eye movements

Reinforcement effects in anticipatory smooth eye movements

Dynamic modulation of volatility by reward contingencies: effects on anticipatory smooth eye movement

How the dynamics of human smooth pursuit is influenced by speed uncertainty

Voluntary tracking the moving clouds : Effects of speed variability on human smooth pursuit

The properties of motion processing for driving smooth eye movements have bee investigated using simple, artificial stimuli such as gratings, small dots or random dot patterns. Motion processing in the context of complex, natural images is less …

Operant reinforcement versus reward expectancy: effects on anticipatory eye movements

Effects of motion predictability on anticipatory and visually-guided eye movements: a common prior for sensory processing and motor control?

Modeling the effect of dynamic contingencies on anticipatory eye movements

Voluntary tracking the moving clouds : Effects of speed variability on human smooth pursuit

Voluntary tracking the moving clouds : Effects of speed variability on human smooth pursuit

Voluntary tracking the moving clouds : Effects of speed variability on human smooth pursuit

Anticipatory smooth eye movements and reinforcement

When an object is moving in the visual field, we are able to accurately track it with a combination of saccades and smooth eye movements. These movements allow us to align and stabilize the object on the fovea, thus enabling visual analysis with high …

Anticipatory smooth eye movements as operant behavior

Active inference, eye movements and oculomotor delays

This paper considers the problem of sensorimotor delays in the optimal control of (smooth) eye movements under uncertainty. Specifically, we consider delays in the visuo-oculomotor loop and their implications for active inference. Active inference …

The characteristics of microsaccadic eye movements varied with the change of strategy in a match-to-sample task

Under natural viewing conditions, large eye movements are interspace by small eye movements (microsaccade). Recent works have shown that these two kinds of eye movements are generate by the same oculomotor mechanisms (Goffart et al., 2012) and are …

Axonal delays and on-time control of eye movements

Moving objects generate sensory information that may be noisy and ambiguous, yet it is important to be able to reconstruct object speed as fast as possible. One unsolved question is to understand how the brain pools motion information to give an …

On the nature of anticipatory eye movements and the factors affecting them

Measuring speed of moving textures: Different pooling of motion information for human ocular following and perception

The visual system does not process information instantaneously, but rather integrates over time. Integration occurs both for stationary objects and moving objects, with very similar time constants (Burr, 1981). We measured, as a function of exposure …

Smooth Pursuit and Visual Occlusion: Active Inference and Oculomotor Control in Schizophrenia

This paper introduces a model of oculomotor control during the smooth pursuit of occluded visual targets. This model is based upon active inference, in which subjects try to minimise their (proprioceptive) prediction error based upon posterior …

The behavioral receptive field underlying motion integration for primate tracking eye movements

Short-latency ocular following are reflexive, tracking eye movements that are observed in human and non-human primates in response to a sudden and brief translation of the image. Initial, open-loop part of the eye acceleration reflects many of the …

Grabbing, tracking and sniffing as models for motion detection and eye movements

Moving objects generate sensory information that may be noisy and ambiguous, yet it is important to be able to reconstruct object speed as fast as possible. One unsolved question is to understand how the brain pools motion information to give an …

Motion-based prediction is sufficient to solve the aperture problem

In low-level sensory systems, it is still unclear how the noisy information collected locally by neurons may give rise to a coherent global percept. This is well demonstrated for the detection of motion in the aperture problem: as luminance of an …

Effect of image statistics on fixational eye movements

Under natural viewing conditions, small movements of the eyes prevent the maintenance of a steady direction of gaze. It is unclear how the spatiotemporal content of the fixated scene has an impact on the properties of miniatures, fixational eye …

Measuring speed of moving textures: Different pooling of motion information for human ocular following and perception.

To measure speed and direction of moving objects, the cortical motion system pools information across different spatiotemporal channels. One yet unsolved question is to understand how the brain pools this information and whether this pooling is …

More is not always better: dissociation between perception and action explained by adaptive gain control

Moving objects generate motion information at different scales, which are processed in the visual system with a bank of spatiotemporal frequency channels. It is not known how the brain pools this information to reconstruct object speed and whether …

Pattern discrimination for moving random textures: Richer stimuli are more difficult to recognize

In order to analyze the characteristics of a rich dynamic visual environment, the visual system must integrate information collected at different scales through different spatiotemporal frequency channels. Still, it remains unclear how reliable …

Perceptions as Hypotheses: Saccades as Experiments

If perception corresponds to hypothesis testing (Gregory, 1980); then visual searches might be construed as experiments that generate sensory data. In this work, we explore the idea that saccadic eye movements are optimal experiments, in which data …

Pattern discrimination for moving random textures: Richer stimuli are more difficult to recognize

In order to analyze the characteristics of a rich dynamic visual environment, the visual system must integrate information collected at different scales through different spatiotemporal frequency channels. Still, it remains unclear how reliable …

Propriétés émergentes d'un modèle de prédiction probabiliste utilisant un champ neural

Sensory informations such as visual images are inherently variable. We use probabilistic models to describe how the low-level visual system could describe superposed and ambiguous information. This allows to describe the interactions of neighboring …

Saccadic foveation of a moving visual target in the rhesus monkey

When generating a saccade toward a moving target, the target displacement that occurs during the period spanning from its detection to the saccade end must be taken into account to accurately foveate the target and to initiate its pursuit. Previous …

Probabilistic models of the low-level visual system: the role of prediction in detecting motion

Sensory informations such as visual images are inherently variable. We use probabilistic models to describe how the low-level visual system could describe superposed and ambiguous information. This allows to describe the interactions of neighboring …

Role of homeostasis in learning sparse representations

Neurons in the input layer of primary visual cortex in primates develop edge-like receptive fields. One approach to understanding the emergence of this response is to state that neural activity has to efficiently represent sensory data with respect …

Models of low-level vision: linking probabilistic models and neural masses

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Different pooling of motion information for perceptual speed discrimination and behavioral speed estimation

Dynamical emergence of a neural solution for motion integration

Probabilistic models of the low-level visual system: the role of prediction in detecting motion

Sensory informations such as visual images are inherently variable. We use probabilistic models to describe how the low-level visual system could describe superposed and ambiguous information. This allows to describe the interactions of neighboring …

Decoding center-surround interactions in population of neurons for the ocular following response

Short presentation of a large moving pattern elicits an Ocular Following Response (OFR) that exhibits many of the properties attributed to low-level motion processing such as spatial and temporal integration, contrast gain control and divisive …

Dynamics of distributed 1D and 2D motion representations for short-latency ocular following

Integrating information is essential to measure the physical 2D motion of a surface from both ambiguous local 1D motion of its elongated edges and non-ambiguous 2D motion of its features such as corners or texture elements. The dynamics of this …

Decoding the population dynamics underlying ocular following response using a probabilistic framework

The machinery behind the visual perception of motion and the subsequent sensorimotor transformation, such as in Ocular Following Response (OFR), is confronted to uncertainties which are efficiently resolved in the primate's visual system. We may …

Modeling spatial integration in the ocular following response to center-surround stimulation using a probabilistic framework

Dynamical Neural Networks: modeling low-level vision at short latencies

The machinery behind the visual perception of motion and the subsequent sensori-motor transformation, such as in ocular following response (OFR), is confronted to uncertainties which are efficiently resolved in the primate's visual system. We may …

Modeling spatial integration in the ocular following response using a probabilistic framework

The machinery behind the visual perception of motion and the subsequent sensori-motor transformation, such as in Ocular Following Response (OFR), is confronted to uncertainties which are efficiently resolved in the primate's visual system. We may …

Input-output transformation in the visuo-oculomotor loop: modeling the ocular following response to center-surround stimulation in a probabilistic framework

The quality of the representation of an object's motion is limited by the noise in the sensory input as well as by an intrinsic ambiguity due to the spatial limi- tation of the visual motion analyzers (aperture problem). Perceptual and oculomotor …