Active inference, eye movements and oculomotor delays

TL;DR

This paper explores how active inference can compensate for sensorimotor delays in eye movement control, using generalized coordinates and hierarchical models to improve prediction and response in uncertain visual environments.

Contribution

It introduces a neurobiologically plausible active inference framework that accounts for delays and enables anticipatory eye movements through hierarchical generative models.

Findings

Effective delay compensation in neuronal simulations

Hierarchical models enable recognition of occluded trajectories

Improved anticipatory responses in simulated eye movements

Abstract

This paper considers the problem of sensorimotor delays in the optimal control of (smooth) eye movements under uncertainty. Specifically, we consider delays in the visuo-oculomotor loop and their implications for active inference. Active inference uses a generalisation of Kalman filtering to provide Bayes optimal estimates of hidden states and action in generalized coordinates of motion. Representing hidden states in generalized coordinates provides a simple way of compensating for both sensory and oculomotor delays. The efficacy of this scheme is illustrated using neuronal simulations of pursuit initiation responses, with and without compensation. We then consider an extension of the gener-ative model to simulate smooth pursuit eye movements - in which the visuo-oculomotor system believes both the target and its centre of gaze are attracted to a (hidden) point moving in the visual field. Finally, the generative model is equipped with a hierarchical structure, so that it can recognise and remember unseen (occluded) trajectories and emit anticipatory responses. These simulations speak to a straightforward and neurobiologically plausible solution to the generic problem of integrating information from different sources with different temporal delays and the particular difficulties encountered when a system - like the oculomotor system - tries to control its environment with delayed signals.