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  1. Author Response:

    Reviewer #2 (Public Review): Gaffield and Christie trained mice to an interval task of self-initiate bouts of licking to understand how the cerebellar activity relates to the organization of well-timed transitions to motor action and inaction during discontinuous periodically performed movements. Recording and optogenetically stimulating the activities of Purkinje cells, they concluded that the cerebellum encodes and influences the motor transitions, initiation and termination of discontinuous movements. The conclusion of the paper is very interesting and potentially provides insights on the neural mechanism of the previously proposed principle that the cerebellum controls the timings of discrete movements (Ivry et al. 2002). However, in the logic and interpretation to the conclusion I have concerns which they need to address. [Major comments]

    We thank the reviewer for their positive evaluation of our work and their helpful comments. We have substantially altered our manuscript to address their concerns, including an entirely new figure as well as additional supplemental figures.

    First, the activity of Purkinje cells can largely encode each bout of licking movements, in addition to initiation and termination of movements. Figure 2BCEF plays the peak of neural activity around the water time and Figure 2DG indicates the relationship between the neural activity and lick rate. The encoding of the initiation and termination alone cannot explain these observations. Related to this, none of the panels Figure 2BCEF shows a lead of the onset of neural activity to that of the lick rates (around -5 sec to water time). This looks inconsistent with the lead shown in Figure 3. The authors need to explain why such an inconsistency can happen.

    We agree that Crus I and II PCs encode parameters of licking bouts in addition to movement initiation and termination and deeply apologize for not making this point more clearly. To address this concern, we have extensively edited the text in several sections and have added an additional figure to emphasize the richness of the PC representation of behavioral attributes, beyond just initiation and termination alone. We disagree that there is an inconsistency in the lead times differences in our datasets. As the reviewer points out, the water-delivery-aligned firing rate z-scores do not seem to lead the licking rate (Fig. 2B-E). However, these data are averaged across trials with a high variance in the timing of lick initiation relative to water delivery; consequently, it is not possible to assess the timing of PC activity relative to lick bout initiation from these panels. When, by contrast, data are aligned to welldefined licking bouts (i.e., bouts with no licking in the preceding 2 s), it becomes clear that PC firing ramps up in advance of the bouts (Fig. 4C-D). We have edited the text, explaining this rationale, as requested by the reviewer.

    Second, the positive sign of neural modulation indicates biased recording sites. So far, many studies have been indicating the increasing firing modulation at the deep cerebellar nuclei in cerebellar timing tasks and motor tasks (e.g. Ten Brinke et al. 2017 eLIFE for the eyeblink conditioning; Ohmae et al. 2017 JNS for a self-initiate timing task; Becker and Person 2019 Neuron). Ramping-up modulation of Purkinje cells is not able to activate the deep cerebellar nuclei. When the motor-driving module generates negative modulation of Purkinje cells, the neighboring modules can generate positive modulation (e.g. Ten Brinke et al. 2017 eLIFE; De Zeeuw 2021 Nat Rev; Ohmae and Medina 2014 Soc. Neurosci. Abstr.). Because the neighboring modules are much wider than the motor-driving module, recording without identifying the driving modules, as in this study, will result in the recording being biased toward the adjacent modules.

    We too were surprised that we did not observe more negatively modulating PCs. However, our craniotomy was relatively large (>2 mm square) exposing an area over Crus I and II that encompassed zebrin bands 7+, 6-, and 6+. We randomly sampled PC activity within this region, so we don’t think our recordings were necessarily “biased”. We are unaware of any definite experiments showing whether positively and negatively PCs form separate, or convergent, channels of output onto their postsynaptic targets in the cerebellar nuclei. If convergent, then the response of the nuclear neurons will be determined by an ensemble of PCs with time varying signs of activity, in addition to the integration of the activity from pontine collaterals.

    We thank the reviewer for highlighting the developing idea of motor and non-motor cerebellar modules and the loops formed by their connectivity. We have edited our text to address how our recordings could fit into such an organizational scheme and have cited their recent unpublished preprint on this topic, now available on BioRxiv (Ohmae et al. 2021). However, we believe several considerations suggest that both positive and negative modulation of Purkinje cell firing rates will impact movement. (1) Large regions of the cerebellar cortex are capable of evoking or modulating movements when microsimulation is applied. Similarly, optogenetic suppression of IntA activity increases the outward velocity of reaching movements in mice (Becker & Person 2019). (2) In contrast with delay eyeblink conditioning, in which the motor output is an impulse-like twitch, rhythmic movements of the tongue (or, similarly, the limbs) require alternating recruitment and de-recruitment of muscles. Thus, motor commands will necessarily be multiphasic in time, and will tend to be out of phase for populations controlling antagonistic muscles. (3) Excitation of the DCN by collaterals of mossy fibers will likely modulate, and perhaps override, Purkinje cell inhibition. Therefore, further work will certainly be necessary to decipher exactly how potential antagonistic cerebellar modules participate organizing complex motor actions.

    Third, the authors used z scores for the unit of spike rate, but it is more appropriate to use spike per second as in Figure 3CD. In particular, I do not understand the meaning of difference of spike rate in the unit of z score in Figure 3E. The spike rate modulation in Figure 4E looks small which should be evaluated in the unit of spike per second as well. For the analysis of the last lick, the spontaneous spike rates should be displayed, instead of (or in addition to) the spike rate in the middle of lick bouts which should be much higher than the spontaneous spike rate according to Figure 2.

    We appreciate the reviewer’s input regarding style, but the current standard in the neurophysiology field is to report firing rate comparisons from a neural population as z-scores. Z-scoring is particularly useful because this metric provides a probability of an individual score occurring within a normal distribution, as well comparisons of different scores from different normal distributions; it also gives an indication of the raw score differs from the mean, information that isn’t available in spike rate comparisons alone. For these reasons, we elect to not change how we represent our data. However, we have modified our figures to report firing rates for traces from individual example cells as z-scoring is not appropriate for this purpose.

    Forth, I did not understand the conclusion for the optogenetic perturbation. In the result section for Figure 7, I think there is a logical gap between the last conclusion sentence and the sentences before it. The suppression of lick bouts in Figure 7D and the rebound induction in Figure 7G can be explained by the cerebellar contribution to each bout of lick movement (shown in Figure 2). I do not understand if these observations indicate the cerebellar contribution to the initiation and termination of a sequence of lick movements. Also, I have a concern about the location of stimulation sites. The stimulation may cover both the motor-driving module and neighboring modules, which makes the observations difficult to interpret because the stimulation is not specific to the positively modulating Purkinje cells.

    A lick bout is composed of a sequence of tongue protrusions and retractions performed at a highly regular rhythm. Apart from the first lick (Bollu et al., 2021), the motor command for this behavior is under the control of central pattern generators in the brainstem. Said another way, a lick bout is a continuous movement rather than series of discrete actions that are repeatedly started and stopped (they are like stepping during locomotion in some animals). Lick bout initiation and directional control of the bout can be commanded by the cerebral cortex. Given this organization, we do not believe our optogenetic experiment can be interpreted as an effect on the initiation and termination of individual licks because licks are not discrete actions when performed in a consummatory bout. However, based on the reviewer’s recommendation, we investigated how PCs encode information pertinent to individual licks in a bout (Figure 3). Although there was entrainment to individual lick cycles, there were no time-locked responses apparent in their average activity. Instead, there was a continuous mapping of the lick cycle across their population. Notably, licking rhythmicity was disrupted by the optogenetic perturbation, consistent with the influence of PC output on this movement parameter. We have edited the text to address these concerns.

    Fifth, For Figure 8, I had difficulty to understand what kind of activity of Purkinje cells can explain the shift of the peak timing of lick rate, because in the result sections of Figures 2-6 I could not find any activity encoding the peak timing of lick rate. For figure 8EFG, the analysis may not be correct. Because lick onset can be delayed with the photostimulation, in Figure 8E the boundary of onset corresponding to the 1s in control should 1+alpha in stimulation trials to correctly pick up the corresponding trials. Because we do not know the exact values of alpha, I think this analysis is not possible.

    PC ramping activity may contribute to the vigor of the ensuing licking response which would dictate peak licking rate timing. In fact, in many individual PCs, we observed correlations between PC firing and lick rate indicating a relationship. However, this was not borne out in the population response, so we did not pursue it further.

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  2. Evaluation Summary:

    Gaffield and Christie investigate how the cerebellum contributes to the reward-driven, periodic licking behavior by using electrophysiology and calcium imaging in awake mice. The authors reveal that the cerebellar Purkinje cells can signal temporal information about the onset and offset of ongoing movements: this may be potentially important in understanding the mechanism for cerebellar temporal processing. However, further data analysis is required to support the main conclusion.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 agreed to share their name with the authors.)

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  3. Reviewer #1 (Public Review):

    In this manuscript, Gaffield and Christie investigate how the lateral cerebellar cortex contributes in real time to a learned, reward-driven, periodic licking behavior. This addresses an important question, as there is a growing appreciation that cerebellar output plays a key role in discrete aspects of both planned and ongoing voluntary movement, but there remains much debate about what features it controls and how.

    By recording from Purkinje cells (PCs) with both high density silicon probes and genetically encoded calcium indicators during behavior, the authors show that Purkinje cell simple spikes (Sspks) are elevated at the onset and offset of goal-directed movement, and that complex spikes (Cspks) are elevated at the onset of goal-directed movement. Further, optogenetic activation of Purkinje cells can suppress licking, produce licking at the offset of stimulation, and delay the time of peak licking if stimulation occurs in close temporal proximity to lick initiation. As a result, the authors conclude that Purkinje cells convey a timing signal related to the initiation and termination of goal-directed movement. This conclusion is of high potential importance, and many of the observations in this manuscript would be of considerable interest to the broader field of motor control and motor learning. However, in its current form, the manuscript also raises some analysis and interpretation questions that may impact whether or not the main conclusions are justified.

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  4. Review #2 (Public Review):

    Gaffield and Christie trained mice to an interval task of self-initiate bouts of licking to understand how the cerebellar activity relates to the organization of well-timed transitions to motor action and inaction during discontinuous periodically performed movements. Recording and optogenetically stimulating the activities of Purkinje cells, they concluded that the cerebellum encodes and influences the motor transitions, initiation and termination of discontinuous movements. The conclusion of the paper is very interesting and potentially provides insights on the neural mechanism of the previously proposed principle that the cerebellum controls the timings of discrete movements (Ivry et al. 2002). However, in the logic and interpretation to the conclusion I have concerns which they need to address.

    Major comments:
    First, the activity of Purkinje cells can largely encode each bout of licking movements, in addition to initiation and termination of movements. Figure 2BCEF plays the peak of neural activity around the water time and Figure 2DG indicates the relationship between the neural activity and lick rate. The encoding of the initiation and termination alone cannot explain these observations. Related to this, none of the panels Figure 2BCEF shows a lead of the onset of neural activity to that of the lick rates (around -5 sec to water time). This looks inconsistent with the lead shown in Figure 3. The authors need to explain why such an inconsistency can happen.

    Second, the positive sign of neural modulation indicates biased recording sites. So far, many studies have been indicating the increasing firing modulation at the deep cerebellar nuclei in cerebellar timing tasks and motor tasks (e.g. Ten Brinke et al. 2017 eLIFE for the eyeblink conditioning; Ohmae et al. 2017 JNS for a self-initiate timing task; Becker and Person 2019 Neuron). Ramping-up modulation of Purkinje cells is not able to activate the deep cerebellar nuclei. When the motor-driving module generates negative modulation of Purkinje cells, the neighboring modules can generate positive modulation (e.g. Ten Brinke et al. 2017 eLIFE; De Zeeuw 2021 Nat Rev; Ohmae and Medina 2014 Soc. Neurosci. Abstr.). Because the neighboring modules are much wider than the motor-driving module, recording without identifying the driving modules, as in this study, will result in the recording being biased toward the adjacent modules.

    Third, the authors used z scores for the unit of spike rate, but it is more appropriate to use spike per second as in Figure 3CD. In particular, I do not understand the meaning of difference of spike rate in the unit of z score in Figure 3E. The spike rate modulation in Figure 4E looks small which should be evaluated in the unit of spike per second as well. For the analysis of the last lick, the spontaneous spike rates should be displayed, instead of (or in addition to) the spike rate in the middle of lick bouts which should be much higher than the spontaneous spike rate according to Figure 2.

    Forth, I did not understand the conclusion for the optogenetic perturbation. In the result section for Figure 7, I think there is a logical gap between the last conclusion sentence and the sentences before it. The suppression of lick bouts in Figure 7D and the rebound induction in Figure 7G can be explained by the cerebellar contribution to each bout of lick movement (shown in Figure 2). I do not understand if these observations indicate the cerebellar contribution to the initiation and termination of a sequence of lick movements. Also, I have a concern about the location of stimulation sites. The stimulation may cover both the motor-driving module and neighboring modules, which makes the observations difficult to interpret because the stimulation is not specific to the positively modulating Purkinje cells.

    Fifth, For Figure 8, I had difficulty to understand what kind of activity of Purkinje cells can explain the shift of the peak timing of lick rate, because in the result sections of Figures 2-6 I could not find any activity encoding the peak timing of lick rate. For figure 8EFG, the analysis may not be correct. Because lick onset can be delayed with the photostimulation, in Figure 8E the boundary of onset corresponding to the 1s in control should 1+alpha in stimulation trials to correctly pick up the corresponding trials. Because we do not know the exact values of alpha, I think this analysis is not possible.

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  5. Reviewer #3 (Public Review):

    In the present manuscript, Gaffield and Christie studied Purkinje cell (PC) activity in Crus I/II while the mice volitionally performed periodic licking behavior. By conducting series of experiments in vivo, the paper reveals simple spikes ramp up before both the initiation and the termination of lick bouts. These activity changes were unique to simple spikes and not detected in complex spikes analyzed by calcium imaging. Most importantly, the onset of ramping in simple spikes occurred hundreds of milliseconds before the lick initiation and this time window was longer for the licks driven internally than the licks triggered after the water delivery. The necessity of the patterned simple spike activity in behavioral timing was further validated by disrupting PC activity by optogenetics. The role of the cerebellum in internal timing is a highly debated topic, and this manuscript delivers a novel aspect of simple spikes in a self-initiated timed behavior. The experiments are well designed, and the analyses are thorough. However, some of the results need clarifications to support their conclusions.

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