bruin, J. P. C., Sànchez-Santed, F., Heinsbroek, R. P. W., Donker, A. & Postmes, P. A behavioural analysis of rats with damage to the medial prefrontal cortex using the Morris water maze: evidence for behavioural flexibility, but not for impaired spatial navigation. Brain Res. 652, 323–333 (1994).

    PubMed  Google Scholar 

  22. 22.

    Hyman, J. M., Wyble, B. P., Goyal, V., Rossi, C. A. & Hasselmo, M. E. Stimulation in hippocampal region CA1 in behaving rats yields long-term potentiation when delivered to the peak of theta and long-term depression when delivered to the trough. J. Neurosci. 23, 11725–11731 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Lowet, E., Roberts, M. J., Bonizzi, P., Karel, J. & De Weerd, P. Quantifying neural oscillatory synchronization: A comparison between spectral coherence and phase-locking value approaches. PLoS One 11, e0146443 (2016).

    PubMed  PubMed Central  Google Scholar 

  24. 24.

    Spellman, T. et al. Hippocampal-prefrontal input supports spatial encoding in working memory. Nature 522, 309–314 (2015).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  25. 25.

    Otmakhova, N., Duzel, E., Deutch, A. Y. & Lisman, J. in Intrinsically Motivated Learning in Natural and Artificial Systems 235–254 (Springer, 2013).

  26. 26.

    Lemon, N. & Manahan-Vaughan, D. Dopamine D1/D5 receptors gate the acquisition of novel information through hippocampal long-term potentiation and long-term depression. J. Neurosci. 26, 7723–7729 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Chen, Z. et al. Roles of dopamine receptors in long-term depression: enhancement via D1 receptors and inhibition via D2 receptors. Receptors Channels 4, 1–8 (1996).

    CAS  PubMed  Google Scholar 

  28. 28.

    Hansen, N. & Manahan-Vaughan, D. Dopamine D1/D5 receptors mediate informational saliency that promotes persistent hippocampal long-term plasticity. Cereb. Cortex 24, 845–858 (2014).

    PubMed  Google Scholar 

  29. 29.

    Lee, D., Hyun, J. H., Jung, K., Hannan, P. & Kwon, H. B. A calcium- and light-gated switch to induce gene expression in activated neurons. Nat. Biotechnol. 35, 858–863 (2017).

    CAS  PubMed  Google Scholar 

  30. 30.

    Kamondi, A., Acsády, L., Wang, X. J. & Buzsáki, G. Theta oscillations in somata and dendrites of hippocampal pyramidal cells in vivo: activity-dependent phase-precession of action potentials. Hippocampus 8, 244–261 (1998).

    CAS  PubMed  Google Scholar 

  31. 31.

    Takeuchi, T. et al. Locus coeruleus and dopaminergic consolidation of everyday memory. Nature 537, 357–362 (2016).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Schmidt, B. et al. Dissociation between dorsal and ventral hippocampal theta oscillations during decision-making. J. Neurosci. 33, 6212–6224 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Tran, A. H. et al. Dopamine D1 receptor modulates hippocampal representation plasticity to spatial novelty. J. Neurosci. 28, 13390–13400 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Fredes, F. et al. Ventro-dorsal hippocampal pathway gates novelty-induced contextual memory formation. Curr. Biol. 31, 25–38.e5 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. 35.

    Li, M., Long, C. & Yang, L. Hippocampal-prefrontal circuit and disrupted functional connectivity in psychiatric and neurodegenerative disorders. BioMed Res. Int. 2015, 810548 (2015).

    PubMed  PubMed Central  Google Scholar 

  36. 36.

    Laubach, M., Amarante, L. M., Swanson, K. & White, S. R. What, if anything, is rodent prefrontal cortex? eNeuro 5, ENEURO.0315-18.2018 (2018).

    PubMed  PubMed Central  Google Scholar 

  37. 37.

    Abbas, A. I. et al. Somatostatin interneurons facilitate hippocampal-prefrontal synchrony and prefrontal spatial encoding. Neuron 100, 926–939.e3 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. 38.

    Adhikari, A., Topiwala, M. A. & Gordon, J. A. Synchronized activity between the ventral hippocampus and the medial prefrontal cortex during anxiety. Neuron 65, 257–269 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. 39.

    Ballarini, F., Moncada, D., Martinez, M. C., Alen, N. & Viola, H. Behavioral tagging is a general mechanism of long-term memory formation. Proc. Natl Acad. Sci. USA 106, 14599–14604 (2009).

    ADS  CAS  PubMed  Google Scholar 

  40. 40.

    Vecsey, C. G. C. G. et al. Daily acclimation handling does not affect hippocampal long-term potentiation or cause chronic sleep deprivation in mice. Sleep 36, 601–607 (2013).

    PubMed  PubMed Central  Google Scholar 

  41. 41.

    Oishi, N. et al. Artificial association of memory events by optogenetic stimulation of hippocampal CA3 cell ensembles. Mol. Brain 12, 2 (2019).

    PubMed  PubMed Central  Google Scholar 

  42. 42.

    Stebbins, M. J. et al. Tetracycline-inducible systems for Drosophila. Proc. Natl Acad. Sci. USA 98, 10775–10780 (2001).

    ADS  CAS  PubMed  Google Scholar 

  43. 43.

    Yamada, M., Suzuki, Y., Nagasaki, S. C., Okuno, H. & Imayoshi, I. Light control of the Tet gene expression system in mammalian cells. Cell Rep. 25, 487–500.e6 (2018).

    CAS  PubMed  Google Scholar 

  44. 44.

    Garí, E., Piedrafita, L., Aldea, M. & Herrero, E. A set of vectors with a tetracycline-regulatable promoter system for modulated gene expression in Saccharomyces cerevisiae. Yeast 13, 837–848 (1997).

    PubMed  Google Scholar 

  45. 45.

    Smith, A. C. et al. Dynamic analysis of learning in behavioral experiments. J. Neurosci. 24, 447–461 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. 46.

    Cohen, J. D., Bolstad, M. & Lee, A. K. Experience-dependent shaping of hippocampal CA1 intracellular activity in novel and familiar environments. eLife 6, 1–27 (2017).

    Google Scholar 

  47. 47.

    Vinck, M., van Wingerden, M., Womelsdorf, T., Fries, P. & Pennartz, C. M. A. The pairwise phase consistency: a bias-free measure of rhythmic neuronal synchronization. Neuroimage 51, 112–122 (2010).

    PubMed  Google Scholar 

  48. 48.

    Cohen, M. X. Analyzing Neural Time Series Data: Theory and Practice (MIT Press, 2014).

  49. 49.

    Belluscio, M. A., Mizuseki, K., Schmidt, R., Kempter, R. & Buzsáki, G. Cross-frequency phase-phase coupling between θ and γ oscillations in the hippocampus. J. Neurosci. 32, 423–435 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. 50.

    Keller, C. J., Chen, C., Lado, F. A. & Khodakhah, K. The limited utility of multiunit data in differentiating neuronal population activity. PLoS One 11, e0153154 (2016).

    PubMed  PubMed Central  Google Scholar 

  51. 51.

    Scheffer-Teixeira, R., Belchior, H., Leão, R. N., Ribeiro, S. & Tort, A. B. L. On high-frequency field oscillations (>100 Hz) and the spectral leakage of spiking activity. J. Neurosci. 33, 1535–1539 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This work was supported by grants from the NIMH (R01 MH096274 to J. A. Gogos, T32 MH018870-29 to A.I.A., R21 MH117454 to C.K., and K08 MH109735 to A.Z.H.). A.I.A. was also supported by the Leon Levy Foundation. A.Z.H. was also supported by the Hope for Depression Research Foundation and BBRF Young Investigator Award. J. A. Gordon is supported by the National Institutes of Health Intramural Research Program. We thank N. Padilla-Coreano for providing sample multiunit and LFP recordings; R. Hen, A. Losonczy, and S. Siegelbaum for suggestions; and A. Ciarleglio for advice on logistic regression models of learning curves.

Author information

Affiliations

Authors

Contributions

A.J.P. conceived the study. A.J.P., A.Z.H., J. A. Gogos, and J. A. Gordon designed the experiments. A.J.P. and C.-Y.C. performed behavioural experiments and in vivo recordings. K.M.M., under the supervision of C.K., performed ex vivo recordings. A.J.P. analysed the data. A.Z.H. and A.I.A. assisted with data analyses. D.C.L. assisted with data collection. A.J.P., A.Z.H., C.K., J. A. Gogos, and J. A. Gordon interpreted the results and wrote the article. A.Z.H., J. A. Gogos, and J. A. Gordon supervised the work.

Corresponding authors

Correspondence to Alan J. Park or Joshua A. Gordon.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature thanks Denise Cai and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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

Extended data figures and tables

Extended Data Fig. 1 Spatial and social novelty, but not general arousal, enhance learning.

After 3 days of free choice sessions, mice were exposed to the novel or familiar arena (Fig. 1f), a novel juvenile male mouse (n = 7), or arousal handling (n = 7) 1 h before flexible choice training. Mice exposed to the novel juvenile mouse performed similarly to mice exposed to the novel arena (two-way RM ANOVA, F(1,22) = 0.03, P = 0.9). Conversely, mice that underwent arousal handling performed similarly to mice exposed to the familiar arena (two-way RM ANOVA, F(1,25) = 0.4, P = 0.5). The average inflection points (learning trial) were 21 (spatial novelty), 19 (social novelty), 38 (familiar), and 39 (arousal) (Kruskal–Wallis test, P = 0.002; familiar versus arousal, P > 0.9; spatial novelty versus familiar, P = 0.03; social novelty versus familiar, P = 0.03). Inset, learning trial of each mouse. n.s., not significant. *P < 0.05, ***P < 0.0005. Data represented as mean ± s.e.m. Source data

Extended Data Fig. 2 Novelty induces prolonged increases in theta power in the vHPC, but not the dHPC or mPFC.

a, LFP power was measured during and 1 h after arena exposure, at the onset of flexible choice training. b, The novel-exposed group displayed higher vHPC theta power 1 h after arena exposure than the other groups (Kruskal–Wallis test, P = 0.0007; novel vs. familiar, P = 0.001; novel versus control, P = 0.008). c, Theta power in the dHPC was comparable across all groups during (Mann–Whitney test, P = 0.1) and 1 h after arena exposure (Kruskal–Wallis test, P = 0.4). d, Novelty exposure increased mPFC theta power (Mann–Whitney test, P = 0.002), but this increase was not seen at the onset of flexible choice training (Kruskal–Wallis test, P = 0.4). e, A separate cohort of mice explored a T-shaped arena for two consecutive days. f, Theta power in the vHPC decreased on day 2 compared with day 1 (Wilcoxon signed-rank test, P = 0.04). g, h, Theta power in the dHPC or mPFC was comparable between day 1 and day 2 (Wilcoxon signed-rank test; g, P = 0.8; h, P = 0.3). Insets, average theta power of each mouse. n.s., not significant. *P < 0.05, **P < 0.005. Data represented as mean ± s.e.m. Source data

Extended Data Fig. 3 Novelty-induced connectivity weakening permits subsequent learning-associated connectivity strengthening in the vHPC–mPFC, but not dHPC–mPFC, circuit.

a, Left, rose plots illustrating the phase-locking of example mPFC single units to vHPC theta oscillations. The novel-exposed group showed lower phase-locking than the familiar-exposed group during arena exposure (novel, 110; familiar,113 cells; Mann–Whitney test, P = 0.04). b, Measuring vHPC MUA-evoked mPFC spike firing. c, The novel-exposed group exhibited lower evoked firing during (novel, 110; familiar, 113 cells; P = 0.02) and 1 h after arena exposure (novel,12; familiar, 24 cells; Mann–Whitney test, P = 0.01). d, In the late phase of flexible choice training, evoked firing increased in the novel-exposed group (66 cells; P = 0.03), but decreased in the familiar-exposed group (97 cells; P = 0.01). Wilcoxon signed-rank test. e, Rose plots illustrate the phase-locking of example mPFC single units to dHPC theta oscillations. The novel- and familiar-exposed groups showed comparable phase-locking levels during (novel, 110; familiar, 107 cells; P = 0.3) and 1 h after arena exposure (novel, 29; familiar, 25 cells; P = 0.07). Mann–Whitney test. f, Both the novel- and familiar-exposed groups exhibited increased phase-locking in the late phase of flexible choice training (Wilcoxon signed-rank test; novel, 66 cells, P = 0.0002; familiar, 103 cells, P = 0.04). Cumulative distribution shows all mPFC single unit values. n.s., not significant. *P < 0.05, **P < 0.005, ***P < 0.0005. Data represented as mean ± s.e.m. for ad, and median with 95% confidence interval for e, f. Source data

Extended Data Fig. 4 Novelty disrupts vHPC encoding of free choice strategy and permits encoding of flexible choice strategy.

a, Machine learning classifier models trained with free choice data (vHPC unit activity and arm bias) successfully classified differences in vHPC unit activity patterns between biased and non-biased arm visits (10 models; 95.8% ± 0.3). b, Machine learning classifier models trained with free choice arm bias data (a) were used to decode flexible choice vHPC spiking data. c, For the first half of the flexible choice training, the models predicted biased arm choice of the familiar-exposed group, but not the novel-exposed group (10 models; two-way RM ANOVA, F(1,18) = 25.1, P < 0.0001). d, Once the novel-exposed group had learned the flexible choice task rule in later trials, the models predicted getting the reward for the novel-exposed group but not the familiar-exposed group (10 models; two-way RM ANOVA, F(1,18) = 5.7, P = 0.02). Insets, model predictions with shuffled flexible choice vHPC spiking data. *P < 0.05, **P < 0.005, ***P < 0.0005. Data represented as mean ± s.e.m. Source data

Extended Data Fig. 5 VTA inputs to the HPC.

Top, AAV-mCherry was injected into the VTA to visualize VTA-to-HPC projections. Bottom, maximum-intensity projection images. ac, VTA terminals in vHPC CA1 (a), CA3 (b), and dentate gyrus (DG; c). df, VTA terminals in dHPC CA1 (d), CA3 (e), and DG (f). g, The expression of mCherry in the VTA. h, VTA dopaminergic neurons expressing tyrosine hydroxylase (TH). i, Merged image of g and h. Blue, DAPI. LMol, lacunosum moleculare layer; Or, oriens; Py, pyramidal; Rad, radiatum . Scale bars, 50 μm.

Extended Data Fig. 6 D1R activation mimics the effect of novelty on vHPC–mPFC synaptic transmission and learning.

a, Optical test pulses were delivered as in Fig. 3c–e. Left, systemic administration of the D1R agonist dihydrexidine induced vHPC–mPFC synaptic depression compared with the vehicle condition (n = 5 mice; one-way RM ANOVA, F(1.6,6.3) = 52.2, P = 0.0002; baseline versus vehicle, P = 0.7; baseline versus dihydrexidine, P = 0.003; vehicle versus dihydrexidine, P = 0.0009). Top right, example average fEPSP traces. Bottom right, average fEPSPs. b, Dihydrexidine treatment enhanced learning relative to vehicle treatment (n = 5 (vehicle), n = 6 (dihydrexidine); two-way RM ANOVA, F(1,9) = 8.7, P = 0.02). The average inflection points (learning trial) were 15 (dihydrexidine) and 46 (vehicle) (Mann–Whitney test, P = 0.009). Inset, learning trials of each mouse. The learning trial of one mouse in the vehicle group was undetermined because the overall slope of its learning curve was negative, indicating that learning had not occurred. *P < 0.05, **P < 0.005, ***P < 0.0005. Data represented as mean ± s.e.m. Source data

Extended Data Fig. 7 Blocking D1Rs in the vHPC abolishes the effects of novelty on hippocampal–prefrontal circuitry.

a, SCH infusion impaired novelty-induced vHPC theta power 1 h after novelty exposure (n = 7 mice each; Mann–Whitney test, P = 0.02). b, During novelty exposure, the SCH group exhibited higher vHPC MUA-evoked mPFC spike firing (SCH, n = 31; vehicle, n = 69 cells; Mann–Whitney test, P = 0.04). c, In late training, mPFC unit phase-locking to vHPC theta activity was not significantly changed in the SCH group (18 cells; P = 0.1) but was increased in the vehicle group (n = 36 cells; P = 0.004). Wilcoxon signed-rank test. d, In late training, evoked mPFC spike firing was not significantly changed in the SCH group (n = 18 cells; P = 0.2) but was increased in the vehicle group (n = 36 cells; P = 0.01). Wilcoxon signed-rank test. e, Mice infused with either vehicle or SCH into the vHPC displayed similar dHPC theta power during and 1 h after novel arena exploration (Mann–Whitney test, P = 0.3 and P = 0.1, respectively; n = 7 mice each). f, SCH infusion impaired novelty-induced mPFC theta power during novel arena exposure (P = 0.04), but did not have an effect 1 h later (P = 0.2). Mann–Whitney test, n = 7 mice each. g, h, Phase-locking of mPFC single units to dHPC theta oscillations. g, Phase-locking was not significantly different between the vehicle and SCH groups during novel arena exploration (SCH, n = 31; vehicle, n = 69 cells; Mann–Whitney test, P = 0.6). h, Phase-locking remained stable during training in both groups (SCH, n = 31, P = 0.6; vehicle, n = 69 cells, P = 0.8; Wilcoxon signed-rank test). Cumulative distribution shows all mPFC unit values. Insets (a, e, f), individual average theta power. n.s., not significant. *P < 0.05, **P < 0.005. Data represented as mean ± s.e.m. (af) or median with 95% confidence interval (g, h). Source data

Extended Data Fig. 8 The Cal-Light technique to tag and inhibit novelty-responsive vHPC cells.

a, Labelling active cells in vHPC CA1 area using the Cal-Light system. Scale bars, 50 μm. b, Cumulative distribution of the green:red ratio of each cell (light + familiar, 1,014 cells/2 mice; no light + novel, 920 cells/2 mice; light + novel, 975 cells/2 mice). As eGFP expression is induced in the virus-infected cells that express the red fluorophore tdTomato, the green:red ratio for each cell was measured. c, Relative to the other conditions, vHPC cells in the light + novel condition displayed a higher green:red ratio (one-way ANOVA, F(2,2906) = 171.9, P < 0.0001; light + novel versus no light + novel, P < 0.0001; light + novel versus light + familiar, P < 0.0001). d, Green light inhibited spiking of eNpHR-expressing novelty-tagged cells (two-way RM ANOVA, F(1,12) = 10.2, P = 0.008, n = 7). Inset, vHPC cells expressing eNpHR–eGFP reporter. e, The mPFC projections of vHPC cells infected with the Cal-Light viruses. Maximum-intensity projection images. Scale bars, 10 μm. f, The projections of vHPC cells expressing D1Rs to the mPFC. Left, Cre-dependent eYFP expression in vHPC cells of Drd1Cre mice. Middle, co-localization of eYFP (green) and D1Rs (red) in the vHPC. Right, vHPC terminals (green) in the mPFC. Blue, DAPI. Scale bars, 20 μm (middle), 500 μm (right). g, Inhibiting familiar-responsive vHPC cells did not affect flexible choice training performance (n = 5 for each group, two-way RM ANOVA, F(1,8) = 0.2, P = 0.7). Inset, learning trials of each mouse. The average learning trials were 40 (eGFP) and 36 (eNpHR) (Mann–Whitney test, P = 0.8). The learning trials of two mice in the eGFP group were undetermined because the overall slopes of their learning curves were negative, indicating that learning had not occurred. n.s., not significant. *P < 0.05, ***P < 0.0005. Data represented as mean ± s.e.m. Source data

Extended Data Fig. 9 A model illustrating the effects of novelty on vHPC–mPFC circuitry and information encoding.

The vHPC–mPFC circuit encodes a strategy to get the reward after free choice sessions. This circuit encoding of the free choice strategy remains stable under familiar conditions and conflicts with learning on flexible choice training. By contrast, exposure to novelty disrupts vHPC activity patterns encoding the free choice strategy and weakens existing vHPC–mPFC connectivity, reducing adherence to the free choice strategy. During flexible choice training, the vHPC develops new task-driven activity patterns and vHPC–mPFC functional connectivity undergoes learning-dependent strengthening. The vHPC then transmits newly encoded task-specific information to the mPFC, updating mPFC encoding with new task-relevant information. Hence, exposure to novelty enhances new learning by resetting the vHPC–mPFC circuit.

Extended Data Fig. 10 The novel arena is not anxiogenic.

To avoid anxiogenic effects of the novel arena exposure, experiments were performed in the dark. Top, example behaviour trajectories in the novel and familiar arenas. a, Total path length was comparable between the novel and familiar groups (t-test, t(35) = 1.1, P = 0.3). b, c, Percentage path length (b; t-test, t(35) = 0.3, P = 0.7) or time spent in the centre (c; t-test, t(35) = 0.6, P = 0.6) was similar between the two groups. Novel, n = 17, familiar, n = 20 mice. Data represented as mean ± s.e.m. Source data

Supplementary information

Source data

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Park, A.J., Harris, A.Z., Martyniuk, K.M. et al. Reset of hippocampal–prefrontal circuitry facilitates learning. Nature 591, 615–619 (2021). https://doi.org/10.1038/s41586-021-03272-1

Download citation

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

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