Accurate planning of manual tracking requires a 3D visuomotor transformation of velocity signals

Context effects on smooth pursuit and manual interception of a disappearing target

In our natural environment, we interact with moving objects that are surrounded by richly textured, dynamic visual contexts. Yet most laboratory studies on vision and movement show visual objects in front of uniform gray backgrounds. Context effects on eye movements have been widely studied, but it is less well known how visual contexts affect hand movements. Here we ask whether eye and hand movements integrate motion signals from target and context similarly or differently, and whether context effects on eye and hand change over time. We developed a track-intercept task requiring participants to track the initial launch of a moving object ("ball") with smooth pursuit eye movements. The ball disappeared after a brief presentation, and participants had to intercept it in a designated "hit zone." In two experiments (n = 18 human observers each), the ball was shown in front of a uniform or a textured background that either was stationary or moved along with the target. Eye and hand movement latencies and speeds were similarly affected by the visual context, but eye and hand interception (eye position at time of interception, and hand interception timing error) did not differ significantly between context conditions. Eye and hand interception timing errors were strongly correlated on a trial-by-trial basis across all context conditions, highlighting the close relation between these responses in manual interception tasks. Our results indicate that visual contexts similarly affect eye and hand movements but that these effects may be short-lasting, affecting movement trajectories more than movement end points.NEW & NOTEWORTHY In a novel track-intercept paradigm, human observers tracked a briefly shown object moving across a textured, dynamic context and intercepted it with their finger after it had disappeared. Context motion significantly affected eye and hand movement latency and speed, but not interception accuracy; eye and hand position at interception were correlated on a trial-by-trial basis. Visual context effects may be short-lasting, affecting movement trajectories more than movement end points.

Computations underlying the visuomotor transformation for smooth pursuit eye movements

Smooth pursuit eye movements are driven by retinal motion and enable us to view moving targets with high acuity. Complicating the generation of these movements is the fact that different eye and head rotations can produce different retinal stimuli but giving rise to identical smooth pursuit trajectories. However, because our eyes accurately pursue targets regardless of eye and head orientation (Blohm G, Lefèvre P. J Neurophysiol 104: 2103-2115, 2010), the brain must somehow take these signals into account. To learn about the neural mechanisms potentially underlying this visual-to-motor transformation, we trained a physiologically inspired neural network model to combine two-dimensional (2D) retinal motion signals with three-dimensional (3D) eye and head orientation and velocity signals to generate a spatially correct 3D pursuit command. We then simulated conditions of 1) head roll-induced ocular counterroll, 2) oblique gaze-induced retinal rotations, 3) eccentric gazes (invoking the half-angle rule), and 4) optokinetic nystagmus to investigate how units in the intermediate layers of the network accounted for different 3D constraints. Simultaneously, we simulated electrophysiological recordings (visual and motor tunings) and microstimulation experiments to quantify the reference frames of signals at each processing stage. We found a gradual retinal-to-intermediate-to-spatial feedforward transformation through the hidden layers. Our model is the first to describe the general 3D transformation for smooth pursuit mediated by eye- and head-dependent gain modulation. Based on several testable experimental predictions, our model provides a mechanism by which the brain could perform the 3D visuomotor transformation for smooth pursuit.

Evidence for a reference frame transformation of vestibular signal contributions to voluntary reaching

To contribute appropriately to voluntary reaching during body motion, vestibular signals must be transformed from a head-centered to a body-centered reference frame. We quantitatively investigated the evidence for this transformation during online reach execution by using galvanic vestibular stimulation (GVS) to simulate rotation about a head-fixed, roughly naso-occipital axis as human subjects made planar reaching movements to a remembered location with their head in different orientations. If vestibular signals that contribute to reach execution have been transformed from a head-centered to a body-centered reference frame, the same stimulation should be interpreted as body tilt with the head upright but as vertical-axis rotation with the head inclined forward. Consequently, GVS should perturb reach trajectories in a head-orientation-dependent way. Consistent with this prediction, GVS applied during reach execution induced trajectory deviations that were significantly larger with the head forward compared with upright. Only with the head forward were trajectories consistently deviated in opposite directions for rightward versus leftward simulated rotation, as appropriate to compensate for body vertical-axis rotation. These results demonstrate that vestibular signals contributing to online reach execution have indeed been transformed from a head-centered to a body-centered reference frame. Reach deviation amplitudes were comparable to those predicted for ideal compensation for body rotation using a biomechanical limb model. Finally, by comparing the effects of application of GVS during reach execution versus prior to reach onset we also provide evidence that spatially transformed vestibular signals contribute to at least partially distinct compensation mechanisms for body motion during reach planning versus execution.

Accounting for direction and speed of eye motion in planning visually guided manual tracking

Accurate motor planning in a dynamic environment is a critical skill for humans because we are often required to react quickly and adequately to the visual motion of objects. Moreover, we are often in motion ourselves, and this complicates motor planning. Indeed, the retinal and spatial motions of an object are different because of the retinal motion component induced by self-motion. Many studies have investigated motion perception during smooth pursuit and concluded that eye velocity is partially taken into account by the brain. Here we investigate whether the eye velocity during ongoing smooth pursuit is taken into account for the planning of visually guided manual tracking. We had 10 human participants manually track a target while in steady-state smooth pursuit toward another target such that the difference between the retinal and spatial target motion directions could be large, depending on both the direction and the speed of the eye. We used a measure of initial arm movement direction to quantify whether motor planning occurred in retinal coordinates (not accounting for eye motion) or was spatially correct (incorporating eye velocity). Results showed that the eye velocity was nearly fully taken into account by the neuronal areas involved in the visuomotor velocity transformation (between 75% and 102%). In particular, these neuronal pathways accounted for the nonlinear effects due to the relative velocity between the target and the eye. In conclusion, the brain network transforming visual motion into a motor plan for manual tracking adequately uses extraretinal signals about eye velocity.

3D kinematics using dual quaternions: theory and applications in neuroscience

In behavioral neuroscience, many experiments are developed in 1 or 2 spatial dimensions, but when scientists tackle problems in 3-dimensions (3D), they often face problems or new challenges. Results obtained for lower dimensions are not always extendable in 3D. In motor planning of eye, gaze or arm movements, or sensorimotor transformation problems, the 3D kinematics of external (stimuli) or internal (body parts) must often be considered: how to describe the 3D position and orientation of these objects and link them together? We describe how dual quaternions provide a convenient way to describe the 3D kinematics for position only (point transformation) or for combined position and orientation (through line transformation), easily modeling rotations, translations or screw motions or combinations of these. We also derive expressions for the velocities of points and lines as well as the transformation velocities. Then, we apply these tools to a motor planning task for manual tracking and to the modeling of forward and inverse kinematics of a seven-dof three-link arm to show the interest of dual quaternions as a tool to build models for these kinds of applications.