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Parameter tuning differentiates granule cell subtypes enriching transmission properties at the cerebellum input stage

Authors: Stefano Masoli* 1, Marialuisa Tognolina* 1, Umberto Laforenza 2, Francesco Moccia 3, Egidio D'Angelo 1,4

Author information: 1 Department of Brain and Behavioral Sciences, University of Pavia, Via Forlanini 6, I-27100, Pavia, Italy, 2 Department of Molecular Medicine, University of Pavia, Via Forlanini 6, I-27100, Pavia, Italy, 3 Department of Biology and Biotechnology, University of Pavia, Via Forlanini 6, I-27100, Pavia, Italy, 4 Brain Connectivity Center, IRCCS Mondino Foundation, Via Mondino 2, I-27100, Pavia, Italy, * Co-Author,

Corresponding author: Egidio D'Angelo ( dangelo@unipv.it )

Journal: Nature

Download Url: https://www.nature.com/articles/s42003-020-0953-x

Citation: Masoli S.*, Tognolina M.*, Laforenza U., Moccia F., D’Angelo E. Parameter tuning differentiates granule cell subtypes enriching transmission properties at the cerebellum input stage. Nature Communications Biology 2020.

DOI: https://doi.org/10.1038/s42003-020-0953-x

Licence: the Creative Commons Attribution (CC BY) license  applies for all files. Under this Open Access license anyone  may copy, distribute, or reuse the files as long as the authors and the original source are properly cited.

Abstract:
The cerebellar granule cells (GrCs) are classically described as a homogeneous neuronal population discharging regularly without adaptation. We show that GrCs in fact generate diverse response patterns to current injection and synaptic activation, ranging from adaptation to acceleration of firing. Adaptation was predicted by parameter optimization in detailed computational models based on available knowledge on GrC ionic channels. The models also predicted that acceleration required additional mechanisms. We found that yet unrecognized TRPM4 currents specifically accounted for firing acceleration and that adapting GrCs outperformed accelerating GrCs in transmitting high-frequency mossy fiber (MF) bursts over a background discharge. This implied that GrC subtypes identified by their electroresponsiveness corresponded to specific neurotransmitter release probability values. Simulations showed that fine-tuning of pre- and post-synaptic parameters generated effective MF-GrC transmission channels, which could enrich the processing of input spike patterns and enhance spatio-temporal recoding at the cerebellar input stage.
Resources

Data and models: Experimental data and models used in the paper are available at the links reported below, grouped into the following categories: