Profound motor deficits such as ataxia and loss of oculomotor control are the most obvious manifestations of cerebellar damage. This has contributed to the popular view that the cerebellum is involved primarily in motor function, but this is far from a complete view of the behavioral functions of the cerebellum. fMRI studies suggest that some regions of the cerebellar cortex are devoted to motor function, but other regions are involved in working memory, language, emotion, executive function and many other nonmotor functions (Stoodley and Schmahmann, 2009; Van Overwalle et al., 2014). The cerebellum is also implicated in autism spectrum disorder (Wang et al., 2014), anxiety (Moreno-Rius, 2018), attention deficit disorder (Berquin et al., 1998), schizophrenia (Andreasen and Pierson, 2008), and other nonmotor neurological disorders (Phillips et al., 2015).

The posterior vermis region of the cerebellar cortex is particularly intriguing with regard to involvement in nonmotor behaviors. Damage to the cerebellar vermis in adults can lead to deficits in executive function, spatial cognition, linguistic processing, affect regulation, irritability, anger, aggression, and pathological crying or laughing (Schmahmann and Sherman, 1998; Levisohn et al., 2000). There is also extensive evidence suggesting that the vermis influences aggression. In seminal studies mapping the somatotopic organization of the cerebellar cortex, the Italian physiologist Guisseppe Pagano found that injecting curare into the vermis caused the animal to ‘become suddenly furious, and throw itself at those present, trying to bite them’ or to ‘jump into the air, struggling to bite who knows how many phantoms of its agitated psyche’ (Pagano, 1904). Later lesions studies demonstrated that resection of the vermis had the opposite influence on behavior and produced a calming effect (Sprague and Chambers, 1959; Peters and Monjan, 1971; Berman et al., 1974). Electrical stimulation of the deep cerebellar nuclei has been shown to drive aggressive behaviors such as sham rage (Zanchetti and Zoccolini, 1954) and attack (Reis et al., 1973). In human clinical studies, stimulating the surface of the vermis improved emotional control and reduced aggressive outbursts (Heath, 1977), and reduced feelings of anger (Cooper et al., 1976).

These studies implicated the vermis in regulating aggression, but they have been difficult to interpret. Purkinje cells (PCs), the sole output cells of the cerebellar cortex, fire continuously at up to 100 Hz, and inhibit neurons in the deep cerebellar nuclei (DCN) that in turn influence other brain regions. The observations that electrical stimulation of the vermis reduced aggression (Heath, 1977), while stimulation of the DCN increased aggression (Reis et al., 1973), are consistent with PC activity inhibiting cells in the DCN (Telgkamp and Raman, 2002; Alviña et al., 2008). This leads to the interpretation that elevated PC activity and decreased DCN activity suppress aggression, and conversely elevated DCN activity (and by implication decreased PC activity) suppresses aggression. However, it is difficult to reconcile stimulation studies with the taming effect observed in lesion studies (Sprague and Chambers, 1959). Lesions of the vermis will decrease PC inhibition of the DCN, and would thus be expected to promote aggression by elevating firing within the DCN. Instead, they suppress aggression.

Numerous factors make both the electrical stimulation and lesion experiments difficult to interpret, and could contribute to the apparent discrepancy between these two approaches. Electrical stimulation of the cerebellar cortex activates all types of neurons in the vicinity of the electrode, including PCs. Molecular layer interneurons will also be activated, and they inhibit PC firing (Heiney et al., 2014). Stimulation also antidromically activates mossy fibers, climbing fibers, and modulatory inputs from other regions (Llinás and Sasaki, 1989; Baker and Edgley, 2006), which might contribute to the behavioral consequences of stimulation. In addition, electrical stimulation of PCs can synchronize activity, which could paradoxically increase spiking in the DCN (Person and Raman, 2012a; Person and Raman, 2012b). For these reasons it is unclear how electrical stimulation of the vermal cortex influences cerebellar circuitry. For lesion studies of the cerebellar vermis, it is not clear how the firing of downstream DCN neurons was altered. Although the loss of inhibition would be expected to increase DCN firing, genetic ablation of PCs has been shown to paradoxically decrease firing in the DCN (Bäurle et al., 1997), suggesting that compensatory mechanisms regulate the properties of DCN neurons in the absence of PC input. In addition, previous studies did not quantify the magnitude and time course of behavioral effects driven by cerebellar interventions.

To determine the role of the cerebellum in regulating aggression, we used optogenetic techniques to selectively control PC activity in mice. We used the resident-intruder assay, a measure of natural territorial aggression in rodents, to provide a measure of the extent and time course of an aggressive behavior (Koolhaas et al., 2013). Manipulating PC firing in the vermis, but not in another cerebellar region, enabled rapid, bidirectional control of aggression. This study provides evidence that in the cerebellar vermis elevated PC firing suppresses aggression, whereas suppressing PC firing promotes aggressive behavior.

To selectively modulate the activity of PCs in the cerebellar vermis, we used PCP2-cre mice (Zhang et al., 2004) to restrict expression of the microbial opsins ChR2 (channelrhodopsin-2, [Boyden et al., 2005]) and NpHR3.0 (halorhodopsin, [Zhang et al., 2007]) to PCs. In vitro electrophysiological recordings (Figure 1a) confirmed that ChR2 stimulation could drive graded increases in PC firing that scaled with light intensity (Figure 1b), as previously reported (Guo et al., 2016). Similarly, halorhodopsin stimulation decreased PC firing rates in a light intensity-dependent manner (Figure 1c). To manipulate PC activity in vivo, optical fibers were chronically implanted in adult (>P42) male PCP2-cre::ChR2 or PCP2-cre::NpHR mice over the surface of the cerebellar vermis. Fibers were positioned at the midline over lobule VII (Figure 1—figure supplement 1), a region suggested to play a role in emotional processing (Stoodley and Schmahmann, 2009). Subsequent in vivo recordings through an adjacent craniotomy in anesthetized animals confirmed the ability of light from the implanted optical fiber to reliably increase or decrease the firing rate of putative PCs expressing ChR2 or halorhodopsin, respectively (Figure 1d–f). As with electrical stimulation, optogenetic stimulation has the potential to induce pauses in PC firing. If pauses occur synchronously among multiple PCs that provide inhibition to a DCN neuron, it could promote firing in the DCN (Person and Raman, 2012a). We examined the timing of optically-evoked firing of PCs and found that there were complex temporal responses in different PCs, although there was not a pause in average firing of PCs (Figure 1—figure supplement 2). We went on to record responses of neurons in the deep cerebellar nuclei (DCN) to optogenetic manipulations of PC firing in awake animals (Figure 1g). Increasing PC firing with ChR2 decreased the firing of DCN neurons (Figure 1h, Figure 1—figure supplement 2), while decreasing PC firing with halorhodopsin increased the firing of neurons in the DCN (Figure 1i). The magnitudes of the changes in DCN neuron firing were relatively modest. This may reflect in part the heightened firing rates of neurons in awake animals. In addition, it was a challenge to record from DCN neurons that were targets of the PC population that was influenced with light and other neurons in the DCN may be more strongly targeted and undergo larger changes in activity than those reported here. For this reason the effects on DCN firing should be considered lower bounds.

Figure 1 with 2 supplements see all

Download asset Open asset

Figure 1—source data 1

Optogenetic firing modulation data.

https://cdn.elifesciences.org/articles/53229/elife-53229-fig1-data1-v2.xlsx

Download elife-53229-fig1-data1-v2.xlsx

After allowing at least 1 week for recovery from fiber implantation surgeries, animals were placed in an open field arena and stimulated with increasing light intensities to determine if manipulating PC activity produced overt motor deficits or behavioral consequences. In ChR2-expressing mice, strong vermal stimulation using the highest light intensities (~110 mW/mm² at the face of the fiber optic implant) often resulted in clear motor effects, causing mice to become immobile or exhibit seizure-like and dystonic activity. This behavior resembled previous descriptions of seizure-like activity driven by strong electrical stimulation of the vermal cortex (Clark, 1937; Chambers, 1947). Thus, for all subsequent assays we tailored the intensity of light delivered to each animal to the maximal intensity where animals remained mobile in the open field arena and did not display signs of motor impairment (mean intensity 90 ± 3.9 mW/mm²). In contrast, halorhodopsin-expressing animals exhibited no obvious behavioral effects in response to stimulation at the maximal light intensity deliverable by the fiber-coupled LED light source (61 mW/mm²). This value was used for all subsequent assays.

Because the cerebellum plays well-established roles in motor control and balance, and optogenetic manipulation of PCs in the simplex lobe has been shown to perturb forelimb movements (Lee et al., 2015), we first tested whether manipulating vermal PC firing caused more subtle motor impairments than those described above, that might interfere with the expression of other behaviors. To evaluate coordination, animals were tested on accelerating rotarod assays for two consecutive trials during which they received either optical stimulation or no stimulation. Neither excitation with ChR2 (Figure 2a) nor inhibition with halorhodopsin (Figure 2b) affected the rotarod performance. We next assessed locomotion during open-field assays. Animals received alternating 3 min blocks of optogenetic excitation (Figure 2c). Automated animal tracking (Figure 2d) revealed that optogenetic activation of PCs had no effect on distance traveled, nor the time animals spent in the center of the arena, a measure of anxiety (Figure 2e). To assess the effect of stimulation on locomotion with greater temporal resolution, we averaged animal speed across all blocks of stimulation within the trial, centered around the onset of stimulation, and found that stimulation did not induce any transient change in locomotion (Figure 2—figure supplement 1). Similarly, optogenetic inhibition did not affect locomotion or the time animals spent in the center of the arena (Figure 2f–g and Figure 2—figure supplement 1). Together, these data suggest that manipulating vermal PC firing does not strongly affect coordination, locomotion or anxiety, although optogenetic stimulation of PCs at strong light intensities (greater than those used for behavioral assays) consistently drove profound motor impairment as previously described for vermal electrical stimulation (Chambers, 1947).

Figure 2 with 1 supplement see all

Download asset Open asset

Figure 2—source data 1

Open field (ChR2) data.

https://cdn.elifesciences.org/articles/53229/elife-53229-fig2-data1-v2.xlsx

Download elife-53229-fig2-data1-v2.xlsx

Figure 2—source data 2

Open field (Halo) data.

https://cdn.elifesciences.org/articles/53229/elife-53229-fig2-data2-v2.xlsx

Download elife-53229-fig2-data2-v2.xlsx

Figure 2—source data 3

Rotarod data for Figure 2A.

https://cdn.elifesciences.org/articles/53229/elife-53229-fig2-data3-v2.xlsx

Download elife-53229-fig2-data3-v2.xlsx

To assess the impact of cerebellar activity on aggressive and social behaviors we performed resident-intruder assays while optogenetically manipulating PC activity in the resident (aggressor) animal (Figure 3a). Although resident mice reliably display aggressive behaviors in resident-intruder assays, attacks occur at a relatively infrequent rate of <1 attack per minute (Leypold et al., 2002; Yang et al., 2013; Lewis et al., 2015). In order to increase baseline aggression, fiber-implanted mice were housed with females, providing the opportunity to mate, then subsequently singly-housed for at least 1 week prior to assays. Adult male BALB/c intruders were introduced into the resident’s home cage for 10 min. Optogenetic stimulation was delivered to residents in alternating 1 min blocks. The onset and duration of multiple behaviors were recorded, including aggression (attacks, tail rattles, chasing and lateral threat), social encounters (face-to-face contact and ano-genital sniffing), as well as self-grooming by the resident (Figure 3b).

Figure 3 with 3 supplements see all

Download asset Open asset

Figure 3—source data 1

Resident Intruder Halo Vermis data.

https://cdn.elifesciences.org/articles/53229/elife-53229-fig3-data1-v2.xlsx

Download elife-53229-fig3-data1-v2.xlsx

Figure 3—source data 2

Resident Intruder No Opsin Vermis data.

https://cdn.elifesciences.org/articles/53229/elife-53229-fig3-data2-v2.xlsx

Download elife-53229-fig3-data2-v2.xlsx

Optogenetic activation of vermal PCs significantly decreased the number of attacks (p=0.003, two-tailed paired Student’s t-test) (Figure 3c, see Figure 3—figure supplement 1 for detailed statistics). Stimulation did not affect the frequency of social interactions (p=0.7), or the rate of tail rattles, chasing, or lateral threat, though it did increase the rate of self-grooming by the resident (Figure 3—figure supplement 2). An advantage of the optogenetic approach we have used is that it allows us to precisely determine the time course of the effect of stimulation on aggressive behavior with greater temporal resolution. We binned attacks in 10 s increments and averaged across alternating blocks at the onset of stimulation. Even though attacks are infrequent and stochastic, this analysis revealed that optical activation of PCs immediately reduced attack frequency, and when illumination was stopped the attack frequency gradually ramped up in the subsequent minute (Figure 3d). Stimulation reduced the frequency of attacks by 56% in the 10 s immediately following the onset of stimulation (Figure 3d). To put this into context, genetically ablating neurons in the ventromedial hypothalamus, a brain region colloquially referred to as the ‘attack area’ because of its importance in regulating aggression, decreases the attack frequency by a little more than 50% (Yang et al., 2013).

To test whether decreased attacks might result from a distracting influence of light escaping from the implanted optical fiber, we performed resident-intruder assays with a separate cohort of wildtype mice that did not express opsins, and found that optical stimulation had no effect on either attacks or social interactions (Figure 3—figure supplement 3). To test whether the effect on aggression was specific to stimulating activity in the posterior vermis, we repeated the experiments in ChR2-expressing animals but implanted the optical fiber over a region outside the vermis. Optogenetic manipulations of Purkinje cell activity in many regions have been shown to drive motor movements in mice (Witter et al., 2013; Heiney et al., 2014; Proville et al., 2014; Lee et al., 2015), which could indirectly affect the expression of aggression and other behaviors. To avoid the confound of motor effects, implants were positioned over Crus II, a region that has not been implicated in regulating aggression, but where manipulation of neuronal activity does not drive overt motor phenotypes in rodents (Yamaguchi and Sakurai, 2016). In these mice, stimulating PC firing had no effect on the frequency of attacks (Figure 3—figure supplement 3). Together, these results suggest that increased PC firing in the cerebellar vermis results in a rapid and significant decrease in aggression.

If elevating PC firing in the vermis decreases aggression, does suppressing PC firing increase aggression? It is not possible to address this question with electrical stimulation, but it is possible using optogenetics. Inhibiting PCs with halorhodopsin (Figure 3e) had opposing effects on aggression, significantly increasing the number of attacks (p=0.01), and decreasing social interactions (p=0.03) (Figure 3f). Averaging the attack frequency across multiple epochs of stimulation showed that attack frequency nearly doubled in the 10 s following the onset of halorhodopsin-driven inhibition of PCs (Figure 3g). These results indicate that the activity of PCs in the cerebellar vermis exerts a bidirectional influence over aggressive behavior.

Here we demonstrate that Purkinje cell activity in the posterior vermis drives rapid, bidirectional changes in aggressive behavior. Several aspects of our study provide important advances over previous studies that implicated the cerebellum in the regulation of aggression. First, we demonstrate that cerebellar activity regulates rodent aggression in an established assay that is amenable to quantification. This approach opens the door for quantitative studies in a genetically-manipulatable animal model, and promises to be beneficial for future studies of cerebellar control of aggression. Second, given the role of the cerebellum in motor control, it was important to determine whether the effects on aggression were a secondary consequence of impaired motor function. We evaluated this using open field and rotorod assays, and found that the same stimulation that altered aggression did not affect motor performance. Previous studies did not perform such a quantitative evaluation of motor performance. Third, the stimulation we used to suppress behavior was more selective than could be achieved with the electrical stimulation employed in previous studies, which in addition to stimulating PCs directly, can activate modulatory fibers, mossy fibers, climbing fibers, and inhibitory neurons in the cerebellar cortex. Consequently, in our ChR2 experiments, we can attribute decreased aggression to an increase in PC activity. Fourth, we showed that in our experiments increases in PC firing decreased firing in the DCN and decreasing PC firing did the opposite. Fifth, we find that suppressing PC activity increased aggression. This is consistent with the observation that stimulating the DCN promotes aggression (Zanchetti and Zoccolini, 1954; Reis et al., 1973), but differs from the observation that cerebellar lesions suppress aggression. Studies in other brain regions have described similar behavioral differences between the effects of acutely manipulating activity and lesions (Hong et al., 2018). It is likely that lesions within the vermis are accompanied by compensatory mechanisms within the DCN (Bäurle et al., 1997). Finally, by optogenetically regulating PC firing, we provide evidence that the cerebellum can rapidly and bidirectionally regulate aggression.

The present study raises a number of important questions regarding the manner in which the cerebellum controls behavior. What specific region of the cerebellar cortex is involved? We find that manipulating the activity of Purkinje cells in the posterior vermis is sufficient to significantly modulate aggression. This is consistent with clinical studies implicating lobule VII of the vermis in affective processing (Stoodley and Schmahmann, 2009). However, it is difficult to determine the precise region of the cerebellum that was influenced by our optogenetic stimulation. Light emanating from the face of implanted fibers scatters and disperses over hundreds of microns (Aravanis et al., 2007; Li et al., 2019). Consequently, it is likely that in addition to lobule VII, lobules VIb and VIII received significant illumination, and that PC activity in these regions was also likely modulated to some extent. More detailed studies that manipulate activity in other areas of the midline vermis could add clarity to the specific regions of the cerebellar cortex that regulate aggression. It is also possible that more specific regulation of PC activity in the region controlling aggression (for example, without affecting PC firing in neighboring regions that alter other behaviors) will lead to larger effects on aggression. This could be accomplished by performing similar experiments to those described here, but using viral expression of ChR2 or halorhodopsin to restrict optogenetic manipulation to specific regions of the cerebellar cortex. Furthermore, what is the nature of inputs that control this region? Different regions of the cerebellar cortex typically combine mossy fiber inputs from diverse sources, and it will be interesting to determine how these inputs are combined within the cerebellum to control aggression. Finally, what is the output pathway and the downstream targets that are ultimately regulated by activity in this region of the cerebellar cortex? Anatomical studies have described connections between the cerebellum and regions implicated in aggression, including hypothalamus (Haines et al., 1997) and prefrontal cortex (Kelly and Strick, 2003; Suzuki et al., 2012). Electrophysiological recordings have found that cerebellar stimulation evokes responses in those regions, along with limbic structures such as the hypothalamus, amygdala, and hippocampus (Anand et al., 1959; Snider and Maiti, 1976). Yet, while the somatotopic organization of the cerebellum is well characterized in regions that influence motor function, the output pathways of areas like the posterior vermis have yet to be clearly defined.

It is interesting to speculate on the nature of the role of the cerebellum in controlling aggressive behavior. The cerebellum has expanded in size relative to the cerebral cortex over the course of human evolution (Weaver, 2005), it contains more than half the neurons in brain and it possesses myriad connections to other brain regions. It is unsurprising that its influence should extend beyond the motor realm. Experiments on motor control suggest that the cerebellum combines inputs to generate predictions. It is natural to think that this computational strategy might be used by the posterior vermis of the cerebellum to learn how to respond to cues, and to ultimately decide when aggression is the correct response. Perhaps even subtle dysfunctions or misdirected plasticity within this region can lead to inappropriate aggressive behavior. For example, cerebellar damage often occurs in patients with PTSD (Rabellino et al., 2018). As non-invasive stimulation techniques like transcranial magnetic stimulation of the cerebellum emerge as a clinical treatment options (Demirtas-Tatlidede et al., 2010), it is increasingly important to understand the which areas of the cerebellum control non-motor behaviors (Kelly and Strick, 2003). Future work could shed light on the anatomical projections and physiological impact of non-motor regions of the cerebellum.

Source data files have been provided for Figures 1, 2 and 3.

1. 1. Alviña K
   2. Walter JT
   3. Kohn A
   4. Ellis-Davies G
   5. Khodakhah K

   (2008) Questioning the role of rebound firing in the cerebellum

   Nature Neuroscience 11:1256–1258.

   https://doi.org/10.1038/nn.2195

   • PubMed
   • Google Scholar
2. 1. Anand BK
   2. Malhotra CL
   3. Singh B
   4. Dua S

   (1959) Cerebellar projections to limbic system

   Journal of Neurophysiology 22:451–457.

   https://doi.org/10.1152/jn.1959.22.4.451

   • PubMed
   • Google Scholar
3. 1. Andreasen NC
   2. Pierson R

   (2008) The role of the cerebellum in schizophrenia

   Biological Psychiatry 64:81–88.

   https://doi.org/10.1016/j.biopsych.2008.01.003

   • PubMed
   • Google Scholar
4. 1. Aravanis AM
   2. Wang LP
   3. Zhang F
   4. Meltzer LA
   5. Mogri MZ
   6. Schneider MB
   7. Deisseroth K

   (2007) An optical neural interface: in vivo control of rodent motor cortex with integrated fiberoptic and optogenetic technology

   Journal of Neural Engineering 4:S143–S156.

   https://doi.org/10.1088/1741-2560/4/3/S02

   • PubMed
   • Google Scholar
5. 1. Baker MR
   2. Edgley SA

   (2006) Non-uniform olivocerebellar conduction time in the vermis of the rat cerebellum

   The Journal of Physiology 570:501–506.

   https://doi.org/10.1113/jphysiol.2005.099176

   • PubMed
   • Google Scholar
6. 1. Bäurle J
   2. Helmchen C
   3. Grüsser-Cornehls U

   (1997) Diverse effects of purkinje cell loss on deep cerebellar and vestibular nuclei neurons in purkinje cell degeneration mutant mice: a possible compensatory mechanism

   The Journal of Comparative Neurology 384:580–596.

   https://doi.org/10.1002/(SICI)1096-9861(19970811)384:4<580::AID-CNE7>3.0.CO;2-Z

   • PubMed
   • Google Scholar
7. 1. Berman A
   2. Berman D
   3. Prescott J

   (1974)

   The Cerebellum, Epilepsy, and Behavior

   277–284, The effect of cerebellar lesions on emotional behavior in the rhesus monkey, The Cerebellum, Epilepsy, and Behavior, Springer, 10.1007/978-1-4613-4508-4.

   • Google Scholar
8. 1. Berquin PC
   2. Giedd JN
   3. Jacobsen LK
   4. Hamburger SD
   5. Krain AL
   6. Rapoport JL
   7. Castellanos FX

   (1998) Cerebellum in attention-deficit hyperactivity disorder: a morphometric MRI study

   Neurology 50:1087–1093.

   https://doi.org/10.1212/WNL.50.4.1087

   • PubMed
   • Google Scholar
9. 1. Boyden ES
   2. Zhang F
   3. Bamberg E
   4. Nagel G
   5. Deisseroth K

   (2005) Millisecond-timescale, genetically targeted optical control of neural activity

   Nature Neuroscience 8:1263–1268.

   https://doi.org/10.1038/nn1525

   • Google Scholar
10. 1. Chambers WW

    (1947) Electrical stimulation of the interior of the cerebellum in the cat

    American Journal of Anatomy 80:55–93.

    https://doi.org/10.1002/aja.1000800105

    • PubMed
    • Google Scholar
11. 1. Clark SL

    (1937) A prolonged after effect from electrical stimulation of the cerebellar cortex in unanesthetized cats

    Science 86:377–379.

    https://doi.org/10.1126/science.86.2234.377

    • PubMed
    • Google Scholar
12. 1. Cooper IS
    2. Amin I
    3. Riklan M
    4. Waltz JM
    5. Poon TP

    (1976) Chronic cerebellar stimulation in epilepsy clinical and anatomical studies

    Archives of Neurology 33:559–570.

    https://doi.org/10.1001/archneur.1976.00500080037006

    • PubMed
    • Google Scholar
13. 1. Demirtas-Tatlidede A
    2. Freitas C
    3. Cromer JR
    4. Safar L
    5. Ongur D
    6. Stone WS
    7. Seidman LJ
    8. Schmahmann JD
    9. Pascual-Leone A

    (2010) Safety and proof of principle study of cerebellar vermal theta burst stimulation in refractory schizophrenia

    Schizophrenia Research 124:91–100.

    https://doi.org/10.1016/j.schres.2010.08.015

    • PubMed
    • Google Scholar
14. 1. Friard O
    2. Gamba M

    (2016) BORIS : a free, versatile open‐source event‐logging software for video/audio coding and live observations

    Methods in Ecology and Evolution 7:1325–1330.

    https://doi.org/10.1111/2041-210X.12584

    • Google Scholar
15. 1. Guo C
    2. Witter L
    3. Rudolph S
    4. Elliott HL
    5. Ennis KA
    6. Regehr WG

    (2016) Purkinje cells directly inhibit granule cells in specialized regions of the cerebellar cortex

    Neuron 91:1330–1341.

    https://doi.org/10.1016/j.neuron.2016.08.011

    • PubMed
    • Google Scholar
16. 1. Haines DE
    2. Dietrichs E
    3. Mihailoff GA
    4. McDonald EF

    (1997) The cerebellar-hypothalamic Axis: basic circuits and clinical observations

    International Review of Neurobiology 41:83–107.

    https://doi.org/10.1016/s0074-7742(08)60348-7

    • PubMed
    • Google Scholar
17. 1. Heath RG

    (1977) Modulation of emotion with a brain pacemamer. treatment for intractable psychiatric illness

    The Journal of Nervous and Mental Disease 165:300–317.

    https://doi.org/10.1097/00005053-197711000-00002

    • PubMed
    • Google Scholar
18. 1. Heiney SA
    2. Kim J
    3. Augustine GJ
    4. Medina JF

    (2014) Precise control of movement kinematics by optogenetic inhibition of purkinje cell activity

    Journal of Neuroscience 34:2321–2330.

    https://doi.org/10.1523/JNEUROSCI.4547-13.2014

    • PubMed
    • Google Scholar
19. 1. Hong YK
    2. Lacefield CO
    3. Rodgers CC
    4. Bruno RM

    (2018) Sensation, movement and learning in the absence of barrel cortex

    Nature 561:542–546.

    https://doi.org/10.1038/s41586-018-0527-y

    • PubMed
    • Google Scholar
20. 1. Jackman SL
    2. Beneduce BM
    3. Drew IR
    4. Regehr WG

    (2014) Achieving high-frequency optical control of synaptic transmission

    Journal of Neuroscience 34:7704–7714.

    https://doi.org/10.1523/JNEUROSCI.4694-13.2014

    • PubMed
    • Google Scholar
21. 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

    • PubMed
    • Google Scholar
22. 1. Koolhaas JM
    2. Coppens CM
    3. de Boer SF
    4. Buwalda B
    5. Meerlo P
    6. Timmermans PJ

    (2013) The resident-intruder paradigm: a standardized test for aggression, violence and social stress

    Journal of Visualized Experiments e4367.

    https://doi.org/10.3791/4367

    • PubMed
    • Google Scholar
23. 1. Lee KH
    2. Mathews PJ
    3. Reeves AM
    4. Choe KY
    5. Jami SA
    6. Serrano RE
    7. Otis TS

    (2015) Circuit mechanisms underlying motor memory formation in the cerebellum

    Neuron 86:529–540.

    https://doi.org/10.1016/j.neuron.2015.03.010

    • PubMed
    • Google Scholar
24. 1. Leshner AI
    2. Nock BL

    (1976) The effects of experience on agonistic responding: an expectancy theory interpretation

    Behavioral Biology 17:561–566.

    https://doi.org/10.1016/S0091-6773(76)91009-9

    • PubMed
    • Google Scholar
25. 1. Levisohn L
    2. Cronin-Golomb A
    3. Schmahmann JD

    (2000) Neuropsychological consequences of cerebellar tumour resection in children: cerebellar cognitive affective syndrome in a paediatric population

    Brain : A Journal of Neurology 123 ( Pt 5:1041–1050.

    https://doi.org/10.1093/brain/123.5.1041

    • PubMed
    • Google Scholar
26. 1. Lewis AS
    2. Mineur YS
    3. Smith PH
    4. Cahuzac ELM
    5. Picciotto MR

    (2015) Modulation of aggressive behavior in mice by nicotinic receptor subtypes

    Biochemical Pharmacology 97:488–497.

    https://doi.org/10.1016/j.bcp.2015.07.019

    • PubMed
    • Google Scholar
27. 1. Leypold BG
    2. Yu CR
    3. Leinders-Zufall T
    4. Kim MM
    5. Zufall F
    6. Axel R

    (2002) Altered sexual and social behaviors in trp2 mutant mice

    PNAS 99:6376–6381.

    https://doi.org/10.1073/pnas.082127599

    • Google Scholar
28. 1. Li N
    2. Chen S
    3. Guo ZV
    4. Chen H
    5. Huo Y
    6. Inagaki HK
    7. Chen G
    8. Davis C
    9. Hansel D
    10. Guo C
    11. Svoboda K

    (2019) Spatiotemporal constraints on optogenetic inactivation in cortical circuits

    eLife 8:e48622.

    https://doi.org/10.7554/eLife.48622

    • PubMed
    • Google Scholar
29. 1. Llinás R
    2. Sasaki K

    (1989) The functional organization of the Olivo-Cerebellar system as examined by multiple purkinje cell recordings

    European Journal of Neuroscience 1:587–602.

    https://doi.org/10.1111/j.1460-9568.1989.tb00365.x

    • PubMed
    • Google Scholar
30. 1. Moreno-Rius J

    (2018) The cerebellum in fear and anxiety-related disorders

    Progress in Neuro-Psychopharmacology and Biological Psychiatry 85:23–32.

    https://doi.org/10.1016/j.pnpbp.2018.04.002

    • PubMed
    • Google Scholar
31. 1. Pagano G

    (1904)

    Saggio di localizzazione cerebellare

    Rivista Di Patologia Nervosa a Mental 9:209–228.

    • Google Scholar
32. 1. Person AL
    2. Raman IM

    (2012a) Purkinje neuron synchrony elicits time-locked spiking in the cerebellar nuclei

    Nature 481:502–505.

    https://doi.org/10.1038/nature10732

    • Google Scholar
33. 1. Person AL
    2. Raman IM

    (2012b) Synchrony and neural coding in cerebellar circuits

    Frontiers in Neural Circuits 6:97.

    https://doi.org/10.3389/fncir.2012.00097

    • PubMed
    • Google Scholar
34. 1. Peters M
    2. Monjan AA

    (1971) Behavior after cerebellar lesions in cats and monkeys

    Physiology & Behavior 6:205–206.

    https://doi.org/10.1016/0031-9384(71)90091-6

    • PubMed
    • Google Scholar
35. 1. Phillips JR
    2. Hewedi DH
    3. Eissa AM
    4. Moustafa AA

    (2015) The cerebellum and psychiatric disorders

    Frontiers in Public Health 3:66.

    https://doi.org/10.3389/fpubh.2015.00066

    • PubMed
    • Google Scholar
36. 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
37. 1. Rabellino D
    2. Densmore M
    3. Théberge J
    4. McKinnon MC
    5. Lanius RA

    (2018) The cerebellum after trauma: resting-state functional connectivity of the cerebellum in posttraumatic stress disorder and its dissociative subtype

    Human Brain Mapping 39:3354–3374.

    https://doi.org/10.1002/hbm.24081

    • PubMed
    • Google Scholar
38. 1. Reis DJ
    2. Doba N
    3. Nathan MA

    (1973) Predatory attack, grooming, and consummatory behaviors evoked by electrical stimulation of cat cerebellar nuclei

    Science 182:845–847.

    https://doi.org/10.1126/science.182.4114.845

    • PubMed
    • Google Scholar
39. 1. Schmahmann JD
    2. Sherman JC

    (1998) The cerebellar cognitive affective syndrome

    Brain 121 ( Pt 4:561–579.

    https://doi.org/10.1093/brain/121.4.561

    • PubMed
    • Google Scholar
40. 1. Snider RS
    2. Maiti A

    (1976) Cerebellar contributions to the papez circuit

    Journal of Neuroscience Research 2:133–146.

    https://doi.org/10.1002/jnr.490020204

    • PubMed
    • Google Scholar
41. 1. Sparta DR
    2. Stamatakis AM
    3. Phillips JL
    4. Hovelsø N
    5. van Zessen R
    6. Stuber GD

    (2012) Construction of implantable optical fibers for long-term optogenetic manipulation of neural circuits

    Nature Protocols 7:12–23.

    https://doi.org/10.1038/nprot.2011.413

    • Google Scholar
42. 1. Sprague JM
    2. Chambers W

    (1959)

    An analysis of cerebellar function in the cat, as revealed by its partial and complete destruction, and its interaction with the cerebral cortex

    Archives italiennes de biologie 97:68–88.

    • Google Scholar
43. 1. Stoodley CJ
    2. Schmahmann JD

    (2009) Functional topography in the human cerebellum: a meta-analysis of neuroimaging studies

    NeuroImage 44:489–501.

    https://doi.org/10.1016/j.neuroimage.2008.08.039

    • PubMed
    • Google Scholar
44. 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
45. 1. Telgkamp P
    2. Raman IM

    (2002) Depression of inhibitory synaptic transmission between purkinje cells and neurons of the cerebellar nuclei

    The Journal of Neuroscience 22:8447–8457.

    https://doi.org/10.1523/JNEUROSCI.22-19-08447.2002

    • PubMed
    • Google Scholar
46. 1. Van Overwalle F
    2. Baetens K
    3. Mariën P
    4. Vandekerckhove M

    (2014) Social cognition and the cerebellum: a meta-analysis of over 350 fMRI studies

    NeuroImage 86:554–572.

    https://doi.org/10.1016/j.neuroimage.2013.09.033

    • PubMed
    • Google Scholar
47. 1. Wang SS
    2. Kloth AD
    3. Badura A

    (2014) The cerebellum, sensitive periods, and autism

    Neuron 83:518–532.

    https://doi.org/10.1016/j.neuron.2014.07.016

    • PubMed
    • Google Scholar
48. 1. Weaver AH

    (2005) Reciprocal evolution of the cerebellum and neocortex in fossil humans

    PNAS 102:3576–3580.

    https://doi.org/10.1073/pnas.0500692102

    • PubMed
    • Google Scholar
49. 1. Witter L
    2. Canto CB
    3. Hoogland TM
    4. de Gruijl JR
    5. De Zeeuw CI

    (2013) Strength and timing of motor responses mediated by rebound firing in the cerebellar nuclei after purkinje cell activation

    Frontiers in Neural Circuits 7:133.

    https://doi.org/10.3389/fncir.2013.00133

    • PubMed
    • Google Scholar
50. 1. Yamaguchi K
    2. Sakurai Y

    (2016) Inactivation of cerebellar cortical crus II disrupts temporal processing of absolute timing but not relative timing in voluntary Movements

    Frontiers in Systems Neuroscience 10:16.

    https://doi.org/10.3389/fnsys.2016.00016

    • PubMed
    • Google Scholar
51. 1. Yang CF
    2. Chiang MC
    3. Gray DC
    4. Prabhakaran M
    5. Alvarado M
    6. Juntti SA
    7. Unger EK
    8. Wells JA
    9. Shah NM

    (2013) Sexually dimorphic neurons in the ventromedial hypothalamus govern mating in both sexes and aggression in males

    Cell 153:896–909.

    https://doi.org/10.1016/j.cell.2013.04.017

    • PubMed
    • Google Scholar
52. 1. Zanchetti A
    2. Zoccolini A

    (1954) Autonomic hypothalamic outbursts elicited by cerebellar stimulation

    Journal of Neurophysiology 17:475–483.

    https://doi.org/10.1152/jn.1954.17.5.475

    • PubMed
    • Google Scholar
53. 1. Zhang X-M
    2. Ng AH-L
    3. Tanner JA
    4. Wu W-T
    5. Copeland NG
    6. Jenkins NA
    7. Huang J-D

    (2004) Highly restricted expression of Cre recombinase in cerebellar Purkinje cells

    Genesis 40:45–51.

    https://doi.org/10.1002/gene.20062

    • Google Scholar
54. 1. Zhang F
    2. Wang LP
    3. Brauner M
    4. Liewald JF
    5. Kay K
    6. Watzke N
    7. Wood PG
    8. Bamberg E
    9. Nagel G
    10. Gottschalk A
    11. Deisseroth K

    (2007) Multimodal fast optical interrogation of neural circuitry

    Nature 446:633–639.

    https://doi.org/10.1038/nature05744

    • PubMed
    • Google Scholar

Author details

1. Skyler L Jackman

   1. Department of Neurobiology, Harvard Medical School, Boston, United States
   2. Vollum Institute, Oregon Health and Science University, Portland, United States

   Contribution

   Conceptualization, Supervision, Investigation, Methodology, Writing - original draft

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-6500-3937

2. Christopher H Chen

   Department of Neurobiology, Harvard Medical School, Boston, United States

   Contribution

   Investigation, Writing - original draft

   Competing interests

   No competing interests declared

3. Heather L Offermann

   Department of Neurobiology, Harvard Medical School, Boston, United States

   Contribution

   Investigation

   Competing interests

   No competing interests declared

4. Iain R Drew

   Department of Neurobiology, Harvard Medical School, Boston, United States

   Contribution

   Investigation

   Competing interests

   No competing interests declared

5. Bailey M Harrison

   Department of Neurobiology, Harvard Medical School, Boston, United States

   Contribution

   Investigation

   Competing interests

   No competing interests declared

6. Anna M Bowman

   Vollum Institute, Oregon Health and Science University, Portland, United States

   Contribution

   Investigation

   Competing interests

   No competing interests declared

7. Katelyn M Flick

   Department of Neurobiology, Harvard Medical School, Boston, United States

   Contribution

   Investigation

   Competing interests

   No competing interests declared

8. Isabella Flaquer

   Department of Neurobiology, Harvard Medical School, Boston, United States

   Contribution

   Investigation

   Competing interests

   No competing interests declared

9. Wade G Regehr

   Department of Neurobiology, Harvard Medical School, Boston, United States

   Contribution

   Conceptualization, Resources, Supervision, Funding acquisition, Writing - original draft

   For correspondence

   wade_regehr@hms.harvard.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3485-8094

• 27,928

  views

• 4,428

  downloads

• 39

  citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.