Motion Detection

An open-source vision-science tool for the auto-regressive generation of dynamic stochastic textures Motion Clouds
Motion Clouds are a generative model for naturalistic visual stimulation that offer full parametric control and more naturalism than …
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Speed-Selectivity in Retinal Ganglion Cells is Sharpened by Broad Spatial Frequency, Naturalistic Stimuli
Motion detection represents one of the critical tasks of the visual system and has motivated a large body of research. However, it …
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Speed-Selectivity in Retinal Ganglion Cells is Sharpened by Broad Spatial Frequency, Naturalistic Stimuli
Bayesian Modeling of Motion Perception using Dynamical Stochastic Textures
A common practice to account for psychophysical biases in vision is to frame them as consequences of a dynamic process relying on …
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Bayesian Modeling of Motion Perception using Dynamical Stochastic Textures
Speed uncertainty and motion perception with naturalistic random textures
It is still not fully understood how visual system integrates motion energy across different spatial and temporal frequencies to build …
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Estimating and anticipating a dynamic probabilistic bias in visual motion direction
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How the dynamics of human smooth pursuit is influenced by speed uncertainty
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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 …
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Voluntary tracking the moving clouds : Effects of speed variability on human smooth pursuit
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Voluntary tracking the moving clouds : Effects of speed variability on human smooth pursuit
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Voluntary tracking the moving clouds : Effects of speed variability on human smooth pursuit
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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. …
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Active inference, eye movements and oculomotor delays
Motion-based prediction model for flash lag effect
The flash lag effect (FLE) is a well known visual illusion that reveals the perceptual difference in position coding of moving and …
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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 …
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Signature of an anticipatory response in area V1 as modeled by a probabilistic model and a spiking neural network
As it is confronted to inherent neural delays, how does the visual system create a coherent representation of a rapidly changing …
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Signature of an anticipatory response in area V1 as modeled by a probabilistic model and a spiking neural network
2014-04-25
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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 …
2014-01-10
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Motion-based prediction explains the role of tracking in motion extrapolation
During normal viewing, the continuous stream of visual input is regularly interrupted, for instance by blinks of the eye. Despite these …
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Anisotropic connectivity implements motion-based prediction in a spiking neural network
Predictive coding hypothesizes that the brain explicitly infers upcoming sensory input to establish a coherent representation of the …
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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 …
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Motion-based prediction and development of the response to an 'on the way' stimulus
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 …
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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 …
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Pattern discrimination for moving random textures: Richer stimuli are more difficult to recognize
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 …
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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 …
2012-01-27
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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 …
2012-01-12
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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 …
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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 …
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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 …
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More is not always better: dissociation between perception and action explained by adaptive gain control
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 …
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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 …
2011-07-02
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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 …
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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 …
2010-12-17
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Models of low-level vision: linking probabilistic models and neural masses
2010-01-08
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Different pooling of motion information for perceptual speed discrimination and behavioral speed estimation
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Dynamical emergence of a neural solution for motion integration
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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 …
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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 …
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Inferring monkey ocular following responses from V1 population dynamics using a probabilistic model of motion integration
Short presentation of a large moving pattern elicits an ocular following response that exhibits many of the properties attributed to …
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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 …
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Dynamics of distributed 1D and 2D motion representations for short-latency ocular following
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 …
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Decoding the population dynamics underlying ocular following response using a probabilistic framework
Modeling spatial integration in the ocular following response to center-surround stimulation using a probabilistic framework
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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 …
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Dynamic inference for motion tracking
When the visual information about an object’s motion differs at the local level, the visuomotor system needs to integrate …
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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 …
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Modeling spatial integration in the ocular following response using a probabilistic framework
Input-output transformation in the visuo-oculomotor loop: modeling the ocular following response to center-surround stimulation in a probabilistic framework
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Input-output transformation in the visuo-oculomotor loop: modeling the ocular following response to center-surround stimulation in a probabilistic framework
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 …
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Dynamics of motion representation in short-latency ocular following: A two-pathways Bayesian model
The integration of information is essential to measure the exact 2D motion of a surface from both local ambiguous 1D motion produced by …
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