Modelling 3D saccade generation by feedforward optimal control

Modeling kinematic variability reveals displacement and velocity based dual control of saccadic eye movements

Noise is a ubiquitous component of motor systems that leads to behavioral variability of all types of movements. Nonetheless, systems-based models investigating human movements are generally deterministic and explain only the central tendencies like mean trajectories. In this paper, a novel approach to modeling kinematic variability of movements is presented and tested on the oculomotor system. This approach reconciles the two prominent philosophies of saccade control: displacement-based control versus velocity-based control. This was achieved by quantifying the variability in saccadic eye movements and developing a stochastic model of its control. The proposed stochastic dual model generated significantly better fits of inter-trial variances of the saccade trajectories compared to existing models. These results suggest that the saccadic system can flexibly use the information of both desired displacement and velocity for its control. This study presents a potential framework for investigating computational principles of motor control in the presence of noise utilizing stochastic modeling of kinematic variability.

Realistic 3D human saccades generated by a 6-DOF biomimetic robotic eye under optimal control

We recently developed a biomimetic robotic eye with six independent tendons, each controlled by their own rotatory motor, and with insertions on the eye ball that faithfully mimic the biomechanics of the human eye. We constructed an accurate physical computational model of this system, and learned to control its nonlinear dynamics by optimising a cost that penalised saccade inaccuracy, movement duration, and total energy expenditure of the motors. To speed up the calculations, the physical simulator was approximated by a recurrent neural network (NARX). We showed that the system can produce realistic eye movements that closely resemble human saccades in all directions: their nonlinear main-sequence dynamics (amplitude-peak eye velocity and duration relationships), cross-coupling of the horizontal and vertical movement components leading to approximately straight saccade trajectories, and the 3D kinematics that restrict 3D eye orientations to a plane (Listing's law). Interestingly, the control algorithm had organised the motors into appropriate agonist-antagonist muscle pairs, and the motor signals for the eye resembled the well-known pulse-step characteristics that have been reported for monkey motoneuronal activity. We here fully analyse the eye-movement properties produced by the computational model across the entire oculomotor range and the underlying control signals. We argue that our system may shed new light on the neural control signals and their couplings within the final neural pathways of the primate oculomotor system, and that an optimal control principle may account for a wide variety of oculomotor behaviours. The generated data are publicly available at https://data.ru.nl/collections/di/dcn/DSC_626870_0003_600.

Dynamic control of eye-head gaze shifts by a spiking neural network model of the superior colliculus

Introduction

To reorient gaze (the eye's direction in space) towards a target is an overdetermined problem, as infinitely many combinations of eye- and head movements can specify the same gaze-displacement vector. Yet, behavioral measurements show that the primate gaze-control system selects a specific contribution of eye- and head movements to the saccade, which depends on the initial eye-in-head orientation. Single-unit recordings in the primate superior colliculus (SC) during head-unrestrained gaze shifts have further suggested that cells may encode the instantaneous trajectory of a desired straight gaze path in a feedforward way by the total cumulative number of spikes in the neural population, and that the instantaneous gaze kinematics are thus determined by the neural firing rates. The recordings also indicated that the latter is modulated by the initial eye position. We recently proposed a conceptual model that accounts for many of the observed properties of eye-head gaze shifts and on the potential role of the SC in gaze control.

Methods

Here, we extend and test the model by incorporating a spiking neural network of the SC motor map, the output of which drives the eye-head motor control circuitry by linear cumulative summation of individual spike effects of each recruited SC neuron. We propose a simple neural mechanism on SC cells that explains the modulatory influence of feedback from an initial eye-in-head position signal on their spiking activity. The same signal also determines the onset delay of the head movement with respect to the eye. Moreover, the downstream eye- and head burst generators were taken to be linear, as our earlier work had indicated that much of the non-linear main-sequence kinematics of saccadic eye movements may be due to neural encoding at the collicular level, rather than at the brainstem.

Results and discussion

We investigate how the spiking activity of the SC population drives gaze to the intended target location within a dynamic local gaze-velocity feedback circuit that yields realistic eye- and head-movement kinematics and dynamic SC gaze-movement fields.

Enhancing the Sense of Attention from an Assistance Mobile Robot by Improving Eye-Gaze Contact from Its Iconic Face Displayed on a Flat Screen

One direct way to express the sense of attention in a human interaction is through the gaze. This paper presents the enhancement of the sense of attention from the face of a human-sized mobile robot during an interaction. This mobile robot was designed as an assistance mobile robot and uses a flat screen at the top of the robot to display an iconic (simplified) face with big round eyes and a single line as a mouth. The implementation of eye-gaze contact from this iconic face is a problem because of the difficulty of simulating real 3D spherical eyes in a 2D image considering the perspective of the person interacting with the mobile robot. The perception of eye-gaze contact has been improved by manually calibrating the gaze of the robot relative to the location of the face of the person interacting with the robot. The sense of attention has been further enhanced by implementing cyclic face explorations with saccades in the gaze and by performing blinking and small movements of the mouth.

A change in perspective: The interaction of saccadic and pursuit eye movements in oculomotor control and perception

Due to the close relationship between oculomotor behavior and visual processing, eye movements have been studied in many different areas of research over the last few decades. While these studies have brought interesting insights, specialization within each research area comes at the potential cost of a narrow and isolated view of the oculomotor system. In this review, we want to expand this perspective by looking at the interactions between the two most important types of voluntary eye movements: saccades and pursuit. Recent evidence indicates multiple interactions and shared signals at the behavioral and neurophysiological level for oculomotor control and for visual perception during pursuit and saccades. Oculomotor control seems to be based on shared position- and velocity-related information, which leads to multiple behavioral interactions and synergies. The distinction between position- and velocity-related information seems to be also present at the neurophysiological level. In addition, visual perception seems to be based on shared efferent signals about upcoming eye positions and velocities, which are to some degree independent of the actual oculomotor response. This review suggests an interactive perspective on the oculomotor system, based mainly on different types of sensory input, and less so on separate subsystems for saccadic or pursuit eye movements.