The environment provides constantly updating sensory signals that must be acted upon for an animal to perform basic behaviors necessary for survival, including navigating through the environment, feeding/foraging, and other goal-directed behaviors. These perception and action loops require various sensory modalities (i.e. somatosensation, audition, and vision) to be integrated and translated into directed motor output. Both the cerebral cortex (Stein and Stanford, 2008) and the cerebellum (Snider and Stowell, 1944; Rondi-Reig et al., 2014; Baumann et al., 2015) are major brain regions involved in this sensorimotor integration and translation. Connections between these two brain regions form one of the largest projection pathways in the brain and selective expansion of this cortico-cerebellar system occurs across evolution (Gutiérrez-Ibáñez et al., 2018; Smaers and Vanier, 2019). This reflects the importance of cerebrocerebellar communication, however, the precise functions of these pathways are not fully understood (Apps and Watson, 2013). A vital initial step in understanding the role of cerebrocerebellar communication is to have a comprehensive map of the pathways linking these two structures as well as the precise organization of the termination of these pathways within the cerebellum.

Due to the indirect nature of cerebrocerebellar connections, it has been difficult to study their organization in precise detail. While a large body of research has mapped out the corticopontine projections (Brodal and Bjaalie, 1997; Glickstein, 1997; Leergaard and Bjaalie, 2007; Proville et al., 2014) or the pontocerebellar projections (Pijpers and Ruigrok, 2006; Pakan et al., 2010; Proville et al., 2014; Biswas et al., 2019), few studies have utilized neurotropic viruses (Kelly and Strick, 2003; Suzuki et al., 2012). Therefore, the precise routes for information flow from the cortex to the cerebellum, including detailed terminal organization in the highly modular cerebellar cortex, have remained largely inferred. The integration of multimodal inputs to the cerebellum is a fundamental operation that would allow for the precise coordination of sensory-driven movements within this brain region. Anatomically, the potential for a single granule cell to receive multimodal input via both descending motor cortex and ascending proprioceptive pathways has been shown in mice (Huang et al., 2013). However, the potential for co-innervation originating from various cortical areas spanning multiple modalities is unknown, even on the regional level in the cerebellum, and has consequences for the role of cerebro-cerebellar-cerebro feedback loops in learning and predictive motor control (e.g. Chabrol et al., 2019).

Using a mono-trans-synaptic anterograde viral tracer (Zingg et al., 2017; Zingg et al., 2020), we investigated the precise cerebrocerebellar pathways from key sensory, motor, and association regions of the cortex via the pontine and other intermediate precerebellar nuclei to all regions of the cerebellar cortex (Figure 1A–C); ultimately providing a map of the potential pathways linking various functionally specific cortical regions with the cerebellum. Following injections into the primary motor (M1), somatosensory (S1), visual (V1), auditory (A1), posterior parietal association cortex (PPC), and the dorsal field of auditory cortex (AuD), we found a highly organized topography of labeled pontine cells, with the notable exception that injections into A1 produced only terminal labeling in the pons; indicating the lack of a A1-ponto-cerebellar pathway in mice. We quantified the number of resulting mossy fiber terminals and described their relationship to the internal organization of the cerebellum. The majority of labeled mossy fiber terminals from the primary sensory and motor cortical regions were in the contralateral cerebellar hemisphere, whereas from association cortices this laterality was less evident. Cortical influences were not restricted to the cerebellar hemispheres, as terminals spanned all regions of the cerebellar cortex, with biases depending on the cortical modality. Cerebellar subdivisions with the highest regional co-innervation of multimodal inputs were crus I, the paraflocculus (PFl), vermal lobule VI and lobules IV/V, highlighting the potential for modular multimodal processing of information originating from the cerebral cortex.

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To examine the topography of cerebrocerebellar pathways from primary sensory and motor cortical regions as well as sensory association areas, we utilized an AAV1.cre construct that has been shown to act as a trans-synaptic anterograde tracer that crosses a single functional synapse (mono-trans-synaptic; Zingg et al., 2017; Zingg et al., 2020). We injected AAV1.cre into various cortical regions in tdTomato reporter mice and quantified the resulting labeled precerebellar pathways and mossy fiber terminals in the cerebellum (Figure 1). Target cortical areas included M1 (forelimb/hindlimb regions), S1 (forelimb/hindlimb regions), PPC, V1, A1, and AuD (Figure 1A,D; three mice per target region; see Supplementary file 1A).

Anterograde tracing of indirect cerebrocerebellar pathways

Following cortical injections, mono-trans-synaptically labeled cells were found in the ipsilateral basal pontine nuclei (referred to as pontine nuclei throughout) from all cortical target regions, with the exception of A1 (Figure 1E). In contrast, after injections in the more dorsal secondary auditory region, AuD, a corticopontine pathway was observed (Figure 1E). The lack of corticopontine projections from A1, was confirmed by injecting CAV.cre into the pontine nuclei; this viral vector is preferentially taken up by axon terminals, resulting in retrograde labeling. Here we found retrogradely labeled cells in AuD and more ventral auditory cortex (AuV), but no labeled cells in A1 (Figure 1—figure supplement 1). Although anterogradely labeled cell bodies were not observed in the pontine nuclei following AAV1.cre injections in A1, labeled fibers were found in the dorsomedial portion of the ipsilateral pons (Figure 1E; Supplementary file 1B). These fibers could be either traversing through the pons, potentially towards lower brainstem structures (e.g., cochlear and vestibular nuclei see Figure 2A; see also Budinger et al., 2000), or disynaptic terminals resulting from labeled indirect pathways from A1 to the pontine nuclei, likely via the inferior colliculus (Schuller et al., 1991b; Caicedo and Herbert, 1993). Indeed, anterogradely labeled neurons were consistently observed in the inferior colliculus after A1 injections (Figure 2B) and following injection of AAV1.cre in the inferior colliculus, anterogradely labeled cells were found in the pontine nuclei as well as mossy fiber terminals in the cerebellum, demonstrating the potential for a trisynaptic A1-collicular-cerebellar pathway via the pontine nuclei (Figure 1—figure supplement 2).

Figure 2

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In agreement with previous studies (Leergaard and Bjaalie, 2007; for review see, Kratochwil et al., 2017), resulting pontine labeling after cortical injections in mice was topographically organized with more rostral cortical regions projecting more medially in the pons and caudal cortical areas projecting towards the lateral extent of the pontine nuclei (Figure 1E, see also Figure 3B). While most pontine labeling was strictly ipsilateral, M1 was the only cortical target region that resulted in bilateral pontine labeling (average of 118 ± 36 neurons ipsilateral to 8 ± 3 neurons contralateral; Figure 1E). Previous anterograde tracer studies have observed corticopontine fibers largely in the ipsilateral pontine nuclei with relatively sparse labeling in the contralateral pons (Mihailoff et al., 1985; Leergaard and Bjaalie, 2007). However, it was unclear if these sparse contralateral projections were fibers of passage or axon terminals; our results suggest the later for M1 projections and the former for all other cortical targets regions described here. Interestingly, the existence of functional synapses for contralateral corticopontine projections was also reported in primates, however, also exclusively after M1 injections (Morecraft et al., 2018).

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We observed anterogradely labeled cells in various other precerebellar nuclei (Figure 2A; Supplementary file 1B; see also Ruigrok et al., 2015). In fact, after S1 injections we found more labeled cells in extra-pontine precerebellar nuclei than in pontine nuclei (70 ± 8% of total labeling) and after M1 injections, just under half (40 ± 3%). This labeling spanned several precerebellar nuclei, including the red nucleus and reticulotegmental nucleus, as well as more caudal brainstem regions including the spinal trigeminal nucleus, lateral reticular nucleus, the matrix region x and the vestibular nuclei (Figure 2, Supplementary file 1B). While the reticulotegmental nucleus is often grouped together with the basal pontine nuclei, these regions in the pons appear to play different functional roles (Cicirata et al., 2005), hence, in this study we classify the reticulotegmental nucleus as a separate extra-pontine region. Additionally, we observed labeled fibers in both the medial and inferior cerebellar peduncles (see Figure 2A), indicating disynaptic tracts projecting to the cerebellum from pontine regions and more caudal extra-pontine precerebellar nuclei, respectively. Since there was no labeling observed in the pontine nuclei after A1 injections, the resulting mossy fiber terminals must reach the cerebellum through other precerebellar nuclei, of which we found labeling in the vestibular as well as the cochlear nuclei (see Figure 2A).

We did not observe labeled cells from any target cortical region in the spinal or lateral vestibular nuclei, the external cuneate nucleus, or the inferior olive. We did, however, observe fibers and terminal labeling in the inferior olive following injections in S1 (Figure 2C) and to a lesser extent after injections in M1. Interestingly, also only after S1 and M1 injections, anterogradely labeled cells were observed in the matrix region x, which has been suggested as a candidate preolivary relay nucleus (Ackerley et al., 2006). There is some controversy regarding the existence of direct cerebro-olivary connections in rodents, particularly originating from M1 (Swenson et al., 1989; Baker et al., 2001; Ackerley et al., 2006); for review see Watson and Apps, 2019); our results support disynaptic input from the cerebral cortex to inferior olivary neurons. Sparse fibers were also observed in the lateral cerebellar nucleus following S1 and M1 injections, likely from pontocerebellar collaterals (Cicirata et al., 2005; Biswas et al., 2019).

Lobule co-innervation of cerebrocerebellar inputs from distinct cortical areas

To determine the spatial overlap of cerebrocerebellar input from various cortical regions we examined the distribution of the total number of mossy fiber terminals within each lobule for each side of the cerebellum. All cerebellar lobules, on both ipsilateral and contralateral sides, received some cerebrocerebellar projections, however, the proportion of terminals in each lobule varied widely (ranging from 0.1–19.3% of the total ipsilateral terminal labeling and 0.1–16.9% of the total contralateral labeling; Figure 4A,B). The cerebellar hemispheres (Sim, crus I, crus II, PM, and Cop) received the majority of the total cerebrocerebellar mossy fiber input (68.2% of ipsilateral terminals, 67.1% of contralateral terminals), followed by vermal lobules IV/V and VI together (18.1% of ipsilateral terminals, 17.7% of contralateral terminals). Interestingly, we found a notable scarcity of mossy fiber terminals in posterior vermis, especially vermal lobule VII (1.2% of ipsilateral terminals, 0.4% contralateral terminals), which is contrary to studies of pontocerebellar projections alone (Serapide et al., 1994). Considering its relatively smaller volume, the PFl also received a large proportion of inputs (7.9% of ipsilateral terminals, 11.6% contralateral terminals; Figure 4A,B).

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All cerebellar lobules also received mossy fiber inputs from two or more cortical regions; however, the proportion of cerebrocerebellar projections to a single lobule from each functionally distinct cortical region again varied substantially (Figure 4A,B). To examine the dominance of these projections from each target cortical region, we calculated the density of terminal labeling for each cerebellar subdivision according to the number of mossy fibers and the volume based on 16.4T MRT data (Ullmann et al., 2012; Figure 4C; Supplementary file 1C). In the cerebellar hemispheres, we found the highest density of terminals from motor input (M1), especially ipsilaterally, including Sim, crus I, crus II, and PM, but excluding the Cop (Supplementary file 1C). Bilaterally, the Cop had the highest density from somatosensory input; to the extent that 96% of the mossy fiber terminals found in the contralateral Cop originated in S1 (Figure 4B).

Lobules in the vermis had the highest density from S1 input (Figure 4C), except for ipsilateral lobule VI, which had a relatively large number of mossy fibers from M1 injections, and the most posterior vermal region, vermal lobules IX and X, which are part of the vestibulocerebellum (Figure 4A,B; see also Figure 3D). In general, the vestibulocerebellum had diverse cerebrocerebellar input. Bilaterally, the PFL and Fl had the highest density of terminals from S1 injections, although both also had substantial input from most other cortical regions (Figure 4A–C). Lobule IX and X also had sparse input from most cortical regions, however, IX had a proportionally large number of terminals from auditory regions (especially A1 but also AuD), while M1 was largely represented in lobule X (Figure 4A,B). The representation of inputs from A1 and AuD in vermal vestibulocerebellar regions is interesting considering the large number of labeled cells observed in the vestibular nuclei relative to other precerebellar nuclei from auditory cortical regions (see Supplementary file 1B). It is important to note, however, that most regions of the vestibulocerebellum (with the exception of the PFl) had a small density of mossy fiber terminals (Figure 4C, Supplementary file 1C); hence, while still representative, caution must be taken in interpreting the pattern of labeling within these regions.

We then classified the topography of mossy fiber inputs to the various cerebellar lobules according to the degree of regional overlap, as this would represent a prerequisite for potential multimodal processing between corticocerebellar inputs (Figure 4D). Since all cerebellar lobules received input from two or more cortical regions but some lobules had a low density of total mossy fiber terminals, we included subdivisions that received a minimum proportion of the total mossy fiber input for each side (>4%; see Figure 4A,B) and classified lobules as: ‘highly co-innervated’ if >15% of mossy fiber labeling was from at least two different functional cortical regions in addition to the dominant one, and ‘moderately co-innervated’ if this value was <15% (Figure 4D). Using these criteria, bilateral crus I, PFl, vermal lobule VI, and IV/V had the greatest potential for multimodal co-innervation; followed by bilateral Sim, crus II, PM, and contralateral Cop.

Spatial organization of mossy fiber terminals in molecularly defined cerebellar modules

Cerebellar lobules contain highly organized parasagittally oriented modules based on anatomical, physiological and molecular subdivisions (for review see Apps and Hawkes, 2009). Therefore, to determine more precisely the potential for spatial overlap of multimodal information, we examined the distribution of mossy fiber terminals across the mediolateral and rostrocaudal extent of the identified multimodal lobules. To do this, we used the parasagittal expression pattern of aldolase C (or zebrin Brochu et al., 1990; Ahn et al., 1994) as a molecular marker, which is highly conserved across individuals. This allowed us to align the pattern of labeling observed in cerebellar regions across animals and, hence, quantify the spatial relationship between mossy fiber terminals originating from functionally distinct cortical areas (Figure 5, Figure 6, see also Figure 5—figure supplement 1, including validation of alignment across animals Figure 5—figure supplement 1J).

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Figure 6

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After alignment, for identified lobules with substantial co-innervation in the cerebellar hemispheres, terminals from both sensory and motor cortical areas were spatially overlapping (Figure 5) - with the exception of crus II, where M1 injections resulted in terminal labeling largely in dorsal regions and S1 in ventral regions (Figure 5A). Consequently, crus II had diverse functional cerebrocerebellar input but labeling was more spatially segregated within the lobule, with the distance between M1 terminals to themselves being significantly shorter than the distance between M1 terminals and those originating from other cortical injection sites (Figure 5B; M1-M1: 258 ± 22 µm, M1-Other: 305 ± 10 µm, p=0.007, two-sample t-test), this was also true for S1 (S1-S1: 190 ± 13 µm, S1-Other: 316 ± 15 µm, p<0.001, two-sample t-test). Hence, when identifying the nearest neighbors of M1 terminal locations in crus II, over 80% of these were also of M1 origin (Figure 5C); therefore, crus II has lower potential for multimodal spatial overlap at the modular level. In contrast, crus I showed highly spatially overlapping patterns, that is, the distance between both M1 and S1 terminal locations to that of other cortical origins was not significantly different to the distance between themselves (Figure 5B, M1–M1: 222 ± 8 µm, M1-Other: 220 ± 7 µm, p=0.953; S1-S1: 246 ± 10 µm, S1-Other: 233 ± 7 µm, p<0.001, two-sample t-test), and a higher proportion of their nearest neighbors came from extrinsic cortical origins (Figure 5C). Throughout the hemispheres, terminals from primary sensory regions V1 and A1 as well as association cortices (PPC and AuD) were generally located more on the apex of the folia, where they were intermingled with M1 terminals, whereas S1 terminals tended to be more at the base of the folia, also intermingled with M1 terminals.

This same apical/basal pattern was also observed in the PFl (Figure 6A); hence, the ventral PFl (part of the vestibulocerebellum) was highly co-innervated with terminal labeling from sensory and association cortices and the dorsal PFl largely contained S1 and M1 terminals. In contrast, in vermal lobules IV/V and VI terminals from all cortical regions were overlapping in more medial zones and S1 and M1 terminals were additionally in more paravermal zones, with little labeling from other modalities (Figure 6). Therefore, S1 and M1 terminals were quite widely distributed parasagittally, whereas terminals from other primary sensory and association areas tended to be in medial-vermal and lateral-hemispheric regions. In general, the pairwise distance between terminal locations was not significantly different between M1 and other cortical origins, however, S1 terminals were more tightly clustered to each other in both the PFl and lobule VI (Figure 6B).

Generally throughout the cerebellum, S1 injections resulted in the patchiest distribution with clusters of mossy fiber terminals in certain lobules aligning to the AldoC expression pattern; this was especially the case in Cop and to a lesser extent in the PM, where mossy fiber clusters aligned with AldoC+ stripes (Figure 5—figure supplement 1D). Interestingly, this pattern of projections is in agreement with results from electrophysiological recordings in the PM in rats, demonstrating alternating patches of somatosensory responses to hindlimb/forelimb stimulation (Shambes et al., 1978). However, distributed mossy fiber labeling was also present in both AldoC+ and AldoC- regions in the Cop and PM (Figure 5—figure supplement 1D), so that no specific bias was seen on average (Figure 5—figure supplement 1G–I). Conversely, in crus I clustered S1 mossy fiber terminals were more biased towards AldoC- regions (Figure 5—figure supplement 1B,G), although not strictly so.

To test for spatial randomness of terminal locations, we calculating the Ripley’s K-function for each lobule and compared these distributions with simulated distributions of complete spatial randomness (CSR; see Materials and methods); for S1, all lobules except crus II (p=0.260) and lobule IV (p=0.642) showed significant deviation from CSR (p≤0.028; t = 60 µm, 100 simulated CSR distributions; 3D Ripley’s K-function; Hansson et al., 2013). Mossy fiber terminals from M1 injections generally had a more distributed, less clustered, pattern throughout the lobules and did not appear to consistently follow particular AldoC expression boundaries (Figure 5, Figure 6, Figure 5—figure supplement 1E,F); however, with the exception of lobule VI (p=0.391), M1 terminal locations still showed significant deviation from CSR (p≤0.015; t = 60 µm, 100 simulated CSR distributions; 3D Ripley’s K-function; Hansson et al., 2013). Injections in the other cortical regions also resulted in distributed and/or sparse terminal labeling which could not be assigned to a particular AldoC expression pattern and only deviated from CSR in crus I, sim, PM and Cop, and the PFl (p≤0.001; t = 60 µm, 100 simulated CSR distributions; 3D Ripley’s K-function; Hansson et al., 2013). Therefore, mono-trans-synaptic cerebrocerebellar mossy fiber terminals did not adhere to a specific pattern of zonal organization with respect to AldoC expression boundaries, however, many patterns of expression significantly deviated from spatial randomness. Since these terminals potentially relay in a number of different precerebellar nuclei (see Supplementary file 1B and Figure 2) our results do not preclude the existence of a finer-scale relationship with respect to individual cerebrocerebellar pathways and/or in a lobule specific manner.

Intermediate cerebrocerebellar brainstem pathways

Based on the results of the mono-trans-synaptic tracer, there are a number of precerebellar nuclei, both pontine and extra-pontine, that have the potential to act as intermediate nuclei for cerebrocerebellar projections (summarized in Figure 7A; see also Supplementary file 1B). To gain insight into the likelihood that these various precerebellar nuclei act as intermediate sources of mossy fiber input to the lobules identified as having high co-innervation, we performed additional tracing experiments with injections of the retrograde tracer Cholera-toxin-B (CTB) into key vermal regions (lobules IV/V, IV) as well as cerebellar hemispheres (Sim and crus I; Figure 7—figure supplement 1). Additionally, we performed dual injections of CTB into lobule IV/V or crus I and the trans-mono-synaptic AAV1.cre into either M1 or S1, respectively (Figure 7B). Our results show that the majority of retrogradely labeled cells were located in the pons (across all cases: pontine = 6429 cells [73% of total]; extra-pontine = 2378 cells [27% of total]; Figure 7—figure supplement 1). With our dual injections, we also observed some double labeled cells in the pontine nuclei (e.g. Figure 7B), demonstrating direct confirmation that these pontine cells receive cerebrocerebellar disynaptic input. We note that the probability of double labeling was likely low due to the spatially restricted injection sites.

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We also observed that many extra-pontine precerebellar nuclei identified as receiving cortical projections (Figure 2; Supplementary file 1B) contained retrograde labeling (e.g. lateral reticular nucleus, reticulotegmental nucleus, vestibular nuclei, interpolar part of the spinal trigeminal nucleus, and matrix region x; Figure 7B; Figure 7—figure supplement 1; Supplementary file 1D). Although double labeled cells were not directly observed in extra-pontine precerebellar nuclei, the labeling was spatially overlapping (Figure 7B), and quantification of the identity of the five nearest neighbors to cells originating from anterograde cortical injections, reveled that 13–45% of these were retrogradely labeled cells from the cerebellar cortex (Figure 7C; see also Figure 7—figure supplement 2).

From retrograde injections into the cerebellar cortex, we found that, while the majority of retrograde labeling was observed in the pontine nuclei, lobules IV/V and VI showed relatively higher proportions of extra-pontine retrograde labeling (IV/V, 44%; VI, 39%) in comparison to the cerebellar hemispheres (sim, 17%; crus 1, 21%; Figure 7—figure supplement 1). Lastly, although we did not observe significant cerebrocerebellar projections to lobule VII (e.g. see Figure 3), we confirmed that this lobule does receive pontocerebellar projections, but these were also proportionally few in comparison to other injected cerebellar regions (52% pontine vs 48% extra-pontine retrograde labeling, Figure 7—figure supplement 3), and originated largely from lateral regions of the pons, an area that topographically has been shown to receive corticopontine projections from the RSC (Suzuki et al., 2012; see also Figure 1—figure supplement 1).

Although, the proportion of observed mossy fiber terminals that relay through extra-pontine pathways cannot be precisely specified, we found a stronger positive correlation with the total number of mossy fiber terminals when all precerebellar cells are accounted for (R = 0.837, p<0.001, n = 18, Pearson correlation; Figure 7D) compared to when only pontine labeled cells are included (R = 0.632, p=0.012, n = 18, Pearson correlation). Additionally, we found lower variability in the total number of mossy fibers per labeled cell when all precerebellar cells are included (all cells: 50 ± 12 mossy fibers per cell; pontine cells only: 120 ± 63 mossy fibers per cell). Whether this ratio of ~50 mossy fiber terminals per precerebellar neuron can be generalized across individual cortico-precerebellar pathways remains to be determined, however, using single neuron tracing techniques, previous studies have reported a comparable 67 ± 7 (mice: Biswas et al., 2019) and 46 ± 9 (rats: Na et al., 2019) mossy fiber terminals in the cerebellum per pontine projecting neuron.

In this study we elucidated the cerebrocerebellar projections from primary motor, sensory, and secondary/association cortical areas to various regions of the mouse cerebellum. By using a mono-trans-synaptic anterogradely transported AAV (Zingg et al., 2017; Zingg et al., 2020), we found a highly organized topography of labeled corticopontine cells and also observed a number of potential extra-pontine cerebrocerebellar pathways. Notably, injections into A1 produced only terminal labeling in the pons, whereas injections into more dorsal secondary auditory cortex showed evidence of an auditory cortico-ponto-cerebellar pathway. We quantified the proportion and detailed the precise organization of cerebrocerebellar terminals from each injected cerebral cortical region. The majority of labeled mossy fiber terminals from primary sensory and motor cortical regions were in the contralateral cerebellum, whereas projections from the secondary/association areas PPC and AuD resulted in less laterality in the cerebellum. Cerebellar subdivisions with the highest spatial overlap of multimodal cerebrocerebellar inputs within molecularly defined modules were bilateral crus I, PFl, vermal lobules VI, and lobule IV/V indicating that these regions may act as hubs for the integration of multimodal information originating from the cerebral cortex.

Experiments were performed with 42 mice (9–12 weeks; both males and females) of the Rosa26-CAG-LSL-tdTomato Cre reporter mice line (Ai9; RRID:IMSR_JAX:007909). Note that this tdTomato reporter line is known to have increased levels of auto-fluorescence (Hahn et al., 2019), particularly in Purkinje cells (e.g. Figure 1F), however, this was easily distinguishable from cre-induced tdTomato expression under the microscope and in merged images. Animals were housed in standard laboratory cages (22°C, 12 hr light-dark cycle) with food and water available ad libitum. All experiments were performed according to the NIH Guide for the Care and Use of Laboratory animals (2011) and the Directive of the European Communities Parliament and Council on the protection of animals used for scientific purposes (2010/63/EU) and were approved by the animal care committee of Sachsen-Anhalt, Germany (42502-2-1479 DZNE).

Data generated during this study (e.g cell counts, etc) are included in the manuscript and supporting files.

1. 1. Ackerley R
   2. Pardoe J
   3. Apps R

   (2006) A novel site of synaptic relay for climbing fibre pathways relaying signals from the motor cortex to the cerebellar cortical C1 zone

   The Journal of Physiology 576:503–518.

   https://doi.org/10.1113/jphysiol.2006.114215

   • PubMed
   • Google Scholar
2. 1. Ahn AH
   2. Dziennis S
   3. Hawkes R
   4. Herrup K

   (1994)

   The cloning of zebrin II reveals its identity with aldolase C

   Development 120:2081–2090.

   • PubMed
   • Google Scholar
3. 1. Apps R
   2. Hawkes R

   (2009) Cerebellar cortical organization: a one-map hypothesis

   Nature Reviews Neuroscience 10:670–681.

   https://doi.org/10.1038/nrn2698

   • PubMed
   • Google Scholar
4. Book

   1. Apps R
   2. Watson TC

   (2013) Cerebro-cerebellar connections

   In: Manto M, Gruol D. L, Schmahmann J, editors. Handbook of the Cerebellum and Cerebellar Disorders. Dordrecht. Netherlands: Springer. pp. 1131–1154.

   https://doi.org/10.1007/978-94-007-1333-8_48

   • Google Scholar
5. 1. Ayaz A
   2. Stäuble A
   3. Hamada M
   4. Wulf MA
   5. Saleem AB
   6. Helmchen F

   (2019) Layer-specific integration of locomotion and sensory information in mouse barrel cortex

   Nature Communications 10:2585.

   https://doi.org/10.1038/s41467-019-10564-8

   • PubMed
   • Google Scholar
6. 1. Azizi SA
   2. Burne RA
   3. Woodward DJ

   (1985) The auditory corticopontocerebellar projection in the rat: inputs to the paraflocculus and midvermis. An anatomical and physiological study

   Experimental Brain Research 59:36–49.

   https://doi.org/10.1007/BF00237663

   • PubMed
   • Google Scholar
7. 1. Baker MR
   2. Javid M
   3. Edgley SA

   (2001) Activation of cerebellar climbing fibres to rat cerebellar posterior lobe from motor cortical output pathways

   The Journal of Physiology 536:825–839.

   https://doi.org/10.1111/j.1469-7793.2001.00825.x

   • PubMed
   • Google Scholar
8. 1. Barnstedt O
   2. Keating P
   3. Weissenberger Y
   4. King AJ
   5. Dahmen JC

   (2015) Functional microarchitecture of the mouse dorsal inferior colliculus revealed through in vivo Two-Photon calcium imaging

   Journal of Neuroscience 35:10927–10939.

   https://doi.org/10.1523/JNEUROSCI.0103-15.2015

   • PubMed
   • Google Scholar
9. 1. Baumann O
   2. Borra RJ
   3. Bower JM
   4. Cullen KE
   5. Habas C
   6. Ivry RB
   7. Leggio M
   8. Mattingley JB
   9. Molinari M
   10. Moulton EA
   11. Paulin MG
   12. Pavlova MA
   13. Schmahmann JD
   14. Sokolov AA

   (2015) Consensus paper: the role of the cerebellum in perceptual processes

   The Cerebellum 14:197–220.

   https://doi.org/10.1007/s12311-014-0627-7

   • PubMed
   • Google Scholar
10. 1. Bengtsson F
    2. Jörntell H

    (2009) Sensory transmission in cerebellar granule cells relies on similarly coded mossy fiber inputs

    PNAS 106:2389–2394.

    https://doi.org/10.1073/pnas.0808428106

    • PubMed
    • Google Scholar
11. 1. Biswas MS
    2. Luo Y
    3. Sarpong GA
    4. Sugihara I

    (2019) Divergent projections of single pontocerebellar axons to multiple cerebellar lobules in the mouse

    Journal of Comparative Neurology 527:1966–1985.

    https://doi.org/10.1002/cne.24662

    • PubMed
    • Google Scholar
12. 1. Bjaalie JG
    2. Sudbø J
    3. Brodal P

    (1997) Corticopontine terminal fibres form small scale clusters and large scale lamellae in the cat

    NeuroReport 8:1651–1655.

    https://doi.org/10.1097/00001756-199705060-00019

    • PubMed
    • Google Scholar
13. 1. Brochu G
    2. Maler L
    3. Hawkes R

    (1990) Zebrin II: a polypeptide antigen expressed selectively by purkinje cells reveals compartments in rat and fish cerebellum

    The Journal of Comparative Neurology 291:538–552.

    https://doi.org/10.1002/cne.902910405

    • PubMed
    • Google Scholar
14. 1. Brodal P

    (1972) The corticopontine projection from the visual cortex in the cat. II. the projection from Areas 18 and 19

    Brain Research 39:319–335.

    https://doi.org/10.1016/0006-8993(72)90439-8

    • PubMed
    • Google Scholar
15. 1. Brodal P
    2. Bjaalie JG

    (1997) Salient anatomic features of the cortico-ponto-cerebellar pathway

    Progress in Brain Research 114:227–250.

    https://doi.org/10.1016/s0079-6123(08)63367-1

    • PubMed
    • Google Scholar
16. 1. Budinger E
    2. Heil P
    3. Scheich H

    (2000) Functional organization of auditory cortex in the mongolian gerbil (Meriones unguiculatus). IV. connections with anatomically characterized subcortical structures

    European Journal of Neuroscience 12:2452–2474.

    https://doi.org/10.1046/j.1460-9568.2000.00143.x

    • PubMed
    • Google Scholar
17. 1. Caicedo A
    2. Herbert H

    (1993) Topography of descending projections from the inferior colliculus to auditory brainstem nuclei in the rat

    The Journal of Comparative Neurology 328:377–392.

    https://doi.org/10.1002/cne.903280305

    • PubMed
    • Google Scholar
18. 1. Chabrol FP
    2. Arenz A
    3. Wiechert MT
    4. Margrie TW
    5. DiGregorio DA

    (2015) Synaptic diversity enables temporal coding of coincident multisensory inputs in single neurons

    Nature Neuroscience 18:718–727.

    https://doi.org/10.1038/nn.3974

    • PubMed
    • Google Scholar
19. 1. Chabrol FP
    2. Blot A
    3. Mrsic-Flogel TD

    (2019) Cerebellar contribution to preparatory activity in motor neocortex

    Neuron 103:506–519.

    https://doi.org/10.1016/j.neuron.2019.05.022

    • PubMed
    • Google Scholar
20. 1. Cicirata F
    2. Serapide MF
    3. Parenti R
    4. Pantò MR
    5. Zappalà A
    6. Nicotra A
    7. Cicero D

    (2005) The basilar pontine nuclei and the nucleus reticularis tegmenti pontis subserve distinct cerebrocerebellar pathways

    Progress in Brain Research 148:259–282.

    https://doi.org/10.1016/S0079-6123(04)48021-2

    • PubMed
    • Google Scholar
21. 1. Coffman KA
    2. Dum RP
    3. Strick PL

    (2011) Cerebellar vermis is a target of projections from the motor Areas in the cerebral cortex

    PNAS 108:16068–16073.

    https://doi.org/10.1073/pnas.1107904108

    • PubMed
    • Google Scholar
22. Book

    1. Franklin KBJ
    2. Paxinos G

    (2007)

    The Mouse Brain in Stereotaxic Coordinates

    Academic Press.

    • Google Scholar
23. 1. Fu Y
    2. Tvrdik P
    3. Makki N
    4. Paxinos G
    5. Watson C

    (2011) Precerebellar cell groups in the hindbrain of the mouse defined by retrograde tracing and correlated with cumulative Wnt1-cre genetic labeling

    The Cerebellum 10:570–584.

    https://doi.org/10.1007/s12311-011-0266-1

    • PubMed
    • Google Scholar
24. 1. Gao Z
    2. Davis C
    3. Thomas AM
    4. Economo MN
    5. Abrego AM
    6. Svoboda K
    7. De Zeeuw CI
    8. Li N

    (2018) A cortico-cerebellar loop for motor planning

    Nature 563:113–116.

    https://doi.org/10.1038/s41586-018-0633-x

    • PubMed
    • Google Scholar
25. 1. Giovannucci A
    2. Badura A
    3. Deverett B
    4. Najafi F
    5. Pereira TD
    6. Gao Z
    7. Ozden I
    8. Kloth AD
    9. Pnevmatikakis E
    10. Paninski L
    11. De Zeeuw CI
    12. Medina JF
    13. Wang SS

    (2017) Cerebellar granule cells acquire a widespread predictive feedback signal during motor learning

    Nature Neuroscience 20:727–734.

    https://doi.org/10.1038/nn.4531

    • PubMed
    • Google Scholar
26. 1. Glickstein M
    2. May JG
    3. Mercier BE

    (1985) Corticopontine projection in the macaque: the distribution of labelled cortical cells after large injections of horseradish peroxidase in the pontine nuclei

    The Journal of Comparative Neurology 235:343–359.

    https://doi.org/10.1002/cne.902350306

    • PubMed
    • Google Scholar
27. 1. Glickstein M

    (1997) Mossy-fibre sensory input to the cerebellum

    Progress in Brain Research 114:251–262.

    https://doi.org/10.1016/s0079-6123(08)63368-3

    • PubMed
    • Google Scholar
28. 1. Guo W
    2. Chambers AR
    3. Darrow KN
    4. Hancock KE
    5. Shinn-Cunningham BG
    6. Polley DB

    (2012) Robustness of cortical topography across fields, Laminae, anesthetic states, and neurophysiological signal types

    Journal of Neuroscience 32:9159–9172.

    https://doi.org/10.1523/JNEUROSCI.0065-12.2012

    • PubMed
    • Google Scholar
29. 1. Gutiérrez-Ibáñez C
    2. Iwaniuk AN
    3. Wylie DR

    (2018) Parrots have evolved a primate-like telencephalic-midbrain-cerebellar circuit

    Scientific Reports 8:9960.

    https://doi.org/10.1038/s41598-018-28301-4

    • PubMed
    • Google Scholar
30. 1. Hahn C
    2. Becker K
    3. Saghafi S
    4. Pende M
    5. Avdibašić A
    6. Foroughipour M
    7. Heinz DE
    8. Wotjak CT
    9. Dodt HU

    (2019) High-resolution imaging of fluorescent whole mouse brains using stabilised organic media (sDISCO)

    Journal of Biophotonics 12:e201800368.

    https://doi.org/10.1002/jbio.201800368

    • PubMed
    • Google Scholar
31. 1. Hansson K
    2. Jafari-Mamaghani M
    3. Krieger P

    (2013) RipleyGUI: software for analyzing spatial patterns in 3D cell distributions

    Frontiers in Neuroinformatics 7:5.

    https://doi.org/10.3389/fninf.2013.00005

    • PubMed
    • Google Scholar
32. 1. Henschke JU
    2. Noesselt T
    3. Scheich H
    4. Budinger E

    (2015) Possible anatomical pathways for short-latency multisensory integration processes in primary sensory cortices

    Brain Structure and Function 220:955–977.

    https://doi.org/10.1007/s00429-013-0694-4

    • PubMed
    • Google Scholar
33. 1. Henschke JU
    2. Ohl FW
    3. Budinger E

    (2018) Crossmodal connections of primary sensory cortices largely vanish during normal aging

    Frontiers in Aging Neuroscience 10:1–14.

    https://doi.org/10.3389/fnagi.2018.00052

    • PubMed
    • Google Scholar
34. 1. Huang CM
    2. Liu G
    3. Huang R

    (1982) Projections from the cochlear nucleus to the cerebellum

    Brain Research 244:1–8.

    https://doi.org/10.1016/0006-8993(82)90897-6

    • PubMed
    • Google Scholar
35. 1. Huang CC
    2. Sugino K
    3. Shima Y
    4. Guo C
    5. Bai S
    6. Mensh BD
    7. Nelson SB
    8. Hantman AW

    (2013) Convergence of pontine and proprioceptive streams onto multimodal cerebellar granule cells

    eLife 2:e00400.

    https://doi.org/10.7554/eLife.00400

    • PubMed
    • Google Scholar
36. 1. Inoue K
    2. Terashima T
    3. Inoue Y

    (1991) Postnatal development of the pontine projections from the visual cortex of the mouse

    Okajimas Folia Anatomica Japonica 67:479–492.

    https://doi.org/10.2535/ofaj1936.67.6_479

    • PubMed
    • Google Scholar
37. 1. Ishikawa T
    2. Shimuta M
    3. Häusser M

    (2015) Multimodal sensory integration in single cerebellar granule cells in vivo

    eLife 4:e12916.

    https://doi.org/10.7554/eLife.12916

    • PubMed
    • Google Scholar
38. 1. Jafari-Mamaghani M
    2. Andersson M
    3. Krieger P

    (2010) Spatial point pattern analysis of neurons using Ripley's K-Function in 3D

    Frontiers in Neuroinformatics 4:9.

    https://doi.org/10.3389/fninf.2010.00009

    • PubMed
    • Google Scholar
39. 1. Jelitai M
    2. Puggioni P
    3. Ishikawa T
    4. Rinaldi A
    5. Duguid I

    (2016) Dendritic excitation–inhibition balance shapes cerebellar output during motor behaviour

    Nature Communications 7:1–13.

    https://doi.org/10.1038/ncomms13722

    • Google Scholar
40. 1. Jörntell H
    2. Ekerot CF

    (2006) Properties of somatosensory synaptic integration in cerebellar granule cells in vivo

    Journal of Neuroscience 26:11786–11797.

    https://doi.org/10.1523/JNEUROSCI.2939-06.2006

    • PubMed
    • Google Scholar
41. Book

    1. Kandel ER
    2. Schwartz JH
    3. Jessell TM

    (2000)

    Principles of Neural Science

    McGraw-Hill, Health Professions Division.

    • Google Scholar
42. 1. Kandler K
    2. Herbert H

    (1991) Auditory projections from the cochlear nucleus to pontine and mesencephalic reticular nuclei in the rat

    Brain Research 562:230–242.

    https://doi.org/10.1016/0006-8993(91)90626-7

    • PubMed
    • Google Scholar
43. 1. Kelly RM
    2. Strick PL

    (2003) Cerebellar loops with motor cortex and prefrontal cortex of a nonhuman primate

    The Journal of Neuroscience 23:8432–8444.

    https://doi.org/10.1523/JNEUROSCI.23-23-08432.2003

    • Google Scholar
44. Book

    1. Kirkcaldie MTK

    (2012) Neocortex

    In: Watson C, Paxinos G, Puelles L, editors. The Mouse Nervous System. Academic Press. pp. 52–111.

    https://doi.org/10.1016/B978-0-12-369497-3.10004-4

    • Google Scholar
45. 1. Knowlton BJ
    2. Thompson JK
    3. Thompson RF

    (1993) Projections from the auditory cortex to the pontine nuclei in the rabbit

    Behavioural Brain Research 56:23–30.

    https://doi.org/10.1016/0166-4328(93)90019-M

    • PubMed
    • Google Scholar
46. 1. Kralj-Hans I
    2. Baizer JS
    3. Swales C
    4. Glickstein M

    (2007) Independent roles for the dorsal paraflocculus and vermal lobule VII of the cerebellum in visuomotor coordination

    Experimental Brain Research 177:209–222.

    https://doi.org/10.1007/s00221-006-0661-x

    • PubMed
    • Google Scholar
47. 1. Kratochwil CF
    2. Maheshwari U
    3. Rijli FM

    (2017) The long journey of pontine nuclei neurons: from rhombic lip to Cortico-Ponto-Cerebellar circuitry

    Frontiers in Neural Circuits 11:33.

    https://doi.org/10.3389/fncir.2017.00033

    • PubMed
    • Google Scholar
48. 1. Leergaard TB
    2. Bjaalie JG
    3. Devor A
    4. Wald LL
    5. Dale AM

    (2003) In vivo tracing of major rat brain pathways using manganese-enhanced magnetic resonance imaging and three-dimensional digital atlasing

    NeuroImage 20:1591–1600.

    https://doi.org/10.1016/j.neuroimage.2003.07.009

    • PubMed
    • Google Scholar
49. 1. Leergaard TB
    2. Bjaalie JG

    (2007) Topography of the complete corticopontine projection: from experiments to principal maps

    Frontiers in Neuroscience 1:211–223.

    https://doi.org/10.3389/neuro.01.1.1.016.2007

    • PubMed
    • Google Scholar
50. 1. Legg CR
    2. Mercier B
    3. Glickstein M

    (1989) Corticopontine projection in the rat: the distribution of labelled cortical cells after large injections of horseradish peroxidase in the pontine nuclei

    The Journal of Comparative Neurology 286:427–441.

    https://doi.org/10.1002/cne.902860403

    • Google Scholar
51. Book

    1. Léna C
    2. Popa D

    (2015) Cerebrocerebellar Loops in the Rodent Brain

    In: Heck DH, editors. The Neuronal Codes of the Cerebellum. Academic Press. pp. 135–153.

    https://doi.org/10.1016/B978-0-12-801386-1.00006-X

    • Google Scholar
52. 1. Marani E
    2. Voogd J

    (1979)

    The morphology of the mouse cerebellum

    Acta Morphologica Neerlando-Scandinavica 17:33–52.

    • PubMed
    • Google Scholar
53. 1. Markwalter KH
    2. Yang Y
    3. Holy TE
    4. Bonni A

    (2019) Sensorimotor coding of vermal granule neurons in the developing mammalian cerebellum

    The Journal of Neuroscience 39:6626–6643.

    https://doi.org/10.1523/JNEUROSCI.0086-19.2019

    • PubMed
    • Google Scholar
54. 1. Mihailoff GA
    2. Lee H
    3. Watt CB
    4. Yates R

    (1985) Projections to the basilar pontine nuclei from face sensory and motor regions of the cerebral cortex in the rat

    The Journal of Comparative Neurology 237:251–263.

    https://doi.org/10.1002/cne.902370209

    • PubMed
    • Google Scholar
55. 1. Mihailoff GA
    2. Kosinski RJ
    3. Azizi SA
    4. Border BG

    (1989) Survey of noncortical afferent projections to the basilar pontine nuclei: a retrograde tracing study in the rat

    The Journal of Comparative Neurology 282:617–643.

    https://doi.org/10.1002/cne.902820411

    • PubMed
    • Google Scholar
56. 1. Morecraft RJ
    2. Ge J
    3. Stilwell-Morecraft KS
    4. Rotella DL
    5. Pizzimenti MA
    6. Darling WG

    (2018) New corticopontine connections in the primate brain: contralateral projections from the arm/Hand area of the precentral motor region

    Frontiers in Neuroanatomy 12:68.

    https://doi.org/10.3389/fnana.2018.00068

    • PubMed
    • Google Scholar
57. 1. Muzzu T
    2. Mitolo S
    3. Gava GP
    4. Schultz SR

    (2018) Encoding of locomotion kinematics in the mouse cerebellum

    PLOS ONE 13:e0203900.

    https://doi.org/10.1371/journal.pone.0203900

    • PubMed
    • Google Scholar
58. 1. Na J
    2. Sugihara I
    3. Shinoda Y

    (2019) The entire trajectories of single pontocerebellar axons and their lobular and longitudinal terminal distribution patterns in multiple aldolase C-positive compartments of the rat cerebellar cortex

    Journal of Comparative Neurology 527:2488–2511.

    https://doi.org/10.1002/cne.24685

    • PubMed
    • Google Scholar
59. 1. Niell CM
    2. Stryker MP

    (2010) Modulation of visual responses by behavioral state in mouse visual cortex

    Neuron 65:472–479.

    https://doi.org/10.1016/j.neuron.2010.01.033

    • PubMed
    • Google Scholar
60. 1. Odeh F
    2. Ackerley R
    3. Bjaalie JG
    4. Apps R

    (2005) Pontine maps linking somatosensory and cerebellar cortices are in register with climbing fiber somatotopy

    Journal of Neuroscience 25:5680–5690.

    https://doi.org/10.1523/JNEUROSCI.0558-05.2005

    • PubMed
    • Google Scholar
61. 1. Päällysaho J
    2. Sugita S
    3. Noda H

    (1991) Brainstem mossy fiber projections to lobules VIa, VIb,c, VII and VIII of the cerebellar vermis in the rat

    Neuroscience Research 12:217–231.

    https://doi.org/10.1016/0168-0102(91)90112-C

    • PubMed
    • Google Scholar
62. 1. Pakan JM
    2. Graham DJ
    3. Wylie DR

    (2010) Organization of visual mossy fiber projections and zebrin expression in the pigeon vestibulocerebellum

    The Journal of Comparative Neurology 518:175–198.

    https://doi.org/10.1002/cne.22192

    • PubMed
    • Google Scholar
63. 1. Pakan JM
    2. Lowe SC
    3. Dylda E
    4. Keemink SW
    5. Currie SP
    6. Coutts CA
    7. Rochefort NL

    (2016) Behavioral-state modulation of inhibition is context-dependent and cell type specific in mouse visual cortex

    eLife 5:e14985.

    https://doi.org/10.7554/eLife.14985

    • PubMed
    • Google Scholar
64. 1. Pakan JMP
    2. Francioni V
    3. Rochefort NL

    (2018) Action and learning shape the activity of neuronal circuits in the visual cortex

    Current Opinion in Neurobiology 52:88–97.

    https://doi.org/10.1016/j.conb.2018.04.020

    • Google Scholar
65. 1. Pakan JM
    2. Wylie DR

    (2006) Two optic flow pathways from the pretectal nucleus lentiformis mesencephali to the cerebellum in pigeons (Columba livia)

    The Journal of Comparative Neurology 499:732–744.

    https://doi.org/10.1002/cne.21108

    • PubMed
    • Google Scholar
66. 1. Perales M
    2. Winer JA
    3. Prieto JJ

    (2006) Focal projections of cat auditory cortex to the pontine nuclei

    The Journal of Comparative Neurology 497:959–980.

    https://doi.org/10.1002/cne.20988

    • Google Scholar
67. 1. Pijpers A
    2. Ruigrok TJ

    (2006) Organization of pontocerebellar projections to identified climbing fiber zones in the rat

    The Journal of Comparative Neurology 496:513–528.

    https://doi.org/10.1002/cne.20940

    • PubMed
    • Google Scholar
68. 1. Poulet JFA
    2. Crochet S

    (2019) The cortical states of wakefulness

    Frontiers in Systems Neuroscience 12:64.

    https://doi.org/10.3389/fnsys.2018.00064

    • PubMed
    • Google Scholar
69. 1. Proville RD
    2. Spolidoro M
    3. Guyon N
    4. Dugué GP
    5. Selimi F
    6. Isope P
    7. Popa D
    8. Léna C

    (2014) Cerebellum involvement in cortical sensorimotor circuits for the control of voluntary movements

    Nature Neuroscience 17:1233–1239.

    https://doi.org/10.1038/nn.3773

    • PubMed
    • Google Scholar
70. 1. Rondi-Reig L
    2. Paradis AL
    3. Lefort JM
    4. Babayan BM
    5. Tobin C

    (2014) How the cerebellum may monitor sensory information for spatial representation

    Frontiers in Systems Neuroscience 8:1–13.

    https://doi.org/10.3389/fnsys.2014.00205

    • PubMed
    • Google Scholar
71. Book

    1. Ruigrok TJH

    (2004) Precerebellar Nuclei and Red Nucleus

    In: Paxinos G, editors. The Rat Nervous System. Academic Press. pp. 167–204.

    https://doi.org/10.1016/B978-012547638-6/50009-2

    • Google Scholar
72. Book

    1. Ruigrok TJH
    2. Sillitoe R
    3. Voogd J

    (2015) Cerebellum and cerebellar connections

    In: Paxinos G, editors. The Rat Nervous System. Academic Press. pp. 133–205.

    https://doi.org/10.1016/B978-0-12-374245-2.00009-7

    • Google Scholar
73. 1. Sawtell NB

    (2010) Multimodal integration in granule cells as a basis for associative plasticity and sensory prediction in a cerebellum-like circuit

    Neuron 66:573–584.

    https://doi.org/10.1016/j.neuron.2010.04.018

    • PubMed
    • Google Scholar
74. 1. Schmahmann JD
    2. Pandya DN

    (1997) Anatomic organization of the basilar pontine projections from prefrontal cortices in rhesus monkey

    The Journal of Neuroscience 17:438–458.

    https://doi.org/10.1523/JNEUROSCI.17-01-00438.1997

    • PubMed
    • Google Scholar
75. 1. Schneider DM
    2. Nelson A
    3. Mooney R

    (2014) A synaptic and circuit basis for corollary discharge in the auditory cortex

    Nature 513:189–194.

    https://doi.org/10.1038/nature13724

    • PubMed
    • Google Scholar
76. 1. Schuller G
    2. Covey E
    3. Casseday JH

    (1991a) Auditory pontine grey: connections and response properties in the horseshoe bat

    European Journal of Neuroscience 3:648–662.

    https://doi.org/10.1111/j.1460-9568.1991.tb00851.x

    • PubMed
    • Google Scholar
77. 1. Schuller G
    2. O'Neill WE
    3. Radtke-Schuller S

    (1991b) Facilitation and delay sensitivity of auditory cortex neurons in CF - FM bats, Rhinolophus rouxi and Pteronotus p.parnellii

    European Journal of Neuroscience 3:1165–1181.

    https://doi.org/10.1111/j.1460-9568.1991.tb00051.x

    • PubMed
    • Google Scholar
78. 1. Serapide MF
    2. Cicirata F
    3. Sotelo C
    4. Pantó MR
    5. Parenti R

    (1994) The pontocerebellar projection: longitudinal zonal distribution of fibers from discrete regions of the pontine nuclei to vermal and parafloccular cortices in the rat

    Brain Research 644:175–180.

    https://doi.org/10.1016/0006-8993(94)90362-X

    • PubMed
    • Google Scholar
79. 1. Serapide MF
    2. Zappalà A
    3. Parenti R
    4. Pantò MR
    5. Cicirata F

    (2002) Laterality of the pontocerebellar projections in the rat

    European Journal of Neuroscience 15:1551–1556.

    https://doi.org/10.1046/j.1460-9568.2002.01993.x

    • PubMed
    • Google Scholar
80. 1. Shadmehr R
    2. Smith MA
    3. Krakauer JW

    (2010) Error correction, sensory prediction, and adaptation in motor control

    Annual Review of Neuroscience 33:89–108.

    https://doi.org/10.1146/annurev-neuro-060909-153135

    • Google Scholar
81. 1. Shambes GM
    2. Beermann DH
    3. Welker W

    (1978) Multiple tactile Areas in cerebellar cortex: another patchy cutaneous projection to granule cell columns in rats

    Brain Research 157:123–128.

    https://doi.org/10.1016/0006-8993(78)91000-4

    • PubMed
    • Google Scholar
82. Book

    1. Sillitoe R
    2. Fu Y
    3. Watson C

    (2019)

    The Mouse Nervous System

    Elsevier.

    • Google Scholar
83. 1. Smaers JB
    2. Vanier DR

    (2019) Brain size expansion in primates and humans is explained by a selective modular expansion of the cortico-cerebellar system

    Cortex 118:292–305.

    https://doi.org/10.1016/j.cortex.2019.04.023

    • PubMed
    • Google Scholar
84. 1. Snider RS
    2. Stowell A

    (1944) Receiving Areas of the tactile, auditory, and visual systems in the cerebellum

    Journal of Neurophysiology 7:331–357.

    https://doi.org/10.1152/jn.1944.7.6.331

    • Google Scholar
85. 1. Stein BE
    2. Stanford TR

    (2008) Multisensory integration: current issues from the perspective of the single neuron

    Nature Reviews Neuroscience 9:255–266.

    https://doi.org/10.1038/nrn2331

    • PubMed
    • Google Scholar
86. 1. Stiebler I
    2. Neulist R
    3. Fichtel I
    4. Ehret G

    (1997) The auditory cortex of the house mouse: left-right differences, tonotopic organization and quantitative analysis of frequency representation

    Journal of Comparative Physiology A: Sensory, Neural, and Behavioral Physiology 181:559–571.

    https://doi.org/10.1007/s003590050140

    • Google Scholar
87. 1. Stiebler I
    2. Ehret G

    (1985) Inferior colliculus of the house mouse. I. A quantitative study of tonotopic organization, frequency representation, and tone-threshold distribution

    The Journal of Comparative Neurology 238:65–76.

    https://doi.org/10.1002/cne.902380106

    • PubMed
    • Google Scholar
88. 1. Suzuki L
    2. Coulon P
    3. Sabel-Goedknegt EH
    4. Ruigrok TJ

    (2012) Organization of cerebral projections to identified cerebellar zones in the posterior cerebellum of the rat

    Journal of Neuroscience 32:10854–10869.

    https://doi.org/10.1523/JNEUROSCI.0857-12.2012

    • PubMed
    • Google Scholar
89. 1. Swenson RS
    2. Sievert CF
    3. Terreberry RR
    4. Neafsey EJ
    5. Castro AJ

    (1989) Organization of cerebral cortico-olivary projections in the rat

    Neuroscience Research 7:43–54.

    https://doi.org/10.1016/0168-0102(89)90036-9

    • PubMed
    • Google Scholar
90. 1. Tervo DG
    2. Hwang BY
    3. Viswanathan S
    4. Gaj T
    5. Lavzin M
    6. Ritola KD
    7. Lindo S
    8. Michael S
    9. Kuleshova E
    10. Ojala D
    11. Huang CC
    12. Gerfen CR
    13. Schiller J
    14. Dudman JT
    15. Hantman AW
    16. Looger LL
    17. Schaffer DV
    18. Karpova AY

    (2016) A designer AAV variant permits efficient retrograde access to projection neurons

    Neuron 92:372–382.

    https://doi.org/10.1016/j.neuron.2016.09.021

    • PubMed
    • Google Scholar
91. 1. Thielert CD
    2. Thier P

    (1993) Patterns of projections from the pontine nuclei and the nucleus reticularis tegmenti pontis to the posterior vermis in the rhesus monkey: a study using retrograde tracers

    The Journal of Comparative Neurology 337:113–126.

    https://doi.org/10.1002/cne.903370108

    • PubMed
    • Google Scholar
92. 1. Ullmann JF
    2. Keller MD
    3. Watson C
    4. Janke AL
    5. Kurniawan ND
    6. Yang Z
    7. Richards K
    8. Paxinos G
    9. Egan GF
    10. Petrou S
    11. Bartlett P
    12. Galloway GJ
    13. Reutens DC

    (2012) Segmentation of the C57BL/6J mouse cerebellum in magnetic resonance images

    NeuroImage 62:1408–1414.

    https://doi.org/10.1016/j.neuroimage.2012.05.061

    • PubMed
    • Google Scholar
93. 1. Voogd J
    2. Barmack NH

    (2006) Oculomotor cerebellum

    Progress in Brain Research 151:231–268.

    https://doi.org/10.1016/S0079-6123(05)51008-2

    • PubMed
    • Google Scholar
94. 1. Watson TC
    2. Jones MW
    3. Apps R

    (2009) Electrophysiological mapping of novel prefrontal - cerebellar pathways

    Frontiers in Integrative Neuroscience 3:18.

    https://doi.org/10.3389/neuro.07.018.2009

    • PubMed
    • Google Scholar
95. Book

    1. Watson TC
    2. Apps R

    (2019)

    Cerebro-Cerebellar Connections

    In: Manto M, Schmahmann J. D, Rossi F, Gruol D. L, Koibuchi N, editors. Handbook of the Cerebellum and Cerebellar Disorders. Cham: Springer International Publishing. pp. 1–26.

    • Google Scholar
96. 1. Wiesendanger R
    2. Wiesendanger M

    (1982) The corticopontine system in the rat. I. mapping of corticopontine neurons

    The Journal of Comparative Neurology 208:215–226.

    https://doi.org/10.1002/cne.902080302

    • PubMed
    • Google Scholar
97. 1. Yu X
    2. Wadghiri YZ
    3. Sanes DH
    4. Turnbull DH

    (2005) In vivo auditory brain mapping in mice with Mn-enhanced MRI

    Nature Neuroscience 8:961–968.

    https://doi.org/10.1038/nn1477

    • PubMed
    • Google Scholar
98. 1. Zhao F
    2. Jiang HF
    3. Zeng WB
    4. Shu Y
    5. Luo MH
    6. Duan S

    (2017) Anterograde Trans-Synaptic tagging mediated by Adeno-Associated virus

    Neuroscience Bulletin 33:348–350.

    https://doi.org/10.1007/s12264-017-0099-0

    • PubMed
    • Google Scholar
99. 1. Zingg B
    2. Chou XL
    3. Zhang ZG
    4. Mesik L
    5. Liang F
    6. Tao HW
    7. Zhang LI

    (2017) AAV-Mediated anterograde transsynaptic tagging: mapping corticocollicular Input-Defined neural pathways for defense behaviors

    Neuron 93:33–47.

    https://doi.org/10.1016/j.neuron.2016.11.045

    • PubMed
    • Google Scholar
100. 1. Zingg B
     2. Peng B
     3. Huang J
     4. Tao HW
     5. Zhang LI

     (2020) Synaptic specificity and application of anterograde transsynaptic AAV for probing neural circuitry

     The Journal of Neuroscience 40:3250–3267.

     https://doi.org/10.1523/JNEUROSCI.2158-19.2020

     • PubMed
     • Google Scholar

Acceptance summary:

The authors have used a new mono-trans-synaptic tracing technique to characterize disynaptic cerebrocerebellar pathways. The results suggest a substantial amount of overlap within the cerebellar cortex of projections from distinct regions of cerebral cortex. The comprehensive results are beautifully presented and provide an important foundation for our understanding of how efference copies and other cortical information might be used by cerebellum to perform accurate sensory motor actions.

Decision letter after peer review:

[Editors’ note: the authors submitted for reconsideration following the decision after peer review. What follows is the decision letter after the first round of review.]

Thank you for submitting your work entitled "Convergence of multimodal inputs connecting the cerebral cortex to the cerebellum" for consideration by eLife. Your article has been reviewed by a Senior Editor, a Reviewing Editor, and three reviewers. The following individuals involved in review of your submission have agreed to reveal their identity: Richard Apps (Reviewer #2); Roy V Sillitoe (Reviewer #3).

Our decision has been reached after extensive consultation between the reviewers and the Reviewing Editor. Based on these discussions and the individual reviews below, we regret to inform you that we are not prepared to move forward with publication in eLife at this time. Although the reviewers agreed that the manuscript has the potential to serve as a thorough atlas for cortical projections to precerebellar nuclei, it was agreed that this goal was not achieved by the current manuscript. There were concerns regarding specific biological conclusions that can be reached at this stage, based on the data presented. However, the Editors and reviewers were enthusiastic about several aspects of this study. We have therefore prepared a summary of suggestions brought up during the consultation process, which involve new data and substantial revisions to the manuscript. Should these points, as well as the individual comments of the reviewers, be addressed in a reconfigured version of the paper, we would be willing to consider such a future submission for publication at eLife.

1) Overall, the reviewers felt that packaging this paper as a Short Report made it difficult to evaluate the findings, and we suggest expanding the manuscript to strengthen the evidence for the claims that are made. All reviewers wanted more documentation of injection sites (volumes and cell counts), and more evidence for truly comprehensive mapping. This was seen as critical for supporting the main potential strength of this paper as a comprehensive atlas study.

2) While all three reviewers supported the paper in principle, and agreed that it presents an interesting angle on topography and convergence of cortico-cerebellar connections, they each struggled with the data interpretation in light of limitations of the technique. The fundamental problem was that the experiments are unable to indicate the brainstem origin of the MF projection patterns. They may be mainly from the pons, but it is not possible to say if any of the other brainstem structures labelled are also sources. The reviewers came up with two suggested experiments to address this concern:

a) In the spirit of an "atlas paper," the authors could confirm pontine projections to the labeled and unlabelled (A1) regions of cerebellum using retrograde AAV (to rule out extrapontine projections). This could validate the method and strengthen novel findings such as pontine projections to lobes IV/V.

b) Another possibility could be to do dual viral injections: (transsynaptic) AAV-cre in cortex, and AAV-floxed-XFP in pons. If feasible, this could confirm the presence of certain cortical-pontine-cerebellar projections.

3) It was agreed that the conclusions regarding potential multimodal integration in individual granule cells were not adequately supported by the data. Rather, this was seen as one possible (and reasonable) interpretation based on a general overlap of MF labelling. Although reviewers (particularly #1) suggested specific experiments that could strengthen this claim, we do not think that it is critical to demonstrate this kind of convergence in the current manuscript. The demonstration of broad overlap itself is interesting. However, the conclusions regarding ultimate convergence should be toned down. The current findings can be presented as broadly consistent with the idea of multimodal integration in individual granule cells, which has been previously suggested by earlier studies (eg Huang, Ishikawa…).

We hope that you will find these comments and the reviews below helpful in preparing a revised version of the manuscript.

Reviewer #1:

In this manuscript, Henschke and Pakan describe a beautiful set of experiments in which they used an AAV2.1-based anterograde, fluorescence protein-based tracing technique (Zingg et al., 2017) to elucidate cerebro-pontine-cerebellar pathways. They focused on primary sensory (S1, V1 and A1), motor and one association area (PPC). They observed, as in previous studies, that these regions target ipsilateral basal pons in a spatially segregated manner. In turn, cerebellar mossy fiber (MFs) are found to be labelled in specific regions cerebellum including both in the vermis and lateral hemispheres. These results are consistent with other tracer and electrophysiological studies. Interestingly they find that A1 does not provide pontine-cerebellar projections, but dorsal auditory cortex does. This contrasts previous results in other species. Finally, and most novel, the authors examined the spatial overlap of MF projections from different cortical regions and show that in some regions multimodal processing is likely. While this has been shown for single granule cells in vivo in Crus I (Ishikawa et al., 2016), a survey of what cerebellar regions are likely to receive multimodal cerebro-pontine input had not been shown previously. In summary, the authors provide provoking evidence of a strategy to specifically label and manipulate different that pontine-cerebellar circuits will be possible.

The technique and results described in this manuscript are illuminating, and the data thoroughly analyzed. The manuscript, therefore, has the potential to serve as a thorough atlas for cortical projections to precerebellar nuclei. This study paves the way for future studies to refine our understanding of how efference copies and other cortical information might be used by cerebellum to perform accurate sensory motor actions. Unfortunately, limitations in the method preclude a clear biological conclusion from the current dataset, beyond the notion that cortical-pontine-cerebellar wiring is similar in mice as other species:

1) The authors show that AAV1-cre injections in most cortical regions tested indeed label the pons, but also extra-pontine precerebellar nuclei. This highlights the fundamental problem that we cannot be sure that the MF projection patterns in cerebellum are solely a result of pontine projections -as implied in the manuscript. One example of a new biological conclusion is that cerebro-pontine projections were largely thought to be restricted to posterior and lateral cerebellum, but here the authors seem to show prominent projections in lobes 4 and 5. However, we cannot be sure of this conclusion because the MF labelling in lobes 4 and 5 could be from another precerebellar nucleus. One possible experiment to confirm that pons projects to a given region of cerebellum would be to perform retrograde labelling from different cerebellar regions identified in the anterograde transynaptic method, and verify that cell bodies in pons are labeled.

2) Another conclusion proposed by the authors is that multimodal integration is likely in certain cerebellar regions. While overlapping domains of MF projections is necessary to achieve multimodal integration. A critical question is whether single granule cells receive different cortical inputs. Such multimodal combinations have been described for motor and proprioception (Huang et al., 2015), for visual, somatosensory and auditory (Ishikawa et al., 2015), as well as visual and vestibular information (Chabrol et al., 2015). Understanding the role of multimodal processing in cerebellum requires knowing whether cortical information is "mixed" at the level of single granule cells, as proposed by Marr and Albus. Are there specific wiring rules for cerebro-ponto-cerebellar projections? For example, perhaps corollary information only pairs with its principal sensory modality partner. Unfortunately, these experiments are more challenging and would require two-color labelling using another conditional method (e.g. Flp), in addition to a strategy to sparsely label GCs (electroporation, patch or mouse lines (Huang et al., 2013)). Nevertheless, this would significantly advance our understanding of how cortical information is processed at the input layer of cerebellum.

3) The lack of cortico-pontine projections into cerebellum from A1 is surprising, in light of previous work. Thus, it is necessary to independently confirm this result using retrograde labelling strategies. If true, a better discussion of why it might be different than previous results is merited. Finally, another concern about the A1 experiments, is that in Figure 1—figure supplement1 AAV1-cre injections there is very little labeling of inferior colliculus. As I understand the method, retrograde labelling is also expected. As the exact mechanism of transynaptic propagation of the virus or Cre is not known, is it possible that the method failed for this brain region?

I also have additional specific concerns.

1) When examining table 2, I noticed that similar numbers of labelled precerebellar cell bodies can produce differences in the number of MFs by nearly a factor of 10. Does this discrepancy limit the ability normalize for labelling efficiency and thus limit quantification of the results? How could this happen?

2) The conditions used to perform imaging should be better described. For example, how was high-resolution imaging performed with a 2.5 x objective? What was the NA of this objective? Given the accuracy of the galvanometer mirrors, necessary zooms may not be possible to achieve true diffraction limit resolution. The pixel and image sizes should be mentioned.

3) How was the injection volume measured? The width of the column size measure was presumably estimated from a line profile along an image, but what width parameter was taken as a width. The images shown are clearly saturated. Is this the same image in which the size of the infected region was estimated?

Reviewer #2:

This is a short report using a trans mono synaptic anterograde tracer method to chart cerebro-cerebellar anatomical projections in mice. Injections into a number of different neocortical regions (M1, S1, V1, A1, posterior parietal association cortex or the dorsal field of auditory cortex) revealed topographically organized projections to the pons and mossy fibre terminals in the cerebellar cortex. The report is generally well written and provides a valuable 'road map' for future studies of the functional significance of cerebro-cerebellar projections in mice.

Essential revisions:

1) The report needs to make clear what are the novel findings.

2) How did differences in cell counts and other measures of injection site affect the pattern and extent of anterogradely labelled cell and mossy fibre terminals? It was not clear to me if Figure 2A shows the total extent of injection sites into different neocortical areas or just the defined regions of interest. Either way the area clearly varies considerably between targets which will affect projection density and possibly topography.

3) The histogram axes in Figure 2D are not all drawn on the same scale making comparisons difficult. Also percentage values are potentially misleading given the large variation in cell counts and mossy fibre terminals listed in Figure 1—figure supplement 1B.

4) Given that the pons is the primary source of mossy fibre inputs, how did the authors determine that other brainstem nuclei also containing labelled cells in the same experiments necessarily provided mossy fibre projections?

5) The topographical organization within the pons should be compared to the principles of organization defined in previous studies (eg Leergaard, 2003; Odeh et al., 2005).

6) The discussion should consider the extent to which cerebro-cerebellar pathways are conserved across mammalian species. How useful is the mouse as a model for study of cerebro-cerebellar projections?

Reviewer #3:

Henschke and Pakan have submitted a manuscript entitled "Convergence of multimodal inputs connecting the cerebral cortex to the cerebellum" in which they use modern neuronal tracing methods to map circuit projections into the mouse cerebellum. The authors traced the cerebellar inputs originating from sensory, motor, and association cortices. They argue that diverse functional connections project from the cortex to cerebellum, where they ultimately exhibit a convergent terminal field distribution within specific lobules. The manuscript is well written and technically, it offers a much-needed approach to better understand the organization and trajectories of major cortico-cerebellar projections. In addition, the figures are well made, schematics very helpful, and overall the panels are easy to follow. However, below we provide a number of comments and concerns that we hope will improve the clarity and impact of the study.

1) Throughout the text, the discussion of A1 and its unique projection through non-pontine pre-cerebellar nuclei is often highlighted, however the significance of this point is not well articulated. Further clarification in the abstract and in the body is needed if the authors wish to highlight the uniqueness of this pathway. This is especially true given the findings in the text that S1 and M1 both have substantial, if not even majority in the case of S1, projections to non-pontine pre-cerebellar nuclei.

2) Introduction. Please clarify why the identified cortical regions were selected. In addition, while we agree that the characterization of the injections is rather comprehensive, there is a limitation in this study in that either the number of cortical regions chosen or the breadth of the characterization of the selected regions (ie: why weren't at least two neighboring sites in a given cortical region analyzed) prevent the present study from providing a fully comprehensive map, as stated by the authors.

3) Figure 1A. Please indicate the circumscribed subregion in each cortical area where the injection was made.

4) Subsection “Anterograde tracing of indirect cerebrocerebellar pathways”. Please clarify percentages for A1 projections in order to make the second sentence "This pattern of extra-pontine labeling was similar…" clearer. Further, in Figure 2B, while the scarcity of the projections to the pontine nuclei is similar, they seem to be qualitatively different in that A1 projects terminals, while the AuD experiment labels cell bodies. This distinction is not clear in the text. Moreover, the fact you see terminals in one region and then cell bodies another makes it a challenge to piece together what the actual pathway(s) might look like. That is, how do you substantiate the claim that the cell bodies in the pons (the unexpected labeling) actually project to the cerebellum? And on the flip side, for the majority of S1 labeling, which is in the precerebellar non-pontine nuclei, can we really assume that these all project to cerebellum? If not, what percentage?

5) The Supplementary file 1 is a bit difficult to interpret. Please include the percentages referenced in the text in the table. In addition, it is unclear why in some injection sites the sum of the individual pre-cerebellar nuclei cells equals the summed total, while in other cases the sum is less than or greater than the listed total. (ie M1-1 52 vs 55; V1-1 8 vs 8; A1-1 10 vs 8)

6) The significance of terminals in pontine/pre-cerebellar nuclei without cell body labelling is unclear and there should be an explanation of this in the text. For instance, in regard to A1/AuD does this indicate inefficiency in trans-synaptic labelling, that there is an alternative monosynaptic projection from A1/AuD to the pontine nuclei, or is there an alternative explanation? This is mentioned for M1 projections to the olivary nuclei (Subsection “Anterograde tracing of indirect cerebrocerebellar pathways”).

7) In the subsection "Convergence of multimodal cerebrocerebellar input within lobules…" the metric for dominant representation (> or < 55%) is problematic given the relative sparsity of the injections (either across or within cortical regions). Furthermore, given the variability of numbered terminals across individual animals in a given cortical area (ie from 2406 to 25616 from the M1 injections), this type of quantification and conclusions about convergence seem premature.

8) While the discussion about convergence and integration is quite interesting to speculate upon, it is hard to grasp whether the current data is sufficient to reach such a conclusion. Given the vast number of granule cells and the fine scale nature of cerebellar microzones, conclusions about integration of multimodal afferent information by single units (whether microzone or granule cell) cannot be easily drawn. To do this, a method distinct from the approach used in this paper would be needed whereby labelling from two distinct cortical areas could be distinguished in the cerebellum in a single animal. In the end, I am having trouble fully appreciating how integrated the "multimodal" and "convergence" nature of the pathways actually is, based on the data provided.

9) Finally, there is a core assumption at play, which is that cortical injection - pontine/precerebellar cell body labeling - mossy fiber terminal marking. In the case of cortico-ponto-cerebellar pathways, the abundance of literature makes this assumption sound. However, in the case of the precerebellar projections (especially S1 which has a majority non-pontine projections), sagittal sections (for example) demonstrating the axonal projections, and elucidating the monosynaptic pathway would provide a helpful piece of evidence to support the current content.

1) In the Abstract, it is not clear what is actually meant by "Prominent terminal overlap across motor and sensory modalities…". And, how was this measured?

2) It would be very helpful to include the species studied in the Title and/or the Abstract.

3) It is critical that the authors fully outline the limitations of the mono-trans synaptic anterograde viral tracer, in their hands, and specifically for the purpose of this study.

4) In Figure 1B, it is not clear what the red arrows are representing and pointing towards. Aren't the arrows pointing the wrong way if this is to show anterograde tracing direction?

5) Is there a time dependence on the tracing? That is, do longer periods of survival after injection label additional projections?

6) In Figure 1F, M1 should project ipsilateral, but in the cerebellum one can see many terminals on both sides. Please explain.

7) The authors state "…extent M1, indicating the presence of a polysynaptic cerebro-olivary pathway…" What is the literature to support this?

8) The authors state "We quantified the number of resulting mossy fiber terminals throughout the extent of the cerebellum and found that this was highly variable across cortical regions…" How variable is the size of the infected cell population in the cortex?

9) The authors state "There was a clear and consistent topography of…" It would be helpful to fully define what you mean by topography here. There are many levels of topography, in different brain regions, and this could mean very different things to different researchers.

10) In Figure 3E, what does each data point represent? A single terminal?

11) Along the same lines as above, it would be helpful to see more actual data with the combined zebrin labeling. Mossy fiber patterns, by nature of their clustered appearance, are not so easily appreciated and therefore additional examples, at higher power magnification, would be welcomed.

12) The authors state "This allowed for a detailed comparison of cerebellar regions across brains and, hence, across functional cortical regions representing multiple modalities (see Figure 3—figure supplement 1)." However, I don't see a full description or explanation of the data in the text.

13) The number of animals used in the study seems quite low.

14) In Figure 3—figure supplement 1, what is the red staining in Purkinje cells?

[Editors’ note: further revisions were suggested prior to acceptance, as described below.]

Thank you for resubmitting your work entitled "Cerebral cortical connections to the cerebellum across multiple modalities" for further consideration by eLife. Your revised article has been evaluated by Richard Ivry (Senior Editor) and a Reviewing Editor.

The manuscript has been improved but there are some remaining issues that need to be addressed before acceptance, as outlined below:

Summary:

Henschke and Pakan have provided a substantially revised version of a paper describing the connectivity between different areas of the cerebral cortex with the cerebellum. The authors have used a virus based transsynaptic tracing approach to show that multi-modal inputs may converge upon specific topographical domains within the cerebellar vermis and hemispheres. The study is anatomical in nature and takes an in-depth analysis of mossy fiber terminal field distributions in the cerebellum, but the authors also examine the different intermediate projections of the cerebral-cerebellar projections that are located within various brainstem nuclei. The paper is well-written and the images are high quality. reviewers particularly appreciated the addition of important controls (characterization of extra-pontine sources of MFs, confirmation of pontine sources using retrograde labeling, and identification of an A1-colliculo-cerebellar pathway), which significantly increase confidence in their original findings and propel the study towards the authors' original objective as a seminal reference, or atlas, for the characterization of cerebrocerebellar mossy fiber (MF) pathways.

Essential revisions:

The major remaining concern – shared by both reviewers – is the overemphasis/ speculation on 'multimodality' for this essentially anatomical study. Specifically:

1) I was delighted to see a more detailed examination of the location of MFs from different modalities within each lobule, since a prerequisite for multimodal processing is that the information project to the same subregion of a lobule. I also found rather striking the case in Crus II where there was still segregation between two MF types within the same lobe. This latter result highlights the notion that multimodal innervation within lobes is necessary but not sufficient to conclude multimodal processing. I therefore encourage the authors to soften their choice of words of "highly multimodal" and "moderately multimodal" as a conclusion of Figure 4. Perhaps the use of the term "lobule co-innervation" is more appropriate. Then after Figure 5, the argument for putative multimodal processing is much stronger, but still only suggestive.

2) Indeed, Figure 5 shows an essential set of analyses suggestive of multimodal processing, but I was left wanting for some clear quantification of "intermingled" and a simple overall summary.

a) Would it be possible to analyze the distribution of nearest-neighbor distances between terminals of different origins? Those that co-innervate would have shorter distances and those that do not, e.g. Crus II, would show a shifted distribution. Perhaps a more sophisticated point-process analysis, such as the application of the bivariate Ripley K-function, could be used to test for spatial randomness between two species of points and provide statistical confidence.

b) To add some statistical rigor to the alignment with adolase C staining, one could compare the frequency of AldoC positive and negative terminals for each cortical injection. Statistical tests for the frequency of events can then be used.

3) The title continues to hint at a more functional set of analyses, which the paper really does not provide. Please revise.

4) Similarly, the Abstract could present the key anatomical distinctions that were uncovered rather than the speculative discussion about multimodal sensory input – this functional idea should remain, but it should be toned down to make space to better clarify the actual anatomical findings.

5) The main Figure 6 merits a more thorough quantification of retrograde labeling.

6) Quantification and presentation of co-labeled and spatially intermingled neurons following dual viral tracing injections would be appropriate.

7) I like the estimation of the number of MFs per pontine neuron and would like to see it as a main figure.

8) The Discussion section rambles on a bit. I believe it can be shortened and used to more clearly summarize the major findings, the similarities and differences with previous results, and the implications for cerebellar function.

9) The section titles are rather vague. For example, "Organization of cerebrocerebellar mossy fiber terminals" is essentially duplicated in the Results and Discussion, and perhaps needs more specific wording. "Spatial organization of cerebrocerebellar mossy fiber types". I am not really sure why there is a Discussion subsection on "Diversity of cerebrocerebellar pathways" as you define the pathways by viral injection. Perhaps something like: "Cerebellar cortical target diversity of cerebrocerebellar pathways?"

[Editors’ note: the authors resubmitted a revised version of the paper for consideration. What follows is the authors’ response to the first round of review.]

Our decision has been reached after extensive consultation between the reviewers and the Reviewing Editor. Based on these discussions and the individual reviews below, we regret to inform you that we are not prepared to move forward with publication in eLife at this time. Although the reviewers agreed that the manuscript has the potential to serve as a thorough atlas for cortical projections to precerebellar nuclei, it was agreed that this goal was not achieved by the current manuscript. There were concerns regarding specific biological conclusions that can be reached at this stage, based on the data presented. However, the Editors and reviewers were enthusiastic about several aspects of this study. We have therefore prepared a summary of suggestions brought up during the consultation process, which involve new data and substantial revisions to the manuscript that are likely to take more than two months. Should these points, as well as the individual comments of the reviewers, be addressed in a reconfigured version of the paper, we would be willing to consider such a future submission for publication at eLife.

1) Overall, the reviewers felt that packaging this paper as a Short Report made it difficult to evaluate the findings, and we suggest expanding the manuscript to strengthen the evidence for the claims that are made. All reviewers wanted more documentation of injection sites (volumes and cell counts), and more evidence for truly comprehensive mapping. This was seen as critical for supporting the main potential strength of this paper as a comprehensive atlas study.

As suggested, we have now structured the manuscript as a full Research Article adding additional experiments, main and supplementary Figures, and agree that this allows us to more fully elaborate on the many implications that follow from our results.

2) While all three reviewers supported the paper in principle, and agreed that it presents an interesting angle on topography and convergence of cortico-cerebellar connections, they each struggled with the data interpretation in light of limitations of the technique. The fundamental problem was that the experiments are unable to indicate the brainstem origin of the MF projection patterns. They may be mainly from the pons, but it is not possible to say if any of the other brainstem structures labelled are also sources. The reviewers came up with two suggested experiments to address this concern:

We have performed a number of new experiments that provide additional information regarding the brainstem origin of the mossy fiber projections. These are described in detail below, and also further in the specific responses to the three reviewers.

a) In the spirit of an "atlas paper," the authors could confirm pontine projections to the labeled and unlabelled (A1) regions of cerebellum using retrograde AAV (to rule out extrapontine projections). This could validate the method and strengthen novel findings such as pontine projections to lobes IV/V.

We have confirmed the finding of pontine projections to lobules IV/V by using retrograde tracers as suggested (see new Figure 6 and Figure 6—figure supplement 1).

We have further completed retrograde injections in the key cerebellar regions identified as hubs for multimodal spatial convergence (see new Figure 6 and related supplementary Figures). However, It is difficult to know specifically which A1 receiving cerebellar regions (‘unlabelled’ through pons) would not actually receive pontine projections via other cortical areas and hence still result in substantial pontine labelling via retrograde injections (e.g. see lobule VII injections and Figure 6 – supplementary Figure 2). Pontine and extrapontine pathways may have overlapping terminal fields in the cerebellum – hence, success in separating them spatially with retrograde injections would be unlikely. This is also evident from our retrograde injections in Sim, Crus I, and lobules IV/V, VI, and VII where in each case we found retrogradely labelled cells in both pontine and numerous extrapontine nuclei (see new Figure 6 and Figure 6—figure supplement 1 and Figure 6—figure supplement 2).

Furthermore, we do not think that extrapontine projections should be ‘ruled out’ in this regard – but rather that these pathways are actually likely to contribute (in combination with pontine pathways) to disynaptic cerebrocerebellar input (see Discussion section; reviewer 1 point 1). Of course, this makes these pathways more complicated to separate on the individual level, and the feasibility of making anatomical injections in each separate precerebellar nuclei to trace individual mossy fibers is quite low (e.g. due to difficulty in targeting these brainstem nuclei without approaching through the cerebellum, see also point 2b below). However, we feel that the addition of our new experiments as a whole have added substantial information regarding the potential for both pontine and extra-pontine cerebrocerebellar pathways and the implications of this are also discussed in more detail in the revised Discussion section.

b) Another possibility could be to do dual viral injections: (transsynaptic) AAV-cre in cortex, and AAV-floxed-XFP in pons. If feasible, this could confirm the presence of certain cortical-pontine-cerebellar projections.

Due to the technical challenges inherent in this approach as well as some limitations specified below, we opted for the strategy described above (see point 2a). Specifically, to reach the pontine nuclei you must either go through the cerebellum or cortex – creating potential confounds through the chance for AAV leakage of the floxed-XFP construct. Additionally, one would need 100% transfection rate in the pontine nuclei to be able to conclude that any RFP labelled mossy fiber terminals were from extra-pontine sources. If even one or two pontine cells expressed RFP but not the floxed-XFP, then we would still be unable to conclude the specificity of this pathway; 100% transfection rates with AAVs are rarely feasible – given the rostral caudal extent of labelling possible in the pons, even less so. Finally, to accurately determine the likelihood of each separate precerebellar nuclei projecting as intermediate connections between the cerebral cortex and cerebellar cortex we would have to complete this strategy (AAV-floxed-XFP) for all noted individual precerebellar nuclei. This strategy was not feasible – due to the same issues as stated above, as well as the need for targeting each nuclei without spreading to surrounding structures but still resulting in enough labelling to double label mossy fibers.

In short, we fully agree that the precise brainstem origin of these mossy fiber terminals is of great interest. The most feasible strategy (retrograde injections in the cerebellar cortex, see point 2a) allowed us to determine with greater precision the potential for the specific extrapontine precerebellar nuclei that receive corticofugal input to, in turn, provide input to key cerebellar regions of multimodal spatial convergence. We believe that this additional information provided by our study will be vital to guide many future studies specifically targeting individual pathways for more in depth polysynaptic circuit analysis. This has now been discussed throughout the manuscript and many potential avenues for future research pointed out in the Discussion section.

3) It was agreed that the conclusions regarding potential multimodal integration in individual granule cells were not adequately supported by the data. Rather, this was seen as one possible (and reasonable) interpretation based on a general overlap of MF labelling. Although reviewers (particularly #1) suggested specific experiments that could strengthen this claim, we do not think that it is critical to demonstrate this kind of convergence in the current manuscript. The demonstration of broad overlap itself is interesting. However, the conclusions regarding ultimate convergence should be toned down. The current findings can be presented as broadly consistent with the idea of multimodal integration in individual granule cells, which has been previously suggested by earlier studies (eg Huang, Ishikawa…).

We agree that this is a specific point of interest and also should be explored in future studies – particularly with further development of circuit tracing tools combined with electrophysiological techniques. Here, we have been more careful to describe convergence as regional or spatial in nature, rather than at the cellular-integration level, and have expanded our discussion with regard to the individual granule cell level with reference to previously published literature which was already cited (e.g. Huang, Ishikawa, Hantman, etc) and including additional evidence from Markwalter et al., 2019 (subsection “Neuroanatomical injections”).

Reviewer #1:

In this manuscript, Henschke and Pakan describe a beautiful set of experiments in which they used an AAV2.1-based anterograde, fluorescence protein-based tracing technique (Zingg et al., 2017) to elucidate cerebro-pontine-cerebellar pathways. They focused on primary sensory (S1, V1 and A1), motor and one association area (PPC). They observed, as in previous studies, that these regions target ipsilateral basal pons in a spatially segregated manner. In turn, cerebellar mossy fiber (MFs) are found to be labelled in specific regions cerebellum including both in the vermis and lateral hemispheres. These results are consistent with other tracer and electrophysiological studies. Interestingly they find that A1 does not provide pontine-cerebellar projections, but dorsal auditory cortex does. This contrasts previous results in other species. Finally, and most novel, the authors examined the spatial overlap of MF projections from different cortical regions and show that in some regions multimodal processing is likely. While this has been shown for single granule cells in vivo in Crus I (Ishikawa et al., 2016), a survey of what cerebellar regions are likely to receive multimodal cerebro-pontine input had not been shown previously. In summary, the authors provide provoking evidence of a strategy to specifically label and manipulate different that pontine-cerebellar circuits will be possible.

The technique and results described in this manuscript are illuminating, and the data thoroughly analyzed. The manuscript, therefore, has the potential to serve as a thorough atlas for cortical projections to precerebellar nuclei. This study paves the way for future studies to refine our understanding of how efference copies and other cortical information might be used by cerebellum to perform accurate sensory motor actions. Unfortunately, limitations in the method preclude a clear biological conclusion from the current dataset, beyond the notion that cortical-pontine-cerebellar wiring is similar in mice as other species:

1) The authors show that AAV1-cre injections in most cortical regions tested indeed label the pons, but also extra-pontine precerebellar nuclei. This highlights the fundamental problem that we cannot be sure that the MF projection patterns in cerebellum are solely a result of pontine projections -as implied in the mansucript. One example of a new biological conclusion is that cerebro-pontine projections were largely thought to be restricted to posterior and lateral cerebellum, but here the authors seem to show prominent projections in lobes 4 and 5. However, we cannot be sure of this conclusion because the MF labelling in lobes 4 and 5 could be from another precerebellar nucleus. One possible experiment to confirm that pons projects to a given region of cerebellum would be to perform retrograde labelling from different cerebellar regions identified in the anterograde transynaptic method, and verify that cell bodies in pons are labeled.

We performed additional tracing experiments with injections of the retrograde tracer Choleratoxin-B (CTB) into lobes IV/V, VI, VII, Sim and crus I of the cerebellum, as well as using a dual injection approach as a proof of principle to show double labelled cells in the pontine nuclei from injections of the trans-mono-synaptic AAV1.cre into M1 and retrograde CTB injections in lobule IV/V (Figure 6 and Figure 6—figure supplement 1, Figure 6—figure supplement 2). Our results show that the majority of retrogradely labeled cells were located in the pons, with some cells also double labeled, i.e. direct confirmation that these pontine cells receive disynaptic input from the specified cortical regions. We also note, however, that many precerebellar nuclei identified as receiving cortical projections also contained retrograde labelling in these key regions (e.g. lateral reticular nucleus (LRt), reticulotegmental nucleus (RtTg), vestibular nucleus (VN), interpolar part of the spinal trigeminal nucleus (Sp5I) and matrix region x (Mx) (see new Figure 6 and Figure 6—figure supplement 1). Although double labelled cells were not directly observed in extra-pontine nuclei, the labelling was spatially overlapping (Figure 6B) and the proportion of retrogradely labeled cells in extra-pontine nuclei were particularly substantial from lobule IV/V and VI (Figure 6—figure supplement 1). Given the low density of trans-synaptic mossy fiber labelling and the spatially restricted injection sites, we believe the probability of observing double labelled cells within these precerebellar nuclei was very low; however, importantly, these results indicate the potential for specific precerebellar nuclei to either relay or integrate cerebrocerebellar information. Therefore, we conclude that cortical information is likely to reach the cerebellum through both pontine as well as extra-pontine intermediate nuclei. This is now discussed in detail in the revised manuscript (e.g. Discussion section).

2) Another conclusion proposed by the authors is that multimodal integration is likely in certain cerebellar regions. While overlapping domains of MF projections is necessary to achieve multimodal integration. A critical question is whether single granule cells receive different cortical inputs. Such multimodal combinations have been described for motor and proprioception (Huang et al., 2015), for visual, somatosensory and auditory (Ishikawa et al., 2015), as well as visual and vestibular information (Chabrol et al., 2015). Understanding the role of multimodal processing in cerebellum requires knowing whether cortical information is "mixed" at the level of single granule cells, as proposed by Marr and Albus. Are there specific wiring rules for cerebro-ponto-cerebellar projections? For example, perhaps corollary information only pairs with its principal sensory modality partner. Unfortunately, these experiments are more challenging and would require two-color labelling using another conditional method (e.g. Flp), in addition to a strategy to sparsely label GCs (electroporation, patch or mouse lines (Huang et al., 2013)). Nevertheless, this would significantly advance our understanding of how cortical information is processed at the input layer of cerebellum.

We agree that this is a very interesting question, and indeed, difficult to address fully at this time with our current tools. A very recent proof of principle paper has just been published (Zingg et al., 2020) using similar techniques to that suggested, with Flp and cre dual labeling, so this may be a strategy we can also pursue in the future given the availability of AAVs, mouse lines, etc. Regardless, for any future in vivo study of multimodal cellular integration in this regard, targeting in the cerebellum will also be difficult since the density of labelled mossy fiber projections is limited, one would need to maximize the likelihood of targeting investigations to a region (and even a specific module) with high spatial overlap of cerebrocerebellar terminals. This was a large motivation for the current study and is where we see a main strength – as a vital first step/road-map towards future in vivo experiments examining the convergence of cortical input in the cerebellum; making the current manuscript a unique resource moving forward for the field as a whole (see also response to editor, point 3).

3) The lack of cortico-pontine projections into cerebellum from A1 is surprising, in light of previous work. Thus, it is necessary to independently confirm this result using retrograde labelling strategies. If true, a better discussion of why it might be different than previous results is merited. Finally, another concern about the A1 experiments, is that in Figure 1—figure supplement 1 AAV1-cre injections there is very little labeling of inferior colliculus. As I understand the method, retrograde labelling is also expected. As the exact mechanism of transynaptic propagation of the virus or Cre is not known, is it possible that the method failed for this brain region?

To further support our finding of a lack of cortico-pontine projections from A1 we performed two additional sets of experiments. First, we injected a retrograde CAV.cre virus into the pons in the tdTomato reporter mice and found numerous retrogradely labeled cells in the dorsal (AuD) and ventral (AuV) auditory cortex but none in the primary auditory cortex (A1). This finding confirms our previous results that there is no mono-synaptic cerebro-pontine pathway originating in mouse A1.

However, there is a disynaptic pathway connecting A1 with the IC and the pons. This was already evident from our previous experiments, where we found mono-trans-synaptic labeled cells (most likely not retrogradely labeled cells; see below) in the IC. These cells were mainly found in the ECIC and DCIC but rarely in the CIC, as shown in Figure 2 of the revised version of the manuscript, which better illustrates the large amount of labeling in the ECIC/DCIC; therefore, we do not feel as though this method failed along this particular pathway and this is now further demonstrated. Additionally, in order to provide further support for a disynaptic A1-IC-pons pathway, we injected the anterograde trans-monosynaptic AAV1.cre virus into the IC. Following these injections, we found labeled cells in the pons and subsequent MFs in the cerebellum (Figure 1—figure supplement 2).

Based on the results of these two new sets of experiments we conclude that there is indeed not a direct cerebro-pontine pathway to the cerebellum from A1, but instead likely a trisynaptic pathway via the IC. Although the extent of this trisynaptic pathway is yet to be precisely determined, we discuss these findings and outline the potential pathways in detail in the revised manuscript (subsection “Anterograde tracing of indirect cerebrocerebellar pathways”; Discussion section).

Regarding the potential retrograde transport of the AAV1.cre virus, we note that there is no reported projection from IC directly to A1 in mice, this pathway is ‘top-down’ from A1 to IC and not reciprocal, rather information from IC travels to A1 via the thalamus (see also Zingg et al., 2020 where this pathway is chosen specifically for its unidirectional nature). We also note that following our AAV1.cre injections into the IC, we found only a couple labeled cells in the auditory cortex of each experimental animal – very likely representing the extent of retrograde capability of this AAV. This is also in agreement with the original Zingg and colleagues papers (2017; 2020), demonstrating the retrograde transport of this virus is not substantial and far less efficient than in the anterograde direction. These considerations have been clarified in the revised manuscript (see subsection “Neuroanatomical injections”).

4) When examining table 2, I noticed that similar numbers of labelled precerebellar cell bodies can produce differences in the number of MFs by nearly a factor of 10. Does this discrepancy limit the ability normalize for labelling efficiency and thus limit quantification of the results? How could this happen?

We do not wish to downplay the variability in the quantity of labelling we see after viral injections, and hence have mentioned this is in a number of places (including providing the data in the revised Supplementary file 1). However, we do see a significant correlation between the number of anterogradely labeled cells within precerebellar nuclei and the number of mossy fiber terminals (this has been made more clear in the revised manuscript, see subsection “Intermediate cerebrocerebellar brainstem pathways”; Figure 6—figure supplement 3) and a surprising amount of consistency across our cases in the pattern of observed labelling. We have made efforts to present the data in both normalized (scaled [Figure 3] and unscaled [Figure 4]) and raw (Supplementary file 1) format to avoid any misleading conclusions based on normalization.

We believe the variability in absolute numbers is a property of the virus/trans-synaptic transport which is highly dependent on the titre, not only of the injected solution, but subsequently that gets taken up into individual cells; which, in turn, is dependent on a number of factors: volume, spread, speed of injection, etc. For instance, an individual cell that contains a high virus titre will result in transport, however, a neighboring cell that still contains virus at the injection site, but at a low titre, will not contribute to the trans-synaptic quantification. We believe this introduces some inherent variability across cases, even with similar injection site total volume. We have expanded our description of the potential factors to be aware of during injection in this regard (see subsection “Neuroanatomical injections”).

5) The conditions used to perform imaging should be better described. For example, how was high-resolution imaging performed with a 2.5 x objective? What was the NA of this objective? Given the accuracy of the galvanometer mirrors, necessary zooms may not be possible to achieve true diffraction limit resolution. The pixel and image sizes should be mentioned.

We have added the appropriate information into the revised manuscript: Sections of 40µm thickness were examined using a confocal microscope (Zeiss LSM 700, Germany) equipped with a 2.5x objective (NA 0.085, Zeiss, Germany). For each section throughout the extent of the cerebellum two high-resolution images (2048 x 2048 Pixel) were acquired, i.e. one for each hemisphere. The two tiles were merged using custom written MatLab scripts (Mathworks, MA, USA; resulting in a ~4000 x 4000 pixel image of the cerebellum). See subsection “Data analysis”.

6) How was the injection volume measured? The width of the column size measure was presumably estimated from a line profile along an image, but what width parameter was taken as a width. The images shown are clearly saturated. Is this the same image in which the size of the infected region was estimated?

We have added further information regarding the exact parameters used to determine the injection site volume, including a supporting Supplementary file 2A: The injection sites had a roughly cylindrical shape. All sections that covered the central core but not surrounding halo of each injection site were included in the analysis (see Supplementary file 2). We then calculated injection site volume as follows: V = π*a*b*h, where h corresponds to the maximum value across sections for the height of the injection site [dorso-ventral direction], a corresponds to the maximum value across sections for the radius of the injection site parallel to the cortical layers [medio-lateral direction], and b corresponds to the rostrocaudal extent of the core injection site. The Line Measure Tool of the Zen software (Zeiss, Germany) was used to measure h and a, and b was calculated by counting the numbers of sections covering the core injection site multiplied by their thickness (40 µm). See subsection “Data analysis”.

Reviewer #2:

This is a short report using a trans mono synaptic anterograde tracer method to chart cerebro-cerebellar anatomical projections in mice. Injections into a number of different neocortical regions (M1, S1, V1, A1, posterior parietal association cortex or the dorsal field of auditory cortex) revealed topographically organized projections to the pons and mossy fibre terminals in the cerebellar cortex. The report is generally well written and provides a valuable 'road map' for future studies of the functional significance of cerebro-cerebellar projections in mice.

Essential revisions:

1) The report needs to make clear what are the novel findings.

The main strength of our work is the description of the multiple disynaptic pathways, in all their complexity, in a single study directly comparable across brain regions. Here we go beyond a focus simply on traditional pontine projections and also detail the various precerebellar nuclei that receive both direct cortical input and project to the cerebellum, for corticocerebellar pathways originating from multiple sensory and motor processing brain regions.

Sorting out all the specific disynaptic and trisynaptic pathways observed in our findings and the functional implications is now perhaps a years-long endeavor – building on the vast amount of solid anatomical work that has come before us, with the ever advancing circuit tracing tools and functional markers now at our disposal. We have confirmed previous hypothesized results, removing ambiguity of terminal fields where functional synaptic connections were unclear, and also provided data from mice that had only previously been investigated in other mammalian species. We strongly believe that this study provides a critical starting point to further investigations and we detail a number of implications from our findings that should be pursued. While this strength of our paper is perhaps not a traditional ‘novel finding’ that can be easily pinpointed by bullet points, we have also uncovered novel findings along the way and have made efforts to highlight these in the revised manuscript, particularly throughout the discussion.

2) How did differences in cell counts and other measures of injection site affect the pattern and extent of anterogradely labelled cell and mossy fibre terminals? It was not clear to me if Figure 2A shows the total extent of injection sites into different neocortical areas or just the defined regions of interest. Either way the area clearly varies considerably between targets which will affect projection density and possibly topography.

We have provided further clarification of the injection site extent (revised Figure 3A; additional Supplementary file 2A), relationship between the injection site volume and mossy fiber terminals (additional Supplementary file 2B) as well as cell counts and mossy fiber terminals (Figure 6—figure supplement 3); including explanation throughout the text (e.g. subsection “Intermediate cerebrocerebellar brainstem pathways”). In short, we found that the number of all anterogradely labelled cells correlated most strongly with the number of mossy fiber terminals and measures of injections site volume were a poor predictor of general extent of mossy fiber labeling.

This may be due to a number of factors related to the fact that the trans-synaptic properties of the virus are heavily reliant on having a high titer concentration and, therefore, a high concentration of virus taken up by individual cells; the number of viral particles within each cell is of course difficult to assess and may be reliant on other properties such as the speed of injection, properties of diffusion within the cortical layers, and proximity to the pipette tip, for example – making the number of cells that are transfected to a level amenable to transsynaptic transport variable, even across injection sites with equal volumes. In fact, one may argue that, given the same volume of injected solution, a smaller injection site would indicate a higher concentration of viral particles and therefore predict a negative correlation between injection site and resulting trans-synaptic labeling.

In reality, there are a number of factors at play that may lead to the variability we see here. Of course, although the absolute number of resulting anterograde and terminal labelling is still of interest, this is one reason why for this study we have opted to inject in a limited number of pre-defined key cortical regions, and to normalize the mossy fiber labelling we have observed across regions to present the data in a way that the pattern of resulting labelling can be appreciated independently of the variability we see across injection sites. We have made considerable effort to make this clear in the revised manuscript with the new Figures noted above and further discussion (e.g. noting the need for further targeted exploration of neighboring somatotopically organized regions, subsection “Diversity of cerebrocerebellar pathways”).

3) The histogram axes in Figure 2D are not all drawn on the same scale making comparisons difficult. Also, percentage values are potentially misleading given the large variation in cell counts and mossy fibre terminals listed in supplementary Figure 1B.

We understand the reasoning of the reviewer, it would be ideal to have the same scaling in all graphs for the revised Figure 3D. However, the percentages of labeled mossy fiber terminals varied substantially across the individual cortical areas and we felt that putting them on the same absolute scale would detract from subtle, but still appreciable, differences observed in the pattern of labelling across various lobules for the less well studied cortical targets (i.e. beyond M1 and S1). To overcome this issue and to directly compare the magnitude of inputs of various modalities into the different lobules we choose the format depicted in the revised Figure 4A,B, as well as including the density measures in Figure 4C (and Supplementary file 1C for reference), which are more scalable reflections of the input given by each cortical target region. In this way, both the pattern of expression across all areas and the biases for cortical contribution to individual cerebellar regions can be appreciated. We have also made a note in the manuscript regarding the interpretation of data from regions with very low-density terminal labelling (subsection “Regional convergence of multimodal cerebrocerebellar input within lobules”).

4) Given that the pons is the primary source of mossy fibre inputs, how did the authors determine that other brainstem nuclei also containing labelled cells in the same experiments necessarily provided mossy fibre projections?

While further investigation is required in relation to individual pathways in this regard, we now provide different lines of evidence showing the potential for specific extra-pontine precerebellar nuclei to act as cerebrocerebellar intermediaries:

- Since no pontine labeled cells were observed after A1 injections, but mossy fiber terminals were still found in the cerebellum, one can conclude that at least for this disynaptic pathway, extra-pontine intermediate nuclei play a large role.

- We observed labelling in the inferior cerebellar peduncle as well as the middle cerebellar peduncle, which is now shown in revised Figure 2.

- Our observations from retrograde tracer injections into key cerebellar lobules show a spatial overlap between trans-synaptically labelled precerebellar cells and retrogradely labelled cells from cerebellar injections.

We have detailed this evidence throughout the Results section and discussed in detail in the revised Discussion section (e.g. subsection “Diversity of cerebrocerebellar pathways”; see also reviewer 1, point 1) and note that further investigations into the role of these precerebellar nuclei as relay versus integration centers for cortical signals will make for interesting future studies.

5) The topographical organization within the pons should be compared to the principles of organization defined in previous studies (eg Leergaard, 2003; Odeh et al., 2005).

We significantly expanded our discussion in this regard in the revised version of the manuscript in both the Results section and the Discussion section.

6) The discussion should consider the extent to which cerebro-cerebellar pathways are conserved across mammalian species. How useful is the mouse as a model for study of cerebro-cerebellar projections?

We have added comparison to other species in various applicable places throughout the discussion (e.g. subsection “Diversity of cerebrocerebellar pathways”) and included a statement regarding the role of the mouse as a model for cerebrocerebellar projections (subsection “Convergence of functionally distinct cerebrocerebellar input”).

Reviewer #3:

Henschke and Pakan have submitted a manuscript entitled "Convergence of multimodal inputs connecting the cerebral cortex to the cerebellum" in which they use modern neuronal tracing methods to map circuit projections into the mouse cerebellum. The authors traced the cerebellar inputs originating from sensory, motor, and association cortices. They argue that diverse functional connections project from the cortex to cerebellum, where they ultimately exhibit a convergent terminal field distribution within specific lobules. The manuscript is well written and technically, it offers a much-needed approach to better understand the organization and trajectories of major cortico-cerebellar projections. In addition, the figures are well made, schematics very helpful, and overall the panels are easy to follow. However, below we provide a number of comments and concerns that we hope will improve the clarity and impact of the study.

1) Throughout the text, the discussion of A1 and its unique projection through non-pontine pre-cerebellar nuclei is often highlighted, however the significance of this point is not well articulated. Further clarification in the abstract and in the body is needed if the authors wish to highlight the uniqueness of this pathway. This is especially true given the findings in the text that S1 and M1 both have substantial, if not even majority in the case of S1, projections to non-pontine pre-cerebellar nuclei.

We have significantly expanded our discussion in regard to the unique A1 pathways and added additional experiments to support our findings. See subsection “Anterograde tracing of indirect cerebrocerebellar pathways”, subsection “Diversity of cerebrocerebellar pathways” (see also reviewer 1 point 3 and point 4 below).

2) Introduction. Please clarify why the identified cortical regions were selected. In addition, while we agree that the characterization of the injections is rather comprehensive, there is a limitation in this study in that either the number of cortical regions chosen or the breadth of the characterization of the selected regions (ie: why weren't at least two neighboring sites in a given cortical region analyzed) prevent the present study from providing a fully comprehensive map, as stated by the authors.

We agree that the term ‘fully comprehensive map’ was misleading, as the goal of the study was to describe, in detail, only key sensory and motor cerebrocerebellar pathways – consequently, we have toned down these terms throughout. Indeed, two separate strategies could be to (1) briefly characterize many regions without much breadth, or (2) to fully characterize immediately neighboring regions with great detail; however, we opted for a strategy in between, so that we could devote enough space to fully explore the potential for multimodal overlap along with the implications that arise from our findings.

We strongly feel that this type of experimental design is advantageous as it allows us to compare within a single study a number of key functional regions without creating a dataset that acts as only a resource and must be fully interpreted by the reader alone. There is clearly a tradeoff between the number of cortical sites that could be investigated and the detail in which those specific pathways can be highlighted and discussed in depth. We believe that the necessity still exists for more detailed topographic mapping within single modalities, as well as large scale fully comprehensive mapping of pathways (as is provided, for instance, by resources such as the Allen brain Institute), but the strength of our study allows for both the presentation of a large dataset spanning key cortical regions as well as detailed quantification and interpretation of both the results, and identification of key avenues of future research in light of the findings. We believe that with the expansion of the manuscript into a full Research Article format we have achieved this.

3) Figure 1A. Please indicate the circumscribed subregion in each cortical area where the injection was made.

We have further specified the core and halo region of the injection site within the cortical subregions in the revised Figure 3.

4) Subsection “Anterograde tracing of indirect cerebrocerebellar pathways”. Please clarify percentages for A1 projections in order to make the second sentence "This pattern of extra-pontine labeling was similar…" clearer. Further, in Figure 2B, while the scarcity of the projections to the pontine nuclei is similar, they seem to be qualitatively different in that A1 projects terminals, while the AuD experiment labels cell bodies. This distinction is not clear in the text. Moreover, the fact you see terminals in one region and then cell bodies another makes it a challenge to piece together what the actual pathway(s) might look like. That is, how do you substantiate the claim that the cell bodies in the pons (the unexpected labeling) actually project to the cerebellum? And on the flip side, for the majority of S1 labeling, which is in the precerebellar non-pontine nuclei, can we really assume that these all project to cerebellum? If not, what percentage?

The sentence in question has been revised in conjunction with the expanded discussion of the projections from A1 throughout, specifically clarifying the difference between the terminal labelling we see in the pons after A1 injections and the cell bodies observed after AuD injections (with supporting evidence from retrograde labelling from the pontine nuclei [Figure 1—figure supplement 1] and mono-trans-synaptic anterograde labelling in the pons following IC injection [Figure 1—figure supplement 2]). See subsection “Anterograde tracing of indirect cerebrocerebellar pathways” and subsection “Diversity of cerebrocerebellar pathways“ (see also reviewer 1 point 3). We have also further quantified the percentage of extra-pontine versus pontine labeling observed after targeted retrograde injections (new Figure 6—figure supplement 1).

5) The supplementary file 1 is a bit difficult to interpret. Please include the percentages referenced in the text in the table. In addition, it is unclear why in some injection sites the sum of the individual pre-cerebellar nuclei cells equals the summed total, while in other cases the sum is less than or greater than the listed total. (ie M1-1 52 vs 55; V1-1 8 vs 8; A1-1 10 vs 8)

We have included the percentages in the revised Supplementary file 1B (total cell count and mean ± s.e.m. for the percentage of extra-pontine labeled cells for each target cortical region, as discussed in the text). We have also amended the sums, as these were typos based on a previous version of the Table.

6) The significance of terminals in pontine/pre-cerebellar nuclei without cell body labelling is unclear and there should be an explanation of this in the text. For instance, in regard to A1/AuD does this indicate inefficiency in trans-synaptic labelling, that there is an alternative monosynaptic projection from A1/AuD to the pontine nuclei, or is there an alternative explanation? This is mentioned for M1 projections to the olivary nuclei (Subsection “Anterograde tracing of indirect cerebrocerebellar pathways”).

We have performed additional experiments (e.g. IC injection) and expanded the discussion regarding these points in the text (in the subsection “Anterograde tracing of indirect cerebrocerebellar pathways” as well as the subsection “Diversity of cerebrocerebellar pathways”). We indicate the potential for polysynaptic pathways and discuss likely routes for cerebral information from A1 to get to the cerebellar cortex through higher-order polysynaptic pathways. Clearly, deciphering all trisynaptic pathways from all cortical target regions is beyond the scope of the current study, but here we provide not only a starting road-map for these targeted investigations, but also functional ties and implications in the discussion (e.g. in relation to A1/AuD, subsection “Diversity of cerebrocerebellar pathways”; in relation to olivary projections, subsection “Diversity of cerebrocerebellar pathways”).

7) In the subsection "Convergence of multimodal cerebrocerebellar input within lobules" the metric for dominant representation (> or < 55%) is problematic given the relative sparsity of the injections (either across or within cortical regions). Furthermore, given the variability of numbered terminals across individual animals in a given cortical area (ie from 2406 to 25616 from the M1 injections), this type of quantification and conclusions about convergence seem premature.

We agree with the reviewer and have replaced this figure with a more quantitative assessment of density (Figure 4C and Supplementary file 1C). This still demonstrates the point that motor and somatosensory cortical projections in general dominate throughout the cerebellar cortex, without setting arbitrary thresholds or presenting misleading summaries per lobule based on narrow cortical target regions. Additionally, we have included a note in the manuscript regarding the interpretation of data from regions with sparse terminal labelling (subsection “Regional convergence of multimodal cerebrocerebellar input within lobules”).

8) While the discussion about convergence and integration is quite interesting to speculate upon, it is hard to grasp whether the current data is sufficient to reach such a conclusion. Given the vast number of granule cells and the fine scale nature of cerebellar microzones, conclusions about integration of multimodal afferent information by single units (whether microzone or granule cell) cannot be easily drawn. To do this, a method distinct from the approach used in this paper would be needed whereby labelling from two distinct cortical areas could be distinguished in the cerebellum in a single animal. In the end, I am having trouble fully appreciating how integrated the "multimodal" and "convergence" nature of the pathways actually is, based on the data provided.

The concept of ‘convergence’ in this study has been clarified throughout to mean regional spatial overlap and the text has been revised throughout to limit speculation about integration and highlight the potential for modular multimodal processing (see also response to editor point 3). Additionally, we have expanded our discussion regarding convergence on the single cell level with more extensive reference to previously published literature (e.g. see subsection “Convergence of functionally distinct cerebrocerebellar input”).

9) Finally, there is a core assumption at play, which is that cortical injection – pontine/precerebellar cell body labeling – mossy fiber terminal marking. In the case of cortico-ponto-cerebellar pathways, the abundance of literature makes this assumption sound. However, in the case of the precerebellar projections (especially S1 which has a majority non-pontine projections), sagittal sections (for example) demonstrating the axonal projections, and elucidating the monosynaptic pathway would provide a helpful piece of evidence to support the current content.

We thank the reviewer for the suggestion and note that we were able to observe clear labelling in the inferior cerebellar peduncle (even in coronal sections), which has now been included in the revised manuscript (Figure 2; subsection “Anterograde tracing of indirect cerebrocerebellar pathways”). Please also see response to reviewer 2 point 4.

10) In the Abstract, it is not clear what is actually meant by "Prominent terminal overlap across motor and sensory modalities…". And, how was this measured?

We have altered this sentence in the Abstract to read: ‘Within molecularly defined cerebellar modules we found spatial overlap of mossy fiber terminals across motor and sensory modalities…’ and in combination with edits to the last sentence: ‘…the regional convergence of multimodal inputs.’ we have clarified this.

11) It would be very helpful to include the species studied in the Title and/or the Abstract.

The species has now been included in the Abstract.

12) It is critical that the authors fully outline the limitations of the mono-trans synaptic anterograde viral tracer, in their hands, and specifically for the purpose of this study.

This has been made more explicitly clear in the various places in the manuscript (e.g. subsection “Neuroanatomical injections”).

13) In Figure 1B, it is not clear what the red arrows are representing and pointing towards. Aren't the arrows pointing the wrong way if this is to show anterograde tracing direction?

Here, the red ‘arrows’ were indicative of labeled projection neurons (i.e. layer 5 pyramidal cell bodies). These were, however, quite small illustrations, and we have revised this figure for clarity and changed the symbols to circles (Figure 1B).

14) Is there a time dependence on the tracing? That is, do longer periods of survival after injection label additional projections?

Previous studies using this AAV as a mono-trans-synaptic tracer (Zingg et al., 2017) have systematically investigated the time dependence of this technique. They found no significant difference in the number of anterogradely labelled cells between 2, 3, or 4 weeks expression. Indeed, in pilot studies we also confirmed their results by testing different survival times after the injections, up to 4 weeks and, additionally, never observed labelled granule cell/Purkinje cells or other identifiable non-specific labeling – which would indicate transmission beyond mono-synaptically connected neurons. We did not test survival times for shorter than 2 weeks, but this is a fairly standardized time period for any AAV transfection. Hence, 2 weeks expression was used for all the data collected for the main study. We have added a note in the methods to this effect (subsection “Neuroanatomical injections”).

15) In Figure 1F, M1 should project ipsilateral, but in the cerebellum one can see many terminals on both sides. Please explain.

We are unsure as to the specific confusion, but we can clarify that after M1 injections, pontine labeling was mostly located on the ipsilateral side, with few cells also labelled on the contralateral side (Figure 1E), as has been previously suggested in rodents examining terminal labelling in the pons (Mihailoff et al., 1985; Leergaard and Bjaalie, 2007). This conclusion is also supported by studies in primates, by using anterograde tracer to confirm additional corticopontine fibers from M1 on the contralateral side with functional synapses (Morecraft et al., 2018). This is now shown here in mice and with trans-synaptic anterograde labelling without confusion regarding the presence of axon terminals or fibers of passage – a significant advantage of our study. This information has been further clarified in the revised text (see subsection “Anterograde tracing of indirect cerebrocerebellar pathways”). However, in the cerebellum, the majority of mossy fiber labeling after all injections into the cerebral cortices (including M1) was located on the contralateral site (e.g. M1: ~25% ipsilateral and 75% contralateral; Figure 3C). The prominent contralateral ponto-cerebellar pathways are well documented (e.g. Serapide et al., 2002) but recent studies examining the projections of single pontine cells in rodents have found both ipsilateral and contralateral collaterals, with some even crossing twice (Biswas et al., 2019; this is also documented in the revised manuscript, subsection “Organization of cerebrocerebellar terminals”). The image shown in Figure 1F is representative of the proportion of ipsilateral and contralateral labelling observed in our study (see also Figure 3C,D), as well as in agreement with previous literature.

16) The authors state "…extent M1, indicating the presence of a polysynaptic cerebro-olivary pathway…" What is the literature to support this?

We have expanded on this in subsection “Diversity of cerebrocerebellar pathways”.

17) The authors state "We quantified the number of resulting mossy fiber terminals throughout the extent of the cerebellum and found that this was highly variable across cortical regions…" How variable is the size of the infected cell population in the cortex?

It is difficult to determine the precise number of transfected cells within the injection site due to the trans-synaptic nature of the AAV and the density of labeling in the core region. This is why we have opted to report the volume of the injection site core (Supplementary file 1A and Supplementary file 2A). We additionally added a new supplementary file (Supplementary file 2) to illustrate the quantification of the injection site, and further characterize the relationship with the resulting mossy fiber labeling.

18) The authors state "There was a clear and consistent topography of…" It would be helpful to fully define what you mean by topography here. There are many levels of topography, in different brain regions, and this could mean very different things to different researchers.

We have rephrased this for clarity: ‘In agreement with previous studies (Leergaard and Bjaalie, 2007; for review see, Kratochwil et al., 2017), resulting pontine labeling after cortical injections was topographically organized with more rostral cortical regions projecting more medially in the pons and caudal cortical areas projecting towards the lateral extent of the pontine nuclei (Figure 1E, see also Figure 3B).’ (subsection “Anterograde tracing of indirect cerebrocerebellar pathways”).

19) In Figure 3E, what does each data point represent? A single terminal?

For the high density projections, M1 and S1, each dot represents 5-10 mossy fiber terminals, for all other lower density projections each dot represents 1-5 mossy fiber terminals. Because this is a representative schematic to show the modular pattern of labelling, we refer readers to Figure 3 and Figure 4 for quantification of results across cerebellar regions. We have clarified this in the figure legend (revised Figure 5).

20) Along the same lines as above, it would be helpful to see more actual data with the combined zebrin labeling. Mossy fiber patterns, by nature of their clustered appearance, are not so easily appreciated and therefore additional examples, at higher power magnification, would be welcomed.

We revised the current Figure 5 and have added the new Figure 5—figure supplement 1 to the revised manuscript, presenting more AldoC related data. We have also added additional text to the results, specifically detailing the pattern of distributions in relation to the molecular zones (subsection “Regional convergence of multimodal cerebrocerebellar input within lobules”).

21) The authors state "This allowed for a detailed comparison of cerebellar regions across brains and, hence, across functional cortical regions representing multiple modalities (see Figure 3—figure supplement 1)." However, I don't see a full description or explanation of the data in the text.

We have rephrased this to clarify the goal of using the aldolase c expression pattern as a tool to align cerebellar regional maps across target cortical injection sites (subsection “Regional convergence of multimodal cerebrocerebellar input within lobules”). Additionally, as noted above, we have added further description of the pattern of labelling in the text (subsection “Regional convergence of multimodal cerebrocerebellar input within lobules”). Our results were relatively surprising, in that we did not see clear patterns of sagittal organization on a larger scale (which we were anticipating). We believe this is partially due to the fact that we are labelling multiple cerebrocerebellar pathways, and finer scale projections may show more defined sagittal organization. This is now explicitly noted in the revised manuscript (subsection “Regional convergence of multimodal cerebrocerebellar input within lobules”).

22) The number of animals used in the study seems quite low.

We have added a substantial number of additional animals through various new experiments and have almost tripled the number of animals used in this study; we now use 42 animals. Although somewhat subjective for anatomical studies, we would argue that for our experimental design, descriptive statistics, and multiple target regions investigated, the animal numbers we use are in the normal range (for example, Zingg et al., 2017, n = 4 for main anatomical experiments examining a single pathway).

23) In Figure 3—figure supplement 1, what is the red staining in Purkinje cells?

We use the tdTomato Ai9 mice line, which tends to have a level of background fluorescence (see https://www.jax.org/strain/00790, and also e.g. Hahn et al., 2019), as reported by the donating investigator to the Jackson Laboratory: “Importantly, the donating investigator reports that very low levels of tdTomato expression may be present prior to introduction of Cre recombinase – but the tdTomato expression levels after Cre recombination are significantly greater than those baseline levels”.

In our hands, this background staining is very clearly distinguishable, particularly under the microscope, and qualitatively distinct from the AAV1.cre-induced tdTomato expression in cells and terminals. We have added an explanation to this effect in the revised manuscript (Materials and methods section, and revised Figure 5—figure supplement 1 legend).

[Editors’ note: what follows is the authors’ response to the second round of review.]

Essential revisions:

The major remaining concern – shared by both reviewers – is the overemphasis/ speculation on 'multimodality' for this essentially anatomical study. Specifically:

1) I was delighted to see a more detailed examination of the location of MFs from different modalities within each lobule, since a prerequisite for multimodal processing is that the information project to the same subregion of a lobule. I also found rather striking the case in Crus II where there was still segregation between two MF types within the same lobe. This latter result highlights the notion that multimodal innervation within lobes is necessary but not sufficient to conclude multimodal processing. I therefore encourage the authors to soften their choice of words of "highly multimodal" and "moderately multimodal" as a conclusion of Figure 4. Perhaps the use of the term "lobule co-innervation" is more appropriate. Then after Figure 5, the argument for putative multimodal processing is much stronger, but still only suggestive.

In reference to Figure 4, we have changed the terms here as suggested to utilize ‘coinnervated’ and we thank the reviewer for this suggestion (e.g. subsection “Lobule co-innervation of cerebrocerebellar inputs from distinct cortical areas”, Figure 4).

We have additionally further reworked our concept of multimodal ‘integration’ for this more anatomically relevant term throughout the manuscript where appropriate. Therefore, we have toned down the functional ‘multimodal’ emphasis and highlighted the strength of the work as an anatomical study (e.g. Title; Introduction).

2) Indeed, Figure 5 shows an essential set of analyses suggestive of multimodal processing, but I was left wanting for some clear quantification of "intermingled" and a simple overall summary.

a) Would it be possible to analyze the distribution of nearest-neighbor distances between terminals of different origins? Those that co-innervate would have shorter distances and those that do not, e.g. Crus II, would show a shifted distribution. Perhaps a more sophisticated point-process analysis, such as the application of the bivariate Ripley K-function, could be used to test for spatial randomness between two species of points and provide statistical confidence.

b) To add some statistical rigor to the alignment with adolase C staining, one could compare the frequency of AldoC positive and negative terminals for each cortical injection. Statistical tests for the frequency of events can then be used.

a) As suggested, we have analyzed the distribution of nearest neighbor distances (Figure 5B and Figure 6B) as well as the identity of the cortical origin of nearest neighbors (Figure 5C and Figure 6C) and included appropriate statistical tests for significance (see also exact pvalues in Supplementary file 1E). Consequently, we have split the previous Figure 5 into two figures due to space constraints (now Figure 5 and Figure 6). The results have been amended to reflect these changes and incorporate the main points from the quantification (e.g. subsection “Spatial organization of mossy fiber terminals in molecularly defined cerebellar modules”). We have additionally included analysis using the Ripley K function to test for spatial randomness and included the results in the text (subsection “Spatial organization of mossy fiber terminals in molecularly defined cerebellar modules”). Of course, the methods section has also been updated to reflect the new analysis (subsection “Quantification and data analysis”). We believe these additional analyses have indeed increased the statistical confidence in the qualitative pattern of data previously reported and thank the reviewer for their detailed suggestions.

b) We have added statistical rigor and internal validation of the AldoC+/- alignment across animals by correlating the frequency of mossy fiber terminals across + and – regions of each lobule. See new Figure 5—figure supplement 1J where we present the correlation matrix across all animals as well as the associated p-values; demonstrating the high correlation across animals with injections within the same cortical target region (referenced in the figure legend as well as subsection “Spatial organization of mossy fiber terminals in molecularly defined cerebellar modules” and subsection “Quantification and data analysis”).

3) The title continues to hint at a more functional set of analyses, which the paper really does not provide. Please revise.

We have revised the title accordingly: ‘Disynaptic cerebrocerebellar pathways originating from multiple functionally distinct cortical areas’. We think this title preserves the concept of functional specificity of cortical inputs, but that it is now also clear that the study is based on an anatomical premise (see also point 1).

4) Similarly, the Abstract could present the key anatomical distinctions that were uncovered rather than the speculative discussion about multimodal sensory input – this functional idea should remain, but it should be toned down to make space to better clarify the actual anatomical findings.

We have rewritten the Abstract to downplay the multimodal integration further and to highlight the anatomical strengths. We agree that it is now much more focused.

5) The main Figure 6 merits a more thorough quantification of retrograde labeling.

We have added further quantification to (now) Figure 7, including a quantitative assessment of the origin of nearest neighbors for anterogradely labelled cells (Figure 7C) as well as the distance between anterograde and retrograde labelled cells from dual injections (Figure 7—figure supplement 2; subsection “Intermediate cerebrocerebellar brainstem pathways”). We also refer to supplementary file 1B which includes a table of the quantification of retrograde labelling and Figure 7—figure supplement 1 and Figure 7—figure supplement 3 as qualitative as well as quantitative representation of this data.

6) Quantification and presentation of co-labeled and spatially intermingled neurons following dual viral tracing injections would be appropriate.

We have added this information in conjunction to the points listed above (point 5), including further quantification and description regarding co-labeled and spatially intermingled neurons (see also Figure 7 figure legend).

7) I like the estimation of the number of MFs per pontine neuron and would like to see it as a main figure.

We have including this into the updated main Figure 7 (see Figure 7D).

8) The Discussion section rambles on a bit. I believe it can be shortened and used to more clearly summarize the major findings, the similarities and differences with previous results, and the implications for cerebellar function.

We have edited the Discussion section throughout to be more concise and clearer (reducing the length by ~500 words), highlighting the major findings while still maintaining a thorough discussion of the nuances of this extensive dataset.

9) The section titles are rather vague. For example, "Organization of cerebrocerebellar mossy fiber terminals" is essentially duplicated in the Results and Discussion, and perhaps needs more specific wording. "Spatial organization of cerebrocerebellar mossy fiber types". I am not really sure why there is a Discussion subsection on "Diversity of cerebrocerebellar pathways" as you define the pathways by viral injection. Perhaps something like: "Cerebellar cortical target diversity of cerebrocerebellar pathways?"

We have amended and refined most section titles. In the Results section, we now move from the more general trans-synaptic anterograde tracing technique and general pathway results, to the regional organization of terminals in the cerebellum, to the co-innervation of inputs at the level of the lobule, to the precise spatial organization of inputs on the level of molecularly defined modules within each lobule, and finally to the summary examining in detail the entire cerebrocerebellar pathway including the intermediate brainstem nuclei.

Likewise, the Discussion section titles have been amended to explore the stages of the cerebrocerebellar pathways, first cortex to precerebellar nuclei (subsection “Pontine and extra-pontine cerebrocerebellar pathways”), then the terminal organization in the cerebellum (subsection “Organization of cerebrocerebellar input to the cerebellum”), and finally the functional implications of the study (subsection “Functional implications”). We believe the general flow is now improved.

Author details

1. Julia U Henschke

   1. Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University, Magdeburg, Germany
   2. German Centre for Neurodegenerative Diseases, Magdeburg, Germany

   Contribution

   Conceptualization, Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-2435-8627

2. Janelle MP Pakan

   1. Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University, Magdeburg, Germany
   2. German Centre for Neurodegenerative Diseases, Magdeburg, Germany
   3. Center for Behavioral Brain Sciences, Universitätsplatz, Magdeburg, Germany

   Contribution

   Conceptualization, Supervision, Funding acquisition, Methodology, Writing - original draft, Project administration, Writing - review and editing

   For correspondence

   janelle.pakan@med.ovgu.de

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-9384-8067

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