The representation of time for motor learning

We have identified factors that control precise motor timing by studying learning in smooth pursuit eye movements. Monkeys tracked a target that moved horizontally for a fixed time interval before changing direction through the addition of a vertical component of motion. After repeated presentations of the same target trajectory, infrequent probe trials of purely horizontal target motion evoked a vertical eye movement around the time when the change in target direction would have occurred. The pursuit system timed the vertical eye movement by keeping track of the duration of horizontal target motion and by measuring the distance the target traveled before changing direction, but not by learning the position in space where the target changed direction. We conclude that high temporal precision in motor output relies on multiple signals whose contributions to timing vary according to task requirements.     

Search efficiency but not response interference affects visual selection in frontal eye field

Two manipulations of a visual search task were used to test the hypothesis that the discrimination of a target from distractors by visually responsive neurons in the frontal eye field (FEF) marks the outcome and conclusion of visual processing instead of saccade preparation. First, search efficiency was reduced by increasing the similarity of the distractors to the target. Second, response interference was introduced by infrequently changing the location of the target in the array. Both manipulations increased reaction time, but only the change in search efficiency affected the time needed to select the target by visually responsive neurons. This result indicates that visually responsive neurons in FEF form an explicit representation of the location of the target in the image.     

Attention governs action in the primate frontal eye field

While the motor and attentional roles of the frontal eye field (FEF) are well documented, the relationship between them is unknown. We exploited the known influence of visual motion on the apparent positions of targets, and measured how this illusion affects saccadic eye movements during FEF microstimulation. Without microstimulation, saccades to a moving grating are biased in the direction of motion, consistent with the apparent position illusion. Here we show that microstimulation of spatially aligned FEF representations increases the influence of this illusion on saccades. Rather than simply impose a fixed-vector signal, subthreshold stimulation directed saccades away from the FEF movement field, and instead more strongly in the direction of visual motion. These results demonstrate that the attentional effects of FEF stimulation govern visually guided saccades, and suggest that the two roles of the FEF work together to select both the features of a target and the appropriate movement to foveate it.     

Cortical mechanisms of smooth eye movements revealed by dynamic covariations of neural and behavioral responses

Neural activity in the frontal eye fields controls smooth pursuit eye movements, but the relationship between single neuron responses, cortical population responses, and eye movements is not well understood. We describe an approach to dynamically link trial-to-trial fluctuations in neural responses to parallel variations in pursuit and demonstrate that individual neurons predict eye velocity fluctuations at particular moments during the course of behavior, while the population of neurons collectively tiles the entire duration of the movement. The analysis also reveals the strength of correlations in the eye movement predictions derived from pairs of simultaneously recorded neurons and suggests a simple model of cortical processing. These findings constrain the primate cortical code for movement, suggesting that either a few neurons are sufficient to drive pursuit at any given time or that many neurons operate collectively at each moment with remarkably little variation added to motor command signals downstream from the cortex.     

A neural correlate of oculomotor sequences in supplementary eye field

Complex learned motor sequences can be composed of a combination of a small number of elementary actions. To investigate how the brain represents such sequences, we devised an oculomotor sequence task in which the monkey had to choose the target solely by the sequential context, not by the current stimulus combination. We found that many neurons in the supplementary eye field (SEF) became active with a specific target direction (D neuron) or a specific target/distractor combination (C neuron). Furthermore, such activity was often selective for one among several sequences that included the combination (S neuron). These results suggest that the SEF contributes to the generation of saccades in many learned sequences.     

The neural selection and control of saccades by the frontal eye field

Recent research has provided new insights into the neural processes that select the target for and control the production of a shift of gaze. Being a key node in the network that subserves visual processing and saccade production, the frontal eye field (FEF) has been an effective area in which to monitor these processes. Certain neurons in the FEF signal the location of conspicuous or meaningful stimuli that may be the targets for saccades. Other neurons control whether and when the gaze shifts. The existence of distinct neural processes for visual selection and saccade production is necessary to explain the flexibility of visually guided behaviour.     

Transplantation of Xenopus laevis Tissues to Determine the Ability of Motor Neurons to Acquire a Novel Target

The evolutionary origin of novelties is a central problem in biology. At a cellular level this requires, for example, molecularly resolving how brainstem motor neurons change their innervation target from muscle fibers (branchial motor neurons) to neural crest-derived ganglia (visceral motor neurons) or ear-derived hair cells (inner ear and lateral line efferent neurons). Transplantation of various tissues into the path of motor neuron axons could determine the ability of any motor neuron to innervate a novel target. Several tissues that receive direct, indirect, or no motor innervation were transplanted into the path of different motor neuron populations in Xenopus laevis embryos. Ears, somites, hearts, and lungs were transplanted to the orbit, replacing the eye. Jaw and eye muscle were transplanted to the trunk, replacing a somite. Applications of lipophilic dyes and immunohistochemistry to reveal motor neuron axon terminals were used. The ear, but not somite-derived muscle, heart, or liver, received motor neuron axons via the oculomotor or trochlear nerves. Somite-derived muscle tissue was innervated, likely by the hypoglossal nerve, when replacing the ear. In contrast to our previous report on ear innervation by spinal motor neurons, none of the tissues (eye or jaw muscle) was innervated when transplanted to the trunk. Taken together, these results suggest that there is some plasticity inherent to motor innervation, but not every motor neuron can become an efferent to any target that normally receives motor input. The only tissue among our samples that can be innervated by all motor neurons tested is the ear. We suggest some possible, testable molecular suggestions for this apparent uniqueness.     

A model of visually-guided smooth pursuit eye movements based on behavioral observations

We report a model that reproduces many of the behavioral properties of smooth pursuit eye movements. The model is a negative-feedback system that uses three parallel visual motion pathways to drive pursuit. The three visual pathways process image motion, defined as target motion with respect to the moving eye, and provide signals related to image velocity, image acceleration, and a transient that occurs at the onset of target motion. The three visual motion signals are summed and integrated to produce the eye velocity output of the model. The model reproduces the average eye velocity evoked by steps of target velocity in monkeys and humans and accounts for the variation among individual responses and subjects. When its motor pathways are expanded to include positive feedback of eye velocity and a switch, the model reproduces the exponential decay in eye velocity observed when a moving target stops. Manipulation of this expanded model can mimic the effects of stimulation and lesions in the arcuate pursuit area, the middle temporal visual area (MT), and the medial superior temporal visual area (MST).     

Effect of expected reward magnitude on the response of neurons in the dorsolateral prefrontal cortex of the macaque

The dorsolateral prefrontal cortex plays a critical role in guiding actions that ensue seconds after an instruction. We recorded from neurons in area 46 and the frontal eye field (FEF) while monkeys performed a memory-guided eye movement task. A visual cue signaled whether a small or large liquid reward would accompany a correct response. Many neurons in area 46 responded more when the monkey expected a larger reward. Reward-related enhancement was evident throughout the memory period and was most pronounced when the remembered target appeared in the neuron's response field. Enhancement was not present in the FEF. The mixture of neural signals representing spatial working memory and reward expectation appears to be a distinct feature of area 46.     

Complex predictive eye pursuit in monkey: a model system for cerebellar studies of skilled movement

Smooth pursuit eye movements provide a good model system for cerebellar studies of complex motor control in monkeys. First, the pursuit system exhibits predictive control along complex trajectories and this control improves with training. Second, the flocculus/paraflocculus region of the cerebellum appears to generate this control. Lesions impair pursuit and neural activity patterns are closely related to eye motion during complex pursuit. Importantly, neural responses lead eye motion during predictive pursuit and lag eye motion during non-predictable target motions that require visual control. The idea that flocculus/paraflocculus predictive control is non-visual is also supported by a lack of correlation between neural activity and retinal image motion during pursuit. Third, biologically accurate neural network models of the flocculus/paraflocculus allow the exploration and testing of pursuit mechanisms. Our current model can generate predictive control without visual input in a manner that is compatible with the extensive experimental data available for this cerebellar system. Similar types of non-visual cerebellar control are likely to facilitate the wide range of other skilled movements that are observed.     

Tuning Properties of MT and MSTd and Divisive Interactions for Eye-Movement Compensation

The primate brain intelligently processes visual information from the world as the eyes move constantly. The brain must take into account visual motion induced by eye movements, so that visual information about the outside world can be recovered. Certain neurons in the dorsal part of monkey medial superior temporal area (MSTd) play an important role in integrating information about eye movements and visual motion. When a monkey tracks a moving target with its eyes, these neurons respond to visual motion as well as to smooth pursuit eye movements. Furthermore, the responses of some MSTd neurons to the motion of objects in the world are very similar during pursuit and during fixation, even though the visual information on the retina is altered by the pursuit eye movement. We call these neurons compensatory pursuit neurons. In this study we develop a computational model of MSTd compensatory pursuit neurons based on physiological data from single unit studies. Our model MSTd neurons can simulate the velocity tuning of monkey MSTd neurons. The model MSTd neurons also show the pursuit compensation property. We find that pursuit compensation can be achieved by divisive interaction between signals coding eye movements and signals coding visual motion. The model generates two implications that can be tested in future experiments: (1) compensatory pursuit neurons in MSTd should have the same direction preference for pursuit and retinal visual motion; (2) there should be non-compensatory pursuit neurons that show opposite preferred directions of pursuit and retinal visual motion.     

Segregation of object and background motion in visual area MT: effects of microstimulation on eye movements

To track a moving object, its motion must first be distinguished from that of the background. The center-surround properties of neurons in the middle temporal visual area (MT) may be important for signaling the relative motion between object and background. To test this, we microstimulated within MT and measured the effects on monkeys' eye movements to moving targets. We found that stimulation at "local motion" sites, where receptive fields possessed antagonistic surrounds, shifted pursuit in the preferred direction of the neurons, whereas stimulation at "wide-field motion" sites shifted pursuit in the opposite, or null, direction. We propose that activating wide-field sites simulated background motion, thus inducing a target motion signal in the opposite direction. Our results support the hypothesis that neuronal center-surround mechanisms contribute to the behavioral segregation of objects from the background.     

The fractional-order dynamics of brainstem vestibulo-oculomotor neurons

The vestibulo-ocular reflex (VOR) and other oculomotor subsystems such as pursuit and saccades are ultimately mediated in the brainstem by premotor neurons in the vestibular and prepositus nuclei that relay eye movement commands to extraocular motoneurons. The premotor neurons receive vestibular signals from canal afferents. Canal afferent frequency responses have a component that can be characterized as a fractional-order differentiation (d ^k x/dt _k where k is a nonnegative real number). This article extends the use of fractional calculus to describe the dynamics of motor and premotor neurons. It suggests that the oculomotor integrator, which converts eye velocity into eye position commands, may be of fractional order. This order is less than one, and the velocity commands have order one or greater, so the resulting net output of motor and premotor neurons can be described as fractional differentiation relative to eye position. The fractional derivative dynamics of motor and premotor neurons may serve to compensate fractional integral dynamics of the eye. Fractional differentiation can be used to account for the constant phase shift across frequencies, and the apparent decrease in time constant as VOR and pursuit frequency increases, that are observed for motor and premotor neurons. Fractional integration can reproduce the time course of motor and premotor neuron saccade-related activity, and the complex dynamics of the eye. Insight into the nature of fractional dynamics can be gained through simulations in which fractional-order differentiators and integrators are approximated by sums of integer-order high-pass and low-pass filters, respectively. Fractional dynamics may be applicable not only to the oculomotor system, but to motor control systems in general.     

Motion Control in Saccade and Smooth Pursuit for Bionic Eye Based on Three-dimensional Coordinates

Saccade and smooth pursuit are two important functions of human eye.In order to enable bionic eye to imitate the two functions,a control method that implements saccade and smooth pursuit based on the three-dimensional coordinates of target is proposed.An optimal observation position is defined for bionic eye based on three-dimensional coordinates.A kind of motion planning method with high accuracy is developed.The motion parameters of stepper motor consisting of angle acceleration and turning time are computed according to the position deviation,the target's angular velocity and the stepper motor's current angular velocity in motion planning.The motors are controlled with the motion parameters moving to given position with desired angular velocity in schedule time.The experimental results show that the bionic eye can move to optimal observation positions in 0.6 s from initial location and the accuracy of 3D coordinates is improved.In addition,the bionic eye can track a target within the error of less than 20 pixels based on three-dimensional coordinates.It is verified that saccade and smooth pursuit of bionic eye based on three-dimensional coordinates are feasible.     

Covert tracking: a combined ERP and fixational eye movement study

Attention can be directed to particular spatial locations, or to objects that appear at anticipated points in time. While most work has focused on spatial or temporal attention in isolation, we investigated covert tracking of smoothly moving objects, which requires continuous coordination of both. We tested two propositions about the neural and cognitive basis of this operation: first that covert tracking is a right hemisphere function, and second that pre-motor components of the oculomotor system are responsible for driving covert spatial attention during tracking. We simultaneously recorded event related potentials (ERPs) and eye position while participants covertly tracked dots that moved leftward or rightward at 12 or 20°/s. ERPs were sensitive to the direction of target motion. Topographic development in the leftward motion was a mirror image of the rightward motion, suggesting that both hemispheres contribute equally to covert tracking. Small shifts in eye position were also lateralized according to the direction of target motion, implying covert activation of the oculomotor system. The data addresses two outstanding questions about the nature of visuospatial tracking. First, covert tracking is reliant upon a symmetrical frontoparietal attentional system, rather than being right lateralized. Second, this same system controls both pursuit eye movements and covert tracking.     

Where do i look? From attention to action in the frontal eye field

The frontal eye field (FEF) has been known as a key player in the generation of saccade motor commands and in the allocation of spatial attention. In this issue of Neuron, Schafer and Moore demonstrate that FEF microstimulation enhances the effect of a position illusion induced by visual motion on saccades. This finding suggests that FEF activity can modulate the deployment of spatial attention, which in turn can alter saccade motor commands.     

Optimizing visual motion perception during eye movements.

We usually perceive a stationary, stable world and we are able to correctly estimate the direction of heading from optic flow despite coherent visual motion induced by eye movements. This astonishing example of perceptual invariance results from a comparison of visual information with internal reference signals predicting the visual consequences of an eye movement. Here we demonstrate that the reference signal predicting the consequences of smooth-pursuit eye movements is continuously calibrated on the basis of direction-selective interactions between the pursuit motor command and the rotational flow induced by the eye movement, thereby minimizing imperfections of the reference signal and guaranteeing an ecologically optimal interpretation of visual motion.     

The anatomy and motor nerve distribution of the eye muscles in the crayfish

Summary The gross anatomy of the muscles in the crayfish compound eye and the distribution of brain oculomotor neurons were studied by a variety of anatomical and physiological techniques. There are 11 major muscles in each eye. These vary considerably in size and influence upon eye movements and in their source of motor innervation. Muscles that cause defensive eyestalk withdrawal are controlled by axons of a giant motor neuron cluster. Muscles that move the eyecup in vertical planes are innervated by cells of an anterior motor cluster, as well as by cells in the medulla terminalis. Muscles which move the eyecup horizontally are supplied by neurons of the lateral motor cluster. The separation of the oculomotor system into different neuronal groups that supply different sets of muscles thus reflects functional specializations of the component divisions.I am grateful to Mr. Gene Lorton for his technical assistance with some phases of this work. I also thank Sharon Greene for executing the illustration in Figure 1 and Susan Suarez for illustrating Figure 2. This work was supported by USPHS research grant NS04989.     

Sexually dimorphic neuron number in lumbosacral dorsal root ganglia of the rat: Development and steroid regulation

Rats possess a sexually dimorphic neuromuscular system that controls penile reflexes critical for copulation. This system includes two motor nuclei in the lumbar cord and their target musculature in the perineum. The spinal nucleus of the bulbocavernosus (SNB) and the dorsolateral nucleus (DLN) motoneuron populations and their target perineal muscles are much larger in males than in females. The sex difference in motoneuron number develops via androgen-regulated differential cell death during the perinatal period; androgen also regulates retention of the target muscles. The developmental pattern and steroid sensitivity of peripheral afferents to the SNB/DLN motor nuclei were previously unknown. In order to characterize the peripheral sensory component of the dimorphic SNB/DLN system, the neurons of the relevant dorsal root ganglia (DRGs) were quantified in terms of number, size, and androgen sensitivity at various perinatal ages. DRG neuron number is greatest prenatally, then decreases in both sexes after birth; the timing and pattern of neuron number development are similar to those seen in the SNB and DLN. Postnatally, males have more DRG neurons than females, as a result of greater neuron death in the DRGs of females. Females treated with testosterone propionate during the perinatal period exhibit masculine development of DRG neuron number. Thus, the normal development of DRG neuron number parallels that of the SNB/DLN motor nuclei and target muscles in pattern and timing, is sexually dimorphic, and is regulated by androgen. © 1993 John Wiley & Sons, Inc.