Letter | Published:

Cerebellar granule cells encode the expectation of reward

Nature volume 544, pages 96100 (06 April 2017) | Download Citation

Abstract

The human brain contains approximately 60 billion cerebellar granule cells1, which outnumber all other brain neurons combined. Classical theories posit that a large, diverse population of granule cells allows for highly detailed representations of sensorimotor context, enabling downstream Purkinje cells to sense fine contextual changes2,3,4,5,6. Although evidence suggests a role for the cerebellum in cognition7,8,9,10, granule cells are known to encode only sensory11,12,13 and motor14 context. Here, using two-photon calcium imaging in behaving mice, we show that granule cells convey information about the expectation of reward. Mice initiated voluntary forelimb movements for delayed sugar-water reward. Some granule cells responded preferentially to reward or reward omission, whereas others selectively encoded reward anticipation. Reward responses were not restricted to forelimb movement, as a Pavlovian task evoked similar responses. Compared to predictable rewards, unexpected rewards elicited markedly different granule cell activity despite identical stimuli and licking responses. In both tasks, reward signals were widespread throughout multiple cerebellar lobules. Tracking the same granule cells over several days of learning revealed that cells with reward-anticipating responses emerged from those that responded at the start of learning to reward delivery, whereas reward-omission responses grew stronger as learning progressed. The discovery of predictive, non-sensorimotor encoding in granule cells is a major departure from the current understanding of these neurons and markedly enriches the contextual information available to postsynaptic Purkinje cells, with important implications for cognitive processing in the cerebellum.

  • Subscribe to Nature for full access:

    $199

    Subscribe

Additional access options:

Already a subscriber?  Log in  now or  Register  for online access.

Change history

  • Corrected online 05 April 2017

    Fig. 1b was corrected to remove an erroneous dashed line.

References

  1. 1.

    Coordinated scaling of cortical and cerebellar numbers of neurons. Front. Neuroanat. 4, 12 (2010)

  2. 2.

    A theory of cerebellar cortex. J. Physiol. (Lond.) 202, 437–470 (1969)

  3. 3.

    A theory of cerebellar function. Math. Biosci. 10, 25–61 (1971)

  4. 4.

    Adaptive filter model of the cerebellum. Biol. Cybern. 45, 195–206 (1982)

  5. 5.

    et al. High-fidelity transmission of sensory information by single cerebellar mossy fibre boutons. Nature 450, 1245–1248 (2007)

  6. 6.

    et al. Convergence of pontine and proprioceptive streams onto multimodal cerebellar granule cells. eLife 2, e00400 (2013)

  7. 7.

    Control of mental activities by internal models in the cerebellum. Nat. Rev. Neurosci. 9, 304–313 (2008)

  8. 8.

    , & Cerebellum and nonmotor function. Annu. Rev. Neurosci. 32, 413–434 (2009)

  9. 9.

    , & Functional topography of the cerebellum for motor and cognitive tasks: an fMRI study. Neuroimage 59, 1560–1570 (2012)

  10. 10.

    et al. Autistic-like behaviour and cerebellar dysfunction in Purkinje cell Tsc1 mutant mice. Nature 488, 647–651 (2012)

  11. 11.

    & Sensory transmission in cerebellar granule cells relies on similarly coded mossy fiber inputs. Proc. Natl Acad. Sci. USA 106, 2389–2394 (2009)

  12. 12.

    , , , & Dynamic properties of sensory stimulation evoked responses in mouse cerebellar granule cell layer and molecular layer. Neurosci. Lett. 585, 114–118 (2015)

  13. 13.

    , & Multimodal sensory integration in single cerebellar granule cells in vivo. eLife 4, e12916 (2015)

  14. 14.

    , , & Synaptic representation of locomotion in single cerebellar granule cells. eLife 4, e07290 (2015)

  15. 15.

    , & Cerebellar Purkinje cell simple spike discharge encodes movement velocity in primates during visuomotor arm tracking. J. Neurosci. 19, 1782–1803 (1999)

  16. 16.

    , & Dopamine responses comply with basic assumptions of formal learning theory. Nature 412, 43–48 (2001)

  17. 17.

    et al. Silencing the majority of cerebellar granule cells uncovers their essential role in motor learning and consolidation. Cell Reports 3, 1239–1251 (2013)

  18. 18.

    & Links from complex spikes to local plasticity and motor learning in the cerebellum of awake-behaving monkeys. Nat. Neurosci. 11, 1185–1192 (2008)

  19. 19.

    & The primate cerebellum selectively encodes unexpected self-motion. Curr. Biol. 23, 947–955 (2013)

  20. 20.

    Predictive reward signal of dopamine neurons. J. Neurophysiol. 80, 1–27 (1998)

  21. 21.

    , , , & Neuron-type-specific signals for reward and punishment in the ventral tegmental area. Nature 482, 85–88 (2012)

  22. 22.

    , , & Neuronal activity in monkey ventral striatum related to the expectation of reward. J. Neurosci. 12, 4595–4610 (1992)

  23. 23.

    & Reward-related neuronal activity during go-nogo task performance in primate orbitofrontal cortex. J. Neurophysiol. 83, 1864–1876 (2000)

  24. 24.

    , & Activation of dorsal raphe serotonin neurons underlies waiting for delayed rewards. J. Neurosci. 31, 469–479 (2011)

  25. 25.

    & Representation of negative motivational value in the primate lateral habenula. Nat. Neurosci. 12, 77–84 (2009)

  26. 26.

    , , , & Roles of the lateral habenula and anterior cingulate cortex in negative outcome monitoring and behavioral adjustment in nonhuman primates. Neuron 88, 792–804 (2015)

  27. 27.

    et al. Ultrasensitive fluorescent proteins for imaging neuronal activity. Nature 499, 295–300 (2013)

  28. 28.

    et al. Transgenic mice for intersectional targeting of neural sensors and effectors with high specificity and performance. Neuron 85, 942–958 (2015)

  29. 29.

    et al. Visualizing the distribution of synapses from individual neurons in the mouse brain. PLoS One 5, e11503 (2010)

  30. 30.

    et al. Smaller inner ear sensory epithelia in Neurog1 null mice are related to earlier hair cell cycle exit. Dev. Dyn. 234, 633–650 (2005)

  31. 31.

    et al. Math1 is essential for genesis of cerebellar granule neurons. Nature 390, 169–172 (1997)

  32. 32.

    et al. A robust and high-throughput Cre reporting and characterization system for the whole mouse brain. Nat. Neurosci. 13, 133–140 (2010)

  33. 33.

    , & Towards development of a 2-DOF planar oparallel robot with optimal workspace use. In 2007 IEEE International Conference on Systems, Man and Cybernetics. 1562–1566 (ISIC, 2007)

  34. 34.

    et al. Visualizing mammalian brain area interactions by dual-axis two-photon calcium imaging. Nat. Neurosci. 17, 1825–1829 (2014)

  35. 35.

    , & ScanImage: flexible software for operating laser scanning microscopes. Biomed. Eng. Online 2, 13 (2003)

  36. 36.

    , & A pyramid approach to subpixel registration based on intensity. IEEE Trans. Image Process. 7, 27–41 (1998)

  37. 37.

    , & Automated analysis of cellular signals from large-scale calcium imaging data. Neuron 63, 747–760 (2009)

  38. 38.

    , & Efferents and afferents of the ventral tegmental-A10 region studied after local injection of [3H]leucine and horseradish peroxidase. Brain Res. 178, 17–40 (1979)

  39. 39.

    , , & Dopaminergic and non-dopaminergic neurons in the ventral tegmental area of the rat project, respectively, to the cerebellar cortex and deep cerebellar nuclei. Neuroscience 51, 719–728 (1992)

  40. 40.

    The projections of the ventral tegmental area and adjacent regions: a combined fluorescent retrograde tracer and immunofluorescence study in the rat. Brain Res. Bull. 9, 321–353 (1982)

  41. 41.

    , , & Ascending systems of catecholamine neurons from the lower brain stem. Acta Physiol. Scand. 62, 485–486 (1964)

  42. 42.

    , & The projections of the A8, A9 and A10 dopaminergic cell bodies: evidence for a nigral-hypothalamic-median eminence dopaminergic pathway. Brain Res. 108, 363–370 (1976)

  43. 43.

    , & Dopaminergic innervation and binding in the rat cerebellum. Neurosci. Lett. 130, 208–212 (1991)

  44. 44.

    et al. Cerebellar neurotransmission in attention-deficit/hyperactivity disorder: does dopamine neurotransmission occur in the cerebellar vermis? J. Neurosci. Methods 151, 62–67 (2006)

  45. 45.

    et al. Viral-genetic tracing of the input–output organization of a central noradrenaline circuit. Nature 524, 88–92 (2015)

  46. 46.

    . et al. Cre recombinase-mediated restoration of nigrostriatal dopamine in dopamine-deficient mice reverses hypophagia and bradykinesia. Proc. Natl Acad. Sci. USA 103, 8858–8863 (2006)

  47. 47.

    et al. Circuit architecture of VTA dopamine neurons revealed by systematic input-output mapping. Cell 162, 622–634 (2015)

  48. 48.

    et al. A designer AAV variant permits efficient retrograde access to projection neurons. Neuron 92, 372–382 (2016)

Download references

Acknowledgements

We thank C. Kim for designing and assembling the capacitive lick sensor, L. Kitch for image processing code, J. Lecoq for microscope design, H. Zeng, E. Kim, E. Callaway and members of the Luo laboratory for reagents, mouse lines, and helpful discussions, and W. Newsome and J. Raymond for critical comments on the manuscript. M.J.W. was supported by Epilepsy Training Grant. M.J.S. and L.L. are HHMI investigators. This work was supported by NIH grants and Hughes Collaborative Innovation Award to L.L.

Author information

Author notes

    • Mark J. Wagner
    •  & Tony Hyun Kim

    These authors contributed equally to this work.

Affiliations

  1. Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, California 94305, USA

    • Mark J. Wagner
    • , Tony Hyun Kim
    • , Joan Savall
    • , Mark J. Schnitzer
    •  & Liqun Luo
  2. Department of Electrical Engineering, Stanford University, Stanford, California 94305, USA

    • Tony Hyun Kim
  3. Department of Applied Physics, Stanford University, Stanford, California 94305, USA

    • Mark J. Schnitzer

Authors

  1. Search for Mark J. Wagner in:

  2. Search for Tony Hyun Kim in:

  3. Search for Joan Savall in:

  4. Search for Mark J. Schnitzer in:

  5. Search for Liqun Luo in:

Contributions

M.J.W. designed and executed all experiments and analysed the data. T.H.K. contributed microscopy instrumentation as well as processing of brain imaging and behavioural videos. J.S. contributed to manipulandum design. M.J.S. provided imaging hardware, software, and expertise. L.L. supervised the project. M.J.W. and L.L. wrote the paper with contributions from all authors.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Mark J. Wagner or Mark J. Schnitzer or Liqun Luo.

Reviewer Information Nature thanks C. De Zeeuw, T. Knopfel and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Extended data

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    This file contains Supplementary Text 1-2, additional references and Supplementary Table 1.

Videos

  1. 1.

    Example two-photon Ca2+ imaging of cerebellar granule cells during a forelimb movement task

    The video is 4x temporally down-sampled from the 13.5-Hz acquisition rate.

  2. 2.

    Example body motion tracking during a forelimb movement task

    Side view was used to track right forepaw and base of tail motion while bottom view was used to track motion of each hind paw.

About this article

Publication history

Received

Accepted

Published

DOI

https://doi.org/10.1038/nature21726

Rights and permissions

To obtain permission to re-use content from this article visit RightsLink.

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.