Electrical coupling regulated by GABAergic nucleo-olivary afferent fibres facilitates cerebellar sensory–motor adaptation

Abstract

The inferior olivary (IO) nucleus makes up the signal gateway for several organs to the cerebellar cortex. Located within the sensory–motor-cerebellum pathway, the IO axons, i.e., climbing fibres (CFs), massively synapse onto the cerebellar Purkinje cells (PCs) regulating motor learning whilst the olivary nucleus receives negative feedback through the GABAergic nucleo-olivary (NO) pathway. The NO pathway regulates the electrical coupling (EC) amongst the olivary cells thus facilitating synchrony and timing. However, the involvement of this EC regulation on cerebellar adaptive behaviour is still under debate. In our study we have used a spiking cerebellar model to assess the role of the NO pathway in regulating vestibulo-ocular-reflex (VOR) adaptation. The model incorporates spike-based synaptic plasticity at multiple cerebellar sites and an electrically-coupled olivary system. The olivary system plays a central role in regulating the CF spike-firing patterns that drive the PCs, whose axons ultimately shape the cerebellar output. Our results suggest that a systematic GABAergic NO deactivation decreases the spatio-temporal complexity of the IO firing patterns thereby worsening the temporal resolution of the olivary system. Conversely, properly coded IO spatio-temporal firing patterns, thanks to NO modulation, finely shape the balance between long-term depression and potentiation, which optimises VOR adaptation. Significantly, the NO connectivity pattern constrained to the same micro-zone helps maintain the spatio-temporal complexity of the IO firing patterns through time. Moreover, the temporal alignment between the latencies found in the NO fibres and the sensory–motor pathway delay appears to be crucial for facilitating the VOR. When we consider all the above points we believe that these results predict that the NO pathway is instrumental in modulating the olivary coupling and relevant to VOR adaptation.

Publication
Neural Networks
Niceto Luque
Niceto Luque
Associate Professor

Associate Professor at the Department of Computer Engineering, Automation and Robotics and Principal Investigator at the Applied Computational Neuroscience Group.

Francisco Naveros
Francisco Naveros
Postdoctoral Researcher

Senior postdoc at the Applied Computational Neuroscience Research Group at the University of Granada.

Ignacio Abadia
Ignacio Abadia
Postdoctoral Researcher

Postdoctoral Researcher at the Applied Computational Neuroscience Research Group at the University of Granada.

Eduardo Ros
Eduardo Ros
Full Professor

Full professor in computer architecture, principal investigator at the Computational Neuroscience and Neurorobotics Lab and principal investigator of the VALERIA lab of the University of Granada.