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J Neurophysiol 92: 743-753, 2004; doi:10.1152/jn.00016.2004
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Phasic Stimuli Evoke Precisely Timed Spikes in Intermittently Discharging Mitral Cells

Ramani Balu, Phillip Larimer and Ben W. Strowbridge

Department of Neurosciences, Case Western Reserve University, Cleveland, Ohio 44106

Submitted 6 January 2004; accepted in final form 17 February 2004


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
Mitral cells, the principal cells of the olfactory bulb, respond to sensory stimulation with precisely timed patterns of action potentials. By contrast, the same neurons generate intermittent spike clusters with variable timing in response to simple step depolarizations. We made whole cell recordings from mitral cells in rat olfactory bulb slices to examine the mechanisms by which normal sensory stimuli could generate precisely timed spike clusters. We found that individual mitral cells fired clusters of action potentials at 20-40 Hz, interspersed with periods of subthreshold membrane potential oscillations in response to depolarizing current steps. TTX (1 µM) blocked a sustained depolarizing current and fast subthreshold oscillations in mitral cells. Phasic stimuli that mimic trains of slow excitatory postsynaptic potentials (EPSPs) that occur during sniffing evoked precisely timed spike clusters in repeated trials. The amplitude of the first simulated EPSP in a train gated the generation of spikes on subsequent EPSPs. 4-aminopyridine (4-AP)–sensitive K+ channels are critical to the generation of spike clusters and reproducible spike timing in response to phasic stimuli. Based on these results, we propose that spike clustering is a process that depends on the interaction between a 4-AP–sensitive K+ current and a subthreshold TTX-sensitive Na+ current; interactions between these currents may allow mitral cells to respond selectively to stimuli in the theta frequency range. These intrinsic properties of mitral cells may be important for precisely timing spikes evoked by phasic stimuli that occur in response to odor presentation in vivo.


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
Olfactory information is encoded through spatio-temporal patterns of activity in mitral cells located in the olfactory bulb (Fig. 1A). Intracellular recordings from salamander olfactory bulb in vivo have shown that individual mitral cells fire clusters of action potentials interspersed with periods of inhibition in response to sensory stimulation (Hamilton and Kauer 1985Go, 1989Go). Such temporal patterning of spikes has also been shown for projection neurons (analogous to vertebrate mitral cells) of the insect antennal lobe (Laurent 1996Go; Laurent et al. 1996Go; Wehr and Laurent 1996Go). In this system, individual projection neurons were found to fire unique temporal sequences of spikes in response to different odorants. Spike patterns were repeatable across trials of repeated odor presentation and were precisely phase-locked to the odorant evoked local field potential. In response to sensory stimulation, mammalian mitral cells generate spike clusters that are phase-locked to the inspiratory rhythm (Cang and Isaacson 2003Go; Macrides and Chorover 1972Go; Margrie and Schaefer 2003Go; Sobel and Tank 1993Go). Spike timing is especially precise in repeated odorant applications that generate clusters with the same number of spikes (Margrie and Schaefer 2003Go). Thus temporal coding of mitral cell spike times may be a critical aspect of the neuronal encoding of odorants.



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FIG. 1. Intermittent firing and subthreshold oscillations in olfactory bulb mitral cells. A: schematic cartoon of olfactory bulb circuitry showing relative position of mitral cells and patch pipette. B: responses to graded step depolarizations (180-360 pA, 4-s duration). Mitral cells fire intermittent clusters of action potentials in response to each step with intervening periods of subthreshold membrane potential oscillations. Responses recorded in NBQX (5 µM) and D-APV (25 µM); resting membrane potential (RMP) = –69 mV. C: plots of relationship between current step amplitude and within cluster firing frequency (left), number of spikes per cluster (middle), and mean pause duration (right). Data points represent mean ± SD of ≥3 trials. D: plot of the effect of TTX (1 µM) on the steady-state depolarization reached during a 200-pA current step (3-s duration). Example traces shown above in control conditions (left) and after exposure to TTX for 2.3 and 3.5 min (right). Arrow marks point during current step where steady-state voltage was measured. Action potentials clipped in example traces. Note that TTX reduces both the depolarizing extent of the step response and amplitude of subthreshold oscillations normally present near firing threshold. E: enlargements of steady-state responses in control, after 2.3- and 3.5-min exposure to TTX, and during washout of TTX.

 
Relatively little is known about the mechanisms that enable mitral cells to respond to synaptic stimulation with precisely timed patterns of action potentials that are unique for different odorants. One possibility is that interactions between mitral cells and local inhibitory interneurons within the olfactory bulb might sculpt the incoming spatial pattern of mitral cell activation and produce an evolving spatio-temporal olfactory code. Reciprocal dendrodendritic synapses between mitral cells and granule cells can produce feedback inhibition onto activated mitral cells (Isaacson and Strowbridge 1998Go; Jahr and Nicoll 1980Go, 1982Go) and laterally inhibit neighboring mitral cells (Isaacson and Strowbridge 1998Go; Yokoi et al. 1995Go). Recurrent dendrodendritic inhibition also can modulate the pattern of mitral cell activity evoked by phasic stimuli (Halabisky and Strowbridge 2003Go). In addition, extrasynaptic N-methyl-D-aspartate (NMDA) autoreceptors on mitral cell dendrites (Aroniadou-Anderjaska et al. 1999Go; Friedman and Strowbridge 2000Go; Isaacson 1999Go) may provide feedback excitation during spiking. The interaction of these inhibitory and excitatory mechanisms could modulate the pattern of spikes in single mitral cells to produce temporal codes for odors.

In addition to synaptic mechanisms, mitral cells may possess intrinsic membrane properties that sculpt and pattern their responses evoked by olfactory sensory neuron activation. Previous work has shown that mitral cells fire clusters of spikes interspersed with periods of fast gamma-frequency subthreshold oscillations in response to DC current injection (Desmaisons et al. 1999Go). Spike clustering is most likely due to intrinsic membrane properties of mitral cells, since it persisted in the presence of ionotropic glutamate and GABA receptor blockers. This intrinsic behavior is strikingly similar to spike clustering in response to DC current injection seen in neurons of other brain areas, including stellate cells of the medial entorhinal cortex (Alonso and Klink 1993Go; Alonso and Llinas 1989Go; Klink and Alonso 1993Go) and inhibitory interneurons of the basal forebrain (Alonso et al. 1996Go; Wang 2002Go). This behavior has been proposed to be critical for allowing these cells to serve as pacemakers for the theta rhythm.

Using whole cell recordings, we found that mitral cells generated intermittent, irregularly timed spike clusters at slow theta frequencies (1-5 Hz). In contrast, phasic current stimuli—mimicking the trains of slow excitatory postsynaptic potentials (EPSPs) that occur during sniffing—evoked precisely timed spike clusters. Both spike clustering during step depolarizations and precise timing evoked by phasic stimuli are likely due to the interplay of a 4-aminopyridine (4-AP)–sensitive potassium current and a subthreshold inward current. The ability of mitral cells to fire precisely timed spikes in response to phasic stimuli suggests that their intrinsic membrane properties may allow them to act as filters—converting incoming olfactory sensory neuron activity into precise temporal patterns of spikes that are relayed to higher brain centers.


    METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
Horizontal slices (300 µm) through the olfactory bulb were prepared from anesthetized (ketamine, 140 mg/kg ip) P14–P25 Sprague-Dawley rats using a modified Leica (Nussloch, Germany) VT1000S vibrotome, as described previously (Halabisky et al. 2000; Isaacson and Strowbridge 1998Go). Olfactory bulb slices were incubated at 30°C for 25 min and maintained submerged at room temperature until needed. Whole cell patch-clamp recordings were made in mitral cells visualized under infrared-differential interference contrast optics (Zeiss Axioskop 1 FS) using an Axopatch 1D amplifier (Axon Instruments). During recordings, olfactory bulb slices were superfused with artificial cerebrospinal fluid (ACSF) that contained (in mM) 124 NaCl, 3 KCl, 1.23 NaH2PO4, 26 NaHCO3, 10 dextrose, 2.5 CaCl2, and 1.2 MgSO4, equilibrated with 95% O2-5% CO2 and warmed to 30°C (flow rate, 1-2 ml/min). A modified ACSF solution was employed when making slices and in the holding chamber that contained reduced CaCl2 (1 mM) and elevated MgSO4 (3 mM). Patch electrodes used for current-clamp recordings (3-5 M{Omega} resistance) contained (in mM) 140 K-methylsulfate, 8 NaCl, 10 HEPES, 0.2 EGTA, 4 MgATP, 0.3 Na3GTP, and 10 phosphocreatine. All recording were obtained in the presence of 1,2,3,4-tetrahydro-6-nitro-2,3-dioxo-benzo[f]quinoxaline-7-sulfonamide disodium (NBQX, 5 µM) and D-APV (25 µM) in the bath solution to block ionotropic glutamate receptors.

Voltage records were low-pass filtered at 2 kHz and digitized at 5 kHz using a 16-bit A/D converter (ITC-18, Instrutech). In some experiments, a current injection waveform consisting of a train of two to eight temporally overlapping EPSP-like waveforms was injected into mitral cells. Each simulated EPSP in the train was generated using a single alpha function with a decay time constant of 50-100 ms. This stimulus train was modeled after respiration-evoked calcium and voltage oscillations recorded from mitral cell glomerular tufts in vivo (Charpak et al. 2001Go). In these in vivo experiments, oscillations at the beginning of odor application tended to be larger than those occurring later. For this reason, in many of our experiments, we used simulated EPSP trains where the last three EPSPs were gradually reduced in amplitude (see Fig. 5A).



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FIG. 5. Precise spike timing in mitral cells activated by phasic stimuli. A: alternating responses to either a step depolarization (left) or a train of 6 simulated excitatory postsynaptic potentials (sEPSPs) at 2.5 Hz (middle). Right: expansion of responses to 2nd sEPSP. Variability in 1st spike latency was reduced with phasic stimuli to 1.18 ms compared with 258 ms in responses to step depolarizations in this cell. Note the reduction in action potential threshold by the 1st sEPSP. RMP = –66 mV. B: responses to trains of 4 uniform sEPSPs at different frequencies. Repeated sEPSP stimuli at >1 Hz evoked firing in mitral cells, which increased with increasing sEPSP frequency. Note the absence of spikes triggered by the 1st sEPSP in all examples responses. RMP = –65 mV; action potentials clipped. C: summary plot of relationship between sEPSP frequency and total number of spikes evoked by the 4-sEPSP train (data from 5 mitral cells).

 
Electrophysiological data were recorded and analyzed using custom software written in Visual Basic 6 (Microsoft) and Origin 7 (OriginLab). Spike latencies were determined using a threshold crossing (0 mV) algorithm implemented in Origin and confirmed by visual inspection in most cells. Variability in spike timing across trials was measured by calculating the standard deviation (SD) of the first spike latency from repeated current stimulus presentations (10-30 trials). Spike timing variability is generally assayed either by measuring the regularity or the reproducibility of spiking at particular times across repeated trials. Regularity can be measured either by the CV of the interspike interval distribution or the ratio of the variance of spike count to the mean spike count in a fixed time interval (the Fano Factor) (Dayan and Abbott 2001Go). Because mitral cell firing is intrinsically intermittent, these measures were not well suited for our analyses of spike timing. Reproducibility of spike timing has been studied previously both in vitro (Harsch and Robinson 2000Go; Mainen and Sejnowski 1995Go; Nowak et al. 1997Go) and in vivo (Reinagel and Reid 2002Go) by measuring the precision (SD of spike times) for spikes that occur within repeatable spike events. Repeatable spike events often are defined by analyzing the peristimulus time histogram (PSTH) and identifying peaks in the PSTH that exceed a defined threshold value (e.g., 3 times the mean spike rate). These methods also are less suited to analyze spike timing in mitral cells that generate clusters of near-regular firing intermittently. To separate inter-cluster and within-cluster sources of variability, we choose to focus on the variability (SD) of the latency to the first spike cluster.

Membrane potentials indicated are not corrected for the liquid junction potential. All chemicals were obtained from Sigma (St. Louis, MO) except for TTX (Calbiochem). Data are shown as the means ± SE. Statistical significance was determined using paired t-tests except where noted.


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
Mitral cells generate clusters of action potentials intermittently in response to stepwise depolarizing current injections. Intermittent firing was maintained across a large (2-fold) variation in current step amplitude (Fig. 1B). These pauses did not reflect recurrent synaptic interactions since ionotropic glutamate receptor blockers (5 µM NBQX and 25 µM D-APV) were included in these and subsequent experiments. While the number of spikes per cluster and intra-cluster firing frequency increased with current step amplitude, altering the depolarizing stimulus intensity had little effect on the mean pause duration (Fig. 1C). This characteristic clustered spiking pattern was observed at a range of resting membrane potentials (from –75 to –55 mV, data not shown); in these voltage ranges, there was almost no discernible effect of resting potential on spike patterning. We were able to induce tonic firing with current steps only by holding mitral cells very near spike threshold, where subthreshold oscillations were prominent. Intermittent firing has been reported previously in mitral cells (Chen and Shepherd 1997Go; Desmaisons et al. 1999Go; Friedman and Strowbridge 2000Go) and other cell types (Alonso and Klink 1993Go; Alonso and Llinas 1989Go; Bracci et al. 2003Go; Gutfreund et al. 1995Go; Llinas et al. 1991Go; Pedroarena and Llinas 1997Go); however, the mechanism underlying this behavior is unclear.

Mitral cells also generate prominent subthreshold membrane potential oscillations near firing threshold (Fig. 1, D and E). Large subthreshold oscillations are often correlated with intermittent firing in a variety of neurons (mitral cells: Desmaisons et al. 1999Go; entorhinal neurons: Klink and Alonso 1993Go; thalamocortical projection neurons: Pedroarena and Llinas 1997Go). Computational models of subthreshold oscillations suggest they are mediated by opposing low-threshold inward and outward currents (Wang 1993Go, 2002Go). We first sought to test whether mitral cells generate a sustained Na+ current and whether this current is involved in subthreshold oscillations. We found that bath application of TTX (1 µM) reversibly reduced the steady-state depolarization produced by step current injection by 5.5 ± 0.7 mV (Fig. 1D; n = 5 cells). This effect could be due to blocking either persistent Na+ currents or subthreshold inactivating Na+ currents. TTX also blocked subthreshold oscillations (Fig. 1E; membrane potential variance decreased from 0.57 ± 0.1 mV2 at –41.1 mV to 0.021 ± 0.0004 mV2 at –46.5 mV; P < 0.05), suggesting that these oscillations may result from the interaction between K+ currents and subthreshold Na+ currents. Since TTX also blocks action potentials, it is difficult to determine directly if these Na+ currents are also necessary for intermittent firing.

The timing of spike clusters was highly variable even when mitral cells were activated by constant current steps (1st spike SD = 169 ± 32 ms; n = 11 mitral cells; Fig. 2A). The distribution of interspike intervals shows two distinct peaks: one at <100 ms that reflects intervals within spike clusters and one centered at 470 ms that represents inter-cluster pauses (Fig. 2B; n = 5 cells). Mitral cells typically generated a small afterhyperpolarization (AHP) following each spike cluster. As shown in Fig. 2C, these cluster AHPs decay exponentially with a mean time constant of 202 ± 40 ms (n = 4 cells) and were associated with a transient decrease in input resistance estimated by responses to small hyperpolarizing test pulses (73.9 ± 7.7% of precluster input resistance; n = 3 cells). This decrease in input resistance at the end of a spike discharge suggests that the buildup of an outward current may be responsible for cluster termination and may contribute to low frequency of short inter-cluster pauses (<250 ms).



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FIG. 2. Variability of clustered spike discharge timing in mitral cells. A: variable responses in a single mitral cell to 4 250-pA step depolarizations, repeated every 20 s; RMP = –65 mV. B: histogram of interspike intervals in 5 mitral cells (7,789 interspike intervals). Distribution of pauses between spike clusters (interspike intervals > 100 ms, determined by visual inspection; n = 511) was well fit by a Gaussian function with a mean of 470 ms (R2 = 0.95). Note that the y-axis was clipped to reveal the distribution of long interspike intervals. C: example response to a step depolarization in a different mitral cell (RMP = 68 mV). Expansion on right shows afterhyperpolarization (AHP) that normally follows each cluster of action potentials. Cluster AHPs in this cell could be fit using a single exponential function that decayed with a time constant of 179 ± 49 ms.

 
Spike timing remained highly variable in repeated responses to both small and large amplitude step current injections (Fig. 3A; mean 1st spike latency SD for weak stimuli = 365 ± 48 ms; mean SD for strong stimuli = 273 ± 47 ms; n = 5 cells; not statistically significant). Imprecise firing in mitral cells was not limited to the first spike cluster; the duration of the first pause between spike clusters also was variable (mean SD = 195 ± 27 ms; n = 6 cells) and was not correlated with the latency to the first spike (R = –0.155 ± 0.09; n = 4 cells). Figure 3B shows the superposition of two responses to the same current step in one mitral cell. The initial membrane potential trajectory of both responses was similar despite the 420 ms difference in first spike latencies. We found no correlation between first spike latency and resting membrane potential (R = –0.083 ± 0.092; n = 9 cells) or input resistance (R = –0.10 ± 0.07; n = 9 cells). We tested whether the large variability of first spike latencies reflected differences availability of voltage-dependent channels by evoking depolarizing step responses following hyperpolarizing prepulses, which should "reset" the resting activation state of Na+ and K+ channels. We found no difference in the variability of spike timing with either 500-ms or 1-s duration hyperpolarizing prepulses (Fig. 3, C and D), suggesting that the variability likely reflects properties of voltage-gated channels activated by the depolarizing step.



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FIG. 3. Variability in mitral cell firing patterns does not reflect initial conditions. A: responses to repeated weak (150 pA) and strong (300 pA) depolarizing steps in a mitral cell. Vertical lines on raster plot represent times of individual action potentials during repeated trials. Responses were variable to both weak and strong depolarizing steps. RMP = –69 mV. B: superposition of 2 responses to the same depolarizing current step in 1 mitral cell in which the latency to the 1st action potential varied by 420 ms. C: hyperpolarizing prepulses (either 500-ms or 1-s duration) did not reduce the spike timing variability to subsequent depolarizing steps. RMP = –63 mV. D: summary of effect of hyperpolarizing prepulses on 1st spike latencies (mean and SD). Data from 5 mitral cells.

 
We next attempted to regularize mitral cell firing by resetting ionic currents activated by the step depolarization by introducing brief (25-75 ms) repolarizations back to rest. As shown in Fig. 4A, this protocol eliminated most of the variability in first spike latency (mean SD = 0.50 ± 0.07 ms; n = 5 cells) while responses to step depolarizations remained highly variable. Action potential threshold was reduced by the brief repolarizing steps (see Fig. 4A, inset), suggesting that the brief repolarizations recovered more inactivated Na+ current than K+ current. In addition to controlling to onset of spiking, a brief repolarization often could terminate clusters, although this phenomenon was not as robust (successful in 204 of 300 attempts in 5 cells) as the first repolarization initiating firing, which worked with 100% reliability in nine mitral cells. Figure 4B shows that brief repolarizations can initiate and terminate firing at different times during the step depolarization.



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FIG. 4. Transient repolarizations promote precise phase locking in mitral cells. A: responses to repeated trials of step depolarizations alone (left) or with 4 transient repolarizations (50-ms duration; right). Spikes were triggered reliably following the offset of the repolarizing pulse (1st spike SD = 0.50 ± 0.07 ms) compared with the large variability in 1st spike latency in response to simple step stimuli (SD = 230 ± 34 ms). Both set of records from the same mitral cell; RMP = –68 mV. Periods of tonic firing could be halted by a 2nd transient repolarizing pulse. Inset: expansion of recording during 1st repolarization; dashed line represents steady-state membrane potential achieved before repolarization. Note that the repolarizing step altered action potential threshold (arrow) now occurred 6.1 mV below the previous steady-state level. Calibration bar in inset: 10 mV, 25 ms. B: tonic firing initiated and halted at arbitrary times. Four responses to the same depolarizing step stimuli (280 pA) with repolarizing pulses occurring at different latencies (offset by 50 ms in each trace). RMP = –68 mV.

 
The ability of transient repolarizing steps to evoke precise firing in mitral cells suggests that mitral cells may respond selectively to slow time-modulated or oscillatory stimuli. In the intact animal, mitral cells receive phasic EPSPs in the theta frequency band (2-7 Hz) from upstream olfactory receptor neurons that are coupled to the respiratory rhythm (Cang and Isaacson 2003Go; Charpak et al. 2001Go; Macrides and Chorover 1972Go; Margrie and Schaefer 2003Go). We therefore tested whether phasic EPSP-like stimuli evoke reproducible spiking in control mitral cells. In these experiments, we injected a train of six simulated EPSPs at 1-5 Hz; these stimuli were designed to mimic the natural response of mitral cells during respiration (Charpak et al. 2001Go) and have been used in other in vitro studies (Halabisky and Strowbridge 2003Go). Trials with phasic waveforms were alternated with simple step depolarizations. As shown in Fig. 5A, phasic stimuli generated precise spike timing (1st spike SD = 1.6 ± 0.33 ms; 2.5 Hz; n = 7 cells) compared with the large variability of spike latencies that resulted from the alternating step trials (1st spike SD = 230 ± 34 ms; n = 18 cells). The first simulated EPSP failed to generate action potentials but decreased the apparent action potential threshold for subsequent sEPSPs. The facilitating effect of the first EPSP on later responses was time dependent; increasing the delay between four identical sEPSPs (Fig. 5B) rapidly diminished the total number of spikes evoked by the sEPSP train. This frequency filtering effect (Fig. 5C) was observed in five of five mitral cells and was not simply due to temporal summation since firing was facilitated at relatively low frequencies (1.3 vs. 1 Hz) in which the membrane potential recovered completely between sEPSP cycles. At higher frequencies, firing occurred at threshold membrane potentials more hyperpolarized than reached during the response to the first sEPSP (at 2 and 2.5 Hz). Higher frequency sEPSP trains also were effective in phase-locking mitral cell spikes (1st spike SD = 1.89 ± 0.43 ms at 4 Hz; n = 3 cells; data not shown).

Our results show that mitral cells, which fire intermittently in response to step stimuli, can generate spikes with reproducible timing in response to phasic stimuli repeated at relatively low frequencies. These properties enable mitral cells to act as high-pass filters, responding selectively to stimuli repeated at >1 Hz and ignoring single simulated EPSP (sEPSP) events (unless they are extremely large amplitude). As shown in Fig. 6, the first sEPSP in a train controls spiking in subsequent sEPSPs. In this experiment, we varied the amplitude of either the first (Fig. 6A) or second (Fig. 6B) sEPSP in a two-sEPSP train stimulus; results from these experiments are summarized in Fig. 6C. Interestingly, the first sEPSP controlled spiking in the subsequent sEPSP in an all-or-none manor. In this neuron, no spikes were evoked by either sEPSP if the first sEPSP amplitude was <17 mV. Increasing the amplitude of the first sEPSP enabled spiking on the second sEPSP; increasing the amplitude of the first sEPSP further did not change the frequency or number of spikes evoked by the second sEPSP appreciably (Fig. 6, B and C; n = 3 cells). By contrast, varying the amplitude of the second sEPSP modulated both firing frequency and spike number. Suprathreshold responses also could be gated by short trains of small-amplitude simulated EPSPs (Fig. 6D; n = 4 cells), similar to those recorded in resting mitral cells in vivo (Cang and Isaacson 2003Go; Margrie and Schaefer 2003Go; Spors and Grinvald 2002Go).



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FIG. 6. Different effects of 1st and 2nd sEPSPs. A: effect of varying the 1st sEPSP in a 2-sEPSP train (sEPSP2 = 450 pA). The 1st sEPSP regulated spiking evoked by sEPSP2 in an all-or-none manner. B: varying the 2nd sEPSP in a 2-sEPSP train (sEPSP1 = 450 pA) altered both number and frequency of action potentials evoked by sEPSP2. Responses in A and B from the same mitral cell; RMP = –62 mV. C: plots of relationship between amplitude of sEPSP1 (left) and sEPSP2 (right) and spike frequency (top), and number of action potentials evoked by sEPSP2 (bottom). Each point represents data from 1 trial. D: gating by small-amplitude sEPSP trains. No spikes were evoked by the 1st sEPSP (arrow) in a 4-Hz sEPSP train (left). Preceding this train with a 2nd 4-Hz train composed of small-amplitude sEPSPs (5-6 mV) enabled spiking on 1st sEPSP (middle). No spikes were evoked by the 1st sEPSP (arrow) if the small-amplitude train occurred 500 ms before the 1st sEPSP (right).

 
We next tested whether activation of transient K+ currents facilitated phase-locking in response to repeated phasic stimuli. We found that low concentrations of 4-AP (5 µM) enhanced the response to first sEPSP in a train (Fig. 7A), which was usually subthreshold in mitral cells. In the presence of 5 µM 4-AP, the first sEPSP now triggered multiple spikes with variable latencies (mean 1st spike SD in sEPSP1 = 11.9 ± 3.0 ms; n = 5 cells). Spikes evoked by second sEPSP in 5 µM 4-AP remained precisely timed (1st spike SD = 1.8 ± 0.4 ms; not different from control). Increasing the 4-AP concentration to 100 µM slowed the average firing rate and decreased the temporal precision of spikes evoked by the second sEPSP (SD = 6.6 ± 2.1 ms; different from control, P < 0.05; unpaired t-test; n = 5 cells). These results are summarized in Fig. 7B and suggest that 4-AP–sensitive K+ currents facilitate precise timing in mitral cells driven by phasic stimuli.



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FIG. 7. Disruption of precise spiking by 4-aminopyridine (4-AP). A: responses to repeated trials using a 6-sEPSP train at 2.5 Hz showed phase locking. Low concentrations of 4-AP (5 µM) allowed the 1st sEPSP to trigger spikes that were poorly phase locked; action potentials evoked by sEPSP2 remain time-locked on repeated trials. Higher concentrations of 4-AP (100 µM) disrupted phase locking to both sEPSP1 and sEPSP2. Control and 100 µM 4-AP example responses are from the same mitral cells (RMP = –70 mV), while the example responses in 5 µM 4-AP are from a different cell (RMP = –65 mV). B: summary of variability in 1st spike latencies to sEPSP1 (open bars) and sEPSP2 (closed bars) in control conditions and in 5 and 100 µM 4-AP. Data from 5-7 mitral cells in each condition. *P < 0.05; **P < 0.01.

 
Besides facilitating phase-locking during phasic stimuli, 4-AP–sensitive K+ currents also are required for intermittent firing following step depolarizations. As shown in Fig. 8A, 5 µM 4-AP gradually eliminated pauses between spike clusters, eventually producing tonic firing (n = 8 cells). Intermittent firing could be restored on washout of 4-AP (Fig. 8A, right). As shown in Fig. 8B, 5 µM 4-AP did not eliminate the initial delay before spiking; this delay was reduced by increasing the concentration of 4-AP to 100 µM (from 208 ± 28 ms in 5 µM 4-AP to 31.9 ± 13 ms in 100 µM 4-AP; n = 5 cells). Low concentrations of 4-AP also dramatically decreased the variability in first spike latencies in responses to step depolarizations (1st spike SD = 17.2 ± 3.5 ms in 5 µM 4-AP vs. 169 ± 32 ms in control conditions; n = 4 mitral cells; P < 0.05; Fig. 8C). While 4-AP reduced the first spike latency, this effect did not explain the reduction in SD observed with 4-AP (1st spike latency CVcontrol = 25.5 ± 2.8%; CV4-AP = 8.54 ± 0.74%; P < 0.05). This concentration of 4-AP did not alter the input resistance (Fig. 8D), suggesting that 4-AP did not block K+ channels active at rest. Higher concentrations of 4-AP (100 µM) caused an even greater reduction (3.64 ± 1.3 ms; n = 5 cells) in the SD of first spike latency. The effects of different concentrations of 4-AP on spike timing are summarized in Fig. 8E.



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FIG. 8. 4-AP sensitive K+ currents regulate intermittent discharges in mitral cells. A: responses of a mitral cell to a step depolarization in control conditions and in 5 µM 4-AP (RMP = –65 mV; 260-pA current step; example traces 4 and 5 min after exposure to 4-AP). This concentration of 4-AP reliably converted the intermittent discharge response pattern into tonic firing. B: higher concentrations of 4-AP (100 µM) decreased the initial delay before tonic firing. C: raster display of suprathreshold responses to step depolarizations repeated every 20 s before and after bath application of 5 µM 4-AP. Step amplitude = 200 pA, RMP = –67 mV. D: plot of reduction in 1st spike latency by 5 µM 4-AP. This concentration of 4-AP did not affect resting input resistance as measured by responses to small amplitude hyperpolarizing test pulses applied immediately before the step depolarization (bottom). E: summary plot of the variability in 1st spike latency in control and in different concentrations of 4-AP. Data from 14 mitral cells; each point represents the mean from ≥4 cells.

 

    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
In this study, we used in vitro brain slices to investigate the nature of intermittent firing in mitral cells. We made three principal conclusions from this study. First, the intermittent firing pattern normally recorded in mitral cells activated with depolarizing current steps is highly sensitive to K+ channel blockers specific for slowly inactivating ID-like currents and could be converted into tonic firing by <10 µM 4-AP. Second, the timing of individual spike clusters was highly variable with repeated steps; this variability also was reduced by low concentrations of 4-AP. Finally, when activated by phasic stimuli, mitral cells function as high-pass filters and generate precisely timed spike clusters in response to inputs that mimic the natural 2- to 5-Hz sensory synaptic drive to these neurons in vivo during sniffing.

We found that mitral cells fire clusters of action potentials at 20-40 Hz interspersed with periods of subthreshold membrane potential oscillations at 30-50 Hz. This spike clustering was dependent on intrinsic membrane properties, since it persisted in the presence of blockers of fast synaptic transmission. This finding is consistent with earlier reports on the intrinsic behavior of mitral cells (Chen and Shepherd 1997Go; Desmaisons et al. 1999Go; Friedman and Strowbridge 2000Go). Spike clustering in response to step depolarizing stimuli or tonic depolarization has been observed in neurons from numerous brain areas, including stellate cells of the medial entorhinal cortex (Alonso and Klink 1993Go; Alonso and Llinas 1989Go; Klink and Alonso 1993Go), noncholinergic inhibitory interneurons of the basal forebrain (Alonso et al. 1996Go), striatal fast spiking interneurons (Bracci et al. 2003Go), and layer IV frontal cortex neurons (Gutfreund et al. 1995Go; Llinas et al. 1991Go).

The usefulness of temporal coding as a strategy to represent information in the CNS requires that the timing of individual spikes in single neurons be highly reproducible across repeated identical stimuli. The reproducibility of spiking in response to repeated stimuli has generally been quantified by measuring spike precision (Mainen and Sejnowski 1995Go; Nowak et al. 1997Go). Precision refers to the temporal "jitter" of spiking across multiple trials and is measured as the SD of spike latency. Previous in vitro studies have suggested that regular spiking cortical neurons have very low intrinsic noise and can respond with high precision to the onset of a step current stimulus (Mainen and Sejnowski 1995Go; Nowak et al. 1997Go); noisy stimuli increase the precision of later spikes. In contrast, the intrinsic properties of mitral cells give rise to highly variable, unreliable spiking in response to simple step depolarizations but enable mitral cells to respond reproducibly to phasic stimuli in the theta frequency range.

In many cell types, K+ currents that are sensitive to very low concentrations of 4-AP have relatively slow deactivation and inactivation kinetics and are frequently termed ID-like (Coetzee et al. 1999Go; Fadool and Levitan 1998Go; Mitterdorfer and Bean 2002Go; Saviane et al. 2003; Storm 1988Go; Wu and Barish 1992Go). While the subunit composition of ID has not been established, this current may reflect heteromultimers containing Kv1-family subunits (Coetzee et al. 1999Go). Kv1.3 subunits have been shown to be expressed strongly in the olfactory bulb (Kues and Wunder 1992Go). A recent study has shown that Kv1.3 protein is initially expressed in all layers of the rat olfactory bulb in early postnatal development (P1–P10), including mitral cell somata, but becomes progressively greater in the external plexiform layer, where the primary and secondary dendrites of mitral cells reside. While this staining pattern could be due in part to channel subunits localized to granule cell dendrites, dendrites terminating in glomeruli (presumably mitral/tufted cell primary dendrites) are especially heavily stained (Fadool et al. 2000Go). Other studies have shown that Kv1.3-mediated currents constitute the dominant outward conductance in cultured olfactory bulb neurons and that these currents decay with a time constant of several hundreds of milliseconds (Fadool and Levitan 1998Go). Olfactory bulb cultures contain two morphologically distinct types of neurons: small bipolar neurons that are thought to be granule and periglomerular cells and larger pyramidal shaped neurons with prominent apical and secondary dendrites that are putative mitral/tufted cells (Egan et al. 1992Go; Fadool and Levitan 1998Go; Trombley and Westbrook 1990Go). Both neuronal types express large amounts of Kv1.3 currents; however, there are subtle differences in the rate of inactivation of voltage-dependent currents in these subtypes (Fadool and Levitan 1998Go). This may reflect different Kv1.3-containing heteromultimeric channels that are present in output versus local interneurons in the olfactory bulb. Fadool et al. (2004)Go recently investigated Kv1.3 knockout mice and found dramatic alterations in olfactory-mediated behaviors and glomerular anatomy. In addition, cultured neurons from olfactory bulbs of knockout animals show profound alterations in their voltage responses to current steps. These results underscore the potential importance of ID-like currents that involve Kv1.3 subunits in the function of the olfactory bulb. The long initial spike latency (Storm 1988Go) and the sensitivity of intermittent discharges to specific blockers of slowly inactivating Kv1 family members that we have found in mitral cells suggest that ID-like currents play a critical role in patterning mitral cell responses. Preliminary mitral cell voltage-clamp recordings indicate that mitral cells express at least two 4-AP–sensitive transient potassium currents with decay kinetics that range from 40 to >500 ms (in response to steps from –80 to 0 mV; data not shown). A parallel study is underway in our laboratory with the goal of identifying the molecular basis of the transient K+ currents in mitral cells that enable intermittent firing in response to step stimuli and phase-locking in response to phasic stimuli.

Mechanisms of spike clustering and phase locking

Based on our results, we propose that spike clustering in mitral cells depends on the interplay between slowly inactivating ID-like K+ channels and a subthreshold TTX-sensitive Na+ current. Intermittent firing has been investigated previously using computational (Wang 1993Go, 2002Go) and experimental (Klink and Alonso 1993Go) studies to explain the genesis of fast subthreshold membrane potential oscillations and spike clustering in cells of the medial entorhinal cortex and basal forebrain (Alonso et al. 1996Go). These studies have proposed that cluster initiation depends on the level of inactivation of outward currents, while cluster termination depends on the buildup of potassium currents during a burst. Our studies support the view that spike cluster termination is controlled by potassium current buildup, since blocking ID-like currents increases cluster duration (and eventually abolishes intermittent firing). In addition, spike threshold increases slightly during the course of a cluster (see Fig. 2C), which suggests that outward currents increase during spike clusters. The first spike in a cluster is always smaller than later spikes; however, there is very little (<3 mV) modulation of spike amplitude during a cluster. This suggests that processes that control Na+ channel availability, such as cumulative inactivation during a train of spikes, may not play a prominent role in cluster termination. While elevated K+ currents are likely to be responsible for cluster termination, the precise biophysical mechanisms involved have not been determined experimentally. Potassium currents may increase during clusters as result of very rapid recovery from inactivation between individual spikes within a cluster (Wang 1993Go). Alternatively, macroscopic potassium currents may increase throughout each cluster, reflecting the slow deactivation kinetics of individual ID channels (Mitterdorfer and Bean 2002Go).

The origin of the variability in spike timing across repeated trials of step current is unlikely to reflect subtle changes in membrane properties of mitral cells from trial to trial. We found no correlation between the first spike latency and membrane potential or input resistance immediately preceding the depolarizing stimulus. One possible explanation for spike time variability is spike initiation in mitral cells is controlled by a small number of ion channels, such that spike variability is a reflection of noise from channel gating events. Several studies have addressed this issue using computational (Jones 2003Go; Schneidman et al. 1998Go; White et al. 1998Go) and experimental (Johansson and Arhem 1994Go) approaches. However, the functional significance of stochastic channel gating in controlling spike timing in mitral cells has not been established and may not apply to neurons as large as mitral cells. Alternatively, variability in discharge times may reflect the complex oscillatory dynamics of opposing inward and outward macroscopic currents active near threshold. Our preliminary voltage-clamp studies indicate that mitral cells express high levels of transient 4-AP–sensitive K+ currents, suggesting that oscillating inward and outward currents may be a more important mechanism for controlling spike timing than stochastic channel gating events. Previous studies on the role of transient 4-AP–sensitive K+ currents in controlling spike timing in neurons have focused on the characteristic delay in the timing of the first spike (Saviane et al. 2003; Storm 1988Go). Blockade of 4-AP–sensitive K+ currents reduces this delay (McCormick 1998Go; Saviane et al. 2003; Storm 1988Go); however, it is not known whether expression of ID-like currents in these neurons leads to variable spike timing.

Precise spike timing evoked by phasic stimuli likely arises because of differences in the kinetics of recovery from inactivation of transient outward currents and voltage-dependent Na+ currents. The initial depolarization from the first simulated EPSP causes a rapid activation of outward currents that inhibit spiking. During the falling phase of the first EPSP, fast transient Na+ currents should recover rapidly from inactivation (Kuo and Bean 1994Go). By contrast, slowly inactivating ID-like currents will likely de-inactivate at much slower rates (Fadool and Levitan 1998Go), enabling a subsequent depolarization totrigger a cluster of spikes. Spike clusters are terminated either by repolarization during the falling phase of the EPSP or buildup of outward currents. This scheme is supported by experiments that show that the amplitude of the first EPSP gates the generation of spikes on subsequent EPSPs. Small amplitude simulated EPSPs may not inactivate sufficient K+ currents to allow firing on subsequent simulated EPSPs (as shown in bottom traces in Fig. 6A). Larger initial simulated EPSPs presumably inactivate more ID-like K+ current, thereby facilitating firing following a repolarization/depolarization cycle. Preferential recovery of Na+ versus K+ currents during the repolarization phase is likely to account for the decreased firing threshold following brief repolarizing steps (Fig. 4) and during responses to the trains of simulated EPSPs (Fig. 5).

Functional implications for odor coding

Several theoretical studies have suggested that action potential timing may be important for representing sensory stimuli (Hopfield 1995Go; Rieke et al. 1997Go). Temporal coding appears to be especially important in olfactory processing (Laurent et al. 1996Go; Wehr and Laurent 1996Go), where single olfactory receptor neurons have broad specificity for many odorants (Araneda et al. 2000Go; Duchamp-Viret et al. 1999Go), to increase the number of odorants that can be uniquely identified. Recent studies in insects have shown that downstream neurons that receive information from projection neurons act as coincidence detectors (Perez-Orive et al. 2002Go). Such a coding scheme requires that incoming spike trains be highly reproducible across repeated trials.

Our study suggests that intrinsic ionic mechanisms in mitral cells promote precise spiking in response to phasic stimuli in the theta frequency range. Prominent 2- to 7-Hz activity coupled to the respiratory rhythm has been observed in mitral cells in vivo using extracellular unit (Belluscio et al. 2002Go; Macrides and Chorover 1972Go) and whole cell intracellular (Margrie and Schaefer 2003Go) recordings, voltage dye imaging (Spors and Grinvald 2002Go), and calcium imaging in mitral cell apical dendritic tufts (Charpak et al. 2001Go). The genesis of this respiratory-coupled activity is likely to reflect changes in odorant concentration (and thus activation of olfactory receptor neurons) in the olfactory epithelium during inspiration (Sobel and Tank 1993Go). Our results suggest that mitral cells are "tuned" to receive synaptic input in the theta band frequency range in which rodents normally sniff. The intrinsic properties of mitral cells allow them to filter olfactory information by controlling the generation of spikes that are evoked by inspiration-induced theta activity. By this mechanism, the activation of a broad subset of olfactory receptor neurons would result in precisely timed trains of spikes in a small subset of mitral cells. Weak or transient stimuli may not evoke spiking at all, whereas sustained stimuli that are not modulated in time might produce spikes that are highly variable from trial to trial, presumably impairing downstream coincidence detection mechanisms. These intrinsic filtering mechanisms might act in concert with synaptic mechanisms that synchronize theta oscillations in adjacent mitral cells (Schoppa and Westbrook 2001Go; Urban and Sakmann 2002Go) to ensure that mitral cells which project to the same glomerulus act as distinct functional units.


    GRANTS
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 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
This study was supported by National Institute on Deafness and Other Communication Disorders Grant DC-04285.


    ACKNOWLEDGMENTS
 TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
We thank B. Halabisky and T. Pressler for helpful discussion. We also thank Drs. Diana Kunze and Steve Jones for constructive comments on this manuscript.


    FOOTNOTES
 
The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Address for reprint requests and other correspondence: B. W. Strowbridge, Dept. of Neurosciences, Case Western Reserve Univ., 10900 Euclid Ave., Cleveland, OH 44106 (E-mail: bens{at}cwru.edu).


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