Motor preparation in the macaque smooth pursuit eye movement system

Motor preparation is a key component in the control of movement. It allows higher-level cognitive factors, like expectation, to enhance the speed and accuracy of planned movements. Smooth pursuit eye movements are relatively simple, voluntary eye movements that allow ocular tracking of moving objects. Smooth pursuit eye movements are driven by an integration of two signals: visual motion and visual-motor gain. Here, we use smooth pursuit eye movement in macaque monkeys as a model sensorimotor behavior to examine how motor preparation is incorporated into neural circuits responsible for controlling movement. First, we developed a behavioral paradigm that allowed rapid adaptation of expectation and shed light on how expectation-related motor preparation could be incorporated into the smooth pursuit eye movement circuit. We used blocks of trials with different blends of target speeds to influence the pursuit system’s expectation of upcoming target speed; we estimated the effect of expectation with probe trials of equal speed across the different blocks of trials. Pursuit initiation during the probe trials was faster during blocks of trials where most trials presented relatively fast-moving versus slow-moving targets. Contextual modulation of eye speed during pursuit initiation had a larger effect for low-contrast targets, consistent with a Bayesian-like computation that estimates target speed by a reliability-weighted combination between expectation and sensory evidence. Importantly, a model that adjusts the gain of visual-motor transmission predicts the behavioral effects of speed expectation and target contrast. Second, we collected single unit neurophysiological data in the smooth eye movement region of the frontal eye fields (FEFsem) while monkeys tracked targets during the speed context paradigm. Expectation of target speed is encoded as preparatory ramps of firing rate in FEFsem during fixations in advance of any target or eye movement. Following target motion onset, the preparatory activity is used in a Bayesian-like decoding computation that estimates the speed of target motion as a combination of the preparatory activity and visual motion inputs weighted according to the reliability of visual motion. Third, we evaluated what effect preparatory modulation of activity in FEFsem has on visual-motor gain during motor preparation. At the population level, FEFsem preparatory activity ramps up along “output-potent” dimensions and in parallel with a preparatory-related modulation of visual-motor gain. Taken together, these findings suggest that the pursuit system uses a visual-motor gain signal, implemented by FEFsem, to incorporate expectation-related signals into preparation for impending visual motion and smooth pursuit eye movement. This preparatory signal both dials up gain in advance of any visual motion or eye movement and influences the gain that is set during initiation of pursuit in a Bayesian-like manner.