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J Neurosci. Author manuscript; available in PMC 2010 August 17.
Published in final edited form as:
PMCID: PMC2923072
EMSID: UKMS30948

Synaptic and cellular properties of the feed-forward inhibitory circuit within the input layer of the cerebellar cortex

Abstract

Precise representation of the timing of sensory stimuli is essential for rapid motor coordination, a core function of the cerebellum. Feed-forward inhibition has been implicated in precise temporal signalling in several regions of the brain, but little is known about this type of inhibitory circuit within the input layer of the cerebellar cortex. We have investigated the synaptic properties of feed-forward inhibition at near physiological temperatures (35°C) in rat cerebellar slices. We establish that the previously uncharacterized mossy fibre–Golgi cell–granule cell pathway can act as a functional feed-forward inhibitory circuit. The synchronous activation of 4 mossy fibres, releasing a total of 6 quanta onto a Golgi cell, can reset spontaneous Golgi cell firing with high temporal precision (200μs). However, only modest increases in Golgi cell firing rate were observed during trains of high frequency mossy fibre stimulation. This decoupling of Golgi cell activity from mossy fibre firing rate was due to a strong after-hyperpolarization following each action potential, preventing mossy fibre–Golgi cell signalling for ~50 ms. Feed-forward excitation of Golgi cells induced a temporally precise inhibitory conductance in granule cells that curtailed the excitatory action of the mossy fibre EPSC. The synaptic and cellular properties of this feed-forward circuit appear tuned to trigger a fast inhibitory conductance in granule cells at the onset of stimuli that produce intense bursts of activity in multiple mossy fibres, thereby conserving the temporal precision of the initial granule cell response.

Keywords: cerebellum, synaptic integration, Golgi cell, mossy fibre

Introduction

The precision with which an action potential (AP) can be triggered by synaptic input sets the fidelity with which temporal events can be represented and the amount of information carried by an individual AP (Rieke et al., 1997). Precise AP timing is crucial for neural codes that represent physical variables as spike times relative to oscillating reference signals (Stopfer et al., 1997; Harris et al., 2002). Spike timing is also important in motor systems because encoding temporal sequences is essential for coordinating movements (Ivry and Keele, 1989; Medina and Mauk, 2000). Indeed, impairment of spike precision causes ataxia (Walter et al., 2006). Many of the neurons in motor systems, particularly in the cerebellum, are spontaneously active (Llinás, 1988; Hausser et al., 2004) and several of these participate in feed-forward inhibitory loops (Mittmann et al., 2005), which are thought to preserve temporal signalling as sensory signals flow through networks (Pouille and Scanziani, 2001; Mittmann et al., 2005). But, relatively little is known about how processing is accomplished in the presence of intrinsic activity in feed-forward interneurons.

Golgi cells (GoCs), which reside in the input layer of the cerebellar cortex, are spontaneously active and provide the sole source of inhibition for thousands of granule cells (GrCs; (Eccles et al., 1967). GoCs are important for normal cerebellar function as pharmacological ablation of this inhibitory interneuron leads to sever motor deficits (Watanabe et al., 1998). Although classical anatomical studies have indicated the presence of a feed-forward inhibitory circuit in the granule cell layer (Eccles et al., 1967), little is known about its functional properties. Moreover, in vivo experimental evidence for precise temporal signaling in the input layer of the cerebellar cortex is scarce. We have used patch-clamp recordings and imaging in acute cerebellar slices to unambiguously identify the feed-forward mossy fibre (MF) input onto GoCs and investigate its properties. We show that the synchronous activation of a small number of MFs can reset the timing of spontaneously firing GoCs with high precision. However, a powerful after-hyperpolarization following each spike, reduced the reliability of MF-GoC transmission as the frequency increased, decoupling GoC firing from MF excitation. A MF-evoked GoC spike produced a precisely timed feed-forward inhibitory conductance in GrCs which cancelled slow MF-GrC EPSC components. These results establish that a functional feed-forward MF-GoC-GrC pathway is present in the input layer of the cerebellar cortex. The synaptic properties of this circuit, together with intrinsic pacemaker currents of the GoC suggest that this circuit could help preserve information on the precise timing of the start a discrete sensory stimulus by shaping the early GrC response.

Materials and Methods

Electrical Recording Conditions

Parasagittal slices of cerebellum (200-220μm thick) were prepared from 25-day old (P25) Sprague Dawley rats as previously described (Silver et al., 1996). Brain slices were either prepared in artificial cerebro-spinal fluid (ACSF; 125 NaCl, 2.5 KCl, 2 CaCl2, 1 MgCl2, 1.25 NaH2PO4, 26 NaHCO3, and 25 glucose, pH=7.3 equilibrated with 5%CO2/95%O2) or in 130 K-gluconate, 15 KCl, 0.05 EGTA, 20 HEPES and 25 glucose, pH=7.4 with NaOH (Dugue et al., 2005), as this was found to increase GoC viability (Dugue et al., 2005; Forti et al., 2006), and incubated in ACSF at 30-31°C for 45min. The tissue was then stored at room temperature for up to 6 hours before use. In the recording chamber, brain slices were continuously perfused with ACSF at 34-36°C. The following pharmacological agents were added to the external perfusion solution when mentioned: 10μM SR95531 (Gabazine), 0.3μM Strychnine, 10-100μM NBQX and 10μM APV. All chemicals were obtained from either Sigma-Aldrich (Dorset, UK) or Tocris (Bristol, UK). Release probability was lowered by reducing the Ca2+ / Mg2+ ratio in the extracellular solution to 1mM / 5mM in a subset of experiments.

Slices were visualised with a ×60 (NA=0.9) water-immersion objective using infrared differential interference contrast optics (Olympus BX50W1) and a CCD camera. Patch pipettes were produced from borosilicate glass capillaries (Sutter Instruments) using a Sutter P97 horizontal Puller (Sutter Instruments, Novato, CA, USA). We used an Axopatch 200B for whole-cell voltage-clamp and an Axoclamp 2B amplifier (Molecular Devices, Sunnyvale, CA, USA) for current-clamp recordings. High quality voltage and current recordings were not possible in the same cell due to the limitations of these amplifiers. Some later recordings were also performed with an Axopatch 700B. Data was low-pass filtered at 10-30kHz and digitized at 50-100kHz. Recordings were acquired and analyzed with IgorPro (WaveMetrics, Oregon, USA) using NeuroMatic (http://www.physiol.ucl.ac.uk/research/silver_a/neuromatic/). All traces displayed in figures were further digitally filtered to 7kHz using a binomial smoothing function in IgorPro. MF inputs were activated via an ACSF-filled glass pipette (2-3 MΩ) placed in the WMT, typically 100-200μm away from the recording site using a stimulus isolator (Model DS2A, Digitimer Ltd, Hertfordshire, UK) to generate 10-100V pulses of 20-200μs duration. Parallel fibres (PFs) were activated by stimulating the upper GrC layer or molecular layer, which led to qualitatively similar results.

Loose cell-attached (LCA) recordings

GoC firing behaviour was monitored in LCA voltage-clamp configuration with ACSF-filled pipettes (7-10 MΩ). APs were identified based on prominent upward and downward deflections in the current trace (Vos et al., 1999). Recording stability was monitored by observing the AP shape. AP latency was defined as the time point of half-maximal amplitude of the inward deflection. The effect of MF stimulation on spontaneous rhythmic GoC firing was assessed with a phase-response curve, calculated with equation 1, which determines whether a perturbation advances or retards the phase of an oscillator (Rinzel and Ermentrout, 1998).

Δθ=T0Tn(θ)T0
(1),

Where Δθ is the phase-response, T0 is the median of interspike-interval (ISI) before stimulation and Tn is the ISI between APs of interest. Tn can depend on time or the phase at which the stimulus occurs (θ = Ts/T0; where Ts is the interval between the spontaneous AP before stimulation and time point of stimulation).

Whole cell recordings

Postsynaptic currents (PSCs) and potentials (PSPs) were measured with 5-7 MΩ patch electrodes filled with (in mM): 5 Na-MeSO3, 130 K-MeSO3, 10 HEPES, 5 MgCl2, 0.1 EGTA, 0.3 NaGTP, 4 MgATP and 100μM Alexa488 or Alexa594, pH=7.3 with KOH for GoC and 110 K-MeSO3, 40 HEPES, 6 NaOH, 3 MgCl2, 0.02 CaCl2, 0.15 BAPTA, 0.3 NaGTP, 4 NaATP, pH=7.3 with KOH for GrC recordings. In some experiments voltage-gated channel blockers QX314 (5mM) and TEA (17.5mM) were included in the internal solution. Voltage-clamp recordings were made at holding potentials of −60mV and −30mV (GoCs), −70mV and 0mV (GrCs) and not corrected for the 8mV (GoC internal) and 6.3mV (GrC internal) liquid junction potential. Whole-cell capacitance and series resistance were determined by canceling the current transient evoked by a 50ms, 5mV hyperpolarizing voltage step and read from the amplifier dials. Cell input resistance was calculated from the steady state current at the end of the voltage step and the recording stability was accessed with a Spearman’s rank correlation test. GoCs had a whole cell capacitance of 37±14pF and in patch-clamp recordings the electrode series resistance (16±6MΩ, n=64) was compensated (60-70%, 7-10μs lag) to around 5MΩ. This gave an effective filtering (1/(2πRCm)) of approximately 1kHz. GrCs had a whole cell capacitance of <5pF and were recorded with an uncompensated series resistance of 26±10MΩ (n=19) which resulted in an effective filtering of 1.5 kHz.

GoC current-clamp recordings were initially carried out in the absence of current injection to compare the spontaneous firing in LCA and whole-cell configuration. Since the whole-cell configuration affected the spontaneous firing in an unpredictable fashion (Forti et al., 2006) we injected hyper- or depolarising currents to match the firing frequency observed in LCA recordings. The spike threshold was defined as the membrane voltage when the derivative of the membrane voltage (dV/dt) was 5 SDs above the mean dV/dt for subthreshold regions. This gave a threshold criterion of approximately 5mV/ms (see also (Forti et al., 2006), which reliably identified the rising phase of APs and closely matched the visually identified inflection point. The threshold potential was then corrected for the liquid junction potential.

Postsynaptic currents (PSCs) were baseline subtracted using a 0.5ms time window before the stimulus. In some cases the stimulus artefact was removed by subtracting a double exponential fit to the averaged artefact. Individual events were classified as failures when the mean amplitude in a 1ms window around the peak of the PSC was smaller than 3x SD of the mean background current of a 1ms time window before the stimulus. To further distinguish slowly rising spillover currents we grouped all events with a rise time 5x SD above the mean rise time of successes with failures (DiGregorio et al., 2002). To describe the PSC kinetics we measured the 20-80% rise time, calculated the weighted decay (normalized integral over a 20ms time window; (DiGregorio et al., 2002) or fit the decay with a double exponential function.

The time course of synaptic reversal potential was calculated as follows (Johnston and Wu, 1995).

ESyn=GexcEexc+GinhEinhGexc+Ginh
(2),

ESyn = reversal potential of the combined excitatory and inhibitory conductances, Gexc = excitatory conductance, Eexc = reversal potential of excitatory conductance (estimated to be 0mV), Ginh = inhibitory conductance, Einh = reversal potential of inhibitory conductance (estimated to be −75mV). When ESyn is below the voltage threshold for spike initiation the combined synaptic conductances will not induce firing.

Response latencies were measured between the beginning of the stimulus artefact and the 20% rise time point of the PSC. Since monosynaptic MF-GrC EPSCs have a mean latency of 0.8ms (Sargent et al., 2005) we excluded all GoCs responding to WMT stimulation with currents of latencies larger than 1.2ms (5x SD above mean MF-GrC latency) from further analysis. Disynaptic IPSC latency jitter in GrCs arises from the jitter of MF-evoked GoC APs and the jitter of GoC-GrC transmission. Since variances add when two Gaussian distributions are convolved the expected jitter of disynaptic GrC inhibition is

SD=σ2MFGoC+σ2GoCGrc
(3).

Deconvolution analysis was performed as previously described (Sargent et al., 2005) without spillover correction. Uniquantal events were measured under low release probability conditions, aligned on their 20% rise time. To reduce the effects of noise these were determined from fits of equation 4 to individual currents and averaged.

EPSC(t)=A1(1exp(tt0τrise))n(A2exp(tt0τdecay1)+(1A2)exp(tt0τdecay2))
(4)

The resulting mean current was also fit with equation 4 and deconvolved with a fit of the average stimulus evoked EPSC under control conditions to yield the vesicular release rate as a function of time across all release sites at the connection. We verified this approach by directly determining the release time course from the first latencies of EPSCs in low release probability conditions for four cells. At high failure rates (>80%) the correction for the occurrence of multiquantal events (Barrett and Stevens, 1972) was negligible (KS test: P > 0.2, n=4).

The quantal size at the time of the peak of the evoked EPSC (Qp) was determined in two ways. First we averaged stimulus-aligned quantal events recorded under low release probability conditions (failure rate >0.8) and corrected the measured amplitude for multiquantal events (~10%; (Silver, 2003). We also calculated Qp from variance/mean analysis under low release probability conditions (Silver, 2003). We corrected this estimate of Qp for the variance arising from quantal amplitude variability and latency jitter, measured from variability of stimulus-aligned uniquantal events,

Qp=σ2I(1+CVT2)
(5),

where σ2 = peak variance, I = mean EPSC amplitude at the time of the peak under low release probability conditions and CVT = coefficient of variation of total quantal variability measured from the peak of stimulus-aligned successes.

Image Acquisition and Analysis

Golgi cell anatomy was visualized with the dyes Alexa488 or Alexa594 (100μM, Molecular Probes, Invitrogen, UK) using fluorescence microscopy. Imaging was carried out using whole field excitation (USH102D Mercury Lamp, Ushio America, Cypress, CA, USA) and image acquisition (excitation filters, in nm: 480/40 and 580/20; dichroic 505lp and 595lp; emission filters 535/50 and 630/60 for Alexa488 and 594 respectively) with a cooled digital camera (ORCA100, Hamamatsu Photonics UK Ltd, Hertfordshire, UK) and Prairie Technologies (Middleton, WI, USA) Software. Several images of cell body and dendritic arborisation were taken to identify the cell type patched.

For Ca2+-measurements we substituted Alexa dye with 200μM OregonGreen BAPTA1 (OGB1, Molecular Probes). Images (series of 3-4) were taken of various parts of the cell before and during a 100Hz (100 pulses) stimulation of the white matter. We used a custom-made image analysis routine in Matlab (Mathworks, Cambridge, UK) to calculate the ΔF/F for each pixel by averaging the images before and during stimulation and relating the intensity difference before and during stimulation to the average pixel intensity before stimulation. The distribution of ΔF/F values was fitted with a Gaussian function. Only pixels with an intensity value 5 SDs above the mean pixel intensity value, that formed a contiguous group in the image were considered to represent a significant increase in local calcium concentration. The large depth of focus of CCD imaging allowed the simultaneous observation of fluorescence changes in large parts of the cell and hence reliable detection and mapping of synaptically evoked calcium signals (ΔF/F > 0.1) onto the cell morphology in fewer trials than for confocal imaging. During Ca2+-imaging experiments whole-cell capacitance and series resistance compensation was disabled to induce poor space-clamp as this increased the probability of detecting a Ca2+-transient upon MF stimulation. The Ca2+-signal was fully inhibited by blockers of glutamatergic synaptic transmission, but NMDA receptors (NMDAR) contributed little to the synaptic response (see Supplementary Figure 1) and were thus an unlikely source of the Ca2+-increase. Furthermore, 100μM Ni2+ a non-selective voltage-dependent Ca2+-channel blocker fully inhibited the Ca2+-signal (n=3, data not shown). Activation of voltage-gated Ca2+-channels by synaptically induced local depolarisation is therefore likely to be responsible for the Ca2+-signal, although we cannot exclude Ca2+-permeable AMPA receptors (AMPAR) or synaptically induced release from internal Ca2+-stores.

Statistics

Data are presented as mean ± standard deviation (SD) and sample means compared with paired or unpaired two-tailed student’s t-test. For pair-wise comparison of groups we employed single and two-factor ANOVA and distributions were compared using a Kolmogorov-Smirnov (KS) test. Mean values were considered significantly different at p<0.05. Linear, exponential and Gaussian functions were fit to data points using the least squares method.

Results

Identification of Golgi cells and the functional properties of their excitatory inputs

Golgi cells (GoCs) in acute slices of cerebellar cortex from P25 rats (Materials and Methods) were initially identified on the basis of their location within the granule cell (GrC) layer and their large somata (>15μm). In loose cell-attached (LCA) recordings, using pipettes containing extracellular solution, most of these putative GoCs (83%) exhibited spontaneous rhythmic firing (9±5Hz, n=38), consistent with previous studies (Mitchell and Silver, 2000; Forti et al., 2006). For whole-cell recordings we included a fluorescent tracer dye in the intracellular solution and visualised the cell morphology with fluorescence microscopy. Only those cells with basal dendrites in the GrC layer and ascending dendrites in the molecular layer were confirmed as GoCs (Eccles et al., 1967; Dieudonne, 1998) and included in our data set (64 of 68). The extent of the ascending and basolateral arborisation was approximately 200μm and 100μm, respectively, in agreement with previous morphological description of GoCs (Eccles et al., 1967; Palay and Chan-Palay, 1974; Dieudonne, 1998). Identified GoCs exhibited frequent spontaneous excitatory postsynaptic events, a larger cell capacitance (37±14pF; range 10-74pF, n=64) than the surrounding GrCs (<5pF) and a relatively low input resistance (Rin=330±70MΩ).

Anatomical data suggests that GoCs receive three types of excitatory inputs. Parallel fibres (PFs, GrC axons) synapse onto their ascending dendrites within the molecular layer, MFs contact basolateral dendrites in the GrC layer and climbing fibres (CFs) may make connections at the soma (Eccles et al., 1967). To date only the PF to GoC input has been characterised functionally (Dieudonne, 1998; Bureau et al., 2000; Beierlein et al., 2007). To establish whether MFs make functional synapses onto GoCs we electrically stimulated the white matter tract (WMT), which is primarily comprised of MFs. However, this could also potentially activate CF input monosynaptically and PF input disynaptically, via the activation GrCs. We therefore examined the functional properties (kinetics, pharmacology and plasticity) and anatomical location of WMT-evoked synaptic inputs and compared them to the properties of PF (to GoC) and CF (to Purkinje cell) transmission to determine whether MFs could be activated in isolation. Figure 1 compares the properties of synaptic currents evoked in GoCs by WMT and PF stimulation (see Materials and Methods). Both WMT and PF stimulation induced inward currents at −60mV indicating an excitatory input (Cl reversal potential = −70mV). Bath application of GABA and glycine receptor blockers had no significant effect on the mean WMT evoked EPSC waveform (n=7, p>0.5, t-test), nor did the incorporation of the sodium and potassium channels blockers, QX314 (5mM) and TEA (17.5mM), in the patch pipette (n=10, p>0.9, t-test, data not shown). However, the evoked currents were blocked by NBQX (10-100 μM) confirming they were both glutamate receptor mediated (Figure 1Ai, Bi). The time between stimulation and the 20% rise of the mean synaptic current was short for both WMT and PF inputs (1.0±0.1ms and 1.0±0.4ms, respectively), consistent with monosynaptic activation. WMT stimulation produced EPSCs in GoC with both a fast rise (20-80% rise time = 0.23±0.04ms) and weighted decay times (τWD = 1.6±0.5ms, n=42, Figure 1Ai ,Aii). In contrast, PF-evoked EPSCs had significantly slower rise (0.5±0.2ms, p<0.05, n=6) and decay kinetics (τWD = 3.4±1.5ms; n=6, p<0.05, Figure 1Bi, Bii) and EPSCs occurred over a longer time window (80% of events within 430±270μs compared to 190±50μs for WMT stimulation, Figures 1Aiii and Biii). To test the potential contribution of NMDARs to WMT evoked EPSCs we applied APV at depolarised holding potentials (−30mV). APV did not change the EPSC waveform in 3 out of 7 cells and in the remaining cells the overall EPSC charge was reduced by only 18±11%. This indicates that NMDARs contribute little to the EPSC waveform and currents remain fast at depolarised potentials (τWD = 1.9±0.7ms at −30mV, n=7, p>0.2, paired t-test, Supplementary Figure 1A). The distinct kinetics of short latency EPSCs arising from WMT and PF stimulation indicate that they arise from different synaptic inputs.

Figure 1
Comparison of Golgi cell EPSCs evoked by white matter tract and parallel fibre stimulation

We next examined whether the properties of WMT-evoked EPSCs depended on the stimulation voltage. The mean EPSC amplitude increased and the fraction of failures decreased as the stimulus intensity was increased (Figure 1C, D). However, the EPSC waveform (Figure 1C, inset) remained the same, indicating that the increase in EPSC size was due to the recruitment of inputs with similar kinetics. The initial step-like relationship between EPSC amplitude and stimulus voltage suggests that at low voltages a single fibre was activated, as previously observed for MF-GrC synaptic connections (Silver et al., 1996). Single fibre activation exhibited a 22±13% failure probability and a mean EPSCs amplitude of −66±26pA (n=42). In 5 of these 42 recordings we observed slowly rising EPSCs similar to spillover currents described at the MF-GrC synapse (DiGregorio et al., 2002). In these cells spillover currents contributed 32±17% (n=5) of the EPSC charge (Supplementary Figure 1Bi, Bii). During high voltage WMT stimulation, when multiple fibres are activated, a second longer latency (>2ms) EPSC component was occasionally observed (22% of recordings; see Figure 1Aii, arrow). The kinetics of this late component were similar to PF evoked events (20-80% rise time = 0.4±0.1 and τWD = 2.3±0.03ms, p > 0.3, n=3), consistent with the recruitment of a disynaptic PF input.

Synaptic connections made by PFs (onto GoCs and Purkinje cells), CFs (onto Purkinje cells) and MFs (onto GrCs) exhibit distinct short-term plasticity (STP) characteristics. WMT-evoked EPSCs onto GoCs exhibited little STP during 5 pulse 25Hz stimulus trains (amplitude ratio EPSC5/EPSC1 = 0.95±0.27, n=14, Figure 2Ai). Even when the stimulation frequency was increased to 100Hz the EPSC only depressed by 22±17% during 10 stimuli (n=10, Figure 2Aii). This STP behaviour contrasted with the 50% facilitation observed for 5 pulse 25 Hz PF stimulation (n=6, p<0.05, two-factor ANOVA on 25Hz WMT vs PF, Figure 2B), consistent with previous studies of the PF input (Bureau et al., 2000). The STP characteristics of WMT EPSCs are also distinct from CF to Purkinje cell transmission, which depresses profoundly (Llano et al., 1991; Silver et al., 1998). Although the MF-GrC synapse also depresses moderately this is predominantly due to postsynaptic AMPAR desensitization. Indeed, lack of plasticity in the WMT input onto GoC is similar to the presynaptic component of MF-GrC transmission, which depresses little during high frequency stimulation (Saviane and Silver, 2006). The functional properties of WMT-evoked EPSCs are therefore consistent with MF rather than PF or CF input.

Figure 2
Short-term plasticity of EPSCs evoked by white matter tract and parallel fibre stimulation

Synaptic location of putative mossy fibre inputs

Anatomical studies have shown that excitatory inputs onto GoCs are spatially segregated (Eccles et al., 1967). We therefore examined the spatial location of putative MF-GoC synapses by calcium imaging during low intensity WMT stimulation, which activated 1 or 2 fibres (see Materials and Methods). Figure 3A shows a 2D projection of a GoC manually reconstructed from a montage of fluorescence images taken with a cooled CCD camera at different focal planes (e.g. Figure 3B). The three fluorescent images in Figure 3B show part of the ascending dendrite (top), soma and basal dendritic arbour (below). Figure 3C shows the fluorescent change during WMT stimulation for the same regions. In this cell, the fluorescence (ΔF/F) and therefore calcium concentration, increased in one of the basal dendrites. In cells where calcium changes were detectable (7 out of 11), WMT stimulation induced local calcium changes (ΔF/F = 0.31±0.29) in descending or lateral dendrites of GoCs within the GrC layer but never in the soma or in the dendrites ascending into the molecular layer. Perfusion of NBQX (100 μM) and AP5 (10 μM) fully and reversibly blocked both the WMT-evoked EPSCs and the calcium signal confirming their synaptic origin (n=7). The lack of any calcium signals from the ascending dendrites was not due to an inability of the ascending dendrites to respond, because robust calcium signals were observed in the ascending dendrites during molecular layer stimulation (Supplementary Figure 2A-C; n=3).

Figure 3
Calcium imaging of Golgi cells during white matter tract stimulation

The EPSCs associated with the calcium signal in the basolateral dendrites were similar in latency (1.0±0.1 ms, n=7, p>0.2), kinetics (20-80% rise time = 0.26±0.1ms, p>0.3; τWD = 1.8±0.7ms, p>0.2) and STP behaviour (amplitude ratio EPSC5/EPSC1 = 1.02±0.12, p>0.9) to WMT-evoked EPSCs described earlier (Figure 3D, E). The mean distance between the peak of the fluorescence change and the centre of the cell body was 56±25 μm (range 20–90μm, n=7). The fast rise time of the EPSCs and its weak distance dependence (Figure 3F) suggest that basolateral dendrites introduce relatively little filtering of the synaptic current. The location of synaptic inputs on the basolateral dendrites and the short latency and lack of STP of the EPSCs confirm that WMT stimulation activates MFs rather than PF of CF inputs.

Mossy fibre input resets Golgi cell firing

To investigate the effects of MF excitation on GoC firing we used the non-invasive LCA recording method to prevent disruption of the internal milieu. Figure 4A shows a LCA recording from a GoC that exhibited spontaneous rhythmic firing at 12Hz. Single-pulse stimulation of the MF input induced an AP soon after the onset of the stimulus. APs induced by WMT stimulation were blocked by NBQX (10 μM) confirming their synaptic origin and ruling out direct activation of the GoC axon. The raster plot in Figure 4B shows that MF stimulation induced an AP that was time-locked to the stimulus across multiple trials. MF-evoked APs occurred in a narrow time window, but entrainment of subsequent spikes (Figure 4C) was variable from cell to cell. To understand how the MF input affected GoC rythmicity as a function of stimulus timing we calculated the phase-response curve for each cell (see Materials and Methods). Figure 4D shows the phase-response averaged over 21 cells for the 1st (solid line) and 2nd (broken line) AP after the stimulus as a function of stimulus phase. A phase response of 0 indicates that the stimulus had no effect on the spike timing of subsequent spikes, as seen for the 2nd AP after stimulation. A value greater 0 implies a phase advance, which is observed for the 1st AP after stimulation when the stimulation phase was > 0.2. The phase response curves are statistically significantly different (p < 0.0001; single factor ANOVA). This implies that the phase of spontaneous firing can be reset for stimulation phases greater 0.2.

Figure 4
Effect of mossy fibre input on spontaneous Golgi cell firing

The probability of the MF input eliciting a spike depended on the time since the preceding spike. To quantify this we used a paired-pulse protocol to assay the probability of triggering a spike at different times after an initial AP (Figure 4E). On average, it took 52±29ms after the first spike (range 20-120ms, n=9 cells) for the spike probability to recover to 50% (Figure 4E, F). This value was similar to the time during which MF stimulation was ineffective in producing an AP after a spontaneous spike (p > 0.9, paired t-test, n = 6). These results show that the feed-forward excitatory MF input onto GoCs can reset the spike timing and thus the phase of the GoC firing pattern, but that the transmission reliability depends on the timing of the input with respect to the phase of the spontaneous activity.

Action potential precision and transmission reliability at low and high MF firing frequencies

APs evoked by low frequency MF input had a mean latency across cells of 1.1±0.4ms (n=37) and exhibited remarkably little temporal jitter (Figure 5A, B). Their precision, defined as the standard deviation (SD) of AP times, was 200±120μs (n=37). This precision was unaffected by application of 10μM Gabazine (p>0.5, n=4; paired t-test), which excluded the involvement of feed-forward inhibition in setting the precision of GoC firing. Moreover, precision was only weakly dependent on stimulation strength since there was no correlation between SD and AP probability across cells (Figure 5C). However, when comparing the precision at different AP probabilities in individual cells a weak but significant correlation was evident (Pearson’s r = −0.28, p < 0.05, t-test on fractional change, n=9). On average APs were evoked in 52±21% of trials across 37 cells. These results show that the MF-GoC synapse can achieve a greater precision in EPSP-spike coupling than has been reported for other inhibitory interneurons (Fricker and Miles, 2000; Galarreta and Hestrin, 2001; Pouille and Scanziani, 2001; Carter and Regehr, 2002).

Figure 5
Precision and reliability of mossy fibre evoked Golgi cell firing

We next examined AP precision during trains of MF activity, since some sensory inputs are sustained (van Kan et al., 1993). The spike raster plots in Figures 5D and E show APs evoked by 10Hz and 100Hz MF stimulation. GoCs fired in a brief time window following the stimulus. Analysis of the spike jitter in response to the 1st and consecutive stimuli showed that spike time distributions did not change during the train (KS test p>0.9 for 10 and 100Hz, n=6) indicating that spike precision was maintained. As stimulation frequencies increased from 10Hz to 100Hz the mean values of the SD of evoked AP times increased from 0.2±0.2ms to 0.4±0.2ms (Figure 5F). We also observed an increase in the mean spike latency from 1.4±0.2ms to 1.8±0.6ms. This is likely to be due to a reduction in GoC excitability, as we observed a decline in spontaneous firing after high frequency stimulation (0.4±0.4Hz after 100Hz MF stimulation; p<0.05; paired t-test). The probability of an AP occurring on a particular trial depended on both the initial spike probability and on the time since the last spike, as expected from the relative refractory period. At stimulation frequencies of 1 Hz and 10Hz the AP probability did not change during a train. However, when the frequency was increased to 100Hz the reliability of triggering an AP dropped from 51±31% on the first spike to approximately 20% during the rest of the train (single-factor ANOVA p < 0.01, Figure 5G). Thus, low frequency MF stimulation (1-10Hz) produced little change in the GoC firing rate from the baseline firing rate of 6±3Hz (n=5), but a stimulation frequency above 10Hz led to sub-linear increase in GoC firing to a saturated level of 17±12Hz (n=5) at 100Hz (Figure 5H). The decoupling of GoC firing rate from MF rate shows that this connection transmits rate-based information poorly. However, timing information is reliably transmitted at low frequencies and at the onset of a high frequency stimulus train.

Properties of EPSP-spike coupling

To examine how MF synapses induce precise firing and yet have little effect on GoC firing rate, we examined the membrane potential during synaptic integration. To do this we established the MF stimulus intensity necessary to evoke an AP with approximately 50% reliability in the LCA configuration (49±18%, n=5) and then re-patched with an electrode containing internal solution in the whole-cell current clamp configuration. Figure 6A shows two voltage trajectories of a spontaneously firing GoC during MF stimulation. AP threshold was −55mV and APs produced a pronounced afterhyperpolarization to −80mV, followed by a slower depolarising phase leading to the next spike. These values were similar to the averages across cells (−55±6mV and −80±5mV, n=5, respectively) and to previous findings (Forti et al., 2006). When MF input was stimulated soon after the spike, during the hyperpolarised phase, no AP was induced (Figure 6A, black trace), but when it occurred later, during the depolarising phase, an AP was triggered (Figure 6A, red trace). This is also illustrated in Figure 6B which plots the preceding membrane potential before an MF induced event (AP = red and EPSP = black). On average, the minimum interval between an evoked AP and the proceeding spontaneous AP was 58±17ms (n=5), similar to the relative refractory period determined in LCA recordings (Figure 4F). These results suggest that the after-hyperpolarization prevents EPSPs reaching threshold and underlies the relative refractory period in MF-GoC signalling observed in LCA recordings (Figure 4F).

Figure 6
EPSP–spike coupling and efficacy of mossy fibre – Golgi cell transmission

Figure 6C (upper panel) shows examples of successes and failures on an expanded timescale. On average MF-evoked EPSPs had a rise time of 0.42±0.07ms (20-80%), a mean amplitude of 8.5±2.2mV, a coefficient of variation of 0.24±0.1 and a rapid initial decay time constant (τdecay1 = 2±1ms, n=5). The latency jitter of MF-GoC EPSPs was only 80±40μs (20% rise point, n = 5). MF-evoked APs tended to arise from the rising phase of the EPSP and had a narrow latency distribution (SD = 250±40μs, n=5), consistent with LCA recordings (Figure 5C). Figure 6C (lower panel) compares the time courses of a typical spike latency histogram (measured as time to threshold crossing), corresponding mean sub-threshold EPSP for that cell and aligned population mean EPSC time course (see Materials and Methods). The average interval between the EPSP (20% rise time) and time of threshold crossing was 400±200μs (n=5), confirming that many of the APs were triggered during the rising phase of EPSPs. Comparison of EPSP and the population mean EPSC time course shows that the EPSC rise and initial decay occur during the rising phase of the EPSP. Indeed, the shape of the spike latency distribution shared more similarity with the mean EPSC than EPSP waveform (Fetz and Gustafsson, 1983; Galarreta and Hestrin, 2001). Previous work in other cells has found that voltage-gated conductances in dendrites can contribute to rapid EPSP-spike coupling (Fricker and Miles, 2000; Martina et al., 2000). However, the lack of dependence of EPSP amplitude on preceding membrane potential (Figure 6D; n=5) suggests that they do not play a major role in boosting the MF-GoC EPSP. These results show that EPSP-spike precision is achieved by triggering spikes predominantly during the rising phase of the EPSP, which is determined by the rapid initial components of the EPSC time course.

To investigate how many MF inputs were necessary to trigger an AP we examined the mean EPSC peak amplitude under whole-cell voltage-clamp at the same stimulus settings that gave a spike probability of 51±14% (n=9) in the LCA configuration. The EPSCs had a mean peak amplitude of − 260±172pA (n=9). Comparison with EPSCs arising from single MFs recorded in the same cells (−66±29pA, n=9) revealed that, on average, 4 MF inputs are sufficient to trigger a GoC AP with 50% probability (Figure 6E). These results show that the synchronous activation of a small number of MFs can trigger an AP in GoCs with high temporal precision.

Quantal determinants of the EPSC at mossy fibre - Golgi cell connections

At calycal and climbing fibre synapses the synchronous release of several hundred quanta averages out fluctuations in the release time course, allowing precise temporal signalling with little trial-to-trial variability (Silver et al., 1998; Taschenberger et al., 2005). To investigate how MF-GoC synaptic connections achieve high EPSP-spike precision we examined the quantal content and release time course at this connection. To do this we reduced the release probability by changing the external Ca2+ and Mg2+ concentration from 2/1 to 1/5 (mM), which increased the failure probability from ~0.2 to >0.8 at a single fibre connection. Under these conditions EPSC successes are predominately uniquantal irrespective of the number of release sites present (Silver, 2003). Figure 7A shows a group of evoked uniquantal EPSCs and failures. Averaging successes and correcting for multiquantal contamination gave a mean quantal size across cells of −37±11pA (n=9, see Materials and Methods). This was similar to the estimate obtained by variance/mean analysis (Silver, 2003); Qp = −34±10pA, n=9). Surprisingly, the mean single fibre EPSC amplitude under control conditions was often comparable to the quantal size (Figure 7B). Dividing the mean EPSC amplitude under control conditions (−52±14pA, not significantly different from the average single fibre EPSC across all cells; p>0.2) by the uniquantal size for these cells yielded a quantal content of 1.5±0.4 (n=9). Since the synchronous activation of 4 MFs triggered a GoC spike, our findings indicate that the release of only 6 quanta can generate spike output with high temporal precision.

Figure 7
Release time course and quantal content at mossy fibre - Golgi cell synapses

The rise time distribution of mean quantal waveforms overlapped with the fastest mean stimulus-aligned evoked currents (Figure 7C) in control conditions as did the weighted decay distribution of the quantal and control currents (Figure 7D). Currents in control conditions with slowest decay kinetics typically exhibited a noticeable slow spillover-mediated current component (Supplementary Figure 1Bi-Bii). On average MF-evoked EPSCs in control conditions had a decay that could be fit by a two-exponential function (τ1 = 0.6±0.4ms, A1 = 79±16% and τ2 = 4.4±3.0ms, A2 = 21±16%, n=38). The mean time course of rise-aligned quantal EPSCs, recorded in low calcium solution, was only marginally faster (20-80% rise time = 0.16±0.04ms and a two-exponential decay of τ1 = 0.4±0.1ms; A1 = 85±11% and τ2 = 4.2±2.2ms; A2 =15±11%, giving a τw = 1.1±0.3ms, n=9; Figure 7E). The similarity of the waveforms suggests that the time course of quantal release is brief producing little temporal ‘smearing’.

We quantified the release time course under control conditions by deconvolving the mean evoked EPSC waveform with the mean quantal waveform measured from the same cell (see Materials and Methods; (Sargent et al., 2005). The time course of quantal release under normal conditions increased and decayed rapidly (Figure 7F). Across cells the peak release rate was 4.3±1.2ms−1 and the release function decayed with a time constant of 133±99μs (n=9, Figure 7F). This is comparable to release at giant auditory synapses (Isaacson and Walmsley, 1995; Taschenberger et al., 2005), but slower than reported at the MF-GrC connection (τ = 75 μs; (Sargent et al., 2005). While the 58μs difference between MF-GrC and MF-GoC synapses could reflect differences in the vesicular release process, it could also be due to the lower temperature of the recordings (35°C vs 37°C) and subtle differences in deconvolution methods used (see Materials and Methods). To verify the results obtained by deconvolution analysis we directly measured the time course of quantal release in four cells that had sufficient numbers of events, by examining the latency of uniquantal EPSCs under low probability conditions (Figure 7G). Cumulative release functions for the direct measurement and deconvolution had similar shapes (p>0.5, KS test, Figure 7H, n=4) and their 10-90% rise time were 253±145μs (n=4) and 255±113μs (n=9), respectively. Vesicular release was therefore largely over by the time of the peak of the EPSC (black section on Figure 7F). These results show that highly synchronous vesicular release and a rapid time course of quantal currents allow MF inputs to reset GoC firing, precisely, with only few quanta.

Feed-forward inhibition of granule cells

To investigate the downstream effects of feed-forward excitation of GoCs we made whole-cell voltage-clamp recordings from GrCs. IPSCs were recorded at an average holding potential of 3±6mV (n=19), close to the reversal potential of AMPA and NMDARs. WMT stimulation evoked IPSCs in 16 out of 19 GrCs (84%) and these often had two distinct latency components (Figure 8A, red traces). To test whether the two latency components arose from direct stimulation of the GoC axon and disynaptic activation of the MF-GoC-GrC circuit we blocked excitatory transmission with NBQX (10 μM). This eliminated the longer latency component, confirming its disynaptic origin and left only the short latency monosynaptic IPSC (Figure 8A, black traces). Figure 8B shows individual short latency monosynaptic IPSCs (black traces) recorded in NBQX. Across cells monosynaptic IPSCs had a latency of 1.2±0.1ms, a jitter of 160±100μs and a success probability of 81±20%. IPSCs had a mean amplitude of 33±19pA with rise time of 0.4±0.2ms and a weighted decay of 8±1ms (n=7). Application of Gabazine blocked the outward current confirming that the IPSCs were GABAA receptor mediated.

Figure 8
Feed-forward inhibition of granule cells

The pooled latency distribution of NBQX insensitive (black) and NBQX sensitive (grey) IPSCs is shown in Figure 8C. The two latency distributions were clearly distinguishable allowing us to identify IPSCs arising from the MF-GoC-GrC feed-forward circuitry using a latency criterion (>1.6ms, 3xSDs above mean latency of monosynaptic IPSCs). IPSCs with latencies >1.6ms were observed in 13 of 19 GrCs, suggesting that at least 68% of GrCs received feed-forward inhibition. Of these, 7 exhibited only the long latency IPSCs component (average latency 2.0±0.3ms; range: 1.6-2.2ms, Figure 8D). These disynaptic IPSCs occurred with a success probability of 52±29% (range: 18-91%) and had an average amplitude of 13.3±10.2pA (range: 4.8-31pA). Their mean kinetics were very similar to monosynaptic IPSCs, with 20-80% rise of 0.4±0.1ms and a weighted decay of 7±1ms (p > 0.2, t-test, n=7). Application of 10μM Gabazine also blocked these IPSCs (n=2) indicating that they were GABAA receptor mediated. Feed-forward IPSCs had a latency jitter of 310±140μs (SD; n=7, Figure 8C) as expected for the combined latency jitter of evoked GoC spikes and GoC-GrC transmission (p>0.2; one-sample t-test, see Materials and Methods).

Cells that exhibited disynaptic inhibition in isolation were subsequently hyperpolarised to −70mV to examine whether an excitatory MF-GrC input was also activated, as expected for an intact feed-forward circuit. In 6 of the 7 cells we observed inward EPSCs with latency (0.8±0.2ms), kinetics (20-80% rise time of 0.20±0.02ms and weighted decay of 2.3±1.1ms) and mean peak amplitude (−41±37 pA), similar to single fibre evoked MF-GrC EPSCs previously described (DiGregorio et al., 2002; Sargent et al., 2005). Since 4 MFs are required to fire the GoC, this suggests that more MFs contact a GoC than the average of 4 that contact a GrC. However, the exact number of MF synaptic inputs onto a GoC remains uncertain. Figure 8E shows the timing and average time courses of both the excitatory conductance (EPSG) and the inhibitory conductance (IPSG) for a representative cell. Although the EPSG peak amplitude was 1.5±0.4 times larger than the IPSG (340±230 pS vs 230±130 pS), by the time the peak of the inhibitory conductance occurred the EPSG had decayed by 30±11% so that the inhibitory conductance was comparable in size (Figure 8E, top panel). The time course of the net reversal potential of these two conductances (synaptic reversal potential; see Materials and Methods) is plotted in the middle panel of Figure 8E (solid line). For this cell the synaptic reversal potential drops below spike threshold (red broken line; −40mV; (Cathala et al., 2003) 1.9 ms after the onset of the EPSG due to the inhibitory action of the IPSG. Thus the IPSG restricts the excitatory action of the EPSG to a 1.6±0.3 ms time window (n=6, see Figure 8E). These results confirm that a functional feed-forward inhibitory network is present in the GrC layer and shows that the disynaptic IPSG truncates slow MF-GrC EPSG components, thereby narrowing the time window of synaptic integration.

Discussion

We have examined the functional properties of the previously uncharacterized feed-forward MF input onto GoCs in the cerebellar cortex. Our results show that synchronous activation of 4 MFs can reset the spontaneous firing of GoCs with a precision of around 200μs. This precise EPSP-spike coupling is achieved by the highly synchronous release of few quanta. Spontaneous pacemaker conductances dominate GoC firing rate and introduce a relative refractory period for MF-GoC transmission. These features allow synchronously active MFs to entrain a GoC with high temporal precision at low frequencies but decouples GoC and MF firing during higher frequency stimulation. Recordings from downstream GrCs confirm the presence of a functional feed-forward inhibitory circuit. These results suggest that the MF-GoC-GrC pathway is tuned to transmit the precise timing of coincident MF activity preferentially at low frequencies and at the onset of a high frequency stimulus train.

Properties of the MF- GoC EPSC

The MF-GoC synaptic connection has long been recognized from anatomical studies of the cerebellar cortex (Eccles et al., 1967; Palay and Chan-Palay, 1974), but its functional properties have not been examined. We have used a number of functional and anatomical characteristics to identify MF inputs and distinguish them from CF and PF inputs. A characteristic feature of the MF-GoC connection is the rapid time course of the evoked EPSC. We show that this is generated by highly synchronized vesicular release and fast quantal currents. The time course of evoked EPSCs at the MF-GoC connection is significantly faster than MF-evoked EPSCs in cerebellar GrCs (τWD = 1.6ms vs 2.9ms, respectively; (DiGregorio et al., 2002) although they share the same presynaptic element. The prominent slow current components of the MF-GrC EPSC decay, which are mediated by glutamate spillover onto AMPARs (DiGregorio et al., 2002) and NMDARs (Cathala et al., 2000), are smaller or absent at MF-GoC synapses even though these two connections are made within the same glomerular structure (Eccles et al., 1967). A smaller spillover component could be due to differences in the anatomical arrangement (Cathala et al., 2005), a lower release probability (DiGregorio et al., 2002), an increased activity of glutamate transporters, or lower affinity AMPARs at the MF-GoC synapse than the MF-GrC synapse (DiGregorio et al., 2007). The time courses of quantal and control evoked EPSCs at the MF–GoC synapse are comparable to those between hippocampal GrCs and basket cells (Geiger et al., 1997). Fast EPSCs have also been reported onto other interneurons (Galarreta and Hestrin, 2001; Carter and Regehr, 2002), suggesting that this is common to excitatory synapses in feed-forward inhibitory circuits. Another characteristic feature of the MF-GoC synapse is the lack of STP. Resistance to frequency-dependent depression is likely to arise from rapid reloading of release-ready vesicles in the MF terminal (Saviane and Silver, 2006) and less AMPAR desensitization than at the MF-GrC synapse, where it underlies the majority of the EPSC depression (Saviane and Silver, 2006; DiGregorio et al., 2007).

Properties of EPSP-spike coupling

GoC spikes are triggered predominantly during the rising phase of MF EPSPs, which is determined by the time course of synaptic charge injection. The fast time course of the MF-GoC EPSC is therefore of particular importance in determining AP precision (Fetz and Gustafsson, 1983; Galarreta and Hestrin, 2001). At synapses with few quanta and high quantal efficacy (Gulyas et al., 1993; Carter and Regehr, 2002) the stochastic nature of vesicular release can produce significant temporal jitter in the EPSC timing and shape from trial-to-trial (Sargent et al., 2005) and thus limit EPSP-spike coupling to about 1ms, even when the quantal EPSCs are fast (Miles, 1990; Galarreta and Hestrin, 2001; Carter and Regehr, 2002; Gabernet et al., 2005). Here we show that MF-GoCs synapses counteract this limitation with rapid vesicular release (τ=130 μs) that produces a rapidly rising EPSP (20-80% rise time = 0.42 ms) and introduces little trial-to-trial jitter in the timing of the EPSP (SD~80 μs) even though the quantal content is low. These features allow as few as 4 synchronously active MFs releasing total of 6 quanta to reset spontaneous GoC firing, with high precision.

Our results show that the MF-GoC synapse is effective at signalling the precise timing of coincident MF activity at low input frequencies, close to or below the spontaneous firing rate of the GoC. Rapid EPSC kinetics in combination with active pacemaker currents, which lower the membrane resistance, produce the rapid rise and initial EPSP decay (τ=2 ms), limiting the time window for AP generation. The temporal precision of spike generation that this produces in vitro (200 μs) is likely to represent an upper limit for signalling precision, as the perfectly synchronized activation of MFs used in this study is unlikely to occur in vivo. Precision and phase resetting may also be less precise in vivo because GoC are likely to experience greater synaptic drive than in the slice. Strong after-hyperpolarization (AHP), mediated by M and SK channels (Forti et al., 2006), reduces the efficacy of synaptic input immediately after an AP. Only after about 50ms, is the hyperpolarization overcome sufficiently by depolarizing Ih and sub-threshold Na+ conductances (Dieudonne, 1998; Forti et al., 2006) to allow MF inputs to trigger an AP reliably. Such prolonged membrane hyperpolarization has been shown to improve AP precision in a number of cell types by reducing jitter accumulation during trains (Berry and Meister, 1998; Schaefer et al., 2006) and is likely to contribute to the maintenance of GoC spike-time precision during trains of MF stimulation. But the dominant after-hyperpolarization in GoCs make EPSP-spike coupling much less reliable at higher MF input frequencies, permitting only a weak modulation of GoC firing rate by MF inputs. This rejection of MF rate information contrasts with MF transmission onto GrCs where slow EPSC components arising from spillover onto AMPARs produce a substantial tonic excitatory drive at high firing frequencies (Saviane and Silver, 2006). This together with the wide dynamic range and non-accommodating nature of GrCs firing, promotes the efficient transmission of rate-coded information from MFs to GrCs (Mitchell and Silver, 2003). The distinct properties of the EPSCs and spike generating mechanisms in GrC and GoCs could confer the ability to route information on the timing of a stimulus and more general rate information through separate synaptic ‘channels’ in the cerebellar input layer.

Physiological implications

The cerebellar cortex coordinates movements and maintains balance by computing motor sequences from many types of sensory inputs on time scales from tens of milliseconds to several seconds (Eccles et al., 1967; Orlovsky, 1972; Rosen and Scheid, 1972; Yakusheva et al., 2007). How might the properties of the input layer feed-forward inhibitory circuit aid these functions? Although it is difficult to extrapolate results from the in vitro slice preparation to in vivo function, the properties of the synaptic and cellular components of this circuit suggest that it is tuned to transmit the precise timing of coincident MF activity and then becomes refractory for tens of milliseconds. The size and timing of the inhibitory conductance produced in GrCs, suggest that it could help shape the latency and precision of the early GrC response to sensory stimulation. However, since this circuit is only activated reliably for certain MF input patterns feed-forward inhibition is only likely to be effective in response to some sensory stimuli.

In vivo recordings from MFs and GoCs show a range of behaviours that depend on both the properties and modality of the sensory input. MFs that convey information about joint angle and head velocity are tonically active and show relatively slow modulations in firing rate during sensory stimulation in awake and anesthetized preparations (van Kan et al., 1993; Barmack and Yakhnitsa, 2008). GoCs respond to such sensory input with a modest and relatively slow modulation of their firing rate (Edgley and Lidierth, 1987; Barmack and Yakhnitsa, 2008). Under these conditions the feed-forward circuit may have little effect. In contrast, experiments in decerebrate and anesthetized animals show that tactile stimulation of whiskers and forelimbs evokes a barrage of EPSCs at hundreds of Hertz in GrCs arising from one or multiple MFs, which exhibit low firing rates at rest (Jorntell and Ekerot, 2006; Rancz et al., 2007). At the onset of such sensory stimulation, some GoCs exhibit a temporally precise spike response followed by a pause in firing (Vos et al., 1999; Holtzman et al., 2006), consistent with feed-forward excitation of GoCs, although pauses in firing in the absence of excitation were more commonly observed and had a larger receptive field (Holtzman et al., 2006). These diverse properties of MF inputs and the wide range of GoC responses make it difficult to identify unequivocally the role of feed-forward excitation of GoC from in vivo experiments published to date.

Our results establish that most GrCs receive feed-forward inhibition and suggest that activation of a small number of MFs onto a GoC can trigger phasic inhibition in over a thousand GrCs innervated by its axon (Eccles et al., 1967). The feed-forward inhibitory conductance produced is small, but appropriately timed to cancel the slow component of the MF-GrC EPSC. Previous studies of feed-forward inhibition in other systems suggest that these properties will enhance spike timing precision by reducing the time window for synaptic integration (Pouille and Scanziani, 2001). Feed-forward inhibition could therefore influence the latency and precision of the first GrC spike at the onset of a stimulus, however later spikes are unlikely to be affected by this circuit, because of the inability of GoCs to follow MF high frequency activity. Curiously, fast stimulus-locked inhibition of GrCs has rarely been observed in vivo (Chadderton et al., 2004; Jorntell and Ekerot, 2006). This might be due to the small size of the inhibitory conductance, a developmental change in inhibitory transmission (Brickley et al., 1996; Wall and Usowicz, 1997) and the variability of GoC responses to sensory stimuli (Holtzman et al., 2006). Although further in vitro and in vivo studies are required to determine the role of feed-forward inhibition in the cerebellar input layer, our in vitro characterization of its synaptic and cellular properties suggests that GoCs can extract the precise timing of coincident MF activity and reduce the time window for synaptic integration in GrCs at the onset of certain sensory stimuli.

Supplementary Material

Supplementary Figures

Acknowledgements

Supported by the Wellcome Trust, MRC (G0400598) and EU (EUSynapse LSHM-CT-2005-019055). RAS is in receipt of a Wellcome Senior Research Fellowship. RTK is supported by the Wellcome Trust Neuroscience Graduate Program. We thank Zoltan Nusser for helpful discussions during the project and Beverly Clark, David DiGregorio, Mark Farrant, Padraig Gleeson, Troy Margrie, Zoltan Nusser and Koen Vervaeke for their comments on the manuscript.

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