LETTER

doi:10.1038/nature09633

Preplay of future place cell sequences by
hippocampal cellular assemblies
George Dragoi1 & Susumu Tonegawa1

During spatial exploration, hippocampal neurons show a sequential
firing pattern in which individual neurons fire specifically at particular locations along the animal’s trajectory (place cells1,2).
According to the dominant model of hippocampal cell assembly
activity, place cell firing order is established for the first time duringexploration, to encode the spatial experience, and is subsequently
replayed during rest3–6 or slow-wave sleep7–10 for consolidation of
the encoded experience11,12. Here we report that temporal sequencesof firing of place cells expressed during a novel spatial experienceoccurred on a significant number of occasions during the resting or
sleeping period preceding the experience. This phenomenon, whichis called preplay, occurred in disjunction with sequences of replay of
a familiar experience. These results suggest that internal neuronal
dynamics during resting or sleep organize hippocampal cellularassemblies13–15 into temporal sequences that contribute to theencoding of a related novel experience occurring in the future.
We recorded neuronal firing sequences from the CA1 area of themouse hippocampus (Supplementary Fig. 1) during periods of awake
rest (Fam-Rest) alternating with periods of running (Fam-Run) on afamiliar track (Fam session; Supplementary Fig. 2a) that preceded the
exploration of a novel linear arm in contiguity with the familiar track(Contig-Run on L-shaped track; Fig. 1, Supplementary Fig. 2a andMethods). All the place cells active on the novel arm during ContigRun, whether previously silent16 (19% in both directions and 31% in atleast one direction; Methods and Supplementary Tables 1–3) or active
during Fam-Run (subpanels a in Fig. 1), fired during Fam-Rest at theends of the familiar track (range, 0.17–11.7 Hz; Supplementary Fig. 3)
as part of a number of ‘spiking events’. The spiking events were definedas epochs composed of multiple individual spikes from at least four
different place cells active on the novel arm or familiar track, separated
by less than 50 ms and flanked by at least 50 ms of silence3,4. Moresignificantly, the temporal sequence in which the cells active on thenovel arm fired during Fam-Rest (subpanels b in Fig. 1) was significantly correlated with the spatial sequence in which they fired later asplace cells on the novel arm during Contig-Run (subpanels c in Fig. 1),
despite being uncorrelated with their spatial sequence as place cells on
the familiar track during Fam-Run. This is illustrated as place cell
sequences during Contig-Run (subpanels c in Fig. 1) and Fam-Run(subpanels a in Fig. 1) compared with the firing sequences of these cells
within individual spiking events observed during Fam-Rest (subpanels
b in Fig. 1). We refer to this process as ‘preplay’ of place cell sequences
because the temporal sequence of firing during Fam-Rest had occurred
before the actual exploration of the novel arm in the subsequentContig-Run and was not a replay of the place cell sequences fromthe previous Fam-Run.
To quantify the significance of preplay and to compare it with replay,
we created place cell sequence templates according to the spatial orderof the peak firing of place cells3,4,10 on the novel arm during Contig-Run(novel arm templates; subpanels c in Fig. 1 and Methods) and on thefamiliar track during Fam-Run (familiar track templates) for each run
direction. The spikes of all the place cells used to construct the two typesof template that were emitted during Fam-Rest were sorted by time, andspiking events were determined as explained above (subpanels b in
Fig. 1). For each spiking event, we calculated a rank-order correlation
between the novel arm templates and the temporal sequence of firing of
the corresponding cells in the spiking events during Fam-Rest. The
event correlation was considered significant if it exceeded the 97.5th
percentile of a distribution of correlations resulting from randomly
shuffling the order of place cells in the novel arm templates 200 times(P , 0.025). Forward4 and reverse3,4 preplay refers to the cases in which
the sequence of place cells during Contig-Run and the firing order ofthe corresponding cells in Fam-Rest were in the same and opposite
directions, respectively. In 91% of the preplay cases, the spiking eventswere correlated with the novel arm template in one direction only. The
distribution of event correlation values obtained using the original
novel arm templates was significantly shifted towards higher positiveor negative values in comparison with the distribution of correlation
values obtained using shuffled templates (Fig. 2a and Supplementary
Fig. 4). Figure 2a also shows the distribution of significant preplay
events (in red). Of all the spiking events detected as above and in which
at least four novel arm place cells were active, 14.2% were significant
preplay events for the place cell sequence on the novel arm (P , 10232,
binomial probability test4) in the forward or reverse order (Fig. 2b).
The occurrence of significant preplay events was correlated with theoccurrence of high-frequency ripple oscillations in CA1 (Fig. 2c). The
majority of the significant preplay events (81.1%; Fig. 2d, total, blue)
took place at the junction between the familiar and novel arms, and theremaining 18.9% took place at the free end of the familiar track(Fig. 2d, total, purple). The proportion of significant preplay events
among the total events at each of the two track ends was higher at thejunctional end (15.2%, P , 10226) than at the free end (8.5%,
P , 1024) of the familiar track (P , 0.035, Z-test; Fig. 2d, normalized).
We found a relatively high correlation between the place field maps
(Fig. 1A, B and Supplementary Fig. 5) of the familiar track before andafter the novel experience (median r 5 0.66; Fig. 2e, familiar track,blue); it was significantly higher than the correlations obtained when
the cell identities were shuffled (median r 5 0.23, P , 1024; Fig. 2e,familiar track, black). A similar correlation analysis showed a relatively
high stability of the newly formed place fields on the novel arm fromthe beginning to the end of Contig-Run (median r 5 0.62 (newly
formed) versus median r5 0.21 (shuffled), P , 1023; Fig. 2e, novelarm, blue versus grey). These results suggest that preplay of the novelarm does not occur over an entirely new (that is, remapped) representation of the whole L-shaped track but rather benefits from therelative stability of the familiar track representation across sessions
and perhaps facilitates the rapid, stable encoding of the novel arm
experience.
Using the familiar track templates and spiking events during FamRest, constructed as above, we determined that 16.2% (P , 10291; data
not shown) were significant replay events3–6,17 among the spiking eventsin which a minimum of four familiar track place cells were active. All
significant preplay events occurring during Fam-Rest (n 5 75) were1

The Picower Institute for Learning and Memory, RIKEN-MIT Center for Neural Circuit Genetics, Department of Biology and Department of Brain and Cognitive Sciences, Massachusetts Institute ofTechnology, Cambridge, Massachusetts 02139, USA.
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RESEARCH LETTER
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Position (cm)Figure 1 | Preplay of novel place cell sequences. Fam-Run and Fam-Rest
respectively denote run and rest sessions on the familiar linear track before
barrier removal; Contig-Run denotes run sessions on the L-shaped track after
barrier removal. The L-shape track was linearized for display/analysis.
A, B, mouse 1; C, D, mouse 2; E, mouse 3. A–E, a, Spatial activity on the familiar
track during Fam-Run of the cells that had place fields in Contig-Run andpreplayed during Fam-Rest (one cell per row); activity on the novel arm andfamiliar track are on the same scale. Horizontal arrows indicate run directions.
Vertical grey bars indicate barrier locations during Fam-Run and Fam-Rest.
A–E, b, Examples of representative spiking events in the forward or reverse

direction during Fam-Rest in 250-ms time windows (350 ms for the second andfourth panels from left in E, b). Tick marks indicate individual spikes: red,
preplay events for place cell sequences in the novel arm; blue (in A, b andB, b), additional spikes from the familiar track place cells participating in the
spiking event (not shown in C–E, b). Numbers on the left denote cell numbers
and correspond to the place cell numbers in A–E, a. Square boxes indicate theends of the familiar track where preplay events occurred. Local field potentials
recorded simultaneously with the spikes are shown above spiking events.
A–E, c, Place cell sequences in the novel arm (C–E, c; red) or in both the novelarm (red) and the familiar arm (blue) (A, c and B, c) in Contig-Run.

tested for possible replay of the familiar track spatial sequence: thesespiking events were more correlated with the novel arm template(Fig. 2f, red) than the familiar track template (Fig. 2f, blue). Seventytwo percent (n 5 54) of the significant events previously considered to
be preplay had no significant correlation with the familiar track template. An additional 16% (n 5 12) of those events were better correlatedwith the novel arm templates (mean absolute r 5 0.92) than with thefamiliar track template (mean absolute r 5 0.67, P , 1023). Together,
these findings reject the hypothesis that the preplay events simply represent a replay of the familiar track activity (see additional controls in
Supplementary Information). Moreover, we found that the proportionof events exclusively composed of silent cells that perfectly matched thenovel arm spatial templates was 0.67 (16 of 24 triplets), which is significantly greater (P , 0.025) than the proportion of by-chance perfectmatches (0.33).
To illustrate the distribution and relative proportions of preplay andreplay events among all significant spiking events during Fam-Rest, we

calculated a ‘template specificity index’ (Fig. 2g and Methods) for each
event. Pure preplay events (Fig. 2g, red) and pure replay events (Fig. 2g,blue) were segregated, and only a minority of events were significant
for both preplay and replay (Fig. 2g, yellow). Consistent with thissegregation of preplay and replay events, the novel arm and the ‘corresponding familiar track’ templates were not significantly correlated(Fig. 2h and Methods). The ratio between the number of pure replay
events (n 5 171) and the number of pure preplay events (n 5 54)
during Fam-Rest was about 3.1 (Fig. 2g, inset; see Supplementary
Information for proportions of events). Preplay and replay events were
distributed in time across Fam-Rest (Supplementary Fig. 6a–c) andtheir occurrences were generally uncorrelated (Supplementary Fig. 6d).
The majority (79.9%) of the spiking events during Fam-Rest did not
significantly correlate with either of the two templates (data not shown).
We used a Bayesian reconstruction algorithm2,5,6,18,19 (Methods) to
decode the animals’ position from the spiking activity during FamRun (Fig. 3a) or Fam-Rest (Fig. 3b, c). For all original and shuffled6

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LETTER RESEARCH

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Number of eventsaFigure 2 | Quantification of the preplay phenomenon and comparison withreplay. a, Distribution of correlations between spiking events in Fam-Rest andspatial templates of the novel arm. Open bars indicate spiking events versus theoriginal (unshuffled) templates; filled bars indicate spiking events versus 200
shuffled templates scaled down 200 times; red bars show the distribution of
preplay (that is, significant) events. Similar distributions (not shown) ofcorresponding spiking events were obtained when spatial templates wereconstructed using all place cells active on the L-shaped track (Figs 1A, b, c and
1B, b, c; red and blue). b, Proportion of all, forward and reverse preplay events
among the spiking events in Fam-Rest. The dotted line indicates the chancelevel (3.2%). c, Cross-correlation between preplay events and ripple epochs.
d, Location of preplay events on the familiar track: total, proportions of preplay
events at ends of the track; normalized, proportion of preplay events
normalized by the number of spiking events at each end of track. Preplay events
represented a trajectory running from the free end of the novel arm to thejunctional end (40%) or begun near the familiar track (60%); the latter suggeststhat in some cases preplay events could be triggered by the activity of thefamiliar track place cells during Fam-Rest. e, Stability of place cell spatial tuning
across the novel experience: familiar track, stability of the place fields active on
the familiar track before (Fam-Run) versus after (Contig-Run) barrier removal;
novel arm, stability of the place fields active on the novel arm at the beginning(first four laps of run) versus the end (last four laps) of the Contig-Run session.
Data (blue), within-cell correlation of place cell spatial tuning for thecorresponding track/arm; shuffle (black), cell identity shuffle (Supplementary
Information). Error bars, s.e.m.; asterisks in d and e indicate significant
differences. f, Distribution of preplay event correlations (red) versus
distribution of these event correlations with the familiar track template (blue).
Spiking events were detected using all place cells from the familiar track andnovel arm templates (.1 Hz). Red bars are the same as in a. Correlation isstrong with the novel arm template (preplay) and weak with the familiar arm
template (replay). The P value corresponds to there being a significant
difference between the two distributions. g, Disjunctive distribution of pure
preplay (red), pure replay (blue) and preplay/replay (yellow) events during
Fam-Rest over their template specificity index (Supplementary Information).
Inset, proportions of pure preplay events (red), pure replay events (blue) and
preplay/replay events (yellow) among all of the spiking events that weresignificantly correlated with at least familiar track templates or novel arm
templates. h, Lack of correlation between the novel arm template and thecorresponding familiar track template. Each of the six dots represents either aforward or a reverse run direction of one of the three mice analysed. Red
horizontal line denotes a P value of 0.05. The correlation values were notsignificant in any of the cases (Supplementary Information).

probability distributions, a line was fitted to the data using a line-finding
algorithm6 to represent the decoded virtual trajectory (Methods
and Supplementary Information). In 16.36% of cases representing
trajectories, the reconstructed trajectory during spiking events in FamRest was contained within the novel arm (Fig. 3c, top), a place theanimal had not yet visited (that is, trajectory preplay). Moreover, in
79.8% of the trajectory preplay cases the shuffling procedures resulted
in lines that were significantly less or not at all contained within thenovel arm (that is, not preplay; Supplementary Information). The
remaining trajectories decoded during Fam-Rest represented replayof the familiar track (64.15%; Fig. 3c, middle) or spanned the joint
familiar track/novel arm space (19.49%; Fig. 3c, bottom). Means ofabsolute rank-order correlations between spiking activity and novel
arm templates (Fig. 2a) restricted during epochs of trajectory preplay
were significantly larger than those between spiking activity and familiar
track templates calculated during the same epochs (0.75 versus 0.59,
P , 1024). Overall, these results support the existence of the preplay
phenomenon.
To investigate the possibility that preplay of novel arm place cell
sequences during Fam-Rest depends on the prior run experience on
the familiar track, mice with no prior experience on any linear track
were placed in a high-walled sleep box and recorded while resting/sleeping. The animals were then transferred to a novel isolated linear
track that was in the same room but could not be seen from inside thebox, and the recording continued during de novo formation of place
cells (Supplementary Fig. 2b, de novo session). We found that in a
relatively large proportion (16.1%) of spiking events identified during
sleep/rest in the sleep box, the neuronal firing sequences were significantly correlated with the place cell sequences observed during the firstrun session on the novel track (Fig. 4A, B and Methods); this was thecase for all four individual mice (Supplementary Fig. 7). Preplay eventswere associated with the ripple occurrence (Fig. 4C). The place cells
established on the novel track in the de novo session were more
dynamic (median r 5 0.42; Fig. 4D, blue) than in Contig-Run (medianr 5 0.62, P , 0.016; Fig. 2e, right, blue).
We have demonstrated that a significant number of temporal firing
sequences of CA1 cells during resting periods of a familiar track
exploration that preceded a novel track exploration in the same generalenvironment were correlated with the place cell sequences of the novel
track rather than the familiar track. This phenomenon, preplay, is
temporally opposite to the process of replay3–10,19,20, when activity during rest or sleep periods recapitulates place cell sequences that havealready occurred during previous explorations. Preplay differs fundamentally from replay because it occurs before exploration of novel
tracks.
Although our recordings were carried out in CA1, we believe thatwhat we observed could be a reflection of the output of the recurrent
cellular assemblies from upstream regions (CA3 or entorhinal cortex).
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RESEARCH LETTER

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Time (s)Figure 3 | Bayesian reconstruction of the animal’s trajectory in the familiar
track (replay) and novel arm (preplay). a, Position reconstruction of a one-lap
run on the familiar track from the ensemble place cell activity during Fam-Run.
The heat map displays the reconstructed position of the animal using ensemble
place cell activity during the run (250-ms bins; animal velocity, .5 cm s21).
The yellow line indicates the actual trajectory of the animal during Fam-Run.
b, Example of virtual trajectory reconstruction (familiar track and novel arm)from the ensemble place cell activity during Fam-Rest at the ends of the familiar
track (20-ms bins; animal velocity, ,5 cm s21) before barrier removal andnovel arm exploration. The yellow line reflects the spatial location of the animalin time: the animal was immobile at the junction end of the familiar track. The
time-compressed (,5 m s21) trajectory reconstruction often ‘jumps’ over thebarrier (top of the figure) into the novel arm area. At around 0.5 s, a preplay of
the novel arm initiated from the distal (free) end of the novel arm ‘propagates’
towards the location of the animal. c, Examples of preplay of the novel arm(top), replay of the familiar track (middle) and preplay of the novel arm
together with replay of the familiar track (bottom) during Fam-Rest. All
conditions are the same as in b. The white line shows the linear fit maximizing
the likelihood along the virtual trajectory. Colour bars indicate probability of
trajectory reconstruction.

During running on a familiar track, some of the cells in the postulated
upstream cellular assemblies fire sequentially at spatial locations whileothers, although connected anatomically to these cells, remain silent.
The lack of expression of preplay sequences during Fam-Run may
reflect their state-dependent suppression or subthreshold activation
during these exploratory behaviours. Owing to increased net excitation
during rest periods predominantly during ripples21, some of thesesilent cells together with some of the familiar track cells are activatedabove threshold and fire in a certain sequence. Their sequence ofactivation may be determined in part by their functional connectivity
within the hippocampal formation network. Some of these sequences
may in turn be activated on a novel track as place cell sequences(Supplementary Fig. 8). The activation of the novel place cell sequences
during running may strengthen their pre-existing assembly organization manifested during preplay.
It could be argued that during Contig-Run the animals simply considered the novel arm to be an extension of the familiar arm and, thus,
what we considered to be preplay events were replays of the previous
runs on the familiar track. If this was the case, preplay events would not

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Figure 4 | Preplay of novel place cell sequences before any linear track
experience. A, Sleep/rest session in the sleep box (Pre-Run sleep/rest) before
the first run session on a linear track (De novo-Run). Display format is the sameas in Fig. 1. A, a, Representative spiking events in the forward or reverse orderduring Pre-Run sleep/rest in 400-ms time windows. A, b, Place cell sequenceson the novel track (red) during the De novo-Run session. Each row represents
one cell in which the activity was normalized to the maximum firing rate. One
run direction in one animal is shown. The median number of place cells activeon the novel track participating in preplay events is six. B, Distribution of
spiking events in Pre-Run sleep/rest as a function of the rank-order correlation
with the place cell sequence template of the novel track. Display format is thesame as in Fig. 2a. C, Cross-correlation between preplay events and ripple
epochs during Pre-Run sleep/rest. D, Stability of place cell spatial tuning acrossthe novel track experience. Display format is the same as in Fig. 2e (novel arm).
Error bars, s.e.m.; asterisk indicates significant difference.

be expected to be found when the experience of the familiar track run iseliminated. This idea was refuted by the demonstration of frequent
preplay events in the sleep box before the mice were transferred onto anovel linear track (de novo condition). Under this condition, the place
cell sequences were more dynamic and a higher proportion of all
spiking events correlated with the place cell sequences in these runs
than in the later runs on novel linear tracks. These results suggest ashift in the relative contribution of internal22,23 and external drives in
the formation of place cell sequences on encounter with a novel track.
In the early phase, internal drives originating in the dynamic cellularassembly activities, which probably reflect numerous past experiencesdistinct from the current one and expressed as preplay, may have agreater role, whereas in the late phase, external drives that come fromthe specific set of stimuli of the current experience may dominate.
Thus, place cell sequences on novel tracks seem to be products of a
dynamic interplay between the internal and external drives.
Several previous studies did not reveal preplay7,8,10,20. Although it isdifficult to pinpoint the apparent discrepancies between these studies
and the present one, we suggest that the use of insufficiently sensitive
methods (pairwise correlations) by some studies7,8,20 and small sample
sizes by others10 might have precluded detection of preplay in previous
work (see Supplementary Information for details). Data from the denovo condition (Fig. 4), in which we observed an even higher proportion of preplay events, have not been reported previously.
Our data showed that novel preplay events coexist in disjunction
with familiar replay events during the rest periods on the familiar
track. This and the finding that these preplay and replay events
together make up fewer than one-quarter of all detected spiking events
suggest that they are part of a dynamic repertoire of temporalsequences in the hippocampus that are past-experience dependent(replay) or future-experience expectant24 (preplay). Post-experience
replay of place cell sequences during resting3–6 or slow-wave sleep8–10
has been proposed to have an important role in memory consolidation11,12. The temporal preplay of new place cell sequences duringresting or sleep is consistent with a predictive function for the hippocampal formation25 and may contribute to accelerating learning26

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LETTER RESEARCH
when a new experience is introduced in multiple steps of increasing
novelty.

METHODS SUMMARY
We recorded place cells from the CA1 area of the hippocampus with six independently movable tetrodes in four mice during sleep/rest sessions in the sleep box
before any experience on linear tracks and during the first run session on a novel
track. Following familiarization with the linear track, animals were subsequently
allowed to explore a continuous (L-shaped) track in which the now familiar track
and a new novel arm were made contiguous. To quantify the significance of the
preplay and replay processes, spiking events in which at least four cells were active
were detected during sleep/rest (speed, ,1 cm s21) periods in the sleep box orawake rest (speed, ,2 cm s21) periods at the ends of the familiar track and novelarm, predominantly during ripple epochs.
We calculated statistical significance at the P , 0.025 level for each event bycomparing the rank-order correlation between the event sequence and the place
cell sequence (template) with the distribution of correlation values from 200 templates obtained by shuffling the original order of the place cells. Proportions ofsignificant events were calculated as the ratio between the number of significant
events and the total number of spiking events. We calculated the overall significanceof preplay or replay processes by comparing the distribution of correlation values ofall events with the distribution of correlation values of shuffled templates(Kolmogorov–Smirnov test). The significance of the proportion of significant events
out of the total number of spiking events was determined as the binomial probabilityof observing the number of significant events (as successes) from the total number ofspiking events (as independent trials), with a probability of success of 0.025 in any
given trial. We reconstructed the position of the animal from the spiking activity
emitted during resting periods using Bayesian decoding procedures6.
Full Methods and any associated references are available in the online version of
the paper at www.nature.com/nature.
Received 4 December 2009; accepted 29 October 2010.
Published online 22 December 2010.
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population activity by reconstruction: unified framework with application tohippocampal place cells. J. Neurophysiol. 79, 1017–1044 (1998).
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Supplementary Information is linked to the online version of the paper at
www.nature.com/nature.
Acknowledgements We thank M. A. Wilson for assistance with data acquisition,
discussions and comments on an earlier version of the manuscript; J. O’Keefe,
A. Siapas, F. Kloosterman, D. L. Buhl for comments on earlier versions of themanuscript; and F. Kloosterman for providing assistance with the line detection for theBayesian decoding. This work was supported by NIH grants R01-MH078821 andP50-MH58880 to S.T., who was an HHMI Investigator in an earlier part of this study.
Author Contributions S.T. and G.D. conceived the project jointly. G.D. designed andperformed the experiments and the analyses. G.D. and S.T. wrote the paper.
Author Information Reprints and permissions information is available atwww.nature.com/reprints. The authors declare no competing financial interests.
Readers are welcome to comment on the online version of this article atwww.nature.com/nature. Correspondence and requests for materials should be
addressed to G.D. (gdragoi@mit.edu) or S.T. (tonegawa@mit.edu).

2 0 J A N U A RY 2 0 1 1 | VO L 4 6 9 | N AT U R E | 4 0 1©2011 Macmillan Publishers Limited. All rights reserved

RESEARCH LETTERMETHODS
Surgery and experimental design. Electrophysiological recordings were performed on four C57BL/6 mice (strain NR1-floxed27) with ages between 18 and
22 weeks. All animals were implanted under Avertin anaesthesia with six independently movable tetrodes aiming for the CA1 area of the right hippocampus(1.5–2 mm posterior to bregma and 1–2 mm lateral to the midline; Supplementary
Fig. 1). The reference electrode was implanted posterior to lambda over the cerebellum. During the following week of recovery, the electrodes were advanced daily
while animals rested in a small, walled sleeping box (12 3 20 cm2, 35 cm high). The
animal position was monitored by means of two infrared diodes attached to theheadstage.
The experimental apparatus consisted of a 90 3 65 cm2 rectangular, walled,
linear track maze. All tracks were 4 cm wide at the bottom and 8–9 cm wide at
the top, and all linear track walls were 10 cm high. Experimental sessions wereconducted while the animals explored for chocolate sprinkle rewards placedalways at the ends of the corresponding linear tracks (one sprinkle at each endof the track on each lap). Neuronal activity was recorded in naive animals (fourmice) during the sleep/rest session in the sleep box immediately preceding the firstexperience on linear tracks, and continued (Fig. 4) during the first run session on anovel track. After familiarization with the linear track, the animals went through arecording session of 15–60 min (Fam session), and the recordings continued forthe next 34–42 min (Contig session) while the animals explored an L-shaped track
for the first time. In this track, the familiar arm and the novel arm were madecontiguous by removing the barrier that had separated them (Fig. 1). For the
purpose of analysing the recording data, the Fam session was further divided into
Fam-Run, in which the animals ran through the track (velocity of animal’s movement was higher than 5 cm s21), and Fam-Rest, where the animals took awake rests
at the ends of the track (velocity of animal’s movement was less than 2 cm s21).
During resting periods, the animals consumed the chocolate sprinkle andgroomed, but mostly they were still until they self-initiated the next lap of run
on the linear track. After completion of the experiments, the brains of all mice were
perfused, fixed, sectioned and stained using nuclear fast red (Supplementary Fig. 1)
or cresyl violet for electrode track reconstruction.
Recordings and single-unit analysis. A total of 87 neurons were recorded fromthe CA1 area of the hippocampus in four mice during the Fam and Contig sessions(Supplementary Tables 1–3). A total of 69 CA1 neurons were recorded from thefour mice in the de novo condition (26, 20, 10 and 13 cells, respectively). Single cells
were identified and isolated using the manual clustering method Xclust2 and theapplication of cluster quality measurements28. Pyramidal cells were distinguishedfrom interneurons on the basis of spike width, average rate and autocorrelations22.
Place fields were computed as the ratio between the number of spikes and thetime spent in 2-cm bins along the track, smoothed with a Gaussian kernel with astandard deviation of 2 cm. Bins where the animal spent a total of less than 0.1 s
and periods during which the animal’s velocity was below 5 cm s21 were excluded.
Place field length and peak rate were calculated after separating the direction of
movement and linearizing the trajectory of the animal. Linearized place fields were
defined as areas with a localized increase in firing rate above 1 Hz for at least fivecontiguous bins (10 cm). The place field peak rate and location were given by therate and location of the bin with the highest ratio between spike counts and timespent. Place field borders were defined as the points where the firing rate becameless than 10% of the peak firing rate or 1 Hz (whichever was bigger) for at least
2 cm.
Local field potential analysis. Ripple oscillations were detected during sleep/rest
periods in the sleep box and during rest periods at the ends of the tracks. The
electroencephalography signal was filtered (120–200 Hz) and ripple-band amplitude was computed using the Hilbert transform. Ripple epochs with maximal
amplitude more than 5 s.d. above the mean, beginning and ending at 1 s.d. weredetected. The time of ripple occurrence (Figs 2c and 4C) was the time of its
maximal amplitude. The proportion of ripples with which cells with place fields
on the novel arm of the L-shaped track fired in the preceding session(Supplementary Fig. 3) was calculated for each qualifying cell as the ratio between
the number of ripples during which the cell fired at least one spike and the total
number of ripples during the corresponding exploratory session.
Preplay and replay analyses. To analyse the preplay and replay processes, spiking
events were detected during Pre-Run sleep/rest periods in the sleep box (de novo
condition; velocity, ,1 cm s21) or during awake rest periods at the ends of therunning tracks (Contig condition; velocity, ,2 cm s21). A spiking event was
defined as a transient increase in the firing activity of a population of at least four
different place cells within a temporal window preceded and followed by at least
50 ms of silence. Overall, similar results were obtained using 50-, 60-, 75- and 100-ms
time windows. The spikes of all the place cells active on the novel track that were
emitted during the Pre-Run sleep/rest in the box for the de novo condition as well as
the spikes of all the place cells active on the familiar track or the novel arm that were

emitted during Fam-Rest session at the two ends of the familiar track for Contig
condition were respectively sorted by time and further used for the detection of the
spiking events.
All four animals exhibited a significant number of spiking events in the Pre-Run
session of the de novo condition. Three of the four animals (mice 1–3) exhibited asignificant number of spiking events in the Contig condition, the remaining animal(mouse 4) having a below-threshold number of simultaneously active CA1 place
cells. The time of the spiking event used to compute the cross-correlation withripple epoch occurrence (Figs 2c and 4C) was the average time of all spikes comprising the spiking event. The place cell sequences (templates) were calculated foreach direction of the animal’s movement and for each run session (De novo-Run,
Fam-Run and Contig-Run) by ordering the spatial location of the place field peaks
that were above 1 Hz. For place cells with multiple place fields above 1 Hz on aparticular arm or track in the Contig condition (six of 52 place cells active on thenovel arm in the two directions, or 12%: two for each direction in mouse 1, one inmouse 2 and one in mouse 3), only the place field corresponding to the peak firing
rate of the place cell on that arm or track was considered for the construction of thetemplate of that particular arm or track, to be consistent with all the previous
studies that used spatial templates to demonstrate replay during sleep or awake
rest3,4,10. Place cells with fields on both the novel arm in the Contig-Run session andthe familiar track in the Fam-Run session participated in the construction of boththe novel arm and familiar track templates.
Statistical significance was calculated for each event by comparing the rankorder correlation between the sequence of cells’ firing during the event (that is,event sequence) and the place cell sequence (template), on the one hand, and the
distribution of correlation values between the event sequence and 200 surrogate
templates obtained by shuffling the order of place cells, on the other4 (Fig. 2a). The
significance level was set at 0.025 to control for multiple comparisons (two directions of run). The proportions of significant events (preplay novel track, preplay
novel arm (Fig. 2b), replay novel arm and replay familiar track) were each calculated as the ratio between the number of significant events and the total number ofspiking events in which at least four corresponding place cells were active4.
Corresponding familiar track templates (Fig. 2h) were constructed by ordering
the location of peak firing on the familiar track during Fam-Run (no minimum
threshold of firing) of all place cells that subsequently fired on the novel arm. Cells
comprising the corresponding familiar track templates are the same as thosecomprising the novel arm templates. We note that these corresponding familiar
track templates are different from the ones used in Figs 1 and 2a–g, which wereconstructed by ordering the peak firing of all place cells active on the familiar track.1 Hz.
The overall significance of the preplay (Fig. 2a) or replay process was calculated
by comparing the distribution of correlation values of all events relative to theoriginal template with the distribution of correlation values relative to the shuffledsurrogate templates, using the Kolmogorov–Smirnov test3. Quantification of thereplay versus preplay events during the Fam-Run session (Fig. 2f, g) was performed as described above using different spatial templates for the familiar track
and the novel arm. All spiking events were correlated with both the novel arm andthe familiar track templates. Events significantly correlated only with familiar
track or with novel arm templates were considered pure replay and pure preplay,respectively. The template specificity index was calculated for each event as thedifference between the absolute value of the event’s correlation with the novel arm
template (preplay, high positive index) and the event’s correlation with the familiar track template (replay, high negative index). For the purpose of displaying thetemplate specificity index, events correlated with the novel arm but not with thefamiliar track templates were considered preplay and events correlated with thefamiliar track but not with the novel arm templates were considered replay(Fig. 2g). Additionally, events correlated with both the familiar track and the novel
arm templates formed a third group, preplay/replay events, displayed in yellow in
the inset of Fig. 2g.
Correlations between pairs of familiar track and novel arm templates (Fig. 2h)
were performed using modified familiar track templates that were constructedusing the location of peak firing (.0 Hz) of only those cells that had place fields on
the novel arm (peak rate, .1 Hz). The lack of significant correlation in this casedemonstrates that the novel arm place cell sequence is not simply a transpositionof a familiar track place cell sequence on the novel arm.
We also identified neurons that did not fire during Fam-Run, that activatedduring Fam-Rest events and that corresponded to trajectories on the novel arm
during Contig-Run (silent cells). We calculated the correlation between the orderin which they fired during Fam-Rest events and their spatial sequence as new place
cells on the novel arm during Contig-Run, as previously explained. Owing to the
low absolute number of silent neurons, only triplets of cells were available forfurther analysis (n 5 24). The proportion of events perfectly matching the spatial
template was compared with the proportion of by-chance perfect matching (0.33).

©2011 Macmillan Publishers Limited. All rights reserved

LETTER RESEARCH
Stability of place cell maps. Stabilities of place cell firing on the familiar track
before and after barrier removal as well as on the novel track (de novo condition)and the novel arm (Contig condition) in the beginning versus the end of the run
session were assessed by calculating, for each place cell and each direction, acorrelation between the spatial firing in the corresponding paired situations(before versus after barrier removal for the familiar track or the first four laps
versus the last four laps of the De novo-Run or Contig-Run session for the novel
track or arm, respectively). The place cell activity was not partitioned in place
fields; rather, the whole activity on the particular track or arm was consideredseparately for each cell and direction (average correlations are shown in Figs 2e
and 4D, blue bars). In addition, we calculated the same type of correlation after
shuffling the identity of the cell in one member of the correlation (once for eachdifferent cell; average correlations are in Figs 2e and 4D, black bars). Shuffle results(Figs 2e and 4D, black bars) were computed as correlation between spatial tuningof cells on the familiar track during Fam-Run and spatial tuning of all othersimultaneously recorded cells on the familiar arm during Contig-Run (familiar
track group; Fig. 2e, left), or correlation between spatial tuning of cells on the novelarm (or novel track) during the beginning of Contig-Run (or De novo-Run) andspatial tuning of all the other simultaneously recorded cells on the novel arm (ornovel track) during the end of Contig-Run (novel arm group; Fig. 2e, right) or De
novo-Run (Fig. 4D). Original and shuffled correlations were compared using therank-sum test. The average number of laps (traversal of the novel track in both
directions) per session was 20.5 in De novo-Run (21, 16, 27 and 18 in the four mice)and 16.3 in Contig-Run (13, 14 and 22 in the three mice).
Bayesian reconstruction of actual and virtual trajectories. For each cell, we
calculated a linearized spatial tuning curve on the familiar track during the
Fam-Run session and a linearized spatial tuning curve on the novel arm during
the Contig-Run session. The tuning curves were constructed in 2-cm bins fromspikes emitted in both run directions at velocities higher than 5 cm s21, and weresmoothed with a Gaussian kernel with a standard deviation of 2 cm. We constructed a joint spatial tuning curve for each cell by juxtaposing the spatial tuning
curve on the familiar track during the Fam-Run session and the spatial tuning
curve on the novel arm during the Contig-Run session. We also detected for eachcell all the spiking activity emitted at velocities below 5 cm s21 during the FamRest session, where replay and preplay events where shown to occur using therank-order correlation method. We used a Bayesian reconstruction algorithm6,18
to decode the virtual position of the animal from the spiking activity during FamRest (Fig. 3b) in non-overlapping, 20-ms bins using the joint spatial tuning curves.
We then extracted epochs of reconstructed trajectory matching the time of the
spiking events as detected using multiunit activity of place cells from the familiar

track and novel arm (rank-order correlation method; see ‘Preplay and replay
analyses’, above).
We used two shuffling procedures to measure the quality of the Bayesian
decoding. In the first shuffling procedure, for each event, the original time-bin
columns of the probability distribution function (PDF) were replaced with anequal number of time-bin columns randomly extracted from a pool containing
the time-bin columns of all PDFs of all detected events6. The shuffling procedure
was repeated 500 times. In the second shuffling procedure, the identity of the place
cells was randomly shuffled 100 times and new PDFs were calculated for all events.
For all original and shuffled PDFs, a line was fitted to the data using a previously
described line-finding algorithm6. Lines fitted to the original and shuffled data
were compared using slope, spatial extent, location on the track and probability
score. We defined replay and preplay as the epochs of Fam-Rest in which thereconstructed trajectory was located on the familiar track or the novel arm,
respectively. The trajectory was defined across a set of position estimates during
the corresponding epoch (Fig. 3c). Only epochs that lasted at least 60 ms (threebins) and which contained reconstructed trajectories spanning at least 10 cm wereconsidered for further analysis. Trajectories for which 75% or more of their length
was located on the familiar track were considered to represent replay of an animal’s
trajectory on the familiar track (Fig. 3c, middle), and trajectories for which 75% ormore of their length was located in the novel arm were considered to represent
preplay of the animal’s future trajectory on the novel arm (Fig. 3c, top). The
remaining events were considered preplay–replay (Fig. 3c, bottom).
An epoch was considered significant if the new line was less than 75% containedin the familiar track for replay or novel arm for preplay in at least 95% of the
shuffled cases. For each epoch that was significant for replay or preplay using thereconstruction method, we retrieved the value of the rank-order correlation
between the neuronal firing sequences and the familiar track and novel arm spatial
templates as calculated using the rank-order correlation method. We compared
the absolute correlation values between the epoch’s firing sequences and familiar
track templates with the absolute correlation values between the same epoch’s
firing sequences and novel arm templates. We also reconstructed the trajectory of
the animal on the familiar track from the spiking activity during the Fam-Run
session at velocities above 5 cm s21 in 250-ms bins using the spatial tuning curves
on the familiar track6,18 (Fig. 3a) to validate the decoding procedure.
27. Tsien, J. Z., Huerta, P. T. & Tonegawa, S. The essential role of hippocampal CA1
NMDA receptor-dependent synaptic plasticity in spatial memory. Cell 87,
1327–1338 (1996).
28. Schmitzer-Torbert, N., Jackson, J., Henze, D., Harris, K. & Redish, A. D. Quantitative
measures of cluster quality for use in extracellular recordings. Neuroscience 131,
1–11 (2005).

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