Pattern separation in the cerebellum

Robin Angus Silver (primary)
Neuroscience, Physiology and Pharmacology
University College London
Michael Hausser (secondary)
Wolfson Institute for Brain Reaseach
University College London

Abstract

The cerebellum plays key roles in coordinating movements and predicting its consequences. Remarkably, the cerebellar cortex accounts for more than half of all the neurons in the vertebrate brain. The large neuronal expansion in input layer has been investigated in numerous theoretical studies, which predict that it separates sensorimotor activity patterns by projecting them into higher dimensional representations that are faster to learn, thereby improving performance. However, these theories have not been experimentally tested. This project will use 3D two-photon imaging, optogenetics and statistical analysis of high dimensional datasets to directly test the specific predictions of cerebellar pattern separation theories.


References

[1] Cayco-Gajic, N.A and Silver, R.A. (2019) Re-evaluating Circuit Mechanisms Underlying Pattern Separation. Neuron, 101(4):584-602. doi: 10.1016/j.neuron.2019.01.044. PMID: 30790539.
[2] Griffiths, V.A., Valera, A.M., Lau, J.Y., Roš, H., Younts, T.J., Marin, B., Baragli, C., Coyle, D., Evans, G.J., Konstantinou,, G., Koimtzis T., Nadella, K.M.N.S., Punde, S.A.., Kirkby, PA., Bianco, I.H., Silver, R.A. (2020) Real-time 3D movement correction for two-photon imaging in behaving animals. Nature Methods, 17(7):741-748. doi: 10.1038/s41592-020-0851-7. Epub 2020 Jun 1. PMID: 32483335
[3] Lanore, F. Cayco-Gajic, N.A., Gurnani, H., Coyle, D and Silver, R.A. (2021) Cerebellar granule cell axons support high dimensional representations, Nature Neuroscience, in Press.
[4] Cayco-Gajic, N.A., Clopath, C. and Silver, R.A. (2017). Sparse synaptic connectivity is required for decorrelation and pattern separation in feedforward networks. Nature Communications, 8(1):1116. doi: 10.1038/s41467-017-01109-y. PMID: 29061964.
[5] Gleeson, P., Cantarelli, M., Marin, B., Quintana, A., Earnshaw, M., Sadeh, S., Piasini, E., Birgiolas, J., Cannon, R.C., Cayco-Gajic, N.A., Crook, S., Davison, A.P., Dura-Bernal, S., Ecker, A., Hines, M.L., Idili, G., Lanore, F., Larson, S.D., Lytton, W.W., Majumdar, A., McDougal, R.A., Sivagnanam, S., Solinas, S., Stanislovas, R., van Albada, S.J., van Geit, W., Silver, R.A. (2019) Open Source Brain: A Collaborative Resource for Visualizing, Analyzing, Simulating, and Developing Standardized Models of Neurons and Circuits. Neuron, 103(3):395-411.e5. doi: 10.1016/j.neuron.2019.05.019. PMID: 31201122


BBSRC Area
Animal disease, health and welfare
Area of Biology
NeurobiologyPhysiology
Techniques & Approaches
Mathematics / StatisticsMicroscopy / ElectrophysiologySimulation / Modelling