Synchronous Infra-Slow Bursting in the Mouse Accessory Olfactory Bulb Emerge from Interplay between Intrinsic Neuronal Dynamics and Network Connectivity

Abstract

Rhythmic neuronal activity of multiple frequency bands has been described in many brain areas and attributed to numerous brain functions. Among these, little is known about the mechanism and role of infra-slow oscillations, which have been demonstrated recently in the mouse accessory olfactory bulb (AOB). Along with prolonged responses to stimuli and distinct network connectivity, they inexplicably affect the AOB processing of social relevant stimuli. Here, we show that assemblies of AOB mitral cells are synchronized by lateral interactions through chemical and electrical synapses. Using a network model, we demonstrate that the synchronous oscillations in these assemblies emerge from interplay between intrinsic membrane properties and network connectivity. As a consequence, the AOB network topology, in which each mitral cell receives input from multiple glomeruli, enables integration of chemosensory stimuli over extended time scales by interglomerular synchrony of infra-slow bursting. These results provide a possible functional significance for the distinct AOB physiology and topology. Beyond the AOB, this study presents a general model for synchronous infra-slow bursting in neuronal networks.SIGNIFICANCE STATEMENT Infra-slow rhythmic neuronal activity with a very long (>10 s) duration has been described in many brain areas, but little is known about the role of this activity and the mechanisms that produce it. Here, we combine experimental and computational methods to show that synchronous infra-slow bursting activity in mitral cells of the mouse accessory olfactory bulb (AOB) emerges from interplay between intracellular dynamics and network connectivity. In this novel mechanism, slow intracellular Na⁺ dynamics endow AOB mitral cells with a weak tendency to burst, which is further enhanced and stabilized by chemical and electrical synapses between them. Combined with the unique topology of the AOB network, infra-slow bursting enables integration and binding of multiple chemosensory stimuli over a prolonged time scale.

Keywords: AOB; calcium imaging; infra-slow bursting; mouse; network model; sensory integration.

Figure 1.

AOB mitral cells exhibit infra-slow bursting. A, Voltage recording from an AOB mitral cell showing highly rhythmic bursting. B, Smoothed time histogram (2 s bins) of the firing shown in A. C, Autocorrelation function of the histogram shown in B demonstrating the method of RI extraction (red) based on the envelope (blue, Hilbert transform power function) of the autocorrelation function. D–F, Similar to A–C but applied for a recording from a less rhythmic mitral cell.

Figure 2.

Synchronous rhythmic bursting in mitral cell assemblies is revealed by two-photon imaging. A, Image of AOB slice incubated with OGB-1 AM showing the area mapped in E (red rectangle). White arrows denote tissue orientation (A, anterior; P, posterior; D, dorsal; and V, ventral). B, Fluorescence intensity of two example cells from A shown as a waveform (top) and raster plot in which color intensity denotes fluorescence intensity (bottom). C, Cross-correlation function based on the signals of the two cells shown in B. D, Distribution of RIs in all observed cells from 21 slices (blue bars) and distribution of RIs in a simulated population of random signals (red line). E, Distribution of period duration in all rhythmic cells (n = 304). F, Map of the detected mitral cells in the slice shown in A in which synchronous cells are similarly colored. Noncolored cells are not synchronous and may be rhythmic, not rhythmic, or not active. G, Calcium indicator fluorescence displayed in raster plot (as in B) for all the cells marked in F clustered to synchronous assemblies and ordered by relative phase within each assembly. H, Average fluorescence in each assembly calculated after eliminating phase differences between cells. The period durations of two rhythmic assemblies are presented above their traces. I, Histogram of the probability of rhythmic cells to belong to a synchronous assembly as calculated in 500 resampled populations (blue bars) and the fitted normal distribution (red line). The arrow indicates the value calculated based on experimental results.

Figure 3.

Both chemical and electrical synapses mediate synchrony and support rhythmicity in mitral cell assemblies. A, Map of assemblies of synchronous cells (top), calcium indicator fluorescence of the cells in these assemblies (middle), and the average fluorescence of the cells in each assembly (bottom traces) in a slice incubated with blockers of chemical synaptic transmission. B, Effect of synaptic blockers on the synchrony index (log scale, top) and the average period duration (bottom) in multiple AOB slices (n = 21 control, n = 13 blockers). C, Spontaneous spikelets recorded intracellularly from a mitral cell (left) and their average waveform (right). Note the biphasic appearance of the waveform. D, Voltage-clamp recordings from three mitral cells (denoted by red, green, and blue) before, during, and after optogenetic stimulation of the entire slice (red bar) in the presence of chemical synaptic blockers (DC changes and resulting artifacts are removed). E, Correlation matrix of the fluorescence signal of the cells from the assemblies marked in A before (left) and after (right) CBX application. F, Normalized slice synchrony index (left), mean RI (middle), and mean signal SD (right) in five slices from four different animals before and after CBX application. Filled circles represent the slice shown in E.

Figure 4.

Infra-slow bursting activity is predicted by an AOB mitral cell model and enhanced by feedback. A, Top, Bursting activity is reproduced in the mitral cell model using noise-free model and a carefully adjusted stimulus (red bar). Middle, Bursting in the same cell is markedly reduced by injecting current white noise. Bottom, Bursting is also reduced when stimulus duration was increased by 1 s. B, RI of the firing of a single cell (with 10 random morphology variations) stimulated by a transient stimulus with varying duration (x-axis) in the presence of current Gaussian noise with varying SD (y-axis). Arrow and arrowhead mark examples of a cell showing no rhythmicity and a cell showing rhythmicity in certain conditions, respectively. C, Diagram of the minimal abstract model containing HH-style spiking mechanism, Ca²⁺ conductance, Ca²⁺-dependent conductance (I_CAN), and Na⁺-dependent outward current (I_pump). An optional “synaptic” feedback mechanism is outlined in red. D, Membrane potential resulting from running the minimal model without feedback (blue) and with a unitary gain feedback (red). E, Results of running the minimal model without feedback (blue) and with a unitary gain feedback (red) shown in phase space projection of the membrane potential (V_m), the Na⁺ concentration ([Na⁺]_i), and the inactivation gating variable (n). Arrows mark the quiescence and firing epochs. F, Critical [Na⁺]_i resulting in bifurcation that initiates and terminates each burst as a function of the feedback gain. G, Mean voltage during bursts and the interburst voltage as a function of the feedback gain. H, Map of the bursting properties as a function of the feedback gain (x-axis) and the bias current (y-axis) showing the occurrence and frequency of bursting. As apparent, introducing feedback increases the range of bias currents that result in bursting (cf. I and II).

Figure 5.

Robust, synchronous, infra-slow bursting activity is predicted to emerge at the network level. A, Schematic illustration of the AOB network showing the afferent fibers from the VNO (green), mitral cells (cyan, blue, purple), and inhibitory interneurons (orange). Magnification of the putative intraglomerulus synaptic connectivity used in the network simulation is shown in the inset, demonstrating direct synaptic excitation, indirect synaptic inhibition, and electrical coupling. B, Examples of simulating the glomeruli of six cells (left) and 20 cells (right), both with random morphological variation and white noise current injection. The blue traces show the voltage responses of four representative cells to a 4 s stimulus. Population firing time histogram during the period denoted by black box (purple) and autocorrelation function of the time histogram (green) both demonstrate stronger rhythmicity in the 20 cells glomerulus. C, Blue, Raster plot showing the firing of 20 unconnected morphologically distinct model cells without noise as a response to a stimulus (gray bar). Red, Response of the same 20 cells when connected by glomerular interactions. D, RI, calculated from the population firing, as a function of the number of cells showing monotonic increase. An exponential curve (red line) was fitted to the data. E, Same as in C but for the experimental observation in AOB slices showing the maximal RI within each assembly as a function of observed assembly size. F, RI values of the firing of a randomly chosen cell from a 30-cell glomerulus stimulated with a transient stimulus with varying duration (x-axis) in the presence of current Gaussian noise with varying SD (y-axis). Each of the 10 surfaces shows the results of simulating a glomerulus comprising a different set of 30 cells with random morphological variations. Note the difference from the similar analysis of 10 unconnected cells shown in Figure 4B.

Figure 6.

Model glomerulus predicting multiple experimental observations. A, Simulating an afferent stimulus in a 20-cell glomerulus showing membrane potential of a representative cell (top) and its firing histogram (bottom). Synchronous rhythmic bursting was induced by a first stimulus (data not shown), whereas the second stimulus (gray line) was given during synchronous bursting, showing the resulting phase delay and reduction in intraburst firing frequency. B, “I,” Fluorescence of four cells that form one assembly (top) and another two cells that form a second assembly in the same slice (bottom). Local electrical stimulation (gray bar) evoked an immediate response followed by a marked delay, as indicated by the dotted line that shows sinusoidal functions that approximately follow the fluorescence before the stimulation and predicts the expected activity without stimulation. “II,” Fluorescence of a different cell that shows a marked reduction in the amplitude of the rhythmic activity after the stimulation (gray bar). C, Current in a simulated mitral cell belonging to a 35-cell glomerulus clamped to −70 mV in the absence of chemical synaptic transmission showing rhythmic episodes of inward current (top) composed of summation of unitary events (bottom). D, Current recorded experimentally in a mitral cell after blocking synaptic transmission by substitution of extracellular Ca²⁺ with Mg²⁺ showing similar results in terms of both the rhythmic episodes and the unitary events. E, Whole-cell recording of an AOB mitral cell (black) during injection of hyperpolarizing current steps (red). F, Simulated injection of hyperpolarizing DC current to a member cell from a 20-cell glomerulus. In the injected cell (top), prevention of action potentials by hyperpolarization revealed rhythmic subthreshold events of which the period duration increased with further hyperpolarization. The similar change in activity in another cell from the same glomerulus (bottom) shows that this effect is a network property. G, Period duration of synchronous bursting in a model 20-cell glomerulus as a function of the DC current injected to a single cell, when 0.17 nS (blue) or 0.05 nS (orange) were used as gap junction conductance.

Figure 7.

Inhibitory interactions determine the size of assemblies and the extent of rhythmicity and restrict interglomerular burst propagation. A, Map of an AOB slice in control conditions showing seven assemblies (color coded) of correlated activity. B, Map of the same slice after gabazine application showing global synchrony. C, Top, Raster plot of the fluorescence of cells from the slice shown in A and B before and during gabazine application (red bar). Note the emergent of global synchronous rhythmicity. Bottom, Example of the fluorescence recorded from a single cell bursting under control conditions demonstrating an increase in amplitude and interburst interval in the presence of gabazine. D–G, Wide-field imaging of an AOB slice in which GCaMP6 is expressed in mitral cells in the presence of gabazine. D, Simultaneous recording of electrical activity (black trace) and fluorescence changes in a two ROIs marked in E with corresponding colors. APV (blue bar) and DNQX (green bar) were added sequentially. E, Magnification of a single event marked in D, showing the temporal relationship among the signals. F, Photomicrograph of the imaged area, showing the locations of the recording pipette (black) and the ROIs (red and green squares). mcl, Mitral cell layer; gl, glomerular layer; P, posterior; A, anterior). G, Time-lapse imaging of the propagation of the burst of activity shown in E. H, Reproducing the blockers' effects in a network of five glomeruli of different sizes, in which pairs of “adjacent” glomeruli share mitral cells. Electrical activity of representative cells from the three glomeruli is shown in matching colors. The blue glomerulus was stimulated (blue bar) to initiate synchronous bursting activity that spread to adjacent glomeruli upon blockade of synaptic inhibition (cyan bar). After blockade of synaptic excitation (green bar), modified synchronous bursting activity continues in some of the glomeruli.

Figure 8.

Interglomerular interactions enable integration of inputs over extended time scales. A, Network topology used in the simulation, containing four glomeruli of 15, 13, 13, and 12 member cells. Each pair form an assembly via one shared cell that project dendrites to both glomeruli. The lateral excitation and inhibition weights are slightly different in each assembly. B, Raster plot showing the firing of the cells from assembly I (left) and assembly II (right) color coded to match the glomeruli. Times of stimulation of each glomerulus are denoted by vertical arrows. C, Population firing time histogram for each glomerulus in the original topology (top, solid lines) and in the absence of shared cells (bottom, dotted lines). D, Correlation matrix of the entire population, ordered by glomeruli, in the original topology (left) and in the absence of shared cells (right). Note that correlated activity between the glomeruli of each assembly occurs only when shared cells are present and it is independent of the time of stimulation.