Oculomotor Pursuit Research Articles

Tuning characteristics of low-frequency EEG to positions and velocities in visuomotor and oculomotor tracking tasks

Movement decoders exploit the tuning of neural activity to various movement parameters with the ultimate goal of controlling end-effector action. Invasive approaches, typically relying on spiking activity, have demonstrated feasibility. Results of recent functional neuroimaging studies suggest that information about movement parameters is even accessible non-invasively in the form of low-frequency brain signals. However, their spatiotemporal tuning characteristics to single movement parameters are still unclear. Here, we extend the current understanding of low-frequency electroencephalography (EEG) tuning to position and velocity signals. We recorded EEG from 15 healthy participants while they performed visuomotor and oculomotor pursuit tracking tasks. Linear decoders, fitted to EEG signals in the frequency range of the tracking movements, predicted positions and velocities with moderate correlations (0.2–0.4; above chance level) in both tasks. Predictive activity in terms of decoder patterns was significant in superior parietal and parieto-occipital areas in both tasks. By contrasting the two tracking tasks, we found that predictive activity in contralateral primary sensorimotor and premotor areas exhibited significantly larger tuning to end-effector velocity when the visuomotor tracking task was performed.

Developmental visual perception deficits with no indications of prosopagnosia in a child with abnormal eye movements

Visual categories are associated with eccentricity biases in high-order visual cortex: Faces and reading with foveally-biased regions, while common objects and space with mid- and peripherally-biased regions. As face perception and reading are among the most challenging human visual skills, and are often regarded as the peak achievements of a distributed neural network supporting common objects perception, it is unclear why objects, which also rely on foveal vision to be processed, are associated with mid-peripheral rather than with a foveal bias.Here, we studied BN, a 9 y.o. boy who has normal basic-level vision, abnormal (limited) oculomotor pursuit and saccades, and shows developmental object and contour integration deficits but with no indication of prosopagnosia. Although we cannot infer causation from the data presented here, we suggest that normal pursuit and saccades could be critical for the development of contour integration and object perception. While faces and perhaps reading, when fixated upon, take up a small portion of central visual field and require only small eye movements to be properly processed, common objects typically prevail in mid-peripheral visual field and rely on longer-distance voluntary eye movements as saccades to be brought to fixation. While retinal information feeds into early visual cortex in an eccentricity orderly manner, we hypothesize that propagation of non-foveal information to mid and high-order visual cortex critically relies on circuitry involving eye movements. Limited or atypical eye movements, as in the case of BN, may hinder normal information flow to mid-eccentricity biased high-order visual cortex, adversely affecting its development and consequently inducing visual perceptual deficits predominantly for categories associated with these regions.

Dynamic causal modelling of eye movements during pursuit: Confirming precision-encoding in V1 using MEG

This paper shows that it is possible to estimate the subjective precision (inverse variance) of Bayesian beliefs during oculomotor pursuit. Subjects viewed a sinusoidal target, with or without random fluctuations in its motion. Eye trajectories and magnetoencephalographic (MEG) data were recorded concurrently. The target was periodically occluded, such that its reappearance caused a visual evoked response field (ERF). Dynamic causal modelling (DCM) was used to fit models of eye trajectories and the ERFs. The DCM for pursuit was based on predictive coding and active inference, and predicts subjects' eye movements based on their (subjective) Bayesian beliefs about target (and eye) motion. The precisions of these hierarchical beliefs can be inferred from behavioural (pursuit) data. The DCM for MEG data used an established biophysical model of neuronal activity that includes parameters for the gain of superficial pyramidal cells, which is thought to encode precision at the neuronal level. Previous studies (using DCM of pursuit data) suggest that noisy target motion increases subjective precision at the sensory level: i.e., subjects attend more to the target's sensory attributes. We compared (noisy motion-induced) changes in the synaptic gain based on the modelling of MEG data to changes in subjective precision estimated using the pursuit data. We demonstrate that imprecise target motion increases the gain of superficial pyramidal cells in V1 (across subjects). Furthermore, increases in sensory precision – inferred by our behavioural DCM – correlate with the increase in gain in V1, across subjects. This is a step towards a fully integrated model of brain computations, cortical responses and behaviour that may provide a useful clinical tool in conditions like schizophrenia.

Active inference and oculomotor pursuit: The dynamic causal modelling of eye movements

This paper introduces a new paradigm that allows one to quantify the Bayesian beliefs evidenced by subjects during oculomotor pursuit. Subjects' eye tracking responses to a partially occluded sinusoidal target were recorded non-invasively and averaged. These response averages were then analysed using dynamic causal modelling (DCM). In DCM, observed responses are modelled using biologically plausible generative or forward models - usually biophysical models of neuronal activity. Our key innovation is to use a generative model based on a normative (Bayes-optimal) model of active inference to model oculomotor pursuit in terms of subjects' beliefs about how visual targets move and how their oculomotor system responds. Our aim here is to establish the face validity of the approach, by manipulating the content and precision of sensory information - and examining the ensuing changes in the subjects' implicit beliefs. These beliefs are inferred from their eye movements using the normative model. We show that on average, subjects respond to an increase in the 'noise' of target motion by increasing sensory precision in their models of the target trajectory. In other words, they attend more to the sensory attributes of a noisier stimulus. Conversely, subjects only change kinetic parameters in their model but not precision, in response to increased target speed. Using this technique one can estimate the precisions of subjects' hierarchical Bayesian beliefs about target motion. We hope to apply this paradigm to subjects with schizophrenia, whose pursuit abnormalities may result from the abnormal encoding of precision.

Two components of oculomotor pursuit isolated by covariance based methods

We assessed covariation in performance between 55 individuals on various psychophysical tasks as well as an oculomotor pursuit task to a ramped stimulus. This analysis isolated two pursuit components of particular interest: 1) an early “latency” component consisting of latency to both presaccadic pursuit and the initial saccade, and 2) a later “accuracy” component consisting of accuracy of eye velocity during the 120ms following the first saccade. The early pursuit component was associated with three dynamic psychophysical tasks: motion detection (“Newsome” paradigm), velocity discrimination, and counterphase flicker identification. However, it was not associated with our two static psychophysical tasks: form detection and orientation discrimination. We propose that this pattern of results may reflect the presence of a high-level, temporal resolution of attention mechanism. It cannot reflect an entirely motion based mechanism because the counterphase flicker identification task does not evoke a motion percept, and moreover its thresholds are quite slow, ranging from 2 to 6 hz. It is unlikely that it reflects a generalized visual or temperamental mechanism because then one would expect the static psychophysical tasks to covary as well with this early stage of pursuit. The later, “accuracy” pursuit component was associated only with psychophysical velocity discrimination. Since this component was not associated with psychophysical motion detection, we propose that it reflects the presence of a mechanism devoted specifically to motion magnitude estimation, distinct from mechanisms devoted to the detection of motion.

Two Distinct Visual Motion Mechanisms for Smooth Pursuit: Evidence from Individual Differences

Smooth-pursuit eye velocity to a moving target is more accurate after an initial catch-up saccade than before, an enhancement that is poorly understood. We present an individual-differences-based method for identifying mechanisms underlying a physiological response and use it to test whether visual motion signals driving pursuit differ pre- and postsaccade. Correlating moment-to-moment measurements of pursuit over time with two psychophysical measures of speed estimation during fixation, we find two independent associations across individuals. Presaccadic pursuit acceleration is predicted by the precision of low-level (motion-energy-based) speed estimation, and postsaccadic pursuit precision is predicted by the precision of high-level (position-tracking) speed estimation. These results provide evidence that a low-level motion signal influences presaccadic acceleration and an independent high-level motion signal influences postsaccadic precision, thus presenting a plausible mechanism for postsaccadic enhancement of pursuit.

Adaptive modification of oculomotor pursuit influences manual tracking responses.

We have addressed the question of whether adaptively modifying the oculomotor response to a visual pursuit stimulus has an influence on a related manual tracking response. Subjects used their unseen right hand to track targets moving at constant velocities while visually fixating a stationary LED. Manual tracking performance was compared before and after a 20 min period during which smooth pursuit eye movements alone were adaptively enhanced by adding 50% of the instantaneous eye position signal to target position. Compared with the preadaptation trials, hand gain was markedly increased during the postadaptation period. These results imply that the adaptation occurred at a level common to both motor systems, probably in CNS structures concerned with visual motion processing.

Co-variability of smooth and saccadic latencies in oculomotor pursuit.

Latencies of smooth pursuit and saccadic eye movement responses to a horizontal ramp target show considerable random variation from trial to trial, which is uncorrelated between the two types of response. This implies that the functional pathways that are responsible for most of the delay in each case are essentially independent.

Cognitive expectations, not habits, control anticipatory smooth oculomotor pursuit

Human smooth pursuit eye movements anticipate the future path of moving targets. Anticipatory pursuit is sometimes attributed to cognitive expectations about future motion and other times to the habitual repetition of previous pursuit responses. Expectations and habits were separated by having subjects smoothly pursue a target moving along a randomly-selected path that was either undisclosed to the subject before each trial or disclosed by means of auditory or visual cues. When the path was undisclosed, the direction of anticipatory smooth eye movements was determined by the direction of target motion in the previous trial. In the presence of cues—the critical condition for separating habits and expectations—effects of previous trials diminished and anticipatory smooth eye movements were primarily determined by the direction of motion the subject was told to expect. These results show a strong contribution of cognitive expectations which overrides persevering smooth oculomotor habits. Smooth pursuit eye movements are driven by a signal that combines the present target motion with the target motion expected to occur several hundred milliseconds into the future. The expected motion is based on a genuine cognitive prediction, not lower-level sensory or motor memories of past events.

Multiple sensory and motor cues enhance the accuracy of pursuit eye movements : J. A. Mather and J. R. Lackner 1980 Aviation, Space and Environmental Medicine51(9), 856–859. (4 pages, 2 tables, 14 references)

Oculomotor pursuit can be elicited by moving visual, tactile, proprioceptive, and occasionally auditory targets presented singly. Both the accuracy and amount of pursuit are enhanced if the position of the target is specified by cues from several sensory modalities. When the motion of the target is topologically related to movements of the subject's arm, the subjects's eyes are more closely phase-locked with the target and reversals of the eyes generally precede target reversal by 10-20 ms.

A comparison of oculomotor pursuit of a target in circular real, beta or sigma motion

Pursuit of a point target in real or apparent motion upon a dark, diffusely lighted or structured background was recorded with a scleral coil technique. Smooth and saccadic components were separated and analyzed with computer techniques. Sigma-pursuit was superior to pursuit of beta- or real motion: smooth pursuit gain was higher, saccadic rate was lower and the detrimental effect of a structured background was smaller. Due to directional errors, smooth pursuit velocity often exceeded target velocity when this was smaller than about 10°/sec. However, the smooth component in the correct direction of the target motion had a gain ⩽ 1.0 and decreasing at higher target velocities for all pursuit modes, inclusive sigma-pursuit.

Adaptation to visual displacement: contribution of proprioceptive, visual, and attentional factors.

A study is reported of the sensory and oculomotor factors that influence adaptation to visual displacement when only sight of the hand and of a target light is permitted. Ten subjects each participated in five counterbalanced sessions in which the relative contributions to adaptation of limb proprioception, oculomotor pursuit, retinal image displacement, and attention were determined. Recordings of eye position were taken throughout the sessions. A discordance between the visual direction of the hand and the proprioceptively specified position of the hand was essential but not sufficient for adaptation to occur. When such a discordance was present adaptation was enhanced by improving position sense of the arm by moving it passively, maximizing accuracy of visual tracking, and focusing attention on the hand. Attentional factors played a smaller part than has been reported for exposure situations involving error feedback about limb position. Eye-movement recordings showed that tracking the passively moved hand visually was vastly superior to tracking a target light undergoing comparable motion.

Oculomotor Pursuit in Schizophrenia

<h3>To the Editor.—</h3> The presence of impaired eye-tracking in schizophrenic patients has been studied by Holzman et al,^1.2Shagass et al,^3.4and Kuechenmeister et al.⁵These studies have also investigated the effects of age, sex, drugs, neuropathy, affective disorders, and perceptual-cognitive tasks on eye-tracking. Although these articles represent important findings, other factors appear to warrant further study. Questions arise as to whether lengthy tracking tasks used by previous studies might produce fatigue or inattention that could affect eye-tracking in schizophrenics. In addition, Young's observation⁶that a velocity range exists in which accurate tracking for humans is optimal would support further study of the effects of target velocity on eye-tracking. A study was conducted to determine whether the reported deficiency in pursuit tracking by schizophrenics was a function of the target velocity and/or the duration of the tracking trial. Twelve male and five female schizophrenic patients participated.

Parietal lobe mechanisms for directed visual attention

1. Experiments were made on the cortex of the inferior parietal lobule in 10 hemispheres of six alert, behaving monkeys. The electrical signs of the impulse discharges of single cortical cells were recorded as the monkeys executed tasks requiring them to fixate stationary visual targets, track those which moved slowly, and to make saccadic movements to foveate those which suddenly jumped from one locus to another within the field of view. A total of 907 neurons of area 7 were identified in terms of their physiological properties, particularly the correlation of their activity with the oculomotor components of these behavioral acts of directed visual attention; 480 of these were located by cytoarchitectural layer. Most identifiable cells of area 7 are visuomotor neurons, in a special and conditional sense. Their discharge frequencies increase before and during those steady fixations and movements of the eyes which secure and maintain foveation of objects, but only if the visual targets engaged are linked by a strong motivational drive; in our experiments, one between thirst and the light whose dimming the animal has learned to detect for liquid reward. We have identified and studied three major classes of neurons in area 7. 2. The visual fixation neurons (57%) accelerate discharge synchronously with fixation of a visual object the animal desires. The incremented discharge continues until reward, but then declines abruptly even when there is no immediate shift of the line of gaze. Fixation neurons are relatively inactive during those casual fixations by which the animal insepcts the surrounding environment. Mist fixation neurons subtend gaze fields limited to one quadrant or half of the total gaze field. The sum of the gaze fields of the fixation neurons in one hemisphere is weighted moderately toward the contralateral side. Fixation cells also discharge during slow pursuit movements in any direction so long as the movement stays within the gaze field of the neuron under study. About 40% of fixation cells are suppressed before and during saccadic movements of the eyes to a new target within the gaze field of the fixation cell. Those suppressed are located preferentially in layer V of the cortex. Suppression is maximal for saccades directed contralaterally to the hemisphere under study. 3. Visual tracking neurons are active during oculomotor pursuit of slowly moving visual objects, not during steady fixations. They show a marked directional but no laterality relation, and are suppressed before and during a visually evoked saccade superimposed on the smooth pursuit movement. The rate of discharge is a flat function of tracking speed so that these cells do not appear to emit signals which specify the speed of smooth pursuit movements. 4. The saccade neurons are active before and during visually evoked saccadic movements of the eyes but not before spontaneous saccades, no matter whether made in light or near darkness. The discharge of saccade neurons leads the eye movement by as much as 150 ms (mean, 73 ms)...

Anticipation, Stability and the Transfer Function of the Human Pursuit System

Investigation into the 'predictive' properties of the human oculomotor pursuit system revealed that most of the anticipatory behaviour can be explained in tarns of an adaptive control system. A generalised 2 parameter describing function model has been derived which showed an excellent agreement with the experimentally obtained frequency response data.

Oculomotor pursuit of vertical sinusoidal targets.

THERE are two principal types of gross eye movements, saccadic (flickering movements) and smooth (continuous compensatory or pursuit movements). Of the two, smooth movements have by far the lower velocity limit. An increasingly popular technique for investigation of the smooth system's performance has been to elicit pursuit of targets moving in sinusoidal motion for a range of test frequencies. One outstanding investigation1 using this method puts the smooth pursuit system's saturation point at some 20°–30°/s (that is appropriate up to only 1.0–1.5 Hz for a peak to peak target amplitude of 8.8°). This contrasts, incidentally, with the saccadic system's known ability2 to exceed 700°/s of appropriate velocity (during flicks between two fixation points).