A Stochastic Optimal Control Model with Internal Feedback and Velocity Tracking for Saccades

TL;DR

This paper introduces a novel stochastic optimal control model for saccadic eye movements that incorporates velocity tracking and internal feedback, validated against human behavioral data and capable of predicting various saccade directions.

Contribution

It presents the first optimal control model of saccades based on velocity control, integrating recent neurophysiological findings into a comprehensive framework.

Findings

Successfully predicts horizontal, vertical, and oblique saccades.

Aligns with neurophysiological evidence of velocity encoding.

Provides a new perspective on saccade control mechanisms.

Abstract

A stochastic optimal control based model with velocity tracking and internal feedback for saccadic eye movements is presented in this paper. Recent evidence from neurophysiological studies of superior colliculus suggests the presence of a dynamic input to the saccade generation system that encodes saccade velocity, rather than just the saccade amplitude and direction. The new evidence makes it imperative to test if saccade control can use a desired velocity input which is the basis for the proposed velocity tracking model. The model is validated using behavioral data of saccades generated by healthy human subjects. It generates trajectories of horizontal saccades made to different amplitudes as well as predicts vertical and oblique saccade behavior. This paper presents the first-ever model of the saccadic system in an optimal control framework using an alternate interpretation of velocity-based control, contrary to the dominant end-point based models available in the literature.