Propagation of Specific Network Patterns Throughthe Mouse Hippocampus

Martin Both,1* Florian Bahner,1 Oliver von Bohlen und Halbach,2 and Andreas Draguhn1

ABSTRACT: Network oscillations bind neurons into transient assem-blies with coherent activity, enabling temporal coding. In the mamma-lian hippocampus, spatial relationships are represented by sequences ofaction potentials of place cells. Such patterns are established duringmemory acquisition and are re-played during sharp wave-ripple com-plexes in CA1 in subsequent sleep episodes. These events originate inCA3 and travel towards CA1 and downstream cortical areas. It isunclear, however, whether specific sequences of ripple-associated firingare solely defined within the CA1 network or whether these patternsare directly entrained by preceding activities of neurons within CA3.Using a model of sharp wave-ripple oscillations (SPW-R) in mouse hip-pocampal slices we analyzed the propagation of these signals betweenCA3 and CA1. We found tight coupling between high-frequency net-work activity in CA3 and CA1. Propagation of ripples through the hip-pocampal loop maintained precise temporal relationships at the networkand cellular level, as indicated by coupling of field potentials, multiunitand single cell activity between major portions of CA3 and CA1. More-over, SPW-R-like activity in CA1 could be elicited by electrical stimula-tion within area CA3 while antidromic activation of CA1 failed toinduce organized high-frequency oscillations. Our data show that thespecificity of neuronal assemblies is maintained with cell-to-cell preci-sion while SPW-R propagate along the hippocampal loop.VVC 2008 Wiley-Liss, Inc.

KEY WORDS: high-frequency oscillations; assemblies; memory; sharpwaves; ripples

INTRODUCTION

Temporal coding is of key importance for spatial memory formationin the mammalian hippocampus. During exploration of an open field,principal neurons in the rodent hippocampus discharge at specific loca-tions (O’Keefe and Dostrovsky, 1971; O’Keefe and Nadel, 1978). Theseplace cells are phase-coupled to the underlying theta network oscillation(McNaughton et al., 1983; O’Keefe and Recce, 1993; Skaggs et al.,1996) such that they establish sequences of action potentials which, inprinciple, allow for a reconstruction of the animal’s trajectory. Duringsubsequent phases of rest or slow-wave sleep, the same sequences arere-played on top of fast �200 Hz ‘‘ripple’’ oscillations which are super-

imposed on sharp waves (forming sharp wave-ripplecomplexes, SPW-R; Skaggs and McNaughton, 1996;Wilson and McNaughton, 1994). It has been sug-gested that the formation of such place-cell firingsequences forms a transiently stored representation ofspatial information in the hippocampal network, whiletheir re-play during sleep mediates consolidation ofspatial/declarative memory by transferring this infor-mation to neocortical areas (Buzsaki, 1989, 1998;Nadasdy et al., 1999; Battaglia et al., 2004; Ji andWilson, 2007).

Sharp wave-ripple complexes propagate from areaCA3 (where they appear as network bursts) towardsCA1, and then leave the hippocampal formation viathe subiculum and the entorhinal cortex (EC)(Chrobak and Buzsaki, 1994, 1996; Csicsvari et al.,2000; Maier et al., 2003). During this state, the hip-pocampus seems to be less controlled by input fromthe EC but rather generates output signals which areendogneously generated within the hippocampal net-works (Chrobak and Buzsaki, 1994, 1996). The re-activation of specific sequential firing patterns duringSPW-R in CA1 requires precise selection of participat-ing pyramidal cells and precise timing of their activa-tion within network events at a millisecond time scale.Several local network mechanisms underlying thesewell-defined spatio-temporal activity patterns havebeen identified within CA1, including strong inhibi-tion of nonparticipating pyramidal cells during SPW-R (Ylinen et al., 1995; Maier et al., 2003), electricalcoupling of CA1 pyramidal cells (Draguhn et al.,1998; Schmitz et al., 2001), and the ability to bringabout fast (�200 Hz) oscillations within the isolatedCA1 (Nimmrich et al., 2005). Nevertheless, SPW-R-events are initiated by propagating excitatory wavesfrom CA3. This opens the possibility that CA1 py-ramidal cells receive specific instructions from theupstream CA3 network for ripple-associated firingduring sharp waves. Alternatively, the excitatory inputfrom CA3 would provide a rather unspecific activationof local networks within CA1 which can autono-mously generate highly specific patterns of activity.

Here, we addressed this question by analyzing thecoupling of cell firing between CA3 and CA1 duringSPW-R. We found that discharges of single pyramidalcells within CA3 are precisely phase-coupled to net-work ripples in CA1 showing that this hippocampalsubfield receives specific instructions from an upstreamnucleus. In addition, SPW-R could not be triggered

1 Institute of Physiology and Pathophysiology, University of Heidelberg,Im Neuenheimer Feld 326, 69120 Heidelberg, Germany; 2 Institute forAnatomy and Cell Biology, University of Heidelberg, Im NeuenheimerFeld 307, 69120 Heidelberg, Germany

*Correspondence to: Martin Both, Institute of Physiology and Pathophysi-ology, University of Heidelberg, Im Neuenheimer Feld 326, 69120Heidelberg, Germany. E-mail: mboth@physiologie.uni-heidelberg.de

Grant sponsor: Deutsche Forschungsgemeinschaft; Grant numbers: DFGDr 326/1-4, SFB 636.

Accepted for publication 19 March 2008DOI 10.1002/hipo.20446Published online 20 May 2008 in Wiley InterScience (www.interscience.wiley.com).

HIPPOCAMPUS 18:899–908 (2008)

VVC 2008 WILEY-LISS, INC.

by local activation of CA1 but required preceding activation ofCA3 networks. These findings show that CA1 is not auto-nomous in generating the highly organized network activity ofsharp wave-coupled ripple oscillations but is entrained by spe-cific input from CA3.

METHODS

Experiments were performed on male C57Bl6 mice aged 4–8 weeks and were approved by the state government of Baden-Wurttemberg. Brains of ether-anesthetized mice were removedand cooled to 1–48C in artificial cerebrospinal fluid (ACSF),containing (mM): NaCl 124, KCl 3, MgSO4 1.8, CaCl2 1.6,glucose 10, NaH2PO4 1.25, NaHCO3 26, saturated with 95%O2/5% CO2 (pH 7.4 at 378C). After removal of the cerebel-lum and frontal brain structures, we cut horizontal slices of450 lm on a vibratome (Leica, VT 1000 S, Germany). Beforestarting recordings, slices were allowed to recover for at least2 h in a Haas-type interface recording chamber at 35 6 0.58C.Some experiments were performed at 32 6 0.58C where unitdischarges could be separated more clearly. SPW-R waveformwas maintained at this temperature, albeit with slightly lowerripple frequency. Glass microelectrodes for extracellular record-ing had tip diameters of >5 lm and were filled with ACSFbefore use. Extracellular field potentials were recorded from thepyramidal layers of CA1 and CA3, respectively, and from stra-tum radiatum of CA1. Potentials were amplified 3100 with aEXT 10–2F amplifier (npi electronic, Tamm, Germany), low-pass filtered at 3,000 Hz, and digitized at 5–10 kHz for off-line analysis (1401 interface, CED, Camebridge, UK). Unit ac-tivity was recorded with tetrodes (Thomas Recording, Giessen,Germany) with �40 lm distance between the central contactand the outer contacts which were separated by �20 lm.These signals were recorded with custom made pre-amplifiers,amplified 310,000, high-pass filtered at 500 Hz with DPA2FX amplifiers (npi electronic, Tamm, Germany) and digitizedat 20 kHz. Electrical stimulation was performed with bipolarplatinum/iridium wire electrodes which were located in thealveus, in the Schaffer collaterals, or in CA3 stratum pyrami-dale, respectively. Monopolar square pulses of 50 or 100 ls du-ration were delivered at the strength indicated in the resultssection.

Juxtacellular recording were performed with glass electrodes(12–25 MX) filled with �1.5% Neurobiotin in 0.5 M NaClwith a SEC-05LX amplifier (npi electronic, Tamm, Germany)in bridge mode. The signal was low-pass filtered at 8 kHz anddigitized at 20 kHz. Action potentials were detected offlineafter high-pass filtering at 500 Hz and setting a threshold at sixtimes standard deviation (SD) to an ‘up-only’ filtered signal(Cohen and Miles, 2000). After unit-recording (75–3,076 s),positive current steps (up to 9 nA, 200 ms) were applied toobtain juxtacellular labeling (Pinault, 1996). Neurobiotin stain-ings of cell populations (see Fig. 6) were performed by applica-tion of 2–3 small pellets of dry neurobiotin onto the surface of

the slice (pyramidal cell layer and edge of the cut alveus). Sliceswere maintained in the interface recording chamber for a mini-mum of 30 min before fixation in 4% paraformaldehyde inphosphate buffer for at least 48 h (48C). Subsequently, sliceswere embedded in 4% (w/v) agar in phosphate buffered saline(PBS) and were re-sectioned at 50 lm with a vibrating blademicrotome (Leica VT-1000S, Leica Microsystems, Wetzlar, Ger-many). Sections were mounted on superfrost microscope slides(Menzel-Glaser, Braunschweig, Germany) and stored at2208C. For staining, sections were permeated in methanol(2208C) for 10 min and then rehydrated in PBS at room tem-perature. Background fluorescence was minimized by incuba-tion in 0.3 M glycine in PBS for 30 min. After three washingsteps, unspecific antibody binding sites were blocked with 1%bovine serum albumin in PBS. Cells were stained with an avi-din-Alexa Fluor488 conjugate (Invitrogen, Karlsruhe, Germany)at 48C overnight. For identification and reconstruction ofstained neurons, z-stacks (step-width 1 lm) were generatedusing a high-resolution digital camera (Axiocam, Zeiss, Ger-many) attached to a fluorescence microscope with a motorizedstage (Axioplan Imaging, Zeiss, Germany), controlled by thecustom-made software AxioVision (Zeiss, Germany). These z-stacks were analyzed and neurons were reconstructed using Neu-roLucida (MBF Biosciences, USA).

Data Processing and Analysis

Data were sampled with the Spike-2 program (CED, Cam-bridge, UK) and analyzed off-line using custom-written rou-tines in Matlab (The MathWorks, Natick, MA). Sharp waveswere detected after low-pass filtering of raw data at 50 Hz andfinding local maxima with �120 lV amplitude within 30 mstime windows. This value corresponds to 4 SDs of event-freebaseline noise (Maier et al., 2003) yielding stable and reliabledetection of SPW-R (as confirmed by visual inspection of tracesand detected events). Subsequently, sharp wave-ripple com-plexes or stimulation-evoked field potentials were analyzed withcontinuous wavelet transform (complex Morlet wavelet), start-ing 33 ms before and ending 67 ms after the peak of thedetected sharp wave (Figs. 1B,C). From this spectrogram, weextracted the leading ripple frequency and the peak power ofthe oscillation at frequencies higher than 140 Hz. Also, thetime delay between the point of peak power and the maximumof the underlying sharp wave was extracted from the spectro-gram. For detection of extracellularly recorded action potentials(‘units’), raw data were high-pass filtered at 500 Hz and singleevents were extracted by setting a threshold at four times SDto an ‘up-only’ filtered signal (Cohen and Miles, 2000).

Coupling strength of unit firing to field ripple was computedfrom event cross-correlograms of units and ripple troughs. Ifthere is a stable temporal correlation between unit firing andphase of the ripple oscillation (cycle length �5 ms) these dia-grams show prominent peaks at intervals corresponding to thecycle length of individual ripple cycles (Fig. 2B). To quantifythe coupling strength we constructed cumulative diagrams ofaction potentials (units) with respect to one full ripple cycle

900 BOTH ET AL.

Hippocampus

around the most prominent peak (maximal amplitude in thecross-correlogram, see Figs. 2B,C). This cumulative distributionwas normalized to 100%. A random distribution of actionpotentials with respect to ripples would result in 50% of spikesoccurring within 50% of the full cycle time. Lower values(50% of spikes occurring in less than 50% of the ripple cycle)indicate a temporal correlation between spikes and individualripples. This time (expressed as % of the full ripple cycle) wasused as a quantitative measure of the spike-ripple coupling.Lower values indicate stronger coupling. The procedure isshown in Figure 2C. The same procedure was used to evaluatethe coupling between units at one recording location and unitsat another recording site (Fig. 3D), to evaluate cross-correla-tions between ripple field and units over long distances betweenmultiple electrodes (Fig. 3C) and between single-unit activityin CA3 and field ripples in CA1 (Fig. 4). In multi-electroderecordings from different locations in CA3 and CA1, delaysbetween units in CA3 and corresponding ripples in CA1 werecalculated. In principal, the delay was taken as the time shifttowards 0 of the peak in the cross-correlogram of units in CA3versus ripples in CA1. As described above, these cross-correlo-grams show prominent peaks with 5 ms modulation. In orderto correct for this phase modulation and to obtain an accuratevalue for the mean time required for activity propagating from

CA3 to CA1, we used the shuffled cross-correlograms (seeabove) which show a smooth, Gaussian-like peak.

Quantitative results are given as mean 6 s.e.m. Significanceof results was tested by Wilcoxon rank sum test or Kruskal-Wallis nonparametric one-way Analysis of Variance and P <0.05 was regarded as significant.

RESULTS

Spontaneously occurring network events were recorded asfield potentials in the pyramidal layers of horizontal mousehippocampal slices. These events started as rather irregular fieldbursts in CA3 and propagated towards CA1 where theyappeared as typical sharp wave-ripple complexes (SPW-R; Fig.1). Sharp waves reversed polarity between stratum radiatumand stratum pyramidale of CA1 (see Fig. 5). In both areas,time-frequency plots revealed a fast oscillatory componentwhich was most pronounced in CA1 (leading frequency 240 6

5 Hz; n 5 31 slices from 16 animals; Fig. 1B). The coupledoccurrence of field events at both locations was reflected by aclear coherence in the low-frequency (sharp wave) and high-frequency (ripple) domain (Fig. 1C; tested for 6 slices from 3

FIGURE 1. Analysis of spontaneous SPW-R events in CA1and CA3. Sample recording from a representative slice. A: 10 s epi-sode of the field potential from stratum pyramidale of CA1 andCA3 and the corresponding time-frequency (TF) analysis. B: Fieldpotentials and corresponding TFs of a single event marked by the

asterisk in panel A. C: Averaged TF-plot from 994 events in oneslice (recorded over 332 s). Leading frequency in CA1: 238 Hz;leading frequency in CA3: 203 Hz. D: Coherence (left) and cross-correlation (right) of the field potential in CA1 and CA3.

RIPPLE PROPAGATION 901

Hippocampus

animals). Events regularly started in CA3 and propagatedtowards CA1 (Figs. 1C; 3E,F). These basic features of sharpwave-ripple complexes are well consistent with previous find-ings in vitro (Maier et al., 2002) and in vivo (Buzsaki et al.,1992; Ylinen et al., 1995).

Action Potential Firing in CA3 is StronglyCoupled to Ripple Oscillations and ActionPotential Firing in CA1

Action potentials of CA1 pyramidal cells during SPW-Roccur at precisely determined times (Ylinen et al., 1995; Csics-vari et al., 2000), constituting representations of previouslystored information in complex spatio-temporal patterns of net-work activity (Wilson and McNaughton, 1993; Leutgeb et al.,2005). Do these patterns arise autonomously within CA1 or docells in CA3 already show entrainment to the 200 Hz rhythm?In order to address this question, we analyzed the interactionbetween both regions at the network and cellular level. High-pass filtered recordings of field potentials revealed multiple unitdischarges during field bursts (CA3) and ripples (CA1), respec-tively (Fig. 2A). Band-pass filtered traces revealed the concomi-tant high-frequency network oscillation which was very regularin CA1 and exhibited the typical spindle-shaped time course ofSPW-R (Buzsaki, 1986). First, we calculated cross-correlations

between multiunit activity and field ripples. Within CA1, unitsand local field potentials were strongly coupled during SPW-R(Fig. 2B, left), in line with previous reports (Ylinen et al.,1995; Csicsvari et al., 1999; Maier et al., 2003). More surpris-ingly, cross-correlograms between unit activity in CA3 and fieldripples in CA1 did also show prominent peaks at �5 ms inter-vals, corresponding to the cycle length of the fast oscillation(Fig. 2B). This finding indicates that unit discharges in CA3entrain fast coherent activity in CA1 by propagation via theSchaffer collaterals. A possible source of artifact is, however, theapparent coupling of two unrelated oscillators which cycle atsimilar frequencies. We therefore shuffled our data by correlat-ing the field ripples of the nth sharp wave with unit dischargesfrom the n 1 1th sharp wave. This led to a complete loss ofpeaks in cross-correlations, yielding smooth (Gaussian-like) dis-tributions (Fig. 2B insets). We conclude that individual neuro-nal action potentials in CA3 are indeed linked to SPW-associ-ated field ripples in CA1.

To quantify the phase-coupling of units to field ripples weplotted cumulative histograms of spikes with respect to theirtime of occurrence during one single ripple cycle (see methods).Random distribution would yield 50% of spikes occurring dur-ing 50% of an individual ripple cycle. If 50% of action poten-tials occur during shorter sections of the full ripple cycle, theseaction potentials are phase-coupled (Fig. 2C). We performed

FIGURE 2. Temporal structure and coupling between field rip-ples and unit discharges in different hippocampal subfields. A:Example traces showing simultaneously recorded field potentials inCA1 (top), and CA3 (bottom). Units are uncovered in the high-pass filtered signal and marked by vertical lines. Ripple oscillationtroughs in CA1 are detected in the 140–320 Hz band-pass filteredsignal and marked by vertical lines. B: Temporal correlationbetween unit discharges in different areas of the hippocampus.Cross-correlations between unit discharges in CA1 pyramidal layer(left) and CA3 pyramidal layer (right), respectively, and field rip-ples in CA1. Note prominent peaks at �5 ms intervals reflecting

the temporal coherence between action potentials and CA1 fieldripples in both regions. Insets are cross-correlations after assigningthe ripples of sharp wave number n to sharp wave number n 1 1(shuffled data, see methods). C: Precision of spike coupling tofield ripples. Left: Enlarged view of the cross-correlogram (barplot) and shuffled cross-correlogram (light gray line) from panel B(left). The frame marks the time window of analysis. Right: Cumu-lative probability of unit discharges during one full ripple cycle(�5 ms). Peak of the cross-correlogram is located at 50% of theripple cycle on the abscissa. Shuffled distribution indicated bylight gray line. Computed coupling strength: 23%.

902 BOTH ET AL.

Hippocampus

FIGURE 3. Temporal relationships between propagating SPW-R throughout CA3 and CA1. A: Schematic drawing of the elec-trode positions within CA1 and CA3. B: Mean ripple frequenciesin different subregions of CA1. C: Coupling strength of units inCA3 (positions a, b, c as shown in panel A) to field ripples inCA1. D: Coupling strength of units in CA3 to units in CA1 (n 56 slices from 3 animals, asterisk indicates P < 0.05). E: Time delayof activity from subregions in CA3 to subregions in CA1 (n 5 6

slices from 3 animals, asterisk indicates P < 0.05). F: Summary ofcoupling strength between three subregions in CA3 and three sub-sregions in CA1. Left panel: CA1 field ripples versus. CA3 unitdischarges, data from C. Right panel: CA1 unit discharges versusCA3 unit discharges, data from D. G: Summary of time delaysbetween activity in CA3 and CA1, data from E (n 5 6 slices from3 animals).

multiple recordings of field potentials and multiunit activityalong the hippocampal loop and systematically assessed cou-pling between the respective subfields. Within CA1, SPW-Rshowed a slight increase in frequency towards the subiculum(207 6 8 Hz in the vicinity of CA3; 223 6 14 Hz in midCA1; 253 6 14 Hz close to subiculum; n 5 6 slices from 3animals; P < 0.05; Fig. 3B). Triple recordings from thesepoints were compared to simultaneous single-electrode record-ings from three different locations in CA3 (CA3 a, b, c; Fig.3A). We then computed pair-wise cross-correlations betweenthe respective electrode locations in CA3 and CA1 and quanti-fied coupling as illustrated in Figure 2C. Multiunit activityrecorded from all three locations of CA3 was clearly correlatedwith field ripples (Fig. 3C) and with unit discharges (Fig. 3D)in the two most proximal regions of CA1. In contrast, the

FIGURE 4. Activity of single principal neurons in CA3 is pre-cisely correlated to ripple troughs in CA1. A: NeuroLucida recon-struction of a coupled CA3 pyramidal cell (left) with schematicfield potential recording electrode location in CA1 (right). B: Rep-resentative trace of a SPW-R event and the corresponding single-cell recording. C: Cross-correlogram between discharges of the celldepicted in panel A and CA1 ripple troughs (upper plot) andcumulative distribution of the most prominent peak over one rip-ple cycle (lower plot). Coupling strength: 37%.

FIGURE 5. Induction of field events by stimulation withinCA3 or within the Schaffer collaterals, respectively. Aa: Spontane-ous SPW-R in CA1. Ab-d: Field potentials and corresponding(averaged) TF-plots for events evoked by increasing stimulationstrength in CA3. All data in A are from the same slice. B: Sponta-neous SPW-R in CA1 (Ba) compared to events evoked by increas-ing stimulation strength in the Schaffer collaterals (Bb-d). Data inB are from one slice, TF-plots averaged. C: Group data for SPW-R-like events evoked by stimulation in the Schaffer collaterals (SC)and in CA3 (normalized to values from spontaneous SPW-R).Note the large difference in temporal relationship between ripplesand underlying sharp waves upon stimulation of the Schaffer col-laterals (n 5 7 slices for stimulation in SC; n 5 15 for stimulationin CA3).

904 BOTH ET AL.

Hippocampus

most distal recording site within CA1 (close to the subiculum)showed little or no correlation to events in CA3. The differentcoupling strengths of units versus units and units versus ripplesare summarized in the 3 3 3 matrices in Figure 3F. In orderto get a measure for the propagation of field bursts and SPW-R, we quantified delay times from the peak of cross-correlo-grams between all recording sites (see methods). All three sub-fields of CA3 showed short (<6 ms) time delays towards thetwo more proximal electrode positions in CA1. Again, themost distal recording point in CA1 had clearly longer delays(Figs. 3E,G). Together, these data show that sharp wave-associ-ated network events in CA3 and CA1 are highly interdepend-ent and that neuronal discharges in CA1 are, at least in part,determined by previous activity in CA3.

Multiunit activity reflects the concomitant recording ofaction potentials from multiple cells. This method is, therefore,not able to demonstrate the coupling of individual neurons todownstream network activity. As a final step, we thereforerecorded juxtacellularly from individual cells in CA3 pyramidallayer. Stable recordings could be established from 36 single cellsin 22 slices from 19 animals and were used to construct cross-correlations with field ripples in CA1 (Fig. 4). Of these neu-rons, 17 cells showed a coupling index <50% of a ripple cycle,indicating phase-coupling. Seven cells were histologically recon-structed after electroporation with neurobiotin (Pinault, 1996),including five clearly identified CA3 pyramidal cells whichwere coupled to field ripples in CA1. Thus, individual princi-pal neurons of CA3 are phase-locked to ripples in CA1, indica-tive of specific instruction of this downstream region by preced-ing activity in CA3.

Unspecific Activation of CA3 Leads toOscillatory Activity in the CA3-CA1 Network

Previous findings show that high-frequency oscillations at�200 Hz can be generated within CA1 minislices (Nimmrichet al., 2005) while the present data point towards an instructiverole of CA3 for native SPW-R. In order to unravel the role ofupstream nuclei more precisely, we therefore evoked networkevents by electrical stimuli at different stages along the hippo-campal loop and compared the resulting activity with spontane-ously occurring SPW-R. Weak electrical stimulation in the py-ramidal cell layer of CA3b regularly evoked field events in CA1resembling spontaneously occurring SPW-R with typical wave-forms in stratum pyramidale and stratum radiatum (Fig. 5Ab).If stimulation occurred during or shortly after spontaneousSPW-R, the event was prolonged but did not show a clear re-fractory period (data not shown). This patterned activity startedfrom a variable voltage threshold (less than 20% of the voltagerequired for eliciting maximal population spike amplitude)which was sufficient to elicit field-EPSPs in CA1 with the am-plitude of natural sharp waves. Increasing stimulation strengthresulted in larger field-EPSPs which were devoid of the super-imposed high-frequency oscillation (Fig. 5Ac,d). Raw waveformpattern and time-frequency plots of such evoked networkevents had similar temporal characteristics and frequency com-

ponents as spontaneously occurring SPW-R (Fig. 5A). Likewise,quantitative parameters of SPW-R revealed very similar values,despite some minor differences in leading ripple frequencyand in the timing between sharp wave and ripple maximum(Fig. 5C).

Following the normal propagation pattern of SPW-R in vivo(Chrobak and Buzsaki, 1996; Csicsvari et al., 2000; Dragoiand Buzsaki, 2006) and in vitro (Maier et al., 2003), we thentried to evoke SPW-R in CA1 by stimulating Schaffer collater-als (Fig. 5B). This stimulation paradigm elicits an orthodromicaction potential propagating towards CA1 and at the sametime an antidromic action potential propagating towards CA3.When stimulus strength was adapted to yield field-EPSP ampli-tudes similar to sharp waves, the resulting field potentials wereagain reminiscent of native SPW-R, including phase reversalbetween strata (Fig. 5Bb). At stronger stimulus intensities, theripple-like field potentials were consistently replaced by asmooth field-EPSP of larger amplitude carrying a typical popu-lation spike (Fig. 5Bc,d). Time-frequency plots of evokedSPW-R-like field events in stratum pyramidale were reminis-cent of native SPW-R but did, however, lack a clear separationbetween fast and slow frequencies. Moreover, the peak activityin the high-frequency band appeared as short as 1.6 6 0.7 msbefore the peak of the low frequency component, in contrastto native SPW-R (5.0 6 0.2 ms; n 5 7 slices from 7 animals;P < 0.05; Fig. 5C). This difference in temporal structurebetween spontaneous and evoked SPW-R was much less promi-nent upon stimulation in CA3 (delay 5.5 6 0.2 ms; n 5 15slices from 10 animals; P < 0.05; Fig. 5C). Thus, weak activa-tion of the Schaffer collaterals elicits network activity withinCA1 which has strong similarities, but also some differences ascompared to native SPW-R.

Unspecific Activation of CA1 Does not Lead toOscillatory Activity in the CA3-CA1 Network

Previous work suggests that ripples are organized by electri-cally coupled axons which can, in principle, form an autono-mously oscillating network (Draguhn et al., 1998; Traub et al.,1999; Hamzei-Sichani et al., 2007). We therefore tried to triggerSPW-R by antidromic activation of the axonal output pathwayfrom CA1. Electrical stimulation of the alveus with varyingstrength (0.5–40 V, 100 ls; 6 slices from 5 animals) caused pop-ulation spikes in stratum pyramidale (depending on stimulusstrength), followed by a positive going field potential (Figs. 6B–D) which was sensitive to CNQX (20 lM; data not shown).Time-frequency analysis of the evoked potentials revealed aprominent slow component which developed continuously intoa higher frequency component and was markedly different fromspontaneously occurring SPW-R (Fig. 6B). In no case did theantidromically evoked potential contain clearly visible high-fre-quency oscillations (see Figs. 6B–D). We also tried to elicit sig-nals resembling SPW-R by repetitive antidromic stimulation atdifferent frequencies (Fig. 6E), including the ripple frequencyrange (3–10 stimuli at 10, 100, 166, and 250 Hz; n 5 4 slicesfrom 4 animals). Again, we were unable to elicit any high-

RIPPLE PROPAGATION 905

Hippocampus

frequency oscillations, except for population spikes which weredirectly generated by strong stimuli (Fig. 6Ec).

Moreover, spontaneous SPW-R in stratum pyramidale per-sisted after removing distal axons of CA1 pyramidal cells bycutting off the alveus at �100–150 lm distance from stratum

pyramidale (see Fig. 6G for a scheme and comparison withnative slice). In all slices tested, spontaneous SPW-R were stillpresent (Fig. 6A) and showed only minor differences as com-pared to SPW-R recorded from the same slices before cutting:ripple frequency was slightly reduced (control 250.5 6 7.7 Hz,

FIGURE 6. Antidromically evoked field potentials in CA1 lackproperties of spontaneous SPW-R whereas slices with removed distalaxons exhibit SPW-R like events. A: Time-frequency components ofspontaneously occurring SPW-R in stratum pyramidale followingdissection of the alveus. B–D: Time-frequency components and fieldpotential recordings of antidromically evoked responses in CA1 byweak (B), medium (C) and strong (D) stimulation, respectively. E:Repetitive antidromic stimulation does not induce SPW-R in CA1.Ea, Eb: Response to three and to six weak stimulations at 166 Hz.Ec: Six stimulations of medium strength (corresponding to C) at

166 Hz. Note the pronounced high-frequency component in time-frequency plot corresponding to the stimulations. F: Parameters ofspontaneous SPW-R events in native slices versus slices with cutalveus. Significant differences were revealed for ripple frequency,peak ripple power, and for the temporal relationship between themaximum of the ripple oscillation and the underlying sharp wave (n5 8; P < 0.05 for all parameters). G: Schematic drawing (Ga) andneurobiotin-stained sample from a native slice (Gb) and from a slicewith cut alveus (Gc).

906 BOTH ET AL.

Hippocampus

slices with cut alveus 211.0 6 7.0 Hz; n 5 8 slices from 5 ani-mals; P < 0.05) and the temporal relationship between themaximum of the fast ripple oscillation and the maximum ofthe underlying sharp wave was shifted by 2 ms (control 5.18 6

0.33 ms, cut alveus 3.18 6 0.48 ms; n 5 8 slices from 5 ani-mals; P < 0.05; see Fig. 6F).

Thus, sharp wave-ripple complexes could not be elicited byantidromic stimulation of CA1 pyramidal cell axons and werenot abolished by removal of the distal part of these axons. To-gether with the SPW-R-resembling field potentials elicitedfrom CA3, these findings makes it likely that the othodromi-cally propagating activity does indeed play a major role for thegeneration of SPW-R in CA1.

DISCUSSION

Here, we show that sharp wave-ripple complexes in CA1 aretightly coupled to preceding field bursts and to single-cell activ-ity in CA3. Our findings suggest that transient assemblieswithin CA1 are entrained by upstream activity within CA3.Our key observation is the strong cross-correlation of cellularand network activity between CA3 and CA1 during propagat-ing SPW-R. This strictly timed input from CA3 was demon-strated at the single-cell level where individual CA3 pyramidalcells showed clear coupling to downstream ripple oscillations inCA1. The coupling of individual CA3 pyramidal cells withdownstream field ripples in CA1 may indicate that field ripplesin CA1 can be influenced by single cells within CA3, consistentwith recent findings during slow hippocampal oscillations(Mikkonen et al., 2006). The surprising long-range coordina-tion of ripple activity within and between both subfields (Figs.3 and 4) confirms and extends previous findings from in vivorecordings (Chrobak and Buzsaki, 1996; Csicsvari et al., 2000).This finding suggests a role for assembly-to-assembly communi-cation during the propagation of patterned network activity.Thus, CA1 networks, although showing particularly pro-nounced ripples in vivo (Csicsvari et al., 2000) and in vitro(Maier et al., 2003), are not autonomous in generating highlyorganized high-frequency oscillations.

Additionally, our findings suggest that plastic changes withinCA3 during learning states (e.g., exploration of a new territory)are relevant for the subsequent replay and propagation of these sig-nals through the hippocampal output pathway. SPW-R arebelieved to represent an output signal from the hippocampus, car-rying specific representations of previously acquired spatial infor-mation. During this state, temporal relationships between CA1place cells are re-played (Wilson and McNaughton, 1994; Skaggsand McNaughton, 1996). On the basis of the present findings it islikely that these specific patterns of activity are, at least partially,defined by network functions within CA3. By propagatingthrough the hippocampal-neocortical output pathway, these pat-terns of activity may induce additional plastic changes in their tar-get regions and thus mediate memory consolidation (King et al.,1999; Nadasdy et al., 1999; Behrens et al., 2005).

The important role of CA3 in orchestrating CA1 networkbehavior during SPW-R was also illustrated by stimulation-induced sharp wave-resembling events. We were unable to elicitany high-frequency network events with characteristics of ripplesby directly activating CA1. Previous experiments in CA1 mini-slices have shown that this subfield does, in principle, containall necessary elements to generate high-frequency oscillations(Nimmrich et al., 2005). The underlying network mechanismsmay include fast synaptic inhibition by rapidly firing interneur-ons (Ylinen et al., 1995; Klausberger et al., 2003, 2004) or mayinvolve electrical coupling between axons of CA1 pyramidal cells(Draguhn et al., 1998; Maier et al., 2003). Axonal gap junctionshave recently been found in mossy fibers of dentate granule cells(Hamzei-Sichani et al., 2007). In our present experiments, wefailed to induce ripples by single or rhythmic antidromic stimu-lation in the alveus. Moreover, cutting off distal axons (>100–150 lm) did not abolish ripple oscillations. Thus, a specific den-dritic input to CA1 seems to be essential to trigger and orches-trate local high-frequency oscillations. This does not exclude,though, that additional activity-dependent plastic processes doexert lasting changes in CA1 which may select assembly mem-bers in the local network. Indeed, coupling between single unitsin CA1 and the local ripple oscillation was consistently strongerthan coupling between CA3 and CA1.

In contrast to antidromic stimulation within CA1, SPW-Rin CA1 could be readily elicited by brief unspecific activationof the CA3 network. In line with this finding, stimulatingSchaffer collaterals induced SPW-R-like events in CA1 whichdid, though, show a delayed appearance of ripples with respectto the underlying sharp wave. This finding is well consistentwith the feed-forward activation of excitatory synapses in CA1and the concomitant antidromic propagation of action poten-tials towards CA3. These action potentials may induce activityin the recurrent network within CA3, again triggering high-fre-quency oscillations which propagate towards CA1 with theobserved delay (see Figs. 3E and 5C).

In summary, our data show that SPW-R oscillations are notfully defined within the CA1 network. By contrast, precedingnetwork bursts within CA3 induce the highly ordered patternof network activity in downstream CA1 networks. Single-cellfiring in CA3 is precisely coupled to units and field ripple ac-tivity in CA1. Taken together this indicates that SPW-R-relatedoscillating cell assemblies in CA1 are instructed by preciseinput from CA3 and that information propagates with highprecision through the hippocampal loop.

Acknowledgments

We thank F. von Wegner for expert help with wavelet analy-sis, T. Kunsting for helpful discussions and N. Zuber for stain-ing of single neurons.

REFERENCES

Battaglia FP, Sutherland GR, McNaughton BL. 2004. Hippocampalsharp wave bursts coincide with neocortical ‘‘up-state’’ transitions.Learn Mem 11:697–704.

RIPPLE PROPAGATION 907

Hippocampus

Behrens CJ, van den Boom LP, de HL, Friedman A, Heinemann U.2005. Induction of sharp wave-ripple complexes in vitro and reor-ganization of hippocampal networks. Nat Neurosci 8:1560–1567.

Buzsaki G. 1986. Hippocampal sharp waves: Their origin and signifi-cance. Brain Res 398:242–252.

Buzsaki G. 1989. Two-stage model of memory trace formation: a rolefor ‘‘noisy’’ brain states. Neuroscience 31:551–570.

Buzsaki G. 1998. Memory consolidation during sleep: A neurophysio-logical perspective. J Sleep Res 7(Suppl 1):17–23.

Buzsaki G, Horvath Z, Urioste R, Hetke J, Wise K. 1992. High-fre-quency network oscillation in the hippocampus. Science 256:1025–1027.

Chrobak JJ, Buzsaki G. 1994. Selective activation of deep layer (V-VI)retrohippocampal cortical neurons during hippocampal sharp wavesin the behaving rat. J Neurosci 14:6160–6170.

Chrobak JJ, Buzsaki G. 1996. High-frequency oscillations in the out-put networks of the hippocampal-entorhinal axis of the freelybehaving rat. J Neurosci 16:3056–3066.

Cohen I, Miles R. 2000. Contributions of intrinsic and synaptic activ-ities to the generation of neuronal discharges in in vitro hippocam-pus. J Physiol 524(Part 2):485–502:485–502.

Csicsvari J, Hirase H, Czurko A, Mamiya A, Buzsaki G. 1999. Oscil-latory coupling of hippocampal pyramidal cells and interneurons inthe behaving Rat. J Neurosci 19:274–287.

Csicsvari J, Hirase H, Mamiya A, Buzsaki G. 2000. Ensemble patternsof hippocampal CA3-CA1 neurons during sharp wave-associatedpopulation events. Neuron 28:585–594.

Dragoi G, Buzsaki G. 2006. Temporal encoding of place sequences byhippocampal cell assemblies. Neuron 50:145–157.

Draguhn A, Traub RD, Schmitz D, Jefferys JG. 1998. Electrical cou-pling underlies high-frequency oscillations in the hippocampus invitro. Nature 394:189–192.

Hamzei-Sichani F, Kamasawa N, Janssen WG, Yasumura T, DavidsonKG, Hof PR, Wearne SL, Stewart MG, Young SR, WhittingtonMA, Rash JE, Traub RD. 2007. Gap junctions on hippocampalmossy fiber axons demonstrated by thin-section electron micros-copy and freeze-fracture replica immunogold labeling. Proc NatlAcad Sci USA 104:12548–12553.

Ji D, Wilson MA. 2007. Coordinated memory replay in the visualcortex and hippocampus during sleep. Nat Neurosci 10:100–107.

King C, Henze DA, Leinekugel X, Buzsaki G. 1999. Hebbian modifi-cation of a hippocampal population pattern in the rat. J Physiol521(Part 1):159–167.

Klausberger T, Magill PJ, Marton LF, Roberts JD, Cobden PM, Buz-saki G, Somogyi P. 2003. Brain-state- and cell-type-specific firingof hippocampal interneurons in vivo. Nature 421:844–848.

Klausberger T, Marton LF, Baude A, Roberts JD, Magill PJ, SomogyiP. 2004. Spike timing of dendrite-targeting bistratified cells duringhippocampal network oscillations in vivo. Nat Neurosci 7:41–47.

Leutgeb S, Leutgeb JK, Moser MB, Moser EI. 2005. Place cells, spa-tial maps and the population code for memory. Curr Opin Neuro-biol 15:738–746.

Maier N, Guldenagel M, Sohl G, Siegmund H, Willecke K, DraguhnA. 2002. Reduction of high-frequency network oscillations (ripples)and pathological network discharges in hippocampal slices fromconnexin 36-deficient mice. J Physiol 541:521–528.

Maier N, Nimmrich V, Draguhn A. 2003. Cellular and networkmechanisms underlying spontaneous sharp wave-ripple complexesin mouse hippocampal slices. J Physiol 550:873–887.

McNaughton BL, Barnes CA, O’Keefe J. 1983. The contributions ofposition, direction, and velocity to single unit activity in the hippo-campus of freely-moving rats. Exp Brain Res 52:41–49.

Mikkonen JE, Huttunen J, Penttonen M. 2006. Contribution of a singleCA3 neuron to network synchrony. Neuroimage 31:1222–1227.

Nadasdy Z, Hirase H, Czurko A, Csicsvari J, Buzsaki G. 1999. Replayand time compression of recurring spike sequences in the hippo-campus. J Neurosci 19:9497–9507.

Nimmrich V, Maier N, Schmitz D, Draguhn A. 2005. Induced sharpwave-ripple complexes in the absence of synaptic inhibition inmouse hippocampal slices. J Physiol 563:663–670.

O’Keefe J, Dostrovsky J. 1971. The hippocampus as a spatial map.Preliminary evidence from unit activity in the freely-moving rat.Brain Res 34:171–175.

O’Keefe J, Nadel L (1978). The Hippocamus as a Cognitive Map.Oxford, UK: Clarendon Press. pp 570.

O’Keefe J, Recce ML. 1993. Phase relationship between hippocampalplace units and the EEG theta rhythm. Hippocampus 3:317–330.

Pinault D. 1996. A novel single-cell staining procedure performed invivo under electrophysiological control: Morpho-functional featuresof juxtacellularly labeled thalamic cells and other central neuronswith biocytin or Neurobiotin. J Neurosci Methods 65:113–136.

Schmitz D, Schuchmann S, Fisahn A, Draguhn A, Buhl EH, Petrasch-Parwez E, Dermietzel R, Heinemann U, Traub RD. 2001. Axo-axonal coupling. A novel mechanism for ultrafast neuronal com-munication. Neuron 31:831–840.

Skaggs WE, McNaughton BL. 1996. Replay of neuronal firing sequen-ces in rat hippocampus during sleep following spatial experience.Science 271:1870–1873.

Skaggs WE, McNaughton BL, Wilson MA, Barnes CA. 1996. Thetaphase precession in hippocampal neuronal populations and thecompression of temporal sequences. Hippocampus 6:149–172.

Traub RD, Schmitz D, Jefferys JG, Draguhn A. 1999. High-frequencypopulation oscillations are predicted to occur in hippocampal py-ramidal neuronal networks interconnected by axoaxonal gap junc-tions. Neuroscience 92:407–426.

Wilson MA, McNaughton BL. 1993. Dynamics of the hippocampalensemble code for space. Science 261:1055–1058.

Wilson MA, McNaughton BL. 1994. Reactivation of hippocampal en-semble memories during sleep. Science 265:676–679.

Ylinen A, Bragin A, Nadasdy Z, Jando G, Szabo I, Sik A, Buzsaki G.1995. Sharp wave-associated high-frequency oscillation (200 Hz)in the intact hippocampus: Network and intracellular mechanisms.J Neurosci 15:30–46.

908 BOTH ET AL.

Hippocampus