Abstract
Cortical slow waves reflect the need for sleep, and their presence indicates a state of disconnection and homeostatic regulation. However, little is known about the neural signatures of sleep need beyond the cortex. Here we performed chronic, continuous, 48-h Neuropixels recordings in male rats to capture hippocampal activity over sleep/wake cycles. We show that hippocampal sharp waves (SPWs) and, to some extent, ripples and dentate spikes (DSs) closely reflect sleep need. Hippocampal SPWs occurred during behavioral sleep and, unlike cortical slow waves, also during quiet wake. The expression of hippocampal SPW, ripple and DS during cortical wakefulness was negatively correlated with that during subsequent cortical sleep, suggesting that these events fulfill similar homeostatic functions. Moreover, the slow-to-fast gamma ratio was always high during SPW, consistent with a switch to a partially disconnected mode. We propose that SPWs define a partially disconnected, homeostatically regulated, unitary state of the hippocampus, which we refer to as ‘hippocampal sharp wave sleep’.
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Data availability
All processed data needed to reproduce statistical results and figures are publicly available at https://gin.g-node.org/grahamfindlay/Findlay_et_al_2025_Nature_Neuroscience ref. 108. Access to unprocessed data is available upon request from the corresponding authors.
Code availability
All original code is available at https://github.com/grahamfindlay/Findlay_et_al_2025_Nature_Neuroscience ref. 106.
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Acknowledgements
The authors are grateful to C. Punke for sleep scoring, to K. Driessen for many helpful conversations and for helping in developing methods, to D. Retzlaff for managing over half a petabyte of data, to B. Karsh for SpikeGLX and his eagerness to accommodate the unique challenges of multiday continuous recordings and to R. Mao, J. Ellefson, S. Loschky and F. Squarcio for the help with SDs. This work was supported fully or in part by U.S. Department of Defense grant (W911NF1910280 to C.C. and G.T.), NIH grant (1R01GM116916 to G.T.) and the Tiny Blue Dot Foundation (to G.T.).
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C.C., G.T. and G.F. designed the study and wrote the paper. G.F. and M.L.C. collected the data. G.F. and T.B. analyzed the data. G.F. and W.M. performed the statistical analysis.
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Extended data
Extended Data Fig. 1 Examples of single-unit activity during NREM sleep associated with sharp waves (SPWs) and dentate spikes (DSs).
a, Subset of thalamic, neocortical, and subcortical regions from the full dataset is shown, chosen to illustrate diversity of modulation. In 11 of 16 subjects, additional Neuropixel probes were implanted in more anterior and/or posterior regions of the brain, including frontal and visual cortical areas and striatum. Hippocampal pyramidal cells, narrow interneurons, and wide interneurons were classified on the basis of their NREM waveform and autocorrelogram shapes102. Perievent time histograms were computed using 25 ms bins for windows extending ±10 s around each event, then Z-scored relative to this entire window. Only cells that could be tracked continuously for the full 48 h of experiments featuring sleep deprivation with novel object exposure are shown, ±1 s around event, shaded regions represent standard error of the mean. CA1 (n = 20), CA3 (n = 45), DG (dentate gyrus; n = 35). b, Same for thalamic single units. Po (posterior medial nucleus; n = 298), LP (lateral posterior nucleus; n = 182), VPM (ventral posterior medial nucleus; n = 126), CL (central lateral nucleus; n = 44), LD (lateral dorsal nucleus; n = 26). c, Same for neocortex. PPC (parietal association cortex; n = 72), M2 (secondary motor cortex; n = 275), PrL (prelimbic cortex; n = 234), Cg1 (cingulate area 1; n = 81), VO (ventral orbital cortex; n = 54), MO (medial orbital cortex; n = 49), IL (infralimbic cortex; n = 38), V2 (secondary visual cortex; n = 28). d, Same for CPu (caudate putamen; n = 30), CLA (claustrum; n = 58), BRF (brainstem reticular formation; n = 36), ZI (zona incerta; n = 36) and OB (olfactory bulb; n = 21).
Extended Data Fig. 2 Comparison of sleep architecture by experiment type (novelty and locomotion).
a, Proportion of total time spent in each state (‘fractional occupancy’). There are no significant differences between novelty (n = 16 subjects) and locomotion (n = 8 subjects) experiments in baseline or recovery. b, Same data, but presented to facilitate comparison between baseline and recovery. Sleep deprivation in both experiments induces similar increases in NREM occupancy, and novelty also increases time spent in REM sleep. Black bars represent significant differences, assessed using general linear hypothesis tests on mixed effects models. Gray bars indicate that either a main effect or post hoc test was nonsignificant. The gray dot in a indicates a p-value between 0.05 and 0.1. All tests were two-sided and corrected for multiple comparisons (see Supplementary Table 1, Supplementary Information, and Methods for details). Boxplots show medians and quartiles. Whiskers are drawn to the farthest datapoint within 1.5 IQRs from the nearest hinge. c, Mean cumulative distribution functions for bout duration, separated by sleep stage (columns), experiment type (row) and presleep or postsleep deprivation (color), with 95% confidence intervals. Sleep deprivation in both novelty and locomotion experiments produces a clear rightward shift of NREM bout duration, and locomotion results in longer REM bouts without changes in time spent in REM sleep (b).
Extended Data Fig. 3 Slow wave, sharp wave, ripple and dentate spike properties by experiment type.
a, Same data as Fig. 2d and Supplementary Table 1, separated by experiment. In this and the following panels, bars above plots indicate general linear hypothesis tests on mixed effects models (n = 29 sessions of 3 kinds from 16 animals). Black bars reflect post hoc comparisons that were significant. Black bars with triangular endcaps indicate the presence of a significant interaction between experiment and condition, assessed using an asymptotic likelihood ratio test. Black bars with circular endcaps reflect the absence of a significant interaction between experiment and condition, but a significant main effect of condition. All tests were two-sided and corrected for multiple comparisons (see Supplementary Table 1 and Methods for details). Note that in the dual experiment, the time elapsed between early and late extended wake is longer than for novelty and locomotion, and the time elapsed between early and late recovery sleep is shorter. b, Same data as Fig. 2e, separated by experiment. c, Same data as Fig. 2f, separated by experiment. d, Same data as Fig. 3e, separated by experiment. e, Cortical power in the 2–6 Hz range during extended wake, replicating20. Power was computed identically to SWA, but for the frequencies of interest (2–6 Hz). As for SWA, a linear mixed effects model was created using all six conditions of interest (early and late baseline NREM sleep, early and late extended wake, early and late recovery NREM sleep) and tested for an interaction of condition with the 2–6 Hz power. After finding a significant interaction (p < 1 × 10−7; f2 = 0.447), we performed post hoc tests for a difference between early and late extended wake, which were significant for novelty (p = 0.017; d = 0.873; n = 12 subjects) and locomotion (p = 0.017; d = 1.23; n = 6 subjects), but not dual (p = 0.182; d = 0.755; n = 5 subjects). Boxplots show medians and quartiles. Whiskers are drawn to the farthest datapoint within 1.5 IQRs from the nearest hinge. f, Neocortical single unit mean firing rates in early and late baseline NREM sleep (ON periods; blue), early and late extended wake (green), and early and late recovery NREM sleep (red), for putative pyramidal cells (n = 721), narrow interneurons (n = 83), and wide interneurons (n = 55). All data are from novelty experiments, and only cells that could be tracked continuously for the full 48 h were analyzed. Bars above plots indicate post hoc tests performed on mixed effects models. Examination of residual plots revealed that model assumptions of constant variance and normality were better satisfied by square-root transformation of firing rates than log transformation, so the former was used for statistical analyses. The full model was formulated with condition as primary covariate and a nested random effects structure, with unique cell ID nested inside subject. A main effect of condition was found in every case, followed by post hoc tests for comparisons between conditions. The somewhat paradoxical increase in pyramidal cell firing rates from early to late recovery sleep may be explained by the relatively short elapsed duration between the two conditions (relative to early and late baseline sleep), since late recovery sleep was constrained to fall within the light cycle, to account for the known effects of immediate light exposure on cortical SWA (Methods). During this period, NREM sleep is prioritized over REM sleep, the latter of which may be associated with the largest decreases in firing rate24. g, As in f, but for hippocampal single units (putative pyramidal cells, n = 27; narrow interneurons, n = 57; wide interneurons, n = 16). See Methods (spike sorting) for details. In f,g, boxen plots show the median and quartiles, and a number of additional quantiles proportional to the size of the data: In both f and g, additional boxes show the 12.5% and 87.5% quantiles. In f only, outer boxes show the 6.25% and 93.75% quantiles.
Extended Data Fig. 4 Measures of locomotor and exploratory activity during sleep deprivation.
a, Comparing EMG levels across conditions shows no significant differences between early and late extended wake, regardless of experiment, suggesting that increases in SPW-ripples during sleep deprivation are not attributable to muscle fatigue. Right, same extended wake data, faceted by experiment type (novelty, n = 12 subjects; locomotion, n = 6 subjects; dual, n = 5 subjects) and showing within-subject changes. b, Hippocampal theta shows a strong, significant increase over the course of extended waking in both novelty and locomotion experiments (the lack of change from early to late dual extended wake should be interpreted with care, since it is a comparison of forced locomotion (early) to novelty (late)). The increase in theta during sleep deprivation is the opposite of what one might expect if muscle fatigue had increased during sleep deprivation. c, Over long timescales theta power on its own may be confounded by broader homeostatic tendencies. Taking the ratio of hippocampal theta to hippocampal delta effectively normalizes theta to account for broader spectral changes. The theta:delta ratio does not change significantly from early to late extended wake in novelty experiments. It shows a slight but significant increase in locomotion experiments, and a slight but significant decrease in dual experiments. Black bars represent significant differences, assessed using general linear hypothesis tests on mixed effects models. All tests were two-sided and corrected for multiple comparisons (see Supplementary Table 1 for p-values and effect sizes, and Supplementary Information for confidence intervals; see Methods for details). In a–c, boxplots show medians and quartiles. Whiskers are drawn to the farthest datapoint within 1.5 IQRs from the nearest hinge. d, Normalizing theta by delta (or overall spectral power) still produces a measure that behaves similarly to theta in most respects and provides information complementary to EMG. The black solid line indicates the presence of a significant linear relationship in the absence of an interaction with experiment type. Linear relationships and 95% confidence intervals are model expectations estimated using a marginal effects method (see Supplementary Table 1 for p-values and effect sizes, and Supplementary Information for confidence intervals; see Methods for details).
Extended Data Fig. 5 Comparison of sharp wave, ripple and dentate spike properties during sleep deprivation with novel objects after free behavior versus after forced locomotion.
In novelty experiments, subjects are sleep deprived using novel objects after a night of free behavior. In dual experiments, subjects are sleep deprived using novel objects after forced locomotion (conveyor). a, Comparing the first hour of novel object exposure in both cases shows that SPW rate and amplitude are higher after forced locomotion. b-c, As for SPW rate and amplitude, ripple rate, DS rate, and DS amplitude are higher after forced locomotion. Boxplots show all subjects (n = 16), including the subset (n = 11), who did not experience novel object exposure after forced locomotion. Boxplots show medians and quartiles. Whiskers are drawn to the farthest datapoint within 1.5× IQRs from the nearest hinge. Black bars represent significant differences, assessed using asymptotic likelihood ratio tests on mixed effects models (see Supplementary Table 1 for p-values and effect sizes, and Supplementary Information for confidence intervals; see Methods for details). Pair plots show only subjects who received both kinds of novel object exposure within the same experiment (that is, ‘dual’ experiments) (n = 5).
Extended Data Fig. 6 Effect of REM sleep on SPW rate and amplitude.
We identified all episodes of REM sleep that were ‘sandwiched’ on either side by episodes of NREM sleep, and possibly preceded by IS. That is, we found all NREM1 → REM → NREM2 and NREM1 → IS → REM → NREM2 sequences. We then computed the change in mean within-subject, Z-scored SPW rate and amplitude from pre-REM (NREM1) to post-REM (NREM2). a, Left, the distribution of changes in NREM SPW amplitude from pre-to-post-REM sleep. Right, the same changes in SPW amplitude as a function of the sandwiched REM sleep bout’s duration. b, Same as a, but for SPW rate.
Extended Data Fig. 7 Relationships between cortical DS, SPW and spindles.
a, Consistent with recent reports29, most DSs were not expressed within +/− 50 ms of an SPW (median (IQR) 91.8% (90.1–93.2%), n = 29 sessions of 3 kinds from 16 subjects). b, Cross-correlograms of DS-ripple coupling during Wake, NREM sleep, IS and REM sleep. There was a small increase in the probability of ripples around the time of DSs, and a smaller increase in the probability of DSs around the time of ripples, also replicating29. Shaded regions represent 95% confidence intervals for the mean (n = 29 sessions of 3 kinds from 16 subjects). c, Various spindle properties during early and late baseline NREM sleep, and early and late recovery NREM sleep. d, Spindle and DS detection rates in wake, NREM sleep, intermediate state (IS) and REM sleep. Although spindle rates were high in IS sleep relative to NREM sleep, DS rates were not. In c and d, black bars represent significant differences, assessed using general linear hypothesis tests on mixed effects models. Gray bars indicate that either a main effect or post hoc test was nonsignificant. All tests were two-sided and corrected for multiple comparisons (see Supplementary Table 1 for p-values and effect sizes, and Supplementary Information for confidence intervals; see Methods for details). Boxplots show medians and quartiles. Whiskers are drawn to the farthest datapoint within 1.5 IQRs from the nearest hinge. e, Little-to-no coupling of DS to spindles was observed. Right, normalized or ‘excess’ ripple probabilities, after accounting for covariation of event rates at timescales greater than 2 s (shift-predictor method, 1 s jitter, 100 surrogates each). Shaded regions represent 95% confidence intervals for the mean. f, Ripple probability was consistently modulated by spindle occurrence. g, No qualitative difference was observed in the spindle-ripple cross-correlogram profile either over or between baseline and recovery NREM sleep. Shaded regions represent 95% confidence intervals for the mean (n = 29 sessions of 3 kinds from 16 subjects) in e–g.
Extended Data Fig. 8 Additional analyses of cortical and hippocampal sleep needs.
a, Time points (1 h each) used for comparison (as in Fig. 4). b, Lack of significant correlation between SPW-ripple and DS rebounds between early recovery sleep and matched circadian time in baseline (n = 28 sessions of 3 kinds from 16 animals). c, Lack of correlation between cortical SWA rebound and changes in most hippocampal parameters (ripple frequency being the exception) during recovery sleep (n = 28 sessions of 3 kinds from 16 animals). In this and the following panels, the asterisk on the x-axis indicates that the hippocampal parameter did not show a significant difference across the interval being considered (for example, early and late recovery sleep in c). d, As in c, but for the baseline day (n = 28 sessions of 3 kinds from 16 animals). e,f, Same as c and d but, analogously to Fig. 4, expanded to include additional cortical regions (64 observations across 13 cortical areas) and the possibility of an interaction with neocortical region—primary visual (V1; n = 6), secondary visual (V2; n = 14), primary motor (M1; n = 4), secondary motor (M2; n = 10), medial parietal association (mPPC; n = 8), lateral parietal association (lPPC; n = 4), prelimbic (PrL; n = 5), cingulate (Cg1; n = 4), infralimbic (IL; n = 3), ventral orbital (VO; n = 3), medial orbital (MO; n = 1), entorhinal (EC; n = 1), retrosplenial (RS; n = 1). For analysis, areas were grouped (see Methods for details)—M1 and M2 into motor cortex (n = 14), V1 and V2 into visual cortex (n = 20), mPPC and lPPC into parietal association cortex (n = 12), VO, MO, IL, PrL, and Cg1 into frontal cortex (n = 16), and EC and RS into parahippocampal cortex (n = 2). Solid gray and gold lines indicate significant linear relationships in the presence of an interaction between experiment and the covariate (not region), and black solid lines indicate the presence of a significant linear relationship in the absence of an interaction. The solid green line in e indicates a negative correlation between DS amplitude decline and cortical SWA decline only in visual cortex following locomotion. Interactions and main effects were assessed using asymptotic likelihood ratio tests, and post hoc tests were performed using general linear hypothesis tests. All tests were performed on linear mixed effects models, were two-sided and corrected for multiple comparisons. Linear relationships and 95% confidence intervals are model expectations estimated using a marginal effects method (see Supplementary Table 1 and Methods for details).
Extended Data Fig. 9 Slow:fast gamma ratios by region.
a, Slow:fast gamma ratio in 1-s bins when SPWs are present (SPW-wake, NREM) or absent (no-SPW wake) (n = 29 sessions of 3 kinds from 16 subjects). Boxplots show medians and quartiles. Whiskers are drawn to the farthest datapoint within 1.5× IQRs from the nearest hinge. b, As in a, subdividing the 1-s epochs based on the number of SPW (n = 47,028,743 epochs across 29 sessions of 3 kinds from 16 animals). Given that (1) the association of higher slow/fast gamma with higher numbers of SPW is present in most areas, (2) is not maximal in the stratum radiatum, where artifactual gamma should be highest (for example, stratum oriens c.f. stratum radiatum), and (3) is present in bins with only 1 SPW, it is unlikely that the entire association is driven by the artifactual increase in slow gamma induced by ripple chains39. c, As in b, but showing slow gamma only. Note the association of SPW number with slow gamma in remote, upstream regions that are dominant sources of physiological slow gamma (DG and CA3), where no SPW-associated waveform that can induce artifactual gamma is present. Boxen plots show the median for each distribution in b and c, and the logarithm of each distribution’s size determines the number of quantile ranges shown, so that each level accounts for half of the remaining probability mass, and the outermost boxes approximate the data’s Tukey fences.
Extended Data Fig. 10 Power spectral densities by region and condition.
a, Time points (1 h each) used for comparison. b, Mean power spectral density (PSD) and 95% confidence interval, colored by condition according to a. c, Comparisons between PSD in b, expressed as percent change. For example, NREM rebound (dark purple) is the percent change in early recovery NREM power spectral density relative to late baseline NREM. All comparisons are performed within-subject before averaging. Shaded regions show 95% confidence intervals. For space reasons, all data presented are from novelty experiments. No qualitative differences were observed for locomotion or dual experiments. As expected, the largest modulation is of cortical low frequencies, being ~150–200% higher in early recovery sleep than in late (circadian-matched) baseline sleep. The next largest modulation is of ripple power in the stratum pyramidale, being ~ 50–150% higher in early recovery sleep than in late baseline sleep, and of low frequencies in the stratum oriens, being ~50–80% higher in early recovery sleep than in late baseline sleep. Rebound in hippocampal high frequencies is more moderate (~20–40%) elsewhere.
Supplementary information
Supplementary Information
Supplementary Figs. 1–5 and Supplementary Note (statistical data).
Supplementary Table 1
Exact P values and effect sizes for main text Figs. 2d-i, 3e-f, 4b-e, 5a,c, Extended Data Figs. 2a-b, 3a-f, 4a-d, 5a-c, 7c-d, 8b-f, and Supplementary Fig. 5c. All tests were performed on LME models, were two-sided and corrected for multiple comparisons. Interactions and main effects were assessed using asymptotic likelihood ratio tests, and post hoc tests were performed using general linear hypothesis tests. All other statistical data, including test statistics, regression coefficients, confidence intervals and effect sizes for nonsignificant results, can be found in the Supplementary Note, and all statistical code is publicly available on GitHub. See Methods for details. For Fig. 4d,e and Extended Data Fig. 8e,f, results of tests for interactions are reported in the following order: region–experiment–covariate/experiment–covariate/region–covariate/experiment–region.
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Findlay, G., Cavelli, M.L., Bugnon, T. et al. A hippocampal ‘sharp-wave sleep’ state that is dissociable from cortical sleep. Nat Neurosci (2025). https://doi.org/10.1038/s41593-025-02141-8
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DOI: https://doi.org/10.1038/s41593-025-02141-8
