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When required, humans can generate very short latency reaches toward visual targets, such as catching a falling cellphone. During such rapid reaches, express arm responses are the first wave of upper limb muscle recruitment, occurring -80-100 ms after target appearance. There is accumulating evidence that express arm responses arise from signaling along the tecto-reticulo-spinal tract, but the involvement of the reticulospinal tract has not been well studied. Since the reticulospinal tract projects bilaterally, we studied whether express arm responses would be generated bilaterally. Human participants (n = 14; 7 females) performed visually guided reaches in a modified emerging target paradigm where either arm could intercept the target. We recorded electromyographic activity bilaterally from the pectoralis major muscle. Our analysis focused on target locations where participants reached with the right arm on some trials, and the left arm on others. In support of the involvement of the reticulospinal tract, express arm responses persisted bilaterally regardless of which arm reached to the target. The latency and magnitude of the express arm response did not depend on whether the arm was chosen to reach or not. However, on the reaching arm, the magnitude of the express arm response was correlated to the level of anticipatory activity. The bilateral generation of express arm responses supports the involvement of the reticulospinal tract. We surmise that the correlation between anticipatory activity and the magnitude of express arm responses on the reaching arm arises from convergence of cortically derived signals with a parallel subcortical pathway mediating the express arm response. NEW & NOTEWORTHY Express arm responses have been proposed to arise from the tecto-reticulo-spinal tract originating within the superior colliculus, but the involvement of the reticulospinal tract has not been well studied. Here, we show these responses appear bilaterally in a task where either arm can reach to a newly appearing stimulus. Our results suggest that the most rapid visuomotor transformations for reaching are performed by a subcortical pathway. [ABSTRACT FROM AUTHOR]

When we learn a novel task, the motor system needs to acquire both feedforward and feedback control. Currently, little is known about how the learning of these two mechanisms relate to each other. In the present study, we tested whether feedforward and feedback control need to be learned separately, or whether they are learned as common mechanism when a new control policy is acquired. Participants were trained to reach to two lateral and one central target in an environment with mirror (left-right)-reversed visual feedback. One group was allowed to make online movement corrections, whereas the other group only received visual information after the end of the movement. Learning of feedforward control was assessed by measuring the accuracy of the initial movement direction to lateral targets. Feedback control was measured in the responses to sudden visual perturbations of the cursor when reaching to the central target. Although feedforward control improved in both groups, it was significantly better when online corrections were not allowed. In contrast, feedback control only adaptively changed in participants who received online feedback and remained unchanged in the group without online corrections. Our findings suggest that when a new control policy is acquired, feedforward and feedback control are learned separately, and that there may be a trade-off in learning between feedback and feedforward controllers. [ABSTRACT FROM AUTHOR]

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 twodimensional (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. [ABSTRACT FROM AUTHOR]

Eye-hand coordination is crucial for our ability to interact with the world around us. However, much of the visually guided reaches that we perform require a spatial decoupling between gaze direction and hand orientation. These complex decoupled reaching movements are in contrast to more standard eye and hand reaching movements in which the eyes and the hand are coupled. The superior parietal lobule (SPL) receives converging eye and hand signals; however, what is yet to be understood is how the activity within this region is modulated during decoupled eye and hand reaches. To address this, we recorded local field potentials within SPL from two rhesus macaques during coupled vs. decoupled eye and hand movements. Overall we observed a distinct separation in synchrony within the lower 10- to 20-Hz beta range from that in the higher 30- to 40-Hz gamma range. Specifically, within the early planning phase, beta synchrony dominated; however, the onset of this sustained beta oscillation occurred later during eye-hand decoupled vs. coupled reaches. As the task progressed, there was a switch to low-frequency and gamma-dominated responses, specifically for decoupled reaches. More importantly, we observed local field potential activity to be a stronger task (coupled vs. decoupled) and state (planning vs. execution) predictor than that of single units alone. Our results provide further insight into the computations of SPL for visuomotor transformations and highlight the necessity of accounting for the decoupled eye-hand nature of a motor task when interpreting movement control research data. [ABSTRACT FROM AUTHOR]

When we learn a novel task, the motor system needs to acquire both feedforward and feedback control. Currently, little is known about how the learning of these two mechanisms relate to each other. In the present study, we tested whether feedforward and feedback control need to be learned separately, or whether they are learned as common mechanism when a new control policy is acquired. Participants were trained to reach to two lateral and one central target in an environment with mirror (left-right)-reversed visual feedback. One group was allowed to make online movement corrections, whereas the other group only received visual information after the end of the movement. Learning of feedforward control was assessed by measuring the accuracy of the initial movement direction to lateral targets. Feedback control was measured in the responses to sudden visual perturbations of the cursor when reaching to the central target. Although feedforward control improved in both groups, it was significantly better when online corrections were not allowed. In contrast, feedback control only adaptively changed in participants who received online feedback and remained unchanged in the group without online corrections. Our findings suggest that when a new control policy is acquired, feedforward and feedback control are learned separately, and that there may be a trade-off in learning between feedback and feedforward controllers., (Copyright © 2015 the American Physiological Society.)