Cellular-resolution mapping uncovers spatial adaptive filtering at the rat cerebellum input stage

Stefano Casali,Marialuisa Tognolina,Daniela Gandolfi,Egidio D’Angelo,Jonathan Mapelli

doi:10.1038/s42003-020-01360-y

Stefano Casali, Marialuisa Tognolina + Show 3 more

Open Access

https://doi.org/10.1038/s42003-020-01360-y

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Abstract

Long-term synaptic plasticity is thought to provide the substrate for adaptive computation in brain circuits but very little is known about its spatiotemporal organization. Here, we combined multi-spot two-photon laser microscopy in rat cerebellar slices with realistic modeling to map the distribution of plasticity in multi-neuronal units of the cerebellar granular layer. The units, composed by ~300 neurons activated by ~50 mossy fiber glomeruli, showed long-term potentiation concentrated in the core and long-term depression in the periphery. This plasticity was effectively accounted for by an NMDA receptor and calcium-dependent induction rule and was regulated by the inhibitory Golgi cell loops. Long-term synaptic plasticity created effective spatial filters tuning the time-delay and gain of spike retransmission at the cerebellum input stage and provided a plausible basis for the spatiotemporal recoding of input spike patterns anticipated by the motor learning theory.

Highlights

Long-term synaptic plasticity is thought to provide the substrate for adaptive computation in brain circuits but very little is known about its spatiotemporal organization
The combination of SLM-2PM and microcircuit modeling, followed by validation using VSD recordings, shows how long-term synaptic plasticity, once distributed over functional multi-neuronal units, creates spatial filters capable of tuning the time delay and gain of spike retransmission at the cerebellum input stage. These results provide a plausible basis to explain the spatiotemporal recoding[9,10,11] and adaptive filtering[19,20,21] of input spike patterns anticipated by theory
The spatial filtering properties of the cerebellar granular layer revealed in this work support a critical prediction of motor learning theory[7,9,10,21]

Summary

Introduction

Long-term synaptic plasticity is thought to provide the substrate for adaptive computation in brain circuits but very little is known about its spatiotemporal organization. The combination of SLM-2PM and microcircuit modeling, followed by validation using VSD recordings, shows how long-term synaptic plasticity, once distributed over functional multi-neuronal units, creates spatial filters capable of tuning the time delay and gain of spike retransmission at the cerebellum input stage These results provide a plausible basis to explain the spatiotemporal recoding[9,10,11] and adaptive filtering[19,20,21] of input spike patterns anticipated by theory

Methods

Results

Conclusion