The consolidation of context-dependent emotional memory requires communication between the hippocampus and the basolateral amygdala (BLA), but the mechanisms of this process are unknown. We recorded neuronal ensembles in the hippocampus and BLA while rats learned the location of an aversive air puff on a linear track, as well as during sleep before and after training. We found coordinated reactivations between the hippocampus and the BLA during non-REM sleep following training. These reactivations peaked during hippocampal sharp wave–ripples (SPW-Rs) and involved a subgroup of BLA cells positively modulated during hippocampal SPW-Rs. Notably, reactivation was stronger for the hippocampus–BLA correlation patterns representing the run direction that involved the air puff than for the 'safe' direction. These findings suggest that consolidation of contextual emotional memory occurs during ripple-reactivation of hippocampus–amygdala circuits.
Subscribe to Journal
Get full journal access for 1 year
only $18.75 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
Vazdarjanova, A. & McGaugh, J.L. Basolateral amygdala is involved in modulating consolidation of memory for classical fear conditioning. J. Neurosci. 19, 6615–6622 (1999).
Paré, D., Collins, D.R. & Pelletier, J.G. Amygdala oscillations and the consolidation of emotional memories. Trends Cogn. Sci. 6, 306–314 (2002).
Maren, S. & Fanselow, M.S. Synaptic plasticity in the basolateral amygdala induced by hippocampal formation stimulation in vivo. J. Neurosci. 15, 7548–7564 (1995).
Ikegaya, Y., Saito, H. & Abe, K. Attenuated hippocampal long-term potentiation in basolateral amygdala-lesioned rats. Brain Res. 656, 157–164 (1994).
Ikegaya, Y., Saito, H. & Abe, K. High-frequency stimulation of the basolateral amygdala facilitates the induction of long-term potentiation in the dentate gyrus in vivo. Neurosci. Res. 22, 203–207 (1995).
Goshen, I. et al. Dynamics of retrieval strategies for remote memories. Cell 147, 678–689 (2011).
Reijmers, L.G., Perkins, B.L., Matsuo, N. & Mayford, M. Localization of a stable neural correlate of associative memory. Science 317, 1230–1233 (2007).
Redondo, R.L. et al. Bidirectional switch of the valence associated with a hippocampal contextual memory engram. Nature 513, 426–430 (2014).
Hsiang, H.-L.L. et al. Manipulating a “cocaine engram” in mice. J. Neurosci. 34, 14115–14127 (2014).
Xu, C. et al. Distinct hippocampal pathways mediate dissociable roles of context in memory retrieval. Cell 167, 961–972 (2016).
Phillips, R.G. & LeDoux, J.E. Differential contribution of amygdala and hippocampus to cued and contextual fear conditioning. Behav. Neurosci. 106, 274–285 (1992).
Zelikowsky, M., Hersman, S., Chawla, M.K., Barnes, C.A. & Fanselow, M.S. Neuronal ensembles in amygdala, hippocampus, and prefrontal cortex track differential components of contextual fear. J. Neurosci. 34, 8462–8466 (2014).
O'Keefe, J. & Nadel, L. The Hippocampus as a Cognitive Map (Oxford Univ. Press, 1978).
Kjelstrup, K.G. et al. Reduced fear expression after lesions of the ventral hippocampus. Proc. Natl. Acad. Sci. USA 99, 10825–10830 (2002).
Royer, S., Sirota, A., Patel, J. & Buzsáki, G. Distinct representations and theta dynamics in dorsal and ventral hippocampus. J. Neurosci. 30, 1777–1787 (2010).
Moser, M.B., Moser, E.I., Forrest, E., Andersen, P. & Morris, R.G. Spatial learning with a minislab in the dorsal hippocampus. Proc. Natl. Acad. Sci. USA 92, 9697–9701 (1995).
Moser, E.I.E., Krobert, K.A., Moser, M.B. & Morris, R.G. Impaired spatial learning after saturation of long-term potentiation. Science 281, 2038–2042 (1998).
Small, S.A. The longitudinal axis of the hippocampal formation: its anatomy, circuitry, and role in cognitive function. Rev. Neurosci. 13, 183–194 (2002).
Kim, J.J. & Fanselow, M.S. Modality-specific retrograde amnesia of fear. Science 256, 675–677 (1992).
Corcoran, K.A., Desmond, T.J., Frey, K.A. & Maren, S. Hippocampal inactivation disrupts the acquisition and contextual encoding of fear extinction. J. Neurosci. 25, 8978–8987 (2005).
Maren, S. & Quirk, G.J. Neuronal signalling of fear memory. Nat. Rev. Neurosci. 5, 844–852 (2004).
Pitkänen, A., Pikkarainen, M., Nurminen, N. & Ylinen, A. Reciprocal connections between the amygdala and the hippocampal formation, perirhinal cortex, and postrhinal cortex in rat. A review. Ann. NY Acad. Sci. 911, 369–391 (2000).
Herry, C. et al. Switching on and off fear by distinct neuronal circuits. Nature 454, 600–606 (2008).
Girardeau, G. & Zugaro, M. Hippocampal ripples and memory consolidation. Curr. Opin. Neurobiol. 21, 452–459 (2011).
Wang, D.V. et al. Mesopontine median raphe regulates hippocampal ripple oscillation and memory consolidation. Nat. Neurosci. 18, 728–735 (2015).
van de Ven, G.M., Trouche, S., McNamara, C.G., Allen, K. & Dupret, D. Hippocampal offline reactivation consolidates recently formed cell assembly patterns during sharp wave-ripples. Neuron 92, 968–974 (2016).
Popa, D., Duvarci, S., Popescu, A.T., Léna, C. & Paré, D. Coherent amygdalocortical theta promotes fear memory consolidation during paradoxical sleep. Proc. Natl. Acad. Sci. USA 107, 6516–6519 (2010).
Huff, M.L., Miller, R.L., Deisseroth, K., Moorman, D.E. & LaLumiere, R.T. Posttraining optogenetic manipulations of basolateral amygdala activity modulate consolidation of inhibitory avoidance memory in rats. Proc. Natl. Acad. Sci. USA 110, 3597–3602 (2013).
Patel, J., Schomburg, E.W., Berényi, A., Fujisawa, S. & Buzsáki, G. Local generation and propagation of ripples along the septotemporal axis of the hippocampus. J. Neurosci. 33, 17029–17041 (2013).
Lovett-Barron, M. et al. Dendritic inhibition in the hippocampus supports fear learning. Science 343, 857–863 (2014).
Mizuseki, K., Royer, S., Diba, K. & Buzsáki, G. Activity dynamics and behavioral correlates of CA3 and CA1 hippocampal pyramidal neurons. Hippocampus 22, 1659–1680 (2012).
Kudrimoti, H.S., Barnes, C.A. & McNaughton, B.L. Reactivation of hippocampal cell assemblies: effects of behavioral state, experience, and EEG dynamics. J. Neurosci. 19, 4090–4101 (1999).
Lansink, C.S., Goltstein, P.M., Lankelma, J.V., McNaughton, B.L. & Pennartz, C.M.A. Hippocampus leads ventral striatum in replay of place-reward information. PLoS Biol. 7, e1000173 (2009).
Hoffman, K.L. & McNaughton, B.L. Coordinated reactivation of distributed memory traces in primate neocortex. Science 297, 2070–2073 (2002).
Wilson, M. & McNaughton, B. Reactivation of hippocampal ensemble memories during sleep. Science (80- ) 5, 14–17 (1994).
Shen, J., Kudrimoti, H.S., McNaughton, B.L. & Barnes, C.A. Reactivation of neuronal ensembles in hippocampal dentate gyrus during sleep after spatial experience. J. Sleep Res. 7 (Suppl. 1), 6–16 (1998).
Genzel, L., Spoormaker, V.I., Konrad, B.N. & Dresler, M. The role of rapid eye movement sleep for amygdala-related memory processing. Neurobiol. Learn. Mem. 122, 110–121 (2015).
Hutchison, I.C. & Rathore, S. The role of REM sleep theta activity in emotional memory. Front. Psychol. 6, 1439 (2015).
LeDoux, J.E. Coming to terms with fear. Proc. Natl. Acad. Sci. USA 111, 2871–2878 (2014).
Moita, M.A., Rosis, S., Zhou, Y., LeDoux, J.E. & Blair, H.T. Putting fear in its place: remapping of hippocampal place cells during fear conditioning. J. Neurosci. 24, 7015–7023 (2004).
Wang, M.E. et al. Differential roles of the dorsal and ventral hippocampus in predator odor contextual fear conditioning. Hippocampus 23, 451–466 (2013).
Bannerman, D.M. et al. Regional dissociations within the hippocampus—memory and anxiety. Neurosci. Biobehav. Rev. 28, 273–283 (2004).
Ciocchi, S., Passecker, J., Malagon-Vina, H., Mikus, N. & Klausberger, T. Brain computation. Selective information routing by ventral hippocampal CA1 projection neurons. Science 348, 560–563 (2015).
Buzsáki, G. Hippocampal sharp wave-ripple: a cognitive biomarker for episodic memory and planning. Hippocampus 25, 1073–1188 (2015).
Logothetis, N.K. et al. Hippocampal–cortical interaction during periods of subcortical silence. Nature 491, 547–553 (2012).
Sparta, D.R. et al. Inhibition of projections from the basolateral amygdala to the entorhinal cortex disrupts the acquisition of contextual fear. Front. Behav. Neurosci. 8, 129 (2014).
Chrobak, J.J. & Buzsáki, G. High-frequency oscillations in the output networks of the hippocampal-entorhinal axis of the freely behaving rat. J. Neurosci. 16, 3056–3066 (1996).
Boyce, R., Glasgow, S.D., Williams, S. & Adamantidis, A. Causal evidence for the role of REM sleep theta rhythm in contextual memory consolidation. Science (80- ) 23, 812 (2016).
Maquet, P. et al. Experience-dependent changes in cerebral activation during human REM sleep. Nat. Neurosci. 3, 831–836 (2000).
Atherton, L.A., Dupret, D. & Mellor, J.R. Memory trace replay: the shaping of memory consolidation by neuromodulation. Trends Neurosci. 38, 560–570 (2015).
Vandecasteele, M. et al. Large-scale recording of neurons by movable silicon probes in behaving rodents. J. Vis. Exp. 3568, e3568 (2012).
Hazan, L., Zugaro, M. & Buzsáki, G. Klusters, NeuroScope, NDManager: a free software suite for neurophysiological data processing and visualization. J. Neurosci. Methods 155, 207–216 (2006).
Peyrache, A., Khamassi, M., Benchenane, K., Wiener, S.I. & Battaglia, F.P. Replay of rule-learning related neural patterns in the prefrontal cortex during sleep. Nat. Neurosci. 12, 919–926 (2009).
Lopes-dos-Santos, V., Ribeiro, S. & Tort, A.B.L. Detecting cell assemblies in large neuronal populations. J. Neurosci. Methods 220, 149–166 (2013).
We thank J. LeDoux, C. Léna, E. Stark, A. Peyrache and L. Roux for comments and discussions on the analyses and manuscript and all the members of the Buzsáki laboratory for their support. This work was supported by the Fondation pour la Recherche Médicale (FRM), the Fyssen Foundation, a Charles H. Revson Senior Fellowship in Biomedical Science (G.G.), NIH MH54671 and MH107396, NS 090583 and the Simons Foundations (G.B.).
The authors declare no competing financial interests.
Integrated supplementary information
a. The speed of the animal was measured in the 20-cm segment preceding the airpuff location (current or previous danger zone: DZ) during pre-RUN, RUN and post-RUN. b. Ratios were calculated as indicated. The reversal of ratio between pre and post RUN indicates that all animals learned the new location during RUN and remembered it during post-RUN (one-way repeated measure ANOVAS; Rat1: n=11 sessions, p=0.000214, df=2, F=13.26; Rat2: n=10 sessions, p=0.00556 df=2, F=7.02; Rat3: n=14 sessions, p=3.9469x10-07, df=2, F=27.41; Rat4: n=16 sessions, p=0.021754, df=2, F=4.36; followed by Bonferroni-corrected post-hoc paired t-test *p<0.05, **p<0.01, ***p<0.001; white lines: median, black dotted lines: mean; box: upper and lower quartiles; whiskers: minimum and maximum values). c. Habituation index across days for each animals. The index is calculated as the number of airpuff laps divided by the total time spent on the track x100. Habituated animals run more laps in a given time, yielding to increased habituation index values. Empty dots: training days where the physiological data was not considered for analysis for technical reasons.
Supplementary Figure 2 Histological reconstruction from DAPI-stained brain slices and reconstructed anatomical maps of recording sites for all four animals.
The probe was moved after each session and the depth of the recording sites of each shank (8 shanks with a 140 μm depth span of recording sites) was estimated from the histological reconstructions of the shanks from the lesion-marked final position of the probe (see Online Methods). The maps were reconstructed from consecutive brain slices. Only one slice per side and animal is shown here, without (upper pictures) and with (lower picture) the superimposed reconstruction grid. The group memberships of neurons and LFPs for analyses were defined according to the boundaries of the nuclei (black lines).
a. Example excitatory (left) and inhibitory (right) connections detected by cross-correlograms (black line: predicted values; red dotted lines: upper and lower significance thresholds with p=0.001) Significant bins in the monosynaptic time window (0.001-0.004s) are plotted in red and light blue. Autocorrelograms for the reference (black) and target (grey) cells are also shown. b. The putative type of the remaining cells was identified using a kmeans clustering with 2 clusters on the waveform properties of the cells (spike width and peak to trough time), separately for amygdala (BLA, BLV, LaDL, BMA and BMP; n=4 rats), olfactory areas (Pir, VEn and Den; n=4 rats) and hippocampal neurons (n=3 rats). Monosynaptically and kmeans-identified pyramidal cells and interneurons are shown in dark and light pink and blue, respectively.
a. EV and REV calculated using all hippocampus-hippocampus cell pairs (left; NREM: n= 38 sessions, p=7.75x10-05, z=3.95; REM: n= 34 sessions, p=0.965, z=0.04; n=3 rats) or putative pyramidal cells only (right; NREM: n=38 sessions, p=6.45x10-05, z=3.99; REM: n=34 sessions, p=0.499, z=-0.67; 3 rats). b. EV and REV calculated using all BLA-BLA cell pairs (left; NREM: n=34 sessions, p=0.00606, z=2.74; REM: n=28 sessions, p=0.39948, z=0.84; n=4 rats) or putative pyramidal cells only (right; NREM: n=32 sessions, p=0.00157, z=3.16; REM: n=26 sessions, p=0.158, z=1.40; n=4 rats). Some outliers (included in the analysis) are represented above the upper y-axis limit for the clarity of the scale. All boxplots show the median (red line), upper and lower quartiles (box) and maximal and minimal values excluding outliers (whiskers).
a. EV and REV calculated using all cell pairs (i.e., including pyramidal cells and putative interneurons) for NREM (n=27 sessions, p=0.00014, z=3.79; n=3 rats) and REM-sleep (n=25 sessions, p=0.47583, z=-0.71; n=3 rats), and reactivation decay over the first hour of NREM (right; n=17 sessions; p=8.85x10-05, z=3.91; p=0.00282, z=2.98; p=0.14458, z=-0.71; Wilcoxon signed rank tests; n=3 rats). b. EV and REV for pairs between hippocampus and ripple-modulated/non-ripple modulated BLA cells. Pyramidal cell pairs only (right; n=18 sessions, p=0.00053, z=3.46;p=0.00377, z=2.89; n=3 rats) and all pairs (including pyramidal and interneuron; left; n=19 sessions, p=0.00034, z=3.58; p=0.00194, z=3.09; Wilcoxon signed rank tests; n=3 rats) are shown separately. Some outliers are displayed above the y-axis limit for clarity. Reactivations were significantly higher for pairs with ripple-modulated BLA cell in both pyr-pyr and all cell conditions (Wilcoxon ranksum test on EV-REV differences; All cells: n=19 sessions, p=0.00662, z=2.71; Pyr-pyr only: n=18 sessions, p=0.00992, z=2.57; Mean EV-REV: all cells, ripple-mod 6.07+/-1.3%; non-ripple mod 1.76+/-0.56%; pyr-pyr ripple-mod 7.16+/-2.19%, non-ripple mod 1.90+/-0.71%; s.e.m; n=3 rats); All boxplots show the median (red line), upper and lower quartiles (box), maximal and minimal values excluding outliers (whiskers).
Supplementary Figure 6 A subset of cell pairs with high run correlations and ripple up-modulated BLA cell partner contribute to the reactivations.
a. Distributions of pre/post nonREM correlation differences shown separately for 9 subgroups of cell pairs based on 1) the type of modulation of the BLA cell during hippocampal ripples (up-, down- or no modulation) and 2) type of correlation during training (RUN; significantly positive, non-significant or significantly negative; see Table S2 for detailed numbers of pairs; n=3 rats, 29 sessions). b. EV and REV calculated on pairs sorted into the same 9 subgroups as shown in a.
Supplementary Figure 7 Highly contributing pairs show correlated changes between pre/post NREM correlation and pre/post run correlation.
a. Replay contributions of each pair were calculated by removing hippocampus-BLA cell pairs (pyramidal-pyramidal pairs) one by one when calculating global EV and REV (left & middle, see Methods). Right, Distribution of EV contribution of all pyramidal cell pairs, divided into four quartiles (red lines indicate division) or separating the highest and lowest 2.5% groups of the distribution (green lines; n=37,660 pairs in 3 rats). b. Changes in pre/post RUN correlation vs changes in pre/post nonREM correlations, shown separately for the four quartiles (1st: r=0.13, p=1.07x10-32; 2nd: r=0.02, p=0.042; 3rd: r=0.005, p=0.61; 4th: r=0.013, p=0.22; n=9415 pairs for each quartile, n=3 rats). c. Changes in pre/post RUN correlation vs changes in pre/post-nonREM correlations for the 2.5% highest and lowest contributing cell pairs (red/blue – same as in Fig. 7; high contribution: n=866 pairs, low contributions: n=845 pairs; n=3 rats), and the remaining 95% (grey; r=0.021, p=0.00027).
Supplementary Figure 8 Highly contributing pairs show correlated changes between pre/post NREM correlation and pre/post run correlation.
a. Average gain of up-modulated cells during pre-NREM hippocampal SPW-Rs (blue) and post-NREM hippocampal SPW-Rs (red), shown separately for the four contribution quartiles (Q). The significance of the pre/post gain difference was calculated on the avergage gain in a 500ms window centered on the ripple peak (Wilcoxon signed rank one-tailed tests; Q1: n=63 cells, p=4.5663x10-5;z=-3.9125 Q2, n=18 cells, p=0.7834 z=0.7839; Q3, n=16 cells, p=0.9704 z=1.8873; Q4,n=39 cells, p=0.9384, z=1.5420; n=3 rats) b. Normalized gain for all up-modulated BLA cells of the 3 lower contribution quartiles during pre-NREM and post-NREM SPW-Rs. Compare these plots with the those of the highest contribution quartile shown in Figure 4c.
a. EV/REV for eight firing rate groups (octiles) averaged across the individual rates of the hippocampus-BLA neuron pairs. The distribution of pairwise averaged firing rates is shown on the right (red lines: octile boundaries) b. EV/REV per octiles of firing rates of BLA cells. c. EV/REV per firing rate octiles of hippocampal cells. The distribution of hippocampal putative pyramidal cells firing rates is shown on the right (n=37,660 pairs in 3 rats for a, b and c).
A template correlation matrix is calculated for all hippocampus-BLA pairs using the binned and z-scored spike trains during training (RUN). The reactivation during each time bin of the "match" epoch, which can be pre-NREM or post-NREM, is calculated as the match between the global correlations during RUN (Crun) and the BLA-HPC correlation a time t. This gives a measure of reactivation strength over time, i.e. the match epoch variance explained by the RUN correlation. The peri-ripple reactivation strength in a +/- 2s window around ripple peaks is computed for pre-NREM (blue) and post-NREM (red) of each session.
a. Mean z-scored peri-ripple reactivation strength of the whole training session (including safe runs, airpuff runs and reward platforms) over animals and sessions for pre-NREM (blue) and post-NREM hippocampal ripples (red; mean±sem). The analysis was first restricted to pyramidal cell pairs (left, n=25 sessions in 3 rats) and then confirmed including all cell types (right, n=27 sessions in 3 rats). Barplots: reactivation strength in a 500ms window around ripple peaks (grey bar in a) was significantly higher in post-NREM compared to pre-NREM for pyramidal cell pairs (left; n=25 sessions in 3 rats, p=7.49x10-4, z=-3.175) and all cell pairs (n=27 sessions in 3 rats, p=0.00189, z=-2.895, Wilcoxon one-tailed signed rank tests). Lines from pre-NREM to post-NREM indicate single sessions. b. Mean z-scored peri-ripple reactivation strength over animals and sessions (n=27 sessions, 3 rats) for pre-NREM (blue) and post-NREM hippocampal ripples (red, ±sem) for all cell type pairs (i.e. including interneurons) for safe vs airpuff trajectories. Barplots: Reactivation strength in a 500ms window around ripple peaks (grey bar in a) was significantly higher in post-NREM compared to pre-NREM for airpuff (n=27 sessions in 3 rats, p=4.38x10-4, z=-3.327) and safe trajectories (n=27 sessions in 3 rats, p=0.036, z=-1.789; Wilcoxon one-tail signed rank tests). Lines from pre-NREM to post-NREM indicate single sessions. c. Pre/Post peak differences (postNREM - preNREM; see methods) in reactivation strength are not significantly different for safe and airpuff trajectories when all cell types are included (n=27 sessions in 3 rats, p=0.0912, z=-1.333; Wilcoxon one-tailed signed rank test). d. SPW-R occurrence rate was not different between pre-NREM and post-NREM. (Wilcoxon signed rank test, n=41 sessions in 3 rats, p=0.1972, z=-1.289). All boxplots show the median (red line), upper and lower quartiles (box), maximal and minimal values excluding outliers (whiskers).
About this article
Cite this article
Girardeau, G., Inema, I. & Buzsáki, G. Reactivations of emotional memory in the hippocampus–amygdala system during sleep. Nat Neurosci 20, 1634–1642 (2017). https://doi.org/10.1038/nn.4637
Real-Time Multi-Modal Estimation of Dynamically Evoked Emotions Using EEG, Heart Rate and Galvanic Skin Response
International Journal of Neural Systems (2020)
Philosophical Transactions of the Royal Society B: Biological Sciences (2020)
In Vivo Characterization of Neurophysiological Diversity in the Lateral Supramammillary Nucleus during Hippocampal Sharp-wave Ripples of Adult Rats
Unaltered EEG spectral power and functional connectivity in REM microstates in frequent nightmare recallers: Are nightmares really a REM parasomnia?
Sleep Medicine (2020)
A time-dependent role for the transcription factor CREB in neuronal allocation to an engram underlying a fear memory revealed using a novel in vivo optogenetic tool to modulate CREB function