A Stochastic Feedback Model to Simulate Saccadic Eye Movement Variability

Variability is an important behavioral signature of biological movements that can be used as a tool to understand motor control. This study has modeled the inter-trial variability of very rapid eye movements called saccades by using a stochastic feedback model. The proposed model represents the brainstem saccade generation system with noise in the loop. Three types of noise signal namely visual noise, premotor noise and motor noise are considered in this model. The model can predict the inter-trial variability in the angular displacement of saccade trajectories. The accuracy of the predictions of the model has been verified using experimental data of horizontal saccades. It is observed that the presence of all the three noise components is important for the prediction of the dynamic evolution of the inter trial variability during eye movement. This work provides a way to better understand the control of the saccadic system. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved