Cerebellar granule cells acquire a widespread predictive feedback signal during motor learning.
Cerebellar granule cells, which constitute half the brain's neurons, supply Purkinje cells with contextual information necessary for motor learning, but how they encode this information is unknown. Here we show, using two-photon microscopy to track neural activity over multiple days of cerebellum-dependent eyeblink conditioning in mice, that granule cell populations acquire a dense representation of the anticipatory eyelid movement. Initially, granule cells responded to neutral visual and somatosensory stimuli as well as periorbital airpuffs used for training. As learning progressed, two-thirds of monitored granule cells acquired a conditional response whose timing matched or preceded the learned eyelid movements. Granule cell activity covaried trial by trial to form a redundant code. Many granule cells were also active during movements of nearby body structures. Thus, a predictive signal about the upcoming movement is widely available at the input stage of the cerebellar cortex, as required by forward models of cerebellar control.
Princeton Neuroscience Institute and Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA.|Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, New York, USA.
Andrea
A
Giovannucci
Princeton Neuroscience Institute and Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA.|Netherlands Institute for Neuroscience, Amsterdam, the Netherlands.
Aleksandra
A
Badura
Princeton Neuroscience Institute and Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA.|Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA.
Ben
B
Deverett
Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Farzaneh
http://orcid.org/0000-0001-6454-2448
F
Najafi
Princeton Neuroscience Institute and Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA.
Talmo D
TD
Pereira
Department of Neuroscience, Erasmus MC, Rotterdam, the Netherlands.
Zhenyu
Z
Gao
Princeton Neuroscience Institute and Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA.|School of Engineering, Brown University, Providence, Rhode Island, USA.
Ilker
I
Ozden
Princeton Neuroscience Institute and Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA.
Alexander D
AD
Kloth
Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, New York, USA.|Departments of Statistics and Neuroscience, Columbia University, New York, New York, USA.
Eftychios
E
Pnevmatikakis
Departments of Statistics and Neuroscience, Columbia University, New York, New York, USA.
Liam
L
Paninski
Netherlands Institute for Neuroscience, Amsterdam, the Netherlands.|Department of Neuroscience, Erasmus MC, Rotterdam, the Netherlands.
Chris I
CI
De Zeeuw
Department of Neuroscience, Baylor College of Medicine, Houston, Texas, USA.
Javier F
JF
Medina
Princeton Neuroscience Institute and Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA.
Samuel S-H
SS
Wang
D000818:Animals; D059031:Anticipation, Psychological / Q000502:physiology; D002531:Cerebellum / Q000502:physiology*; D003214:Conditioning, Classical / Q000502:physiology; D005246:Feedback; D007858:Learning / Q000502:physiology*; D008297:Male; D051379:Mice; D008822:Mice, Transgenic; D009474:Neurons / Q000502:physiology*