During systems-level consolidation, mnemonic representations initially reliant on the hippocampus are thought to migrate to neocortical sites for more permanent storage, with an eminent role of sleep for facilitating this information transfer. Mechanistically, consolidation processes have been hypothesized to rely on systematic interactions between the three cardinal neuronal oscillations characterizing non–rapid eye movement (NREM) sleep. Under global control of de- and hyperpolarizing slow oscillations (SOs), sleep spindles may cluster hippocampal ripples for a precisely timed transfer of local information to the neocortex. We used direct intracranial electroencephalogram recordings from human epilepsy patients during natural sleep to test the assumption that SOs, spindles and ripples are functionally coupled in the hippocampus. Employing cross-frequency phase-amplitude coupling analyses, we found that spindles were modulated by the up-state of SOs. Notably, spindles were found to in turn cluster ripples in their troughs, providing fine-tuned temporal frames for the hypothesized transfer of hippocampal memory traces.
Subscribe to Journal
Get full journal access for 1 year
only $4.92 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
Born, J., Rasch, B. & Gais, S. Sleep to remember. Neuroscientist 12, 410–424 (2006).
Buzsáki, G. The hippocampo-neocortical dialogue. Cereb. Cortex 6, 81–92 (1996).
McClelland, J.L., McNaughton, B.L. & O'Reilly, R.C. Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory. Psychol. Rev. 102, 419 (1995).
Rasch, B. & Born, J. About sleep's role in memory. Physiol. Rev. 93, 681–766 (2013).
Diekelmann, S. & Born, J. The memory function of sleep. Nat. Rev. Neurosci. 11, 114–126 (2010).
Achermann, P. & Borbely, A. Low-frequency (<1 Hz) oscillations in the human sleep electroencephalogram. Neuroscience 81, 213–222 (1997).
Steriade, M., Nunez, A. & Amzica, F. A novel slow (<1 Hz) oscillation of neocortical neurons in vivo: depolarizing and hyperpolarizing components. J. Neurosci. 13, 3252–3265 (1993).
Timofeev, I., Grenier, F., Bazhenov, M., Sejnowski, T. & Steriade, M. Origin of slow cortical oscillations in deafferented cortical slabs. Cereb. Cortex 10, 1185–1199 (2000).
Nir, Y. et al. Regional slow waves and spindles in human sleep. Neuron 70, 153–169 (2011).
Massimini, M., Huber, R., Ferrarelli, F., Hill, S. & Tononi, G. The sleep slow oscillation as a traveling wave. J. Neurosci. 24, 6862–6870 (2004).
Sirota, A., Csicsvari, J., Buhl, D. & Buzsáki, G. Communication between neocortex and hippocampus during sleep in rodents. Proc. Natl. Acad. Sci. USA 100, 2065–2069 (2003).
Steriade, M. Grouping of brain rhythms in corticothalamic systems. Neuroscience 137, 1087–1106 (2006).
Andrillon, T. et al. Sleep spindles in humans: insights from intracranial EEG and unit recordings. J. Neurosci. 31, 17821–17834 (2011).
Sarasso, S. et al. Hippocampal sleep spindles preceding neocortical sleep onset in humans. Neuroimage 86, 425–432 (2014).
Mölle, M., Marshall, L., Gais, S. & Born, J. Grouping of spindle activity during slow oscillations in human non-rapid eye movement sleep. J. Neurosci. 22, 10941–10947 (2002).
Buzsáki, G., Horvath, Z., Urioste, R., Hetke, J. & Wise, K. High-frequency network oscillation in the hippocampus. Science 256, 1025–1027 (1992).
Axmacher, N., Elger, C.E. & Fell, J. Ripples in the medial temporal lobe are relevant for human memory consolidation. Brain 131, 1806–1817 (2008).
Bragin, A., Engel, J., Wilson, C.L., Fried, I. & Buzsáki, G. High-frequency oscillations in human brain. Hippocampus 9, 137–142 (1999).
Clemens, Z. et al. Temporal coupling of parahippocampal ripples, sleep spindles and slow oscillations in humans. Brain 130, 2868–2878 (2007).
Clemens, Z. et al. Fine-tuned coupling between human parahippocampal ripples and sleep spindles. Eur. J. Neurosci. 33, 511–520 (2011).
Wilson, M.A. & McNaughton, B.L. Reactivation of hippocampal ensemble memories during sleep. Science 265, 676–679 (1994).
Rechtschaffen, A. & Kales, A. A Manual of Standardized Terminology, Techniques and Scoring for Sleep Stages of Human Subjects. Brain Information Service (Brain Research Institute. University of California, Los Angeles, 1968).
Mölle, M., Bergmann, T.O., Marshall, L. & Born, J. Fast and slow spindles during the sleep slow oscillation: disparate coalescence and engagement in memory processing. Sleep 34, 1411 (2011).
Tort, A.B., Komorowski, R., Eichenbaum, H. & Kopell, N. Measuring phase-amplitude coupling between neuronal oscillations of different frequencies. J. Neurophysiol. 104, 1195–1210 (2010).
Andrade, K.C. et al. Sleep spindles and hippocampal functional connectivity in human NREM sleep. J. Neurosci. 31, 10331–10339 (2011).
Schabus, M. et al. Hemodynamic cerebral correlates of sleep spindles during human non-rapid eye movement sleep. Proc. Natl. Acad. Sci. USA 104, 13164–13169 (2007).
Bergmann, T.O., Mölle, M., Diedrichs, J., Born, J. & Siebner, H.R. Sleep spindle-related reactivation of category-specific cortical regions after learning face-scene associations. Neuroimage 59, 2733–2742 (2012).
Cox, R., Hofman, W.F., de Boer, M. & Talamini, L.M. Local sleep spindle modulations in relation to specific memory cues. Neuroimage 99, 103–110 (2014).
Cash, S.S. et al. The human K-complex represents an isolated cortical down-state. Science 324, 1084–1087 (2009).
Aru, J. et al. Untangling cross-frequency coupling in neuroscience. Curr. Opin. Neurobiol. 31, 51–61 (2015).
Kramer, M.A., Tort, A.B. & Kopell, N.J. Sharp edge artifacts and spurious coupling in EEG frequency comodulation measures. J. Neurosci. Methods 170, 352–357 (2008).
Logothetis, N.K. et al. Hippocampal-cortical interaction during periods of subcortical silence. Nature 491, 547–553 (2012).
Mölle, M., Yeshenko, O., Marshall, L., Sara, S.J. & Born, J. Hippocampal sharp wave-ripples linked to slow oscillations in rat slow-wave sleep. J. Neurophysiol. 96, 62–70 (2006).
Siapas, A.G. & Wilson, M.A. Coordinated interactions between hippocampal ripples and cortical spindles during slow-wave sleep. Neuron 21, 1123–1128 (1998).
Tort, A.B.L. et al. Dynamic cross-frequency couplings of local field potential oscillations in rat striatum and hippocampus during performance of a T-maze task. Proc. Natl. Acad. Sci. USA 105, 20517 (2008).
Cox, R., van Driel, J., de Boer, M. & Talamini, L.M. Slow oscillations during sleep coordinate interregional communication in cortical networks. J. Neurosci. 34, 16890–16901 (2014).
Tononi, G. & Cirelli, C. Sleep function and synaptic homeostasis. Sleep Med. Rev. 10, 49–62 (2006).
Isomura, Y. et al. Integration and segregation of activity in entorhinal-hippocampal subregions by neocortical slow oscillations. Neuron 52, 871–882 (2006).
Wolansky, T., Clement, E.A., Peters, S.R., Palczak, M.A. & Dickson, C.T. Hippocampal slow oscillation: a novel EEG state and its coordination with ongoing neocortical activity. J. Neurosci. 26, 6213–6229 (2006).
Mölle, M., Eschenko, O., Gais, S., Sara, S.J. & Born, J. The influence of learning on sleep slow oscillations and associated spindles and ripples in humans and rats. Eur. J. Neurosci. 29, 1071–1081 (2009).
Takeuchi, S. et al. Gamma oscillations and their cross-frequency coupling in the primate hippocampus during sleep. Sleep 38, 1085–1091 (2014).
Sullivan, D., Mizuseki, K., Sorgi, A. & Buzsáki, G. Comparison of sleep spindles and theta oscillations in the hippocampus. J. Neurosci. 34, 662–674 (2014).
Wieser, H.G., Elger, C. & Stodieck, S. The 'foramen ovale electrode': a new recording method for the preoperative evaluation of patients suffering from mesio-basal temporal lobe epilepsy. Electroencephalogr. Clin. Neurophysiol. 61, 314–322 (1985).
Ayoub, A., Mölle, M., Preissl, H. & Born, J. Grouping of MEG gamma oscillations by EEG sleep spindles. Neuroimage 59, 1491–1500 (2012).
Buzsáki, G. Hippocampal sharp waves: their origin and significance. Brain Res. 398, 242–252 (1986).
Skaggs, W.E. et al. EEG sharp waves and sparse ensemble unit activity in the macaque hippocampus. J. Neurophysiol. 98, 898–910 (2007).
Buzsáki, G., Logothetis, N. & Singer, W. Scaling brain size, keeping timing: evolutionary preservation of brain rhythms. Neuron 80, 751–764 (2013).
Ngo, H.-V.V., Martinetz, T., Born, J. & Mölle, M. Auditory closed-loop stimulation of the sleep slow oscillation enhances memory. Neuron 78, 545–553 (2013).
Gais, S., Mölle, M., Helms, K. & Born, J. Learning-dependent increases in sleep spindle density. J. Neurosci. 22, 6830–6834 (2002).
Girardeau, G., Benchenane, K., Wiener, S.I., Buzsáki, G. & Zugaro, M.B. Selective suppression of hippocampal ripples impairs spatial memory. Nat. Neurosci. 12, 1222–1223 (2009).
Iber, C., Ancoli-Israel, S., Chesson, A. & Quan, S.F. The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications (American Academy of Sleep Medicine, 2007).
Oostenveld, R., Fries, P., Maris, E. & Schoffelen, J.-M. FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Comput. Intell. Neurosci. 2011, 156869 (2011).
Berens, P. CircStat: a Matlab Toolbox for Circular Statistics. J. Stat. Softw. 31, 1–21 (2009).
Maris, E. & Oostenveld, R. Nonparametric statistical testing of EEG-and MEG-data. J. Neurosci. Methods 164, 177–190 (2007).
Mormann, F. et al. Phase/amplitude reset and thet-gamma interaction in the human medial temporal lobe during a continuous word recognition memory task. Hippocampus 15, 890–900 (2005).
Cohen, M.X. Assessing transient cross-frequency coupling in EEG data. J. Neurosci. Methods 168, 494–499 (2008).
The research was supported by a Sir Henry Wellcome Fellowship (WT089049AIA) to B.P.S., the BrainGain Smart Mix Programme of the Netherlands Ministry of Economic Affairs (T.O.B.), the VICI grant (453-09-002) from the NWO (O.J.) and the DFG grants AX82/2, AX82/3 (N.A.) and SFB1089 (N.A. and J.F.).
The authors declare no competing financial interests.
Integrated supplementary information
a. (top) Post-operative MRI (left, depicting a depth electrode implanted along the longitudinal hippocampal axis) and co-registered pre-operative MRI (right) of a sample participant. (bottom) Power spectra (NREM/WAKE) for all 10 electrode contacts of the same participant, showing a maximum in the spindle range (12-16 Hz, dashed vertical lines) in a posterior hippocampus contact which was then carried forward to the group analysis (red arrow). (inset) NREM/WAKE power spectrum for scalp electrode Cz. Y axes are identical across panels, where a ratio of 1 demarks the same spectral power during NREM and WAKE. b. Hippocampal contacts included in the analysis for all participants. Each panel shows sagittal and coronal slices of the post-operative (top) and the co-registered pre-operative (bottom) MRI for a participant. Crosshairs highlight the contact showing the largest spindle amplitudes during NREM sleep relative to WAKE of all hippocampal contacts (as shown in a for a sample participant). MRIs were unavailable for 3 of the 12 participants. Note the different implantation scheme in one participant (right bottom).
Left: SO-spindle PAC. (a) Grand average unfiltered EEG trace across participants (mean ± s.e.m.), aligned to the maximum of the SO trough (time 0). (b) Average of spindle-trough-locked TFR (% change from pre-event baseline). Y-axis starts at 5 Hz to circumvent the dominance of power in the SO range. (c) Statistically significant change from pre-event baseline (P <.05, corrected). Inset shows unit circle of preferred phases of the SO-spindle modulation for each participant, which illustrates the preferred clustering of spindle power towards the SO peak (328°, white line). Yellow circles represent participants whose Rayleigh test for non-uniformity was significant at P <.05. Right: Spindle-ripple PAC. While the EEG trace in (a) reveals the typical waxing and waning pattern of sleep spindles, no reliable ripple power modulation was observed in the spindle-peak-locked TFR (b) (see also Supplementary Table 3b; presumably due to attenuated signal-to-noise ratio of scalp EEG recordings for higher frequencies). Note that the spindle’s mean potential is above zero, reflecting the grouping of spindles in the SO peak (−.25 s to +.25 s, t(11) = 3.45, P <.01). This is further illustrated in the inset, which shows the grand average EEG trace bandpass filtered from 0.5–1.25 Hz (SO range) and from 12–16 Hz (spindle range), respectively.
(top) PETH of SO occurrences time-locked to SO down-states for Cz (left) and HC (right), highlighting multiple peaks at the distance of one SO cycle (multi-event oscillations). (bottom) PETH of spindle occurrences time-locked to spindle centers, revealing discernable peaks repeating at the SO frequency.
Supplementary Figure 4 Example hippocampal EEG traces illustrating multi-event SOs along with nested spindles.
Top: Unfiltered raw EEG traces, highlighting data segments identified as a SO (green) and spindle (blue) by our automated algorithm. Bottom: Same data segments after applying the event-specific bandpass filters (SO: 0.5–1.25 Hz, spindle: 12–16 Hz).
Bar graphs show the peri-event time histogram (PETH) of spindle center occurrences relative to ripple centers. Spindle centers show the tendency to occur after ripple centers: Within a search interval from −1 s to +1 s around ripple centers, 15.2% (s.d. = 5.0) of all ripples were followed by spindle centers and 12.6% (s.d. = 4.6) of all ripples were preceded by spindle centers. Note however that this difference in occurrence probabilities was not reliable across participants (t(11) = 1.44, P = .177). Importantly, the tendency of spindle centers to occur after ripple centers does not indicate that ripples ‘trigger’ spindles, as the spindle onset occurs at least 250 ms before the spindle center (given our spindle detection duration criterion of ≥ 500 ms). The inset shows the onsets of spindles with respect to the onset of ripples, revealing that 17.1% (s.d. = 5.4) of all ripple onsets were preceded by a spindle onset from −1 to 0 s, whereas only 9.9% (s.d. = 3.2) of all ripple onsets were followed by a spindle onset from 0 to +1 s (t(11) = 4.08, P =.002). This indicates that ripples reliably occur after a spindle has already started. Note that the same statistical result was obtained when reducing the time window to −.5 s to +.5 s around ripple onset.
a. Peri-event time histogram (PETH) showing the probability of SO occurrence (SO down-state) relative to spindle centers (t = 0 s, dashed vertical line). Dark gray area shows time interval used to determine whether a given spindle is located in the up-state of an SO (i.e., a SO down-state is temporally preceding a spindle at −1 to −0.2 s). Note that while there is a clear peak of SO occurrences in the temporal vicinity of spindles (with the asymmetry pointing to a predominant SO -> spindle sequence), many spindles occurred independently of SOs. The subsequent analyses separated spindle-ripple coupling into spindles immediately preceded by SO down-states (left column, average number of events across participants = 124, range = 30–315) and spindles not immediately preceded by SO down-states (right column, average number of events across participants = 697, range = 154–1467). b. Event-locked analysis. (i) (top) Grand average unfiltered iEEG trace across participants (mean ± s.e.m.), aligned to the maximum of the spindle trough. Insets show the bandpass filtered trace from 0.5–1.25 Hz (SO range) and from 12–16 Hz (spindle range) to better illustrate the relation of the spindle to the SO down-state. Note the pronounced SO emerging in spindle-locked raw traces on the left. (middle) Average of spindle-trough-locked TFR (% change from pre-event baseline). (bottom) Statistically significant change from pre-event baseline (P < .05, corrected, with the initial cluster threshold also set to P <.05 to accommodate smaller trial numbers). Inset shows unit circle of preferred phases of the spindle-ripple modulation for each participant. Both V tests (testing for preferred phase at 180°) are significant: spindles immediately preceded by SO down-states: V = 4.36, P =.037, spindles not immediately preceded by SO down-states: V = 5.75, P =.010. (ii) Direct comparison of spindle-trough-locked TFRs (immediately preceded by SO down-states vs. not immediately preceded by SO down-states), revealing only a relative power decrease at SO down-states, but no differential spindle-ripple modulation. (iii) Example data from one participant (same as in main Fig. 2,3,4), showing the nesting of ripples in spindle troughs for both event types. c. Comodulogram analysis. PAC was calculated for data segments around spindles (–2.5 s to +2.5 s relative to the maximum spindle trough). Maps show cluster-corrected comparisons against phase-scrambled surrogate data (all P <.05). Direct comparison of MI averaged from 12–16 Hz phase-providing frequency and 80–100 Hz amplitude-providing frequency revealed no difference between spindles immediately preceded by SO down-states vs. spindles not immediately preceded by SO down-states (using surrogate corrected MI or non-surrogate-corrected MI, both t(11) < 0.71, P >.49).
Top: Unfiltered raw EEG traces, highlighting data segments identified as a SO (green), spindle (blue) and ripple (red) by our automated algorithm. Bottom: Same data segments after applying the event-specific bandpass filters (SO: 0.5–1.25 Hz, spindle: 12–16 Hz, ripple: 80–100 Hz). Insets zoom in on the ripple event, highlighting its oscillatory nature and its nesting in spindle troughs.
Peri-event time histograms (PETH) depicting the occurrence probability of hippocampal SOs time-locked to Cz SOs (a) and of hippocampal spindles time-locked to Cz spindles (b).
Clusters showing a significant Modulation Index (MI) when comparing NREM PAC with WAKE PAC (left) and with trial-shuffled NREM surrogate data (right). Maps are thresholded to show t value clusters whose P < 0.05 and whose size exceeds 25 contiguous frequency pairs.
Supplementary Figure 10 Event-locked analysis of hippocampal PAC after re-referencing hippocampal data against the most anterior (11 participants) or lateral (1 participant) contact on the same depth electrode.
(a) Contact used for re-referencing in a sample participant (red line). (b) Grand average unfiltered EEG trace across participants (mean ± s.e.m.) and (c) average of event-locked TFR (% change from pre-event baseline), locked to SO peak (left) and spindle trough (right). Spindle power (12–16 Hz) shows a significant increase vs. baseline from.25 to.75 s after SO peak (t(11) = 2.69, P = .021) and ripple power (80–100 Hz) shows a significant increase vs. baseline from –.25 to +.25 s around maximal spindle trough (t(11) = 4.00, P = .002). Spindle power (12–16 Hz) also showed a significant increase in the re-referenced data when aligning the TFR to the ripple center (as done in main text Fig. 4a, t(11) = 4.81, P <.001, –.25 to +.25 s around ripple center).
About this article
Cite this article
Staresina, B., Bergmann, T., Bonnefond, M. et al. Hierarchical nesting of slow oscillations, spindles and ripples in the human hippocampus during sleep. Nat Neurosci 18, 1679–1686 (2015). https://doi.org/10.1038/nn.4119
Dynamics of fMRI patterns reflect sub-second activation sequences and reveal replay in human visual cortex
Nature Communications (2021)
Frontiers in Psychology (2021)
Journal of Comparative Neurology (2021)
The nucleus reuniens, a thalamic relay for cortico-hippocampal interaction in recent and remote memory consolidation
Neuroscience & Biobehavioral Reviews (2021)
Neuroscience & Biobehavioral Reviews (2021)