Preparatory Gain Modulation of Visuomotor Transmission for Smooth Pursuit Eye Movements in Monkeys

Mechanisms that allow cortical preparatory activity without inappropriate movement

We reveal a novel mechanism that explains how preparatory activity can evolve in motor-related cortical areas without prematurely inducing movement. The smooth eye movement region of the frontal eye fields (FEF_SEM) is a critical node in the neural circuit controlling smooth pursuit eye movement. Preparatory activity evolves in the monkey FEF_SEM during fixation in parallel with an objective measure of visual-motor gain. We propose that the use of FEF_SEM output as a gain signal rather than a movement command allows for preparation to progress in pursuit without causing movement. We also show that preparatory modulation of firing rate in FEF_SEM predicts movement, providing evidence against the ‘movement-null’ space hypothesis as an explanation of how preparatory activity can progress without movement. Finally, there is a partial reorganization of FEF_SEM population activity between preparation and movement that would allow for a directionally non-specific component of preparatory visual-motor gain enhancement in pursuit.

Control of the strength of visual-motor transmission as the mechanism of rapid adaptation of priors for Bayesian inference in smooth pursuit eye movements

Bayesian inference provides a cogent account of how the brain combines sensory information with "priors" based on past experience to guide many behaviors, including smooth pursuit eye movements. We now demonstrate very rapid adaptation of the pursuit system's priors for target direction and speed. We go on to leverage that adaptation to outline possible neural mechanisms that could cause pursuit to show features consistent with Bayesian inference. Adaptation of the prior causes changes in the eye speed and direction at the initiation of pursuit. The adaptation appears after a single trial and accumulates over repeated exposure to a given history of target speeds and directions. The influence of the priors depends on the reliability of visual motion signals: priors are more effective against the visual motion signals provided by low-contrast vs. high-contrast targets. Adaptation of the direction prior generalizes to eye speed and vice versa, suggesting that both priors could be controlled by a single neural mechanism. We conclude that the pursuit system can learn the statistics of visual motion rapidly and use those statistics to guide future behavior. Furthermore, a model that adjusts the gain of visual-motor transmission predicts the effects of recent experience on pursuit direction and speed, as well as the specifics of the generalization between the priors for speed and direction. We suggest that Bayesian inference in pursuit behavior is implemented by distinctly non-Bayesian internal mechanisms that use the smooth eye movement region of the frontal eye fields to control of the gain of visual-motor transmission.NEW & NOTEWORTHY Bayesian inference can account for the interaction between sensory data and past experience in many behaviors. Here, we show, using smooth pursuit eye movements, that the priors based on past experience can be adapted over a very short time frame. We also show that a single model based on direction-specific adaptation of the strength of visual-motor transmission can explain the implementation and adaptation of priors for both target direction and target speed.

The neuronal basis of on-line visual control in smooth pursuit eye movements

Smooth pursuit eye movements allow us to maintain the image of a moving target on the fovea. Smooth pursuit consists of separate phases such as initiation and steady-state. These two phases are supported by different visual-motor mechanisms in cortical areas including the middle temporal (MT), the medial superior temporal (MST) areas and the frontal eye field (FEF). Retinal motion signals are responsible for beginning the process of pursuit initiation, whereas extraretinal signals play a role in maintaining tracking speed. Smooth pursuit often requires on-line gain adjustments during tracking in response to a sudden change in target motion. For example, a brief sinusoidal perturbation of target motion induces a corresponding perturbation of eye motion. Interestingly, the perturbation ocular response is enhanced when baseline pursuit velocity is higher, even though the stimulus frequency and amplitude are constant. This on-line gain control mechanism is not simply due to visually driven activity of cortical neurons. Visual and pursuit signals are primarily processed in cortical MT/MST and the magnitude of perturbation responses could be regulated by the internal gain parameter in FEF. Furthermore, the magnitude and the gain slope of perturbation responses are altered by smooth pursuit adaptation using repeated trials of a step-ramp tracking with two different velocities (double-velocity paradigm). Therefore, smooth pursuit adaptation, which is attributed to the cerebellar plasticity mechanism, could affect the on-line gain control mechanism.

The effects of smooth pursuit adaptation on the gain of visuomotor transmission in monkeys

Smooth pursuit eye movements are supported by visual-motor systems, where visual motion information is transformed into eye movement commands. Adaptation of the visuomotor systems for smooth pursuit is an important factor to maintain pursuit accuracy and high acuity vision. Short-term adaptation of initial pursuit gain can be produced experimentally using by repeated trials of a step-ramp tracking with two different velocities (double-step paradigm) that step-up (10-30°/s) or step-down (20-5°/s). It is also known that visuomotor gain during smooth pursuit is regulated by a dynamic gain control mechanism by showing that eye velocity evoked by a target perturbation during pursuit increases bidirectionally when ongoing pursuit velocity is higher. However, it remains uncertain how smooth pursuit adaptation alters the gain of visuomotor transmission. Therefore, a single cycle of sinusoidal motion (2.5 Hz, ± 10°/s) was introduced during step-ramp tracking pre- and post-adaptation to determine whether smooth pursuit adaptation affects the perturbation response. The results showed that pursuit adaptation had a significant effect on the perturbation response that was specific to the adapted direction. These results indicate that there might be different visuomotor mechanisms between adaptation and dynamic gain control. Furthermore, smooth pursuit adaptation altered not only the gain of the perturbation response, but also the gain slope (regression curve) at different target velocities (5, 10 and 15°/s). Therefore, pursuit adaptation could affect the dynamic regulation of the visuomotor gain at different pursuit velocities.

Neural activity in the frontal pursuit area does not underlie pursuit target selection

The frontal pursuit area (FPA) contains neurons that are directionally selective for pursuit eye-movements. We found that FPA neurons discriminate target from distracter too late to account for pursuit directional selection. Rather, the timing of neuronal discrimination is linked to pursuit onset, suggesting a role in motor execution. We also found buildup of activity of FPA neurons prior to pursuit onset that correlated with eye acceleration. These results show that the FPA is unlikely to be involved in selection of initial pursuit direction, but could be involved in motor preparation by increasing pursuit gain prior to pursuit onset.

Trial-by-trial updating of the gain in preparation for smooth pursuit eye movement based on past experience in humans

To understand how the CNS uses past experiences to generate movements that accommodate minute-by-minute environmental changes, we studied the trial-by-trial updating of the gain for initiating smooth pursuit eye movements and how this relates to the history of previous trials. Ocular responses in humans elicited by a small perturbing motion presented 300 ms after appearance of a target were used as a measure of the gain of visuomotor transmission. After the perturbation, the target was either moved horizontally (pursuit trial) or remained in a stationary position (fixation trial). The trial sequence randomly included pursuit and fixation. The amplitude of the response to the perturbation was modulated in a trial-by-trial manner based on the immediately preceding trial, with preceding fixation and pursuit trials decreasing and increasing the gain, respectively. The effect of the previous trial was larger with shorter intertrial intervals, but did not diminish for at least 2,000 ms. A time-series analysis showed that the response amplitude was significantly correlated with the past few trials, with dynamics that could be approximated by a first-order linear system. The results suggest that the CNS integrates recent experiences to set the gain in preparation for upcoming tracking movements in a changing environment.