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.
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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.
The authors declare no competing interests.
Peer review information Nature thanks Denise Cai and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Extended data figures and tables
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 a–d, 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
Top, AAV-mCherry was injected into the VTA to visualize VTA-to-HPC projections. Bottom, maximum-intensity projection images. a–c, VTA terminals in vHPC CA1 (a), CA3 (b), and dentate gyrus (DG; c). d–f, 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. (a–f) or median with 95% confidence interval (g, h). Source data
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.
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
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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