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. 2004 Jul 14;559(Pt 2):347–353. doi: 10.1113/jphysiol.2004.068973

Coexistence of gamma and high-frequency oscillations in rat medial entorhinal cortex in vitro

M O Cunningham 1, David M Halliday 2, Ceri H Davies 3, Roger D Traub 4, Eberhard H Buhl 1, Miles A Whittington 1
PMCID: PMC1665136  PMID: 15254156

Abstract

High frequency oscillations (> 80–90 Hz) occur in neocortex and hippocampus in vivo where they are associated with specific behavioural states and more classical EEG frequency bands. In the hippocampus in vitro these oscillations can occur in the absence of pyramidal neuronal somatodendritic compartments and are temporally correlated with on-going, persistent gamma frequency oscillations. Their occurrence in the hippocampus is dependent on gap-junctional communication and it has been suggested that these high frequency oscillations originate as collective behaviour in populations of electrically coupled principal cell axonal compartments. Here we demonstrate that the superficial layers of medial entorhinal cortex can also generate high frequency oscillations associated with gamma rhythms. During persistent gamma frequency oscillations high frequency oscillations occur with a high bispectral coherence with the field gamma activity. Bursts of high frequency oscillations are temporally correlated with both the onset of compound excitatory postsynaptic potentials in fast-spiking interneurones and spikelet potentials in both pyramidal and stellate principal neurones. Both the gamma frequency and high frequency oscillations were attenuated by the gap junction blocker carbenoxolone. These data suggest that high frequency oscillations may represent the substrate for phasic drive to interneurones during persistent gamma oscillations in the medial entorhinal cortex.

In vivo, high frequency oscillations (> 100 Hz) generated by neuronal networks in the hippocampus (Buzsáki et al. 1992) and neocortex (Grenier et al. 2001) have been observed during slow-wave sleep, rest and consummatory behaviour. Due to the fast and transient nature of this activity these events are termed ripples (O'Keefe & Nadel, 1978; Draguhn et al. 2000). Previously, it has been hypothesized that these ripples reflect synchronized IPSPs occurring in the pyramidal cell layer of CA1 of the hippocampus (Buszáki et al. 1992; Ylinen et al. 1995).

Recently, an additional hypothesis has emerged. In 1998, Draguhn et al. observed spontaneous high frequency oscillations which were reminiscent of ripples observed in vivo. These ripples were not inhibited by antagonism of either excitatory or inhibitory synaptic transmission; however, this activity was sensitive to compounds which could block gap junctions. In calcium-free bathing medium or increased alkalization, the ripple activity increased. In addition, patch clamp recordings from CA1 pyramidal neurones revealed spikelet potentials (MacVicar & Dudek, 1982) that were tightly correlated to the field recording. On the basis of these data, they surmised that this activity was dependent on transmission via electrical synapses. Subsequent work has provided evidence that axonal coupling between pyramidal neurones is involved in the generation of high frequency oscillation (Draguhn et al. 1998; Traub et al. 1999; Schmitz et al. 2001) and gamma (20–80 Hz) network oscillatory activity (Traub & Bibbig, 2000; Traub et al. 2002; Traub et al. 2003).

Ripples in the entorhinal cortex were originally observed by Chrobak & Buzsáki (1996). Subsequently, high frequency activity has been reported in the entorhinal cortex of human epileptic patients (Bragin et al. 1999; Staba et al. 2002). This finding has been repeated in epileptic rats in vivo (Bragin et al. 1999). Interestingly, high frequency oscillations have been observed superimposed on epileptiform bursts in an in vitro hippocampal slice preparation (Wong & Traub, 1983). Both experimentally and clinically, high frequency oscillations can be seen before and during ictal discharges, suggesting a role for gap junction coupling during this activity (Traub et al. 2002).

The present study examined the relationship between gamma activity and high frequency oscillations in the medial entorhinal cortex. We have found that gamma activity in the EC is sensitive to blockade of gap junctions, and that in layer II–III of the EC we can observe concurrent high frequency activity and gamma oscillations. In addition we relate this to the behaviour of interneurones and principal cells.

Methods

Transverse EC–hippocampal slices (450 μm) were prepared from brains taken from adult Wistar rats, anaesthetized with a lethal dose of inhaled isoflurane, immediately followed by an i.m. injection of ketamine (≥ 100 mg kg−1) and xylazine (≥ 10 mg kg−1) in accordance with the UK Animals (Scientific Procedures) Act 1986. Slices were then transferred to either a holding chamber or directly to a recording chamber. Here, they were maintained at the interface between a continuous stream (1.2 ml min−1) of artificial cerebrospinal fluid (ACSF; composition, mm: NaCl (126), KCl (3), NaH2PO4 (1.25), NaHCO3 (24), MgSO4 (2), CaCl2 (2) and glucose (10)), and warm, moist carbogen gas (95% O2–5% CO2). All drugs were bath applied at known concentrations: kainic acid ((2S,3S,4R)-carboxy-4-(1-methylethenyl)-3-pyrrolidineacetic acid), 200–400 nm, was obtained from Tocris Cookson (UK); carbenoxenlone, 200 μm, was obtained from Sigma (UK).

Extracellular recording electrodes were filled with ACSF and had resistances in the range of 2–5 MΩ. Intracellular electrodes were filled with KCH3SO4 and had resistances in the range of 70–130 MΩ. Field and cellular recordings were taken from lamina II–III except in experiments attempting to identify the laminar profile of gamma and high frequency rhythms. Peak frequency and power values were obtained from power spectra generated with Fourier analysis in the Axograph software package (Axon Instruments, Union City, CA, USA). All values are given as the mean ± standard error of the mean. Spectrograms were constructed off-line from digitized data (digitization frequency 10 kHz) using a 60 s epoch of recorded activity. High frequency oscillations were isolated from gamma rhythms by digital band-pass filtering off-line at 0.15–0.40 kHz. We use a specific bispectral coefficient to investigate higher order dependency between different frequency components in the field potential data. This coefficient is based on the frequency beating model, which investigates to what extent different frequency components in the field potential add, or beat, together in a non-linear manner. The coefficient is defined for time series, x, as (Brillinger, 1965):

graphic file with name tjp0559-0347-m1.jpg

Here fxxx(λ, μ) is the third order spectrum of process x at frequencies λ and μ, and fxx(λ) is the normal power spectrum, at frequency λ. Estimation of this coefficient, and the setting of confidence limits are described in Halliday et al. (1995). Equation (1) is the modulus squared of the standardized third order bi-spectrum (Brillinger & Rosenblatt, 1967). Standardized bi-spectra provide a measure of higher order interactions which are independent of distinct features in the second order spectra (Godfrey, 1965), an important aspect for the present data. All bispectral coefficients were calculated from 60 s of data. Further information on this methodology can be obtained from David Halliday (dh20@ohm.york.ac.uk).

Results

Bath application of 200–400 nm kainate generated persistent gamma frequency oscillations (46.5 ± 2.1 Hz) in all slices in the study (n = 22). Power was greatest in the superficial layers II and III (see Cunningham et al. 2003). The gap junction blocker carbenoxolone (0.2 mm) significantly reduced the power of the gamma rhythm (control power 381.1 ± 50.1 μV (2 s)−1, in the presence of carbenoxolone 52.7 ± 25.4 μV (2 s)−1, P < 0.05, n = 9), suggesting an involvement of gap junction-mediated intercellular communication (Fig. 1A). Previous studies in area CA1 of the hippocampus showed that persistent gamma rhythms coexist with high-frequency rhythms (80–250 Hz) modulated at the gamma frequency (Whittington & Traub, 2003). High-pass filtering of the medial entorhinal gamma rhythm also showed gamma-modulated epochs of high frequency activity (Fig. 1B). The activity was distributed across a large frequency range from 150 Hz up to > 350 Hz in some cases (Fig. 1Bb). Concomitant with the reduction in gamma power, carbenoxolone also significantly reduced this high frequency component of the rhythm.

Figure 1. Both gamma frequency and high frequency field potential oscillations are sensitive to carbenoxolone.

Figure 1

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A, effects of carbenoxolone, 0.2 mm, on gamma frequency field potential oscillations in superficial medial entorhinal cortex. a, upper trace shows gamma oscillation in the presence of 400 nm kainate. Lower trace shows reduced amplitude of gamma oscillation after 60 min bath application of carbenoxolone. Scale bars 0.2 mV, 200 ms. b, pooled power spectra (n = 8) taken from 60 s epochs of field gamma oscillation in the presence of kainate alone (black line) or kainate plus carbenoxolone (red line). B, effects of carbenoxolone on high frequency oscillations. a, upper traces show another example of population gamma frequency oscillations attenuated by bath application of 0.2 mm carbenoxolone. Lower traces show the high-pass filtered (> 150 Hz) versions of the upper traces demonstrating the gamma-frequency modulated high frequency activity is attenuated by carbenoxolone. Scale bars 0.2 mV, 100 ms. b, example traces of high-pass filtered data on expanded time base, with corresponding autocorrelograms. Scale bars 10 ms, 20 μV. Spectrograms of high-pass filtered field potential data in the absence (left hand panel) and presence (right hand panel) of carbenoxolone. Note the packets of high-frequency activity occurring at gamma frequency in control are abolished by carbenoxolone.

To quantitatively analyse the relationship between the gamma rhythm and the nested high frequency rhythm we calculated bispectral coefficients for frequencies in the range 5 Hz to 250 Hz. The data used were broad-band extracellular recordings (0.1–1 kHz) taken from layers I, II–III and the deep layer IV–V. The bands parallel to the frequency axes centred around the gamma band frequency (see Fig. 2) indicate a significant dependence of the higher frequency components on gamma band activity in all layers. The strongest non-linear interactions occurred in layers I and II/III.

Figure 2. Bispectral analysis showing dependence between high frequency and gamma frequency field potential oscillations.

Figure 2

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A, relationship between gamma frequency and high frequency oscillations in medial entorhinal layer I. Upper example trace shows 0.5 s epoch of field potential data from LI; below that is the corresponding high-pass filtered trace (> 150 Hz). Bispectral coefficient shown for frequencies 5 Hz to 250 Hz; values above 3.3 (the lowest value contour) indicate a significant higher order interaction between frequency components. B, relationship between gamma frequency and high frequency oscillations in medial entorhinal layer II–III. Upper trace shows 0.5 s epoch of field potential data. Note the phase reversal compared to A. Lower trace shows the corresponding high-pass filtered trace (> 150 Hz). Graph sows the bispectral coefficient as in A. C, relationship between gamma and higher frequencies for deep medial entorhinal field potentials. Data represented as in A and B. Scale bars 0.1 mV (unfiltered field), 0.05 mV (high-pass filtered fields), 100 ms.

The proposed mechanism underlying these high frequency rhythms, and the accompanying gamma frequency rhythm, involves the propagations of ectopically generated action potentials through a plexus of principal cell axons connected via gap junctions (Draguhn et al. 1998; Traub et al. 1999, 2002, 2003). If this is the case then some of these ectopic action potentials would be expected to antidromically invade the soma of principal cells. Evidence for such an antidromic invasion was seen in LII–III stellate and pyramidal cells (Fig. 3). Full action potentials were generated in these cells at a frequency of ca 0.7 and ca 5.0 Hz, respectively, as previously reported (Cunningham et al. 2003). First order differentials of full spikes showed the coexistence of brief partial spikes with full spikes in 4/71 stellate cells and 3/17 pyramidal cells. In these cells brief partial spikes (spikelets) were seen unaccompanied by full spikes at a frequency of 5.4 ± 1.1 Hz in stellate cells (data not shown) and 2.9 ± 1.0 Hz in pyramidal cells (Fig. 3). Spikelets had an amplitude of 8.0 ± 0.7 mV and a rise time not significantly different from full spikes (rise time for full spikes was 0.27 ± 0.02 ms, for spikelets 0.34 ± 0.03 ms, P > 0.01, n = 500 events from 3 cells).

Figure 3. Superficial pyramidal cells show spikelets temporally correlated to high frequency field oscillations during field gamma oscillations.

Figure 3

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A, spiking behaviour in a LIII pyramidal cell during kainate-induced gamma frequency population oscillations. a, example trace of a pyramidal cell (membrane potential −61 V) showing sparse action potential generation but more regular (ca 8 Hz) spikelet generation. Inset shows 1st order differential of a full spike to show relationship between full spike and spikelet (scale bars, inset, 40 V s−1, 5 ms). b, the same pyramid hyperpolarized to −70 mV and then to −85 mV to show characteristic membrane voltage dependence of spikelets. Scale bars 10 mV, 0.5 s (a), 2 s (b). B, expanded time scale traces showing concurrently recorded field potential oscillation and spikelets in a pyramidal cell. Upper trace is the unfiltered field potential, with the middle trace the corresponding high-pass filtered recording (> 150 Hz). Spikelets occurred during the high frequency bursts of activity seen in the field. Inset shows spikelet-triggered average (n = 20) of the corresponding field potential 20 ms either side of the pyramidal cell spikelets. Note the temporal relationship between the spikelet and the field. Scale bars, 0.1 mV (unfiltered trace), 0.02 mV (filtered field), 5 mV (pyramidal cell), 25 ms.

If these spikelets represented a somatic correlate of axonal activity then they should occur temporally related to the high frequency field potential rhythm. To investigate this we performed pyramidal cell spikelet-triggered averaging of concurrently recorded, high-pass filtered field potential rhythms (Fig. 3B). Spikelets occurred with a strong temporal relationship to the field potential activity. The delay between the peak of the spikelets and the trough of the negative-going field potential events making up the high frequency activity was 1.4 ± 0.2 ms.

At the synaptic end of principal cell local axon collaterals action potentials generate excitatory postsynaptic potentials (EPSPs) in interneurones. During gamma oscillations these EPSPs are large and compound in nature despite the relatively sparse firing of action potentials in principal cell somata. The axon plexus hypothesis goes some way to explaining this input–output discrepancy if the majority of synaptic events are initiated by ectopic action potentials propagated through the axonal network. If this is the case then there should be a strong temporal correlation between the proposed field correlate of this plexus activity (the high frequency oscillation) and the pattern of EPSPs in individual fast spiking interneurones (Whittington & Traub, 2003). During kainate-induced persistent gamma frequency oscillations, fast spiking interneurones in layer II–III of the entorhinal cortex exhibited large (8.9 ± 0.2 mV, n = 500 events from 4 cells) compound EPSPs at a mean frequency of 25.6 ± 1.7 Hz, a frequency slower than the field oscillation and the concurrent rate of action potential generation in interneurones (see Cunningham et al. 2003) (Fig. 4A). Concurrently recorded interneurones and local field potentials both had a large high-frequency component revealed by high-pass filtering (Fig. 4B).

Figure 4. Superficial fast-spiking interneurones receive compound EPSPs temporally correlated with high frequency field potential oscillations.

Figure 4

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Interneurones received compound EPSPs coincident with bursts of high-frequency activity in the concurrently recorded field potential. A, example 1 s trace of fast-spiking interneurone activity during kainate-induced gamma frequency field potential oscillations. Scale bars 10 mV, 0.1 s. B, concurrently recorded field potential and interneuronal EPSP traces (from −70 mV membrane potential). Upper traces show unfiltered data (400 ms epochs). Lower traces show corresponding high-pass filtered versions of the above traces. Scale bars: 5 mV (unfiltered), 1 mV (filtered) for EPSPs, 0.1 mV (unfiltered), 0.02 mV (filtered) for field traces, 100 ms. Ca, averaged interneuronal EPSPs and corresponding field potential recording (n = 10) showing compound nature of EPSP is preserved with averaging, along with temporal correlation between EPSP components and field oscillations. Scale bars 4 mV (EPSP), 5 μV (field), 10 ms. b, average cross-correlogram of high-pass filtered EPSP and field recordings (n = 10, epoch = 3 s).

EPSP-triggered averaging (taking the peak of each compound EPSP) of the interneurone record and the concurrent local field potential preserved the compound nature of the postsynaptic response (Fig. 4Ca). Each EPSP temporally corresponded to a brief run of high frequency activity in the averaged field recording consisting of three to five negative-going population spikes of amplitude 10 ± 4 μV. The individual components of the EPSP average occurred with mean interval of 4.7 ± 0.6 ms, which was not significantly different from the interval between the components of the average high frequency field event (5.0 ± 0.7 ms, P < 0.05). The mean delay between the peak of each component of the EPSP average and the trough of the components of the high frequency oscillation was 1.8 ± 0.2 ms. Cross correlation of the high-pass filtered interneurone and local field recordings confirmed this analysis, with a mean phase lag of the trough of the high frequency activity with the peak of the filtered EPSP trace of 1.4 ± 0.3 ms.

Discussion

Persistent gamma frequency oscillations in the medial entorhinal cortex in vitro are superficially similar to those generated in hippocampus (Cunningham et al. 2003). Both have an absolute requirement for fast-spiking interneuronal output at gamma frequencies. Both require patent GABAA receptor-mediated synaptic transmission, phasic AMPA receptor-mediated excitation of fast-spiking interneurones and functional gap junctions. Both are sensitive to gap junction blockers but, in the hippocampus, it is not gap junctions between interneurone dendrites that are critical for generation (Hormuzdi et al. 2001). Further work in the hippocampus has suggested that it is interneuronal electrical connectivity in principal cells, particularly principal cell axons, that is required (Traub et al. 2003). Such activity is not dependent on cx36-containing gap junctions (Hormuzdi et al. 2001) and blockade of network activity with carbenoxolone does not involve astrocytic cx43 or other major connexin subtypes (Rouach et al. 2003). However, as with hippocampal principal cells, LII/III entorhinal principal cells express large quantities of mRNA for pannexins, which have been shown to constitute patent gap junctions in oocytes (Bruzzone et al. 2003). One manifestation of this axonal connectivity is the occurrence of high frequency (> 80 Hz) oscillations in field recordings (Draguhn et al. 1998). These high frequency oscillations occur concurrently with persistent gamma oscillations in hippocampus, and as we now show, medial entorhinal cortex. In vivo high frequency oscillations are seen predominantly associated with physiological sharp waves (Chrobak & Buzsáki, 1996). Although much larger in amplitude than the very fast oscillations associated with gamma reported here, a similar mechanism may underlie both phenomena (see Maier et al. 2003).

The role played by axo-axonic electrical connectivity has been proposed to involve the amplification of individual axonal activity by the ‘sharing’ of action potentials across a plexus of axons (Traub & Bibbig, 2000). In this manner the low somatic output from principal cells may be sufficient to provide the large phasic excitatory drive to interneurones and, in addition, the compound nature of EPSPs onto interneurones would be expected to be via multiple excitatory contacts, thus minimizing the risk of habituation. If this scenario occurs then some somatic manifestation of axonally generated action potentials would be expected in otherwise quiescent principal cell somata. Spikelets were seen in approximately 8% of principal cells recorded. Spikelets had rapid rise time kinetics identical to full action potentials and occurred almost instantaneously with individual periods of the concurrently recorded high frequency field oscillation. Spikelets or full spikes were only seen in any cell type of all cells recorded during a very small proportion of very fast oscillation periods, suggesting that these field events were network driven and did not constitute unit recordings. Direct evidence for electrical coupling between superficial principal cells has been shown using recordings from pairs of LIII pyramidal neurones (Dhillon & Jones, 2000). Coupling potentials were seen in ca 2% of cell pairs. At the other end of the principal cell axons, a strong temporal correlation was also seen with individual components of the interneuronal EPSP. The frequency of occurrence of components of the compound EPSP matched the frequency of the field oscillation. Individual components of the field oscillation occurred approximately 1.5 ms before the EPSP components.

These data support the idea that action potentials generated in axons, and not somata, principally underly the source of phasic drive to interneurones during a persistent gamma frequency oscillation. Correlations of the antidromic (somatic spikelet) and orthodromic (interneurone EPSP components) consequences of such ectopic action potential generation suggest that these spikes are generated more at the somatic than synaptic end of principal cell axons. Their dependence on gap junctional conductance (as also seen in the hippocampus) provides evidence for an axonal plexus as the source of drive for gamma oscillations in the entorhinal cortex.

Acknowledgments

We thank the Medical Research Council (UK), GlaxoSmithkline plc, NIH/NINDS, The Volkswagen Stifftung and the Wellcome Trust for financial support.

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