Pausing Purkinje Cells in the Cerebellum of the Awake Cat

A recent controversy has emerged concerning the existence of long pauses, presumably reflecting bistability of membrane potential, in the cerebellar Purkinje cells (PC) of awake animals. It is generally agreed that in the anesthetized animals and in vitro, these cells switch between two stable membrane potential states: a depolarized state (the ‘up-state’) characterized by continuous firing of simple spikes (SS) and a hyperpolarized state (the ‘down-state’) characterized by long pauses in the SS activity. To address the existence of long pauses in the neural activity of cerebellar PCs in the awake and behaving animal we used extracellular recordings in cats and find that approximately half of the recorded PCs exhibit such long pauses in the SS activity and transition between activity – periods with uninterrupted SS lasting an average of 1300 ms – and pauses up to several seconds. We called these cells pausing Purkinje cells (PPC) and they can easily be distinguished from continuous firing Purkinje cells. In most PPCs, state transitions in both directions were often associated (25% of state transitions) with complex spikes (CSs). This is consistent with intracellular findings of CS-driven state transitions. In sum, we present proof for the existence of long pauses in the PC SS activity that probably reflect underlying bistability, provide the first in-depth analysis of these pauses and show for the first time that transitions in and out of these pauses are related to CS firing in the awake and behaving animal.

and recently in preliminary data from rats (Lev et al., 2006). It is important to mention that all of these represent passing, anecdotal references to the existence of pauses and completely lack any quantifi cation of the phenomenon, let alone a detailed analysis. The exception to this is Lev et al. (2006), which is a conference abstract that refl ects a small sample size and limited analysis. Nevertheless, the existence of such long pauses has begun to play a key role in contemporary models of cerebellar function (Fernandez et al., 2007;Jacobson et al., 2008;Loewenstein et al., 2005). The fi eld is therefore in need of convincing proof of the existence of such pauses and a thorough analysis of their characteristics in the awake animal is required in order to settle the controversy and provide the basis for serious modeling. Another prominent issue in the current controversy revolves around the relationship of long pauses in SS activity to that of the second PC neural signature, the CS. In intracellular and extracellular recordings from anesthetized animals and in in vitro experiments, the CS can trigger a transition either from the pausing state of the PCs to its active state or vice versa (Loewenstein et al., 2005;Schonewille et al., 2006). This striking link between the two spiking signatures of the cerebellar PCs has never been observed to occur in the awake and behaving animals and is both surprising and diffi cult to explain with current cerebellar models.
To address the current controversy concerning (1) the existence of long pauses in the SS spiking activity in the awake animal and (2) their link to CSs, we recorded the extracellular neural activity of PCs in awake, behaving cats. We report the existence of such long pauses in the SS fi ring pattern in a large proportion of PCs, provide in-depth analysis of these pauses, and show that transitions in and

INTRODUCTION
Cerebellar Purkinje cells (PC) are one of the most physically striking and enigmatic neurons in the central nervous system. The PC is the only neuron capable of generating two different forms of spikes (Bell and Grimm, 1969): simple spikes (SS) and complex spikes (CS). The cerebellar PC has also been shown to have bistable membrane potentials in vitro (Llinas and Sugimori, 1980;Tal et al., 2008;Williams et al., 2002) and recently in vivo in anesthetized animals (Loewenstein et al., 2005;Schonewille et al., 2006). The membrane potential of the PC has been shown to transition between a depolarized state (often referred to as the 'up-state') and a hyperpolarized state (often referred to as the 'down-state'). Furthermore, the state of the membrane potential is mirrored in the SS fi ring rate: SSs occur solely when the PC membrane potential is in the 'up-state' ('active state') and pause their fi ring during the 'down-state' ('pausing state'). The pausing state can last for periods ranging from several hundreds of milliseconds up to several seconds (Loewenstein et al., 2005;Schonewille et al., 2006). Although the existence of these long pauses in the SSs activity, presumably refl ecting underlying membrane potential bistability, is unarguably observed in vitro and in anesthetized animals, their existence in the awake animal is highly controversial and is currently a matter of heated debate. On the one hand, a recent report failed to observe these long pauses in the awake animal (Schonewille et al., 2006). On the other hand, long pauses in SS fi ring in awake, behaving animals have been observed, without any detailed analysis of these pauses, in the cerebella of awake mice (Servais et al., 2004), cats (Armstrong and Rawson, 1979;Edgley and Lidierth, 1988;McCarley and Hobson, 1972), monkeys

MATERIALS AND METHODS
Data was collected from two healthy cats -M (4.5 kg) and K (6.5 kg), both approximately 2 years old -obtained from a certifi ed animal facility at Weizmann Institute of Science (Rehovot, Israel). Cats were group-housed, provided with water ad libitum and food twice daily. Treatment complied with the regulations of Ben-Gurion University and the State of Israel. The experiments were approved by the University ethics committee.
Both cats underwent MRI scans (Magnetic Resonance Imaging Center at Soroka Hospital, Beer Sheva, 1.5 Tesla, Philips Intera) before and after surgery to establish desired chamber implantation and plan penetrations (Figure 1 and Movie in Supplementary Material). A recording chamber and head holder were implanted under gas anaesthesia (isofl ourane, 1%) in antiseptic conditions. The recording chamber covered a craniotomy extending from the tentorium to the bony ridge on the right side of the midline, exposing the cerebellum.
Before surgery, cats were trained for a period of approximately 2 months to sit quietly in a support frame using food reward. Cats received food mixture delivered through a tube placed near the cat's mouth by a pump activated manually by the experimenter every 1-3 min to ensure the animal remained awake. Regular vocalization also demonstrated wakefulness. The experimental setup is demonstrated in Figure 2 in Supplementary Material. After surgery, cats were accustomed to head restraint for 1-2 weeks before neural recording began.
Neural activity was recorded using one to four glass coated tungsten microelectrodes (impedance 0.6-1.5 MΩ at 1 kHz, Alpha-Omega Engineering, Israel) inserted using microdrives (NaN Instruments, Israel) into the cerebellar cortex. The signal was amplifi ed (×10,000), fi ltered (1-10,000 Hz), digitized at 25 kHz, and stored to disk (AlphaLab Pro, Alpha-Omega Engineering, Israel). We also recorded the TTL signal activating the feeding pump and the sound from the microphone, used to identify licking and vocalizing. We isolated neurons offl ine using custom Matlab (MathWorks) code developed by Beerend Winkelman and Prof. Maarten Frens (Erasmus University, Rotterdam) employing principal component analysis (Figure 3 in Supplementary Material). SSs and CSs were considered isolated from a single PC if the CS caused a statistically signifi cant 8 ms pause in SSs (Figure 4 in Supplementary Material).
Pausing Purkinje cells (PPC) and continuous fi ring Purkinje cells (CFPC) were categorized using the coeffi cient of variation of the inter spike interval [ISI; CV ISI = std (ISI)/mean (ISI)] with PPCs having CV > 1. It should be emphasized that the selection of a single categorization method was not critical as other categorization methods including bi-exponential fi t to the ISI histogram (see below), or testing for unimodality of the instantaneous fi ring rate (IFR) distribution (dip test, Hartigan, 1985) gave identical categorization, as shown in Section 'Results' . Pauses in PPCs were defi ned as ISIs above the cell's pause threshold. Our approach for defi ning the pause threshold was to provide a method which would take into account the variability in baseline fi ring rates between different PCs rather then using a fi xed threshold disregarding this variability. For example: a pause of 100 ms might seem unusual if a cell has a baseline fi ring rate of 80 Hz but is not very surprising if the baseline fi ring rate is 10 Hz. Thus, in order to determine the pause threshold on a per-cell basis, we modeled ISIs of PPCs as a mixture of two Poisson processes. The faster process, generating relatively short ISIs, is responsible for the active state, and the slower process generating the long ISIs is responsible for pausing state. Under this model, the ISI frequency should drop off as a bi-exponential: Because the waiting time of a Poisson process has an exponential distribution, it should appear linear on a semi-log scale and the two separate Poisson processes, if they indeed exist in the data, should appear as a combination of two linear segments. We generated a semi-log plot of the number of ISIs as a function of bin size (t). The initial bin size was the median ISI time, but bins with less then 20 ISI detections were combined with successive bins so that there were at least 20 counts per bin, this in order to reduce noise in the algorithm which might arise due to bins with very low counts. A non-linear fi tting routine (MATLAB, lsqnonlin) found parameters A 1 , A 2 , λ 1 , and λ 2 that minimized the difference between the log of the function above (Eq. 1) to that of the histogram. We then selected the threshold which minimized the probability of error: the point where the two exponentials intersect. For CFPCs, the non-linear minimization routine either did not converge or converged to a solution in which both exponents were identical, implying a single Poisson process. This never occurred for the PCs classifi ed as PPCs. For those cells, the fi t was always successful and the two time constants were well separated, implying the existence of two Poisson processes. Thus, the bi-exponential analysis used to identify pauses could also be used to distinguish PPCs from CFPCs providing additional support for our categorization. We also examined (1) different absolute pause thresholds (such as 158 ms, the longest SS ISI observed during the up-state in all intracellular recordings by Schonewille et al., 2006), (2) different methods of extracting the threshold from the ISI histogram and (3) a defi nition of pauses as an unbroken sequence of ISIs above the cell's pause threshold. In the last defi nition, a pause might contain an isolated spike surrounded by long ISIs. None of these variations caused a signifi cant change in any of our results.
As a further comparison between the ISIs of the PPCs and CFPCs, we calculated the skewness and kurtosis of the log 10 of the ISIs distribution (Schonewille et al., 2006): (2) and the IFR distribution, a measure of fi ring rate distribution un-biased by bin size selection: Following recent reports assessing the bimodality in PC SS activity (Loewenstein et al., 2005;Schonewille et al., 2006), the deviation of IFR from unimodality was tested using the dip test (Hartigan, 1985). The dip test was calculated by sampling the IFR distribution at a number of points equal to the number of spikes generated by the test. Statistical signifi cance was evaluated by calculating the same dip statistic on 5,000 random redistributions of the spikes over the time interval.
To evaluate the contribution of long pauses to the overall PPC fi ring pattern we computed the variance explained by the pauses. This variance is the total variance of the fi ring rate minus variance within the active state and the variance within the pauses (see formula below). Variance in fi ring rate during pauses was always 0 as there were no spikes during pauses: CS relation to state transitions was examined using a peristimulus time histogram of CS around transitions binned at 50 ms. Signifi cance was tested on four bins (the bins before and after both up-and down-state transitions) whose fi ring rate was tested against the overall fi ring rate of the neuron using a z-test with a Bonferroni corrected signifi cance of p < 0.05 (p < 0.0125 for each bin).
For each cell achieving signifi cance, we measured the percentage of CS related to state transitions and state transitions related to CS using a fi xed window of 60 ms. For example, if the signifi cant bin was the bin before the start of a pause, we counted the number of CSs that occurred in the 60 ms before the start of a pause and divided by the total number of CSs. Similarly, we counted the number of pauses that began within 60 ms after a CS and divided by the total number of pauses. If the signifi cant bin was after the start of a pause, the windows were taken in the opposite direction. Similar counts were made if signifi cance was found before or after the end of pauses. We tested the validity of the 60 s window width by developing an algorithm where the window was determined for each cell by determining the width in which CS fi ring was elevated relative to the overall fi ring rate (see Methods and Data in Supplementary Material).

RESULTS
We performed 52 recording sessions (M 35, K 17) with a total of 82 electrodes (M 50, K 32) and recorded 38 well identifi ed PCs (M 22, K 16). Recordings in cat M are from vermal lobuli VI ( Figure 1 and Movie in Supplementary Material) and showed orofacial somatosensory response in agreement with previous recordings from this region (Mano et al., 1996). In cat K, technical diffi culties impeded precise localization. We estimate that our recordings were lateral-caudal to those in cat M, probably in crus II. Neurons responded during vocalizations and there was little or no response to orofacial stimulation. Neuronal recordings lasted between 130 and 790 s (mean 373 s). Mean SS fi ring rate was 47 ± 24 Hz; mean CS fi ring rate was 1.3 ± 0.4 Hz. There was almost no difference between the two cats (mean SS fi ring rate M/K = 47.6/45.9 Hz, mean CS fi ring rate M/K = 1.2/1.3 Hz).

PAUSING AND CONTINUOUS FIRING PURKINJE CELLS EXIST IN THE CEREBELLAR CORTEX OF THE AWAKE ANIMAL
Previous work in vitro and in vivo in anesthetized animals have shown that PCs often exhibit long pauses in their SS fi ring, strongly associated with the PC membrane potential down-state, ranging from hundreds of milliseconds up to several seconds (Loewenstein et al., 2005;Schonewille et al., 2006). Our primary aim was to examine whether such pauses exist in the cerebellar PCs of the awake animal. As we show below, we found many PCs exhibiting such pauses and called these cells PPCs. Other cells were always active and we called these cells CFPCs. The differences between the two groups of cells were robust and we later show that different methods of categorization produced identical categorization of the cells. Figure 1 presents data from two PPCs (Figures 1A,B) and one CFPC (Figure 1C), showing the difference in fi ring patterns between these two groups of PCs: PPCs were constantly changing their states between active fi ring and long pauses. As can be seen in the rasters and raw traces presented in Figures 1A,B  It should be noted, that the latter cells, in comparison to the cells where the second peak was clearly visible, did not exhibit unusually long pause lengths (p > 0.5). Rather, the pauses occurred more frequently (p < 0.005) resulting in the cell spending more time pausing (p < 5e − 5) which explains the larger peak near 0 fi ring rate. These cells also fi red at a signifi cantly lower frequency in the active state (p < 0.005) which explains the proximity of the second peak to the fi rst and makes it hard to discern by eye. Thus, in order to have an objective assessment of the nature of the distribution, we tested for bimodality in fi ring rates of both PPCs and CFPCs using the dip test, a statistical method that assesses the deviation of a distribution from unimodality. Using this method we found that the IFR distributions of all PPCs were signifi cantly multimodal [ Figures 1A(III),B(III); p < 0.0009]. On the other hand, no CFPC IFR histogram ever had a peak near 0 and they were all unimodal both by eye and according to the dip test [ Figure 1C(III); p > 0.2]. The bimodality and unimodality in the fi ring rate distribution of the PPCs and CFPCs was maintained using either the IFR, a method that does not depend on arbitrary bin size selection, or by calculating the fi ring rate using fi xed bin sizes (see Figure 5 in Supplementary Material).
The bimodality of the IFR histograms led us to hypothesize that the ISIs for PPCs could be modeled as the combination of two Poisson-like processes. Indeed, we found that we were able to fi t the ISI histogram of the PPCs using a bi-exponential (Eq. 1), which looks like two separate straight line segments on a semi-log plot [ Figures 1A(IV),B(IV)]. Consistent with our results of the unimodality of the CFPCs we found that the ISI histograms of CFPCs had a single exponential drop off, that is, a single line on a semi-log plot [ Figure 1C(IV)], and we did not succeed in fi tting a bi-exponential to any of the CFPCs histograms.
In order to consider the differences in fi ring patterns of the various PPCs, we used parameter estimates from the bi-exponential fi t to determine a pause threshold by minimizing the error in pause detection (see Materials and Methods). This process resulted in a per-cell pause threshold defi nition which considered each cell's individual SS fi ring pattern used in later analysis.

DIFFERENCES IN FIRING PATTERNS BETWEEN PAUSING AND CONTINUOUSLY FIRING PURKINJE CELLS
PCs could easily be categorized as being PPCs or CFPCs by several methods all resulting in identical categorization.
(1) A bi-exponential fi t to the ISI histogram: cells for which the fi t produced two distinct exponentials were PPCs and the rest were CFPCs.
(2) The CV value of the ISIs: The CV of the ISIs was >2.4 for all PPCs and <0.9 for all CFPCs (Figure 2). Across the population, CV values were 2.07 ± 0.32 (mean ± SEM), in agreement with a recent report (Shin et al., 2007). (  Independently of all methods specifi ed above, the same categorization could also be obtained visually (as seen in Figure 1). Other measures distinguished PPCs and CFPCs statistically. In agreement with recent fi ndings in anesthetized animals (Schonewille et al., 2006), the ISI distribution of PPCs had larger skewness and kurtosis and lower fi ring rates (Figure 2A; p < 0.001 for all tests). SS fi ring rates during PPC active states were also lower then CFPC fi ring rates ( Figure 2B; p < 5e − 5). Differences in fi ring rate for the CSs did not reach signifi cance (Figure 2C; p > 0.12, Bonferroni corrected). Also, PPCs spent a signifi cantly larger fraction of time in long ISIs than CFPCs (p < 1e − 5, Sidak-Holm correction; Figure 2E), mirroring fi ndings in anaesthetized animals (Schonewille et al., 2006, Figure 1E). CFPC ISIs were usually <200 ms whereas those of PPC often were as long as several seconds. There was no difference in the CS ISIs between the two groups ( Figure 2F; p > 0.35). Variance in the SS activity explained by pauses ranged from 19.2 to 48.9% (mean of 32.7%; Figure 2D) indicating that pauses were signifi cant in the overall activity of these cells but that the variation in the up-state fi ring rate was at least as signifi cant. PPC pause thresholds determined using our algorithm averaged 189.8 ± 64.5 ms (mean ± STD), and mean pause length averaged 701.2 ± 329.3 ms (mean ± STD). Pause frequency was 0.54 ± 0.23 Hz (mean ± STD across cells), and the amount of time neurons spent pausing varied from 9.5 to 86.7% (median 28.1%). Active states had average durations of 1,357.3 ± 995 ms (mean ± STD). There was no signifi cant difference between the two cats in any of these parameters (p > 0.2 for pause thresholds, p > 0.5 for mean pause lengths, p > 0.5 for pause frequencies, p > 0.2 for the amount of time spent in pause, p > 0.15 for the mean active state duration).

LINKING COMPLEX SPIKES AND STATE TRANSITIONS
In vitro and in anesthetized animals, state transitions can occur spontaneously, and it has recently been shown that mossy-fi ber input can shift PCs to the up-state via direct excitation from granule cells and to the down-state by indirect inhibition via molecular layer interneurons (Jacobson et al., 2008). In addition, the CSs have also been shown to trigger both down-up and up-down-state transitions. However, this phenomenon has thus far been observed exclusively in vitro and in anesthetized animals (Fernandez et al., 2007;Loewenstein et al., 2005). We explored whether this intriguing connection between the CS spiking and SS pausing also exists in the awake animal. We found that up-down and down-up transitions in PPCs often occurred in close conjunction with CSs. Figure 3A demonstrates this in an extracellular voltage trace, and Figure 3B shows the cell's CS activity aligned on the two directions  (Figures 4A,B, respectively). Overall, 25 ± 2.9% (mean ± SEM) of state transitions occurred in close conjunction with CS events, compared with 6% for the randomized data (a signifi cant difference, Figure 4A, p < 5e − 7). 12 ± 2.1% of all CSs (mean ± SEM) were associated with state transitions. This percentage is higher then the mean value of 3% obtained for the randomized data ( Figure 4B) and signifi cantly different from random for all cells (p < 5e − 4). We tested this analysis by developing an algorithm that identifi ed for each cell the optimal window in which CSs and state transitions can be considered related (see Methods and Data in Supplementary Material). Using the algorithm we obtained qualitatively identical results with no signifi cant difference (see Figure 8 in Supplementary Material). Thus, in agreement with recent data from anesthetized animals (Loewenstein et al., 2005;Schonewille et al., 2006) we fi nd that many of the state transitions are closely related to CS events and vice versa.

DISCUSSION
Long pauses in SS activity were evident in half of the cells we recorded in non-anesthetized cats. PPCs repeatedly transitioned between active fi ring and long pauses whereas CFPCs did not pause. The two PC categories were well separated on coeffi cient of variation, bi-exponential fi t to the ISI histogram, and bimodality of the IFR suggesting that the categories are not artifacts of any particular data analysis. Because our recordings were from awake and behaving animals, an alternative explanation that these pauses were simply the result of synaptic inhibition due to behavioral events, a well known feature in the central nervous system (Kandel et al., 2000), must be considered. However, we can exclude this possibility because although the behavioral events elicited neural responses in the majority of cells in both the PPC and CFPC groups, we never observe a shift in category or an obvious disruption of the cell's activity (see Figure 6 and Data in Supplementary Material). That is, pauses in SS activity were distinct from behavioral modulation of fi ring rate: PPCs continued to transition in and out of pauses both during behavioral events and in their absence and CFPCs did not change their continuous fi ring pattern. Finally, we observed none of the high frequency bursts of neural activity associated with injured cells in any of our PCs. Taken together with a lack of difference between the PPC and CFPC groups in (1) CS fi ring rates, (2) recording duration, (3) stability of the spike waveforms, and with the fact that CSs continued to occur regularly during the SS pauses, we are confi dent that our results were not biased by unstable recording or recordings of injured cells.
Can the pausing behavior we observed be the result of the underlying PC membrane potential bistability previously reported both in vitro as well as in vivo in anesthetized animals? First, it should be emphasized that the question of bistability in the awake animals is in its essence a question of the PC membrane potential state and can thus only be truly solved using stable intracellular recordings in the awake animal, a technically complicated matter. Yet, two arguments lead us to believe that extracellular recording can provide a good answer to this question. First, recent fi ndings have shown that the state of the PC membrane potential can be reliably deduced from the temporal pattern of the extracellulary recorded SS activity. This is because (1) simultaneous intracellular and extracellular recording of SSs and CSs showed a perfect match as every SS and CS recorded intracellular corresponded to a matching single spike in the extracellular voltage trace (Schonewille et al., 2006), and (2) SSs occur during the membrane potential up-state and cease to occur during the down-state (Loewenstein et al., 2005;Williams et al., 2002) and are thus a reliable indicator of the state of the membrane potential. Second, cerebellar PC bistability has several distinctive features which can be evaluated in extracellular recordings. Comparing these traits between the PCs SS pausing behaviour to its intracellular parallel, obtained recently from anesthetized animals, lead us to believe that the pausing behaviour we observed might refl ect underlying PC membrane bistability: (1) the most prominent feature of bistability is the existence of long pauses in SS fi ring interleaved with active periods, in agreement with our observations in the PPCs, (2) in contrast to the SS long pauses and in agreement with recent fi ndings on bistability, the CS fi ring rate did not change during the pauses, nor did the CS exhibit unusually long pauses in their activity, (3) PC bistability is unique in that the SS pauses, caused by the membrane potential down-state, often occur in close conjunction with CSs, and in our data over 25% of state transitions occurred near CSs, much higher then what would be expected by random, (4) we observed pauses that lasted around 700 ms, consistent with the time scale of pauses observed intracellular in vivo under isolfurane anesthesia (800 ms by Schonewille et al., 2006) and only slightly lower then the values reported under ketamine/xylazine anesthesia (1200 ms by Schonewille et al., 2006and 1500ms by Loewenstein et al., 2005, (5) the mean duration of the active states we observed were 1350 ms, consistent with the average values obtained intracellular in vivo under both forms of anesthesia (1100 ms using isolfurane by Schonewille et al., 2006 and 1450 using ketamine/xylazine by Loewenstein et al., 2005). Thus, it would appear reasonable to speculate that the pauses we observed in the awake animal refl ect the underlying bistability in the PC membrane potential.
Our fi ndings contrast with a recent report in mice that sought pauses in awake animals (Schonewille et al., 2006), but we are in agreement with recent results obtained in vivo both in anesthetized rats and guinea pigs as well as with preliminary observations obtained in rats, where long pauses in SS activity have been observed (Lev et al., 2006;Loewenstein et al., 2005). The discrepancy between Schonewille's results and other researchers is hard to explain. It might refl ect differences in experimental procedures and/or different recording locations, but we believe that the most probable explanation for this discrepancy resides in the species difference: Schonewille's data is from mice whereas our results were obtained from cats. This claim is bolstered by the fact that Schonewille et al. (2006) results under ketamine/xylazine anesthesia, where pausing is not disputed, were dramatically different from recent fi ndings obtained from rats and guinea pigs using the exact same anesthetic procedures (Loewenstein et al., 2005). Specifi cally, Loewenstein reported pausing in 100% (24/24) of PCs, Schonewille reported only 60% (6/10). Moreover, the percentage of time the membrane potential was hyperpolarized in Schonewille was reported to be 3 ± 2% in contrast with 52 ± 4% reported by Loewenstein. Thus, Schonewille's results in mice were generally much lower then in other species which suggests that the generality of Schonewille et al. (2006) results to other species is questionable. What might be the functional role of the long pauses in the behaving animal? We found that a signifi cant fraction of SSs fi ring rate variance was explained by the pauses. However, we did not fi nd a link between the behavioral events that drove variation in the SS fi ring rate in our cells and the pauses. However, we also did not fi nd a correlation between the CS fi ring rate and the behavioral events. As we have shown here, over 25% of state transitions were closely related to CSs. This percentage is well above what would be expected by chance, but cannot be taken as evidence either for or against a causal relationship. One possibility is that our behavioral setup simply did not require the functional role of the pauses mediated by the CSs. If so, we would predict that a task that causes changes in the rate of CS fi ring will also cause correlated changes in the rate of pausing. Indeed, in a recent paper where the modulation of state transitions by sensory events were examined in the anesthetized animal, an air puff stimulation eliciting an increase in CS fi ring rate resulted in a dramatic increase in state transition aligned on the air-puff. In that work, over 66% of elicited CSs caused state transitions (Loewenstein et al., 2005). This indicates that pauses in the SS fi ring may have important functional roles.
The current prevailing hypothesis of cerebellar function suggests that the cerebellar output through the deep cerebellar nuclei (DCN) is determined by the PC SS and that the CS serve as a teaching signal (Kandel et al., 2000). A current problem with this theory is that the high fi ring rate and powerful convergence from the PC layer to the DCN means that DCN neurons are bombarded with an enormous amount of inhibitory input (Ito, 1984). It is possible that long pauses in PCs cause sudden and powerful reductions in this inhibition, leading to release fi ring of the DCN. This would be especially true if there is synchronization of SS pauses within cerebellar microzones (Andersson and Oscarsson, 1978;Sugihara et al., 1999): a small cluster of neurons in the inferior olive (IO) can generate nearly simultaneous CS throughout the extent of a single cerebellar microzone, and thus CS fi ring could lead to synchronous pause onset and offset in the cerebellar cortex microzone which in turn will either silence or activate a single DCN. The outcome of such a process across the entire cerebellar output might result in a simple temporal pattern from the cerebellum outward. An alternative theory suggests that long pauses in SS activity are crucial for cerebellar timing but via a different mechanism. This theory, based largely on the complex patterns of synchrony that can develop in the IO network, suggests a reversal of roles between the cerebellar cortex and the IO, the model suggests that long pauses in SS fi ring pattern reconfi gure the IO network through the DCN enabling the generation of temporal patterns in the olivary output (Jacobson et al., 2008).
In sum, we found PCs in the cerebellar cortex of awake cats exhibiting long pauses in their fi ring rate and provided the fi rst in-depth analysis of these pauses. We also reported here, for the fi rst time in the awake animal, the modulation of the PC SS state transition by CS events. Further work is needed, specifi cally involving intracellular recording from the PC of awake animals, to provide conclusive evidence of whether the pauses we observed are due to the underling bistability of the PC membrane potential. Future work aimed directly at addressing the role of these pauses in mediating behavior, specifi cally involving simultaneous recordings from multiple PCs and from cerebellar cortex and DCN, is required to decipher the function of these pauses in mediating cerebellar output in the awake and behaving animals.

CONTRIBUTIONS
Michael M. Yartsev: experimental design, experimental procedures, data collection, data analysis, and writing of the manuscript; Ronit Givon-Mayo: experimental design, experimental procedures and data collection; Michael Maller: experimental procedures and data collection; and Opher Donchin: experimental design, experimental procedures, data analysis, and writing of the manuscript