A ubiquitous feature of neuronal networks, in the brains of multiple mammalian species throughout the evolutionary tree, is their propensity to engage in large-scale, synchronous and rhythmic patterns of electrical activity, reflected as oscillations in the local field potential (LFP) (Buzsáki et al., 2013). LFP oscillations occur at frequencies spanning four or more orders of magnitude, with oscillations at different frequency bands often nested together and co-modulating each other (Steriade, 2006). Different oscillatory patterns are hallmarks of specific brain and behavioral states; for example, theta rhythms (4–9 Hz) are typical of exploratory behavior, sleep spindles (~10 Hz) occur during certain sleep stages, and gamma oscillations (30–90 Hz) are the hallmark of cognitive activity and sensory processing (Lopes da Silva, 2013; Singer, 2018). Even faster, transient 150–200 Hz ‘ripples’ in the pyramidal cell layer of the hippocampus occur during quiet immobility and slow-wave sleep (Bragin et al., 1999a; Bragin et al., 1999b; Csicsvari et al., 1999a), and are thought to be critical for memory consolidation (Girardeau and Lopes-Dos-Santos, 2021). Extracellular voltage signals, including oscillations, are driven by currents entering (sinks) or leaving (sources) the intracellular brain compartment, and reflect both synaptic activity and action potential firing (Mitzdorf, 1985; Liebe et al., 2011; Buzsáki et al., 2012; Schomburg et al., 2012; Reimann et al., 2013; Pesaran et al., 2018). Indeed, excitatory and inhibitory neurons in the hippocampus fire at precise phases of theta, gamma, and ripple oscillations in a subtype-specific manner (Klausberger et al., 2003; Klausberger and Somogyi, 2008; Cardin, 2018), and synaptic interactions between excitatory and inhibitory cells are implicated in the generation of oscillations across the spectrum, although the details may vary between frequency bands, between different brain areas, and even between cortical layers (Kopell et al., 2010; Wang, 2010; Whittington et al., 2018).

At the high end of the frequency range, ultrafast, 250–600 Hz oscillations have been observed in both hippocampus and neocortex. In the hippocampus, such oscillations (often called ‘fast ripples’) are almost exclusively paroxysmal (reviewed in Gulyás and Freund, 2015; Lévesque and Avoli, 2019), although their underlying cellular and network mechanisms remain under debate (Dzhala and Staley, 2004; Foffani et al., 2007; Engel et al., 2009). In the neocortex, however, non-paroxysmal 600 Hz wavelets have been repeatedly observed in scalp recordings from human subjects in response to peripheral nerve stimulation (reviewed in Curio, 2000). Similar 600 Hz LFP oscillations in response to peripheral nerve stimulation were also observed in monkeys and piglets (Ikeda et al., 2002; Baker et al., 2003). Notably, LFP oscillations in the 300–500 Hz range were also consistently observed in rats in response to whisker deflections or to auditory clicks (Jones and Barth, 1999; Jones et al., 2000; Jones and Barth, 2002); however, their underlying mechanisms and functional significance remain largely unexplored.

We recorded ex vivo extracellular and intracellular activity evoked by optogenetic activation of channelrhodopsin (ChR2)-expressing thalamocortical axons in thalamorecipient layers of mouse somatosensory (barrel) cortex. We report here that brief light pulses (as short as 1 ms) elicited a transient (<25 ms), highly reproducible LFP oscillation or ‘ripplet,’ which closely resembled hippocampal ripples but, at ~400 Hz, was more than twice as fast. Paired whole-cell recordings from fast-spiking (FS) inhibitory interneurons and regular-spiking (RS) excitatory cells revealed precise phase relationships between FS spikes, RS spikes and ripplets, and between FS spikes and sequences of alternating EPSCs and IPSCs in RS cells, suggesting that phasic RS→RS and RS→FS excitation underlies ripplet generation. Ripplets may be a stereotypical cortical response to strong, punctate stimuli that activate thalamocortical afferents with a high degree of synchrony and could be used by the cortex to encode specific features of a sensory event. Importantly, optogenetically evoked ex vivo ripplets are a uniquely accessible model for studying the synaptic basis of fast and ultrafast network oscillations, including hippocampal ripples.

We recorded extracellular and intracellular responses in layer 4 (L4) of barrel cortex brain slices, evoked by widefield optogenetic activation of thalamocortical synapses. Slices were prepared from brains of 3–7-postnatal-week-old mice of both sexes expressing ChR2 in the somatosensory thalamus (see ‘Materials and methods’). We applied brief light pulses through the epi-illumination path of the microscope, likely activating most of the thalamocortical axons and terminals within the surrounding L4 barrel. To verify that ChR2 in L4 was expressed by thalamocortical and not intracortical axons, we imaged and quantified the extent of tdTomato reporter expression in the cortex (Figure 1—figure supplement 1). Within the barrel cortex, there was a sparse population of reporter-expressing cell bodies in L2/3 and L5, but virtually none within L4 (Figure 1—source data 1). Since the thalamus and L4 itself are the two main sources of excitatory input to L4 neurons (Feldmeyer et al., 1999; Petersen and Sakmann, 2000; Lefort et al., 2009), we conclude that the network activity we observed was predominantly evoked by thalamocortical activation, although we cannot rule out that a small number of corticothalamic neurons in L6, which send axonal collaterals to L4 (White and Keller, 1987; Kumar and Ohana, 2008), also expressed ChR2 and provided a minor excitatory contribution.

Optogenetic activation of thalamocortical axons evoked ripple-like extracellular wavelets

A brief light pulse (1–10 ms, typically 2–5 ms) evoked a stereotypical field potential wavelet in L4 (Figure 1A). In this and all other electrophysiological traces, the light-evoked response is represented by a 25-ms-long record beginning 1 ms before light onset, and the timing of the light pulse is indicated by a cyan bar above or below the trace. At all stimulus durations, the LFP waveform consisted of an initial low-amplitude negative component (solid arrowhead), followed by 2–5 (typically 3–4) larger negative transients (hollow arrowheads) riding on a slow, positive-going envelope. In the example slice in Figure 1A, the fourth transient was barely discernible in response to a 1 ms light pulse (left), but became noticeably larger with a 5 ms pulse (right). A low-amplitude negative shoulder or ‘hump’ (arrow) was often observed on the rising phase of the first large transient. These optogenetically evoked waveforms were reminiscent of hippocampus ripples, LFP wavelets recorded from the cell body layer of areas CA1 or CA3; we therefore named them RIPPle-Like Extracellular Transients or ‘ripplets’.

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Counts of Cre-expressing neurons in the KN282 mouse.

Four male mice (4–6 weeks old) were deeply anesthetized with 2.5% Avertin and transcardially perfused with saline followed by 50 ml 4% paraformaldehyde (PFA). Brains were removed, post-fixed in 4% PFA at room temperature for 4 hr, stored for at least 72 hr in 30% sucrose solution in phosphate buffered saline (PBS) at 4°C, and sectioned coronally on a freezing stage sliding microtome. For imaging, five 60 μm sections were sampled per brain at 240 μm intervals, in total extending 800–2000 μm posterior to bregma, as determined by comparison with the Paxinos and Franklin atlas (Paxinos and Franklin, The Mouse Brain in Stereotaxic Coordinates, 4th edition, Academic Press 2012). Confocal image stacks were taken with a ×10 objective at 2.5 μm Z-steps on a Zeiss LSM 710 or a Nikon A1R confocal microscope. Labeled cells were counted by visual inspection of the full stack and summed per area over the five sections from each animal; counts thus represent the number of cells in a composite 300 μm section. Areal boundaries follow the designations in the Paxinos and Franklin atlas.

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Synchronous spike volleys in thalamocortical terminals generate relatively large current sinks in layer 4, and these are discernible as negative transients in the LFP (Morin and Steriade, 1981; Agmon and Connors, 1991; Swadlow et al., 2002; Bruno et al., 2003). To reveal any presynaptic thalamocortical components in the ripplets, we blocked fast ionotropic glutamate receptors (iGluRs) pharmacologically with CNQX + APV. This eliminated the large negative transients but left unchanged the early negative component (Figure 1B, left panel, solid arrowhead), which therefore reflected the initial thalamocortical volley. Interestingly, the presynaptic response to 5 ms or longer light pulses revealed one or two additional presynaptic transients of decreasing amplitudes (Figure 1B, right panel, solid arrowheads), suggesting that thalamocortical axons fired additional volleys of decreasing magnitude and coherence. Subtracting the waveforms in CNQX + APV from those in control ACSF isolated the postsynaptic component of the response (Figure 1C). Superposition of the isolated presynaptic (Figure 1D, left) and postsynaptic (Figure 1D, right) contributions at 1, 5, and 10 ms stimulus durations demonstrated that prolonging the light pulse added late components to the response waveform but did not affect the timing of the earlier peaks. To confirm that the iGluR-independent signals reflected action potentials, we added TTX to the bath, which blocked all remaining responses except for a small square waveform (Figure 1—figure supplement 2). The latter was coincident with the light pulse and was most likely an electrical or optoelectrical artifact, and is subtracted from all traces in Figure 1.

Ripplet waveforms, as well as their isolated presynaptic components, were remarkably consistent between animals in their temporal structure, as illustrated in Figure 1E by the superposition of responses in slices from four different animals, drawn at different vertical scales to facilitate time course comparison. To quantify the variability in the temporal structure of ripplets between animals, we measured the peak times (relative to light onset) of the isolated presynaptic volleys (Figure 1F, left; eight slices from eight animals tested in CNQX + APV) and of the postsynaptic transients (Figure 1F, right; 11 slices from 11 animals with ripplet amplitudes ≥0.5 mV). Standard deviations (SDs) of the presynaptic volleys ranged from 0.2 to 0.6 ms, and SDs of ripplet peaks ranged from 0.3 to 1.0 ms. Calculated over the three volleys, the presynaptic axons appeared to fire at an average frequency ( = 1/average ISI) of 239 ± 6 Hz. This is consistent with the observed burst frequency in thalamocortical neurons of the same mouse genotype when activated optogenetically ex vivo, which rarely exceeds 300 Hz (Hu and Agmon, 2016, their Figure 4E). Calculated over the four ripplet peaks, ripplet frequency averaged 408 ± 15 Hz, that is, nearly twice as fast as the apparent presynaptic volleys. To facilitate comparison of presynaptic components and ripplets, we modeled the histogram peaks in Figure 1F as Gaussians with the same mean, SD, and integral as that of the respective event (Figure 1G). Overlaying the Gaussians (Figure 1G, right) highlighted the lack of temporal coherence between the presynaptic volleys and ripplets, indicating that ripplets were not a direct, 1:1 response to bursts in thalamocortical axons but were likely generate de novo within the L4 network.

Optogenetic stimulation of thalamocortical axons evoked precisely timed FS spike bursts

Since ripplets required intact glutamatergic neurotransmission, they most likely reflected population activity within L4; but in which cells? To answer this question, we examined light-induced whole-cell responses in inhibitory FS interneurons and excitatory, RS cells, two subclasses known to receive direct thalamocortical inputs (Agmon and Connors, 1992; Gibson et al., 1999; Porter et al., 2001; Bruno and Simons, 2002; Gabernet et al., 2005; Sun et al., 2006; Cruikshank et al., 2007; Shigematsu et al., 2019). These two subtypes are readily identifiable in slice recordings by their firing patterns and also fall into distinct, nonoverlapping clusters in post hoc analysis of their electrophysiological parameters (Figure 2—figure supplement 1, Figure 2—source data 1).

A brief (typically 2–5 ms) light pulse at 60–90% maximal intensity elicited a strong (10–30 mV) depolarization in L4 FS cells, which, in 80% of cells (N = 44 cells from 35 animals), gave rise to a stereotypical burst of 2–7 (typically 3–5) spikes. Representative bursts in an example FS cell, evoked by 2 and 5 ms light pulses, are illustrated in Figure 2A and B. Spiking almost never persisted beyond the illustrated 25 ms time window, although the underlying subthreshold depolarization often lasted for 50 ms or more. We performed detailed analysis on all FS cells that consistently fired bursts of four or more spikes (25 cells from 20 animals). Bursts in this dataset had three distinguishing properties:

1. Very high frequency: Averaged over these 25 cells, the first three interspike intervals (ISIs) were 2.4 ± 0.05, 2.2 ± 0.08, and 2.7 ± 0.13 ms (mean ± SEM), respectively, for an average burst frequency ( = 1/average ISI) of 418 ± 9.5 Hz, not significantly different from the extracellular ripplet frequency (p=0.56).

2. Very high temporal precision: Bursts in a given cell were precisely reproducible, as illustrated in Figure 2A and B by the near-perfect registration of consecutive sweeps, the alignment of spikes in the raster plots and the very low jitter in spike times indicated above the raster plot. In the full dataset, spike jitter averaged 23 ± 4, 63 ± 10, 110 ± 12, and 183 ± 21 μs for the four spikes, which translates to coefficients of variation (CV = SD/mean) of 0.7 ± 0.1%, 1.1 ± 0.2%, 1.4 ± 0.1% and 1.8 ± 0.2%, respectively. This low jitter is also illustrated in Figure 2H and I, in which the vertical extent of the boxed regions indicates 10–90th percentiles of spike time jitter and CV, respectively.

3. High animal-to-animal reproducibility: Across slices from different animals, the distributions of peak spike times for each of the four spikes in the burst was very narrow: 3.1 ± 0.06, 5.5 ± 0.08, 7.7 ± 0.12, and 10.3 ± 0.14 ms after light onset. This is also illustrated in Figure 2H and I, in which the horizontal extent of the boxed regions indicates 10–90th percentile of spike times.

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Electrophysiological parameters of fast-spiking (FS) and regular-spiking (RS) neurons.

Analysis was done on a subset of 32 FS interneurons and 25 RS cells in slices from 25 and 22 animals, respectively, 3–6.5 weeks old (14 animals were common to both subsets). A total of eight electrophysiological parameters were analyzed per cell. Single-spike parameters were measured at rheobase (minimal current evoking an action potential). All current steps were 600 ms long.

Electrophysiological parameters definitions:

V_rest: resting potential upon break-in, with no holding current applied.

V_threshold: the voltage where dv/dt = 5 V/s.

Spike height: Spike peak-V_threshold.

Spike width at half-height (SWHH): spike width measured half-way between V_threshold and spike peak.

After Hyperpolarization (AHP): V_threshold -spike trough.

Input Resistance (R_in): the slope of the I-V plot, calculated from 4 to 6 positive and negative subthreshold current steps, at membrane potentials up to ±15 mV from rest.

I_max: the maximal current step applied before a noticeable reduction in spike height.

F_max: the maximal steady-state firing frequency, computed as the reciprocal of the average of the last five interspike intervals (ISIs) in a spike train elicited by I_max.

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Since thalamocortical axons also form a lower tier of terminations in L5B (Frost and Caviness, 1980; Herkenham, 1980; Agmon et al., 1993; Meyer et al., 2010), we also tested for occurrence of light-evoked spike bursts in infragranular FS cells. Brief light pulses evoked in L5B FS interneurons spike bursts that were indistinguishable, in spike number and frequency, from those in L4; of 13 cells stimulated with 2 ms light pulses, 11 cells from nine animals fired consistently four spikes/stimulus, at an average frequency of 405 ± 13 Hz (Figure 2—figure supplement 2). In the remainder of this study, we focus on L4.

To examine if burst patterns were dependent on stimulus parameters (light duration and intensity), we first compared bursts elicited by 2 and 5 ms light pulses. In the example cell in Figure 2A, a 2 ms stimulus elicited a precisely reproducible four-spike burst (10 superimposed red traces); increasing stimulus duration to 5 ms left the timing and jitter on these four spikes nearly unchanged but occasionally elicited a fifth, long-latency spike (arrowhead) with considerably higher jitter compared to the first four spikes (blue traces; note increased jitter in the raster plot in the lower panel). We refer to such spikes, with higher jitter and occasional failures, as ‘low-reliability spikes.’ All seven FS cells tested at both stimulus durations fired more spikes in response to a 5 ms compared with 2 ms stimulus, with a median increase of one spike/stimulus (Figure 2C) but with no appreciable change in timing and precision of the earlier spikes, as seen by the identical median values of the second spike jitter and the first ISI at the two stimulus durations (Figure 2E).

We then compared the number and precision of spikes in response to different light intensities. Bursts elicited by 20 and 90% intensity, in the same example cell from Figure 2A, are illustrated in Figure 2B. At the lower intensity, there was again one less spike, but in addition the jitter of all spikes except the first was >3× higher. In a subsample of 14 cells tested with 5 ms light pulses at five different intensities (10, 20, 40, 60, and 90% of maximal intensity), the average number of spikes/trial increased from 2.9 at 10% to 4.8 at 90% intensity (Figure 2D). As seen by comparing the second spike jitter and first ISI between at 20 and 90% light pulses (Figure 2F), overall spike timing did not differ between the two intensities (p=0.38) but at lower intensities spikes were much less precise (second spike jitter: 106 ± 13 vs. 43 ± 6 μs, p<0.0001). That ISIs were largely independent of stimulation intensity suggested that the burst pattern was not intrinsically generated in the FS cell but was imposed on it by extrinsic inputs. Consistent with this conclusion, reducing the light level resulted in some cells in spikes dropping out sporadically, revealing apparent subthreshold EPSPs that remained aligned with the temporal structure of the burst (Figure 2G, guidelines). That EPSPs elicit FS spikes with such high precision is consistent with the properties of excitatory synaptic inputs onto FS interneurons in neocortex and hippocampus (Geiger et al., 1997; Galarreta and Hestrin, 2001).

What were the temporal relationships between FS spike bursts, thalamocortical volleys, and ripplets? We plotted all FS spike times in our dataset as a histogram and then modeled each spike order as a Gaussian (Figure 2J). Overlaying Gaussians representing FS spikes with those representing thalamocortical volleys from Figure 1G (Figure 2K) revealed a close temporal relationship between the first FS spike and the initial thalamocortical volley, with the postsynaptic spike following the presynaptic volley at a latency of 0.8 ms, consistent with a monosynaptic response. Later FS spikes, however, actually preceded the closest presynaptic volley, consistent with the conclusion above that the additional thalamocortical volleys did not drive the postsynaptic bursts in a 1:1 manner. In contrast, overlaying the distributions of FS spikes and LFP transients (Figure 2L) revealed a 1:1 relationship between these events, however, with the two oscillations almost exactly out of phase: each ripplet transient lagged behind the corresponding FS spike peak by 0.44–0.54 of a cycle, translating to 1.0–1.3 ms.

FS cells synchronized their firing with near-zero lag and submillisecond precision

Given the precise temporal relationship between FS spikes and the population activity reflected as ripplets, one would expect different FS cells in the same barrel to fire in tight synchrony with each other. We therefore examined intra-barrel FS-FS temporal relationships by simultaneous paired recordings. Indeed, when stimulated by a light pulse, simultaneously recorded FS-FS pairs exhibited highly precise spike synchrony. In the two example pairs shown in Figure 3A and B, the peaks of the first three spikes in each burst aligned to within 0.1–0.3 ms between the two cells. To quantify the magnitude and precision of pairwise synchrony, we used the Jitter-Based Synchrony Index (JBSI), which is a normalized measure of spike-spike synchrony in excess of that expected by chance (Agmon, 2012; see ‘Materials and methods’). Synchrony is defined as the fraction of spikes co-occurring within a predetermined ‘synchrony window’ (SW), and chance synchrony is the average synchrony remaining after shifting each spike in one train by a random jitter ≤J, J = 2·SW. When calculated for decreasing SW values, the JBSI typically increases to a maximum and then precipitously drops off to zero, as J falls below the intrinsic precision of the system and the applied jitter no longer disrupts the pairwise synchrony. We defined ‘pairwise precision’ as the smallest SW value with JBSI > 0.5. Since neurons can maintain a precise temporal relationship even when they fire at non-zero time lags relative to each other, one can extend this analysis by calculating the JBSI for a range of virtual lags (shifts) of one spike train relative to the other, analogous to a classical cross-correlation histogram; we defined ‘pairwise lag’ as the virtual lag for which the JBSI was maximized. The full analysis can be represented as a two-dimensional matrix in which the JBSI is plotted as a function of the two parameters, SW and virtual lag, as illustrated in Figure 3C for the FS pair shown in panel A. Vertical and horizontal cross-sections through the JBSI matrix are plotted to the right and top of the matrix, illustrating how the JBSI varied with SW and virtual lag values, respectively.

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We calculated the JBSI matrices for six FS-FS pairs from which at least 100 spikes were recorded per cell. The averaged horizontal and vertical cross-sections through the six matrices are plotted in Figure 3E and F, respectively, and the pairwise precision and lag (in absolute values) of the six pairs are plotted in Figure 3G. The median pairwise precision and lag were 0.3 and 0.1 ms, respectively. While there is some degree of arbitrariness in the exact definition of pairwise precision, this analysis indicates that FS spikes within a given barrel synchronized with near-zero lag and with sub-millisecond precision.

What accounted for this highly precise FS-FS synchrony? Precise spike synchrony is most often attributed to electrical coupling via gap junctions (Galarreta and Hestrin, 1999; Mancilla et al., 2007), inhibitory synaptic connectivity (Gibson et al., 2005; Hu et al., 2011), or common excitatory inputs (Perkel et al., 1967; Sears and Stagg, 1976; Alonso et al., 1996). Unlike rat cortex, electrical coupling between FS interneurons in the mouse is weak, with average coupling coefficient of ~1.5% (Galarreta and Hestrin, 2002; Meyer et al., 2002; Hu et al., 2011; Hu and Agmon, 2015). The right panel in Figure 3D illustrates how we tested for electrical coupling, which in all six pairs was absent or barely detectable (coupling coefficient < 1%). In addition, inhibitory synaptic connections were observed in only two of the six FS-FS pairs, including the pair of Figure 3B (Figure 3D, left panels) but not of Figure 3A. We conclude by elimination that the precise FS-FS synchrony we observed was most likely driven by common excitatory inputs.

FS and RS spikes were phase-locked to the ripplet oscillation

To examine directly and in more detail the temporal relationship between FS spike bursts and ripplets, we recorded light-evoked bursts in nine FS cells (from nine animals), simultaneously with the LFP in the same barrel. Three examples from different animals are illustrated in Figure 4A, with averaged LFP ripplets (magenta traces) and 10 superimposed intracellular FS bursts (red traces). As indicated by the vertical guidelines, FS spike peaks were closely aligned with the troughs (the positive maxima) in the extracellular waveforms, almost exactly out of phase with the ripplet peaks (the negative maxima), consistent with the conclusion above from the comparison of the population distributions in Figure 2L. Figure 4A also illustrates that the number of FS spikes in the different slices (3, 4, and 5) was exactly one more than the number of ripplet peaks (2, 3, and 4, respectively), reflecting the fact that an FS spike occurred on every trough, from the one preceding the first LFP peak to the one following the last.

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Population activity reflected in the LFP is likely to be dominated by excitatory (RS) cells, which are the majority (~85%) cell type in L4 (Lin et al., 1985; Gabbott and Somogyi, 1986; Beaulieu, 1993). We recorded from RS cells in whole-cell, current-clamp, and voltage-clamp modes to reveal the timing of spikes and synaptic events, respectively, in relation to ripplets and FS bursts. In current-clamp mode, RS cells (Figure 4B, blue traces) responded to brief light pulses with a large depolarization (up to 15–20 mV above resting potential), crested by a series of 3–5 apparent EPSPs (slanted arrowheads) and typically giving rise to 1–2 spikes. Of 55 RS cells recorded in current-clamp mode and stimulated at a near-maximal light level, 73% fired at least one, but never more than two spikes/stimulus; the rest either remained subthreshold (11%) or occasionally fired three or more spikes (16%). Spikes evoked by near-maximal stimulus levels were mostly highly precise (Figure 4B, left), but spikes arising from late EPSPs were often of lower reliability and occasionally failed (Figure 4B, right, vertical arrowhead). Spikes evoked by low light levels would often switch sporadically between EPSPs, a pattern we refer to as ‘EPSP hopping’ (Figure 4B, left, inset). To examine phase relationships between RS spikes and ripplets, we recorded in current-clamp mode from 10 RS cells (from 10 animals) simultaneously with the LFP. As indicated by the vertical guidelines in the two example records in Figure 4B, peaks of spikes and of apparent EPSPs in RS cells occurred close to and usually slightly before the LFP negative peaks, that is, in-phase with ripplets. This is reminiscent of hippocampus CA1 pyramidal cells, which fire close to the negative ripple peaks (Buzsáki et al., 1992; Csicsvari et al., 1999b; Klausberger et al., 2004; Hulse et al., 2016).

We quantified the phase relationships between ripplets and FS and RS spikes in these two datasets (of 9 and 10 cells from 9 and 10 animals, respectively) by assigning each ripplet trough a phase angle of 0^o, and assigning phase angles of –180^o and 180^o to the negative ripplet peaks preceding and following the trough, respectively. We then assigned a phase angle to each of the 28 FS spikes and 13 RS spikes observed in these experiments by interpolating its time of peak between the nearest ripplet trough and peak (Figure 4C). The phase angles of the two cell types were nonoverlapping, with FS spikes occurring at a median phase angle of 26^o (i.e. slightly past the trough; 10–90th percentile range: (–14)–82^o, translating to a range of 0.65 ms), and RS spikes occurring at a median phase angle of 161^o (i.e. slightly before the peak; 10–90th percentile range: 145–187^o, translating to a range of ~0.3 ms). Thus, on average, FS spikes preceded RS spikes by ~135^o or ~0.9 ms. While this appears inconsistent with the order of firing during hippocampal ripples, in which FS cells lag behind pyramidal cells by about 100^o (Hájos et al., 2013), 100^o of a 180 Hz ripple oscillation amounts to 1.5 ms. Given the 2.4 ms ripplet period, the 0.9 ms delay between L4 FS and RS spikes means that FS spikes (other than the first) occurred 1.5 ms after RS spikes, exactly as in the hippocampus. Notably, a 1.5 ms lag is precisely the time it takes for RS cells to generate monosynaptic EPSPs in FS cells, and for postsynaptic FS cells to reach threshold and fire (Galarreta and Hestrin, 2001). Thus, this analysis is consistent with a model by which FS spikes (other than the first, which was clearly driven by thalamocortical excitation) were directly driven by excitation from neighboring RS cells.

FS spikes and ripplet troughs were phase-locked to EPSC-IPSC alternations in RS cells

To examine the temporal relationships between FS and RS cell responses directly, we performed simultaneous recordings from six FS-RS pairs (from four animals), switching the RS recording mode between current and voltage clamp to reveal both spikes and postsynaptic currents, respectively. When in voltage clamp, we held the RS cells between –50 and –55 mV to distinguish between EPSCs (negative deflections) and IPSCs (positive deflections). We also tested recorded pairs for direct synaptic connections between them. Two example pairs are shown in Figure 5A and B, with 10 superimposed traces of FS spike bursts (red) and simultaneously recorded RS postsynaptic currents (blue), and with sequentially recorded RS spikes in the upper trace. Note that the pair in panel Figure 5A is illustrated at two different stimulus intensities. The voltage-clamped RS responses revealed a sequence of regularly alternating EPSCs and IPSCs (E’s and I’s, onsets marked by filled and hollow arrowheads, respectively). These E-I sequences were tightly synchronized between neighboring RS cells in a given barrel (Figure 5—figure supplement 1). The dashed vertical guidelines in Figure 5A and B are aligned with FS spikes peaks and demonstrate that each FS spike occurred immediately following the onset of an EPSC and before the onset of an IPSC in the RS cell. Although both pairs were synaptically connected in the FS→RS direction (insets), IPSCs in the RS cell were still observed when FS spikes dropped out at the lower stimulus level (rightmost guideline in panel Figure 5A, lower traces), indicating that they were evoked by multiple FS cells in addition to the recorded one. Comparing the total charge transfer (the area under the curve) between the voltage-clamp records of RS cells A and B reveals a net inhibitory response in A (positive total charge) and a net excitatory response in B (negative total charge); this large variability in excitatory-to-inhibitory ratio between RS cells was representative of our sample (see also Figure 5—figure supplement 1), and is also observed in hippocampal pyramidal neurons during ex vivo ripples (Ellender et al., 2010; Hájos et al., 2013; Gan et al., 2017).

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To quantify the temporal relationships between FS spikes and E-I alternations in RS cells, we assigned a phase angle to each of the 16 FS spikes observed in this dataset by defining RS EPSC onsets as 0⁰ and RS IPSC onsets as 180^o (Figure 5C). The median FS spike phase angle was 59^o (10–90th percentile range: 5–106^o). Therefore, given the 2.4 ms oscillation period, each FS spike occurred about 0.4 ms after the onset of an EPSC in the RS cell and 0.8 ms before the onset of an IPSC in the same RS cell. The most parsimonious interpretation for these temporal relationships is that RS and FS cells received a barrage of shared EPSPs at the ripplet frequency; these EPSPs elicited short-latency (0.4 ms) spikes in the FS cells, and FS spike volleys, in turn, elicited IPSPs in RS cells after a 0.8 ms monosynaptic delay. As described above, RS spikes occurred, on average, 0.9 ms after the previous FS spike volley, implying that RS cells reached firing threshold nearly simultaneously with the arrival of a wavefront of inhibition, leaving a very narrow ‘window of opportunity’ for RS cells to fire. The earliest cohort of RS cells to reach spike threshold fired while ‘laggards,’ cells slightly slower to reach threshold, were preempted from firing by the incoming IPSP volley. This explains why only a fraction of RS cells fired on any given cycle and also explains how synchronous RS firing was maintained from one cycle to the next.

To further test the role of inhibition in ripplet oscillations we blocked fast inhibition locally, with the GABA_A antagonist gabazine applied from an extracellular patch pipette placed in the same barrel. As observed in some studies of hippocampus ripples (Behrens et al., 2007; Ellender et al., 2010), this manipulation converted ripplet-related spiking to prolonged (up to 500 ms) paroxysmal discharges, in both FS and RS cells (Figure 5—figure supplement 2).

Lastly, to shed light on the current sinks and sources underlying the extracellular LFP oscillation, we examined directly the temporal relationships between ripplets and E-I sequences in RS cells by recording from RS cells in voltage-clamp mode simultaneously with the LFP in the same barrel. An example recording is shown in Figure 5D, with the averaged voltage-clamped traces from the RS neuron (blue) below the averaged LFP (magenta). The vertical guidelines demonstrate that the troughs of the ripplet waveform were aligned with the onset of EPSCs in the RS cell. Plotting ripplet troughs against EPSC onsets in eight RS cells recorded simultaneously with the LFP (in eight slices from four animals) demonstrated the close temporal correspondence between the extracellular troughs and the onsets of intracellular EPSCs (Figure 5E), suggesting that population EPSCs in RS cells were a major contributor to the current sinks underlying the LFP transients.

We describe here transient (<25 ms), ultrafast (~400 Hz) network oscillations, which we refer to as ‘ripplets,’ elicited in thalamorecipient cortical layers by brief (as short as 1 ms) optogenetic stimulation of thalamocortical axons and terminals. The oscillation was reflected in the extracellular voltage (the LFP) as 2–5 negative waves that immediately followed the initial current sink generated by the thalamocortical volley but were dependent on postsynaptic activity within L4 (Figure 1). In whole-cell intracellular recordings, inhibitory FS cells fired a highly reproducible burst of 3–6 spikes at the ripplet frequency (Figure 2), with spike peaks aligned with LFP troughs (Figure 4A and C). As revealed by pairwise recordings, FS cells fired in exquisitely precise, sub-millisecond synchrony (Figure 3). Excitatory RS cells mostly fired 1–2 spikes per ripplet, which, as a population, were temporally offset from FS spikes, preceding each FS spike (except the first) by ~1.5 ms and aligned with ripplet peaks (Figure 4B and C). Voltage-clamp recordings at an intermediate holding potential revealed a precise, alternating sequence of EPSCs and IPSCs in RS cells (Figure 5A and B), phase-locked to ripplets (Figure 5D) and synchronized between neighboring RS cells (Figure 5—figure supplement 1). On average, each FS spike followed an RS EPSC at short (0.4 ms) latency and preceded an RS IPSC by 0.8 ms (Figure 5C), suggesting that FS spikes were elicited by EPSPs shared with the excitatory cells, and in turn evoked monosynaptic IPSPs in excitatory cells.

Taken together, these observations suggest the following synaptic mechanisms for ripplet generation (Figure 6). The highly synchronous, optogenetically evoked thalamocortical volley set in motion a cascade of ‘spike packets’ in subsets of L4 excitatory cells, each packet triggering the next one (Figure 6A), similar to feedforward ‘synfire chains’ (Abeles, 1991; Diesmann et al., 1999; Mehring et al., 2003; Barral et al., 2019) except that a given excitatory cell could fire in more than one packet. Although only a subset of all RS cells fired on any given cycle, the strength, reliability, and high prevalence of excitatory RS-RS synapses within L4 barrels (Feldmeyer et al., 1999; Petersen and Sakmann, 2000; Schubert et al., 2003; Lefort et al., 2009; Kameda et al., 2012; Koelbl et al., 2015) ensured that this subset was sufficient to extend the oscillation by one more cycle. The 2.4 ms period of the oscillation was determined by the interval between packets, which was the sum of the synaptic delay (from RS spike to EPSP onset in a postsynaptic RS cell) and the rise time (from EPSP onset to spike in the postsynaptic RS cell). The initial thalamocortical volley, as well as each subsequent RS spike packet, elicited highly synchronous FS spike volleys, supported by the strong TC→FS and RS→FS connectivity in L4 of barrel cortex (Simons and Carvell, 1989; Agmon and Connors, 1992; Swadlow et al., 1998; Gibson et al., 1999; Galarreta and Hestrin, 2001; Porter et al., 2001; Bruno and Simons, 2002; Beierlein et al., 2003; Gabernet et al., 2005; Bruno and Sakmann, 2006; Inoue and Imoto, 2006; Sun et al., 2006; Cruikshank et al., 2007; Kameda et al., 2012; Hu and Agmon, 2016; Yu et al., 2019). The delay from an RS spike volley to the evoked FS spike was ~1.5 ms, significantly shorter than the oscillation period, because synaptic latencies, EPSC rise times, and spike rise times are all faster in FS cells (Hu et al., 2014; Tremblay et al., 2016). This left a gap of 0.9 ms between the FS spike volley and the next RS volley, just enough time for FS cells to elicit a wavefront of feedforward IPSPs in RS cells (Figure 6B). This inhibitory wavefront coincided with the rising phase of the RS spikes, too late to block the earliest spikes but just in time to preempt any laggard RS cells from firing. In this manner, FS cells enforced RS firing synchrony and thereby also FS spike synchrony in the next cycle. Only a fraction of all excitatory cells escaped this feedforward inhibitory control and fired on any given cycle, enough to elicit the next cycle but not enough for the excitatory feedforward cascade to turn into a paroxysmal chain reaction. The number of excitatory cells firing likely declined with each cycle, possibly because high-frequency activity suppresses excitatory synapses more than inhibitory ones (Galarreta and Hestrin, 1998), until the oscillation died out.

Figure 6

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According to this model, both phasic inhibition and phasic excitation, reverberating at the same ultrafast frequency but in antiphase with each other (Figure 6B), are necessary for generating this network oscillation. While FS cells are a critical component of the circuit, they do not act as independent pacemakers, and direct FS-FS interactions, chemical or electrical, may not be a necessary feature (see below). Several aspects of this model are at odds with currently proposed models of hippocampal ripples (see below), and this could reflect real differences between the two types of oscillations. Nevertheless, the strong phenomenological similarities between neocortical ripplets and hippocampal ripples (see below) suggest that optogenetically evoked ripplets may be a uniquely accessible model system for deciphering the cellular, synaptic, and network mechanisms underlying other fast and ultrafast neocortical and hippocampal oscillations, mechanisms that to date remain elusive.

Figure 1- Source Data 1 contains the cell count data used for Figure 1 - Figure Supplement 1; Figure 2- Source Data 1 contains the electrophysiological parameters data used for Figure 2 - Figure Supplement 1;Code used to calculate synchrony indices has been deposited to GitHub.

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Author details

1. Hang Hu

   Department of Neuroscience, West Virginia University School of Medicine, Rockefeller Neuroscience Institute, Morgantown, United States

   Contribution

   Formal analysis, Investigation, Writing - review and editing, Electrophysiological recording and analysis

   Competing interests

   No competing interests declared

2. Rachel E Hostetler

   Department of Neuroscience, West Virginia University School of Medicine, Rockefeller Neuroscience Institute, Morgantown, United States

   Contribution

   Formal analysis, Investigation, Writing - review and editing, Histology, confocal imaging, image analysis

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4185-6468

3. Ariel Agmon

   Department of Neuroscience, West Virginia University School of Medicine, Rockefeller Neuroscience Institute, Morgantown, United States

   Contribution

   Conceptualization, Formal analysis, Funding acquisition, Writing - original draft, Writing - review and editing

   For correspondence

   aric.agmon@gmail.com

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-7556-8130

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