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Sleep loss diminishes hippocampal reactivation and replay

Abstract

Memories benefit from sleep1, and the reactivation and replay of waking experiences during hippocampal sharp-wave ripples (SWRs) are considered to be crucial for this process2. However, little is known about how these patterns are impacted by sleep loss. Here we recorded CA1 neuronal activity over 12 h in rats across maze exploration, sleep and sleep deprivation, followed by recovery sleep. We found that SWRs showed sustained or higher rates during sleep deprivation but with lower power and higher frequency ripples. Pyramidal cells exhibited sustained firing during sleep deprivation and reduced firing during sleep, yet their firing rates were comparable during SWRs regardless of sleep state. Despite the robust firing and abundance of SWRs during sleep deprivation, we found that the reactivation and replay of neuronal firing patterns was diminished during these periods and, in some cases, completely abolished compared to ad libitum sleep. Reactivation partially rebounded after recovery sleep but failed to reach the levels found in natural sleep. These results delineate the adverse consequences of sleep loss on hippocampal function at the network level and reveal a dissociation between the many SWRs elicited during sleep deprivation and the few reactivations and replays that occur during these events.

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Fig. 1: SD yields more SWRs but with weaker power and higher frequency ripples.
Fig. 2: Hippocampal firing rates are elevated and more dispersed during SD.
Fig. 3: Reactivation attenuates during SD and is not restored by RS.
Fig. 4: Trajectory replays deteriorate over SD and RS.

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Data availability

The processed group data for this study are available at https://doi.org/10.7302/73hn-m920, which includes NumPy (.npy) files used to generate most of the figures in this study. The remainder of the long-duration datasets generated during and analysed for the present study will be made available by the corresponding author on request.

Code availability

All analyses were performed using custom codes written in Python. General-purpose code is available in our laboratory’s public GitHub repository (https://github.com/diba-lab/NeuroPy, v.0.1). Code specific to this project and used for generating figures herein is located at https://github.com/diba-lab/sleep_loss_hippocampal_replay (v.0.2).

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Acknowledgements

This work was funded by the US National Institute of Mental Health (R01MH117964 to K.D. and T.A.) and by the US National Institute of Neurological Disorders and Stroke (R01NS115233 to K.D.).

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Contributions

K.D., T.A. and B.G. conceived the project. B.G. performed the experiments. B.G. and N.K. analysed the data. U.K. and K.M. contributed analytical insights. K.D. supervised the research. K.D. and B.G. wrote the manuscript with input and edits from T.A. and N.K.

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Correspondence to Kamran Diba.

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The authors declare no competing interests.

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Nature thanks Antoine Adamantidis, Vladyslav Vyazovskiy and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data figures and tables

Extended Data Fig. 1 Power spectra and delta for all recorded sessions.

Power spectral density of the CA1 local field potential (LFP), z-scored over 1–10 Hz for the time periods shown, with temporal evolution of delta (white) overlaid for each recorded session (similar to in Fig. 1b). Hypnograms above each panel show the brain state (active wake (AW), quiet wake (QW), rapid-eye movement (REM) sleep and non-REM sleep (NREM)). State scoring was performed at 1-s resolution but for illustration purposes is provided averaged for 30-s periods (particularly due to rapid transitions between AW and QW during SD). Animal name initial, sex and recording day are provided the left of the y-axes.

Extended Data Fig. 2 Ripple and delta features and controls across sleep and sleep deprivation sessions.

(A) Local field potential spectrogram (1–10 Hz) from a sample theta channel during recovery sleep (RS) from three rats with corresponding hypnogram indicating the scored sleep/wake state above (active wake (AW), quiet wake (QW), rapid eye movement (REM) and non-REM (NREM) sleep). The Fourier spectrogram was calculated from the whitened LFP traces using 4 s windows with 1 s overlap. Z-scored delta power (1–4 Hz, smoothed with a 12 s gaussian kernel) is overlaid in white. More detailed sleep scored sessions are available at https://github.com/diba-lab/sleep_loss_hippocampal_replay. (B) The proportion of time spent in each brain state across all sessions. Individual session values overlaid in connected dots (n = 8 NSD session and n = 8 SD sessions). We note that during sleep deprivation from ZT 0-2.5 (SD1) to ZT 2.5-5 (SD2), there was no significant change in the proportion of time in QW (P = 0.958, t(df = 7) = −0.054) or AW (P = 0.769, t(df = 7) = 0.305). (C) The rate of OFF states compared across sessions. For the non-sleep-deprived (NSD) group, OFF states were most prevalent during NS1 (ZT 0-2.5) and decreased over time, in NS2 (ZT 2.5-5) and NS3 (ZT 5-7.5). The rate of OFF states was initially lower in the SD group, but increased from SD1 to SD2, with a further large increase upon RS. (D) The rate of ripple events calculated in 5 min windows decreased over the first 5 h of NSD but remained stable during 5 h of SD. (E) Ripple rate calculated separately for NREM and WAKE states (individual sessions overlaid with connected dots). A decrease in ripple rates is observed in both NREM and WAKE in the NSD group, but there was no change in WAKE ripples from SD1 to SD2 and a decrease from SD2 to RS. Overall, NREM ripple rates were higher in NS1 vs. RS and WAKE ripple rates were higher in SD2 vs. NS2. (F) The ripple probability (solid line = mean, shaded region = s.e.m., n = 8) was modulated by delta waves. (G) However, the modulation depth of ripples by delta ((peak-trough)/mean) was not significantly different across 2.5 h blocks. (H) OFF states were frequently preceded and followed by ripples69. Modulation of OFF states by ripples did not change across NSD (n = 103,319 ripples across 8 sessions) but the probability that OFF immediately followed a ripple increased over SD, from SD1 to SD2 and further in RS, with a significant difference between RS and NS1. The inducement of OFF states by ripples is similar to the rise in OFF states following bursts induced by sensory stimulation in the cortex76. (I) Interventions needed to stop transitions to sleep during SD were tracked using piezo sensors on the sides of the home cage in 3 sessions. The number of interventions grew with time during SD. (J) Mean and 95% confidence intervals of ripple rate (left) and delta wave rate (right) relative to the onset of interventions. The rate of delta waves and concurrent ripples was higher immediately preceding interventions, consistent with signs of sleepiness that compel such interventions. (K) Ripple features (frequency, sharp wave amplitude and ripple power) evaluated separately in NREM (n = 67007 ripples from 6 NSD sessions, n = 26798 ripples from 7 SD sessions) and WAKE states (n = 74363 ripples from 6 NSD sessions and 128957 ripples from 7 SD sessions). Rightmost panels in each row provide cross-group comparisons in NS1 vs. RS strictly during NREM and NS2 vs. SD2 strictly during WAKE. These results are largely consistent with patterns in Fig. 1g–i, except that here ripple power in NS2 vs. SD2 is not significantly different during WAKE, indicating state-dependence of this effect. Additionally, we note a significant increase in ripple frequency in WAKE from PRE to POST in both NSD and SD groups, indicating an effect of the novel maze exposure. All box plots show the median and top/bottom quartiles (whiskers = 1.5 x interquartile range) of the hierarchically bootstrapped data with individual session means overlaid with connecting dots. Statistics: panels C, E, G, two-sided paired t-tests (within group) and one-sided independent groups (across groups) t-tests; panel D, Pearson correlation coefficients with two-sided p-value; panel H, χ2 tests of independence; panel K, two-sided paired within group and one-sided cross-group comparisons with hierarchical bootstrapping; ns (not significant), *P < 0.05, **P < 0.01, ***P < 0.001, with no correction for multiple comparisons. See Supplementary Tables 1 and 2 for additional details.

Extended Data Fig. 3 Firing rate changes within each state separately.

Mean firing rates calculated solely within the awake (WAKE) state (A) or solely within NREM (B) with individual sessions overlaid and connected. Differences calculated separately within wake or NREM were less pronounced than those shown in Fig. 2b,c, consistent with the noted effect of background state on hippocampal firing rates25,29. However, when estimating the metabolic cost of neuronal firing23, comparisons that overlook the state and consider temporal variations in rates, such as those depicted in Fig. 2b and c, are most appropriate. In WAKE (A), firing rates showed a trend towards decreased rates in pyramidal cells (top row) in the NSD group (n = 442 neurons from 8 sessions) but not in SD (n = 312 neurons from 8 sessions). The decrease in firing rates during brief wakings with the recovery sleep period (right panel) likewise showed a trend towards significance vs. a similar period in NSD. Interneuron firing rates (bottom row) within WAKE in recovery sleep showed a trend towards significance in comparison to the similar period in NSD (n = 48 cells from 8 NSD sessions and n = 48 cells from 8 SD sessions). In NREM (B) no significant differences were detected across groups or periods. (C) and (D) Same as (A) and (B) but for active wake (AW) and quiet wake (QW). (E) Firing rate distribution for all pyramidal cells recorded during SD sessions for AW vs. QW. Firing rates in both WAKE states remain skewed from log-normal distribution throughout SD. (F) Interquartile range (IQR) of the log firing rate of pyramidal cells reveals a trend toward a broader range of firing rates in AW vs. QW during SD. All box plots depict the median and top/bottom quartiles (whiskers = 1.5 x interquartile range) of the hierarchically bootstrapped data with individual session means overlaid with connecting dots. Statistics: A-D, F: two-sided paired within group and one-sided cross-group comparisons with hierarchical bootstrapping; E: Shapiro-Wilk tests performed on each bootstrapped log distribution, with P obtained from the proportion of bootstraps with significant skew; ns (not significant), #P < 0.1, *P < 0.05, **P < 0.01, ***P < 0.001, with no correction for multiple comparisons. See Supplementary Table 1 for additional details.

Extended Data Fig. 4 Temporal evolution of reactivation across recorded sessions.

Reactivation assessed using the explained variance (EV) metric (NSD (black), SD (red) and RS (blue)), in thirteen sessions from six different animals (3 male and 3 female, with 3 sessions from 2 animals (1 male, 1 female) excluded due to an insufficient number of stable neurons), as in Fig. 3a. Chance level (REV) is shown in maize. Solid lines show the mean and shaded regions show the standard deviation of EV/REV across all 15 min windows in POST. Each row provides session(s) from one animal, with number of putative pyramidal neurons and cell pairs used to calculate EV specified inside each panel. Hypnograms above panels depict sleep/wake history in active wake (AW), quiet wake (QW), rapid eye movement (REM) sleep and non-REM (NREM) sleep, with sleep deprivation/recovery sleep in red/blue and natural sleep in black. Animals’ tracked positions on the novel maze (purple) are depicted on the right of the panels along with the session recording day.

Extended Data Fig. 5 Accounting for the variability in reactivation during sleep deprivation.

We observed striking variability in reactivation across animals during the first block of sleep deprivation (SD1) in ZT0-2.5 (Fig. 3 and Extended Data Fig. 4). We conducted a series of analyses in an effort to account for this observation. Differences in (A) the distance run or (B) the total time spent running on the maze, did not account for the variance in EV during SD1. (C) Likewise, the variance in EV during SD1 cannot be attributed to differences in the proportion of time in active wake (left) or quiet wake (right) states during this period. (D) We next tested whether the rate of delta waves during sleep deprivation (top row, n = 7 sessions), an indicator of sleep pressure, could explain the variance in EV during SD1. Remarkably, there was a strong significant negative correlation (P = 0.006) between the rate of delta from ZT 2.5-5 (SD2) and the reactivation (EV) during SD1. If delta during SD2 thus relates to animal’s level sleepiness, consistent with the sleep homeostasis model24,38, the level of sleepiness correlates with the amount of hippocampal reactivation we observe during SD1. In contrast, we observed no correlation between EV and delta at any timepoint for NSD (bottom row, n = 6 sessions). (E) A similar relationship was not evident between delta waves and EV in NS2. (F) Reactivation (EV) during SD1 was not predictive of the reactivation during RS. Statistics: All panels, Pearson correlation coefficients with two-sided P-values, **P < 0.01, with no correction for multiple comparisons.

Extended Data Fig. 6 Comparisons across 1-hour blocks.

Changes in ripple properties, firing rates, explained variance and replays were assessed using 1-h blocks, based on the last hour of PRE, 1-h periods immediately after MAZE (ZT 0-1) and 1-h blocks immediately before and after recovery sleep (ZT 4-5 and ZT 5-6). All box plots depict the median and top/bottom quartiles (whiskers = 1.5 x interquartile range) of the hierarchically bootstrapped data with individual session means overlaid with connecting dots. Similar to our results for 2.5 h blocks in the main text, (A) ripple frequency (left) decreased over NSD (n = 143681 ripples total from 8 sessions) but increased in SD (n = 157964 ripples total from 8 sessions) relative to MAZE, with a rebound drop in RS (ZT 5-6). Rightmost panel highlights cross-group comparisons for the first block of sleep (NS1 vs. RS) and second block of SD vs. NSD. In both groups, sharp-wave amplitudes (middle) and ripple power (right) increased from MAZE to the first block of POST (ZT 0-1). Sharp-wave amplitude (middle) and ripple power (right) further increased in RS. Cross-group comparisons at ZT 4-5 showed increased ripple power in NSD compared to SD. (B) Firing rate of pyramidal neurons show decreasing firing rates during sleep but not during SD (n = 442 pyramidal neurons / 48 interneurons from 8 sessions NSD, 312 pyramidal neurons / 48 interneurons from 8 sessions SD). (C) EV was significantly lower in SD at ZT4-5 compared to NSD, with a modest but significant rebound during RS, but to lower levels than during the first hour of natural sleep. n = 20544 cell-pairs from 6 NSD sessions and n = 8114 cell-pairs from 7 SD sessions. (D) (left). The proportion of candidate ripple events that decoded continuous trajectories in different epochs (n = 65744 candidate events from 7 SD sessions and n = 56669 candidate events from 6 NSD sessions). SD sessions featured significantly fewer trajectory replays by ZT4-5. Critically, the proportion of replays in RS was significantly lower than in NS1. Similar results were observed for replay number (middle). A significant decrease was observed in mean replay event duration (right) for SD (n = 13911 replays from 7 sessions) but not NSD (n = 15866 replays from 6 sessions) from ZT0-1 to ZT4-5. Statistics: two-sided within-group comparisons and one-sided cross-group comparisons with hierarchical bootstrap, #P < 0.1, *P < 0.05, **P < 0.01, ***P < 0.001, with no correction for multiple comparisons. See Supplementary Table 1 for additional details.

Extended Data Fig. 7 Replay characterization during NREM and WAKE.

(A) Replays showed no bias in directionality. (B) The total number of candidate events decreased during POST in non sleep-deprivation (NSD, n = 64205 candidate events from 6 sessions) but remained elevated during sleep deprivation (SD, n = 72584 candidate events from 7 sessions) from the first to second block (SD1 to SD2), but dropping from SD2 to recovery sleep (RS). (C) The proportion of candidate events that scored as trajectory replays in NSD and SD groups, measured separately in WAKE (n = 30852 events from 6 NSD sessions and n = 59820 events from 7 SD sessions) and NREM (n = 32258 events from 6 NSD sessions and 11903 events from 7 SD sessions) states in each block. The rightmost panel provides comparisons between the first block of extended NREM sleep for each group (ZT 0-2.5 in the NSD group vs. ZT 5-7.5 in the SD group) and between WAKE during the second (late) block of POST (ZT 2.5-5 for both groups). There was a significantly lower proportion of trajectory replays in NREM recovery sleep (RS) compared to natural sleep (NS1) and fewer in WAKE (SD2 vs. NS2), demonstrating that these results were significant when assessed within states as well as when compared across time blocks that involved pooled states, as in Fig. 4. Note also that there was a significant increase in the proportion of trajectory replays during NREM from PRE to POST, consistent with previous studies indicating increased replay following novel MAZE exposure43,44. (D) Same as (C) but for the total number of trajectory replay events. Interestingly, the total number of trajectory replays decreased within WAKE in the NSD group, but did not change within SD, resulting in a greater total number of trajectory replays in SD2 compared to NS2. Importantly, however, there were significantly fewer trajectory replays in NREM RS vs. NS1. (E) Same as (C) but for duration of trajectory replay events (NREM: n = 8291 replays from 6 NSD sessions, n = 1869 replays from 7 SD sessions; WAKE: n = 9128 replays from 6 NSD sessions, n = 12940 replays from 7 NSD sessions). Note the decreased duration of these events during waking in SD2 vs. SD1. All box plots depict the median and top/bottom quartiles (whiskers = 1.5 x interquartile range) of the hierarchically bootstrapped data with individual session means overlaid with connecting dots. Statistics: Panel A: two-tailed, paired t-tests for within group comparisons and one-tailed Welch’s t-tests for cross-group comparisons; Panels B-E, two-sided within-group comparisons and one-sided cross-group comparisons with hierarchical bootstrap, #P < 0.01, *P < 0.05, **P < 0.01, ***P < 0.001, with no correction for multiple comparisons. See Supplementary Tables 1 and 2 for additional details.

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Supplementary Tables

Details of statistics for parametric and hierarchical bootstrap tests conducted for figures and Extended Data figures.

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Giri, B., Kinsky, N., Kaya, U. et al. Sleep loss diminishes hippocampal reactivation and replay. Nature 630, 935–942 (2024). https://doi.org/10.1038/s41586-024-07538-2

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