Multiple timescales in the adaptation of the rotational VOR

Author:

Colagiorgio Paolo1,Bertolini Giovanni12,Bockisch Christopher J.23,Straumann Dominik2,Ramat Stefano1

Affiliation:

1. Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy;

2. Department of Neurology, University Hospital Zurich, Zurich, Switzerland; and

3. Departments of Ophthalmology and Otorhinolaryngology, University Hospital Zurich, Zurich, Switzerland

Abstract

Goal-directed movements, such as pointing and saccades, have been shown to share similar neural architectures, in spite of the different neuromuscular systems producing them. Such structure involve an inverse model of the actuator being controlled, which produces the commands innervating the muscles, and a forward model of the actuator, which predicts the sensory consequences of such commands and allows online movement corrections. Recent studies have shown that goal-directed movements also share similar motor-learning and motor-memory mechanisms, which are based on multiple timescales. The hypothesis that also the rotational vestibulo-ocular reflex (rVOR) may be based on a similar architecture has been presented recently. We hypothesize that multiple timescales are the brain's solution to the plasticity-stability dilemma, allowing adaptation to temporary and sudden changes while keeping stable motor-control abilities. If that were the case, then we would also expect the adaptation of reflex movements to follow the same principles. Thus we studied rVOR gain adaptation in eight healthy human subjects using a custom paradigm aimed at investigating the existence of spontaneous recovery, which we considered as the hallmark of multiple timescales in motor learning. Our experimental results show that spontaneous recovery occurred in six of eight subjects. Thus we developed a mathematical model of rVOR adaptation based on two hidden-states processes, which adapts the cerebellar-forward model of the ocular motor plant, and show that it accurately simulates our experimental data on rVOR gain adaptation, whereas a single timescale learning process fails to do so.

Funder

Italian Ministry of Research

Fondazione Cariplo (Cariplo Foundation)

Betty and David Koester Foundation for Brain Research

Publisher

American Physiological Society

Subject

Physiology,General Neuroscience

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