Intraglomerular gap junctions enhance interglomerular synchrony in a sparsely connected olfactory bulb network

Abstract

Key points: Despite sparse connectivity, population-level interactions between mitral cells (MCs) and granule cells (GCs) can generate synchronized oscillations in the rodent olfactory bulb. Intraglomerular gap junctions between MCs at the same glomerulus can greatly enhance synchronized activity of MCs at different glomeruli. The facilitating effect of intraglomerular gap junctions on interglomerular synchrony is through triggering of mutually synchronizing interactions between MCs and GCs. Divergent connections between MCs and GCs make minimal direct contribution to synchronous activity.

Abstract: A dominant feature of the olfactory bulb response to odour is fast synchronized oscillations at beta (15-40 Hz) or gamma (40-90 Hz) frequencies, thought to be involved in integration of olfactory signals. Mechanistically, the bulb presents an interesting case study for understanding how beta/gamma oscillations arise. Fast oscillatory synchrony in the activity of output mitral cells (MCs) appears to result from interactions with GABAergic granule cells (GCs), yet the incidence of MC-GC connections is very low, around 4%. Here, we combined computational and experimental approaches to examine how oscillatory synchrony can nevertheless arise, focusing mainly on activity between 'non-sister' MCs affiliated with different glomeruli (interglomerular synchrony). In a sparsely connected model of MCs and GCs, we found first that interglomerular synchrony was generally quite low, but could be increased by a factor of 4 by physiological levels of gap junctional coupling between sister MCs at the same glomerulus. This effect was due to enhanced mutually synchronizing interactions between MC and GC populations. The potent role of gap junctions was confirmed in patch-clamp recordings in bulb slices from wild-type and connexin 36-knockout (KO) mice. KO reduced both beta and gamma local field potential oscillations as well as synchrony of inhibitory signals in pairs of non-sister MCs. These effects were independent of potential KO actions on network excitation. Divergent synaptic connections did not contribute directly to the vast majority of synchronized signals. Thus, in a sparsely connected network, gap junctions between a small subset of cells can, through population effects, greatly amplify oscillatory synchrony amongst unconnected cells.

Keywords: gap junction; olfactory bulb; synchronization.

Figure 1. Non‐sister MCs are weakly synchronized in a sparsely connected GC–MC network that lacks intraglomerular gap junctions

A, basic model and simulation design. All network models consisted of two glomeruli (Glom A, red; Glom B, blue), each with 10 associated MCs. GCs, 30 per dendritic section, were distributed along the lengths of the MC lateral dendrites. Simulations were performed with the two glomeruli separated by a distance D _GlomA‐B between 0 μm (line 0 at top) and 720 μm. The lateral dendrites of MCs are illustrated much simplified in terms of the number of sections used in the computations. B, GC‐to‐MC connection probability was subjected to an exponentially decaying fall‐off as a function of distance between GC and MC cell bodies (see Methods). Illustrated is the situation for two glomeruli separated by 360 μm. Each trace (red or blue) represents the relative connection probability of a GC to MCs affiliated with one glomerulus as it changes its position with respect to the MC somata. C, example simulated membrane voltage traces (spikes truncated) from a model with no intraglomerular gap junctions. Traces reflect two example MCs and a GC. Horizontal lines at left indicate –65 mV. D and E, time course of synchronized activity amongst MCs affiliated with the same glomerulus (D) or between the two glomeruli (E) for D _GlomA‐B = 72 μm. As calculated (see Methods), the traces indicate synchronized activity within a 5 ms window. F and G, relationship between average synchrony in MCs between the two glomeruli, S _GlomA‐B, versus D _GlomA‐B for the MC–GC model lacking intraglomerular gap junctions (F). Simulations with no GC‐to‐MC connections (G). The white curves in F reflect exactly chance‐level (S _GlomA‐B = 1.0) of observing spikes in the MCs that occur with the specified lag time, assuming random spiking.

Figure 2. Synchronized activity in GCs in a sparsely connected MC–GC network with no intraglomerular gap junctions

A, schematic diagram of analysis. Synchrony between GCs was assessed for the subset of 30 GCs that made connections most proximal to the cell bodies of the MCs at each of the two glomeruli. B and C, time course of synchronized activity, both amongst GCs proximal to the same glomerulus (B) or between the two glomeruli (C; green trace). In C, the between‐glomeruli synchrony function for GCs is shown overlaid with the same function for MCs (purple trace; same as in Fig. 1 E) to allow comparison of the two cell types. The presence of rapid synchronized oscillations that alternate in time between MCs and GCs indicates that synchrony was due to fast reciprocal synaptic interactions between the two cell types. D, relationship between the average synchrony in GCs across the two glomeruli, S _GlomA‐B, and distance between glomeruli. White curves reflect chance‐level of GC synchrony (S _GlomA‐B = 1.0). E, scatter‐plot relating the amplitude of the individual MC and GC oscillations (as in C) indicates that synchronized activity was highly correlated between MCs and GCs. Line reflects fit to linear regression with correlation coefficient = 0.58. Pairing of the GC and MC peaks in the analysis was based on co‐occurrences within 40 ms.

Figure 3. Gap junctions between sister MCs augment interglomerular synchrony in a two‐glomerulus network

Aa, schematic diagram illustrating mutual synchronization in a sparsely connected network of MCs and GCs. Left, synchronized populations of MCs at different glomeruli (A and B) provide coordinated inputs into a population of GCs. Right, GCs synchronized by these inputs in turn provide coordinated inputs into MCs, thereby causing their synchrony. The illustrated networks are much simplified, with only 4 MCs per glomerulus. Cross‐talk between glomeruli is introduced by the GC in the second row that is excited by M_A2 and inhibits M_B1. Ab, all‐to‐all gap junctions (GJs) between MCs at each glomerulus (Pimentel & Margrie, 2008) provide an independent mechanism to synchronize sister MCs. This could help trigger the mutually synchronizing MC–GC interactions shown in Aa. B–D, time course of synchronized activity for a model with a glomerular separation of 72 μm that included intraglomerular gap junctions. Illustrated traces reflect synchrony time courses for MCs affiliated with the same glomerulus (B), GCs proximal to the same glomerulus (C), and MCs and GCs affiliated with different glomeruli (D). Note the large increase in synchronization both within and between glomeruli, as compared to the situation without gap junctions (see Figs 1 D and E, and 2 B and C). E, relationship between the average synchrony in MCs between the two glomeruli, S _GlomA‐B, and distance between glomeruli for the model with gap junctions. White curves reflect chance‐level of synchrony (S _GlomA‐B = 1.0). F, comparison of S _GlomA‐B values for lag = 0 ms in a model with (grey trace) and without (blue trace) intraglomerular gap junctions. Except for gap junctions, all other parameters in the two models were identical. G, relationship between the average degree of synchrony in GCs across the two glomeruli and the distance between glomeruli for the model with gap junctions. H, synchronized activity across glomeruli was correlated between MCs and GCs in the model with gap junctions. Line reflects fit to linear regression with correlation coefficient = 0.65.

Figure 4. Synchronized LFP oscillations are reduced in connexin 36 knockout (Cx36 KO) mice

A, experimental protocol: two electrodes were placed in mouse olfactory bulb slices to record beta/gamma LFP oscillations in the external plexiform layer (EPL) and an LFP in an adjacent glomerulus (Glom). Responses were to theta frequency stimulation of OSN axons (four stimulus bursts; not shown). MCL = mitral cell layer; GCL = granule cell layer. B, unfiltered LFPs (single sweeps) recorded in glomeruli adjacent to the EPL recording sites in C. Responses to the entire theta stimulus are shown. C, LFPs (top/black: WT mice; bottom/blue: Cx36 KO mice) recorded in the EPL in the same experiment as B. For each recording, 3 consecutive sweeps are displayed reflecting 175 ms periods following the first burst in the theta stimulus. Displayed data were band‐pass filtered at 10–1000 Hz or 10–100 Hz (overlaid, smoother traces). D, same raw data as in C but filtered at 0.3–1 kHz. E, main panel: power spectra derived from the EPL LFP recordings in C for WT (black) and Cx36 KO (blue) mice. Thicker traces reflect the average spectra from LFPs recorded during 175 ms epochs after each of four stimulus bursts; thinner traces reflect analysis of a 175 ms control period just preceding the first stimulus burst. Inset: mean integrated beta/gamma (23–57 Hz) power measured following each of four stimulus bursts in the theta stimulus for all experiments (WT, n = 36; Cx36 KO, n = 42). F, average power spectra (±SEM) derived from EPL LFP recordings in which the simultaneously recorded glomerular LFP was ≥0.3 mV (WT, n = 16; Cx36 KO, n = 15). The grey trace reflects subtraction of the KO trace (blue) from the WT trace (black). G, integrated power (23–57 Hz) in the EPL LFP plotted against the glomerular LFP recorded in the same experiment. Lines reflect fits to linear regression of the WT (slope = 0.095) and Cx36KO (slope = 0.037) data. Data values (WT, n = 36; Cx36 KO, n = 42) reflect means of 175 ms epochs following each of the 4 stimulus bursts.

Figure 5. Cx36 KO reduces synchrony of IPSCs in pairs of MCs affiliated with different glomeruli

A, analysis of IPSCs evoked by theta frequency stimulation of OSNs in a pair of MCs from WT mice. Illustrated are 175 ms periods of sample current traces (left; V _hold = –57 mV; grey and black reflect the two MCs), examples of IPSCs that appeared to be synchronized (arrows at left; enlarged in middle), and a histogram reflecting the time lags between IPSCs in the same two MCs (right). Overlaying the histogram is a fit with a four‐parameter Gaussian function that yielded a standard deviation (SD) value of 1.0 ms. B, histogram as in A but for a different MC pair recording. For this histogram, the baseline used for the fitted Gaussian (SD = 1.0 ms) was determined from troughs adjacent to the peak. C, analysis of IPSCs in a pair of MCs from Cx36 KO mice. Illustrated are sample traces (left), an image of the dye‐filled MCs (middle; Alexa‐488, 100 μm), and a histogram of IPSC time lags (right). In the image, the glomeruli to which the MCs sent their apical dendrites are demarcated. Scale bar = 50 μm. Horizontal line in histogram reflects mean of all count values. D, standard deviation (SD) values derived from Gaussian fits of IPSC time‐lag distributions plotted as a function of the lag value at which the peak was observed. Data reflect 6 MC pairs from WT mice with the largest peaks (s/n _IPSC >2.5); each pair produced two data points (same symbols) reflecting the fact that distributions were determined using each MC in the pair as the reference MC. The SD values and the absolute values of the peak position for each pair were similar but not identical. E, IPSC synchronization index (S _IPSC,MC) plotted as a function of IPSC frequency for WT (left; 12 MC pair recordings) and Cx36 KO (right; 9 MC pair recordings) mice. Each MC pair recording had two associated S _IPSC,MC values. This reflected the fact that the analysis was run twice, using each MC as the reference cell. The two largest S _IPSC,MC values are from the same MC pair; one of the values corresponds to the histogram in B. E, box‐plots summarizing IPSC synchronization indices (S _IPSC,pair) for MC pairs from WT and Cx36 KO mice. S _IPSC,pair was the mean of the two S _IPSC,MC values for each pair. ^* P = 0.013, Mann–Whitney test. G, values for the signal‐to‐noise ratio, s/n _IPSC,MC, calculated by dividing the peak in each IPSC time‐lag distribution to the standard deviation of the integrated counts in off‐peak bins. Data reflect same experiments as E. H, box plots summarizing signal‐to‐noise ratios, s/n _IPSC,pair, for each pair (mean of the two s/n _IPSC,MC values). ^* P < 0.01, Mann–Whitney test.

Figure 6. MC IPSCs in WT and Cx36 KO generally have similar frequency and amplitude properties

A, example recordings of spontaneous IPSCs (sIPSCs) in MCs. Illustrated are sample traces consecutively recorded from WT (top, left) and Cx36 KO (bottom, left) mice, along with cumulative amplitude (top, right; ≥227 IPSC events) and instantaneous frequency plots (bottom, right). In the plots, WT and KO curves are overlaid. B, summary histograms of sIPSC amplitude and frequency. Data reflect means ± SEM from 20 MCs in WT, 16 MCs in KO. C, summary of frequency measurements for IPSCs evoked by OSN stimulation, plotted as a function of the glomerular LFP that was simultaneously recorded. The plot has more data points than number of MC recordings (16 MCs for WT, 16 MCs for Cx36 KO), reflecting the fact that, for each recording, multiple OSN stimulation intensities were often used in order to sample different levels of network activity. Data were fitted with lines to estimate Pearson's correlation coefficients (0.44 for WT, 0.70 for KO). D, summary of evoked IPSC amplitude measurements for the same recordings as C. Note that the IPSC amplitudes were larger in WT when the glomerular LFP was larger (>0.2 mV, vertical dashed line). We attribute WT's larger IPSCs under these conditions to summating, synchronous events (see text).

Figure 7. Synchronized IPSCs in non‐sister MCs do not reflect divergent connections from single GCs

A–C, divergent GC‐to‐MC connections (diagram in A) were tested by recording from two MCs in the presence of glutamate receptor antagonists (NBQX and dl‐AP5) in rat olfactory bulb slices. A high‐K⁺ (23 mm) solution drove an increase in IPSC frequency in a MC (B) and spikes in a GC (current‐clamp recording in C), indicating effective stimulation. Delays in B and C were due to the fact that K⁺ was bath applied. D, analysis of K⁺‐evoked IPSCs (at V _hold = –52 mV) in a pair of MCs (same as in B). Illustrated are sample traces (left), an image of the dye‐filled MCs (middle; Alexa‐488, 100 μm), and histogram of IPSC time lags (right). Scale bar = 50 μm. E, summary plot of synchronization indices for K⁺‐evoked IPSCs as a function of IPSC frequency (n = 18 MCs from 9 pairs). The low level of IPSC coupling in these experiments is consistent with a lack of divergent GC‐to‐MC connections. Circles and squares reflect IPSC recordings conducted, respectively, at depolarized (≥–62 mV; outward currents) or hyperpolarized (V _hold = –107 mV; inward currents) holding potentials. F, left, summary plot of synchronization indices as a function of IPSC frequency for IPSCs evoked by theta frequency stimulation of OSNs in rat bulb slices (n = 28 MCs from 14 pairs; same raw data as in Schoppa, 2006a). All recordings were conducted at hyperpolarized holding potentials (V _hold ≤ –107 mV). F, right, example IPSC time‐lag distribution that contributed to the summary plot. Overlaid is a fitted Gaussian with SD = 0.70 ms.

Figure 8. Synchronized EPSCs in GCs do not reflect divergent connections from single MCs

A–C, divergent MC‐to‐GC connections (diagram in A) were tested by recording from two GCs in the presence of a GABA_A receptor blocker (gabazine). Puff application of K⁺ (1 m, 200–450 μm away from the test cells) resulted in a transient increase in the frequency of EPSCs in a GC (B) and action potentials (APs) in a MC (C). EPSC/AP plots reflect mean (±SEM) frequency values over multiple puffs (41 for MC, 6 for GC) that were normalized to the peak values observed with each puff. D, analysis of K⁺‐evoked EPSCs (at V _hold = –82 mV) in a pair of GCs. Illustrated are sample traces (left) and a histogram of EPSC time lags (right). E, summary plot of synchronizations indices (S _EPSC,GC) for K⁺‐evoked EPSCs in GCs as a function of EPSC frequency. Data reflect 5 GC pairs in which K⁺ was puff applied (squares) and 2 pairs in which K⁺ (18–23 mm) was bath applied (diamonds). F, left, summary plot of EPSC synchronization indices as a function of EPSC frequency for EPSCs evoked by theta frequency stimulation of OSNs in rat bulb slices (n = 22 GCs from 11 pairs; same raw data as in Schoppa, 2006b). F, right, example EPSC time‐lag distribution that contributed to the summary plot.

Figure 9. Population‐level mechanism can produce precise synchrony in MC–GC network

A, dual patch‐clamp recordings from unconnected MC–GC pairs were made to test whether a population‐level mechanism could produce precise synchrony. B, sample traces of MC IPSCs (inward currents at V _hold = –107 mV) and GC voltage recorded simultaneously. The IPSC late in the MC trace synchronized to the GC spike reflected GABA release from a GC synchronized to the test GC rather than the test GC itself. C, histogram of time lags between GC spikes and MC IPSCs for the experiment in B. Overlaid is a fitted Gaussian with SD = 1.2 ms. Note that the peak of the histogram is at ∼–0.5 ms rather than at 1–2 ms, as would be expected if the MC IPSCs reflected GABA release from the test GC.

Figure 10. LFP oscillations in slices with and without olfactory cortex

A, traces of LFPs recorded in the EPL during theta frequency OSN stimulation in rat bulb slices with (top) and without (bottom) olfactory cortex. For each recording, 3 consecutive sweeps are displayed reflecting 175 ms periods following the first burst in the theta stimulus. Displayed data were band‐pass filtered at 10–1000 Hz or 10–100 Hz (overlaid, smoother traces). B, unfiltered LFPs in the glomerular layer (single sweeps) recorded in the same experiments as in A, from slices with (left) and without (right) olfactory cortex. Responses to the entire theta stimulus (four stimulus bursts) are shown. C, power spectra derived from the EPL LFP recordings in A from slices with (left) and without (right) olfactory cortex. Traces reflect spectra from LFPs recorded during 175 ms periods after each of the four stimulus bursts. D, integrated power (30–55 Hz) in the EPL LFP plotted against the magnitude of the glomerular layer LFP recorded in the same experiment. Data from slices with (black symbols) and without (grey symbols) olfactory cortex are superimposed (4 recordings each).