Extraction of visual motion information for the control of eye and head movement during head-free pursuit

We investigated how effectively briefly presented visual motion could be assimilated and used to track future target motion with head and eyes during target disappearance. Without vision, continuation of eye and head movement is controlled by internal (extra-retinal) mechanisms, but head movement stimulates compensatory vestibulo-ocular reflex (VOR) responses that must be countermanded for gaze to remain in the direction of target motion. We used target exposures of 50–200 ms at the start of randomised step-ramp stimuli, followed by >400 ms of target disappearance, to investigate the ability to sample target velocity and subsequently generate internally controlled responses. Subjects could appropriately grade gaze velocity to different target velocities without visual feedback, but responses were fully developed only when exposure was >100 ms. Gaze velocities were sustained or even increased during target disappearance, especially when there was expectation of target reappearance, but they were always less than for controls, where the target was continuously visible. Gaze velocity remained in the direction of target motion throughout target extinction, implying that compensatory (VOR) responses were suppressed by internal drive mechanisms. Regression analysis revealed that the underlying compensatory response remained active, but with gain slightly less than unity (0.85), resulting in head-free gaze responses that were very similar to, but slightly greater than, head-fixed. The sampled velocity information was also used to grade head velocity, but in contrast to gaze, head velocity was similar whether the target was briefly or continuously presented, suggesting that head motion was controlled by internal mechanisms alone, without direct influence of visual feedback

Incorporating Prediction in Models for Two-Dimensional Smooth Pursuit

A predictive component can contribute to the command signal for smooth pursuit. This is readily demonstrated by the fact that low frequency sinusoidal target motion can be tracked with zero time delay or even with a small lead. The objective of this study was to characterize the predictive contributions to pursuit tracking more precisely by developing analytical models for predictive smooth pursuit. Subjects tracked a small target moving in two dimensions. In the simplest case, the periodic target motion was composed of the sums of two sinusoidal motions (SS), along both the horizontal and the vertical axes. Motions following the same or similar paths, but having a richer spectral composition, were produced by having the target follow the same path but at a constant speed (CS), and by combining the horizontal SS velocity with the vertical CS velocity and vice versa. Several different quantitative models were evaluated. The predictive contribution to the eye tracking command signal could be modeled as a low-pass filtered target acceleration signal with a time delay. This predictive signal, when combined with retinal image velocity at the same time delay, as in classical models for the initiation of pursuit, gave a good fit to the data. The weighting of the predictive acceleration component was different in different experimental conditions, being largest when target motion was simplest, following the SS velocity profiles

Is Acceleration Used for Ocular Pursuit and Spatial Estimation during Prediction Motion?

Here we examined ocular pursuit and spatial estimation in a linear prediction motion task that emphasized extrapolation of occluded accelerative object motion. Results from the ocular response up to occlusion showed that there was evidence in the eye position, velocity and acceleration data that participants were attempting to pursue the moving object in accord with the veridical motion properties. They then attempted to maintain ocular pursuit of the randomly-ordered accelerative object motion during occlusion but this was not ideal, and resulted in undershoot of eye position and velocity at the moment of object reappearance. In spatial estimation there was a general bias, with participants less likely to report object reappearance being behind than ahead of the expected position. In addition, participants’ spatial estimation did not take into account the effects of object acceleration. Logistic regression indicated that spatial estimation was best predicted for the majority of participants by the difference between actual object reappearance position and an extrapolation based on pre-occlusion velocity. In combination, and in light of previous work, we interpret these findings as showing that eye movements are scaled in accord with the effects of object acceleration but do not directly specify information for accurate spatial estimation in prediction motion

Visuomotor Cerebellum in Human and Nonhuman Primates

In this paper, we will review the anatomical components of the visuomotor cerebellum in human and, where possible, in non-human primates and discuss their function in relation to those of extracerebellar visuomotor regions with which they are connected. The floccular lobe, the dorsal paraflocculus, the oculomotor vermis, the uvula–nodulus, and the ansiform lobule are more or less independent components of the visuomotor cerebellum that are involved in different corticocerebellar and/or brain stem olivocerebellar loops. The floccular lobe and the oculomotor vermis share different mossy fiber inputs from the brain stem; the dorsal paraflocculus and the ansiform lobule receive corticopontine mossy fibers from postrolandic visual areas and the frontal eye fields, respectively. Of the visuomotor functions of the cerebellum, the vestibulo-ocular reflex is controlled by the floccular lobe; saccadic eye movements are controlled by the oculomotor vermis and ansiform lobule, while control of smooth pursuit involves all these cerebellar visuomotor regions. Functional imaging studies in humans further emphasize cerebellar involvement in visual reflexive eye movements and are discussed

A New Approach for Determining Phase Response Curves Reveals that Purkinje Cells Can Act as Perfect Integrators

Cerebellar Purkinje cells display complex intrinsic dynamics. They fire spontaneously, exhibit bistability, and via mutual network interactions are involved in the generation of high frequency oscillations and travelling waves of activity. To probe the dynamical properties of Purkinje cells we measured their phase response curves (PRCs). PRCs quantify the change in spike phase caused by a stimulus as a function of its temporal position within the interspike interval, and are widely used to predict neuronal responses to more complex stimulus patterns. Significant variability in the interspike interval during spontaneous firing can lead to PRCs with a low signal-to-noise ratio, requiring averaging over thousands of trials. We show using electrophysiological experiments and simulations that the PRC calculated in the traditional way by sampling the interspike interval with brief current pulses is biased. We introduce a corrected approach for calculating PRCs which eliminates this bias. Using our new approach, we show that Purkinje cell PRCs change qualitatively depending on the firing frequency of the cell. At high firing rates, Purkinje cells exhibit single-peaked, or monophasic PRCs. Surprisingly, at low firing rates, Purkinje cell PRCs are largely independent of phase, resembling PRCs of ideal non-leaky integrate-and-fire neurons. These results indicate that Purkinje cells can act as perfect integrators at low firing rates, and that the integration mode of Purkinje cells depends on their firing rate

EMDR Effects on Pursuit Eye Movements

This study aimed to objectivize the quality of smooth pursuit eye movements in a standard laboratory task before and after an Eye Movement Desensitization and Reprocessing (EMDR) session run on seven healthy volunteers. EMDR was applied on autobiographic worries causing moderate distress. The EMDR session was complete in 5 out of the 7 cases; distress measured by SUDS (Subjective Units of Discomfort Scale) decreased to a near zero value. Smooth pursuit eye movements were recorded by an Eyelink II video system before and after EMDR. For the five complete sessions, pursuit eye movement improved after their EMDR session. Notably, the number of saccade intrusions—catch-up saccades (CUS)—decreased and, reciprocally, there was an increase in the smooth components of the pursuit. Such an increase in the smoothness of the pursuit presumably reflects an improvement in the use of visual attention needed to follow the target accurately. Perhaps EMDR reduces distress thereby activating a cholinergic effect known to improve ocular pursuit

Einheit von Park und Architektur : der Park am IG Hochhaus

Cerebellar granule cells, which constitute half the brain's neurons, supply Purkinje cells with contextual information necessary for motor learning, but how they encode this information is unknown. Here we show, using two-photon microscopy to track neural activity over multiple days of cerebellum-dependent eyeblink conditioning in mice, that granule cell populations acquire a dense representation of the anticipatory eyelid movement. Initially, granule cells responded to neutral visual and somatosensory stimuli as well as periorbital airpuffs used for training. As learning progressed, two-thirds of monitored granule cells acquired a conditional response whose timing matched or preceded the learned eyelid movements. Granule cell activity covaried trial by trial to form a redundant code. Many granule cells were also active during movements of nearby body structures. Thus, a predictive signal about the upcoming movement is widely available at the input stage of the cerebellar cortex, a

Relating Neuronal to Behavioral Performance: Variability of Optomotor Responses in the Blowfly

Behavioral responses of an animal vary even when they are elicited by the same stimulus. This variability is due to stochastic processes within the nervous system and to the changing internal states of the animal. To what extent does the variability of neuronal responses account for the overall variability at the behavioral level? To address this question we evaluate the neuronal variability at the output stage of the blowfly's (Calliphora vicina) visual system by recording from motion-sensitive interneurons mediating head optomotor responses. By means of a simple modelling approach representing the sensory-motor transformation, we predict head movements on the basis of the recorded responses of motion-sensitive neurons and compare the variability of the predicted head movements with that of the observed ones. Large gain changes of optomotor head movements have previously been shown to go along with changes in the animals' activity state. Our modelling approach substantiates that these gain changes are imposed downstream of the motion-sensitive neurons of the visual system. Moreover, since predicted head movements are clearly more reliable than those actually observed, we conclude that substantial variability is introduced downstream of the visual system

A theory of how active behavior stabilises neural activity: neural gain modulation by closed-loop environmental feedback

During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity) coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results demonstrate the dependence of neural fluctuations, across the brain, on closed-loop brain/body/environment interactions strongly supporting the idea that brain function cannot be fully understood through open-loop approaches alone